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Eur J Radiol 83:226–230\nAndersen FL, Klausen TL, Loft A, Beyer T, Holm S (2013) Clinical evaluation of PET image reconstruction using a spatial resolution model. Eur J Radiol 82:862–869\nBarrington SF, Mikhaeel NG, Kostakoglu L, Meignan M, Hutchings M, Müeller SP et al (2014) Role of imaging in the staging and response assessment of lymphoma: consensus of the International Conference on malignant lymphomas imaging working group. J Clin Oncol 32:3048–3058\nBarrington SF, Qian W, Somer EJ, Franceschetto A, Bagni B, Brun E et al (2010) Concordance between four European centres of PET reporting criteria designed for use in multicentre trials in Hodgkin lymphoma. Eur J Nucl Med Mol Imaging 37:1824–1833\nBiggi A, Gallamini A, Chauvie S, Hutchings M, Kostakoglu L, Gregianin M et al (2013) International validation study for interim PET in ABVD-treated, advanced-stage Hodgkin lymphoma: interpretation criteria and concordance rate among reviewers. J Nucl Med 54:683–690\nBoellaard R, Delgado-Bolton R, Oyen WJG, Giammarile F, Tatsch K, Eschner W et al (2015) FDG PET\u002FCT: EANM procedure guidelines for tumour imaging: version 2.0. Eur J Nucl Med Mol Imaging 42:328–354\nBoellard R, Willemsen AT, Arends B, Visser EP. EARL procedure for assessing PET\u002FCT system specific patient FDG activity preparations for quantitative FDG PET\u002FCT studies. 2013.\nBray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A (2018) Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 68:394–424\nChen KT, Gong E, de Carvalho Macruz FB, Xu J, Boumis A, Khalighi M et al (2019) Ultra–low-dose 18 F-florbetaben amyloid PET imaging using deep learning with multi-contrast MRI inputs. Radiology 290:649–656\nCheson BD, Fisher RI, Barrington SF, Cavalli F, Schwartz LH, Zucca E et al (2014) Recommendations for initial evaluation, staging, and response assessment of Hodgkin and non-Hodgkin lymphoma: the Lugano classification. J Clin Oncol 32:3059–3067\nConti M, Bendriem B (2019) The new opportunities for high time resolution clinical TOF PET. Clin Transl Imaging. 7:139–147\nGallamini A, Hutchings M, Rigacci L, Specht L, Merli F, Hansen M et al (2007) Early interim 2-[ 18 F]fluoro-2-deoxy-D-glucose positron emission tomography is prognostically superior to international prognostic score in advanced-stage Hodgkin’s lymphoma: a report from a joint Italian-Danish study. J Clin Oncol 25:3746–3752\nHuang B, Law MW-M, Khong P-L (2009) Whole-body PET\u002FCT scanning: estimation of radiation dose and cancer risk. Radiology 251:166–174\nItti E, Meignan M, Berriolo-Riedinger A, Biggi A, Cashen AF, Véra P et al (2013) An international confirmatory study of the prognostic value of early PET\u002FCT in diffuse large B-cell lymphoma: comparison between Deauville criteria and ΔSUVmax. Eur J Nucl Med Mol Imaging 40:1312–1320\nKuhnert G, Boellaard R, Sterzer S, Kahraman D, Scheffler M, Wolf J et al (2016) Impact of PET\u002FCT image reconstruction methods and liver uptake normalization strategies on quantitative image analysis. Eur J Nucl Med Mol Imaging 43:249–258\nLy J, Minarik D, Edenbrandt L, Wollmer P, Trägårdh E (2019) The use of a proposed updated EARL harmonization of 18F-FDG PET-CT in patients with lymphoma yields significant differences in Deauville score compared with current EARL recommendations. EJNMMI Res 9\nMeignan M, Gallamini A, Meignan M, Gallamini A, Haioun C (2009) Report on the first international workshop on interim-PET scan in lymphoma. Leuk Lymphoma. 50:1257–1260\nMikhaeel NG, Hutchings M, Fields PA, O’Doherty MJ, Timothy AR (2005) FDG-PET after two to three cycles of chemotherapy predicts progression-free and overall survival in high-grade non-Hodgkin lymphoma. Ann Oncol 16:1514–1523\nMunk OL, Tolbod LP, Hansen SB, Bogsrud TV (2017) Point-spread function reconstructed PET images of sub-centimeter lesions are not quantitative. EJNMMI Phys 4:5\nSmith A, Crouch S, Lax S, Li J, Painter D, Howell D et al (2015) Lymphoma incidence, survival and prevalence 2004–2014: sub-type analyses from the UK’s Haematological Malignancy Research Network. Br J Cancer 112:1575–1584\nSonni I, Baratto L, Park S, Hatami N, Srinivas S, Davidzon G et al (2018) Initial experience with a SiPM-based PET\u002FCT scanner: influence of acquisition time on image quality. EJNMMI Phys 5\nvan der Vos CS, Koopman D, Rijnsdorp S, Arends AJ, Boellaard R, van Dalen JA et al (2017) Quantification, improvement, and harmonization of small lesion detection with state-of-the-art PET. Eur J Nucl Med Mol Imaging 44:4–16\nvan Sluis J, Boellaard R, Dierckx RA, Stormezand G, Glaudemans AWJM, Noordzij W (2019) Image quality and activity optimization in oncological 18 F-FDG PET using the digital Biograph Vision PET\u002FCT. J Nucl Med jnumed. (7):1031–1036\nWeiler-Sagie M, Bushelev O, Epelbaum R, Dann EJ, Haim N, Avivi I et al (2010) 18F-FDG avidity in lymphoma readdressed: a study of 766 patients. J Nucl Med 51:25–30",{"EN":147},"[18F]Fluoro-deoxy-glucose positron emission tomography\u002Fcomputed tomography (FDG-PET\u002FCT) is used for response assessment during therapy in Hodgkin lymphoma (HL) and non-Hodgkin lymphoma (NHL). Clinicians report the scans visually using Deauville criteria. Improved performance in modern PET\u002FCT scanners could allow for a reduction in scan time without compromising diagnostic image quality. Additionally, patient throughput can be increased with increasing cost-effectiveness. We investigated the effects of reducing scan time of response assessment FDG-PET\u002FCT in HL and NHL patients on Deauville score (DS) and image quality. Twenty patients diagnosed with HL\u002FNHL referred to a response assessment FDG-PET\u002FCT were included. PET scans were performed in list-mode with an acquisition time of 120 s per bed position(s\u002Fbp). From PET list-mode data images with full acquisition time of 120 s\u002Fbp and shorter acquisition times (90, 60, 45, and 30 s\u002Fbp) were reconstructed. All images were assessed by two specialists and assigned a DS. We estimated the possible savings when reducing scan time using a simplified model based on assumed values\u002Fcosts for our hospital. There were no significant changes in the visually assessed DS when reducing scan time to 90 s\u002Fbp, 60 s\u002Fbp, 45 s\u002Fbp, and 30 s\u002Fbp. Image quality of 90 s\u002Fbp images were rated equal to 120 s\u002Fbp images. Coefficient of variance values for 120 s\u002Fbp and 90 s\u002Fbp images was significantly \u003C 15%. The estimated annual savings to the hospital when reducing scan time was 8000-16,000 €\u002Fscanner. Acquisition time can be reduced to 90 s\u002Fbp in response assessment FDG-PET\u002FCT without compromising Deauville score or image quality. Reducing acquisition time can reduce costs to the clinic.",{"EN":149},"The effect of reduced scan time on response assessment FDG-PET\u002FCT imaging using Deauville score in patients with lymphoma",{"VOID":151},"10.1186\u002Fs41824-021-00096-0","PUBLICATION","VERIFIED","Auto Verify","https:\u002F\u002Fejhi.springeropen.com\u002Farticles\u002F10.1186\u002Fs41824-021-00096-0",[157,173,186,199],{"id":158,"sortIndex":21,"researcher":20,"roles":159,"affiliations":161,"properties":170},"c19618db-0591-4c3f-ba94-5f7620e46988",[160],"AUTHOR",[162],{"id":20,"sortIndex":21,"affiliation":163,"properties":20},{"id":164,"createTime":165,"updateTime":165,"relativeEntities":166,"slug":20,"properties":167,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"48a22f38-a95a-46df-ac38-307032b2c6ee","2023-12-08T21:01:01.860+00:00",[],{"title":168},{"VI":169},"Department of Clinical Physiology, Nuclear Medicine and PET, 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K, Weaver J, Ul-Hassan F, Jeannon JP, Simo R, Carroll P, et al. Incidence and significance of incidental focal thyroid uptake on (18)F-FDG PET study in a large patient cohort: retrospective single-Centre experience in the United Kingdom. Eur Thyroid J 2015; 4:115-122. doi: https:\u002F\u002Fdoi.org\u002Fhttps:\u002F\u002Fdoi.org\u002F10.1159\u002F000431319\nAre C, Hsu JF, Schoder H, Shah JP, Larson SM et al (2007) FDG-PET detected thyroid incidentalomas: need for further investigation? Ann Surg Oncol 14:239–247\nBae JS, Chae BJ, Park WC, Kim JS, Kim SH et al (2009) Incidental thyroid lesions detected by FDG-PET\u002FCT: prevalence and risk of thyroid cancer. World J Surg Oncol 7:63\nBrindle R, Mullan D, Yap BK, Gandhi A et al (2014) Thyroid incidentalomas discovered on positron emission tomography CT scanning - malignancy rate and significance of standardised uptake values. Eur J Surg Oncol 40(11):1528–1532. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ejso.2014.05.005 Epub 2014 May 24\nChen W, Parsons M, Torigian DA, Zhuang H, Alavi A (2009) Evaluation of thyroid FDG uptake incidentally identified on FDG-PET\u002FCT imaging. Nuclear Med Commun 30(3):240–244\nChen YK, Ding HJ, Chen KT, Chen YL, Liao AC et al (2005) Prevalence and risk of cancer of focal thyroid incidentaloma identified by 18F-fluorodeoxyglucose positron emission tomography for cancer screening in healthy subjects. Anticancer Res 25:1421–1426\nChu QD, Connor MS, Lilien DL, Johnson LW, Turnage RH et al (2006) Positron emission tomography (PET) positive thyroid incidentaloma: the risk of malignancy observed in a tertiary referral center. Am Surg 72(3):272–275\nChu Y, Zheng A, Wang F, Lin W, Yang X, Han L et al (2014) Diagnostic value of 18F-FDG-PET or PET-CT in recurrent cervical cancer: a systematic review and meta-analysis. Nuclear Med Commun 35:144–150\nCohen MS, Arslan N, Dehdashti F, Doherty GM, Lairmore TC et al (2001) Risk of malignancy in thyroid incidentalomas identified by fluorodeoxyglucose-positron emission tomography. Surgery 130:941–946\nDelivanis DA, Castro MR (2018) Thyroid nodules. Humana press; Cham, Switzerland: 2017. Thyroid Incidentalomas; pp. 153–167.\nEloy JA, Brett EM, Fatterpekar GM, Kostakoglu L, Som PM, Desai SC, Genden EM (2009) The significance and management of incidental [18F]fluorodeoxyglucose–positron-emission tomography uptake in the thyroid gland in patients with cancer. Am J Neuroradiol 30(7):1431–1434. https:\u002F\u002Fdoi.org\u002F10.3174\u002Fajnr.A1559\nHaugen BR, Alexander EK, Bible KC, Doherty GM, Mandel SJ, Nikiforov YE et al (2016) 2015 American Thyroid Association management guidelines for adult patients with thyroid nodules and differentiated thyroid cancer: the American Thyroid Association guidelines task force on thyroid nodules and differentiated thyroid cancer. Thyroid 26:1–133. https:\u002F\u002Fdoi.org\u002F. https:\u002F\u002Fdoi.org\u002F10.1089\u002Fthy.2015.0020\nHo TY, Liou MJ, Lin KJ, Yen TC (2011) Prevalence and significance of thyroid uptake detected by 18F-FDG PET. Endocrine. 40(2):297–302\nHoang JK, Langer JE, Middleton WD, Wu CC, Hammers LW, Cronan JJ, et al. Managing incidental thyroid nodules detected on imaging: white paper of the ACR incidental thyroid findings committee. J Am Coll Radiol 2015; 12: 143–150. doi: https:\u002F\u002Fdoi. org\u002Fhttps:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jacr.2014.09.038\nKang KW, Kim SK, Kang HS, Lee ES, Sim JS et al (2003) Prevalence and risk of cancer of focal thyroid incidentaloma identified by 18F-fluorodeoxyglucose positron emission tomography for metastasis evaluation and cancer screening in healthy subjects. J Clin Endocrinol Metabol 88:4100–4104\nKao YH, Lim SS, Ong SC, Padhy AK (2012) Thyroid incidentalomas on fluorine-18-fluorodeoxyglucose positron emission tomography-computed tomography: incidence, malignancy risk, and comparison of standardized uptake values. Cancer Assoc Radiol J 63:289–293\nKim TY, Kim WB, Ryu JS, Gong G, Hong SJ et al (2005) 18F-fluorodeoxyglucose uptake in thyroid from positron emission tomogram (PET) for evaluation in cancer patients: high prevalence of malignancy in thyroid PET incidentaloma. Laryngoscope 115:1074–1078\nKumar V, Nath K, Berman CG, Kim J, Tanvetyanon T et al (2013) Variance of SUVs for FDG-PET\u002FCT is greater in clinical practice than under ideal study settings. Clin Nucl Med 38(3):175–182\nPencharz D, Nathan M, Wagner TL (2018) Evidence-based management of incidental focal uptake of fluorodeoxyglucose on PET-CT. Br J Radiol 91:20170774\nSoelberg KK, Bonnema SJ, Brix TH, Hegedüs L (2012) Risk of malignancy in thyroid incidentalomas detected by 18F-fluorodeoxyglucose positron emission tomography: a systematic review. Thyroid 22:918–925. https:\u002F\u002Fdoi.org\u002F10.1089\u002Fthy.2012.0005\nStangierski A, Woliński K, Czepczyński R, Czarnywojtek A, Lodyga M, Wyszomirska A, et al. The usefulness of standardized uptake value in differentiation between benign and malignant thyroid lesions detected incidentally in 18F-FDG PET\u002FCT examination. PLoS One 2014; 9: e109612. doi: https:\u002F\u002Fdoi.org\u002Fhttps:\u002F\u002Fdoi.org\u002F10.1371\u002Fjournal.pone.0109612\nThe Royal College of radiologists (2012) iRefer: making the best use of clinical radiology, 7th edn. The royal college of Radiologists, London\nVassiliadi D.A., Tsagarakis S. Endocrine incidentalomas—challenges imposed by incidentally discovered lesions. National review of endocrinology, 2011; June 28th; 7:668–680. Doi: https:\u002F\u002Fdoi.org\u002F10.1038\u002Fnrendo.2011.92\nYi JG, Marom EM, Munden RF, Truong MT, Macapinlac HA et al (2005) Focal uptake of fluorodeoxyglucose by the thyroid in patients undergoing initial disease staging with combined PET\u002FCT for non–small cell lung cancer. Radiology 236:271–275",{"VI":260,"EN":261},"Để định lượng tình trạng bệnh lý tuyến giáp tình cờ, bao gồm cả ung thư, trên các hình ảnh PET-CT 18F-FDG định kỳ và so sánh các giá trị hấp thu tiêu chuẩn hóa (SUVmax) trong các phân loại ung thư tuyến giáp. Đây là một nghiên cứu hồi cứu về tất cả các hình ảnh PET-CT 18F-FDG (n = 6179) được thực hiện tại một bệnh viện giảng dạy từ tháng 6 năm 2010 đến tháng 5 năm 2019. Một tìm kiếm trong cơ sở dữ liệu RIS về các báo cáo có chứa từ “tuyến giáp” đã được thực hiện. Các nghiên cứu có bằng chứng hấp thu tuyến giáp đã được đưa vào. Độ tuổi và giới tính của bệnh nhân, chỉ định chính cho quét PET (ung thư hoặc không phải ung thư), kết quả tuyến giáp trên PET (hấp thu đồng vị phóng xạ khuếch tán hoặc vùng), kết quả siêu âm và FNAC được ghi lại. Tỷ lệ hấp thu đồng vị phóng xạ tuyến giáp bất thường tình cờ trong tổng số các hình ảnh PET-CT 18F-FDG là 4,37% (n = 270). Những bệnh nhân ngoài khu vực (n = 87) mà hồ sơ không thể thu thập đã bị loại trừ, để lại nhóm nghiên cứu n = 183. Chín mươi bốn bệnh nhân trong nhóm này có hấp thu khu trú, và 89 có hấp thu khuếch tán. Năm mươi lăm bệnh nhân trong nhóm khu trú đã thực hiện các xét nghiệm bổ sung. Trong số này, 30 bệnh nhân được cho là lành tính chỉ dựa trên siêu âm, và 25 bệnh nhân đã được tiến hành siêu âm\u002FFNAC. Mười ba (24%) ung thư đã được xác định (5 ung thư biểu mô nhú, 6 ung thư biểu mô nang, 1 ung thư tuyến giáp phân loại kém, 1 ung thư di căn). Giá trị trung bình SUVmax cho ung thư biểu mô nhú được ghi nhận là 8,2 g\u002Fml, và ung thư biểu mô nang là 12,6 g\u002Fml. Tỷ lệ hấp thu đồng vị phóng xạ tuyến giáp bất thường trên PET-CT 18F-FDG trong các hình ảnh PET-CT là 4,37% phù hợp với tài liệu hạn chế được biết đến. Một số lượng bệnh nhân tương tự được ghi nhận trong các phân loại hấp thu đồng vị phóng xạ khu trú và khuếch tán trong nhóm nghiên cứu cuối cùng. Khoảng một phần tư của các tổn thương khu trú được xác định có tính chất ác tính, điều đó có nghĩa là các tổn thương khu trú nên luôn được điều tra thêm.","To quantify incidental thyroid pathology including malignancy on routine 18F-FDG PET-CT scans To compare standardised uptake values (SUVmax) in thyroid malignancy subtypes This is a retrospective study of all 18F-FDG PET-CT scans (n = 6179) performed in a teaching hospital between June 2010 and May 2019. RIS database search of reports for the word “thyroid” was performed. Studies with evidence of thyroid uptake were included. Patient age and gender, primary indication for PET scan (malignant or non-malignant), thyroid result on PET (diffuse or focal tracer uptake, SUVmax), ultrasound and FNAC results were recorded. Incidental abnormal thyroid tracer uptake as a proportion of all 18F-FDG PET-CT scans was 4.37% (n = 270). Out of region patients (n = 87) whose records could not be obtained were excluded leaving a study group of n = 183. Ninety-four in this group had focal uptake, and 89 had diffuse uptake. Fifty-five patients in the focal group had undergone further investigations. Of these, 30 were thought to be benign on USS alone, and 25 patients underwent USS\u002FFNAC. Thirteen (24%) malignancies were identified (5 papillary, 6 follicular, 1 poorly differentiated thyroid cancer, 1 metastatic malignancy). Mean SUVmax for papillary carcinoma was noted to be 8.2 g\u002Fml, and follicular carcinoma was 12.6 g\u002Fml. Incidental abnormal thyroid 18F-FDG PET-CT uptake in PET-CT scans of 4.37% is in keeping with the known limited literature. Rather similar number of patients was noted in the focal and diffuse tracer uptake categories in the final study group. Around quarter of the focal lesions were identified to be malignant, implying focal lesions should always be further investigated.",{"VI":263,"EN":264},"Tỷ lệ ung thư tuyến giáp tình cờ trên PET-CT 18F-fluorodeoxyglucose định kỳ tại một bệnh viện đào tạo lớn","Prevalence of incidental thyroid malignancy on routine 18F-fluorodeoxyglucose PET-CT in a large teaching hospital",{"VOID":266},"10.1186\u002Fs41824-020-00089-5",{"VI":268},"","2025-01-23T04:51:20.007+00:00",[271],"VI","https:\u002F\u002Fejhi.springeropen.com\u002Farticles\u002F10.1186\u002Fs41824-020-00089-5",[274,289,312,324,336,348],{"id":275,"sortIndex":188,"researcher":20,"roles":276,"affiliations":277,"properties":286},"1e85df69-bc79-4f4e-8f09-aa7697f342d0",[160],[278],{"id":20,"sortIndex":21,"affiliation":279,"properties":20},{"id":280,"createTime":281,"updateTime":281,"relativeEntities":282,"slug":20,"properties":283,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"b0937eb8-cef0-43dd-ab15-5821af8cf14f","2024-01-13T06:26:07.019+00:00",[],{"title":284},{"VI":285},"Department of Nuclear Medicine, Ninewells Hospital, Dundee, Scotland, UK",{"title":287},{"VI":288},"Thomas Biggans",{"id":290,"sortIndex":291,"researcher":20,"roles":292,"affiliations":293,"properties":309},"a2ec09c9-8f71-44d7-8bba-9a1bf6afc7a5",4,[160],[294,301],{"id":295,"sortIndex":188,"affiliation":296,"properties":300},"9ea3675f-22a1-46c2-a7f2-bfb7a6f2f66b",{"id":280,"createTime":281,"updateTime":281,"relativeEntities":297,"slug":20,"properties":298,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":299},{"VI":285},{},{"id":20,"sortIndex":21,"affiliation":302,"properties":20},{"id":303,"createTime":304,"updateTime":304,"relativeEntities":305,"slug":20,"properties":306,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"0f0060c2-b8c2-4b05-b62c-475b0ced473a","2024-01-13T06:26:07.015+00:00",[],{"title":307},{"VI":308},"Department of Radiology, Ninewells Hospital, Dundee, Scotland, UK",{"title":310},{"VI":311},"Thiru Sudarshan",{"id":313,"sortIndex":175,"researcher":20,"roles":314,"affiliations":315,"properties":321},"76920b47-f5ce-434d-a199-d02310b1262c",[160],[316],{"id":20,"sortIndex":21,"affiliation":317,"properties":20},{"id":303,"createTime":304,"updateTime":304,"relativeEntities":318,"slug":20,"properties":319,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":320},{"VI":308},{"title":322},{"VI":323},"Avinash Kanodia",{"id":325,"sortIndex":21,"researcher":20,"roles":326,"affiliations":327,"properties":333},"1ecc6f63-8a85-4374-a0db-66bf55d8639b",[160],[328],{"id":20,"sortIndex":21,"affiliation":329,"properties":20},{"id":303,"createTime":304,"updateTime":304,"relativeEntities":330,"slug":20,"properties":331,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":332},{"VI":308},{"title":334},{"VI":335},"Shea Roddy",{"id":337,"sortIndex":201,"researcher":20,"roles":338,"affiliations":339,"properties":345},"15475a39-9a84-4525-b52d-bb46b2b07667",[160],[340],{"id":20,"sortIndex":21,"affiliation":341,"properties":20},{"id":303,"createTime":304,"updateTime":304,"relativeEntities":342,"slug":20,"properties":343,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":344},{"VI":308},{"title":346},{"VI":347},"Ahmad K. 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J Thromb Haemost 4:1928–1930\nLiss MA, Stroup SP, Cand ZQ, Hoh C, Hall DJ, Vera DR et al (2014) Robotic-assisted fluorescence sentinel lymph node mapping using multi-nodal image-guidance in an animal model. Urology. 84:982\nLo J, Lu MT, Ihenachor EJ, Wei J, Looby SE, Fitch KV et al (2015) Effects of statin therapy on coronary artery plaque volume and high risk plaque morphology in HIV-infected patients with subclinical atherosclerosis: a randomized double-blind placebo-controlled trial. Lancet HIV 2:e52–e63\nLuehmann HP, Pressly ED, Detering L, Wang C, Pierce R, Woodard PK et al (2014) PET\u002FCT imaging of chemokine receptor CCR% in vascular injury model using targeted nanoparticles. J Nucl Med 55:629–634\nMajluf-Cruz A, Silva-Estrada M, Sánchez-Barboza R, Montiel-Manzano G, Treviño-Pérez S, Santoscoy-Gómez M et al (2004) Venous thrombosis among patients with AIDS. Clin Appl Thromb Hemost 10:19–25\nMalmberg C, Ripa RS, Johnbeck CB, Knigge U, Langer SW, Mortensen J et al (2015) 64Cu-DOTATATE for noninvasive assessment of atherosclerosis in large arteries and its correlation with risk factors: head-to-head comparison with 68Ga-DOTATOC in 60 patients. J Nucl Med 56:1895–1900\nMary-Krause M, Cotte L, Simon A, Partisani M (2003) Costagliola D, and the clinical epidemiology group from the French hospital database. AIDS. 17:2479–2486\nMavroudis CA, Majumder B, Loizides S, Christophides T, Johnson M, Rakhit RD (2013) Coronary artery disease and HIV; getting to the HAART of the matter. Int J Cardiol 167:1143–1153\nMcMurray HF, Parthasarathy S, Steinberg D (1993) Oxidatively modified low density lipoprotein is a chemoattractant for human T lymphocytes. J Clin Invest 92:1004–1008\nMeester EJ, Krenning BJ, de Blois RH, Norenberg JP, de Jong M, Bernsen MR et al (2018) Imaging of atherosclerosis, targeting LFA-1 on inflammatory cells with 111In-DANBIRT. J Nucl Cardiol. Epub ahead of print on 13 March\nMorlat P, Roussillon C, Henard S, Salmon D, Bonnet F, Cacoub P et al (2014) Causes of death among HIV-infected patients in France in 2010 (national survey): trends since 2000. AIDS. 28:1181–1191\nMosepele M, Molefe-Baikai-Molefe OJ, Grinspoon SK, Triant VA (2018) Benefits and risks of statin therapy in HIV-infected population. Curr Infect Dis Rep 20:20\nMusselwhite LW, Sheikh V, Norton TD, Rupert A, Porter BO, Penzak SR et al (2011) Markers of endothelial dysfunction, coagulation and tissue fibrosis independently predict venous thromboembolism in HIV. AIDS. 25:787–795\nObel N, Farkas DK, Kronborg G, Larsen CS, Pedersen G, Riis A et al (2010) Abacavir and risk of myocardial infarction in HIV-infected patients on highly active antiretroviral therapy: a population-based nationwide cohort study. HIV Med 11:130–136\nRidker PM, Everett BM, Thuren T, MacFadyen JG, Chang WH, Ballantyne C et al (2017) Antiinflammatory therapy with Canakinumab for atherosclerotic disease. N Engl J Med 377:1119–1131\nRominger A, Saam T, Wolpers S, Cyran CC, Schmidt M, Foerster S et al (2009) 18F-FDG PET\u002FCT identifies patients at risk for future vascular events in an otherwise asymptomatic cohort with neoplastic disease. J Nucl Med 50:1611–1620\nRudd JHF, Myers KS, Bansilal S, Machac J, Pinto CA, Tong C et al (2008) Atherosclerosis inflammation imaging with 18F-FDG PET: carotid, iliac, and femoral uptake reproducibility, quantification methods, and recommendations. J Nucl Med 49:871–878\nRudd JHF, Warburton EA, Fryer TD, Jones HA, Clark JC, Antoun N et al (2002) Imaging atherosclerotic plaque inflammation with [18F]-Fluorodeoxyglucose positron emission tomography. Circulation. 105:2708–2711\nSene D, Piette JC, Cacoub P (2008) Antiphospholipid antibodies, antiphospholipid syndrome and infections. Autoimmune Rev 7:272–277\nShah ASV, Stelzle D, Lee KK, Beck EJ, Alam S, Clifford S et al (2018) Global burden of atherosclerotic cardiovascular disease in people living with the human immunodeficiency virus: a systematic review and meta-analysis. Circulation. 138:1100–1112\nSilvola JMU, Li XG, Virta J, Marjamäki P, Liljenbäck H, Hytönen JP et al (2018) Aluminium fluoride-18 labeled folate enables in vivo detection of atherosclerotic plaque inflammation by positron emission tomography. Sci Rep 8:9720\nSubramanian S, Tawakol A, Burdo TH, Abbara S, Wei J, Vijayakumar J et al (2012) Arterial inflammation in patients with HIV. JAMA. 308:379–386\nTarkin JM, Joshi FR, Evans NR, Chowdhury MM, Figg NL, Shah AV et al (2017) Detection of atherosclerotic inflammation by 68Ga-DOTATATE PET compared to [18F]FDG PET imaging. J Am Coll Cardiol 69:1774–1791\nTawakol A, Ishai A, Li D, Pakx RAP, Hur S, Kaiser Y et al (2017) Association of Arterial and Lymph Node Inflammation with distinct inflammatory pathways in human immunodeficiency virus infection. JAMA Cardiol 2:163–171\nTawakol A, Migrino RQ, Bashian GG, Bedri S, Vermylen D, Cury RC et al (2006) In vivo 18F-Fluorodeoxyglucose positron emission tomography imaging provides a noninvasive measure of carotid plaque inflammation in patients. J Am Coll Cardiol 48:1818–1824\nUNAIDS (2018) Global HIV & AIDS statistics. Fact sheet. Available on https:\u002F\u002Fwww.unaids.org>resources>fact-sheet. Accessed 27 Oct 2018\nVigne J, Thackeray J, Essers J, Makowski M, Varasteh Z, Curaj A et al (2018) Current and emerging preclinical approaches for imaging-based characterization of atherosclerosis. Mol Imaging Biol. Epub ahead of print on 24 September\nWalenkamp AME, Lapa C, Herrmann K, Wester HJ (2017) CXCR4 ligands: the next big hit? J Nucl Med 58:77S–82S\nWei L, Pertryk J, Gaudet C, Kamkar M, Gan W, Duan Y et al (2018) Development of an inflammation imaging tracer, 111In-DOTA-DAPTA, targeting chemokine receptor CCR5 and preliminary evaluation in an ApoE−\u002F− atherosclerosis mouse model. J Nucl Cardiol. Epub ahead of print on 07 February\nWeinberg D, Thackeray JT, Daum G, Sohns JM, Kropf S, Wester HJ et al (2018) Clinical molecular imaging of chemokine receptor CXCR4 expression in atherosclerotic plaque using 68Ga-Pentixafor PET: correlation with cardiovascular risk factors and calcified plaque burden. J Nucl Med 59:266–272\nXia W, Hilgenbrink AR, Matteson EL, Lockwood MB, Cheng JX, Low PS (2009) A functional folate receptor is induced during macrophage activation and can be used to target drugs to activated macrophages. Blood. 113:438–446\nYamashita T, Kawashima S, Ozaki M, Namiki M, Inoue N, Hirata K et al (2002) Propagermanium reduces atherosclerosis in apolipoprotein E knockout mice via inhibition of macrophage infiltration. Artrioscler Thromb Vasc Biol 22:969–974\nYarasheski KE, Laciny E, Overton ET, Reeds DN, Harrod M, Baldwin S et al (2012) 18FDG PET-CT imaging detects arterial inflammation and early atherosclerosis in HIV-infected adults with cardiovascular disease risk factors. J Inflamm 9:22. https:\u002F\u002Fdoi.org\u002F10.1186\u002F1476-9255-9-26\nZanni MV, Toribio M, Robbins GK, Burdo TH, Lu MT, Ishai AE et al (2016) Effects of antiretroviral therapy on immune function and arterial inflammation in treatment-naïve patients with human immunodeficiency virus infection. JAMA Cardiol 1:474–480\nZanni MV, Toribio M, Wilks MQ, Lu MT, Burdo TH, Walker J et al (2017) Application of a novel CD206+ macrophage-specific arterial imaging strategy in HIV-infected individuals. J Infect Dis 215:1264–1269",{"EN":414},"People living with human immunodeficiency virus (HIV) infection have twice the risk of atherosclerotic vascular disease compared with non-infected individuals. Inflammation plays a critical role in the development and progression of atherosclerotic vascular disease. Therapies targeting inflammation irrespective of serum lipid levels have been shown to be effective in preventing the occurrence of CVD. Radionuclide imaging is a viable method for evaluating arterial inflammation. This evaluation is useful in quantifying CVD risk and for assessing the effectiveness of anti-inflammatory treatment. The most tested radionuclide method for quantifying arterial inflammation among people living with HIV infection has been with F-18 FDG PET\u002FCT. The level of arterial uptake of F-18 FDG correlates with vascular inflammation and with the risk of development and progression of atherosclerotic disease. Several limitations exist to the use of F-18 FDG for PET quantification of arterial inflammation. Many targets expressed on macrophage, a significant player in arterial inflammation, have the potential for use in evaluating arterial inflammation among people living with HIV infection. The review describes the clinical utility of F-18 FDG PET\u002FCT in assessing arterial inflammation as a risk for atherosclerotic disease among people living with HIV infection. It also outlines potential newer probes that may quantify arterial inflammation in the HIV-infected population by targeting different proteins expressed on macrophages.",{"EN":416},"Radionuclide imaging of inflammation in atherosclerotic vascular disease among people living with HIV infection: current practice and future perspective",{"VOID":418},"10.1186\u002Fs41824-019-0053-7","https:\u002F\u002Fejhi.springeropen.com\u002Farticles\u002F10.1186\u002Fs41824-019-0053-7",[421,447,462,474],{"id":422,"sortIndex":188,"researcher":20,"roles":423,"affiliations":424,"properties":444},"ea7300a4-d3e3-4790-b778-f1509d495542",[160],[425,436],{"id":426,"sortIndex":188,"affiliation":427,"properties":435},"1bd9192e-d6aa-4841-af87-92040721f6e6",{"id":428,"createTime":429,"updateTime":429,"relativeEntities":430,"slug":431,"properties":432,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"3a895209-8fd1-4426-8882-cc4a6b5a7855","2024-04-18T14:25:17.941+00:00",[],"Department-of-Nuclear-Medicine-and-Molecular-Imaging-University-Medical-Center-Groningen-University-of-Groningen-Groningen-The-Netherlands",{"title":433},{"EN":434},"Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands",{},{"id":20,"sortIndex":21,"affiliation":437,"properties":20},{"id":438,"createTime":439,"updateTime":439,"relativeEntities":440,"slug":20,"properties":441,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"70113638-903b-47a3-8186-1c1c37c7e9aa","2024-02-09T13:34:49.835+00:00",[],{"title":442},{"VI":443},"Department of Nuclear Medicine, University of Pretoria & Steve Biko Academic Hospital, Pretoria, South Africa",{"title":445},{"VI":446},"Alfred O. Ankrah",{"id":448,"sortIndex":201,"researcher":20,"roles":449,"affiliations":450,"properties":459},"847358f1-a9c0-4b95-b67d-4b4701db257c",[160],[451],{"id":20,"sortIndex":21,"affiliation":452,"properties":20},{"id":453,"createTime":454,"updateTime":454,"relativeEntities":455,"slug":20,"properties":456,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"e4f68123-588b-4410-9c2b-b3ad342dfd85","2024-02-22T22:46:45.550+00:00",[],{"title":457},{"VI":458},"Infectious Disease Unit, Department of Internal Medicine, University of Pretoria & Steve Biko Academic Hospital, Pretoria, South Africa",{"title":460},{"VI":461},"Anton C. Stoltz",{"id":463,"sortIndex":175,"researcher":20,"roles":464,"affiliations":465,"properties":471},"7d64440e-1f28-4390-8d3b-89e612b6e54f",[160],[466],{"id":20,"sortIndex":21,"affiliation":467,"properties":20},{"id":438,"createTime":439,"updateTime":439,"relativeEntities":468,"slug":20,"properties":469,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":470},{"VI":443},{"title":472},{"VI":473},"Mike M. Sathekge",{"id":475,"sortIndex":21,"researcher":20,"roles":476,"affiliations":477,"properties":483},"8dfce13d-dd10-4532-9dc7-c8ebdfb47819",[160],[478],{"id":20,"sortIndex":21,"affiliation":479,"properties":20},{"id":438,"createTime":439,"updateTime":439,"relativeEntities":480,"slug":20,"properties":481,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":482},{"VI":443},{"title":484},{"VI":485},"Ismaheel O. Lawal",{"url":419,"publisher":487,"properties":515},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":488,"slug":10,"properties":489,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":493,"manageAffiliations":494,"indexDatabases":495,"url":20,"thumbnailPath":20,"statistic":510,"gsStatistic":20,"type":132,"analyzePriority":20},[],{"issn":490,"title":491,"url":492},{"VOID":13},{"EN":15},{"VOID":17},[],[],[496,503],{"id":81,"indexDatabase":497,"url":94,"indexYears":95,"academicFieldIds":502,"indexDatabaseRanking":101},{"id":83,"createTime":84,"updateTime":85,"relativeEntities":498,"label":499,"description":500,"key":91,"publicationTags":501,"standard":20},[],{"EN":88,"VI":88},{"EN":88,"VI":90},[93],[97,98,99,100],{"id":103,"indexDatabase":504,"url":20,"indexYears":20,"academicFieldIds":509,"indexDatabaseRanking":20},{"id":105,"createTime":106,"updateTime":107,"relativeEntities":505,"label":506,"description":507,"key":114,"publicationTags":508,"standard":20},[],{"EN":110,"VI":110},{"VI":112,"EN":113},[116,117],[119],{"impactFactor":21,"impactFactorByYear":511,"i10Index":21,"i10IndexLast5Year":21,"totalPublication":122,"totalPublicationByYear":512,"totalCitation":21,"totalCitationByYear":513,"totalCitationPerPublication":21,"totalCitationPerPublicationByYear":514,"hindexLast5Year":21,"hindex":21},{},{"2017":124,"2018":125,"2019":126,"2020":127,"2021":127,"2022":128,"2023":129},{},{},{"volume":516,"pages":518},{"VOID":517},"3",{"VOID":519},"1-16","2019-04-11",2019,{"id":523,"createTime":524,"updateTime":525,"relativeEntities":526,"slug":527,"properties":528,"entityType":152,"verifyStatus":153,"verifyTime":525,"verifyNote":154,"syncStatus":19,"languages":542,"translateLanguages":544,"viewCount":21,"primaryUrl":545,"fullTextUrl":20,"authors":546,"publicationType":212,"publisherRelationship":679,"citationCount":350,"citationInfo":708,"publishDate":20,"publishYear":20,"citationAnalyzeStatus":710,"lastCitationAnalyze":711,"indexDatabases":20,"openAccess":20,"references":712,"isForceReanalyzing":249},"bee803db-6277-4dd6-ad76-a40e094861dd","2024-04-14T08:52:51.924+00:00","2025-02-13T22:43:29.886+00:00",[],"A-role-for-artificial-intelligence-in-molecular-imaging-of-infection-and-inflammation",{"keywords":529,"openalex":530,"abstract":532,"title":535,"pm":538,"doi":540},{"VI":268},{"VOID":531},"W4294125062",{"VI":533,"EN":534},"\u003Cjats:title>Tóm tắt\u003C\u002Fjats:title>\u003Cjats:p>Sự phát hiện các nhiễm trùng tiềm ẩn và viêm nhẹ trong thực hành lâm sàng vẫn là một thách thức lớn và phụ thuộc nhiều vào trình độ chuyên môn của người đọc. Mặc dù hình ảnh phân tử, như [\u003Cjats:sup>18\u003C\u002Fjats:sup>F]FDG PET hoặc xạ hình bạch cầu được gán nhãn phóng xạ, cung cấp dữ liệu toàn thân định lượng và có thể tái lập về các phản ứng viêm, nhưng việc giải thích chúng vẫn bị giới hạn bởi phân tích hình ảnh. Điều này thường dẫn đến chẩn đoán và điều trị chậm trễ, cũng như các lĩnh vực tiềm năng chưa được khai thác. Trí tuệ nhân tạo (AI) cung cấp những cách tiếp cận đổi mới để khai thác khối lượng lớn dữ liệu hình ảnh và đã dẫn đến những bước đột phá mang tính cách mạng trong các lĩnh vực y tế khác. Ở đây, chúng tôi thảo luận về cách các công cụ dựa trên AI có thể cải thiện độ nhạy phát hiện của hình ảnh phân tử trong nhiễm trùng và viêm, nhưng cũng là cách mà AI có thể mở rộng phân tích dữ liệu vượt xa các ứng dụng hiện tại nhằm dự đoán kết quả và đánh giá rủi ro dài hạn.\u003C\u002Fjats:p>","\u003Cjats:title>Abstract\u003C\u002Fjats:title>\u003Cjats:p>The detection of occult infections and low-grade inflammation in clinical practice remains challenging and much depending on readers’ expertise. Although molecular imaging, like [\u003Cjats:sup>18\u003C\u002Fjats:sup>F]FDG PET or radiolabeled leukocyte scintigraphy, offers quantitative and reproducible whole body data on inflammatory responses its interpretation is limited to visual analysis. This often leads to delayed diagnosis and treatment, as well as untapped areas of potential application. Artificial intelligence (AI) offers innovative approaches to mine the wealth of imaging data and has led to disruptive breakthroughs in other medical domains already. Here, we discuss how AI-based tools can improve the detection sensitivity of molecular imaging in infection and inflammation but also how AI might push the data analysis beyond current application toward predicting outcome and long-term risk assessment.\u003C\u002Fjats:p>",{"VI":536,"EN":537},"Vai trò của trí tuệ nhân tạo trong hình ảnh phân tử của nhiễm trùng và viêm","A role for artificial intelligence in molecular imaging of infection and inflammation",{"VOID":539},"36045228",{"VOID":541},"10.1186\u002Fs41824-022-00138-1",[543],"EN",[271],"https:\u002F\u002Fejhi.springeropen.com\u002Farticles\u002F10.1186\u002Fs41824-022-00138-1",[547,568,588,607,624,643,663],{"id":548,"sortIndex":201,"researcher":20,"roles":549,"affiliations":550,"properties":561},"3af3d4c8-f955-4494-942d-16b7d6568a30",[],[551],{"id":20,"sortIndex":21,"affiliation":552,"properties":20},{"id":553,"createTime":554,"updateTime":555,"relativeEntities":556,"slug":557,"properties":558,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"b102fb99-3311-4917-8497-031df2f4d1db","2023-12-13T21:59:46.013+00:00","2025-02-11T03:22:32.018+00:00",[],"Department-of-Internal-Medicine-Radboud-University-Medical-Center-Nijmegen-The-Netherlands",{"title":559},{"VI":560},"Department of Internal Medicine, Radboud University Medical Center, Nijmegen, The Netherlands",{"openalex":562,"orcid":564,"title":566},{"VOID":563},"A5050515977",{"VOID":565},"https:\u002F\u002Forcid.org\u002F0000-0001-9197-8124",{"EN":567},"Niels P. Riksen",{"id":569,"sortIndex":570,"researcher":20,"roles":571,"affiliations":572,"properties":581},"921c4fad-1a6a-4d2e-9b2d-22cceee5eae5",6,[],[573],{"id":20,"sortIndex":21,"affiliation":574,"properties":20},{"id":575,"createTime":576,"updateTime":576,"relativeEntities":577,"slug":20,"properties":578,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"919d65c2-474d-44ee-8b74-5be8032321fd","2023-12-06T05:21:52.753+00:00",[],{"title":579},{"VI":580},"Department of Internal Medicine, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands",{"openalex":582,"orcid":584,"title":586},{"VOID":583},"A5035000626",{"VOID":585},"https:\u002F\u002Forcid.org\u002F0000-0002-3809-0182",{"EN":587},"Erik H.J.G. Aarntzen",{"id":589,"sortIndex":291,"researcher":20,"roles":590,"affiliations":591,"properties":600},"0db742ae-a7d8-4b62-b483-19c8abae1dad",[],[592],{"id":20,"sortIndex":21,"affiliation":593,"properties":20},{"id":594,"createTime":595,"updateTime":595,"relativeEntities":596,"slug":20,"properties":597,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"34a69303-87c7-4390-a723-cd78d3cd3e4d","2023-12-17T20:03:44.441+00:00",[],{"title":598},{"VI":599},"Department of Biomedical Photonic Imaging, Faculty of Science and Technology, University of Twente, Enschede, the Netherlands",{"openalex":601,"orcid":603,"title":605},{"VOID":602},"A5079661110",{"VOID":604},"https:\u002F\u002Forcid.org\u002F0000-0003-3715-6474",{"EN":606},"Douwe J. Mulder",{"id":608,"sortIndex":350,"researcher":20,"roles":609,"affiliations":610,"properties":619},"6ecb7bc0-708f-4fdc-bf6f-3ca8c0cac449",[],[611],{"id":20,"sortIndex":21,"affiliation":612,"properties":20},{"id":613,"createTime":614,"updateTime":614,"relativeEntities":615,"slug":20,"properties":616,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"16c56636-1ac8-4bd4-89d8-ecf1ef00e34d","2024-01-14T20:34:06.611+00:00",[],{"title":617},{"VI":618},"Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, Groningen, The Netherlands",{"openalex":620,"title":622},{"VOID":621},"A5022821998",{"EN":623},"Riemer Slart",{"id":625,"sortIndex":21,"researcher":20,"roles":626,"affiliations":627,"properties":636},"c0b02602-81af-4dae-804e-6896db12c0af",[],[628],{"id":20,"sortIndex":21,"affiliation":629,"properties":20},{"id":630,"createTime":631,"updateTime":631,"relativeEntities":632,"slug":20,"properties":633,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"b3354dea-ebaa-4dbe-852a-56fcfef9107c","2024-01-10T00:06:56.708+00:00",[],{"title":634},{"VI":635},"Department of Nuclear Medicine and Clinical Molecular Imaging, Eberhard Karls University, Tübingen, Germany",{"openalex":637,"orcid":639,"title":641},{"VOID":638},"A5081325500",{"VOID":640},"https:\u002F\u002Forcid.org\u002F0000-0002-2627-4048",{"EN":642},"Johannes 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Eur J Nucl Med Mol Imaging 46(13):2638–2655",{"doi":1170},"10.1007\u002Fs00259-019-04391-8",{"id":1172,"createTime":1173,"updateTime":1174,"relativeEntities":1175,"slug":1176,"properties":1177,"entityType":152,"verifyStatus":153,"verifyTime":1174,"verifyNote":154,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":1186,"fullTextUrl":20,"authors":1187,"publicationType":212,"publisherRelationship":1227,"citationCount":20,"citationInfo":20,"publishDate":1260,"publishYear":521,"citationAnalyzeStatus":19,"lastCitationAnalyze":20,"indexDatabases":20,"openAccess":20,"references":20,"isForceReanalyzing":249},"8777e5e2-c9f1-404e-96b4-c11d62001121","2024-01-12T07:50:58.692+00:00","2025-01-06T21:57:46.134+00:00",[],"Intestinal-FDG-PET-CT-imaging-of-an-Eritrean-with-schistosomiasis-seen-in-Denmark",{"references":1178,"abstract":1180,"title":1182,"doi":1184},{"VOID":1179},"Bueding E (1950) Carbohydrate metabolism of Schistosoma mansoni. J Gen Physiol 33:475–495\nCenter for Disease Control and Prevention. Parasites schistosomiasis. (2018). https:\u002F\u002Fwww.cdc.gov\u002Fparasites\u002Fschistosomiasis. Accessed 10 Feb 2019.\nKouijzer LJE, Mulders-Manders CM, Bleeker-Rovers CP, Oyen WJG (2018) Fever of unknown origin: the value of FDG-PET\u002FCT. Semin Nucl Med 48(2):100–107 10.1053\u002Fj.semnuclmed.2017.11.004\nSusan Montgomery. Center for disease control and prevention. Infectious disease related to travel. Chapter3. 2017. Available at: https:\u002F\u002Fwwwnc.cdc.gov\u002Ftravel\u002Fyellowbook\u002F2018\u002Finfectious-diseases-related-to-travel\u002Fschistosomiasis. Accessed 17 Mar 2019.\nPhelps ME (2000) PET: the merging of biology and imaging into molecular imaging. J Nucl Med 41(4):661–681\nSalem N, Balkman JD, Wang J et al (2010) In vivo imaging of schistosomes to assess disease burden using positron emission tomography (PET). PLoS Negl Trop Dis 4(9):e827. https:\u002F\u002Fdoi.org\u002F10.1371\u002Fjournal.pntd.0000827.\nSkelly PJ (2013) The use of imaging to detect schistosomes and diagnose schistosomiasis. Parasite Immunol 35(9–10):295–301. https:\u002F\u002Fdoi.org\u002F10.1111\u002Fpim.12040",{"EN":1181},"Schistosomiasis is one of the most common parasitic diseases in subtropical and tropical areas and still is considered of public health significance. This disease affects about 200 million people around the world. Intestinal schistosomiasis is mainly diagnosed by parasitological, serological, and molecular methods. A 36-year-old Eritrean man who had lived in Denmark for the past 3 years presented to the hospital with 4 months’ history of abdominal pain, back pain, and weight loss of 12 kg. He underwent 18F-FDG-PET\u002FCT scanning. The scan findings were consistent with schistosomiasis, which were confirmed by serological and pathological tests. PET\u002FCT is a common modality neither to detect schistosomes nor to diagnose schistosomiasis. A presumptive diagnosis can be made based on coincidence of high FDG uptake in visceral lymph nodes below the diaphragm and in relation to abdominal viscera, travel history suggestive of schistosome infection, and exclusion of other causes of abdominal pain.",{"EN":1183},"Intestinal FDG-PET\u002FCT imaging of an Eritrean with schistosomiasis seen in Denmark",{"VOID":1185},"10.1186\u002Fs41824-019-0064-4","https:\u002F\u002Fejhi.springeropen.com\u002Farticles\u002F10.1186\u002Fs41824-019-0064-4",[1188,1203,1215],{"id":1189,"sortIndex":21,"researcher":20,"roles":1190,"affiliations":1191,"properties":1200},"3fa68ee7-331e-4584-b6c6-3acabbb05d29",[160],[1192],{"id":20,"sortIndex":21,"affiliation":1193,"properties":20},{"id":1194,"createTime":1195,"updateTime":1195,"relativeEntities":1196,"slug":20,"properties":1197,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"f7530e9a-9161-48c0-8d45-eea4437dd6b7","2024-01-12T07:50:58.717+00:00",[],{"title":1198},{"VI":1199},"Department of Clinical Physiology and Nuclear Medicine, Zealand University Hospital, Køge, Denmark",{"title":1201},{"VI":1202},"Ata 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Eur Radiol 18(5):1058–1064. \n                    https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00330-007-0843-3",{"doi":1554},"10.1007\u002Fs00330-007-0843-3",{"id":20,"text":1556,"url":20,"identifiers":1557},"Miccò M, Vargas HA, Burger IA et al (2014) Combined pre-treatment MRI and 18F-FDG PET\u002FCT parameters as prognostic biomarkers in patients with cervical cancer. Eur J Radiol 83(7):1169–1176. \n                    https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ejrad.2014.03.024",{"doi":1558},"10.1016\u002Fj.ejrad.2014.03.024",{"id":20,"text":1560,"url":20,"identifiers":1561},"Mirpour S, Mhlanga JC, Logeswaran P, Russo G, Mercier G, Subramaniam RM (2013) The role of PET\u002FCT in the Management of Cervical Cancer. Am J Roentgenol 201(2):W192–W205. \n                    https:\u002F\u002Fdoi.org\u002F10.2214\u002FAJR.12.9830",{"doi":1562},"10.2214\u002FAJR.12.9830",{"id":20,"text":1564,"url":20,"identifiers":1565},"Nakajo K, Tatsumi M, Inoue A et al (2010) Diagnostic performance of fluorodeoxyglucose positron emission tomography\u002Fmagnetic resonance imaging fusion images of gynecological malignant tumors: comparison with positron emission tomography\u002Fcomputed tomography. Jpn J Radiol 28(2):95–100. \n                    https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11604-009-0387-3",{"doi":1566},"10.1007\u002Fs11604-009-0387-3",{"id":20,"text":1568,"url":20,"identifiers":1569},"Nakamura K, Joja I, Nagasaka T et al (2012) The mean apparent diffusion coefficient value (ADCmean) on primary cervical cancer is a predictive marker for disease recurrence. Gynecol Oncol 127(3):478–483. \n                    https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ygyno.2012.07.123",{"doi":1570},"10.1016\u002Fj.ygyno.2012.07.123",{"id":20,"text":1572,"url":20,"identifiers":1573},"Queiroz MA, Kubik-Huch RA, Hauser N et al (2015) PET\u002FMRI and PET\u002FCT in advanced gynaecological tumours: initial experience and comparison. Eur Radiol 25(8):2222–2230. \n                    https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00330-015-3657-8",{"doi":1574},"10.1007\u002Fs00330-015-3657-8",{"id":20,"text":1576,"url":20,"identifiers":1577},"RSM L, Ramdave S, Beech P et al (2016) Utility of SUVmax on 18 F-FDG PET in detecting cervical nodal metastases. Cancer Imaging 16(1):39. \n                    https:\u002F\u002Fdoi.org\u002F10.1186\u002Fs40644-016-0095-z",{"doi":1578},"10.1186\u002Fs40644-016-0095-z",{"id":20,"text":1580,"url":20,"identifiers":1581},"Sarabhai T, Schaarschmidt BM, Wetter A et al (2018) Comparison of 18F-FDG PET\u002FMRI and MRI for pre-therapeutic tumor staging of patients with primary cancer of the uterine cervix. Eur J Nucl Med Mol Imaging 45(1):67–76. \n                    https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00259-017-3809-y",{"doi":1582},"10.1007\u002Fs00259-017-3809-y",{"id":20,"text":1584,"url":20,"identifiers":1585},"Sironi S, Buda A, Picchio M et al (2006) Lymph node metastasis in patients with clinical early-stage cervical Cancer: detection with integrated FDG PET\u002FCT. Radiology 238(1):272–279. \n                    https:\u002F\u002Fdoi.org\u002F10.1148\u002Fradiol.2381041799",{"doi":1586},"10.1148\u002Fradiol.2381041799",{"id":20,"text":1588,"url":20,"identifiers":1589},"Yoo J, Choi JY, Moon SH et al (2012) Prognostic significance of volume-based metabolic parameters in uterine cervical Cancer determined using 18F-Fluorodeoxyglucose positron emission tomography. Int J Gynecol Cancer 22(7):1226–1233. \n                    https:\u002F\u002Fdoi.org\u002F10.1097\u002FIGC.0b013e318260a905",{"doi":1590},"10.1097\u002FIGC.0b013e318260a905",{"id":1592,"createTime":1593,"updateTime":1594,"relativeEntities":1595,"slug":1596,"properties":1597,"entityType":152,"verifyStatus":153,"verifyTime":1594,"verifyNote":154,"syncStatus":19,"languages":1612,"translateLanguages":1613,"viewCount":21,"primaryUrl":1614,"fullTextUrl":20,"authors":1615,"publicationType":212,"publisherRelationship":1774,"citationCount":175,"citationInfo":1803,"publishDate":1805,"publishYear":1806,"citationAnalyzeStatus":710,"lastCitationAnalyze":1807,"indexDatabases":20,"openAccess":20,"references":1808,"isForceReanalyzing":249},"a5a728ae-d3b6-4f4d-a879-bb56a47a073f","2024-04-11T12:23:38.656+00:00","2025-02-05T21:40:07.559+00:00",[],"Multi-parametric-PET-MRI-for-enhanced-tumor-characterization-of-patients-with-cervical-cancer",{"keywords":1598,"openalex":1600,"abstract":1602,"title":1605,"pm":1608,"doi":1610},{"VI":1599},"y học cá nhân hóa, ung thư cổ tử cung, PET\u002FMRI đa tham số, tính không đồng nhất khối u, yếu tố hình ảnh chức năng",{"VOID":1601},"W4224318517",{"VI":1603,"EN":1604},"\u003Cjats:title>Tóm tắt\u003C\u002Fjats:title>\u003Cjats:sec>\n                \u003Cjats:title>Mục tiêu\u003C\u002Fjats:title>\n                \u003Cjats:p>Khái niệm y học cá nhân hóa đã nâng cao nhận thức về tầm quan trọng của sự khác biệt giữa và trong các khối u cho việc điều trị ung thư. Mục tiêu của nghiên cứu này là khám phá việc sử dụng PET\u002FMRI đa tham số đồng thời trước khi hóa trị xạ trị cho ung thư cổ tử cung nhằm phân loại và đánh giá tính không đồng nhất của các khối u.\u003C\u002Fjats:p>\n              \u003C\u002Fjats:sec>\u003Cjats:sec>\n                \u003Cjats:title>Phương pháp\u003C\u002Fjats:title>\n                \u003Cjats:p>Mười bệnh nhân có ung thư cổ tử cung nguyên phát đã được xác nhận bằng mô học được thăm khám bằng PET\u002FMRI đa tham số \u003Cjats:sup>68\u003C\u002Fjats:sup>Ga-NODAGA-E[c(RGDyK)]\u003Cjats:sub>2\u003C\u002Fjats:sub> để lập kế hoạch điều trị bức xạ sau khi thực hiện \u003Cjats:sup>18\u003C\u002Fjats:sup>F-FDG-PET\u002FCT chẩn đoán. Các giá trị hấp thu chuẩn hóa (SUV) của RGD và FDG, MRI khuếch tán và hệ số khuếch tán biểu kiến (ADC) thu được và các bản đồ dược động học được lấy từ MRI tăng cường tương phản động với mô hình Tofts (iAUC\u003Cjats:sub>60\u003C\u002Fjats:sub>, \u003Cjats:italic>K\u003C\u002Fjats:italic>\u003Cjats:sup>trans\u003C\u002Fjats:sup>, \u003Cjats:italic>v\u003C\u002Fjats:italic>\u003Cjats:sub>e\u003C\u002Fjats:sub>, và \u003Cjats:italic>k\u003C\u002Fjats:italic>\u003Cjats:sub>ep\u003C\u002Fjats:sub>) cũng được đưa vào phân tích. Quan hệ không gian giữa các tham số hình ảnh chức năng trong các khối u đã được xem xét bằng phân tích tương quan và biểu đồ chung tại mức voxel. Khả năng của hình ảnh đa tham số trong việc xác định các lớp mô khối u đã được khám phá bằng cách sử dụng phân tích cụm dựa trên mô hình hỗn hợp Gaussian 3D không giám sát.\u003C\u002Fjats:p>\n              \u003C\u002Fjats:sec>\u003Cjats:sec>\n                \u003Cjats:title>Kết quả\u003C\u002Fjats:title>\n                \u003Cjats:p>Hình ảnh MRI và PET chức năng của các khối u cổ tử cung có vẻ khác biệt cả giữa các bệnh nhân và không gian trong các khối u, và các mối quan hệ giữa các tham số thay đổi mạnh mẽ trong nhóm bệnh nhân. Mối tương quan không gian mạnh nhất được quan sát giữa việc hấp thu FDG và ADC (trung vị \u003Cjats:italic>r\u003C\u002Fjats:italic> =  − 0.7). Có sự tương quan mức voxel vừa phải giữa việc hấp thu RGD và FDG, và sự tương quan yếu giữa tất cả các phương pháp khác. Các mối quan hệ rõ ràng giữa ADC và việc hấp thu RGD cũng như giữa ADC và việc hấp thu FDG rõ ràng xuất hiện trong các biểu đồ chung. Phân tích cụm sử dụng sự kết hợp giữa ADC, FDG và sự hấp thu RGD đã gợi ý về các lớp mô có thể liên quan đến các tiểu khối u.","\u003Cjats:title>Abstract\u003C\u002Fjats:title>\u003Cjats:sec>\n                \u003Cjats:title>Aim\u003C\u002Fjats:title>\n                \u003Cjats:p>The concept of personalized medicine has brought increased awareness to the importance of inter- and intra-tumor heterogeneity for cancer treatment. The aim of this study was to explore simultaneous multi-parametric PET\u002FMRI prior to chemoradiotherapy for cervical cancer for characterization of tumors and tumor heterogeneity.\u003C\u002Fjats:p>\n              \u003C\u002Fjats:sec>\u003Cjats:sec>\n                \u003Cjats:title>Methods\u003C\u002Fjats:title>\n                \u003Cjats:p>Ten patients with histologically proven primary cervical cancer were examined with multi-parametric \u003Cjats:sup>68\u003C\u002Fjats:sup>Ga-NODAGA-E[c(RGDyK)]\u003Cjats:sub>2\u003C\u002Fjats:sub>-PET\u002FMRI for radiation treatment planning after diagnostic \u003Cjats:sup>18\u003C\u002Fjats:sup>F-FDG-PET\u002FCT. Standardized uptake values (SUV) of RGD and FDG, diffusion weighted MRI and the derived apparent diffusion coefficient (ADC), and pharmacokinetic maps obtained from dynamic contrast-enhanced MRI with the Tofts model (iAUC\u003Cjats:sub>60\u003C\u002Fjats:sub>, \u003Cjats:italic>K\u003C\u002Fjats:italic>\u003Cjats:sup>trans\u003C\u002Fjats:sup>, \u003Cjats:italic>v\u003C\u002Fjats:italic>\u003Cjats:sub>e\u003C\u002Fjats:sub>, and \u003Cjats:italic>k\u003C\u002Fjats:italic>\u003Cjats:sub>ep\u003C\u002Fjats:sub>) were included in the analysis. The spatial relation between functional imaging parameters in tumors was examined by a correlation analysis and joint histograms at the voxel level. The ability of multi-parametric imaging to identify tumor tissue classes was explored using an unsupervised 3D Gaussian mixture model-based cluster analysis.\u003C\u002Fjats:p>\n              \u003C\u002Fjats:sec>\u003Cjats:sec>\n                \u003Cjats:title>Results\u003C\u002Fjats:title>\n                \u003Cjats:p>Functional MRI and PET of cervical cancers appeared heterogeneous both between patients and spatially within the tumors, and the relations between parameters varied strongly within the patient cohort. The strongest spatial correlation was observed between FDG uptake and ADC (median \u003Cjats:italic>r\u003C\u002Fjats:italic> =  − 0.7). There was moderate voxel-wise correlation between RGD and FDG uptake, and weak correlations between all other modalities. Distinct relations between the ADC and RGD uptake as well as the ADC and FDG uptake were apparent in joint histograms. A cluster analysis using the combination of ADC, FDG and RGD uptake suggested tissue classes which could potentially relate to tumor sub-volumes.\u003C\u002Fjats:p>\n              \u003C\u002Fjats:sec>\u003Cjats:sec>\n                \u003Cjats:title>Conclusion\u003C\u002Fjats:title>\n                \u003Cjats:p>A multi-parametric PET\u002FMRI examination of patients with cervical cancer integrated with treatment planning and including estimation of angiogenesis and glucose metabolism as well as MRI diffusion and perfusion parameters is feasible. A combined analysis of functional imaging parameters indicates a potential of multi-parametric PET\u002FMRI to contribute to a better characterization of tumor heterogeneity than the modalities alone. However, the study is based on small patient numbers and further studies are needed prior to the future design of individually adapted treatment approaches based on multi-parametric functional imaging.\u003C\u002Fjats:p>\n              \u003C\u002Fjats:sec>",{"VI":1606,"EN":1607},"PET\u002FMRI đa tham số nâng cao đặc trưng khối u ở bệnh nhân ung thư cổ tử cung","Multi-parametric PET\u002FMRI for enhanced tumor characterization of patients with cervical 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Acta Oncol (madr) 55(11):1294–1298",{"doi":1996},"10.1080\u002F0284186X.2016.1189091",{"id":20,"text":1998,"url":20,"identifiers":1999},"Tsien C, Cao Y, Chenevert T (2014) Clinical Applications for Diffusion Magnetic Resonance Imaging in Radiotherapy. Semin Radiat Oncol. 24(3):218–226. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.semradonc.2014.02.004",{"doi":2000},"10.1016\u002Fj.semradonc.2014.02.004",{"id":20,"text":2002,"url":20,"identifiers":2003},"Watanabe Y, Nakamura S, Ichikawa Y, Ii N, Kawamura T, Kondo E et al (2021) Early alteration in apparent diffusion coefficient and tumor volume in cervical cancer treated with chemoradiotherapy or radiotherapy: Incremental prognostic value over pretreatment assessments. Radiother Oncol 155:3–9. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.radonc.2020.09.059",{"doi":2004},"10.1016\u002Fj.radonc.2020.09.059",{"id":2006,"createTime":2007,"updateTime":2008,"relativeEntities":2009,"slug":2010,"properties":2011,"entityType":152,"verifyStatus":153,"verifyTime":2008,"verifyNote":154,"syncStatus":19,"languages":2027,"translateLanguages":20,"viewCount":21,"primaryUrl":2028,"fullTextUrl":20,"authors":2029,"publicationType":212,"publisherRelationship":2185,"citationCount":201,"citationInfo":2218,"publishDate":2220,"publishYear":403,"citationAnalyzeStatus":19,"lastCitationAnalyze":20,"indexDatabases":20,"openAccess":20,"references":2221,"isForceReanalyzing":249},"221084f9-40f8-4a9c-902a-08527ef5b19c","2024-04-17T03:23:48.600+00:00","2024-12-26T21:39:40.776+00:00",[],"18F-fluorothymidine-FLT-PET-and-diffusion-weighted-MRI-for-early-response-evaluation-in-patients-with-small-cell-lung-cancer-a-pilot-study",{"mag":2012,"keywords":2014,"pmc":2015,"openalex":2017,"abstract":2019,"title":2021,"pm":2023,"doi":2025},{"VOID":2013},"3026175333",{},{"VOID":2016},"8218141",{"VOID":2018},"W3026175333",{"EN":2020},"\u003Cjats:title>Abstract\u003C\u002Fjats:title>\u003Cjats:sec>\n                \u003Cjats:title>Background\u003C\u002Fjats:title>\n                \u003Cjats:p>Small cell lung cancer (SCLC) is an aggressive cancer often presenting in an advanced stage and prognosis is poor. Early response evaluation may have impact on the treatment strategy.\u003C\u002Fjats:p>\n              \u003C\u002Fjats:sec>\u003Cjats:sec>\n                \u003Cjats:title>Aim\u003C\u002Fjats:title>\n                \u003Cjats:p>We evaluated \u003Cjats:sup>18\u003C\u002Fjats:sup>F-fluorothymidine-(FLT)-PET\u002Fdiffusion-weighted-(DW)-MRI early after treatment start to describe biological changes during therapy, the potential of early response evaluation, and the added value of FLT-PET\u002FDW-MRI.\u003C\u002Fjats:p>\n              \u003C\u002Fjats:sec>\u003Cjats:sec>\n                \u003Cjats:title>Methods\u003C\u002Fjats:title>\n                \u003Cjats:p>Patients with SCLC referred for standard chemotherapy were eligible. FLT-PET\u002FDW-MRI of the chest and brain was acquired within 14 days after treatment start. FLT-PET\u002FDW-MRI was compared with pretreatment FDG-PET\u002FCT. Standardized uptake value (SUV), apparent diffusion coefficient (ADC), and functional tumor volumes were measured. FDG-SUV\u003Cjats:sub>peak\u003C\u002Fjats:sub>, FLT-SUV\u003Cjats:sub>peak\u003C\u002Fjats:sub>, and ADC\u003Cjats:sub>median\u003C\u002Fjats:sub>; spatial distribution of aggressive areas; and voxel-by-voxel analyses were evaluated to compare the biological information derived from the three functional imaging modalities. FDG-SUV\u003Cjats:sub>peak\u003C\u002Fjats:sub>, FLT-SUV\u003Cjats:sub>peak\u003C\u002Fjats:sub>, and ADC\u003Cjats:sub>median\u003C\u002Fjats:sub> were also analyzed for ability to predict final treatment response.\u003C\u002Fjats:p>\n              \u003C\u002Fjats:sec>\u003Cjats:sec>\n                \u003Cjats:title>Results\u003C\u002Fjats:title>\n                \u003Cjats:p>Twelve patients with SCLC completed FLT-PET\u002FMRI 1–9 days after treatment start. In nine patients, pretreatment FDG-PET\u002FCT was available for comparison. A total of 16 T-sites and 12 N-sites were identified. No brain metastases were detected. FDG-SUV\u003Cjats:sub>peak\u003C\u002Fjats:sub> was 2.0–22.7 in T-sites and 5.5–17.3 in N-sites. FLT-SUV\u003Cjats:sub>peak\u003C\u002Fjats:sub> was 0.6–11.5 in T-sites and 1.2–2.4 in N-sites. ADC\u003Cjats:sub>median\u003C\u002Fjats:sub> was 0.76–1.74 × 10\u003Cjats:sup>− 3\u003C\u002Fjats:sup> mm\u003Cjats:sup>2\u003C\u002Fjats:sup>\u002Fs in T-sites and 0.88–2.09 × 10\u003Cjats:sup>−3\u003C\u002Fjats:sup> mm\u003Cjats:sup>2\u003C\u002Fjats:sup>\u002Fs in N-sites. FLT-SUV\u003Cjats:sub>peak\u003C\u002Fjats:sub> correlated with FDG-SUV\u003Cjats:sub>peak\u003C\u002Fjats:sub>, and voxel-by-voxel correlation was positive, though the hottest regions were dissimilarly distributed in FLT-PET compared to FDG-PET. FLT-SUV\u003Cjats:sub>peak\u003C\u002Fjats:sub> was not correlated with ADC\u003Cjats:sub>median\u003C\u002Fjats:sub>, and voxel-by-voxel analyses and spatial distribution of aggressive areas varied with no systematic relation. LT-SUV\u003Cjats:sub>peak\u003C\u002Fjats:sub> was significantly lower in responding lesions than non-responding lesions (mean FLT-SUV\u003Cjats:sub>peak\u003C\u002Fjats:sub> in T-sites: 1.5 vs. 5.7; \u003Cjats:italic>p\u003C\u002Fjats:italic> = 0.007, mean FLT-SUV\u003Cjats:sub>peak\u003C\u002Fjats:sub> in N-sites: 1.6 vs. 2.2; \u003Cjats:italic>p\u003C\u002Fjats:italic> = 0.013).\u003C\u002Fjats:p>\n              \u003C\u002Fjats:sec>\u003Cjats:sec>\n                \u003Cjats:title>Conclusions\u003C\u002Fjats:title>\n                \u003Cjats:p>FLT-PET and DW-MRI performed early after treatment start may add biological information in patients with SCLC. Proliferation early after treatment start measured by FLT-PET is a promising predictor for final treatment response that warrants further investigation.\u003C\u002Fjats:p>\n              \u003C\u002Fjats:sec>\u003Cjats:sec>\n                \u003Cjats:title>Trial registration\u003C\u002Fjats:title>\n                \u003Cjats:p>Clinicaltrials.gov, \u003Cjats:ext-link xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" ext-link-type=\"uri\" xlink:href=\"https:\u002F\u002Fclinicaltrials.gov\u002Fct2\u002Fshow\u002FNCT02995902?term=NCT02995902&rank=1\">NCT02995902\u003C\u002Fjats:ext-link>. Registered 11 December 2014 - Retrospectively registered.\u003C\u002Fjats:p>\n              \u003C\u002Fjats:sec>",{"EN":2022},"18F-fluorothymidine (FLT)-PET and diffusion-weighted MRI for early response evaluation in patients with small cell lung cancer: a pilot study",{"VOID":2024},"34191195",{"VOID":2026},"10.1186\u002Fs41824-019-0071-5",[543],"https:\u002F\u002Fejhi.springeropen.com\u002Farticles\u002F10.1186\u002Fs41824-019-0071-5",[2030,2049,2064,2079,2096,2113,2128,2145,2167],{"id":2031,"sortIndex":175,"researcher":20,"roles":2032,"affiliations":2033,"properties":2044},"1a18fe0c-5415-4dae-b850-4b752f58bde6",[],[2034],{"id":2035,"sortIndex":21,"affiliation":2036,"properties":20},"c54563f8-35f3-44f2-8e8e-c1e0c836a403",{"id":2037,"createTime":2038,"updateTime":2038,"relativeEntities":2039,"slug":2040,"properties":2041,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"174336ba-169a-4dbf-bed1-1d49fc9e7ad4","2024-04-17T03:23:48.684+00:00",[],"Department-of-Clinical-Physiology-Nuclear-Medicine-PET-Rigshospitalet-University-of-Copenhagen-Blegdamsvej-9-2100-Copenhagen-%C3%98-Denmark",{"title":2042},{"EN":2043},"Department of Clinical Physiology, Nuclear Medicine & PET, Rigshospitalet, University of Copenhagen, Blegdamsvej 9, 2100, Copenhagen Ø, Denmark",{"openalex":2045,"title":2047},{"VOID":2046},"A5088700870",{"EN":2048},"Helle Hjorth Johannesen",{"id":2050,"sortIndex":201,"researcher":20,"roles":2051,"affiliations":2052,"properties":2059},"7466a2bd-e439-48df-a018-1fb40feeaacc",[],[2053],{"id":2054,"sortIndex":21,"affiliation":2055,"properties":20},"c3f176fd-a403-4cec-80ca-af0123633b48",{"id":2037,"createTime":2038,"updateTime":2038,"relativeEntities":2056,"slug":2040,"properties":2057,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":2058},{"EN":2043},{"openalex":2060,"title":2062},{"VOID":2061},"A5020786447",{"EN":2063},"Katrine Engholm Villumsen",{"id":2065,"sortIndex":350,"researcher":20,"roles":2066,"affiliations":2067,"properties":2074},"8213eebc-b383-48f4-9789-2178cd696ef2",[],[2068],{"id":2069,"sortIndex":21,"affiliation":2070,"properties":20},"0fb8d4f4-82c7-4cd6-a01c-ea460519080f",{"id":2037,"createTime":2038,"updateTime":2038,"relativeEntities":2071,"slug":2040,"properties":2072,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":2073},{"EN":2043},{"openalex":2075,"title":2077},{"VOID":2076},"A5019190726",{"EN":2078},"Sune H. Keller",{"id":2080,"sortIndex":570,"researcher":20,"roles":2081,"affiliations":2082,"properties":2089},"ac9870bb-5eeb-40a2-9787-778f3945fc13",[],[2083],{"id":2084,"sortIndex":21,"affiliation":2085,"properties":20},"b27b9585-8e9e-4cd5-9a84-2cbb7114487e",{"id":2037,"createTime":2038,"updateTime":2038,"relativeEntities":2086,"slug":2040,"properties":2087,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":2088},{"EN":2043},{"openalex":2090,"orcid":2092,"title":2094},{"VOID":2091},"A5033672920",{"VOID":2093},"https:\u002F\u002Forcid.org\u002F0000-0002-6457-1537",{"EN":2095},"Adam E. Hansen",{"id":2097,"sortIndex":1388,"researcher":20,"roles":2098,"affiliations":2099,"properties":2109},"1c745094-ce4c-4aa4-b301-fd0a7665cf7c",[],[2100],{"id":2101,"sortIndex":21,"affiliation":2102,"properties":20},"d6adc282-b341-4a94-8f9d-c7da2cf223c8",{"id":2103,"createTime":2104,"updateTime":2104,"relativeEntities":2105,"slug":20,"properties":2106,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"b67e574c-bfb9-4bf4-ba37-7f42d3692e23","2024-01-25T15:41:58.528+00:00",[],{"title":2107},{"VI":2108},"Cluster for Molecular Imaging, University of Copenhagen, Copenhagen, Denmark",{"openalex":2110,"orcid":2111,"title":2112},{"VOID":1736},{"VOID":1738},{"EN":1740},{"id":2114,"sortIndex":291,"researcher":20,"roles":2115,"affiliations":2116,"properties":2123},"b9997c05-594c-41fe-aa17-dcbfd2aae07e",[],[2117],{"id":2118,"sortIndex":21,"affiliation":2119,"properties":20},"9cbcda63-68bf-4cb2-86fc-418efa1e25d7",{"id":2037,"createTime":2038,"updateTime":2038,"relativeEntities":2120,"slug":2040,"properties":2121,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":2122},{"EN":2043},{"openalex":2124,"title":2126},{"VOID":2125},"A5061539843",{"EN":2127},"Johan Löfgren",{"id":2129,"sortIndex":21,"researcher":20,"roles":2130,"affiliations":2131,"properties":2138},"7898ce88-2b26-4a6c-a61b-ae405478a951",[],[2132],{"id":2133,"sortIndex":21,"affiliation":2134,"properties":20},"40c48388-28b8-4bca-a4e9-ed6f5785bdcd",{"id":2037,"createTime":2038,"updateTime":2038,"relativeEntities":2135,"slug":2040,"properties":2136,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":2137},{"EN":2043},{"openalex":2139,"orcid":2141,"title":2143},{"VOID":2140},"A5023651187",{"VOID":2142},"https:\u002F\u002Forcid.org\u002F0000-0002-5581-6715",{"EN":2144},"Tine Nøhr Christensen",{"id":2146,"sortIndex":188,"researcher":20,"roles":2147,"affiliations":2148,"properties":2160},"d7d85ff4-39cf-4806-b982-fc5a5b32df02",[],[2149],{"id":2150,"sortIndex":21,"affiliation":2151,"properties":20},"e1d8b95a-3c75-46c4-95b0-cdca63d07d5a",{"id":2152,"createTime":2153,"updateTime":2154,"relativeEntities":2155,"slug":2156,"properties":2157,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"0146fa2f-e9e0-4602-8283-a9a49dedced6","2024-01-16T10:55:14.448+00:00","2025-06-11T14:44:27.927+00:00",[],"Department-of-Oncology-Rigshospitalet-University-of-Copenhagen-Copenhagen-Denmark",{"title":2158},{"VI":2159},"Department of Oncology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark",{"openalex":2161,"orcid":2163,"title":2165},{"VOID":2162},"A5045868855",{"VOID":2164},"https:\u002F\u002Forcid.org\u002F0000-0001-9732-9192",{"EN":2166},"Seppo W. Langer",{"id":2168,"sortIndex":66,"researcher":20,"roles":2169,"affiliations":2170,"properties":2181},"bb2211f1-bd77-4812-a5f0-87f54b595929",[],[2171],{"id":2172,"sortIndex":21,"affiliation":2173,"properties":20},"1cd4f78d-aa40-453b-9d83-814047ac8a44",{"id":2174,"createTime":2175,"updateTime":2175,"relativeEntities":2176,"slug":2177,"properties":2178,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"3a241452-9801-49fa-9076-5f96db8ce974","2024-04-17T03:23:48.710+00:00",[],"PET-Centre-School-of-Biomedical-Engineering-and-Imaging-Science-Kings-College-London-London-UK",{"title":2179},{"EN":2180},"PET Centre, School of Biomedical Engineering and Imaging Science, Kings College London, London, UK",{"openalex":2182,"orcid":2183,"title":2184},{"VOID":1658},{"VOID":1660},{"EN":1662},{"url":20,"publisher":2186,"properties":2214},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":2187,"slug":10,"properties":2188,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":2192,"manageAffiliations":2193,"indexDatabases":2194,"url":20,"thumbnailPath":20,"statistic":2209,"gsStatistic":20,"type":132,"analyzePriority":20},[],{"issn":2189,"title":2190,"url":2191},{"VOID":13},{"EN":15},{"VOID":17},[],[],[2195,2202],{"id":81,"indexDatabase":2196,"url":94,"indexYears":95,"academicFieldIds":2201,"indexDatabaseRanking":101},{"id":83,"createTime":84,"updateTime":85,"relativeEntities":2197,"label":2198,"description":2199,"key":91,"publicationTags":2200,"standard":20},[],{"EN":88,"VI":88},{"EN":88,"VI":90},[93],[97,98,99,100],{"id":103,"indexDatabase":2203,"url":20,"indexYears":20,"academicFieldIds":2208,"indexDatabaseRanking":20},{"id":105,"createTime":106,"updateTime":107,"relativeEntities":2204,"label":2205,"description":2206,"key":114,"publicationTags":2207,"standard":20},[],{"EN":110,"VI":110},{"VI":112,"EN":113},[116,117],[119],{"impactFactor":21,"impactFactorByYear":2210,"i10Index":21,"i10IndexLast5Year":21,"totalPublication":122,"totalPublicationByYear":2211,"totalCitation":21,"totalCitationByYear":2212,"totalCitationPerPublication":21,"totalCitationPerPublicationByYear":2213,"hindexLast5Year":21,"hindex":21},{},{"2017":124,"2018":125,"2019":126,"2020":127,"2021":127,"2022":128,"2023":129},{},{},{"volume":2215,"issue":2216},{"VOID":399},{"VOID":2217},"1",{"total":201,"publishYear":20,"statisticByYear":2219},{"2021":188,"2022":188},"2020-12-01",[2222,2226,2229,2233,2237,2241,2245,2249,2253,2257,2261,2265,2269,2273,2277,2281,2285,2289,2293,2297,2300,2304,2308,2312,2316,2320,2324,2328,2332,2336,2340,2343,2347,2351,2355,2359,2363,2367,2371,2375,2379,2383,2387,2391,2394,2398,2402,2406,2410,2414,2418,2422,2426,2430,2434,2438,2442,2446,2450],{"id":20,"text":2223,"url":20,"identifiers":2224},"Aktan M, Koc M, Kanyilmaz G, Yavuz BB (2017) Prognostic value of pre-treatment (18)F-FDG-PET uptake in small-cell lung cancer. Ann Nucl Med 31(6):462–468",{"doi":2225},"10.1007\u002Fs12149-017-1178-z",{"id":20,"text":2227,"url":20,"identifiers":2228},"Boellaard R, Delgado-Bolton R, Oyen WJ, Giammarile F, Tatsch K, Eschner W et al (2015) FDG PET\u002FCT: EANM procedure guidelines for tumour imaging: version 2.0. Eur J Nucl Med Mol Imaging 42(2):328–354",{"doi":1484},{"id":20,"text":2230,"url":20,"identifiers":2231},"Brockenbrough JS, Souquet T, Morihara JK, Stern JE, Hawes SE, Rasey JS et al (2011) Tumor 3′-deoxy-3′-(18)F-fluorothymidine ((18)F-FLT) uptake by PET correlates with thymidine kinase 1 expression: static and kinetic analysis of (18)F-FLT PET studies in lung tumors. J Nucl Med 52(8):1181–1188",{"doi":2232},"10.2967\u002Fjnumed.111.089482",{"id":20,"text":2234,"url":20,"identifiers":2235},"Chang H, Lee SJ, Lim J, Lee JS, Kim YJ, Lee WW (2019) Prognostic significance of metabolic parameters measured by (18)F-FDG PET\u002FCT in limited-stage small-cell lung carcinoma. J Cancer Res Clin Oncol 145(5):1361-1367",{"doi":2236},"10.1007\u002Fs00432-019-02848-9",{"id":20,"text":2238,"url":20,"identifiers":2239},"Crandall JP, Tahari AK, Juergens RA, Brahmer JR, Rudin CM, Esposito G et al (2017) A comparison of FLT to FDG PET\u002FCT in the early assessment of chemotherapy response in stages IB-IIIA resectable NSCLC. EJNMMI Res 7(1):8",{"doi":2240},"10.1186\u002Fs13550-017-0258-3",{"id":20,"text":2242,"url":20,"identifiers":2243},"Cysouw MCF, Kramer GM, Frings V, De Langen AJ, Wondergem MJ, Kenny LM et al (2017) Baseline and longitudinal variability of normal tissue uptake values of [(18)F]-fluorothymidine-PET images. Nucl Med Biol 51:18–24",{"doi":2244},"10.1016\u002Fj.nucmedbio.2017.05.002",{"id":20,"text":2246,"url":20,"identifiers":2247},"Dayen C, Debieuvre D, Molinier O, Raffy O, Paganin F, Virally J et al (2017) New insights into stage and prognosis in small cell lung cancer: an analysis of 968 cases. J Thorac Dis 9(12):5101–5111",{"doi":2248},"10.21037\u002Fjtd.2017.11.52",{"id":20,"text":2250,"url":20,"identifiers":2251},"Dittmann H, Dohmen BM, Paulsen F, Eichhorn K, Eschmann SM, Horger M et al (2003) [18F] FLT PET for diagnosis and staging of thoracic tumours. Eur J Nucl Med Mol Imaging 30(10):1407–1412",{"doi":2252},"10.1007\u002Fs00259-003-1257-3",{"id":20,"text":2254,"url":20,"identifiers":2255},"Eisenhauer EA, Therasse P, Bogaerts J, Schwartz LH, Sargent D, Ford R et al (2009) New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer 45(2):228–247",{"doi":2256},"10.1016\u002Fj.ejca.2008.10.026",{"id":20,"text":2258,"url":20,"identifiers":2259},"Everitt S, Ball D, Hicks RJ, Callahan J, Plumridge N, Trinh J et al (2017) Prospective study of serial imaging comparing fluorodeoxyglucose positron emission tomography (PET) and fluorothymidine PET during radical chemoradiation for non-small cell lung cancer: reduction of detectable proliferation associated with worse survival. Int J Radiat Oncol Biol Phys 99(4):947–955",{"doi":2260},"10.1016\u002Fj.ijrobp.2017.07.035",{"id":20,"text":2262,"url":20,"identifiers":2263},"Everitt SJ, Ball DL, Hicks RJ, Callahan J, Plumridge N, Collins M et al (2014) Differential (18)F-FDG and (18)F-FLT uptake on serial PET\u002FCT imaging before and during definitive chemoradiation for non-small cell lung cancer. J Nucl Med 55(7):1069–1074",{"doi":2264},"10.2967\u002Fjnumed.113.131631",{"id":20,"text":2266,"url":20,"identifiers":2267},"Fischer BM, Mortensen J, Langer SW, Loft A, Berthelsen AK, Daugaard G et al (2006) PET\u002FCT imaging in response evaluation of patients with small cell lung cancer. Lung Cancer 54(1):41–49",{"doi":2268},"10.1016\u002Fj.lungcan.2006.06.012",{"id":20,"text":2270,"url":20,"identifiers":2271},"Fu L, Zhu Y, Jing W, Guo D, Kong L, Yu J (2018) Incorporation of circulating tumor cells and whole-body metabolic tumor volume of (18)F-FDG PET\u002FCT improves prediction of outcome in IIIB stage small-cell lung cancer. 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Ann Nucl Med 32(3):165–174",{"doi":2280},"10.1007\u002Fs12149-018-1229-0",{"id":20,"text":2282,"url":20,"identifiers":2283},"Halvorsen TO, Herje M, Levin N, Bremnes RM, Brustugun OT, Flotten O et al (2016) Tumour size reduction after the first chemotherapy-course and outcomes of chemoradiotherapy in limited disease small-cell lung cancer. Lung Cancer 102:9–14",{"doi":2284},"10.1016\u002Fj.lungcan.2016.10.003",{"id":20,"text":2286,"url":20,"identifiers":2287},"Horn L, Mansfield AS, Szczesna A, Havel L, Krzakowski M, Hochmair MJ et al (2018) First-line Atezolizumab plus chemotherapy in extensive-stage small-cell lung cancer. N Engl J Med 379(23):2220-2229",{"doi":2288},"10.1056\u002FNEJMoa1809064",{"id":20,"text":2290,"url":20,"identifiers":2291},"Hoshikawa H, Kishino T, Mori T, Nishiyama Y, Yamamoto Y, Mori N (2013) The value of 18F-FLT PET for detecting second primary cancers and distant metastases in head and neck cancer patients. 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J Thorac Oncol 7(6):1015–1020",{"doi":2397},"10.1097\u002FJTO.0b013e31824fe90a",{"id":20,"text":2399,"url":20,"identifiers":2400},"Samarin A, Burger C, Wollenweber SD, Crook DW, Burger IA, Schmid DT et al (2012) PET\u002FMR imaging of bone lesions—implications for PET quantification from imperfect attenuation correction. Eur J Nucl Med Mol Imaging 39(7):1154–1160",{"doi":2401},"10.1007\u002Fs00259-012-2113-0",{"id":20,"text":2403,"url":20,"identifiers":2404},"Shen G, Jia Z, Deng H (2016) Apparent diffusion coefficient values of diffusion-weighted imaging for distinguishing focal pulmonary lesions and characterizing the subtype of lung cancer: a meta-analysis. Eur Radiol 26(2):556–566",{"doi":2405},"10.1007\u002Fs00330-015-3840-y",{"id":20,"text":2407,"url":20,"identifiers":2408},"Sohn HJ, Yang YJ, Ryu JS, Oh SJ, Im KC, Moon DH et al (2008) [18F] Fluorothymidine positron emission tomography before and 7 days after gefitinib treatment predicts response in patients with advanced adenocarcinoma of the lung. Clin Cancer Res 14(22):7423–7429",{"doi":2409},"10.1158\u002F1078-0432.CCR-08-0312",{"id":20,"text":2411,"url":20,"identifiers":2412},"Thureau S, Chaumet-Riffaud P, Modzelewski R, Fernandez P, Tessonnier L, Vervueren L et al (2013) Interobserver agreement of qualitative analysis and tumor delineation of 18F-fluoromisonidazole and 3′-deoxy-3′-18F-fluorothymidine PET images in lung cancer. 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Chest. 129(2):393–401",{"doi":2449},"10.1378\u002Fchest.129.2.393",{"id":20,"text":2451,"url":20,"identifiers":2452},"Yu J, Li W, Zhang Z, Yu T, Li D (2014) Prediction of early response to chemotherapy in lung cancer by using diffusion-weighted MR imaging. TheScientificWorldJournal. 2014:135841",{},{"id":2454,"createTime":2455,"updateTime":2455,"relativeEntities":2456,"slug":20,"properties":2457,"entityType":152,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":2466,"fullTextUrl":20,"authors":2467,"publicationType":212,"publisherRelationship":2617,"citationCount":20,"citationInfo":20,"publishDate":2649,"publishYear":521,"citationAnalyzeStatus":19,"lastCitationAnalyze":20,"indexDatabases":20,"openAccess":20,"references":20,"isForceReanalyzing":249},"3d160b7d-7682-40c4-be4b-a0cb6a6741da","2024-01-27T21:30:27.070+00:00",[],{"references":2458,"abstract":2460,"title":2462,"doi":2464},{"VOID":2459},"Anazodo UC, Farag A, Théberg J, Teuho J, Thompson RT, Teräs M, Taylor R, Butler J, Finger EC, Prato FS, Thiessen JD. (2016) Assessment of PET performance of a 32-Channel MR Brain Array Head Coil Compatible with PET for Integrated PET-MRI. Preceding PSMR conference Cologne, Germany.\nCamici PG, Prasad SK, Rimoldi OE (2008) Stunning, hibernation, and assessment of myocardial viability. Circulation 117(1):103–114\nCarney JP, Townsend DW, Rappoport V, Bendriem B (2006) Method for transforming CT images for attenuation correction in PET\u002FCT imaging. Am Assoc Phys Med 33(4):976–983\nCatana C, Drzezga A, Heiss WD, Rosen BR (2012) PET\u002FMRI for neurologic applications. J Nucl Med 53:1916–1925\nDregely I, Lanz T, Metz S, Mueller MF, Kuschan M, Nimbalkar M, Bundschuh RA, Ziegler SI, Haase A, Nekolla SG (2014) A 16-channel MR coil for simultaneous PET\u002FMR imaging in breast cancer. Eur Soc Radiol 25:1154–1161\nEldib M, Bini J, Robson P, Calcagno C, Faul D, Tsoumpas C, Fayad ZA (2015) Markerless attenuation correction for carotid MRI surface receiver coils in combined PET\u002FMR imaging. Phys Med Biol 60(12):4705\nFerguson A, McConathy J, Su Y, Hewing D, Laforest R (2014) Attenuation effects of MR headphones during brain PET\u002FMR studies. J Nucl Med Technol 42:93–100\nFrohwein LJ, Heß M, Schlicher D, Bolwin K, Büther F, Jiang X, Schäfers K (2018) PET attenuation correction for flexible MRI surface coils in hybrid PET\u002FMRI using a 3D depth camera. Phys Med Biol 63(2):025033\nFürst S, Souvatzoglou M, Martinez-Möller A, Nekolla S, Schwaiger M, Ziegler S. (2012). Impact of MRI surface coils on quantification in integrated PET\u002FMR. The Journal of Nuclear Medicine 53(supplement 1), 436.\nGriswold MA, Jakob PM, Heidemann RM, Nittka M, Jellus V, Wang J, Kiefer B, Haase A (2002) Generalized autocalibrating partially parallel acquisitions (GRAPPA). Magn Reson Med 47(6):1202–1210\nHaacke EM, Wielopolski PA, Tkach JA & Modic MT. (1990). Steady-state free precession imaging in the presence of motion: application for improved visualization of the cerebrospinal fluid. 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Magn Reson Med 63(2):456–464\nNensa F, Bamberg F, Rischpler C, Menezes L, Poeppel TD, Fougère CL, Beitzke D, Rasul S, Loewe C, Nikolaou K, Bucerius J, Kjaer A, Gutberlet M, Prakken NH, Vliegenthart R, Slart RHJA, Nekolla SG, Lassen ML, Pichler BJ, Schlosser T, Jacquier A, Quick HH, Schäfers M, Hacker M, Francone M, Bremerich J, Natale L, Wildberger J, Sinitsyn V, Hyafil F, Verberne HJ, Sciagrà R, Gimelli A, Übleis C, Lindner O, On Behalf of the European Society of Cardiovascular, R. & The European Association of Nuclear Medicine Cardiovascular, C (2018) Hybrid cardiac imaging using PET\u002FMRI: a joint position statement by the European Society of Cardiovascular Radiology (ESCR) and the European Association of Nuclear Medicine (EANM). Eur J Hybrid Imaging 2(1):14\nNensa F, Beiderwellen K, Heusch P, Wetter A (2014) Clinical applications of PET\u002FMRI: current status and future perspectives. 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MAGMA 26(1):99–113\nWhite JA, Rajchl M, Butler J, Thompson RT, Prato FS, Wisenberg G (2013) Active cardiac sarcoidosis first clinical experience of simultaneous positron emission tomography–magnetic resonance imaging for the diagnosis of cardiac disease. Circulation 127(22):e639–e641\nWiggins G, Triantafyllou C, Potthast A, Reykowski A, Nittka M, Wald L (2006) 32-channel 3 tesla receive-only phased-array head coil with soccer-ball element geometry. Magn Reson Med 56(1):216–223\nWintersperger BJ, Reeder SB, Nikolaou K, Dietrich O, Huber A, greiser A, LANZ T, Reiser MF, Schoenberg SO (2006) Cardiac CINE MR imaging with a 32-channel cardiac coil and parallel imaging: impact of acceleration factors on image quality and volumetric accuracy. J Magn Reson Imaging 23(2):222–227",{"EN":2461},"Cardiovascular imaging using hybrid positron emission tomography (PET) and magnetic resonance imaging (MRI) requires a radio frequency phased array resonator capable of high acceleration factors in order to achieve the shortest breath-holds while maintaining optimal MRI signal-to-noise ratio (SNR) and minimum PET photon attenuation. To our knowledge, the only two arrays used today for hybrid PET\u002FMRI cardiovascular imaging are either incapable of achieving high acceleration or affect the PET photon count greatly. This study is focused on the evaluation of the MRI performance of a novel third-party prototype 32-channel phased array designed for simultaneous PET\u002FMRI cardiovascular imaging. The study compares the quality parameters of MRI parallel imaging, such as g-factor, noise correlation coefficients, and SNR, to the conventional arrays (mMR 12-channel and MRI-only 32-channel) currently used with hybrid PET\u002FMRI systems. The quality parameters of parallel imaging were estimated for multiple acceleration factors on a phantom and three healthy volunteers. Using a Germanium-68 (Ge-68) phantom, preliminary measurements of PET photon attenuation caused by the novel array were briefly compared to the photon counts produced from no-array measurements. The global mean of the g-factor and SNRg produced by the novel 32-channel PET\u002FMRI array were better than those produced by the MRI-only 32-channel array by 5% or more. The novel array has resulted in MRI SNR improvements of > 30% at all acceleration factors, in comparison to the mMR12-channel array. Preliminary evaluation of PET transparency showed less than 5% photon attenuation caused by both anterior and posterior parts of the novel array. The MRI performance of the novel PET\u002FMRI 32-channel array qualifies it to be a viable alternative to the conventional arrays for cardiovascular hybrid PET\u002FMRI. A detailed evaluation of the novel array’s PET performance remains to be conducted, but cursory assessment promises significantly reduced attenuation.",{"EN":2463},"Assessment of a novel 32-channel phased array for cardiovascular hybrid PET\u002FMRI imaging: MRI performance",{"VOID":2465},"10.1186\u002Fs41824-019-0061-7","https:\u002F\u002Fejhi.springeropen.com\u002Farticles\u002F10.1186\u002Fs41824-019-0061-7",[2468,2483,2505,2536,2572,2584],{"id":2469,"sortIndex":175,"researcher":20,"roles":2470,"affiliations":2471,"properties":2480},"f3886914-88a1-45d1-bc92-0f23031129ee",[160],[2472],{"id":20,"sortIndex":21,"affiliation":2473,"properties":20},{"id":2474,"createTime":2475,"updateTime":2475,"relativeEntities":2476,"slug":20,"properties":2477,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"4e45b705-4354-4ed2-9665-f971ffe771fa","2024-01-27T21:30:27.180+00:00",[],{"title":2478},{"VI":2479},"Lawson Health Research Institute, Imaging Division, London, Canada",{"title":2481},{"VI":2482},"John Butler",{"id":2484,"sortIndex":188,"researcher":20,"roles":2485,"affiliations":2486,"properties":2502},"ab381a8a-a6e2-487a-aa86-39ecdcc477db",[160],[2487,2492],{"id":20,"sortIndex":21,"affiliation":2488,"properties":20},{"id":2474,"createTime":2475,"updateTime":2475,"relativeEntities":2489,"slug":20,"properties":2490,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":2491},{"VI":2479},{"id":2493,"sortIndex":188,"affiliation":2494,"properties":2501},"13d4d1c6-9164-405b-93c9-4dbcd0c77870",{"id":2495,"createTime":2496,"updateTime":2496,"relativeEntities":2497,"slug":20,"properties":2498,"entityType":65,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"14fb12be-b415-4b93-af25-55d40da3f199","2024-01-17T14:15:47.486+00:00",[],{"title":2499},{"VI":2500},"Department of Medical Biophysics, Western University, London, Canada",{},{"title":2503},{"VI":2504},"R. 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Int J Cardiol 167(5):1737–1749\nBernacki GM, Bahrainy S, Caldwell JH, Levy WC, Link JM, Stratton JR (2016) Assessment of the effects of age, gender, and exercise training on the cardiac sympathetic nervous system using positron emission tomography imaging. J Gerontol A Biol Sci Med Sci 71(9):1195–1201\nCzernin J, Muller P, Chan S, Brunken RC, Porenta G, Krivokapich J et al (1993) Influence of age and hemodynamics on myocardial blood flow and flow reserve. Circulation 88(1):62–69\nDorbala S, Di Carli MF (2014) Cardiac PET perfusion: prognosis, risk stratification, and clinical management. Semin Nucl Med 44(5):344–357\nGould KL, Johnson NP, Bateman TM, Beanlands RS, Bengel FM, Bober R et al (2013) Anatomic versus physiologic assessment of coronary artery disease. Role of coronary flow reserve, fractional flow reserve, and positron emission tomography imaging in revascularization decision-making. J Am Coll Cardiol 62(18):1639–1653\nHutchins GD, Schwaiger M, Rosenspire KC, Krivokapich J, Schelbert H, Kuhl DE (1990) Noninvasive quantification of regional blood flow in the human heart using N-13 ammonia and dynamic positron emission tomographic imaging. J Am Coll Cardiol 15(5):1032–1042\nJuarez-Orozco LE, Alexanderson E, Dierckx RA, Boersma HH, Hillege JL, Zeebregts CJ, et al (2016) Stress myocardial blood flow correlates with ventricular function and synchrony better than myocardial perfusion reserve: a nitrogen-13 ammonia PET study. J Nucl Cardiol. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs12350-016-0669-y\nJuneau D, Erthal F, Ohira H, Mc Ardle B, Hessian R, deKemp RA et al (2016) Clinical PET myocardial perfusion imaging and flow quantification. Cardiol Clin 34(1):69–85\nKan H, Knol RJ, Lazarenko SV, Wondergem M, van der Zant FM (2016) Occurrence of typical perfusion defects attributed to jailed or occluded side branch after ramus descendens anterior stenting in a patient cohort referred for 13NH3 myocardial PET\u002FCT. Nucl Med Commun 37(5):480–486\nKawaguchi N, Okayama H, Kawamura G, Shigematsu T, Takahashi T, Kawada Y et al (2017) Clinical usefulness of coronary flow reserve ratio for the detection of significant coronary artery disease on (13)N-ammonia positron emission tomography. Circ J\nLazarenko SV, Knol RJ, Doodeman PA, Bruin VS, Pan XB, Declerck JM et al (2014) Validation of a fast 20 min two scans protocol for quantitative 13N-ammonia myocardial perfusion PET. Eur J Nucl Med Mol Imaging 41(Suppl 2):S169\nMarinescu MA, Loffler AI, Ouellette M, Smith L, Kramer CM, Bourque JM (2015) Coronary microvascular dysfunction, microvascular angina, and treatment strategies. JACC Cardiovasc Imaging 8(2):210–220\nMarkousis-Mavrogenis G, Juarez-Orozco LE, Alexanderson E (2017) Residual activity correction in quantitative myocardial perfusion 13N-ammonia PET imaging: a study in post-MI patients. Hell J Cardiol 58:245\nMarques AA, Bevilaqua MC, da Fonseca AM, Nardi AE, Thuret S, Dias GP (2016) Gender differences in the neurobiology of anxiety: focus on adult hippocampal neurogenesis. Neural Plast 2016:5026713\nMerhige ME, Breen WJ, Shelton V, Houston T, D'Arcy BJ, Perna AF (2007) Impact of myocardial perfusion imaging with PET and (82)Rb on downstream invasive procedure utilization, costs, and outcomes in coronary disease management. J Nucl Med 48(7):1069–1076\nNesterov SV, Juárez-Orozco LE, Knol RJ, Sciagrà R, Slomka P, Alessio A et al (2017) AMMO-X: a cross-comparison study of 13N-ammonia PET MPQ software tools. Eur J Nucl Med Mol Imaging 44(Suppl 2):S299–S300\nTask Force Members, Montalescot G, Sechtem U, Achenbach S, Andreotti F, Arden C et al (2013) 2013 ESC guidelines on the management of stable coronary artery disease: the task force on the management of stable coronary artery disease of the European Society of Cardiology. Eur Heart J 34(38):2949–3003",{"EN":2658},"Cardiac imaging by means of myocardial Positron Emission Tomography\u002FComputed Tomography (PET\u002FCT) is being used increasingly to assess coronary artery disease, to guide revascularization decisions with more accuracy, and it allows robust quantitative analysis of both regional myocardial blood flow (MBF) and myocardial flow reserve (MFR). Recently, a more time-efficient protocol has been developed in combination with a residual activity correction algorithm in which a stress acquisition is performed directly after completion of the rest acquisition to subtract remaining myocardial radioactivity. The objective of this study is to define flow values of myocardial blood flow (MBF) and Myocardial Flow Reserve (MFR) with 13N–ammonia (13NH3) myocardial perfusion PET\u002FCT on patients without coronary artery disease using a time-efficient protocol, since reference values for this particular type of study are lacking in literature. In addition, we aim to determine the effect of the residual activity correction algorithm in this time-efficient protocol. A mean MBF in rest of 1.02 ± 0.22 ml\u002Fg\u002Fmin, a mean MBF in stress of 2.54 ± 0.41 ml\u002Fg\u002Fmin with a mean MFR of 2.60 ± 0.61 were measured. Female patients had a significant higher MBF in rest and stress, but lower MFR; a small but significant negative correlation was measured between age and MBF in stress and MFR. Residual activity correction had a significant effect resulting in a difference in global stress MBF before and after correction of 0.39 ± 0.13 ml\u002Fg\u002Fmin. This study established flow values for 13NH3 myocardial PET\u002FCT with a time-efficient protocol, and established that MBF in stress corrected for residual activity is comparable with known reference values in normal studies without temporal overlap. Further validation of the technique could be of value, e.g. by comparison to standard imaging without temporal overlap, or validation against catheterization results.",{"EN":2660},"Myocardial blood flow and myocardial flow reserve values in 13N–ammonia myocardial perfusion PET\u002FCT using a time-efficient protocol in patients without coronary artery 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