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Hình ảnh cộng hưởng từ (MR) 1H gián tiếp của nước gắn nhãn 17O cho phép hình ảnh hóa những thay đổi động học trong sự phân chia nước trong cơ thể sống. Mục tiêu của chúng tôi là mô tả tính khả thi của các phương pháp MR 1H gián tiếp để đánh giá ảnh hưởng của H217O lên các tỷ lệ hồi phục MR bằng cách sử dụng thiết bị 3-T thông thường và các tỷ lệ hồi phục theo voxel. Hình ảnh MR đã được sử dụng để tính toán các tỷ lệ hồi phục R1, R2 và R2* trong các mô hình (19 lọ với nồng độ H217O khác nhau, dao động từ 0,039 đến 5,5%). Sau đó, một nghiên cứu thí nghiệm trên động vật (8 con chuột) đã được thiết kế để đánh giá những thay đổi động học R2 tương đối trong não liên quan đến việc tiêm tĩnh mạch nước gắn nhãn 17O ở chuột. Không có sự thay đổi đáng kể nào đối với các giá trị R1 và R2* từ các mô hình. Giá trị R2 đạt được với chuỗi T2-weighted turbo spin-echo với khoảng thời gian hồi âm 20 ms cho thấy sự khác biệt thống kê cao hơn (0.67 s−1, khoảng interquartile 0.34, p < 0.001) và tương quan Spearman (rho 0.79). Sự gia tăng R2 được điều chỉnh theo một đường thẳng giữa 0,25 và 5,5%, được đại diện bằng phương trình R2 = 0.405 nồng độ + 0.3215. Sự khác biệt đáng kể nhất được ghi nhận cho các nồng độ cao hơn (3,1–5,5%). Thí nghiệm MR trên não chuột cho thấy sự thay đổi trung bình 10% trong giá trị R2 sau khi tiêm H217O với sự bình thường hóa tiến triển. Phương pháp hình ảnh MR 1H gián tiếp có khả năng đo nồng độ H217O bằng việc sử dụng các giá trị R2 và thiết bị MR 3-T thông thường. Sự thay đổi động học R2 tương đối đã được bình thường hóa sau khi tiêm tĩnh mạch dung dịch saline H217O mở ra cơ hội độc đáo để lập bản đồ sinh lý bệnh nước trong cơ thể sống, mở ra việc phân tích trạng thái và sự thay đổi của aquaporins do bệnh tật tại các máy quét MR proton 3-T có sẵn lâm sàng.

To investigate the influence of iodinated contrast medium (ICM) on detection of monosodium urate (MSU) with dual-energy computed tomography (DECT) in two types of phantoms and demonstrate an example patient for clinical illustration. Approval is by the institutional review board, and written informed consent was obtained. A grid-like and a biophantom with 25 suspensions containing different concentrations of ICM (0 to 2%) and MSU (0 to 50%) were prepared and scanned with sequential single-source DECT using established methodology. Ascending orders of tube currents were applied at 80 kVp (16.5 to 220.0 mAs) and 135 kVp (2.75 to 19.25 mAs). Volume and mass measurements were performed using clinical gout software (dual-energy decomposition analysis). Numbers of true-positive and false-positive MSU detections were recorded and compared for different ICM concentrations. We demonstrate a patient with gouty arthritis for clinical illustration. Effects of ICM on MSU detection varied with the amount of iodine. Lower ICM concentrations (0.25 and 0.50%) improved detection of small uric acid concentrations of 35 to 45% in comparison to scans without ICM. However, high ICM concentrations (1 and 2%) almost completely precluded MSU detection for all MSU concentrations investigated. In a patient with gouty arthritis, tophi in the wrist were only detected after intravenous ICM administration. Exploring multimodal DECT for arthritis imaging, enhancement of ICM influences tophus detection. It can help in visualizing previously undetected MSU depositions but, with too strong enhancement, also obscure tophi. Use of iodinated contrast media in dual-energy CT might help in visualizing previously undetected uric acid depositions but, with too strong enhancement, obscure gouty tophi. • Iodine significantly influences the uric acid crystal detection in systematic phantom studies. • Lower iodine concentrations improved detection of low and medium uric acid concentrations. • High concentrations of iodine hampered detection of all uric acid concentrations.

We investigated the relationship of two commonly used quantitative ultrasound (QUS) parameters, speed of sound (SoS) and attenuation coefficient (α), with water and macromolecular contents of bovine cortical bone strips as measured with ultrashort echo time (UTE) magnetic resonance imaging (MRI). SoS and α were measured in 36 bovine cortical bone strips utilizing a single-element transducer with nominal 5 MHz center frequency based on the time of flight principles after accommodating for reflection losses. Specimens were then scanned using UTE MRI to measure total, bound, and pore water proton density (TWPD, BWPD, and PWPD) as well as macromolecular proton fraction and macromolecular transverse relaxation time (T2-MM). Specimens were also scanned using microcomputed tomography (μCT) at 9-μm isometric voxel size to measure bone mineral density (BMD), porosity, and pore size. The elastic modulus (E) of each specimen was measured using a 4-point bending test. α demonstrated significant positive Spearman correlations with E (R = 0.69) and BMD (R = 0.44) while showing significant negative correlations with porosity (R = -0.41), T2-MM (R = -0.47), TWPD (R = -0.68), BWPD (R = -0.67), and PWPD (R = -0.45). The negative correlation between α and T2-MM is likely indicating the relationship between QUS and collagen matrix organization. The higher correlations of α with BWPD than with PWPD may indicate that water organized in finer structure (bound to matrix) provides lower acoustic impedance than water in larger pores, which is yet to be investigated thoroughly. This study highlights the importance of future investigations exploring the relationship between QUS measures and all major components of the bone, including the collagenous matrix and water. Investigating the full potential of QUS and its validation facilitates a more affordable and accessible tool for bone health monitoring in clinics. • Ultrasound attenuation demonstrated significant positive correlations with bone mechanics and mineral density. • Ultrasound attenuation demonstrated significant negative correlations with porosity and bone water contents. • This study highlights the importance of future investigations exploring the relationship between QUS measures and all major components of the bone.

The advent of precision medicine, increasing clinical needs, and imaging availability among many other factors in the prostate cancer diagnostic pathway has engendered the utilization of artificial intelligence (AI). AI carries a vast number of potential applications in every step of the prostate cancer diagnostic pathway from classifying/improving prostate multiparametric magnetic resonance image quality, prostate segmentation, anatomically segmenting cancer suspicious foci, detecting and differentiating clinically insignificant cancers from clinically significant cancers on a voxel-level, and classifying entire lesions into Prostate Imaging Reporting and Data System categories/Gleason scores. Multiple studies in all these areas have shown many promising results approximating accuracies of radiologists. Despite this flourishing research, more prospective multicenter studies are needed to uncover the full impact and utility of AI on improving radiologist performance and clinical management of prostate cancer. In this narrative review, we aim to introduce emerging medical imaging AI paper quality metrics such as the Checklist for Artificial Intelligence in Medical Imaging (CLAIM) and Field-Weighted Citation Impact (FWCI), dive into some of the top AI models for segmentation, detection, and classification.

Body composition is associated with survival outcome in oncological patients, but it is not routinely calculated. Manual segmentation of subcutaneous adipose tissue (SAT) and muscle is time-consuming and therefore limited to a single CT slice. Our goal was to develop an artificial-intelligence (AI)-based method for automated quantification of three-dimensional SAT and muscle volumes from CT images. Ethical approvals from Gothenburg and Lund Universities were obtained. Convolutional neural networks were trained to segment SAT and muscle using manual segmentations on CT images from a training group of 50 patients. The method was applied to a separate test group of 74 cancer patients, who had two CT studies each with a median interval between the studies of 3 days. Manual segmentations in a single CT slice were used for comparison. The accuracy was measured as overlap between the automated and manual segmentations. The accuracy of the AI method was 0.96 for SAT and 0.94 for muscle. The average differences in volumes were significantly lower than the corresponding differences in areas in a single CT slice: 1.8% versus 5.0% (p < 0.001) for SAT and 1.9% versus 3.9% (p < 0.001) for muscle. The 95% confidence intervals for predicted volumes in an individual subject from the corresponding single CT slice areas were in the order of ± 20%. The AI-based tool for quantification of SAT and muscle volumes showed high accuracy and reproducibility and provided a body composition analysis that is more relevant than manual analysis of a single CT slice.

Vascular interventions imply radiation exposure to the operating physician (OP). To reduce radiation exposure, we propose a novel passive robotic device for fluoroscopy-guided arterial puncturing. X-ray dose rates were measured for a total of 30 fluoroscopy-guided puncture femoral arteries in 15 pigs. Fifteen punctures were performed with the device while the other 15 were performed without the device by an interventional cardiologist with 10 years of experience. Parametric t test was used. The success rate with the device was 100%. Overall, the OP received more radiation (0.41 mSv/h) as compared to the assistant (0.06 mSv/h) (p <  0.001) and, amongst OP’s body parts, hands received more radiation than other body parts (p <  0.001). The radiation dose rate to the OP’s hands during arterial puncturing performed manually without the device was 0.95 ± 0.25 mSv/h whereas it was 0.14 ± 0.006 mSv/h using the device, resulting in an 85% reduction (p <  0.001). For the head, the dose was reduced from 0.16 mSv/h to 0.08 mSv/h (50% reduction, p <  0.001), and for the dominant arm, from 0.12 mSv/h to 0.07 mSv/h (42% reduction, p <  0.001). The fluoroscopy time was reduced from 4.5 ± 0.15 min to 4.3 ± 0.11 min device (p = 0.002). In a swine model, fluoroscopy time and radiation exposure for the OP puncturing femoral artery were significantly reduced by using the passive robotic device.

Radiation dose in computed tomography (CT) has become a topic of high interest due to the increasing numbers of CT examinations performed worldwide. Hence, dose tracking and organ dose calculation software are increasingly used. We evaluated the organ dose variability associated with the use of different software applications or calculation methods. We tested four commercial software applications on CT protocols actually in use in our hospital: CT-Expo, NCICT, NCICTX, and Virtual Dose. We compared dose coefficients, estimated organ doses and effective doses obtained by the four software applications by varying exposure parameters. Our results were also compared with estimates reported by the software authors. All four software applications showed dependence on tube voltage and volume CT dose index, while only CT-Expo was also dependent on other exposure parameters, in particular scanner model and pitch caused a variability till 50%. We found a disagreement between our results and those reported by the software authors (up to 600%), mainly due to a different extent of examined body regions. The relative range of the comparison of the four software applications was within 35% for most organs inside the scan region, but increased over the 100% for organs partially irradiated and outside the scan region. For effective doses, this variability was less evident (ranging from 9 to 36%). The two main sources of organ dose variability were the software application used and the scan region set. Dose estimate must be related to the process used for its calculation.

To study hippocampus subfield volumes in patients after microsurgical clipping (MC) and/or endovascular coiling (EC) of intracranial aneurysms. Hippocampus subfield volumetry was performed using FreeSurfer v6.0 in 51 patients (35 females, mean age 54.9 ± 11.9 years, range 24–78 years). Visual inspection of image and segmentation quality was performed prior to statistical analyses. Multiple regression analysis, controlled for age, sex, and side of treatment, was used to assess the impact of prior MC and history of subarachnoid haemorrhage (SAH) on hippocampus subfield volumes (cornu ammonis (CA)-2/3, CA-4, subiculum). Partial correlation analyses were used to assess effect of multiple treatments on hippocampus subfield volumes. Prior MC was significantly associated with lower hippocampal subfield volumes in MC patients for right and left CA-2/3 (β = -22.32 [-40.18, -4.45]; p = 0.016 and β = -20.03 [-39.38, -0.68]; p = 0.043) and right CA-4 (β = -17.00 [-33.86, 0.12]; p = 0.048). History of SAH was not significantly associated with hippocampal subfield volumes. We observed a higher disease burden in the MC cohort. The number of aneurysms correlated with right-sided hippocampal subfield volumes while the number of treatment interventions did not. In this explorative study, we found that history of MC was significantly associated with lower volumes in distinct hippocampal subfields, which may be a consequence of a more extensive treatment. This could indicate specific atrophy of CA-2/3 after MC and should motivate hippocampal subfield assessment in larger cohorts.

Among the various stem cell populations used for cell therapy, adult mesenchymal stromal cells (MSCs) have emerged as a major new cell technology. These cells must be tracked after transplantation to monitor their migration within the body and quantify their accumulation at the target site. This study assessed whether rat bone marrow MSCs can be labelled with superparamagnetic iron oxide (SPIO) nanoparticles and perfluorocarbon (PFC) nanoemulsion formulations without altering cell viability and compared magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) results from iron-labelled and fluorine-labelled MSCs, respectively. Of MSCs, 2 × 106 were labelled with Molday ION Rhodamine-B (MIRB) and 2 × 106 were labelled with Cell Sense. Cell viability was evaluated by trypan blue exclusion method. Labelled MSCs were divided into four samples containing increasing cell numbers (0.125 × 106, 0.25 × 106, 0.5 × 106, 1 × 106) and scanned on a 7T MRI: for MIRB-labelled cells, phantoms and cells negative control, T1, T2 and T2* maps were acquired; for Cell Sense labelled cells, phantoms and unlabelled cells, a 19F non-localised single-pulse MRS sequence was acquired. In total, 86.8% and 83.6% of MIRB-labelled cells and Cell Sense-labelled cells were viable, respectively. MIRB-labelled cells were visible in all samples with different cell numbers; pellets containing 0.5 × 106 and 1 × 106 of Cell Sense-labelled cells showed a detectable 19F signal. Our data support the use of both types of contrast material (SPIO and PFC) for MSCs labelling, although further efforts should be dedicated to improve the efficiency of PFC labelling.