Using radiomics for predicting the HPV status of oropharyngeal tumors

Journal of Engineering and Applied Science - 2024
Kamil Saraç1, Albert Güveniş1
1Institute of Biomedical Engineering, Bogazici University, Istanbul, Turkey

Tóm tắt

AbstractKnowing human papillomavirus (HPV) status has important consequences for treatment selection in oropharyngeal cancer. The gold standard is to perform a biopsy. The objective of this paper is to develop a new computed tomography (CT) radiomics-based non-invasive solution to HPV status determination and investigate if and how it can be a viable and accurate complementary technique. Two hundred thirty-eight patients’ CT scans were normalized and resampled. One thousand one hundred forty-two radiomics features were obtained from the segmented CT scans. The number of radiomic attributes was decreased by applying correlation coefficient analysis, backward elimination, and random forest feature importance analysis. Random over-sampling (ROSE) resampling algorithm was performed on the training set for data balancing, and as a result, 161 samples were obtained for each of the HPV classes of the training set. A random forest (RF) classification algorithm was used as a prediction model using five-fold cross-validation (CV). Model effectiveness was evaluated on the unused 20% of the imbalanced data. The applicability of the model was investigated based on previous research and error rates reported for biopsy procedures. The HPV status was determined with an accuracy of 91% (95% CI 83–99) and an area under the curve (AUC) of 0.77 (95% CI 65–89) on the test data. The error rates were comparable to those encountered in biopsy. As a conclusion, radiomics has the potential to predict HPV status with accuracy levels that are comparable to biopsy. Future work is needed to improve standardization, interpretability, robustness, and reproducibility before clinical translation.

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Tài liệu tham khảo

Rettig EM, D’Souza G (2015) Epidemiology of head and neck cancer. Surg Oncol Clin N Am 24:379–396. https://doi.org/10.1016/j.soc.2015.03.001

Marur S, Forastiere AA (2008) Head and neck cancer: changing epidemiology, diagnosis, and treatment. Mayo Clin Proc 83:489–501. https://doi.org/10.4065/83.4.489

Cohen N, Fedewa S, Chen AY (2018) Epidemiology and demographics of the head and neck cancer population. Oral Maxillofac Surg Clin North Am 30:381–395. https://doi.org/10.1016/j.coms.2018.06.001

Mahmood H, Shaban M, Rajpoot N, Khurram SA (2021) Artificial Intelligence-based methods in head and neck cancer diagnosis: an overview. Br J Cancer 124:1934–1940. https://doi.org/10.1038/s41416-021-01386-x

Tanaka TI, Alawi F (2018) Human papillomavirus and oropharyngeal cancer. Dent Clin North Am 62:111–120. https://doi.org/10.1016/j.cden.2017.08.008

Evaluating the incidence of HPV-positive/-negative, according to NCCN guidelines. https://www.targetedonc.com/view/evaluating-the-incidence-of-hpv-positive--negative-according-to-nccn-guidelines. Accessed 14 Dec 2023

Chow LQM (2020) Head and neck cancer. N Engl J Med 382(1):60–72. https://doi.org/10.1056/nejmra1715715

Avery EW, Joshi K, Mehra S, Mahajan A (2023) Role of PET/CT in oropharyngeal cancers. Cancers 15(9):2651. https://doi.org/10.3390/cancers15092651

Rischin D, Young RJ, Fisher R, Fox SB, Le Q-T, Peters LJ, Solomon B, Choi J, O’Sullivan B, Kenny LM, McArthur GA (2010) Prognostic significance of p16ink4a and human papillomavirus in patients with oropharyngeal cancer treated on Trog 02.02 Phase III trial. J Clin Oncol 28(27):4142–4148. https://doi.org/10.1200/jco.2010.29.2904

Perri F, Longo F, Caponigro F, Sandomenico F, Guida A, Della Vittoria Scarpati G, Ottaiano A, Muto P, Ionna F (2020) Management of HPV-related squamous cell carcinoma of the head and neck: pitfalls and caveat. Cancers 12(4):975. https://doi.org/10.3390/cancers12040975

Zakeri K, Dunn L, Lee N (2021) HPV-associated oropharyngeal cancer de-escalation strategies and trials: past failures and future promise. J Surg Oncol 124(6):962–966. https://doi.org/10.1002/jso.26696

Kimple RJ, Harari PM (2014) Is radiation dose reduction the right answer for HPV-positive head and neck cancer? Oral Oncol 50(6):560–564. https://doi.org/10.1016/j.oraloncology.2013.09.015

Bonilla-Velez J, Mroz EA, Hammon RJ, Rocco JW (2013) Impact of human papillomavirus on oropharyngeal cancer biology and response to therapy. Otolaryngol Clin North Am 46(4):521–543. https://doi.org/10.1016/j.otc.2013.04.009

Dermody, S. M., Haring, C. T., Bhambhani, C., Tewari, M., Brenner, J. C., & Swiecicki, P. L. (2021). Surveillance and monitoring techniques for HPV-related head and neck squamous cell carcinoma: circulating tumor DNA. Current Treatment Options in Oncology, 22(3). https://doi.org/10.1007/s11864-021-00821-8

Alam S, Chaurasia A, Singh N (2021) Oral cancer diagnostics: an overview. Nat J Maxillofacial Surg 12(3):324. https://doi.org/10.4103/njms.njms_130_20

Sciubba JJ (2001) Oral cancer. Am J Clin Dermatol 2(4):239–251. https://doi.org/10.2165/00128071-200102040-00005

Macey, R., Walsh, T., Brocklehurst, P., Kerr, A. R., Liu, J. L., Lingen, M. W., Ogden, G. R., Warnakulasuriya, S., & Scully, C. (2015). Diagnostic tests for oral cancer and potentially malignant disorders in patients presenting with clinically evident lesions. Cochrane Database Syst Rev. https://doi.org/10.1002/14651858.cd010276.pub2

Cohan DM, Popat S, Kaplan SE, Rigual N, Loree T, Hicks WL Jr (2009) Oropharyngeal cancer: current understanding and management. Curr Opin Otolaryngol Head Neck Surg 17(2):88–94. https://doi.org/10.1097/moo.0b013e32832984c0

Tshering Vogel, D. W., Zbaeren, P., & Thoeny, H. C. (2010). Cancer of the oral cavity and oropharynx. Cancer Imaging, 10(1). https://doi.org/10.1102/1470-7330.2010.0008

Yang G, Wei L, Thong BK, Fu Y, Cheong IH, Kozlakidis Z, Li X, Wang H, Li X (2022) A systematic review of oral biopsies, sample types, and detection techniques applied in relation to oral cancer detection. Biotech 11:5. https://doi.org/10.3390/biotech11010005

Hoffmann M, Tribius S (2019) HPV and oropharyngeal cancer in the eighth edition of the TNM classification: pitfalls in practice. Transl Oncol 12:1108–1112. https://doi.org/10.1016/j.tranon.2019.05.009

Liu Z, Wang S, Dong D, Wei J, Fang C, Zhou X, Sun K, Li L, Li B, Wang M, Tian J (2019) The applications of radiomics in precision diagnosis and treatment of oncology: opportunities and challenges. Theranostics 9:1303–1322. https://doi.org/10.7150/thno.30309

van Timmeren JE, Cester D, Tanadini-Lang S, Alkadhi H, Baessler B (2020) Radiomics in medical imaging—“how-to” guide and critical reflection. Insights into Imaging.https://doi.org/10.1186/s13244-020-00887-2

Abdollahi H, Chin E, Clark H, Hyde DE, Thomas S, Wu J, Uribe CF, Rahmim A (2022) Radiomics-guided radiation therapy: opportunities and challenges. Phys Med Biol. https://doi.org/10.1088/1361-6560/ac6fab

Rich B, Huang J, Yang Y, Jin W, Johnson P, Wang L, Yang F (2021) Radiomics predicts for distant metastasis in locally advanced human papillomavirus-positive oropharyngeal squamous cell carcinoma. Cancers 13:5689. https://doi.org/10.3390/cancers13225689

Scheckenbach K (2018) Radiomics: big data Statt Biopsie in der Zukunft? Laryngo-Rhino-Otologie. https://doi.org/10.1055/s-0043-121964

Gillies RJ, Kinahan PE, Hricak H (2016) Radiomics: images are more than pictures, they are data. Radiology 278:563–577. https://doi.org/10.1148/radiol.2015151169

Lambin P, Rios-Velazquez E, Leijenaar R, Carvalho S, van Stiphout RGPM, Granton P, Zegers CML, Gillies R, Boellard R, Dekker A, Aerts HJWL (2012) Radiomics: extracting more information from medical images using advanced feature analysis. Eur J Cancer 48:441–446. https://doi.org/10.1016/j.ejca.2011.11.036

Tortora M, Gemini L, Scaravilli A, Ugga L, Ponsiglione A, Stanzione A, D’Arco F, D’Anna G, Cuocolo R (2023) Radiomics applications in head and neck tumor imaging: a narrative review. Cancers 15:1174. https://doi.org/10.3390/cancers15041174

Spadarella G, Ugga L, Calareso G, Villa R, D’Aniello S, Cuocolo R (2022) The impact of radiomics for human papillomavirus status prediction in oropharyngeal cancer: systematic review and Radiomics Quality Score Assessment. Neuroradiology 64:1639–1647. https://doi.org/10.1007/s00234-022-02959-0

Bos P, Brekel MW, Gouw ZA, Al-Mamgani A, Waktola S, Aerts HJ, Beets-Tan RG, Castelijns JA, Jasperse B (2020) Clinical variables and magnetic resonance imaging-based radiomics predict human papillomavirus status of oropharyngeal cancer. Head Neck 43:485–495. https://doi.org/10.1002/hed.26505

Zhinan L, Wei Z, Yudi Y, Yabing D, Yuanzhe X, Xiulan L (2022) Prediction of HPV status in oropharyngeal squamous cell carcinoma based on radiomics and machine learning algorithms: a multi-cohort study. https://doi.org/10.21203/rs.3.rs-1841205/v1

Suh CH, Lee KH, Choi YJ, Chung SR, Baek JH, Lee JH, Yun J, Ham S, Kim N (2020) Oropharyngeal squamous cell carcinoma: radiomic machine-learning classifiers from multiparametricmr images for determination of HPV infection status. Sci Rep. https://doi.org/10.1038/s41598-020-74479-x

Boot PA, Mes SW, de Bloeme CM, Martens RM, Leemans CR, Boellaard R, van de Wiel MA, de Graaf P (2023) Magnetic resonance imaging based radiomics prediction of human papillomavirus infection status and overall survival in oropharyngeal squamous cell carcinoma. Oral Oncol 137:106307. https://doi.org/10.1016/j.oraloncology.2023.106307

Song B, Yang K, Garneau J, Lu C, Li L, Lee J, Stock S, Braman NM, Koyuncu CF, Toro P, Fu P, Koyfman SA, Lewis JS, Madabhushi A (2021) Radiomic features associated with HPV status on pretreatment computed tomography in oropharyngeal squamous cell carcinoma inform clinical prognosis. Front Oncol. https://doi.org/10.3389/fonc.2021.744250

Altinok O, Guvenis A (2022) Interpretable radiomics method for predicting human papillomavirus status in oropharyngeal cancer using Bayesian networks. https://doi.org/10.1101/2022.06.29.22276890

Bogowicz M, Riesterer O, Ikenberg K, Stieb S, Moch H, Studer G, Guckenberger M, Tanadini-Lang S (2017) Computed tomography radiomics predicts HPV status and local tumor control after definitive radiochemotherapy in head and neck squamous cell carcinoma. Int J Radiat Oncol Biol Phys 99:921–928. https://doi.org/10.1016/j.ijrobp.2017.06.002

Bagher-Ebadian H, Lu M, Siddiqui F, Ghanem AI, Wen N, Wu Q, Liu C, Movsas B, Chetty IJ (2020) Application of radiomics for the prediction of HPV status for patients with head and neck cancers. Med Phys 47:563–575. https://doi.org/10.1002/mp.13977

Yu K, Zhang Y, Yu Y, Huang C, Liu R, Li T, Yang L, Morris JS, Baladandayuthapani V, Zhu H (2017) Radiomic analysis in prediction of human papilloma virus status. Clin Transl Radiat Oncol 7:49–54. https://doi.org/10.1016/j.ctro.2017.10.001

Reiazi R, Arrowsmith C, Welch M, Abbas-Aghababazadeh F, Eeles C, Tadic T, Hope AJ, Bratman SV, Haibe-Kains B (2021) Prediction of human papillomavirus (HPV) Association of Oropharyngeal Cancer (OPC) using radiomics: the impact of the variation of CT scanner. Cancers 13:2269. https://doi.org/10.3390/cancers13092269

Sarac K, Guvenis A (2023) Determining HPV status in patients with oropharyngeal cancer from 3D CT images using radiomics: effect of sampling methods. Bioinform Biomed Eng 27–41. https://doi.org/10.1007/978-3-031-34960-7_3

Clark K, Vendt B, Smith K, Freymann J, Kirby J, Koppel P, Moore S, Phillips S, Maffitt D, Pringle M, Tarbox L, Prior F (2013) The Cancer Imaging Archive (TCIA): Maintaining and operating a public information repository. J Digit Imaging 26:1045–1057. https://doi.org/10.1007/s10278-013-9622-7

Karagöz A, Guvenis A (2022) Robust whole-tumour 3D volumetric CT-based radiomics approach for predicting the WHO/ISUP grade of a CCRCC tumour. Comput Methods Biomech Biomed Eng 11:665–677. https://doi.org/10.1080/21681163.2022.2103449

Wels MG, Lades F, Muehlberg A, Suehling M (2019) General purpose radiomics for multi-modal clinical research. Medical Imaging 2019: Computer-Aided Diagnosis. https://doi.org/10.1117/12.2511856

Chianca V, Cuocolo R, Gitto S, Albano D, Merli I, Badalyan J, Cortese MC, Messina C, Luzzati A, Parafioriti A, Galbusera F, Brunetti A, Sconfienza LM (2021) Radiomic machine learning classifiers in spine bone tumors: a multi-software, multi-scanner study. Eur J Radiol 137:109586. https://doi.org/10.1016/j.ejrad.2021.109586

Larue RT, van Timmeren JE, de Jong EE, Feliciani G, Leijenaar RT, Schreurs WM, Sosef MN, Raat FH, van der Zande FH, Das M, van Elmpt W, Lambin P (2017) Influence of gray level discretization on radiomic feature stability for different CT scanners, tube currents and slice thicknesses: a comprehensive phantom study. Acta Oncol 56:1544–1553. https://doi.org/10.1080/0284186x.2017.1351624

Tamal M (2019) Grey level co-occurrence matrix (GLCM) as a Radiomics feature for artificial intelligence (AI) assisted positron emission tomography (PET) images analysis. IOP Conference Series Mater Sci Eng 646:012047. https://doi.org/10.1088/1757-899x/646/1/012047

van Griethuysen JJM, Fedorov A, Parmar C, Hosny A, Aucoin N, Narayan V, Beets-Tan RGH, Fillion-Robin J-C, Pieper S, Aerts HJWL (2017) Computational radiomics system to decode the radiographic phenotype. Cancer Res. https://doi.org/10.1158/0008-5472.can-17-0339

Mohammed R, Rawashdeh J, Abdullah M (2020) Machine learning with oversampling and undersampling techniques: overview study and experimental results. 2020 11th International Conference on Information and Communication Systems (ICICS). https://doi.org/10.1109/icics49469.2020.239556

Menze BH, Kelm BM, Masuch R, Himmelreich U, Bachert P, Petrich W, Hamprecht FA (2009) A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of Spectral Data. BMC Bioinformatics. https://doi.org/10.1186/1471-2105-10-213

Stancin I, Jovic A (2019) An overview and comparison of free python libraries for data mining and big data analysis. 2019 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO).https://doi.org/10.23919/mipro.2019.8757088

Lange MB, Petersen LJ, Nielsen MB, Zacho HD (2021) Validity of negative bone biopsy in suspicious bone lesions. Acta Radiologica Open 10:205846012110306. https://doi.org/10.1177/20584601211030662

Göret CC, Göret NE, Özdemir ZT, Özkan EA, Doğan M, Yanık S, Gümrükçü G, Aker FV (2015) Diagnostic value of fine needle aspiration biopsy in non-thyroidal head and neck lesions: a retrospective study of 866 aspiration materials. Int J Clin Exp Pathol 8(8):8709–8716

Chen S, Forman M, Sadow PM, August M (2016) The diagnostic accuracy of incisional biopsy in the oral cavity. J Oral Maxillofac Surg 74:959–964. https://doi.org/10.1016/j.joms.2015.11.006

S; SD Fine needle aspiration. In: National Center for Biotechnology Information. https://pubmed.ncbi.nlm.nih.gov/32491418/. Accessed 14 Aug 2023

Lambin P, Leijenaar RTH, Deist TM, Peerlings J, de Jong EEC, van Timmeren J, Sanduleanu S, Larue RTHM, Even AJG, Jochems A, van Wijk Y, Woodruff H, van Soest J, Lustberg T, Roelofs E, van Elmpt W, Dekker A, Mottaghy FM, Wildberger JE, Walsh S (2017) Radiomics: the bridge between medical imaging and personalized medicine. Nat Rev Clin Oncol 14:749–762. https://doi.org/10.1038/nrclinonc.2017.141

Zwanenburg A, Vallières M, Abdalah MA, Aerts HJ, Andrearczyk V, Apte A, Ashrafinia S, Bakas S, Beukinga RJ, Boellaard R, Bogowicz M, Boldrini L, Buvat I, Cook GJ, Davatzikos C, Depeursinge A, Desseroit M-C, Dinapoli N, Dinh CV, Echegaray S, El Naqa I, Fedorov AY, Gatta R, Gillies RJ, Goh V, Götz M, Guckenberger M, Ha SM, Hatt M, Isensee F, Lambin P, Leger S, Leijenaar RTH, Lenkowicz J, Lippert F, Losnegård A, Maier-Hein KH, Morin O, Müller H, Napel S, Nioche C, Orlhac F, Pati S, Pfaehler EAG, Rahmim A, Rao AUK, Scherer J, Siddique MM, Sijtsema NM, Socarras Fernandez J, Spezi E, Steenbakkers RJHM, Tanadini-Lang S, Thorwarth D, Troost EGC, Upadhaya T, Valentini V, van Dijk LV, van Griethuysen J, van Velden FHP, Whybra P, Richter C, Löck S (2020) The image biomarker standardization initiative: standardized quantitative radiomics for high-throughput image-based phenotyping. Radiology 295:328–338. https://doi.org/10.1148/radiol.2020191145

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