Radiomic Analysis for Human Papillomavirus Assessment in Oropharyngeal Carcinoma: Lessons and Pitfalls for the Next Future
Source abstract
Abstract
Background: Oropharyngeal Squamous Cell Carcinoma (OPSCC) is rapidly increasing due to the spread of Human Papillomavirus (HPV) infection. HPV-positive disease has unique characteristics, with better response to treatment and consequent better prognosis. HPV status is routinely assessed via p16 immunohistochemistry or HPV DNA Polymerase Chain Reaction. Radiomics is a quantitative approach to medical imaging which can overcome limitations due to its subjective interpretation and correlation with clinical data. The aim of this narrative review is to evaluate the impact of radiomic features on assessing HPV status in OPSCC patients. Methods: A narrative review was performed by synthesizing literature results from PUBMED. In the search strategy, Medical Subject Headings (MeSH) terms were used. Retrospective mono- or multicentric works assessing the correlation between radiomic features and HPV status prediction in OPSCC were included. Selected papers were in English and included studies on humans. The range of publication date was July 2015–April 2023. Results: Our research returned 23 published papers; the accuracy of radiomic models was evaluated by ROC curves and AUC values. MRI- and CT-based radiomic models proved of comparable efficacy. Also, metabolic imaging showed crucial importance in the determination of HPV status, albeit with lower AUC values. Conclusions: Radiomic features from conventional imaging can play a complementary role in the assessment of HPV status in OPSCC. Both primary tumor- and nodal-related features and multisequencing-based models demonstrated higher accuracy.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Radiomics and Machine Learning in Medical Imaging · Head and Neck Cancer Studies · Medical Imaging Techniques and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Experimental and Clinical Biomedical Sciences “Mario Serio”, University of Florence, 50121 Florence, Italy
Radiation Oncology Unit, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy
References (59)
Show source-provided references
1. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries10.3322/caac.21492 ↗
2. Human papillomavirus and rising oropharyngeal cancer incidence in the United States10.1200/JCO.2011.36.4596 ↗
3. HPV in oropharyngeal cancer: The basics to know in clinical practice
4. Survival of squamous cell carcinoma of the head and neck in relation to human papillomavirus infection: Review and meta-analysis10.1002/ijc.22851 ↗
5. Human papillomavirus and survival of patients with oropharyngeal cancer10.1056/NEJMoa0912217 ↗
6. De-escalation studies in HPV-positive oropharyngeal cancer: How should we proceed?10.1016/j.oraloncology.2021.105620 ↗
7. Squamous cell carcinoma of the oral cavity, larynx, oropharynx and hypopharynx: EHNS-ESMO-ESTRO Clinical Practice Guidelines for diagnosis, treatment and follow-up10.1016/j.annonc.2020.07.011 ↗
8. A proposal for classification of oropharyngeal squamous cell carcinoma: Morphology and status of HPV by immunohistochemistry and molecular biology10.1111/jop.12956 ↗
9. Diagnostic accuracy of p16INK4a immunohistochemistry in oropharyngeal squamous cell carcinomas: A systematic review and meta-analysis10.1002/ijc.30516 ↗
10. The impact of radiomics for human papillomavirus status prediction in oropharyngeal cancer: Systematic review and radiomics quality score assessment10.1007/s00234-022-02959-0 ↗
11. Clinical variables and magnetic resonance imaging-based radiomics predict human papillomavirus status of oropharyngeal cancer10.1002/hed.26505 ↗
12. Differences in imaging characteristics of HPV-positive and HPV-Negative oropharyngeal cancers: A blinded matched-pair analysis10.3174/ajnr.A3524 ↗
13. FDG PET/CT imaging of oropharyngeal squamous cell carcinoma: Characteristics of human papillomavirus-positive and -negative tumors10.1097/RLU.0000000000000255 ↗
14. The utility of MRI histogram and texture analysis for the prediction of histological diagnosis in head and neck malignancies
15. Using Texture Analysis to Determine Human Papillomavirus Status of Oropharyngeal Squamous Cell Carcinomas on CT10.3174/ajnr.A4285 ↗
16. CT assessment of tumor heterogeneity and the potential for the prediction of human papillomavirus status in oropharyngeal squamous cell carcinoma10.1007/s11547-019-01028-6 ↗
17. Radiomics: Extracting more information from medical images using advanced feature analysis
18. Radiomics: A primer for the radiation oncologist
19. Radiomics: The bridge between medical imaging and personalized medicine10.1038/nrclinonc.2017.141 ↗
20. Nardone, V., Boldrini, L., Grassi, R., Franceschini, D., Morelli, I., Becherini, C., Loi, M., Greto, D., and Desideri, I. (2021). Radiomics in the Setting of Neoadjuvant Radiotherapy: A New Approach for Tailored Treatment. Cancers, 13.10.3390/cancers13143590 ↗
21. A deep look into radiomics10.1007/s11547-021-01389-x ↗
22. Prototype system for feature extraction, classification and study of medical images10.1016/j.eswa.2016.07.008 ↗
23. Fractal-based radiomic approach to predict complete pathological response after chemo-radiotherapy in rectal cancer10.1007/s11547-017-0838-3 ↗
24. Barucci, A., Farnesi, D., Ratto, F., Pelli, S., Pini, R., Carpi, R., Esposito, M., Olmastroni, M., Romei, C., and Taliani, A. (2018, January 10–12). Fractal-Radiomics as Complexity Analysis of CT and MRI Cancer Images. Proceedings of the IEEE Workshop on Complexity in Engineering (COMPENG), Florence, Italy.10.1109/CompEng.2018.8536249 ↗
25. Radiomics: The facts and the challenges of image analysis10.1186/s41747-018-0068-z ↗
26. Radiomics in medical imaging—“how-to” guide and critical reflection10.1186/s13244-020-00887-2 ↗
27. Radiomics: A Primer on Processing Workflow and Analysis10.1053/j.sult.2022.02.003 ↗
28. Internal validation of predictive models: Efficiency of some procedures for logistic regression analysis10.1016/S0895-4356(01)00341-9 ↗
29. Radiomics analysis in medical imaging research10.1002/jmrs.662 ↗
30. Human papilomaviru-related oropharyngeal squamous cell carcinoma and radiomics: A new era?10.1111/jop.13419 ↗
31. Association of quantitative MRI-based radiomic features with prognostic factors and recurrence rate in oropharyngeal squamous cell carcinoma10.4149/neo_2020_200310N249 ↗
32. Machine learning and magnetic resonance imaging radiomics for predicting human papilloma virus status and prognostic factors in oropharyngeal squamous cell carcinoma10.1002/hed.26979 ↗
33. Machine Learning Based Radiomic HPV Phenotyping of Oropharyngeal SCC: A Feasibility Study Using MRI10.1002/lary.28889 ↗
34. Applying multisequence MRI radiomics of the primary tumor and lymph node to predict HPV-related p16 status in patients with oropharyngeal squamous cell carcinoma10.21037/qims-22-819 ↗
35. Magnetic resonance imaging based radiomics prediction of Human Papillomavirus infection status and overall survival in oropharyngeal squamous cell carcinoma10.1016/j.oraloncology.2023.106307 ↗
36. Oropharyngeal squamous cell carcinoma: Radiomic machine-learning classifiers from multiparametric MR images for determination of HPV infection status10.1038/s41598-020-74479-x ↗
37. Correlation between Human Papillomavirus Status and Quantitative MR Imaging Parameters including Diffusion-Weighted Imaging and Texture Features in Oropharyngeal Carcinoma10.3174/ajnr.A5792 ↗
38. Diffusion-weighted MR imaging in laryngeal and hypopharyngeal carcinoma: Association between apparent diffusion coefficient and histologic findings10.1148/radiol.14131173 ↗
39. The morphologic profile of HPV-related head and neck squamous carcinoma: Implications for diagnosis, prognosis, and clinical management10.1007/s12105-012-0371-6 ↗
40. Largest diameter delineations can substitute 3D tumor volume delineations for radiomics prediction of human papillomavirus status on MRI’s of oropharyngeal cancer10.1016/j.ejmp.2022.07.004 ↗
41. Computed Tomography-Based Texture Analysis to Determine Human Papillomavirus Status of Oropharyngeal Squamous Cell Carcinoma10.1097/RCT.0000000000000682 ↗
42. Radiomic Features Associated With HPV Status on Pretreatment Computed Tomography in Oropharyngeal Squamous Cell Carcinoma Inform Clinical Prognosis10.3389/fonc.2021.744250 ↗
43. Application of radiomics for the prediction of HPV status for patients with head and neck cancers10.1002/mp.13977 ↗
44. Bagher-Ebadian, H., Siddiqui, F., Ghanem, A.I., Zhu, S., Lu, M., Movsas, B., and Chetty, I.J. (2022). Radiomics outperforms clinical factors in characterizing human papilloma virus (HPV) for patients with oropharyngeal squamous cell carcinomas. Biomed. Phys. Eng. Express, 8.10.1088/2057-1976/ac39ab ↗
45. Computed Tomography Radiomics Predicts HPV Status and Local Tumor Control After Definitive Radiochemotherapy in Head and Neck Squamous Cell Carcinoma10.1016/j.ijrobp.2017.06.002 ↗
46. Development and validation of a radiomic signature to predict HPV (p16) status from standard CT imaging: A multicenter study10.1259/bjr.20170498 ↗
47. Prediction of Human Papillomavirus Status and Overall Survival in Patients with Untreated Oropharyngeal Squamous Cell Carcinoma: Development and Validation of CT-Based Radiomics10.3174/ajnr.A6756 ↗
48. Predictive and prognostic value of CT based radiomics signature in locally advanced head and neck cancers patients treated with concurrent chemoradiotherapy or bioradiotherapy and its added value to Human Papillomavirus status10.1016/j.oraloncology.2017.06.015 ↗
49. Hypoxia and tumor metabolism in radiation oncology: Targets visualized by positron emission tomography
50. PET/CT radiomics signature of human papilloma virus association in oropharyngeal squamous cell carcinoma10.1007/s00259-020-04839-2 ↗
51. Lv, W., Xu, H., Han, X., Zhang, H., Ma, J., Rahmim, A., and Lu, L. (2022). Context-Aware Saliency Guided Radiomics: Application to Prediction of Outcome and HPV-Status from Multi-Center PET/CT Images of Head and Neck Cancer. Cancers, 14.10.3390/cancers14071674 ↗
52. Development and Testing of a Machine Learning Model Using 18F-Fluorodeoxyglucose PET/CT-Derived Metabolic Parameters to Classify Human Papillomavirus Status in Oropharyngeal Squamous Carcinoma10.3348/kjr.2022.0397 ↗
53. Role of PET/MRI in oral cavity and oropharyngeal cancers based on the 8th edition of the AJCC cancer staging system: A pictorial essay10.1007/s12149-018-1244-1 ↗
54. Pre-treatment PET/MRI based FDG and DWI imaging parameters for predicting HPV status and tumor response to chemoradiotherapy in primary oropharyngeal squamous cell carcinoma (OPSCC)10.1016/j.oraloncology.2021.105239 ↗
55. Samolyk-Kogaczewska, N., Sierko, E., Dziemianczyk-Pakiela, D., Nowaszewska, K.B., Lukasik, M., and Reszec, J. (2020). Usefulness of Hybrid PET/MRI in Clinical Evaluation of Head and Neck Cancer Patients. Cancers, 12.10.3390/cancers12020511 ↗
56. Prognostic value of simultaneous 18F-FDG PET/MRI using a combination of metabolo-volumetric parameters and apparent diffusion coefficient in treated head and neck cancer10.1186/s13550-018-0357-9 ↗
57. Radiomics for precision medicine: Current challenges, future prospects, and the proposal of a new framework10.1016/j.ymeth.2020.05.022 ↗
58. A review of original articles published in the emerging field of radiomics10.1016/j.ejrad.2020.108991 ↗
59. Tortora, M., Gemini, L., Scaravilli, A., Ugga, L., Ponsiglione, A., Stanzione, A., D’Arco, F., D’Anna, G., and Cuocolo, R. (2023). Radiomics Applications in Head and Neck Tumor Imaging: A Narrative Review. Cancers, 15.10.3390/cancers15041174 ↗