External validation of a radiomic signature to predict p16 (HPV) status from standard CT images of anal cancer patients

Sep 24, 2026

Uploaded by Oliver

Evaluation focuses on the performance of an existing CT-based radiomic signature, previously validated in oropharyngeal cancer, for predicting human papillomavirus (HPV) status in anal cancer. Two-center external data from 59 patients were analyzed, using HPV status determined by p16 immunohistochemistry as the primary endpoint. Predefined statistical tests assessed model performance, yielding an AUC of 0.68 (95% CI 0.32–1.00) and an F1 score of 0.78. Results support the signature as a potential CT imaging biomarker for p16 status and a clinically relevant molecular phenotype across cancers.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages7

Reading Time18 min

AccessFree to download

Materials and methods

Patient cohort

Statistical evaluation and endpoint definition

[www. nature.com/scientificreports](www. nature.com/scientificreports) OPEN External validation of a radiomic signature to predict p16 (HPV) status from standard CT images of anal cancer patients Ralph T. H. Leijenaar1,9, Sean Walsh1,9, AkshayaaVaidyanathan1,2, Lorenzo Aliboni1, Victoria Lopez Sanchez1, Michelle Leech3, Ronan Joyce4, Charles Gillham4, Frédéric Kridelka 5, Roland Hustinx6, Denis Danthine6, Mariaelena Occhipinti1, Wim Vos1, Julien Guiot7, Philippe Lambin2,8,10 & Pierre Lovinfosse6,10* The paper deals with the evaluation of the performance of an existing and previously validated CT based radiomic signature, developed in oropharyngeal cancer to predict human papillomavirus (HPV) status, in the context of anal cancer. For the validation in anal cancer, a dataset of 59 patients coming from two different centers was collected. The primary endpoint was HPV status according to p16 immunohistochemistry. Predefined statistical tests were performed to evaluate the performance of the model. TheAUC obtained here in anal cancer is 0.68 [95% CI (0 .32–1.00)] with F1 score of 0.78. This signature is TRIPOD level 4 (57%) with an RQS of 61%. This study provides proof of concept that this radiomic signature has the potential to identify a clinically relevant molecular phenotype (i.e., the HPV-ness) across multiple cancers and demonstrates potential for this radiomic signature as a CT imaging biomarker of p16 status. Human papillomavirus (HPV) is a common virus that can lead to certain types of cancer later in life. Several studies have shown that HPV status of cancer patients plays an important role in treatment outcomes1,2. In particular, HPV +patients with oropharyngeal cancer present a markedly better prognosis and improved response to conventional radiotherapy3. Also, patients with anal cancer show a better prognosis and response to therapy when HPV + 4. Widely accepted methods for detection of HPV infection are in situ hybridization for viral DNA, HPV DNA or RNA PCR, and immunohistochemical investigation ofthe level ofp16 expression, which strongly correlates with HPV infection1,5. However, these methods are time consuming and require biological patient samples. Image data analysis represents a novel non-invasive method of delivering reliable and quality results from standard-of-care medical images. The extraction of clinically relevant information from medical imaging is called radiomics. Radiomics is a rapidly emerging field, introduced in 2012, which concerns with the highthroughput mining of large amounts of quantitative features, derived from medical image such as CT/MRI/ PET scans6,7. Radiomics is promising within decision support systems for precision medicine and its potential to predict p16 status in head and neck cancer has been recognized8. Previous studies have reported radiologic differences between p16 positive and negative cases in terms of qualitative radiologist’s readout of perfusion CT9. Furthermore, exploratory radiomic studies have shown that heterogeneity of image-based density is potentially associated with p16 status in oropharyngeal squamous cell carcinoma (OPSCC)10. Most of the studies investigating imaging phenotypes of tumors are based on single center data, which introduce bias to a model and limits its applicability. In particular, factors such as CT scanner, tube voltage, tube current, reconstruction kernel and 1Radiomics (Oncoradiomics SA), Liège, Belgium. 2The D-Lab, Department of Precision Medicine, GROW–School for Oncology and Reproduction, Maastricht University, Maastricht, The Netherlands. 3Applied Radiation Therapy, Discipline of Radiation Therapy, Trinity St. James’s Cancer Institute, Trinity College, Dublin, Ireland. 4Department of Radiation Oncology, St. Luke’s Radiation Oncology Network and St James’s Hospital, Dublin, Ireland. 5Department of Obstetrics and Gynecology, University Hospital of Liège, Liège, Belgium. 6Department of Nuclear Medicine and Oncological Imagin

FAQs

What was the main purpose of the study?

To externally validate an existing CT-based radiomic signature, originally developed for oropharyngeal cancer, for predicting p16 (HPV) status in anal cancer patients.

How was HPV status defined for the primary endpoint?

HPV status was determined according to p16 immunohistochemistry.

What performance metrics were reported for the radiomic signature in anal cancer?

The reported AUC was 0.68 (95% CI 0.32–1.00) and the F1 score was 0.78.

Sep 24, 2026

Uploaded by Oliver