Filters are commonly used to enhance specific structures and patterns in images, such as vessels or peritumoral regions, to enable clinical insights beyond the visible image using radiomics. However, their lack of standardization restricts reproducibility and clinical translation of radiomics decision support tools. In this special report, teams of researchers who developed radiomics software participated in a three-phase study (September 2020 to December 2022) to establish a standardized set of filters. The first two phases focused on finding reference filtered images and reference feature values for commonly used convolutional filters: mean, Laplacian of Gaussian, Laws and Gabor kernels, separable and nonseparable wavelets (including decomposed forms), and Riesz transformations. In the first phase, 15 teams used digital phantoms to establish 33 reference filtered images of 36 filter configurations. In phase 2, 11 teams used a chest CT image to derive reference values for 323 of 396 features computed from filtered images using 22 filter and image processing configurations. Reference filtered images and feature values for Riesz transformations were not established. Reproducibility of standardized convolutional filters was validated on a public data set of multimodal imaging (CT, fluorodeoxyglucose PET, and T1-weighted MRI) in 51 patients with soft-tissue sarcoma. At validation, reproducibility of 486 features computed from filtered images using nine configurations × three imaging modalities was assessed using the lower bounds of 95% CIs of intraclass correlation coefficients. Out of 486 features, 458 were found to be reproducible across nine teams with lower bounds of 95% CIs of intraclass correlation coefficients greater than 0.75. In conclusion, eight filter types were standardized with reference filtered images and reference feature values for verifying and calibrating radiomics software packages. A web-based tool is available for compliance checking.

The aim of this study was to evaluate the variation of radiomics features, defined as “delta radiomics”, in patients undergoing neoadjuvant radiochemotherapy (RCT) for rectal cancer treated with hybrid magnetic resonance (MR)-guided radiotherapy (MRgRT). The delta radiomics features were then correlated with clinical complete response (cCR) outcome, to investigate their predictive power. A total of 16 patients were enrolled, and 5 patients (31%) showed cCR at restaging examinations. T2*/T1 MR images acquired with a hybrid 0.35 T MRgRT unit were considered for this analysis. An imaging acquisition protocol of 6 MR scans per patient was performed: the first MR was acquired at first simulation (t0) and the remaining ones at fractions 5, 10, 15, 20 and 25. Radiomics features were extracted from the gross tumour volume (GTV), and each feature was correlated with the corresponding delivered dose. The variations of each feature during treatment were quantified, and the ratio between the values calculated at different dose levels and the one extracted at t0 was calculated too. The Wilcoxon–Mann–Whitney test was performed to identify the features whose variation can be predictive of cCR, assessed with a MR acquired 6 weeks after RCT and digital examination. The most predictive feature ratios in cCR prediction were the L_least and glnu ones, calculated at the second week of treatment (22 Gy) with a p value = 0.001. Delta radiomics approach showed promising results and the quantitative analysis of images throughout MRgRT treatment can successfully predict cCR offering an innovative personalized medicine approach to rectal cancer treatment.

Human papillomavirus 16 infection has been proven to be associated with oropharyngeal squamous cell carcinomas (SCCs) and is probably the main reason of the reported increase in the incidence. The role of high-risk (HR) HPV for carcinogenesis of other sites in the head and neck awaits confirmation. With the aim to evaluate the prevalence of HPV infection and the reliability of different diagnostic tools in SCCs of different sites, 109 consecutive untreated head and neck SCCs were enroled, and fresh tumour samples collected. Human papillomavirus DNA was detected by Digene Hybrid Capture 2 (HC2). Human papillomavirus E6 and E7 mRNA were detected by NucliSENS EasyQ HPVv1. P16 expression was evaluated by immunohistochemistry. In all, 12.84% of cases were infected by HR genotypes and 1.84% by low-risk genotypes. Human papillomavirus 16 accounted for 87% of HR infections. The overall agreement between DNA and RNA detection is 99.1%. Although p16 expression clearly correlates with HPV infection (P=0.0051), the inter-rater agreement is poor (k=0.27). The oropharynx showed the highest HR HPV infection rate (47.6%) and was also the only site in which p16 immunohistochemistry revealed to be a fair, but not excellent, diagnostic assay (κ=0.61). The prognostic role of HR HPV infection in oropharyngeal oncology, with its potential clinical applications, underscores the need for a consensus on the most appropriate detection methods. The present results suggest that viral mRNA detection could be the standard for fresh samples, whereas DNA detection could be routinely used in formalin-fixed, paraffin-embedded samples.