A T2-weighted MRI-based radiomic signature for disease-free survival in locally advanced cervical cancer following chemoradiation: An international, multicentre study.

INTRODUCTION: To develop and validate a T2-weighted magnetic resonance imaging (MRI)-based radiomic signature associated with disease-free survival (DFS) in locally advanced cervical cancer. MATERIALS AND METHODS: The study comprised a training dataset of 132 patients (93 Norwegian; 39 The Cancer Imaging Archive (TCIA) and an independent validation Canadian dataset of 199 patients with FIGO stage IB-IVA cervical cancer treated with chemoradiation. Radiomic features were extracted using PyRadiomics. A radiomic signature was developed based on a multivariable radiomic prognostic model for DFS built using the training dataset, with minimal redundancy maximum relevancy feature selection method. Univariate and multivariable Cox regression analyses were then conducted to examine the association of the derived radiomic signature with DFS. RESULTS: A radiomic signature was prognostic for DFS in the training cohort (Norwegian hazard ratio [HR] 5.54, p = 0.002; TCIA HR 3.59, p = 0.04). The radiomic signature remained independently associated with DFS (HR 3.70, p = 0.004) when adjusted for stage and tumor volume. The radiomic signature was also prognostic for DFS in the validation cohort, both on univariate analysis (HR 2.22, p = 0.003), and multivariable analysis adjusted for stage and tumor volume (HR 1.84, p = 0.04). The 4-year DFS rates of patients with radiomic signature score > 0 vs ≤ 0 were 48.2 % vs 87.9 %, and 56.4 % vs 80.8 % for training and validation cohorts respectively. CONCLUSION: An MRI-based radiomic signature can be used as a prognostic biomarker for DFS in patients with locally advanced cervical cancer undergoing chemoradiation.

RADCURE: An open-source head and neck cancer CT dataset for clinical radiation therapy insights.

PURPOSE: This manuscript presents RADCURE, one of the most extensive head and neck cancer (HNC) imaging datasets accessible to the public. Initially collected for clinical radiation therapy (RT) treatment planning, this dataset has been retrospectively reconstructed for use in imaging research. ACQUISITION AND VALIDATION METHODS: RADCURE encompasses data from 3346 patients, featuring computed tomography (CT) RT simulation images with corresponding target and organ-at-risk contours. These CT scans were collected using systems from three different manufacturers. Standard clinical imaging protocols were followed, and contours were manually generated and reviewed at weekly RT quality assurance rounds. RADCURE imaging and structure set data was extracted from our institution's radiation treatment planning and oncology information systems using a custom-built data mining and processing system. Furthermore, images were linked to our clinical anthology of outcomes data for each patient and includes demographic, clinical and treatment information based on the 7th edition TNM staging system (Tumor-Node-Metastasis Classification System of Malignant Tumors). The median patient age is 63, with the final dataset including 80% males. Half of the cohort is diagnosed with oropharyngeal cancer, while laryngeal, nasopharyngeal, and hypopharyngeal cancers account for 25%, 12%, and 5% of cases, respectively. The median duration of follow-up is five years, with 60% of the cohort surviving until the last follow-up point. DATA FORMAT AND USAGE NOTES: The dataset provides images and contours in DICOM CT and RT-STRUCT formats, respectively. We have standardized the nomenclature for individual contours-such as the gross primary tumor, gross nodal volumes, and 19 organs-at-risk-to enhance the RT-STRUCT files' utility. Accompanying demographic, clinical, and treatment data are supplied in a comma-separated values (CSV) file format. This comprehensive dataset is publicly accessible via The Cancer Imaging Archive. POTENTIAL APPLICATIONS: RADCURE's amalgamation of imaging, clinical, demographic, and treatment data renders it an invaluable resource for a broad spectrum of radiomics image analysis research endeavors. Researchers can utilize this dataset to advance routine clinical procedures using machine learning or artificial intelligence, to identify new non-invasive biomarkers, or to forge prognostic models.

Effect of Radiation Therapy Quality Assurance on Nasopharyngeal Carcinoma: Usage of a Novel, Web-Based Quality Assurance Application.

PURPOSE: We used a new web application for rapid review of radiation therapy (RT) target volumes to evaluate the relationship between target delineation compliance with the international guidelines and outcomes of definitive RT for nasopharyngeal carcinoma (NPC). METHODS AND MATERIALS: The data set consisted of computed tomography simulation scans, RT structures, and clinical data of 354 patients with pathology-confirmed NPC treated with intensity modulated RT between 2005 and 2017. Target volumes were peer-reviewed in RT quality assurance rounds, and target contours were revised, if recommended, before treatment. We imported the contours of intermediate-risk clinical target volumes of the primary tumor (CTVp) of 332 patients into the application. Inclusion of anatomic sites within intermediate-risk CTVp was determined in accordance with 2018 international guidelines for CTV delineation for NPC and correlated with time to local failure (TTLF) using Cox regression. RESULTS: In the peer-review quality assurance analysis, local and distant control and overall survival rates were similar between peer-reviewed and nonreviewed cases and between cases with and without target contour changes. In the CTV compliance analysis, with a median follow-up of 5.6 years, 5-year TTLF and overall survival rates were 93.1% and 85.9%, respectively. The most frequently non-guideline-compliant anatomic sites were sphenoid sinus (n = 69, 20.8%), followed by cavernous sinus (n = 38, 19.3%), left and right petrous apices (n = 37 and 32, 11.1% and 9.6%), and clivus (n = 14, 4.2%). Among 23 patients with a local failure (6.9%), the number of noncompliant cases was 8 for sphenoid sinus, 7 cavernous sinus, 4 left and 3 right petrous apices, and 2 clivus. Cavernous sinus-conforming cases showed higher TTLF in comparison with nonconforming cases (93.6% vs 89.1%, P = .013). Multivariable analysis confirmed that cavernous sinus noncompliance was prognostic for TTLF. CONCLUSIONS: Our application allowed rapid quantitative review of CTVp in a large NPC cohort. Although compliance with the international guidelines was high, undercoverage of the cavernous sinus was correlated with TTLF.