Novel Radiomic Measurements of Tumor- Associated Vasculature Morphology on Clinical Imaging as a Biomarker of Treatment Response in Multiple Cancers
This work addresses the need for better biomarkers to stratify cancer patients by treatment benefit, offering a novel approach that is applicable across multiple cancers and treatments, though it is incremental in building on existing radiomic methods.
The study tackled the problem of predicting treatment response in cancer patients by introducing QuanTAV features, which measure tumor-associated vasculature morphology from clinical imaging, and found that these features significantly predicted response with AUC improvements of 0.06-0.12 and prognostic survival with hazard ratios up to 2.29.
Purpose: Tumor-associated vasculature differs from healthy blood vessels by its chaotic architecture and twistedness, which promotes treatment resistance. Measurable differences in these attributes may help stratify patients by likely benefit of systemic therapy (e.g. chemotherapy). In this work, we present a new category of radiomic biomarkers called quantitative tumor-associated vasculature (QuanTAV) features, and demonstrate their ability to predict response and survival across multiple cancers, imaging modalities, and treatment regimens. Experimental Design: We segmented tumor vessels and computed mathematical measurements of twistedness and organization on routine pre-treatment radiology (CT or contrast-enhanced MRI) from 558 patients, who received one of four first-line chemotherapy-based therapeutic intervention strategies for breast (n=371) or non-small cell lung cancer (NSCLC, n=187). Results: Across 4 chemotherapy-based treatment strategies, classifiers of QuanTAV measurements significantly (p<.05) predicted response in held out testing cohorts alone (AUC=0.63-0.71) and increased AUC by 0.06-0.12 when added to models of significant clinical variables alone. QuanTAV risk scores were prognostic of recurrence free survival in treatment cohorts chemotherapy for breast cancer (p=0.002, HR=1.25, 95% CI 1.08-1.44, C-index=.66) and chemoradiation for NSCLC (p=0.039, HR=1.28, 95% CI 1.01-1.62, C-index=0.66). Categorical QuanTAV risk groups were independently prognostic among all treatment groups, including NSCLC patients receiving chemotherapy (p=0.034, HR=2.29, 95% CI 1.07-4.94, C-index=0.62). Conclusions: Across these domains, we observed an association of vascular morphology on radiology with treatment outcome. Our findings suggest the potential of tumor-associated vasculature shape and structure as a prognostic and predictive biomarker for multiple cancers and treatments.