Novel Radiomic Measurements of Tumor- Associated Vasculature Morphology on Clinical Imaging as a Biomarker of Treatment Response in Multiple Cancers
Nathaniel Braman, Prateek Prasanna, Kaustav Bera, Mehdi Alilou,, Mohammadhadi Khorrami, Patrick Leo, Maryam Etesami, Manasa Vulchi, Paulette, Turk, Amit Gupta, Prantesh Jain, Pingfu Fu, Nathan Pennell, Vamsidhar, Velcheti, Jame Abraham, Donna Plecha, Anant Madabhushi

TL;DR
This study introduces quantitative radiomic features of tumor vasculature from routine imaging that can predict treatment response and survival across multiple cancers, potentially guiding personalized therapy decisions.
Contribution
The paper presents a novel set of radiomic biomarkers called QuanTAV, measuring tumor vasculature twistedness and organization, demonstrating their predictive and prognostic value across different cancers and treatments.
Findings
QuanTAV features significantly predict treatment response (AUC=0.63-0.71).
QuanTAV scores are prognostic of recurrence-free survival in breast and lung cancers.
Adding QuanTAV improves clinical models' predictive accuracy.
Abstract
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…
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