Background: Immune checkpoint inhibitors (ICIs) improve survival in advanced non-small cell lung cancer (NSCLC), yet current biomarkers such as PD-L1 expression and response criteria (RECIST v1.1) align poorly with long-term survival. Radiomics has been proposed as a source of novel biomarkers, but standard radiomic approaches suffer from limited biological interpretability and poor generalizability across treatment settings. We address these gaps by developing the Quantitative Vessel Tortuosity (QVT) Score, a biologically interpretable imaging biomarker that quantifies tumor vascular complexity - a known mediator of immune evasion - from routine imaging. We hypothesized that QVT Score would improve prognostication and enable treatment response monitoring in ICI-treated NSCLC, independent of current biomarkers. Methods: This retrospective, multicenter study analyzed 1,301 CT scans from 682 ICI-treated NSCLC patients. An automated pipeline segmented lesions and tumor-associated vasculature within each scan, extracting 910 QVT features measuring vascular shape and complexity. Unsupervised clustering of these features in a discovery cohort (N=375) was performed to identify fundamental vascular phenotypes. A continuous QVT score was then derived using regularized logistic regression to map patients along this phenotypic spectrum. QVT Score was externally validated in ICI monotherapy (N=172) and chemoimmunotherapy (N=135) cohorts. In a longitudinal cohort (n=143), early on-treatment QVT Score changes were evaluated for overall survival (OS) association. Results: Two robust vascular phenotypes emerged in the discovery cohort: a highly vascularized, chaotic 'QVT High' phenotype with poor post-ICI OS and a 'QVT Low' phenotype with normalized vasculature and improved ICI outcomes. The continuous QVT Score was prognostic for ICI monotherapy (HR=1.17 per 0.1 increase, p=0.0028) and chemoimmunotherapy (HR=1.23 per 0.1 increase, p=4.9E-5). High QVT status remained prognostic for both treatments after adjustment for PD-L1 and clinical variables (adjusted HR range: 2.13-2.38, p=0.002). Early decreases in QVT Score during therapy, indicating vascular normalization, were associated with improved OS (HR=1.93, p=0.0022) independent of RECIST best overall response and tumor volume change. Conclusions: QVT Score is a novel, biologically interpretable imaging biomarker that quantifies vascular complexity. It enables automated, non-invasive prediction and monitoring of ICI outcomes by capturing treatment-induced vascular remodeling. Integrating QVT Score into clinical decision-making and drug development can address critical gaps in precision oncology.

Dr. Chae reports advisory board roles for Roche/Genentech, AstraZeneca, Foundation Medicine, Counsyl, Neogenomics, Guardant Health, Boehringer Ingelheim, Biodesix, Immuneoncia, Lilly Oncology, Merck, Takeda, Pfizer, and Tempus, and research grants from AbbVie, BMS, Biodesix, Lexent Bio, and Freenome. Dr. Zhang reports employment and stock/ownership interests with Picture Health and Sirona Medical, and pending intellectual property with Picture Health. Dr. Hiremath, and Dr. Li report employment and stock/ownership interests with Picture Health. Dr. Haji Maghsoudi reports employment and stock/ownership interests with Picture Health Inc. and Tempus. Dr. Chitalia and Dr. Cantor report employment with Invicro and Picture Health, and stock/ownership interests with Picture Health. Dr. Gupta, an advisor for Picture Health, reports stock/ownership interests in Picture Health, honoraria from Philips Healthcare, and a consulting or advisory role with GE Healthcare. Dr. Velcheti, an advisor for Picture Health, reports honoraria from Galvanize Therapeutics; consulting or advisory roles with Amgen, AstraZeneca/MedImmune, Bristol-Myers Squibb, GlaxoSmithKline, Janssen Oncology, Merck, Novocure, Picture Health, Regeneron, Taiho Oncology, and Takeda; and research funding from Alkermes, Altor BioScience, Atreca, Bristol-Myers Squibb, Eisai, Genentech, Genoptix, GlaxoSmithKline, Heat Biologics, Leap Therapeutics, Merck, NantWorks, OncoPlex Diagnostics, RSIP Vision, and Trovagene. Anant Madabhushi reports employment, leadership roles, and stock/ownership interests with Picture Health and Inspirata, in addition to honoraria from AstraZeneca and Inspirata, consulting or advisory roles with Aiforia, Caris Life Sciences, Castle Biosciences, Cernostics, Merck, Roche, and SimBioSys, and research funding from AstraZeneca, Boehringer Ingelheim, Bristol Myers-Squibb, Inspirata, and Philips Healthcare. He also has intellectual property licensed by Elucid Bioimaging and Inspirata Inc., and technologies licensed from Case Western Reserve University to Picture Health. Trishan Arul reports employment, leadership, and stock/ownership interests with Picture Health Inc., and a consulting or advisory role with Path Presenter Inc. Dr. Braman reports employment and stock/ownership interests with Picture Health and Tempus AI, and intellectual property with IBM Research, Picture Health, and Tempus AI. Other authors have nothing to disclose.

Research reported in this study was funded by Picture Health Inc.

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The Institutional Review Boards of Case Western Reserve University, the Cleveland Clinic Foundation, Northwestern University, and University Hospitals gave approval for this work.

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The private datasets analyzed in this study are not publicly available due to restrictions imposed by data-sharing agreements with the contributing institutions. Access to these datasets is therefore not possible at this time.