Evidence map›Paper›PMID 41720608›Full record

ArticleJournal for immunotherapy of cancer2026

QVT score, a radiomic biomarker of vascular complexity, enables prognostication and monitoring of NSCLC immunotherapy.

Young K Chae, Vamsidhar Velcheti, Kai Zhang, Amogh Hiremath, Liam Il-Young Chung, Omid Haji-Maghsoudi, Rhea Chitalia, Jeeyeon Lee, Haojia Li, Seyoung Lee and 11 more

Abstract readMulticenter Study
In one paragraph

Article in Journal for immunotherapy of cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

21 authors.

Young K Chae *Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA.
Vamsidhar Velcheti *Hematology and Oncology, Mayo Clinic in Florida, Jacksonville, Florida, USA.
Kai Zhang *Picture Health, Cleveland, Ohio, USA.ORCID http://orcid.org/0000-0002-5460-6150
Amogh HiremathPicture Health, Cleveland, Ohio, USA.
Liam Il-Young ChungFeinberg School of Medicine, Northwestern University, Chicago, Illinois, USA.ORCID http://orcid.org/0000-0001-6541-793X
Omid Haji-MaghsoudiPicture Health, Cleveland, Ohio, USA.
Rhea ChitaliaPicture Health, Cleveland, Ohio, USA.
Jeeyeon LeeFeinberg School of Medicine, Northwestern University, Chicago, Illinois, USA.
Haojia LiPicture Health, Cleveland, Ohio, USA.
Seyoung LeeFeinberg School of Medicine, Northwestern University, Chicago, Illinois, USA.
Pushkar MuthaWallace H Coulter Department of Biomedical Engineering, Emory University, Atlanta, Georgia, USA.
Rushil NagabhushanPicture Health, Cleveland, Ohio, USA.
David LevyPicture Health, Cleveland, Ohio, USA.
Diego CantorPicture Health, Cleveland, Ohio, USA.
Yuchan KimFeinberg School of Medicine, Northwestern University, Chicago, Illinois, USA.
Trevor CheungComputer Science, University of Waterloo, Waterloo, Ontario, Canada.
Haseok KimFeinberg School of Medicine, Northwestern University, Chicago, Illinois, USA.
Amit GuptaDivision of Cardiothoracic Imaging, Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA.
Trishan ArulPicture Health, Cleveland, Ohio, USA.
Anant MadabhushiPicture Health, Cleveland, Ohio, USA.ORCID http://orcid.org/0000-0002-4141-8548
Nathaniel BramanPicture Health, Cleveland, Ohio, USA nate@picturehealth.com.ORCID http://orcid.org/0000-0001-5603-0821

Funding

BLRD VA IK6 BX006185
6 · The paper itself

Abstract

backgroundImmune checkpoint inhibitors (ICIs) improve survival in advanced non-small cell lung cancer (NSCLC), yet current biomarkers such as programmed death-ligand 1 (PD-L1) expression and response criteria (Response Evaluation Criteria in Solid Tumors, RECIST, V.1.1) 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.

methodsThis retrospective, multicenter study analyzed 1,301 CT scans from 682 patients with ICI-treated NSCLC. 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.

resultsTwo 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 = 4.9×10⁻⁵). 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.

conclusionsQVT 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.

Indexed as

Carcinoma, Non-Small-Cell LungImmune Checkpoint InhibitorsImmunotherapyLung NeoplasmsAgedBiomarkers, TumorFemaleHumansMaleMiddle AgedPrognosisRadiomicsRetrospective StudiesBiomarkers, TumorImmune Checkpoint InhibitorsBiomarkerCombination therapyImmune Checkpoint InhibitorLung Cancer

Identifiers

PMID41720608
PMCPMC12927358

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.