A tumor vasculature–based imaging biomarker for predicting response and survival in patients with lung cancer treated with checkpoint inhibitors-Reference-Cited by-同舟云学术

A tumor vasculature–based imaging biomarker for predicting response and survival in patients with lung cancer treated with checkpoint inhibitors

Published:2022-11-25 Issue:47 Volume:8 Page:
ISSN:2375-2548
Container-title:Science Advances
language:en
Short-container-title:Sci. Adv.

Author:

Alilou Mehdi¹^ORCID,Khorrami Mohammadhadi²^ORCID,Prasanna Prateek³^ORCID,Bera Kaustav¹^ORCID,Gupta Amit⁴^ORCID,Viswanathan Vidya Sankar²,Patil Pradnya⁵,Velu Priya Darsini⁶^ORCID,Fu Pingfu⁷^ORCID,Velcheti Vamsidhar⁸,Madabhushi Anant²⁹^ORCID

Affiliation:

1. Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA.

2. Department of Biomedical Engineering, Emory University, Atlanta, GA 30322, USA.

3. Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY 11790, USA.

4. University Hospitals Cleveland Medical Center, Case Western Reserve University, Cleveland, OH 44106, USA.

5. Department of Solid Tumor Oncology, Cleveland Clinic, Cleveland, OH 44106, USA.

6. Pathology and Laboratory Medicine, Weill Cornell Medicine Physicians, New York, NY 10021, USA.

7. Department of Population and Quantitative Health Sciences, CWRU, Cleveland, OH 44106, USA.

8. Department of Hematology and Oncology, NYU Langone Health, New York, NY 10016, USA.

9. Atlanta Veterans Administration Medical Center, Atlanta, GA 30322, USA.

Abstract

Tumor vasculature is a key component of the tumor microenvironment that can influence tumor behavior and therapeutic resistance. We present a new imaging biomarker, quantitative vessel tortuosity (QVT), and evaluate its association with response and survival in patients with non–small cell lung cancer (NSCLC) treated with immune checkpoint inhibitor (ICI) therapies. A total of 507 cases were used to evaluate different aspects of the QVT biomarkers. QVT features were extracted from computed tomography imaging of patients before and after ICI therapy to capture the tortuosity, curvature, density, and branching statistics of the nodule vasculature. Our results showed that QVT features were prognostic of OS (HR = 3.14, 0.95% CI = 1.2 to 9.68, P = 0.0006, C-index = 0.61) and could predict ICI response with AUCs of 0.66, 0.61, and 0.67 on three validation sets. Our study shows that QVT imaging biomarker could potentially aid in predicting and monitoring response to ICI in patients with NSCLC.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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