# Macro-vasculature: A Novel Image Biomarker of Lung Cance

> **NIH NIH R01** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2020 · $415,606

## Abstract

ABSTRACT
 Lung cancer remains the leading cause of cancer related deaths in the United States and worldwide. The
high mortality associated with lung cancer is in part due to underutilization of and limited access to lung cancer
screening that impedes early diagnosis. The apprehension of some clinicians and policymakers towards lung
cancer screening with low-dose computed tomography (LDCT) exams is based on concerns of lead-time bias
and high false-positive rate. The development of a robust lung cancer biomarker that reduces screen-detected
false positives and improves classification of indeterminate nodules would relieve some of the concerns related
to lung cancer screening. Although investigations show that screening with LDCT scans may reduce lung cancer
mortality by 20% compared to chest x-ray, it is reported that ~96% of suspicious findings (mostly indeterminate
nodules) turn out to be non-cancerous (false positives). Clinical management of screen-detected indeterminate
nodules often leads to unnecessary, costly, and potentially harmful follow-up procedures (e.g., follow-up CT
scan, positron emission tomography (PET)/CT exam, invasive biopsies). We have developed an exciting and
novel image-based macro-vasculature feature to discriminate benign from malignant nodules. We propose to
further develop the feature and validate it across a range of CT protocols and scans from other institutions. We
will also integrate the macro-vasculature features with clinical information (e.g., age, gender, smoking history,
lung function) and evaluate the model's ability to discriminate benign from malignant screen-detected
indeterminate nodules. We will investigate if a radiologist's classification of indeterminate nodules improves with
the output of the integrative model compared to classification without the integrative model. The success of this
project may lead to a novel and robust lung cancer biomarker to accurately assess screen-detected
indeterminate nodules that can significantly reduce the number of unnecessary follow-up procedures during lung
cancer screening.

## Key facts

- **NIH application ID:** 9883874
- **Project number:** 1R01CA237277-01A1
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Jiantao Pu
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $415,606
- **Award type:** 1
- **Project period:** 2020-01-13 → 2025-01-01

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9883874

## Citation

> US National Institutes of Health, RePORTER application 9883874, Macro-vasculature: A Novel Image Biomarker of Lung Cance (1R01CA237277-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9883874. Licensed CC0.

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