# Quantitative Imaging Clinical Validation Center at Moffitt Cancer Center

> **NIH NIH U01** · H. LEE MOFFITT CANCER CTR & RES INST · 2024 · $1,256,574

## Abstract

PROJECT SUMMARY/ABSTRACT
An overarching goal of cancer screening is to detect cancer at an early stage while it is localized, treatable, and
curable. However, cancer screening is associated with false positives, high rates of indeterminate findings,
overdiagnosis, and overtreatment, which are serious limitations that need to be addressed to improve early
detection efforts. Because medical imaging is a key component of early detection for many cancers, quantitative
imaging/radiomics can provide biomarkers to address many of these limitations with early detection. Our group,
Quantitative Imaging Clinical Validation Center at Moffitt Cancer Center (QICVC-MCC), helped pioneer image
biomarker approaches leveraged in the prior funding cycle to create the first and only EDRN Clinical Validation
Center (CVC) dedicated to the validation of image biomarkers. For breast cancer, we validated several breast
density-type risk markers and diagnostic models in women classified as BI-RADS 4, noting the three
subcategories within this classification were strong diagnostic markers, and constructed a bio-image repository
for this subgroup. For lung cancer, we conducted extensive studies applying conventional radiomics for risk
prediction, discrimination between malignant and benign nodules, distinguishing between indolent and
aggressive lung cancers, predicting tumor mutations, and predicting treatment response. In this renewal, we will
expand our CVC from validated conventional feature-based radiomics as a benchmark to compare end-to-end
deep learning (DL) methods, expand to other populations, and implement AI platforms for analyzing breast, lung,
and other organ site images. In breast imaging (Aim 1), we will expand our efforts from parametric modeling to
machine learning/DL for improved risk, early detection, and diagnostic predictions and continue our data
repository developments. In lung imaging (Aim 2), we will expand our efforts from lung cancer screening to
incidentally detected nodules and surgically resected early-stage lung cancer. Additionally, in Aim 3 we will seek
out additional opportunities within the EDRN to conduct studies of image biomarkers in other organ sites beyond
breast and lung (e.g., prostate, pancreas, and cutaneous) to address emerging Network objectives. The EDRN
has proven that it is greater than the sum of the individual projects. As such, in Aim 4 we propose to build a
repository for the housing and sharing of images, algorithms, radiomics, clinical data, and information on
biospecimens. In this CVC renewal, we will systematically validate radiomic features and novel image metrics
in the early detection of cancer. This research is significant because such information may be able to complement
existing clinical guidelines and lead to new strategies to apply noninvasive image biomarkers. The research of
the QICVC-MCC is performed at an NCI-Designated Comprehensive Cancer Center, which is an outstanding
environment to conduct such studi...

## Key facts

- **NIH application ID:** 10933414
- **Project number:** 5U01CA200464-07
- **Recipient organization:** H. LEE MOFFITT CANCER CTR & RES INST
- **Principal Investigator:** JOHN J HEINE
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $1,256,574
- **Award type:** 5
- **Project period:** 2016-07-22 → 2028-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10933414

## Citation

> US National Institutes of Health, RePORTER application 10933414, Quantitative Imaging Clinical Validation Center at Moffitt Cancer Center (5U01CA200464-07). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10933414. Licensed CC0.

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