# Tumor Detection and Classification using QUS Technology's Structure Function

> **NIH NIH R01** · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · 2024 · $428,275

## Abstract

Project Summary
Our collaborative basic science and clinical team will elucidate the mechanism(s) of ultrasound scattering in
biological tissues by systematically studying a significant component of ultrasonic scattering, the structure
function (SF), using solid tumors from animal models and hepatocellular carcinoma (HCC) in adult human
subjects, and thereby improve the accuracy of Quantitative Ultrasound (QUS, the quantification of tissue
microstructure) techniques in noninvasive tumor detection and classification. The SF concept arises in the
context of wave scattering: the scattered power of a collection of scatterers depends not only on the
properties of the individual scatterers (modeled by the form factor), but also on the spatial correlation among
the scatterers (modeled by the SF).
 Structure function is new: The SF has largely been overlooked wherein the scatterer positions are
assumed to be uncorrelated (i.e., SF is unity). The unity SF assumption is not appropriate for dense
scattering media (e.g., solid tumors and most parenchymal tissues) or sparse media showing special
patterns of scatterer distribution. Non-unity SF has mostly been studied on simple scattering media such as
physical phantoms and blood. This investigation is new, and numerous basic science and technical
innovations will be pursued. Our goal is to systematically study the SF using animal solid tumors and human
liver and HCC data to improve ultrasonic scattering models and ultimately the diagnostic value of QUS
outcomes. The research makes contributions at the basic science level to elucidate the scattering
mechanisms by SF model development and validate using animal tumor models in vivo, and at the
translational level to improve the accuracy of tumor detection/classification using human liver and HCC data.
 Central hypotheses and aims: 1) The SF is critical to elucidate ultrasonic scattering mechanism(s)
in biological tissues. 2) The SF is sensitive to certain disease types and stages. 3) The accuracy of QUS to
noninvasively detect/classify tissues/tumors in vivo will be significantly improved when the SF is utilized
compared to when it is not utilized. To test these hypotheses, we have designed a research program with the
following aims: Aim 1. Develop theoretical SF models that match scatterer spatial distributions of
tumor/tissue types under investigation. Aim 2. Validate SF models using solid tumors in mice/rats. Aim 3.
Test the diagnostic value of SF using clinical human liver data from 100 nonalcoholic fatty liver disease
(NAFLD) participants, 150 cirrhotic participants, 50 HCC participants, and 150 normal participants.
 Summary/Impact: The SF is an ultrasound echo component that is determined by and sensitive to
the architectural pattern of tissue microstructure (e.g., liver cell nuclei). The SF will be a clinically valuable
imaging biomarker for disease diagnosis because many disease processes (e.g., HCC) remarkably change
to a unique architectural pattern an...

## Key facts

- **NIH application ID:** 10817232
- **Project number:** 5R01CA226528-06
- **Recipient organization:** UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
- **Principal Investigator:** William D. O'Brien
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $428,275
- **Award type:** 5
- **Project period:** 2019-04-10 → 2026-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10817232

## Citation

> US National Institutes of Health, RePORTER application 10817232, Tumor Detection and Classification using QUS Technology's Structure Function (5R01CA226528-06). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10817232. Licensed CC0.

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