# Comprehensive characterization of coronary atherosclerotic disease using photon-counting-detector dual-source CT and its impact on patient management

> **NIH NIH R01** · MAYO CLINIC ROCHESTER · 2021 · $657,862

## Abstract

PROJECT SUMMARY/ABSTRACT
Coronary artery disease (CAD) remains the main cause of morbidity and mortality in the United States. Cardiac
CT provides fast non-invasive assessment of CAD with a high sensitivity and negative predictive value –
provided that the lumen can be visualized. However, heavily calcified or stented coronary segments are non-
assessable, precluding non-invasive diagnosis of flow-limiting coronary plaques in an estimated 2 million U.S.
adults. In addition, the spatial resolution of state-of-the-art CT systems is insufficient for robust visualization of
features associated with high risk plaques. Further, while CT can quantitatively evaluate the impact of
obstructive CAD on myocardial function using dynamic perfusion imaging, this requires relatively high patient
radiation doses, which has limited widespread adoption. Considering the high personal and societal cost of
CAD, robust, accurate, non-invasive imaging of calcified and stented coronary arteries, high-risk plaque
features, and myocardial perfusion defects in a single, low-radiation-dose exam is critically needed.
Built by Siemens Healthcare, a first-of-its-kind, whole-body, photon-counting-detector (PCD) CT system was
installed in 2014 at the Mayo Clinic. With support from NIH award EB016966, we showed that the increased
iodine contrast-to-noise ratio, decreased electronic noise, spectral imaging capabilities, and improved spatial
resolution of PCD-CT relative to commercial CT enabled us to accurately measure increased vasa vasorum
density in injured swine carotid arterial walls, demonstrating the exceptional potential of PCD-CT in vascular
imaging. Because this system lacks cardiac imaging capabilities, our objective is to develop and validate a
PCD dual-source (DS) CT system and novel imaging algorithms to accurately assess CAD in humans,
especially in patients with heavily calcified, stented, or high-risk plaques, and to identify patients with
myocardial perfusion defects. Our premise is that the established benefits of PCD-CT, used with a DS
geometry and advanced noise reduction and material decomposition algorithms, can meet these objectives.
Our proposal is significant in many ways: the technology developments will benefit all of CT imaging; robust,
accurate, non-invasive imaging of calcified and stented coronary arteries, high-risk plaque features, and
myocardial perfusion defects in a single, low-radiation-dose exam will obviate the need for additional imaging,
reducing the overall time and cost to comprehensively evaluate CAD and its clinical significance. To extend the
demonstrated benefits of PCDs to cardiac CT will require numerous physics, engineering, and algorithm
innovations, including novel noise reduction and material decomposition algorithms using energy, spatial and
temporal domain redundancies, as well as deep learning. These advances will culminate in a large clinical
study to demonstrate not merely that the images are “better,” as is so often done, ...

## Key facts

- **NIH application ID:** 10150846
- **Project number:** 5R01EB028590-02
- **Recipient organization:** MAYO CLINIC ROCHESTER
- **Principal Investigator:** Shuai Leng
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $657,862
- **Award type:** 5
- **Project period:** 2020-05-01 → 2024-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10150846

## Citation

> US National Institutes of Health, RePORTER application 10150846, Comprehensive characterization of coronary atherosclerotic disease using photon-counting-detector dual-source CT and its impact on patient management (5R01EB028590-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10150846. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*