# Broad Bandwidth Transducers for High Resolution Information Rich IVUS

> **NIH NIH R33** · CLEVELAND CLINIC LERNER COM-CWRU · 2024 · $388,924

## Abstract

Abstract
Intra-coronary imaging is a powerful clinical tool for decision making, treatment planning, and assessment of
stent deployment. It is also a powerful research tool for plaque progression/regression, drug treatments, and
device interventions. There are clear advantages and disadvantages of common intravascular imaging methods.
Intravascular ultrasound (IVUS) provides good resolution and allows one to measure lumen narrowing, wall
thickening, atheroma burden, and to a lesser extent stent deployment. Using spectral analysis of the RF signal
and machine learning, our group has developed software, which was later commercialized, to automatically
classify atherosclerotic tissues using IVUS images. Intravascular optical coherence tomography (IVOCT) has
better resolution than IVUS, enabling visualization and analysis of stent struts, thin caps of vulnerable plaques,
thrombosis, and plaque erosion. IVUS has better tissue penetration than IVOCT, enabling one to assess total
plaque burden. In addition, IVUS, unlike IVOCT, does not require one to flush the blood from the vessel prior to
imaging, a significant issue for patients, given the prevalence of kidney disease. These limitations suggest an
unmet need for a new intravascular imaging modality with attributes of both IVUS and IVOCT.
We will create a novel intravascular, high frequency, broadband, focused ultrasound system (H-IVUS), which
will address clinical needs identified for IVOCT and conventional IVUS. H-IVUS will have near-IVOCT resolution
to enable identification of critical small structures (e.g., thin caps and stent struts), while maintaining the ability
of ultrasound to penetrate tissue and evaluate soft plaque burden. It will have immediate clinical impact by ena-
bling clinicians to plan and optimize procedures that have already shown to benefit from intravascular imaging:
determine true vessel size, identify stent landing zones to choose correct stent lengths, identify plaque morphol-
ogies to guide debulking, detect edge dissection, determine stent malapposition, and detect thin caps. In addi-
tion, the high bandwidth of H-IVUS provides both fundamental and harmonic bands, which are expected to im-
prove tissue classification, as determined by us in carotid arteries. We will use broadband wavelet analysis of
RF, spatial structures in images, and machine learning to determine if wideband H-IVUS can provide improved
segmentation to improve recognition of the important clinical landmarks and provide superior automated plaque
classification over current VH IVUS®, which uses only narrow RF-fundamental-band stationary spectral analysis.
In addition, our manufacturing-friendly design should greatly reduce cost, thereby limiting this barrier to utiliza-
tion. Specifically, we will develop a catheter-based H-IVUS PCB using a focused polymeric ultrasonic transducer;
develop algorithms which utilize broadband RF and harmonic imaging to analyze tissue types w and rigorously
compare results to...

## Key facts

- **NIH application ID:** 10972748
- **Project number:** 4R33HL156154-03
- **Recipient organization:** CLEVELAND CLINIC LERNER COM-CWRU
- **Principal Investigator:** AARON J FLEISCHMAN
- **Activity code:** R33 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $388,924
- **Award type:** 4N
- **Project period:** 2022-06-10 → 2027-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10972748

## Citation

> US National Institutes of Health, RePORTER application 10972748, Broad Bandwidth Transducers for High Resolution Information Rich IVUS (4R33HL156154-03). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10972748. Licensed CC0.

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