The past half-century has seen an amazing trend. Linked advances in vascular biology, endovascular
intervention and drug delivery have dropped morality from cardiovascular disease 4.5 fold. NIH support has
blessed us with involvement in these endeavors and we are humbled by the accomplishments of the community.
Yet, atherosclerotic disease is not eradicated, we do not fully grasp the vascular biology of obstructive vascular
diseases, and interventional therapy is not at a standardized consensus. There is much to be learned in all areas
especially for complex lesions where lesion modification is deemed indispensable. Increasingly sophisticated
methods (e.g. orbital atherectomy, lithotripsy etc.) modify complex plaque before angioplasty or implantation of
devices like stents, and yet modifications are still guided by operator personal experience. There are no criteria
as to which technology to use and when, what constitutes sufficient modification and how to balance benefits
and risks. Intravascular imaging can help visualize lesions peri-modification, but provides no functional feedback,
forcing even experienced interventionalists to guide intricate procedures by sensation (touch, feel, even sound).
What is needed and what our team of academic and industrial scientists, engineers and clinicians aims to
develop are mechanistic insight into the biology of modification and tools for predicting function from imaging
and validated criteria for treatment outcomes. We will relate alterations in lesion micro-morphology (calcium, lipid,
fibrous, fibro-fatty content) to changes in spatial micro-mechanical (compliance, stress) and local drug delivery
(uptake, retention) response, and correlate image-based quantification of lesion micro-morphology to
interventional outcome, providing a framework to predict and optimize, therapy.
Our aims are to (1) Quantify changes in clinical lesion micro-morphology of complex arterial disease as a
function of lesion modification using deep-learning-based image analysis, and investigate how initial lesion state
can predict micro-morphological alterations for different modifications. (2) Use image processing and lesion-
specific inverse modelling to examine effects of lesion modification on micro-mechanics and local drug
distribution in excised human lesions, and (3) compare predictions with clinical performance after angioplasty
and stenting. Combining aims 1 and 2 with computational virtual stent implantation we will predict vascular
responses after modification of vascular morphology, and compare these predictions to outcomes from clinical
trials that have imaging and longitudinal follow-up. In whole we will distinguish clinical outcomes that arise from
optimization of lumen dimensions, from optimization of micro-morphology, -mechanics and drug distribution.
The significance of our work lies in providing a mechanistic framework to explore increasing use of lesion
modification pre-intervention and a means to leverage such insight to guide and optimize effect. The novelty is
in using imaging and computational methods developed with the past NIH support to achieve this understanding.
We are honored that our science may have clinical impact in treating complex vascular disease.