Intravascular ultrasound (IVUS) is recommended in guiding coronary intervention. The segmentation of coronary lumen and external elastic membrane (EEM) borders in IVUS images is a key step, but the... Show moreIntravascular ultrasound (IVUS) is recommended in guiding coronary intervention. The segmentation of coronary lumen and external elastic membrane (EEM) borders in IVUS images is a key step, but the manual process is time-consuming and error-prone, and suffers from inter-observer variability. In this paper, we propose a novel perceptual organisation-aware selective transformer framework that can achieve accurate and robust segmentation of the vessel walls in IVUS images. In this framework, temporal context-based feature encoders extract efficient motion features of vessels. Then, a perceptual organisation-aware selective transformer module is proposed to extract accurate boundary information, supervised by a dedicated boundary loss. The obtained EEM and lumen segmentation results will be fused in a temporal constraining and fusion module, to determine the most likely correct boundaries with robustness to morphology. Our proposed methods are extensively evaluated in non-selected IVUS sequences, including normal, bifurcated, and calcified vessels with shadow artifacts. The results show that the proposed methods outperform the state-of-the-art, with a Jaccard measure of 0.92 for lumen and 0.94 for EEM on the IVUS 2011 open challenge dataset. This work has been integrated into a software QCU-CMS1 to automatically segment IVUS images in a user-friendly environment. Show less
Kishi, S.; Magalhaes, T.A.; Cerci, R.J.; Zimmermann, E.; Matheson, M.B.; Vavere, A.; ... ; Arbab-Zadeh, A. 2020
Purpose To provide comparative prognostic information of coronary atherosclerotic plaque volume and stenosis assessment in patients with suspected coronary artery disease (CAD). Methods We followed... Show morePurpose To provide comparative prognostic information of coronary atherosclerotic plaque volume and stenosis assessment in patients with suspected coronary artery disease (CAD). Methods We followed 372 patients with suspected or known CAD enrolled in the CORE320 study for 2 years after baseline 320-detector row cardiac CT scanning and invasive quantitative coronary angiography (QCA). CT images were analyzed for coronary calcium scanning (CACS), semi-automatically derived total percent atheroma volume (PAV), segment stenosis score (SSS), in addition to traditional stenosis assessment (>= 50%) by CT and QCA for (1) 30-day revascularization and (2) major adverse cardiac events (MACE). Area under the receiver operating characteristic curve (AUC) was used to compare accuracy of risk prediction. Results Sixty percent of patients had obstructive CAD by QCA with 23% undergoing 30-day revascularization and 9% experiencing MACE at 2 years. Most late events (20/32) were revascularization procedures. Prediction of 30-day revascularization was modest (AUC range 0.67-0.78) but improved after excluding patients with known CAD (AUC range 0.73-0.86, p < 0.05 for all). Similarly, prediction of MACE improved after excluding patients with known CAD (AUC range 0.58-0.73 vs. 0.63-0.77). CT metrics of atherosclerosis burden performed overall similarly but stenosis assessment was superior for predicting 30-day revascularization. Conclusions Angiographic and coronary atherosclerotic plaque metrics perform only modestly well for predicting 30-day revascularization and 2-year MACE in high risk patients but improve after excluding patients with known CAD. Atherosclerotic plaque metrics did not yield incremental value over stenosis assessment for predicting events that predominantly consisted of revascularization procedures. Show less
