Browsing by Author "Ramasamy, Anantharaman"

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Cross-Sectional Angle Prediction of Lipid-Rich and Calcified Tissue on Computed Tomography Angiography Images
(Springer Heidelberg, 2024) Zhang, Xiaotong; Broersen, Alexander; Sokooti, Hessam; Ramasamy, Anantharaman; Kitslaar, Pieter; Parasa, Ramya; Dijkstra, Jouke
PurposeThe assessment of vulnerable plaque characteristics and distribution is important to stratify cardiovascular risk in a patient. Computed tomography angiography (CTA) offers a promising alternative to invasive imaging but is limited by the fact that the range of Hounsfield units (HU) in lipid-rich areas overlaps with the HU range in fibrotic tissue and that the HU range of calcified plaques overlaps with the contrast within the contrast-filled lumen. This paper is to investigate whether lipid-rich and calcified plaques can be detected more accurately on cross-sectional CTA images using deep learning methodology.MethodsTwo deep learning (DL) approaches are proposed, a 2.5D Dense U-Net and 2.5D Mask-RCNN, which separately perform the cross-sectional plaque detection in the Cartesian and polar domain. The spread-out view is used to evaluate and show the prediction result of the plaque regions. The accuracy and F1-score are calculated on a lesion level for the DL and conventional plaque detection methods.ResultsFor the lipid-rich plaques, the median and mean values of the F1-score calculated by the two proposed DL methods on 91 lesions were approximately 6 and 3 times higher than those of the conventional method. For the calcified plaques, the F1-score of the proposed methods was comparable to those of the conventional method. The median F1-score of the Dense U-Net-based method was 3% higher than that of the conventional method.ConclusionThe two methods proposed in this paper contribute to finer cross-sectional predictions of lipid-rich and calcified plaques compared to studies focusing only on longitudinal prediction. The angular prediction performance of the proposed methods outperforms the convincing conventional method for lipid-rich plaque and is comparable for calcified plaque.
Electrocardiographically Gated Intravascular Image Segmentation Enables More Reproducible Volumetric Analysis of Atheroma Burden
(Elsevier Science inc, 2021) Erdogan, Emrah; Huang, Xingru; Cooper, Jackie; Jain, Ajay; Ramasamy, Anantharaman; Bajaj, Retesh; Bourantas, Christos
End-Diastolic Segmentation of Intravascular Ultrasound Images Enables More Reproducible Volumetric Analysis of Atheroma Burden
(Wiley, 2022) Erdogan, Emrah; Huang, Xingru; Cooper, Jackie; Jain, Ajay; Ramasamy, Anantharaman; Bajaj, Retesh; Bourantas, Christos V.
Background Volumetric intravascular ultrasound (IVUS) analysis is currently performed at a fixed frame interval, neglecting the cyclic changes in vessel dimensions occurring during the cardiac cycle that can affect the reproducibility of the results. Analysis of end-diastolic (ED) IVUS frames has been proposed to overcome this limitation. However, at present, there is lack of data to support its superiority over conventional IVUS. Objectives The present study aims to compare the reproducibility of IVUS volumetric analysis performed at a fixed frame interval and at the ED frames, identified retrospectively using a novel deep-learning methodology. Methods IVUS data acquired from 97 vessels were included in the present study; each vessel was segmented at 1 mm interval (conventional approach) and at ED frame twice by an expert analyst. Reproducibility was tested for the following metrics; normalized lumen, vessel and total atheroma volume (TAV), and percent atheroma volume (PAV). Results The mean length of the analyzed segments was 50.0 +/- 24.1 mm. ED analysis was more reproducible than the conventional analysis for the normalized lumen (mean difference: 0.76 +/- 4.03 mm(3) vs. 1.72 +/- 11.37 mm(3); p for the variance of differences ratio < 0.001), vessel (0.30 +/- 1.79 mm(3) vs. -0.47 +/- 10.26 mm(3); p < 0.001), TAV (-0.46 +/- 4.03 mm(3) vs. -2.19 +/- 14.39 mm(3); p < 0.001) and PAV (-0.12 +/- 0.59% vs. -0.34 +/- 1.34%; p < 0.001). Results were similar when the analysis focused on the 10 mm most diseased segment. The superiority of the ED approach was due to a more reproducible detection of the segment of interest and to the fact that it was not susceptible to the longitudinal motion of the IVUS probe and the cyclic changes in vessel dimensions during the cardiac cycle. Conclusions ED IVUS segmentation enables more reproducible volumetric analysis and quantification of TAV and PAV that are established end points in longitudinal studies assessing the efficacy of novel pharmacotherapies. Therefore, it should be preferred over conventional IVUS analysis as its higher reproducibility is expected to have an impact on the sample size calculation for the primary end point.
Implications of Coronary Calcification on the Assessment of Plaque Pathology: a Comparison of Computed Tomography and Multimodality Intravascular Imaging
(Springer, 2025) Yap, Nathan Angelo Lecaros; Ramasamy, Anantharaman; Tanboga, Ibrahim Halil; He, Xingwei; Cap, Murat; Bajaj, Retesh; Bourantas, Christos V.
Objectives This study aimed to investigate the impact of calcific (Ca) on the efficacy of coronary computed coronary angiography (CTA) in evaluating plaque burden (PB) and composition with near-infrared spectroscopy-intravascular ultrasound (NIRS-IVUS) serving as the reference standard. Materials and methods Sixty-four patients (186 vessels) were recruited and underwent CTA and 3-vessel NIRS-IVUS imaging (NCT03556644). Expert analysts matched and annotated NIRS-IVUS and CTA frames, identifying lumen and vessel wall borders. Tissue distribution was estimated using NIRS chemograms and the arc of Ca on IVUS, while in CTA Hounsfield unit cut-offs were utilized to establish plaque composition. Plaque distribution plots were compared at segment-, lesion-, and cross-sectional-levels. Results Segment- and lesion-level analysis showed no effect of Ca on the correlation of NIRS-IVUS and CTA estimations. However, at the cross-sectional level, Ca influenced the agreement between NIRS-IVUS and CTA for the lipid and Ca components (p-heterogeneity < 0.001). Proportional odds model analysis revealed that Ca had an impact on the per cent atheroma volume quantification on CTA compared to NIRS-IVUS at the segment level (p-interaction < 0.001). At lesion level, Ca affected differences between the modalities for maximum PB, remodelling index, and Ca burden (p-interaction < 0.001, 0.029, and 0.002, respectively). Cross-sectional-level modelling demonstrated Ca's effect on differences between modalities for all studied variables (p-interaction <= 0.002). Conclusion Ca burden influences agreement between NIRS-IVUS and CTA at the cross-sectional level and causes discrepancies between the predictions for per cent atheroma volume at the segment level and maximum PB, remodelling index, and Ca burden at lesion-level analysis. Clinical relevance statement Coronary calcification affects the quantification of lumen and plaque dimensions and the characterization of plaque composition coronary CTA. This should be considered in the analysis and interpretation of CTAs performed in patients with extensive Ca burden. Key Points Coronary CT Angiography is limited in assessing coronary plaques by resolution and blooming artefacts. Agreement between dual-source CT angiography and NIRS-IVUS is affected by a Ca burden for the per cent atheroma volume. Advanced CT imaging systems that eliminate blooming artefacts enable more accurate quantification of coronary artery disease and characterisation of plaque morphology.
Wall Shear Stress Estimated by 3d-Qca Can Predict Cardiovascular Events in Lesions With Borderline Negative Fractional Flow Reserve
(Elsevier Ireland Ltd, 2021) Tufaro, Vincenzo; Safi, Hannah; Torii, Ryo; Koo, Bon-Kwon; Kitslaar, Pieter; Ramasamy, Anantharaman; Bourantas, Christos, V
Background and aims: There is some evidence of the implications of wall shear stress (WSS) derived from three-dimensional quantitative coronary angiography (3D-QCA) models in predicting adverse cardiovascular events. This study investigates the efficacy of 3D-QCA-derived WSS in detecting lesions with a borderline negative fractional flow reserve (FFR: 0.81-0.85) that progressed and caused events. Methods: In this retrospective cohort study, we identified 548 patients who had at least one lesion with an FFR 0.81-0.85 and complete follow-up data; 293 lesions (286 patients) with suitable angiographic characteristics were reconstructed using a dedicated 3D-QCA software and included in the analysis. In the reconstructed models blood flow simulation was performed and the value of 3D-QCA variables and WSS distribution in predicting events was examined. The primary endpoint of the study was the composite of cardiac death, target lesion related myocardial infarction or clinically indicated target lesion revascularization. Results: During a median follow-up of 49.4 months, 37 events were reported. Culprit lesions had a greater area stenosis [(AS), 66.1% (59.5-72.3) vs 54.8% (46.5-63.2), p<0.001], smaller minimum lumen area [(MLA), 1.66 mm(2) (1.45-2.30) vs 2.10 mm(2) (1.69-2.70), p=0.011] and higher maximum WSS [9.0 Pa (5.10-12.46) vs 5.0 Pa (3.37-7.54), p < 0.001] than those that remained quiescent. In multivariable analysis, AS [hazard ratio (HR): 1.06, 95% confidence interval (CI): 1.03-1.10, p=0.001] and maximum WSS (HR: 1.08, 95% CI: 1.02-1.14, p=0.012) were the only independent predictors of the primary endpoint. Lesions with an increased AS (>= 58.6%) that were exposed to high WSS (>= 7.69Pa) were more likely to progress and cause events (27.8%) than those with a low AS exposed to high WSS (7.4%) or those exposed to low WSS that had increased (12.8%) or low AS (2.7%, p<0.001). Conclusions: This study for the first time highlights the potential value of 3D-QCA-derived WSS in detecting, among lesions with a borderline negative FFR, those that cause cardiovascular events.