Yih Miin Liew

Ischemic heart disease remains a major contributor to mortality in Malaysia, with non-elective percutaneous coronary intervention (PCI) frequently performed in high-risk acute coronary syndrome (ACS) patients. Using nationwide registry data (2007–2020), we evaluated 29,521 patients and compared seven machine learning (ML) models for predicting in-hospital, 30-day, and 1-year mortality. Models were developed in a training cohort and externally validated using hospital-level (TEST1) and prospective temporal (TEST2) cohorts. After logistic recalibration, discrimination for in-hospital mortality ranged from 0.927 to 0.943 (TEST1) and 0.865–0.884 (TEST2). For 30-day mortality, ROC-AUC ranged from 0.902 to 0.923 (TEST1) and 0.753–0.838 (TEST2), and for 1-year mortality from 0.833 to 0.859 (TEST1) and 0.750–0.801 (TEST2). Calibration remained acceptable, and decision curve analysis demonstrated positive net benefit across clinically relevant thresholds. Cross-model stability analysis consistently identified age, haemodynamic status, and renal function as key predictors.

Hill's force-velocity relationship is a fundamental property of myocardial contraction, yet its mechanical role in patient-specific left ventricular hypertrophy (LVH) remains underexplored. This study systematically evaluated the consequences of including versus omitting Hill-type velocity dependence in magnetic resonance imaging (MRI)-derived three-dimensional (3D) finite element (FE) models of three hypertrophic left ventricles subjected to stage 3 hypertensive loading. Incorporating velocity dependence moderated peak systolic pressure, tempered early fibre shortening, sustained mid-systolic deformation, and yielded smoother pressure-volume behaviour with improved energetic efficiency. In contrast, omitting velocity dependence amplified systolic pressure generation, accelerated contraction prematurely, and increased stroke work by 15%. Regional analysis across all three patient-specific LVH models consistently demonstrated that the absence of velocity dependence elevated fibre stress by 15-25%, most prominently in subendocardial and high-curvature regions, accompanied by reduced mid-systolic strain. A biophysical damping formulation was implemented to ensure numerical stability across heterogeneous LVH geometries. Together, these findings provide mechanistic insight into how sarcomere shortening dynamics govern regional ventricular adaptation and advance the physiological fidelity of cardiac simulations under severe hypertensive conditions.

Objective. The Ozaki procedure utilizes glutaraldehyde-treated autologous pericardium for aortic valve (AV) neocuspidization (AVNeo), offering hemodynamic performance comparable to native valves without long-term anticoagulation. Approach. This review synthesizes evidence from 39 studies, up to September 2024, to evaluate post-procedural AV biomechanics. Medical imaging modalities (echocardiography, magnetic resonance image, and computed tomography) and numerical simulations (finite element model, computational fluid dynamics, and fluid-structure interaction (FSI)) are analyzed for assessing hemodynamic and structural parameters for postoperative management and surgical optimization. Main results. Imaging modalities excel in real-time morphology evaluation, while simulations reveal flow and stress distributions inaccessible via clinical tools. Current limitations include imaging resolution, geometry reconstruction and material property model. Future researches emphasize integrating patient-specific imaging data with advanced FSI to enhance valve durability predictions and refine procedural guidelines. Significance. This work serves as a link between clinical observations and computational insights, guiding personalized treatment strategies for AVNeo patients.

Neointimal coverage and stent apposition, as assessed from intravascular optical coherence tomography (IVOCT) images, are crucial for optimizing percutaneous coronary intervention (PCI). Existing state-of-the-art computer algorithms designed to automate this analysis often treat lumen and stent segmentations as separate target entities, applicable only to a single stent type and overlook automation of preselecting which pullback segments need segmentation, thus limit their practicality. This study aimed for an algorithm capable of intelligently handling the entire IVOCT pullback across different phases of PCI and clinical scenarios, including the presence and coexistence of metal and bioresorbable vascular scaffold (BVS), stent types. We propose a multi-task deep learning model, named TriVOCTNet, that automates image classification/selection, lumen segmentation and stent struts segmentation within a single network by integrating classification, regression and pixel-level segmentation models. This approach allowed a single-network, single-pass implementation with all tasks parallelized for speed and convenience. A joint loss function was specifically designed to optimize each task in situations where each task may or may not be present. Evaluation on 4,746 images achieved classification accuracies of 0.999, 0.997, and 0.998 for lumen, BVS, and metal stent features, respectively. The lumen segmentation performance showed a Euclidean distance error of 21.72 μm and Dice’s coefficient of 0.985. For BVS struts segmentation, the Dice’s coefficient was 0.896, and for metal stent struts segmentation, the precision was 0.895 and sensitivity was 0.868. TriVOCTNet highlights its clinical potential due to its fast and accurate results, and simplicity in handling all tasks and scenarios through a single system.

Background: Marine ecosystems, covering 70% of Earth’s surface, hold immense biodiversity and potential for biomaterials. Cuttlefish bone (CB) and marine resources have gained attention as eco-friendly biomaterials. Objectives: We aim to comprehensively study biomedical applications of CB-derived materials. By evaluating both in vivo and in vitro investigations, the review seeks to uncover the diverse potential of CB in the biomedical field. Methods: A comprehensive search of electronic databases yielded 51 articles from 2408 studies. These studies encompassed in vivo animal studies and in vitro investigations. Results: In vivo studies employed for bone repair, dorsal subcutaneous defects, thermal wound healing, muscle injections, and avian blood testing. In vitro studies focused on HAp synthesis, scaffold development, dental material enhancement, and antimicrobial properties. Risk of bias assessments revealed varying degrees of methodological quality in both animal and in vitro studies, underscoring the need for standardised reporting and rigorous study design in future research. Conclusions: This review fills a gap in the literature by providing a comprehensive overview of the applications of CB-derived materials in the biomedical field. Additionally, it offers valuable insights for researchers, clinicians, and policymakers interested in sustainable and effective biomaterials for diverse medical purposes, advancing the fields of regenerative medicine and dentistry.

Background: Increased afterload in aortic stenosis (AS) induces left ventricle (LV) remodeling to preserve a normal ejection fraction. This compensatory response can become maladaptive and manifest with motion abnormality. It is a clinical challenge to identify contractile and relaxation dysfunction during early subclinical stage to prevent irreversible deterioration.Purpose: To evaluate the changes of regional wall dynamics in 3D + time domain as remodeling progresses in AS.Study Type: Retrospective.Population: A total of 31 AS patients with reduced and preserved ejection fraction (14 AS_rEF: 7 male, 66.5 [7.8] years old; 17 AS_pEF: 12 male, 67.0 [6.0] years old) and 15 healthy (6 male, 61.0 [7.0] years old).Field Strength/Sequence: 1.5 T Magnetic resonance imaging/steady state free precession and late-gadolinium enhancement sequences.Assessment: Individual LV models were reconstructed in 3D + time domain and motion metrics including wall thickening (TI), dyssynchrony index (DI), contraction rate (CR), and relaxation rate (RR) were automatically extracted and associated with the presence of scarring and remodeling.Statistical Tests: Shapiro-Wilk: data normality; Kruskal-Wallis: significant difference (P < 0.05); ICC and CV: variability; Mann-Whitney: effect size.Results: AS_rEF group shows distinct deterioration of cardiac motions compared to AS_pEF and healthy groups (TIAS_rEF: 0.92 [0.85] mm, TIAS_pEF: 5.13 [1.99] mm, TIhealthy: 3.61 [1.09] mm, ES: 0.48-0.83; DIAS_rEF: 17.11 [7.89]%, DIAS_pEF: 6.39 [4.04]%, DIhealthy: 5.71 [1.87]%, ES: 0.32-0.85; CRAS_rEF: 8.69 [6.11] mm/second, CRAS_pEF: 16.48 [6.70] mm/second, CRhealthy: 10.82 [4.57] mm/second, ES: 0.29-0.60; RRAS_rEF: 8.45 [4.84] mm/second; RRAS_pEF: 13.49 [8.56] mm/second, RRhealthy: 9.31 [2.48] mm/second, ES: 0.14-0.43). The difference in the motion metrics between healthy and AS_pEF groups were insignificant (P-value = 0.16-0.72). AS_rEF group was dominated by eccentric hypertrophy (47.1%) with concomitant scarring. Conversely, AS_pEF group was dominated by concentric remodeling and hypertrophy (71.4%), which could demonstrate hyperkinesia with slight wall dyssynchrony than healthy. Dysfunction of LV mechanics corresponded to the presence of myocardial scarring (54.9% in AS), which reverted the compensatory mechanisms initiated and performed by LV remodeling.Data Conclusion: The proposed 3D + time modeling technique may distinguish regional motion abnormalities between AS_pEF, AS_rEF, and healthy cohorts, aiding clinical diagnosis and monitoring of AS progression. Subclinical myocardial dysfunction is evident in early AS despite of normal EF.