Computational Perspectives on Left Ventricular Hypertrophy: A Clinical Review with Informatics Driven Case Analyses

Abstract

Left ventricular hypertrophy (LVH) occurs when the heart muscle thickens over time. This often comes from high blood pressure, problems with heart valves or ongoing strain on the heart. In this review, we explore LVH from both a doctor's viewpoint and through the lens of computational health informatics. Tools like echocardiography and ECG are still key for spotting it. But cardiac MRI stands out as the best way to measure the heart's muscle mass accurately. We present seven real-life cases, including two already published. These show different causes, tough spots in diagnosis and how treatments turn out. We also talk about new enablers, such as AI that aids in reading ECGs, tools for calculating left ventricular mass index, and systems that support decisions. This isn't about creating fresh algorithms. Instead, we focus on how informatics can help make sense of LVH and improve patient care. Our insights push for personized treatments. They also encourage smarter ways to use everyday clinical tools and wearable devices in order to improve the overall heart health.