Recent advances in computerized imaging and its vital roles in liver disease diagnosis, preoperative planning, and interventional liver surgery: A review

Abstract

The earliest and most accurate detection of the pathological manifestations of hepatic diseases ensures effective treatments and thus positive prognostic outcomes. In clinical settings, screening and determining the extent of a pathology are prominent factors in preparing remedial agents and administering appropriate therapeutic procedures. Moreover, in a patient undergoing liver resection, a realistic preoperative simulation of the subject-specific anatomy and physiology also plays a vital part in conducting initial assessments, making surgical decisions during the procedure, and anticipating postoperative results. Conventionally, various medical imaging modalities, e.g. , computed tomography, magnetic resonance imaging, and positron emission tomography, have been employed to assist in these tasks. In fact, several standardized procedures, such as lesion detection and liver segmentation, are also incorporated into prominent commercial software packages. Thus far, most integrated software as a medical device typically involves tedious interactions from the physician, such as manual delineation and empirical adjustments, as per a given patient. With the rapid progress in digital health approaches, especially medical image analysis, a wide range of computer algorithms have been proposed to facilitate those procedures. They include pattern recognition of a liver, its periphery, and lesion, as well as pre- and postoperative simulations. Prior to clinical adoption, however, software must conform to regulatory requirements set by the governing agency, for instance, valid clinical association and analytical and clinical validation. Therefore, this paper provides a detailed account and discussion of the state-of-the-art methods for liver image analyses, visualization, and simulation in the literature. Emphasis is placed upon their concepts, algorithmic classifications, merits, limitations, clinical considerations, and future research trends.

Imaging Characteristics and Diagnostic Challenges of Alveolar Hydatid Disease in The Liver: A Comprehensive Analysis

“…By offering a comprehensive analysis of lesion appearance, calcification patterns, enhancement characteristics, and associated complications, we enhance the understanding of AHD's radiological profile. This is crucial for guiding clinicians in making accurate diagnoses and formulating effective management plans (Horkaew et al, 2023;Khullar et al, 2015;Kumar et al, 2023;Mehta et al, 2016). Our findings underscore the importance of considering AHD in the differential diagnosis of liver lesions, particularly in endemic areas.…”

“…While imaging techniques have improved diagnosis, there is a need for further research into specific imaging characteristics and molecular diagnostics. Management strategies must balance surgical and pharmacological approaches, underlined by effective public health measures to prevent transmission (Horkaew et al, 2023). Continued research and awareness are crucial in improving outcomes for individuals affected by this rare but severe parasitic infection (Horkaew et al, 2023).…”

“…Management strategies must balance surgical and pharmacological approaches, underlined by effective public health measures to prevent transmission (Horkaew et al, 2023). Continued research and awareness are crucial in improving outcomes for individuals affected by this rare but severe parasitic infection (Horkaew et al, 2023). Despite advancements in imaging technology, there remains a need for in-depth studies to understand the specific imaging characteristics of AHD better (Horkaew et al, 2023;Vernuccio et al, 2021).…”

“…Continued research and awareness are crucial in improving outcomes for individuals affected by this rare but severe parasitic infection (Horkaew et al, 2023). Despite advancements in imaging technology, there remains a need for in-depth studies to understand the specific imaging characteristics of AHD better (Horkaew et al, 2023;Vernuccio et al, 2021). This study aims to bridge this gap by providing a detailed analysis of the CT and MRI findings in confirmed cases of AHD.…”