Background: Approximately 15% of patients experience post-hepatectomy liver failure after major hepatectomy. Poor hepatocyte uptake of gadoxetate disodium, a magnetic resonance imaging contrast agent, may be a predictor of post-hepatectomy liver failure.
Methods: A retrospective cohort study of patients undergoing major hepatectomy (≥3 segments) with a preoperative gadoxetate disodium-enhanced magnetic resonance imaging was conducted.
Purpose: Secondary usage of patient data has recently become of increasing interest for the development and application of computer analytic techniques. Strict oversight of these data is required and the individual patients themselves are integral to providing guidance. We sought to understand patients' attitudes to sharing their imaging data for research purposes.
View Article and Find Full Text PDFBackground: Atherosclerotic intraplaque hemorrhage (IPH) is a source of free hemoglobin that binds the haptoglobin protein and forms a complex cleared by CD163 macrophages. Compared to the other common haptoglobin genotypes, hemoglobin-haptoglobin2-2 complex has the lowest affinity for tissue macrophages resulting in lower rate of hemoglobin uptake and increased oxidative burden. We hypothesized that haptoglobin2-2 patients' failure to clear hemoglobin results in a greater prevalence and progression of IPH.
View Article and Find Full Text PDFComput Methods Programs Biomed
February 2016
Unlabelled: Anatomical cine cardiovascular magnetic resonance (CMR) imaging is widely used to assess the systolic cardiac function because of its high soft tissue contrast. Assessment of diastolic LV function has not regularly been performed due the complex and time consuming procedures. This study presents a semi-automated assessment of the left ventricular (LV) diastolic function using anatomical short-axis cine CMR images.
View Article and Find Full Text PDFAutomating the detection and localization of segmental (regional) left ventricle (LV) abnormalities in magnetic resonance imaging (MRI) has recently sparked an impressive research effort, with promising performances and a breadth of techniques. However, despite such an effort, the problem is still acknowledged to be challenging, with much room for improvements in regard to accuracy. Furthermore, most of the existing techniques are labor intensive, requiring delineations of the endo- and/or epi-cardial boundaries in all frames of a cardiac sequence.
View Article and Find Full Text PDFMed Image Comput Comput Assist Interv
January 2013
The cardiac ejection fraction (EF) depends on the volume variation of the left ventricle (LV) cavity during a cardiac cycle, and is an essential measure in the diagnosis of cardiovascular diseases. It is often estimated via manual segmentation of several images in a cardiac sequence, which is prohibitively time consuming, or via automatic segmentation, which is a challenging and computationally expensive task that may result in high estimation errors. In this study, we propose to estimate the EF in real-time directly from image statistics using machine learning technique.
View Article and Find Full Text PDFMed Image Comput Comput Assist Interv
November 2011
Early and accurate detection of Left Ventricle (LV) regional wall motion abnormalities significantly helps in the diagnosis and followup of cardiovascular diseases. We present a regional myocardial abnormality detection framework based on image statistics. The proposed framework requires a minimal user interaction, only to specify initial delineation and anatomical landmarks on the first frame.
View Article and Find Full Text PDF