Literature DB >> 25919317

Regional assessment of LV wall in infarcted heart using tagged MRI and cardiac modelling.

Zeinab Jahanzad1, Yih Miin Liew, Mehmet Bilgen, Robert A McLaughlin, Chen Onn Leong, Kok Han Chee, Yang Faridah Abdul Aziz, Ngie Min Ung, Khin Wee Lai, Siew-Cheok Ng, Einly Lim.   

Abstract

A segmental two-parameter empirical deformable model is proposed for evaluating regional motion abnormality of the left ventricle. Short-axis tagged MRI scans were acquired from 10 healthy subjects and 10 postinfarct patients. Two motion parameters, contraction and rotation, were quantified for each cardiac segment by fitting the proposed model using a non-rigid registration algorithm. The accuracy in motion estimation was compared to a global model approach. Motion parameters extracted from patients were correlated to infarct transmurality assessed with delayed-contrast-enhanced MRI. The proposed segmental model allows markedly improved accuracy in regional motion analysis as compared to the global model for both subject groups (1.22-1.40 mm versus 2.31-2.55 mm error). By end-systole, all healthy segments experienced radial displacement by ~25-35% of the epicardial radius, whereas the 3 short-axis planes rotated differently (basal: 3.3°; mid:  -1° and apical:  -4.6°) to create a twisting motion. While systolic contraction showed clear correspondence to infarct transmurality, rotation was nonspecific to either infarct location or transmurality but could indicate the presence of functional abnormality. Regional contraction and rotation derived using this model could potentially aid in the assessment of severity of regional dysfunction of infarcted myocardium.

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Year:  2015        PMID: 25919317     DOI: 10.1088/0031-9155/60/10/4015

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  3 in total

1.  Construction of a Diagnostic Model for Lymph Node Metastasis of the Papillary Thyroid Carcinoma Using Preoperative Ultrasound Features and Imaging Omics.

Authors:  Chao Zhang; Lihua Cheng; Weiwen Zhu; Jian Zhuang; Tong Zhao; Xiaoqin Li; Wenfeng Wang
Journal:  J Healthc Eng       Date:  2022-02-08       Impact factor: 2.682

2.  Comparative studies of deep learning segmentation models for left ventricle segmentation.

Authors:  Muhammad Ali Shoaib; Khin Wee Lai; Joon Huang Chuah; Yan Chai Hum; Raza Ali; Samiappan Dhanalakshmi; Huanhuan Wang; Xiang Wu
Journal:  Front Public Health       Date:  2022-08-25

3.  Development and External Validation of a Nomogram for Predicting Overall Survival in Stomach Cancer: A Population-Based Study.

Authors:  Haonan Ji; Huita Wu; Yu Du; Li Xiao; Yiqin Zhang; Qiuhua Zhang; Xin Wang; Wenfeng Wang
Journal:  J Healthc Eng       Date:  2021-09-24       Impact factor: 2.682

  3 in total

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