Literature DB >> 35933241

Left Ventricular Segmental Strain Identifies Unique Myocardial Deformation Patterns After Intrinsic and Extrinsic Stressors in Mice.

Amina Kunovac1, Quincy A Hathaway2, Emily N Burrage3, Tyler Coblentz4, Eric E Kelley5, Partho P Sengupta6, John M Hollander1, Paul D Chantler7.   

Abstract

We used segmental strain analysis to evaluate whether intrinsic (diet-induced obesity [DIO]) and extrinsic (unpredictable chronic mild stress [UCMS]) stressors can alter deformational patterns of the left ventricle. Six-week-old male C57BL/6J mice were randomized into the lean or obese group (n = 24/group). Mice underwent 12 wk of DIO with a high-fat diet (HFD). At 18 wk, lean and obese mice were further randomized into UCMS and non-UCMS groups (UCMS, 7 h/d, 5 d/wk, for 8 wk). Echocardiography was performed at baseline (6 wk), post-HFD (18 wk) and post-UCMS (26 wk). Machine learning was applied to the DIO and UCMS groups. There was robust predictive accuracy (area under the receiver operating characteristic curve [AUC] = 0.921) when comparing obese with lean mice, with radial strain changes in the lateral (-64%, p ≤ 0.001) and anterior free (-53%, p < 0.001) walls being most informative. The ability to predict mice that underwent UCMS, irrespective of diet, was assessed (AUC = 0.886), revealing longitudinal strain rate of the anterior midwall and radial strain of the posterior septal wall as the top features. The wall segments indicate a predilection for changes in deformation patterns to the free wall (DIO) and septal wall (UCMS), indicating disease-specific alterations to the myocardium.
Copyright © 2022 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Chronic stress; High-fat diet; Machine learning; Obesity; Unpredictable chronic mild stress

Mesh:

Year:  2022        PMID: 35933241      PMCID: PMC9427680          DOI: 10.1016/j.ultrasmedbio.2022.06.004

Source DB:  PubMed          Journal:  Ultrasound Med Biol        ISSN: 0301-5629            Impact factor:   3.694


  32 in total

Review 1.  Interaction revisited: the difference between two estimates.

Authors:  Douglas G Altman; J Martin Bland
Journal:  BMJ       Date:  2003-01-25

Review 2.  Fact or Artifact in Two-Dimensional Echocardiography: Avoiding Misdiagnosis and Missed Diagnosis.

Authors:  Philippe B Bertrand; Robert A Levine; Eric M Isselbacher; Pieter M Vandervoort
Journal:  J Am Soc Echocardiogr       Date:  2016-03-09       Impact factor: 5.251

Review 3.  Validity, reliability and utility of the chronic mild stress model of depression: a 10-year review and evaluation.

Authors:  P Willner
Journal:  Psychopharmacology (Berl)       Date:  1997-12       Impact factor: 4.530

4.  Value of speckle tracking echocardiography for detection of clinically silent left ventricular dysfunction in patients with β-thalassemia.

Authors:  Mozhgan Parsaee; Sedigheh Saedi; Pegah Joghataei; Azita Azarkeivan; Zahra Alizadeh Sani
Journal:  Hematology       Date:  2017-04-12       Impact factor: 2.269

5.  Left Ventricular global longitudinal strain predicts heart failure readmission in acute decompensated heart failure.

Authors:  Simone Romano; Ibrahim N Mansour; Mayank Kansal; Hana Gheith; Zachary Dowdy; Carolyn A Dickens; Cassandra Buto-Colletti; June M Chae; Hussam H Saleh; Thomas D Stamos
Journal:  Cardiovasc Ultrasound       Date:  2017-03-15       Impact factor: 2.062

Review 6.  Artificial intelligence and echocardiography.

Authors:  M Alsharqi; W J Woodward; J A Mumith; D C Markham; R Upton; P Leeson
Journal:  Echo Res Pract       Date:  2018-12-01

7.  Early changes in right ventricular longitudinal function in chronic asymptomatic alcoholics revealed by two-dimensional speckle tracking echocardiography.

Authors:  Sisi Meng; Lijuan Guo; Guangsen Li
Journal:  Cardiovasc Ultrasound       Date:  2016-04-19       Impact factor: 2.062

8.  Speckle tracking echocardiography to assess regional ventricular function in patients with apical hypertrophic cardiomyopathy.

Authors:  María Cristina Saccheri; Tomás Francisco Cianciulli; Luis Alberto Morita; Ricardo José Méndez; Martín Alejandro Beck; Juan Enrique Guerra; Alberto Cozzarin; Luciana Jimena Puente; Lorena Romina Balletti; Jorge Alberto Lax
Journal:  World J Cardiol       Date:  2017-04-26

9.  Ensemble machine learning approach for screening of coronary heart disease based on echocardiography and risk factors.

Authors:  Jingyi Zhang; Huolan Zhu; Yongkai Chen; Chenguang Yang; Huimin Cheng; Yi Li; Wenxuan Zhong; Fang Wang
Journal:  BMC Med Inform Decis Mak       Date:  2021-06-11       Impact factor: 2.796

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.