Failing to Make the Grade: Conventional Cardiac Allograft Rejection Grading Criteria Are Inadequate for Predicting Rejection Severity

Author:

Arabyarmohammadi Sara1,Yuan Cai1,Viswanathan Vidya Sankar1ORCID,Lal Priti2,Feldman Michael D.3,Fu Pingfu4ORCID,Margulies Kenneth B.5ORCID,Madabhushi Anant67ORCID,Peyster Eliot G.5ORCID

Affiliation:

1. Department Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta (S.A., C.Y., V.S.V.).

2. Department of Pathology and Laboratory Medicine at the Hospital of the University of Pennsylvania (P.L.), Perelman School of Medicine, University of Pennsylvania, Philadelphia.

3. Department of Pathology and Laboratory Medicine, School of Medicine, Indiana University, Indianapolis (M.D.F.).

4. Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH (P.F.).

5. Cardiovascular Research Institute, Department of Medicine (K.B.M., E.G.P.), Perelman School of Medicine, University of Pennsylvania, Philadelphia.

6. Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta (A.M.).

7. Atlanta Veterans Affairs Medical Center, Decatur, GA (A.M.).

Abstract

BACKGROUND: Cardiac allograft rejection is the leading cause of early graft failure and is a major focus of postheart transplant patient care. While histological grading of endomyocardial biopsy samples remains the diagnostic standard for acute rejection, this standard has limited diagnostic accuracy. Discordance between biopsy rejection grade and patient clinical trajectory frequently leads to both overtreatment of indolent processes and delayed treatment of aggressive ones, spurring the need to investigate the adequacy of the current histological criteria for assessing clinically important rejection outcomes. METHODS: N=2900 endomyocardial biopsy images were assigned a rejection grade label (high versus low grade) and a clinical trajectory label (evident versus silent rejection). Using an image analysis approach, n=370 quantitative morphology features describing the lymphocytes and stroma were extracted from each slide. Two models were constructed to compare the subset of features associated with rejection grades versus those associated with clinical trajectories. A proof-of-principle machine learning pipeline—the cardiac allograft rejection evaluator—was then developed to test the feasibility of identifying the clinical severity of a rejection event. RESULTS: The histopathologic findings associated with conventional rejection grades differ substantially from those associated with clinically evident allograft injury. Quantitative assessment of a small set of well-defined morphological features can be leveraged to more accurately reflect the severity of rejection compared with that achieved by the International Society of Heart and Lung Transplantation grades. CONCLUSIONS: Conventional endomyocardial samples contain morphological information that enables accurate identification of clinically evident rejection events, and this information is incompletely captured by the current, guideline-endorsed, rejection grading criteria.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3