Cardiovascular Institute, University of Pennsylvania, 3400 Civic Center Blvd, Smilow TRC 11th floor, Philadelphia, PA 19104, USA.
Department of Computer and Data Sciences, Case Western Reserve University, 10900 Euclid Avenue, Nord Hall Suite 500, Cleveland, OH 44106, USA.
Eur Heart J. 2021 Jun 21;42(24):2356-2369. doi: 10.1093/eurheartj/ehab241.
Allograft rejection is a serious concern in heart transplant medicine. Though endomyocardial biopsy with histological grading is the diagnostic standard for rejection, poor inter-pathologist agreement creates significant clinical uncertainty. The aim of this investigation is to demonstrate that cellular rejection grades generated via computational histological analysis are on-par with those provided by expert pathologists.
The study cohort consisted of 2472 endomyocardial biopsy slides originating from three major US transplant centres. The 'Computer-Assisted Cardiac Histologic Evaluation (CACHE)-Grader' pipeline was trained using an interpretable, biologically inspired, 'hand-crafted' feature extraction approach. From a menu of 154 quantitative histological features relating the density and orientation of lymphocytes, myocytes, and stroma, a model was developed to reproduce the 4-grade clinical standard for cellular rejection diagnosis. CACHE-grader interpretations were compared with independent pathologists and the 'grade of record', testing for non-inferiority (δ = 6%). Study pathologists achieved a 60.7% agreement [95% confidence interval (CI): 55.2-66.0%] with the grade of record, and pair-wise agreement among all human graders was 61.5% (95% CI: 57.0-65.8%). The CACHE-Grader met the threshold for non-inferiority, achieving a 65.9% agreement (95% CI: 63.4-68.3%) with the grade of record and a 62.6% agreement (95% CI: 60.3-64.8%) with all human graders. The CACHE-Grader demonstrated nearly identical performance in internal and external validation sets (66.1% vs. 65.8%), resilience to inter-centre variations in tissue processing/digitization, and superior sensitivity for high-grade rejection (74.4% vs. 39.5%, P < 0.001).
These results show that the CACHE-grader pipeline, derived using intuitive morphological features, can provide expert-quality rejection grading, performing within the range of inter-grader variability seen among human pathologists.
同种异体移植排斥反应是心脏移植医学中的一个严重问题。虽然心肌活检和组织学分级是排斥反应的诊断标准,但病理学家之间的一致性较差会导致临床存在较大的不确定性。本研究旨在证明通过计算组织学分析生成的细胞性排斥反应分级与专家病理学家提供的分级相当。
研究队列包括来自美国 3 个主要移植中心的 2472 份心肌活检切片。使用可解释的、受生物学启发的“手工制作”特征提取方法对“计算机辅助心脏组织学评估(CACHE)-分级器”进行了训练。从 154 个与淋巴细胞、心肌细胞和基质的密度和方向有关的定量组织学特征中,开发了一个模型,以重现细胞性排斥反应诊断的 4 级临床标准。CACHE 分级与独立病理学家和“记录等级”进行了比较,以测试非劣效性(δ=6%)。研究病理学家与记录等级的一致性为 60.7%(95%置信区间:55.2-66.0%),所有人类病理学家之间的两两一致性为 61.5%(95%置信区间:57.0-65.8%)。CACHE-Grader 达到了非劣效性的阈值,与记录等级的一致性为 65.9%(95%置信区间:63.4-68.3%),与所有人类病理学家的一致性为 62.6%(95%置信区间:60.3-64.8%)。CACHE-Grader 在内部和外部验证集的性能几乎相同(66.1%比 65.8%),能够抵御组织处理/数字化过程中不同中心的差异,并且对高级排斥反应具有更高的敏感性(74.4%比 39.5%,P<0.001)。
这些结果表明,CACHE 分级器管道使用直观的形态特征,可以提供专家级的排斥反应分级,其性能在人类病理学家之间的分级变异性范围内。