Translational Immunology Research Program, University of Helsinki, Helsinki, Finland.
Department of Pathology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
Mod Pathol. 2022 Sep;35(9):1168-1174. doi: 10.1038/s41379-022-01070-2. Epub 2022 Mar 25.
The ability of thymic histopathology to predict the long-term impact of thymectomy in non-thymomatous myasthenia gravis (NTMG) is mainly uncharted. We applied digital pathology to quantitatively characterize differences of thymic histology between early-onset (EOMG) and late-onset MG (LOMG) and to investigate the role of thymic changes for thymectomy outcomes in MG. We analyzed 83 thymic H&E slides from thymectomized NTMG patients, of which 69 had EOMG and 14 LOMG, using digital pathology open-access software QuPath. We compared the results to the retrospectively assessed clinical outcome at two years after thymectomy and at the last follow-up visit where complete stable remission and minimal use of medication were primary outcomes. The automated annotation pipeline was an effective and reliable way to analyze thymic H&E samples compared to manual annotation with mean intraclass correlation of 0.80. The ratio of thymic tissue to stroma and fat was increased in EOMG compared to LOMG (p = 8.7e-07), whereas no difference was observed in the ratio of medulla to cortex between these subtypes. AChRAb seropositivity correlated with the number of ectopic germinal centers (eGC; p = 0.00067) but not with other histological areas. Patients with an increased number of eGCs had better post-thymectomy outcomes at two years after thymectomy (p = 0.0035) and at the last follow-up (p = 0.0267). ROC analysis showed that eGC area predicts thymectomy outcome in EOMG with an AUC of 0.79. Digital pathology can thus help in providing a predictive tool to the clinician, the eGC number, to guide the post-thymectomy treatment decisions in EOMG patients.
胸腺组织病理学预测非胸腺瘤型重症肌无力(NMGT)患者胸腺切除术长期疗效的能力尚不清楚。我们应用数字病理学方法定量分析早发型(EOMG)和晚发型 MG(LOMG)患者胸腺组织学差异,并探讨胸腺变化对 MG 患者胸腺切除术结果的作用。我们使用数字病理学开放获取软件 QuPath 分析了 83 例 NMGT 患者的胸腺苏木精-伊红(H&E)切片,其中 69 例为 EOMG,14 例为 LOMG。我们将结果与术后 2 年和最后一次随访的回顾性评估临床结果进行比较,完全稳定缓解和最小药物使用是主要结果。与手动注释相比,自动注释流水线是一种有效且可靠的分析胸腺 H&E 样本的方法,其平均组内相关系数为 0.80。与 LOMG 相比,EOMG 的胸腺组织与基质和脂肪的比例增加(p=8.7e-07),而这些亚型的皮质与髓质比例无差异。AChRAb 阳性与异位生发中心(eGC;p=0.00067)的数量相关,但与其他组织学区域无关。eGC 数量增加的患者在胸腺切除术后 2 年(p=0.0035)和最后一次随访时(p=0.0267)的术后效果更好。ROC 分析显示,eGC 面积对 EOMG 的胸腺切除术结果具有预测价值,AUC 为 0.79。因此,数字病理学可以帮助临床医生提供一种预测工具,即 eGC 数量,以指导 EOMG 患者的术后治疗决策。