Lozanski Gerard, Pennell Michael, Shana'ah Arwa, Zhao Weiqiang, Gewirtz Amy, Racke Frederick, Hsi Eric, Simpson Sabrina, Mosse Claudio, Alam Shadia, Swierczynski Sharon, Hasserjian Robert P, Gurcan Metin N
Department of Pathology, The Ohio State University, Columbus, OH, USA.
Division of Biostatistics, College of Public Health, The Ohio State University, Columbus, OH, USA.
J Pathol Inform. 2013 Oct 29;4:30. doi: 10.4103/2153-3539.120747. eCollection 2013.
Pathologists grade follicular lymphoma (FL) cases by selecting 10, random high power fields (HPFs), counting the number of centroblasts (CBs) in these HPFs under the microscope and then calculating the average CB count for the whole slide. Previous studies have demonstrated that there is high inter-reader variability among pathologists using this methodology in grading.
The objective of this study was to explore if newly available digital reading technologies can reduce inter-reader variability.
IN THIS STUDY, WE CONSIDERED THREE DIFFERENT READING CONDITIONS (RCS) IN GRADING FL: (1) Conventional (glass-slide based) to establish the baseline, (2) digital whole slide viewing, (3) digital whole slide viewing with selected HPFs. Six board-certified pathologists from five different institutions read 17 FL slides in these three different RCs.
Although there was relative poor consensus in conventional reading, with lack of consensus in 41.2% of cases, which was similar to previously reported studies; we found that digital reading with pre-selected fields improved the inter-reader agreement, with only 5.9% lacking consensus among pathologists.
Digital whole slide RC resulted in the worst concordance among pathologists while digital whole slide reading selected HPFs improved the concordance. Further studies are underway to determine if this performance can be sustained with a larger dataset and our automated HPF and CB detection algorithms can be employed to further improve the concordance.
病理学家通过选择10个随机高倍视野(HPF)对滤泡性淋巴瘤(FL)病例进行分级,在显微镜下计数这些高倍视野中的中心母细胞(CB)数量,然后计算整个玻片的平均CB计数。先前的研究表明,病理学家使用这种方法进行分级时,读者间的变异性很高。
本研究的目的是探讨新出现的数字阅读技术是否可以减少读者间的变异性。
在本研究中,我们在对FL进行分级时考虑了三种不同的阅读条件(RC):(1)传统(基于玻璃玻片)以建立基线,(2)数字全玻片观察,(3)数字全玻片观察并选择高倍视野。来自五个不同机构的六位获得委员会认证的病理学家在这三种不同的RC下阅读了17张FL玻片。
尽管在传统阅读中达成的共识相对较少,41.2%的病例缺乏共识,这与先前报道的研究相似;我们发现,预先选择视野的数字阅读提高了读者间的一致性,病理学家之间只有5.9%的病例缺乏共识。
数字全玻片RC在病理学家之间的一致性最差,而数字全玻片阅读并选择高倍视野提高了一致性。正在进行进一步的研究,以确定在更大的数据集上这种性能是否可以持续,以及我们的自动高倍视野和中心母细胞检测算法是否可以用于进一步提高一致性。