Nuclear score evaluation in follicular-patterned thyroid lesions using optical and digital environments

ENDOCRINE(2022)

引用 2|浏览6
暂无评分
摘要
Introduction The subjective evaluation of nuclear features in follicular-patterned lesions of the thyroid is a reason for diagnosis discordance. The assessment of nuclear features also varies whether the observation is performed optically or digitally. Our objective was to study the concordance among pathologists regarding the nuclear score (NS) evaluation in a series of follicular-patterned lesions, using optical versus three digital scanning protocols. Methods Three pathologists evaluated the NS in a 3mm(2) area randomly selected from 20 hematoxylin-eosin slides representative of the respective 20 follicular-patterned thyroid lesions. The NS evaluation was performed using optical and three different scanning protocols in two scanners: P1000_20x, P1000_40x and DP200_20x. Kappa statistic (kappa) and intraclass correlation coefficient (ICC) were obtained for intra- and interpathologist concordance. Results We recorded a good agreement among pathologists in the optical evaluation of the NS (ICC of 0.73). The concordance between optical versus digital observation had an almost perfect agreement for P1000_20x [kappa = 0.85 (0.67-1.02); p < 0.0001] and a substantial agreement for both P1000_40x [kappa = 0.69 (0.43-0.95) p = 0.002] and DP200_20x [kappa = 0.77 (0.57-0.97); p = 0.001]. The P1000_20x protocol had the best intrapathologist concordance with the optical method, classified as almost perfect agreement for pathologists A (80%) and B (85%), and substantial agreement for pathologist C (70%). Conclusion Digital observation of the WSI is valid for the NS evaluation in follicular-patterned thyroid lesions, with good agreement among pathologists and between optical and scanning protocols. Performance studies and validation procedures cannot be avoided in this setting to prevent diagnostic discordance due to the scanning process.
更多
查看译文
关键词
Thyroid,Nuclear score,Digital pathology
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要