A digital pathology model for predicting radioiodine-avid metastases on initial post-therapeutic 131I scan in patients with papillary thyroid cancer

Autor: Yuhang Xue, Minghui Zheng, Xinyu Wu, Bo Li, Xintao Ding, Shuxin Liu, Simiao Liu, Qiuyu Liu, Yongju Gao
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Druh dokumentu: article
ISSN: 2045-2322
DOI: 10.1038/s41598-024-78459-3
Popis: Abstract Accurate postoperative assessment is critical for optimizing 131I therapy in patients with papillary thyroid cancer (PTC). This study aimed to develop a pathology model utilizing postoperative digital pathology slides to predict lymph node and/or distant metastases on post-therapeutic 131I scan after initial 131I treatment in PTC patients. A retrospective analysis was conducted on 229 PTC patients who underwent total or near-total thyroidectomy and subsequent 131I treatment after levothyroxine (LT4) withdrawal between January 2022 and August 2023. The pathology model was developed through two stages: patch-level prediction and WSI-level prediction. The clinical model was constructed using statistically significant variables identified from univariate and multivariate logistic regression analysis. Of the 229 patients, 19.6% (45/229) exhibited 131I-avid metastatic foci in post-therapeutic 131I scan. Multifactorial analysis identified stimulated thyroglobulin (sTg) as the sole independent risk factor. The AUC of the pathology model in the training and test cohorts were 0.976 (95% CI 0.948–1.000) and 0.805 (95% CI 0.660–0.951), respectively, which were significantly higher than the clinical model (AUC 0.652 and 0.548, Pall
Databáze: Directory of Open Access Journals
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