1. A digital pathology model for predicting radioiodine-avid metastases on initial post-therapeutic 131 I scan in patients with papillary thyroid cancer.
- Author
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Xue Y, Zheng M, Wu X, Li B, Ding X, Liu S, Liu S, Liu Q, and Gao Y
- Subjects
- Humans, Female, Male, Middle Aged, Adult, Retrospective Studies, Aged, Thyroglobulin blood, Thyroglobulin metabolism, Neoplasm Metastasis, Lymphatic Metastasis, Young Adult, Iodine Radioisotopes therapeutic use, Thyroid Cancer, Papillary pathology, Thyroid Cancer, Papillary therapy, Thyroid Cancer, Papillary radiotherapy, Thyroid Neoplasms pathology, Thyroid Neoplasms radiotherapy, Thyroid Neoplasms therapy, Thyroidectomy
- Abstract
Accurate postoperative assessment is critical for optimizing
131 I 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-therapeutic131 I scan after initial131 I treatment in PTC patients. A retrospective analysis was conducted on 229 PTC patients who underwent total or near-total thyroidectomy and subsequent131 I 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) exhibited131 I-avid metastatic foci in post-therapeutic131 I 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 < 0.05). This model has the potential to serve as a valuable tool for clinicians in tailoring treatment strategies, thereby optimizing therapeutic outcomes for PTC patients., (© 2024. The Author(s).)- Published
- 2024
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