A nomogram for predicting adverse pathologic features in low-risk papillary thyroid microcarcinoma.

BACKGROUND: Identifying risk factors for adverse pathologic features in low-risk papillary thyroid microcarcinoma (PTMC) can provide valuable insights into the necessity of surgical or non-surgical treatment. This study aims to develop a nomogram for predicting the probability of adverse pathologic features in low-risk PTMC patients. METHODS: A total of 662 patients with low-risk PTMC who underwent thyroid surgery were retrospectively analyzed in Qilu Hospital of Shandong University from May 2019 to December 2021. Logistic regression analysis was used to determine the risk factors for adverse pathologic features, and a nomogram was constructed based on these factors. RESULTS: Most PTMC patients with these adverse pathologic features had tumor diameters greater than 0.6 cm (p < 0.05). Other factors (age, gender, family history of thyroid cancer, history of autoimmune thyroiditis, and BRAFV600E mutation) had no significant correlation with adverse pathologic features (p > 0.05 each). The nomogram was drawn to provide a quantitative and convenient tool for predicting the risk of adverse pathologic features based on age, gender, family history of thyroid cancer, autoimmune thyroiditis, tumor size, and BRAFV600E mutation in low-risk PTMC patients. The areas under curves (AUC) were 0.645 (95% CI 0.580-0.702). Additionally, decision curve analysis (DCA) and calibration curves were used to evaluate the clinical benefits of this nomogram, presenting a high net benefit. CONCLUSION: Tumor size > 0.60 cm was identified as an independent risk factor for adverse pathologic features in low-risk PTMC patients. The nomogram had a high predictive value and consistency based on these factors.

Deep learning prediction model for central lymph node metastasis in papillary thyroid microcarcinoma based on cytology.

Controversy exists regarding whether patients with low-risk papillary thyroid microcarcinoma (PTMC) should undergo surgery or active surveillance; the inaccuracy of the preoperative clinical lymph node status assessment is one of the primary factors contributing to the controversy. It is imperative to accurately predict the lymph node status of PTMC before surgery. We selected 208 preoperative fine-needle aspiration (FNA) liquid-based preparations of PTMC as our research objects; all of these instances underwent lymph node dissection and, aside from lymph node status, were consistent with low-risk PTMC. We separated them into two groups according to whether the postoperative pathology showed central lymph node metastases. The deep learning model was expected to predict, based on the preoperative thyroid FNA liquid-based preparation, whether PTMC was accompanied by central lymph node metastases. Our deep learning model attained a sensitivity, specificity, positive prediction value (PPV), negative prediction value (NPV), and accuracy of 78.9% (15/19), 73.9% (17/23), 71.4% (15/21), 81.0% (17/21), and 76.2% (32/42), respectively. The area under the receiver operating characteristic curve (value was 0.8503. The predictive performance of the deep learning model was superior to that of the traditional clinical evaluation, and further analysis revealed the cell morphologies that played key roles in model prediction. Our study suggests that the deep learning model based on preoperative thyroid FNA liquid-based preparation is a reliable strategy for predicting central lymph node metastases in thyroid micropapillary carcinoma, and its performance surpasses that of traditional clinical examination.

Papillary thyroid microcarcinoma with multiple pulmonary metastases following lung cancer surgery: a case report.

BACKGROUND: Distant metastasis is extremely rare for papillary thyroid microcarcinoma (PTMC) without lymph node metastasis or extrathyroidal extension, for which active surveillance (AS) is indicated. The evaluation of distant metastases in low-risk PTMC is controversial. A case of PTMC in which AS would have been performed if chest CT and lung surgery had not been performed is reported. CASE PRESENTATION: The patient was a 71-year-old woman undergoing follow-up in the Department of Thoracic Surgery at our hospital for multiple frosted glass shadows in both lung fields for one and a half years. To make a definitive diagnosis, thoracoscopic right middle lobectomy and left upper partial lobectomy were performed 4 and 6 months earlier, respectively. In both resected specimens, lung adenocarcinoma and small metastasis of papillary thyroid carcinoma (PTC) were found. The patient was transferred to our department for a thorough examination for PTC. Ultrasonography was performed to search for the primary lesion, and it showed an irregular hypoechoic mass of 4 mm and 6 mm in the middle of the right lobe of the thyroid gland. The patient was diagnosed with PTC. Its clinical stage was T1a (m) N0 M1 (stage IVC). Total thyroidectomy and prophylactic central node dissection were performed. The pathological diagnosis was PTC (typical type) pT1a (m) N0. Postoperatively, she received radioactive iodine therapy. CONCLUSIONS: We experienced an extremely rare case and struggled to determine a treatment plan. We might be aware that lung metastases could develop in low-risk PTMC.