<p>Nomogram Including Elastography for Prediction of Contralateral Central Lymph Node Metastasis in Solitary Papillary Thyroid Carcinoma Preoperatively</p>

Abstract

Background It is controversial whether contralateral prophylactic central neck dissection (PCND) should be performed for patients with solitary and clinical lymph node negative (cN 0 ) papillary thyroid carcinoma (PTC) although routine ipsilateral PCND is required. Objective The aim of this study was to develop an improved nomogram including clinical features, ultrasound, and acoustic radiation force impulse (ARFI) elastography for the prediction of contralateral central lymph node metastasis (CLNM) in patients with solitary and cN 0 PTC in the preoperative period. Materials and Methods A total of 340 patients were retrospectively included as the training cohort and 170 patients as the external validation cohort. Patients were grouped according to the pathological results of contralateral CLNM. The association between the clinical characteristics, ultrasound, and ARFI elastography and the risk for contralateral CLNM were analyzed. A nomogram was established based on the result of multivariable logistic analysis to predict the risk of contralateral CLNM, which was assessed by internal and external validation. Results CLNM was found in 213 patients (41.8%), among whom 142 (27.8%) had ipsilateral CLNM and 95 (18.6%) had contralateral CLNM (including 68 (13.3%) with bilateral CLNM). Multivariable analysis revealed that patients with younger age, male gender, larger tumor size, closer distance from the capsule, microcalcification, and larger SWV mean were independent predictors associated with the contralateral CLNM ( P < 0.05), which was served as the basis of the nomogram. It showed good discrimination (C-index: 0.856) and calibration ( χ 2 = 9.028, P = 0.340, Hosmer–Lemeshow test) in the training cohort, and good discrimination was maintained in the external validation cohort (C-index: 0.792). Conclusion The nomogram utilizing the features of ultrasound combined with ARFI elastography in preoperatively predicting the risk of contralateral CLNM in patients with solitary and cN 0 PTC was established, which showed superior performance both in internal and external validation.

Patterns of lymph node metastasis in Level IIB and Contralateral Level VI for Papillary Thyroid Carcinoma with pN1b and Safety of low collar extended incision for neck dissection in Level II

“…Contralateral central lymph node dissection for unilateral PTC is controversial, mainly because of its low metastasis rate, and the occurrence of complications such as hypoparathyroidism and recurrent laryngeal nerve injury. Therefore, some scholars have looked for predictors of contralateral central cervical lymphatic metastasis [13,25].Han et al, create a prediction model for contralateral central cervical lymphatic metastases in unilateral PTC [26]. Kim et al suggested that ipsilateral central lymphatic metastasis could predict contralateral central lymphatic metastasis.…”

“…PTC is prone to central lymph node metastasis. Central lymph nodes can be divided into ipsilateral central lymph nodes and contralateral central lymph nodes [12].Routine prophylactic central lymph node dissection is required [2].However, for unilateral cancer, the dissection of the contralateral central lymph node is controversial, mainly because of low metastasis rate and postoperative complications [13,14].For PTC with N1b, there are few studies on contralateral central lymph node dissection of unilateral cancer.…”

Application of decision tree algorithms to predict central lymph node metastasis in well-differentiated papillary thyroid carcinoma based on multimodal ultrasound parameters: a retrospective study

“…There remains an existing need for improved CLNM prediction performance. Current studies have established a prediction model using a regression algorithm and nomogram, making it possible to forecast CLNM risk in clinical application (14)(15)(16). Machine learning (ML) algorithms have also been widely used in image diagnosis over the last few years.…”

Application of decision tree algorithms to predict central lymph node metastasis in well-differentiated papillary thyroid carcinoma based on multimodal ultrasound parameters: a retrospective study

“…It was recognized that there remains an existing need for improved CLNM prediction performance. Available studies have established the prediction model by regression algorithm and nomogram, making it possible to forecast CLNM risk in clinical application [14][15][16]. Machine learning (ML) algorithm has been widely used in image diagnosis over the last few years.…”