Predicting central lymph node metastasis in patients with papillary thyroid carcinoma based on ultrasound radiomic and morphological features analysis

Abstract

Objectives To build a combined model based on the ultrasound radiomic and morphological features, and evaluate its diagnostic performance for preoperative prediction of central lymph node metastasis (CLNM) in patients with papillary thyroid carcinoma (PTC). Method A total of 295 eligible patients, who underwent preoperative ultrasound scan and were pathologically diagnosed with unifocal PTC were included at our hospital from October 2019 to July 2022. According to ultrasound scanners, patients were divided into the training set (115 with CLNM; 97 without CLNM) and validation set (45 with CLNM; 38 without CLNM). Ultrasound radiomic, morphological, and combined models were constructed using multivariate logistic regression. The diagnostic performance was assessed by the area under the curve (AUC) of the receiver operating characteristic curve, accuracy, sensitivity, and specificity. Results A combined model was built based on the morphology, boundary, length diameter, and radiomic score. The AUC was 0.960 (95% CI, 0.924–0.982) and 0.966 (95% CI, 0.901–0.993) in the training and validation set, respectively. Calibration curves showed good consistency between prediction and observation, and DCA demonstrated the clinical benefit of the combined model. Conclusion Based on ultrasound radiomic and morphological features, the combined model showed a good performance in predicting CLNM of patients with PTC preoperatively.

Quantitative ultrasound radiomics analysis to evaluate lymph nodes in patients with cancer: a systematic review

“…All 47 studies are summarized in Supplementary Table 1 [2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48] and were divided based on the tumor of origin: breast cancer, head and neck cancer, and cervical cancer. Most of the papers were published between 2019 and 2022 (n = 19 articles), and the analyses were conducted using MATLAB, R software, SPSS, OriginPro, a papillary thyroid carcinoma (PTC), cervical LN metastasis (LNM) prediction system (custom-built, n = 3), MIPAV, and Mazda.…”

“…Feature extraction was mainly performed with PyRadiomics, ITK-SNAP, LifeX, MedCalc, ImageJ, PASW and Prism. The values of the area under the curve (AUC), sensitivity, specificity, and accuracy are summarized in ▶ Table 1 [2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48].…”

“…Head and neck cancer studies mainly focused on thyroid cancer, specifically PTC and head and neck squamous cell carcinoma (HNSCC). We identified 20 studies investigating LN status in patients with PTC [13,14,15,16,17,18,19,20,21,22,23,32,35,36,37,38,46,47,48], one study on follicular thyroid carcinoma [25], one on treatment outcome prediction in head and neck malignancies [44], and three studies on HNSCC [29,30,31].…”

“…The overall performance in the PTC context is heterogeneous, with one failed study, three studies that achieve 0.621, 0.600 and 0.65 AUC values, respectively [13,35,37], nine studies that range between 0.727 and 0.881 [15,16,17,18,19,21,36,44,46] and seven with an AUC over 0.900 [17,20,22,23,31,38,47].…”

“…As demonstrated by several recent studies, to bypass this limitation, a multimodal approach combining US-radiomics with additional data (demographic data, clinicopathological information, genetics, or shear-wave elastography) is considered better for predicting LN status and patient risk in thyroid carcinoma [15,16,17,18,46,47,48]. Specifically, methods based on unifying US-radiomics with biochemical results and US findings, the radiomics nomogram that incorporates shear-wave elastography with B-mode US images, or the model combining shear-wave elastography and B-mode US have been considered superior to singlecomponent models based on the estimation of LNM in PTC [15,16,17,18].…”