Development of a Clinical-Radiomics Nomogram That Used Contrast-Enhanced Ultrasound Images to Anticipate the Occurrence of Preoperative Cervical Lymph Node Metastasis in Papillary Thyroid Carcinoma Patients

Abstract

Background and Objectives Papillary thyroid carcinoma (PTC) is a prevalent histological type of thyroid cancer; however, noninvasive assessment of cervical lymph node metastasis (LNM) poses a challenge. This study aims to develop a novel clinical-radiomics nomogram that utilizes ultrasound (US) images to predict the presence of cervical LNM metastasis in patients with PTC. Methods A total of 423 patients with PTC were recruited to participate in this study between January 2020 and December 2022, of which 282 were classified into the training group and 141 patients were classified into the validation set. Contrast-enhanced ultrasound (CEUS) and B-mode ultrasound (BMUS) images were subjected to radiomic analysis, leading to the extraction of 912 radiomic features. Thereafter, a radiomics score (Radscore) was developed to effectively integrate the information derived from BMUS and CEUS modalities. Univariate and multivariate backward stepwise logistic regression analysis techniques were used to construct the clinical and clinical-radiomics models, respectively. Results The findings revealed that the clinical-radiomics nomogram incorporated age, sex, CEUS Radscore, and US-reported LNM as risk factors. The nomogram demonstrated good performance using data from the training (AUC = 0.891) and validation (AUC = 0.870) sets. The decision curve analysis implied that this nomogram exhibited good clinical utility, which was further supported by the results of the calibration curves and Hosmer-Lemeshow test. Conclusion The CEUS Radscore-based clinical radiomics nomogram could serve as a valuable tool for predicting cervical LNM metastasis in patients with PTC, thereby tailoring individualized treatment strategies for them.

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].…”

“…Most studies (n = 15 articles) on PTC showed that it is possible to predict lateral or central LNM using radiomics [13], although one study from Kim et al [14] was unsuccessful. Radiomics analysis included models combining shear-wave elastography and B-mode US combined Rad-score [16], strain elastography US and B-mode US [18], radiomics and clinical features [21,36,37,38,48], textural and radiological features [22], grayscale texture analysis [23], and clinical, radiomics, and extrathyroidal extension features [35].…”

“…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].…”