PT  - JOURNAL ARTICLE
AU  - Xu, X.-Q.
AU  - Zhou, Y.
AU  - Su, G.-Y.
AU  - Tao, X.-W.
AU  - Ge, Y.-Q.
AU  - Si, Y.
AU  - Shen, M.-P.
AU  - Wu, F.-Y.
TI  - Iodine Maps from Dual-Energy CT to Predict Extrathyroidal Extension and Recurrence in Papillary Thyroid Cancer Based on a Radiomics Approach
AID  - 10.3174/ajnr.A7484
DP  - 2022 Apr 14
TA  - American Journal of Neuroradiology
4099  - http://www.ajnr.org/content/early/2022/04/14/ajnr.A7484.short
4100  - http://www.ajnr.org/content/early/2022/04/14/ajnr.A7484.full
AB  - BACKGROUND AND PURPOSE: Accurate prediction of extrathyroidal extension and subsequent recurrence is crucial in papillary thyroid cancer clinical management. Our aim was to conduct iodine map–based radiomics to predict extrathyroidal extension and to explore its prognostic value for recurrence-free survival in papillary thyroid cancer.MATERIALS AND METHODS: A total of 452 patients with papillary thyroid cancer were retrospectively recruited between June 2017 and June 2020. Radiomics features were extracted from noncontrast images, dual-phase mixed images, and iodine maps, respectively. Random forest and least absolute shrinkage and selection operator (LASSO) were applied to build 6 radiomics scores (noncontrast radiomics score_random forest; noncontrast rad-score_LASSO; mixed rad-score_random forest; mixed rad-score_LASSO; iodine radiomics score_random forest; iodine radiomics score_LASSO) respectively. Logistic regression was used to construct 6 radiomics models incorporating 6 radiomics scores with clinical risk factors and to compare them with the clinical model. A radiomics model that achieved the highest performance was presented as a nomogram and assessed by discrimination, calibration, clinical usefulness, and prognosis evaluation.RESULTS: Iodine radiomics scores performed significantly better than mixed radiomics scores. Both of them outperformed noncontrast radiomics scores. Iodine map–based radiomics models significantly surpassed the clinical model. A radiomics nomogram incorporating size, capsule contact, and iodine radiomics score_random forest was built with the highest performance (training set, area under the curve = 0.78; validation set, area under the curve  = 0.84). Stratified analysis confirmed the nomogram stability, especially in group negative for CT-reported extrathyroidal extension (area under the curve  = 0.69). Nomogram-predicted extrathyroidal extension risk was an independent predictor of recurrence-free survival. A high risk for extrathyroidal extension portended significantly lower recurrence-free survival than low risk (P < .001).CONCLUSIONS: Iodine map–based radiomics might be a supporting tool for predicting extrathyroidal extension and subsequent recurrence risk in patients with papillary thyroid cancer, thus facilitating clinical decision-making.AUCarea under the curveBMIbody mass indexETEextrathyroidal extensionDECTdual-energy CTLASSOleast absolute shrinkage and selection operatorPTCpapillary thyroid cancerrad-scoreradiomics scoreRFrandom forestRFSrecurrence-free survival