Ultrasound Radiomics Nomogram to Diagnose Sub-Centimeter Thyroid Nodules Based on ACR TI-RADS
The aim of the present study was to develop a radiomics nomogram to assess whether thyroid nodules (TNs) < 1 cm are benign or malignant. From March 2021 to March 2022, 156 patients were admitted to the Affiliated Hospital of Nantong University, and from September 2017 to March 2022, 116 patients...
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Published in | Cancers Vol. 14; no. 19; p. 4826 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
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01.10.2022
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Abstract | The aim of the present study was to develop a radiomics nomogram to assess whether thyroid nodules (TNs) < 1 cm are benign or malignant. From March 2021 to March 2022, 156 patients were admitted to the Affiliated Hospital of Nantong University, and from September 2017 to March 2022, 116 patients were retrospectively collected from the Jiangsu Provincial Hospital of Integrated Traditional Chinese and Western Medicine. These patients were divided into a training group and an external test group. A radiomics nomogram was established using multivariate logistics regression analysis using the radiomics score and clinical data, including the ultrasound feature scoring terms from the thyroid imaging reporting and data system (TI-RADS). The radiomics nomogram incorporated the correlated predictors, and compared with the clinical model (training set AUC: 0.795; test set AUC: 0.783) and radiomics model (training set AUC: 0.774; test set AUC: 0.740), had better discrimination performance and correction effects in both the training set (AUC: 0.866) and the test set (AUC: 0.866). Both the decision curve analysis and clinical impact curve showed that the nomogram had a high clinical application value. The nomogram constructed based on TI-RADS and radiomics features had good results in predicting and distinguishing benign and malignant TNs < 1 cm. |
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AbstractList | The aim of the present study was to develop a radiomics nomogram to assess whether thyroid nodules (TNs) < 1 cm are benign or malignant. From March 2021 to March 2022, 156 patients were admitted to the Affiliated Hospital of Nantong University, and from September 2017 to March 2022, 116 patients were retrospectively collected from the Jiangsu Provincial Hospital of Integrated Traditional Chinese and Western Medicine. These patients were divided into a training group and an external test group. A radiomics nomogram was established using multivariate logistics regression analysis using the radiomics score and clinical data, including the ultrasound feature scoring terms from the thyroid imaging reporting and data system (TI-RADS). The radiomics nomogram incorporated the correlated predictors, and compared with the clinical model (training set AUC: 0.795; test set AUC: 0.783) and radiomics model (training set AUC: 0.774; test set AUC: 0.740), had better discrimination performance and correction effects in both the training set (AUC: 0.866) and the test set (AUC: 0.866). Both the decision curve analysis and clinical impact curve showed that the nomogram had a high clinical application value. The nomogram constructed based on TI-RADS and radiomics features had good results in predicting and distinguishing benign and malignant TNs < 1 cm. Simple SummaryFine-needle aspiration or surgical resection is used to determine whether thyroid nodules (TNs) are benign or malignant, but there is a risk of overtreatment. Guidelines such as the American College of Radiology thyroid imaging reporting and data system consider follow-up for TNs < 1 cm, even with high-risk ultrasound features; therefore, for these TNs, an ultrasound radiomics nomogram was developed for noninvasive assessment of benign and malignant TNs. In addition, to assess the model’s diagnostic capabilities, the present study tested the model using an external validation group. The test results suggest that ultrasound radiomics is an effective, noninvasive method by which to diagnose noninvasive TNs.AbstractThe aim of the present study was to develop a radiomics nomogram to assess whether thyroid nodules (TNs) < 1 cm are benign or malignant. From March 2021 to March 2022, 156 patients were admitted to the Affiliated Hospital of Nantong University, and from September 2017 to March 2022, 116 patients were retrospectively collected from the Jiangsu Provincial Hospital of Integrated Traditional Chinese and Western Medicine. These patients were divided into a training group and an external test group. A radiomics nomogram was established using multivariate logistics regression analysis using the radiomics score and clinical data, including the ultrasound feature scoring terms from the thyroid imaging reporting and data system (TI-RADS). The radiomics nomogram incorporated the correlated predictors, and compared with the clinical model (training set AUC: 0.795; test set AUC: 0.783) and radiomics model (training set AUC: 0.774; test set AUC: 0.740), had better discrimination performance and correction effects in both the training set (AUC: 0.866) and the test set (AUC: 0.866). Both the decision curve analysis and clinical impact curve showed that the nomogram had a high clinical application value. The nomogram constructed based on TI-RADS and radiomics features had good results in predicting and distinguishing benign and malignant TNs < 1 cm. Fine-needle aspiration or surgical resection is used to determine whether thyroid nodules (TNs) are benign or malignant, but there is a risk of overtreatment. Guidelines such as the American College of Radiology thyroid imaging reporting and data system consider follow-up for TNs < 1 cm, even with high-risk ultrasound features; therefore, for these TNs, an ultrasound radiomics nomogram was developed for noninvasive assessment of benign and malignant TNs. In addition, to assess the model’s diagnostic capabilities, the present study tested the model using an external validation group. The test results suggest that ultrasound radiomics is an effective, noninvasive method by which to diagnose noninvasive TNs. Fine-needle aspiration or surgical resection is used to determine whether thyroid nodules (TNs) are benign or malignant, but there is a risk of overtreatment. Guidelines such as the American College of Radiology thyroid imaging reporting and data system consider follow-up for TNs < 1 cm, even with high-risk ultrasound features; therefore, for these TNs, an ultrasound radiomics nomogram was developed for noninvasive assessment of benign and malignant TNs. In addition, to assess the model’s diagnostic capabilities, the present study tested the model using an external validation group. The test results suggest that ultrasound radiomics is an effective, noninvasive method by which to diagnose noninvasive TNs. The aim of the present study was to develop a radiomics nomogram to assess whether thyroid nodules (TNs) < 1 cm are benign or malignant. From March 2021 to March 2022, 156 patients were admitted to the Affiliated Hospital of Nantong University, and from September 2017 to March 2022, 116 patients were retrospectively collected from the Jiangsu Provincial Hospital of Integrated Traditional Chinese and Western Medicine. These patients were divided into a training group and an external test group. A radiomics nomogram was established using multivariate logistics regression analysis using the radiomics score and clinical data, including the ultrasound feature scoring terms from the thyroid imaging reporting and data system (TI-RADS). The radiomics nomogram incorporated the correlated predictors, and compared with the clinical model (training set AUC: 0.795; test set AUC: 0.783) and radiomics model (training set AUC: 0.774; test set AUC: 0.740), had better discrimination performance and correction effects in both the training set (AUC: 0.866) and the test set (AUC: 0.866). Both the decision curve analysis and clinical impact curve showed that the nomogram had a high clinical application value. The nomogram constructed based on TI-RADS and radiomics features had good results in predicting and distinguishing benign and malignant TNs < 1 cm. |
Audience | Academic |
Author | Lu, Wenwu Qian, Xiaoqin Wei, Yan Zhang, Yuzhi Xia, Zicong Qian, Cheng Ding, Wenbo Ni, Xuejun Zhang, Di |
AuthorAffiliation | 3 Department of Ultrasound, Affiliated People’s Hospital of Jiangsu University, Zhenjiang 212050, China 1 Department of Medical Ultrasound, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong 226001, China 2 Affiliated Hospital of Integration Chinese and Western Medicine with Nanjing University of Traditional Chinese Medicine, Nanjing 210023, China |
AuthorAffiliation_xml | – name: 2 Affiliated Hospital of Integration Chinese and Western Medicine with Nanjing University of Traditional Chinese Medicine, Nanjing 210023, China – name: 3 Department of Ultrasound, Affiliated People’s Hospital of Jiangsu University, Zhenjiang 212050, China – name: 1 Department of Medical Ultrasound, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong 226001, China |
Author_xml | – sequence: 1 givenname: Wenwu surname: Lu fullname: Lu, Wenwu organization: Department of Medical Ultrasound, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong 226001, China – sequence: 2 givenname: Di surname: Zhang fullname: Zhang, Di organization: Department of Medical Ultrasound, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong 226001, China – sequence: 3 givenname: Yuzhi surname: Zhang fullname: Zhang, Yuzhi organization: Affiliated Hospital of Integration Chinese and Western Medicine with Nanjing University of Traditional Chinese Medicine, Nanjing 210023, China – sequence: 4 givenname: Xiaoqin surname: Qian fullname: Qian, Xiaoqin organization: Department of Ultrasound, Affiliated People's Hospital of Jiangsu University, Zhenjiang 212050, China – sequence: 5 givenname: Cheng surname: Qian fullname: Qian, Cheng organization: Department of Medical Ultrasound, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong 226001, China – sequence: 6 givenname: Yan surname: Wei fullname: Wei, Yan organization: Department of Medical Ultrasound, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong 226001, China – sequence: 7 givenname: Zicong surname: Xia fullname: Xia, Zicong organization: Department of Medical Ultrasound, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong 226001, China – sequence: 8 givenname: Wenbo surname: Ding fullname: Ding, Wenbo organization: Affiliated Hospital of Integration Chinese and Western Medicine with Nanjing University of Traditional Chinese Medicine, Nanjing 210023, China – sequence: 9 givenname: Xuejun surname: Ni fullname: Ni, Xuejun organization: Department of Medical Ultrasound, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong 226001, China |
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Keywords | radiomics nomogram thyroid imaging reporting and data system (TI-RADS) thyroid nodules ultrasound |
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Snippet | The aim of the present study was to develop a radiomics nomogram to assess whether thyroid nodules (TNs) < 1 cm are benign or malignant. From March 2021 to... Fine-needle aspiration or surgical resection is used to determine whether thyroid nodules (TNs) are benign or malignant, but there is a risk of overtreatment.... Simple SummaryFine-needle aspiration or surgical resection is used to determine whether thyroid nodules (TNs) are benign or malignant, but there is a risk of... |
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SubjectTerms | Accuracy Benign Correlation analysis Diagnosis Diagnostic imaging Hospitals Logistics Lymphatic system Metastasis Nodules nomogram Nomography (Mathematics) Open source software Patients Physicians Public domain Radiomics Regression analysis Reproducibility Risk factors Technology application Thyroid Thyroid cancer thyroid imaging reporting and data system (TI-RADS) thyroid nodules Ultrasonic imaging Ultrasound Wavelet transforms |
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Title | Ultrasound Radiomics Nomogram to Diagnose Sub-Centimeter Thyroid Nodules Based on ACR TI-RADS |
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