A beneficial role of computer-aided diagnosis system for less experienced physicians in the diagnosis of thyroid nodule on ultrasound

Kang, Seo Young; Lee, Eun Jung; Chung, Chae Won; Jang, Han Na; Moon, Joon Ho; Shin, Yujin; Kim, Kyuho; Li, Ying; Shin, Soo Myoung; Kim, Yoo Hyung; Kwon, Seul Ki; Ahn, Chang Ho; Jung, Kyong Yeun; Hong, A Ram; Park, Young Joo; Park, Do Joon; Kwak, Jin Young; Cho, Sun Wook

doi:10.1038/s41598-021-99983-6

Cited by 10 publications

(9 citation statements)

References 26 publications

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“…Many studies have shown that the CAD system is more beneficial for junior radiologists to improve their diagnostic performance ( 32 – 34 ), which was also confirmed in our study. In this study, we used ACR TI-RADS TR4 and TR5 as the cutoff values separately and found that the AUC of the CAD system was higher than that of both junior and senior radiologists when TR4 was used as the cutoff value, and the specificity of the radiologists was lower than that of the CAD system.…”

Section: Discussionsupporting

confidence: 89%

Investigating the diagnostic efficiency of a computer-aided diagnosis system for thyroid nodules in the context of Hashimoto’s thyroiditis

Gong

Zhou

et al. 2023

Front. Oncol.

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ObjectivesThis study aims to investigate the efficacy of a computer-aided diagnosis (CAD) system in distinguishing between benign and malignant thyroid nodules in the context of Hashimoto’s thyroiditis (HT) and to evaluate the role of the CAD system in reducing unnecessary biopsies of benign lesions.MethodsWe included a total of 137 nodules from 137 consecutive patients (mean age, 43.5 ± 11.8 years) who were histopathologically diagnosed with HT. The two-dimensional ultrasound images and videos of all thyroid nodules were analyzed by the CAD system and two radiologists with different experiences according to ACR TI-RADS. The diagnostic cutoff values of ACR TI-RADS were divided into two categories (TR4 and TR5), and then the sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) of the CAD system and the junior and senior radiologists were compared in both cases. Moreover, ACR TI-RADS classification was revised according to the results of the CAD system, and the efficacy of recommended fine-needle aspiration (FNA) was evaluated by comparing the unnecessary biopsy rate and the malignant rate of punctured nodules.ResultsThe accuracy, sensitivity, specificity, PPV, and NPV of the CAD system were 0.876, 0.905, 0.830, 0.894, and 0.846, respectively. With TR4 as the cutoff value, the AUCs of the CAD system and the junior and senior radiologists were 0.867, 0.628, and 0.722, respectively, and the CAD system had the highest AUC (P < 0.0001). With TR5 as the cutoff value, the AUCs of the CAD system and the junior and senior radiologists were 0.867, 0.654, and 0.812, respectively, and the CAD system had a higher AUC than the junior radiologist (P < 0.0001) but comparable to the senior radiologist (P = 0.0709). With the assistance of the CAD system, the number of TR4 nodules was decreased by both junior and senior radiologists, the malignant rate of punctured nodules increased by 30% and 22%, and the unnecessary biopsies of benign lesions were both reduced by nearly half.ConclusionsThe CAD system based on deep learning can improve the diagnostic performance of radiologists in identifying benign and malignant thyroid nodules in the context of Hashimoto’s thyroiditis and can play a role in FNA recommendations to reduce unnecessary biopsy rates.

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Section: Discussionsupporting

confidence: 89%

Investigating the diagnostic efficiency of a computer-aided diagnosis system for thyroid nodules in the context of Hashimoto’s thyroiditis

Gong

Zhou

et al. 2023

Front. Oncol.

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“…Conventional ultrasound examination has many advantages, such as safety, low costs, simple to use, repeatable, and no radioactivity, and thus, has been widely used in clinical practice (10)(11)(12). Conventional ultrasound images of thyroid malignant nodules are characterized by irregular shape, unclear edge, non-uniformity, microcalcification, low echo, and aspect ratio greater than 1 (13). However, conventional ultrasound has great limitations in the diagnosis of clinically complicated benign and malignant thyroid nodules.…”

Section: Introductionmentioning

confidence: 99%

Systematic review and meta-analysis: diagnostic value of different ultrasound for benign and malignant thyroid nodules

Wang¹,

Zhou²,

Shen³

et al. 2022

Gland Surg

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“…Many research studies on computer-aided diagnoses of disorders, including thyroid diseases, have been carried out. It is reported that computer-aided diagnosis can offer efficient dataset processing, accurate diagnosis, clinical decision-making support, and even potential treatment options for thyroid diagnosis (27)(28)(29)(30). Computer-aided diagnosis of HT has been In this study, we collected fifteen clinical characteristics and laboratory data to study their significant correlations with HT and thyroid cancer.…”

Section: Introductionmentioning

confidence: 99%

Prediction models constructed for Hashimoto’s thyroiditis risk based on clinical and laboratory factors

Liu¹,

Zhao

et al. 2022

Front. Endocrinol.

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BackgroundHashimoto’s thyroiditis (HT) frequently occurs among autoimmune diseases and may simultaneously appear with thyroid cancer. However, it is difficult to diagnose HT at an early stage just by clinical symptoms. Thus, it is urgent to integrate multiple clinical and laboratory factors for the early diagnosis and risk prediction of HT.MethodsWe recruited 1,303 participants, including 866 non-HT controls and 437 diagnosed HT patients. 44 HT patients also had thyroid cancer. Firstly, we compared the difference in thyroid goiter degrees between controls and patients. Secondly, we collected 15 factors and analyzed their significant differences between controls and HT patients, including age, body mass index, gender, history of diabetes, degrees of thyroid goiter, UIC, 25-(OH)D, FT3, FT4, TSH, TAG, TC, FPG, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol. Thirdly, logistic regression analysis demonstrated the risk factors for HT. For machine learning modeling of HT and thyroid cancer, we conducted the establishment and evaluation of six models in training and test sets.ResultsThe degrees of thyroid goiter were significantly different among controls, HT patients without cancer (HT-C), and HT patients with thyroid cancer (HT+C). Most factors had significant differences between controls and patients. Logistic regression analysis confirmed diabetes, UIC, FT3, and TSH as important risk factors for HT. The AUC scores of XGBoost, LR, SVM, and MLP models indicated appropriate predictive power for HT. The features were arranged by their importance, among which, 25-(OH)D, FT4, and TSH were the top three high-ranking factors.ConclusionsWe firstly analyzed comprehensive factors of HT patients. The proposed machine learning modeling, combined with multiple factors, are efficient for thyroid diagnosis. These discoveries will extensively promote precise diagnosis, personalized therapies, and reduce unnecessary cost for thyroid diseases.

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A beneficial role of computer-aided diagnosis system for less experienced physicians in the diagnosis of thyroid nodule on ultrasound

Cited by 10 publications

References 26 publications

Investigating the diagnostic efficiency of a computer-aided diagnosis system for thyroid nodules in the context of Hashimoto’s thyroiditis

Investigating the diagnostic efficiency of a computer-aided diagnosis system for thyroid nodules in the context of Hashimoto’s thyroiditis

Systematic review and meta-analysis: diagnostic value of different ultrasound for benign and malignant thyroid nodules

Prediction models constructed for Hashimoto’s thyroiditis risk based on clinical and laboratory factors

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