Literature DB >> 32041119

Multi-Reader Multi-Case Study for Performance Evaluation of High-Risk Thyroid Ultrasound with Computer-Aided Detection.

Ming-Hsun Wu1, Kuen-Yuan Chen1, Shyang-Rong Shih2, Ming-Chih Ho1, Hao-Chih Tai1, King-Jen Chang1, Argon Chen3, Chiung-Nien Chen1.   

Abstract

Physicians use sonographic characteristics as a reference for the possible diagnosis of thyroid cancers. The purpose of this study was to investigate whether physicians were more effective in their tentative diagnosis based on the information provided by a computer-aided detection (CAD) system. A computer compared software-defined and physician-adjusted tumor loci. A multicenter, multireader, and multicase (MRMC) study was designed to compare clinician performance without and with the use of CAD. Interobserver variability was also analyzed. Excellent, satisfactory, and poor segmentations were observed in 25.3%, 58.9%, and 15.8% of nodules, respectively. There were 200 patients with 265 nodules in the study set. Nineteen physicians scored the malignancy potential of the nodules. The average area under the curve (AUC) of all readers was 0.728 without CAD and significantly increased to 0.792 with CAD. The average standard deviation of the malignant potential score significantly decreased from 18.97 to 16.29. The mean malignant potential score significantly decreased from 35.01 to 31.24 for benign cases. With the CAD system, an additional 7.6% of malignant nodules would be suggested for further evaluation, and biopsy would not be recommended for an additional 10.8% of benign nodules. The results demonstrated that applying a CAD system would improve clinicians' interpretations and lessen the variability in diagnosis. However, more studies are needed to explore the use of the CAD system in an actual ultrasound diagnostic situation where much more benign thyroid nodules would be seen.

Entities:  

Keywords:  computer-aided detection; thyroid cancer; thyroid nodule; ultrasonography

Year:  2020        PMID: 32041119     DOI: 10.3390/cancers12020373

Source DB:  PubMed          Journal:  Cancers (Basel)        ISSN: 2072-6694            Impact factor:   6.639


  3 in total

1.  Risk Stratification in Patients With Follicular Neoplasm on Cytology: Use of Quantitative Characteristics and Sonographic Patterns.

Authors:  Ming-Hsun Wu; Kuen-Yuan Chen; Min-Shu Hsieh; Argon Chen; Chiung-Nien Chen
Journal:  Front Endocrinol (Lausanne)       Date:  2021-04-30       Impact factor: 5.555

2.  Diagnostic performance evaluation of different TI-RADS using ultrasound computer-aided diagnosis of thyroid nodules: An experience with adjusted settings.

Authors:  Nonhlanhla Chambara; Shirley Y W Liu; Xina Lo; Michael Ying
Journal:  PLoS One       Date:  2021-01-15       Impact factor: 3.240

3.  Assessing Detection Accuracy of Computerized Sonographic Features and Computer-Assisted Reading Performance in Differentiating Thyroid Cancers.

Authors:  Hao-Chih Tai; Kuen-Yuan Chen; Ming-Hsun Wu; King-Jen Chang; Chiung-Nien Chen; Argon Chen
Journal:  Biomedicines       Date:  2022-06-26
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.