Observation Variation in Ultrasonography Assessment of Thyroid Nodules

سال انتشار: 1401
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 225

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شناسه ملی سند علمی:

JR_JNMB-10-1_004

تاریخ نمایه سازی: 11 دی 1400

چکیده مقاله:

Objective(s): Accurate detection and competent management of thyroid nodules, as a common disease, basically depends on the reliability of the ultrasonography (US) report. In this research, we evaluated inter and intra-observer variation among ultrasonography reporters, based on ACR-TIRADS.Methods: In this retrospective study, ۳۴۵ thyroid US images of ۱۵۰ patients were reviewed. Three clinicians with at least ۶-year experience in thyroid US reviewed the images twice at ۶-۸ weeks’ intervals. Composition, echogenicity, shape, margin, and echogenic foci based on ACR-TIRADS were reported, independently. Inter and intra-observer variations were calculated based on Cohen’s Kappa statistics.Results: ۳۴۵ ultrasonography images of ۱۵۰ patients with thyroid nodules (۸۳ women and ۶۷ men) with a mean age of ۶۵ years were reviewed. Moderate to the substantial intra-observer agreement was achieved with the highest Kapa value in the category of shape (k=۰.۶۱-۰.۷۷). For TIRADS level, the moderate intra-observer agreement was observed (k=۰.۴۲-۰.۴۶). Inter-observer agreement for the US category of thyroid nodules was obtained slightly to moderate. Composition (k=۰.۴۲ and ۰.۵۱) and echogenicity (k=۰.۴۵ and ۰.۴۶) showed the highest overall agreement and margin showed the lowest overall agreement (k=۰.۱۸ and ۰.۱۹). In assessing TIRADS level of nodules, a fair agreement was obtained (k=۰.۲۳ and ۰.۲۹) .Conclusion: Moderate to substantial intra-observer agreement and slight to moderate inter-observer variation for evaluation of thyroid nodules; shows the need for a computer-aided diagnosis system based on artificial intelligence to assist our physicians in differentiating thyroid nodule characteristics based on explicit image features. An additional training course based on ACR-TIRADS for physicians can be another useful recommendation.

نویسندگان

Yasaman Sharifi

Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran

Susan Shafiei Forumad

Nuclear Medicine Research Center, Mashhad University of Medical Sciences ,Mashhad, Iran

Hamed Tabesh

Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran

Behzad Aminzadeh

Department of Radiology, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran

Parvaneh Layegh

Department of Radiology, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran

Abolfazl Mahmoodzadeh

Department of Radiology, Faculty of Medicine, Neyshabur University of Medical Sciences, Neyshabur, Iran

Seyed Rasoul Zakavi

Nuclear Medicine Research Center, Mashhad University of Medical Sciences ,Mashhad, Iran

Saeid Eslami

Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran

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