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利用放射组学和模型检查进行粘连性肩关节囊炎自动早期诊断的方法。

An approach leveraging radiomics and model checking for the automatic early diagnosis of adhesive capsulitis.

机构信息

Department of Medicine and Surgery "V. Tiberio", University of Molise, 86100, Campobasso, Italy.

出版信息

Sci Rep. 2024 Aug 14;14(1):18878. doi: 10.1038/s41598-024-69392-6.

Abstract

Adhesive Capsulitis of the shoulder is a painful pathology limiting shoulder movements, commonly known as "Frozen Shoulder". Since this pathology limits movement, it is important to make an early diagnosis. Diagnosing capsulitis relies on clinical assessment, although diagnostic imaging, such as Magnetic Resonance Imaging, can provide predictive or supportive information for specific characteristic signs. However, its diagnosis is not so simple nor so immediate, indeed it remains a difficult topic for many general radiologists and expert musculoskeletal radiologists. This study aims to investigate whether it is possible to use disease signs within a medical image to automatically diagnose Adhesive Capsulitis. To this purpose, we propose an automatic Model Checking-based approach to quickly diagnose the Adhesive Capsulitis taking as input the radiomic feature values from the medical images. Furthermore, we compare the performance achieved by our method with diagnostic results obtained by professional radiologists with different levels of experience. To the best of our knowledge, this is the first method for the automatic diagnosis of Adhesive Capsulitis of the Shoulder.

摘要

肩粘连性囊炎是一种疼痛性病理,限制了肩部运动,通常被称为“冻结肩”。由于这种病理限制了运动,因此早期诊断很重要。肩粘连性囊炎的诊断依赖于临床评估,尽管诊断性影像学,如磁共振成像,可以为特定特征性标志提供预测或支持性信息。然而,其诊断并不那么简单和直接,事实上,它仍然是许多普通放射科医生和专业肌肉骨骼放射科医生的难题。本研究旨在探讨是否可以使用医学图像中的疾病特征自动诊断粘连性囊炎。为此,我们提出了一种基于模型检查的自动方法,通过输入来自医学图像的放射组学特征值,快速诊断粘连性囊炎。此外,我们还将我们的方法所取得的性能与具有不同经验水平的专业放射科医生的诊断结果进行了比较。据我们所知,这是自动诊断肩粘连性囊炎的第一种方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cbd/11324739/c6b0c240eca0/41598_2024_69392_Fig1_HTML.jpg

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