Abstract

Salivary gland ultrasonography (SGUS) has shown good potential in the diagnosis of primary Sjögren's syndrome (pSS). However, a series of international studies have reported needs for improvements of the existing pSS scoring procedures in terms of inter/intra observer reliability before being established as standardized diagnostic tools. The present study aims to solve this problem by employing radiomics features and artificial intelligence (AI) algorithms to make the pSS scoring more objective and faster compared to human expert scoring. The assessment of AI algorithms was performed on a two-centric cohort, which included 600 SGUS images (150 patients) annotated using the original SGUS scoring system proposed in 1992 for pSS. For each image, we extracted 907 histogram-based and descriptive statistics features from segmented salivary glands. Optimal feature subsets were found using the genetic algorithm based wrapper approach. Among the considered algorithms (seven classifiers and five regressors), the best preforming was the multilayer perceptron (MLP) classifier (κ = 0.7). The MLP over-performed average score achieved by the clinicians (κ = 0.67) by the considerable margin, whereas its reliability was on the level of human intra-observer variability (κ = 0.71). The presented findings indicate that the continuously increasing HarmonicSS cohort will enable further advancements in AI-based pSS scoring methods by SGUS. In turn, this may establish SGUS as an effective noninvasive pSS diagnostic tool, with the final goal to supplement current diagnostic tests.

Highlights

  • P RIMARY Sjogren’s Syndrome is a chronic autoimmune disease, whose manifesting symptoms are oral and ocular dryness, fatigue, arthralgia and arthritis

  • 1) Computerized Analysis of salivary gland ultrasonography (SGUS) and Assessment of P RIMARY Sjogren’s Syndrome (pSS): After literature review, we report that the computerized medical image analysis of salivary gland (SG) and pSS remain underestimated problems

  • Humans are efficient in high-level cognitive tasks, our limitation in performing lower-level vision tasks such as calculation of textures’ statistics or differentiating shades of colors are well studied and depend on many factors [35]

Read more

Summary

Introduction

P RIMARY Sjogren’s Syndrome (pSS) is a chronic autoimmune disease, whose manifesting symptoms are oral and ocular dryness, fatigue, arthralgia and arthritis. Four standardized guides are: European Classification (PEC) criteria [2], American European Consensus Group (AECG 2002) classification criteria [3] the American College of Rheumatology (ACR 2012) criteria [4] and the more recent ACR-European League Against Rheumatism (EULAR) 2016 criteria [5]. These guides are based on the combination of examined clinical symptoms, results of autoantibody tests and salivary gland (SG) biopsy [6]. According to clinical reports, failing to include any imaging modalities (as mentioned in the standardized guides) has been reported as an obstacle in the practice – as patients frequently complain at invasive tests and biopsies, especially during follow-up studies or when presented with negative findings [8]

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call