Session Title: Imaging of Rheumatic Diseases: Ultrasound
Session Type: Abstract Submissions (ACR)
Primary Sjögren’s syndrome (pSS) is an autoimmune chronic inflammatory disease mainly affecting the salivary and lacrimal glands, with symptoms such as dryness of the mouth and eyes as well as fatigue. The diagnosis is based on the objective findings of reduced secretion of saliva- and/or tears, the detection of auto-antibodies against Ro/SSA and/or La/SSB in serum, and the observation of focal mononuclear cell infiltration in minor labial salivary gland biopsies. In the recent years, interest in major salivary gland ultrasonography as a diagnostic tool for pSS has increased. Several scoring systems evaluating glandular homogeneity and echogenicity have been suggested, presenting a challenge for both researchers and clinicians. The aim of this study was to develop a reliable automated digital evaluation of ultrasound images as a useful tool for the clinician and as an objective method for the researcher.
The parotid glands of patients (n=26) fulfilling the AECG criteria (Vitali et al 2002) had previously been examined using a GE LogiqE9 with a linear high-frequency transducer (6-15MHz) and the images evaluated using a simplified grading system (0-3) (Hocevar et al, 2005). The stored images were analysed digitally with a pilot version of the software developed for this study. Briefly, the software analyses local variability in grayscale values. The algorithm used for the digital analysis was developed using MATLAB (MathWorks, Natick, Massachusetts).
The patients were randomly selected from a previously characterized cohort (n=97) where the ultrasound findings correlated with objective findings such as reduced saliva secretion, minor salivary gland inflammation and elevated autoantibody titers, as well as sicca symptoms of the mouth (manuscript found acceptable for publication in Clinical and Experimental Rheumatology 2014).
Preliminary findings show an excellent correlation between the scores obtained with the simplified grading system (0-3) and the automated digital evaluation (p>0.05, r=0.816, n=26). Mean digital score for images graded 0-3 were -9.833 (grade 0), -6.018 (grade 1), 2.752 (grade 2) and 6.850 (grade 3), respectively.
The preliminary results of ultrasound image analysis show an excellent correlation between the automated digital analysis and the evaluation by a trained clinician. In future studies, automated analysis will enable an objective and reproducible analytic method for the researcher as well as provide a useful diagnostic and possibly prognostic tool for the clinician.
D. S. Hammenfors,
P. G. Nes,
J. G. Brun,
M. V. Jonsson,
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ACR Meeting Abstracts - https://acrabstracts.org/abstract/automated-digital-analysis-of-major-salivary-gland-ultrasound-images/