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Journal of Medical Imaging

Pixel-based approach to assess contrast-enhanced ultrasound kinetics parameters for differential diagnosis of rheumatoid arthritis
Author(s): Gaia Rizzo; Bernd Raffeiner; Alessandro Coran; Luca Ciprian; Ugo Fiocco; Costantino Botsios; Roberto Stramare; Enrico Grisan
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Paper Abstract

Inflammatory rheumatic diseases are the leading causes of disability and constitute a frequent medical disorder, leading to inability to work, high comorbidity, and increased mortality. The standard for diagnosing and differentiating arthritis is based on clinical examination, laboratory exams, and imaging findings, such as synovitis, bone edema, or joint erosions. Contrast-enhanced ultrasound (CEUS) examination of the small joints is emerging as a sensitive tool for assessing vascularization and disease activity. Quantitative assessment is mostly performed at the region of interest level, where the mean intensity curve is fitted with an exponential function. We showed that using a more physiologically motivated perfusion curve, and by estimating the kinetic parameters separately pixel by pixel, the quantitative information gathered is able to more effectively characterize the different perfusion patterns. In particular, we demonstrated that a random forest classifier based on pixelwise quantification of the kinetic contrast agent perfusion features can discriminate rheumatoid arthritis from different arthritis forms (psoriatic arthritis, spondyloarthritis, and arthritis in connective tissue disease) with an average accuracy of 97%. On the contrary, clinical evaluation (DAS28), semiquantitative CEUS assessment, serological markers, or region-based parameters do not allow such a high diagnostic accuracy.

Paper Details

Date Published: 11 September 2015
PDF: 12 pages
J. Med. Img. 2(3) 034503 doi: 10.1117/1.JMI.2.3.034503
Published in: Journal of Medical Imaging Volume 2, Issue 3
Show Author Affiliations
Gaia Rizzo, Univ. degli Studi di Padova (Italy)
Bernd Raffeiner, General Hospital of Bolzano (Italy)
Alessandro Coran, Univ. degli Studi di Padova (Italy)
Luca Ciprian, Nursing Home Giovanni XXIII (Italy)
Ugo Fiocco, Univ. degli Studi di Padova (Italy)
Costantino Botsios, Univ. degli Studi di Padova (Italy)
Roberto Stramare, Univ. degli Studi di Padova (Italy)
Enrico Grisan, Univ. degli Studi di Padova (Italy)


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