Computer-Aided Diagnosis

Pixel-based approach to assess contrast-enhanced ultrasound kinetics parameters for differential diagnosis of rheumatoid arthritis

[+] Author Affiliations
Gaia Rizzo, Enrico Grisan

University of Padova, Department of Information Engineering, G. Gradenigo 6/A, Padova 35131, Italy

Bernd Raffeiner

General Hospital of Bolzano, Rheumatology Unit, Via Lorenz Boehler 5, Bolzano 39100, Italy

Alessandro Coran, Ugo Fiocco, Costantino Botsios, Roberto Stramare

University of Padova, Department of Medicine, Via Giustiniani 2, Padova 35128, Italy

Luca Ciprian

Nursing Home Giovanni XXIII, Via Giovanni XXIII 7, Monastier di Treviso (TV) 31050, Italy

J. Med. Imag. 2(3), 034503 (Sep 11, 2015). doi:10.1117/1.JMI.2.3.034503
History: Received April 1, 2015; Accepted August 13, 2015
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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.

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© 2015 Society of Photo-Optical Instrumentation Engineers

Citation

Gaia Rizzo ; Bernd Raffeiner ; Alessandro Coran ; Luca Ciprian ; Ugo Fiocco, et al.
"Pixel-based approach to assess contrast-enhanced ultrasound kinetics parameters for differential diagnosis of rheumatoid arthritis", J. Med. Imag. 2(3), 034503 (Sep 11, 2015). ; http://dx.doi.org/10.1117/1.JMI.2.3.034503


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