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Annals of the Rheumatic Diseases logoLink to Annals of the Rheumatic Diseases
. 2004 Aug 5;64(2):239–245. doi: 10.1136/ard.2004.024224

First clinical evaluation of sagittal laser optical tomography for detection of synovitis in arthritic finger joints

A Scheel 1, M Backhaus 1, A Klose 1, B Moa-Anderson 1, U Netz 1, K Hermann 1, J Beuthan 1, G Muller 1, G Burmester 1, A Hielscher 1
PMCID: PMC1755361  PMID: 15297282

Abstract

Objective: To identify classifiers in images obtained with sagittal laser optical tomography (SLOT) that can be used to distinguish between joints affected and not affected by synovitis.

Methods: 78 SLOT images of proximal interphalangeal joints II–IV from 13 patients with rheumatoid arthritis were compared with ultrasound (US) images and clinical examination (CE). SLOT images showing the spatial distribution of scattering and absorption coefficients within the joint cavity were generated. The means and standard errors for seven different classifiers (operator score and six quantitative measurements) were determined from SLOT images using CE and US as diagnostic references. For classifiers showing significant differences between affected and non-affected joints, sensitivities and specificities for various cut off parameters were obtained by receiver operating characteristic (ROC) analysis.

Results: For five classifiers used to characterise SLOT images the mean between affected and unaffected joints was statistically significant using US as diagnostic reference, but statistically significant for only one classifier with CE as reference. In general, high absorption and scattering coefficients in and around the joint cavity are indicative of synovitis. ROC analysis showed that the minimal absorption classifier yields the largest area under the curve (0.777; sensitivity and specificity 0.705 each) with US as diagnostic reference.

Conclusion: Classifiers in SLOT images have been identified that show statistically significant differences between joints with and without synovitis. It is possible to classify a joint as inflamed with SLOT, without the need for a reference measurement. Furthermore, SLOT based diagnosis of synovitis agrees better with US diagnosis than CE.

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Figure 1.

Figure 1

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 Ultrasound images of PIP joint II (C, D) and IV (A, B) of patients with RA at different synovitis stages. T, tendon; JC, joint cavity. In all images, bone surface is without irregularities, no erosions are visible. Images are taken from the palmar side, and the left side of the image is nearer to, and the right side further from, the hand. Different extents of effusion (ef) can be seen in images B–D. Close to the synovial membrane, synovial proliferation can be detected in images C and D. The images were graded according to the degree of effusion and synovial hypertrophy using the adjusted semiquantitative score of Szkudlarek et al15: (A) grade 0 = none; (B) grade 1 = minimal; (C) grade 2 = moderate; and (D) grade 3 = extensive; the degree of inflammation was interpreted by effusion and synovitis.

Figure 2.

Figure 2

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 Experimental setup for sagittal joint imaging. The laser is positioned above and a photodetector is placed below the finger joint to be examined. Both, detector and diode laser are attached to stepping motor driven translation stages that permit independent control of the position of the laser diode and photodetector relative to the joint. Detector and laser are connected to a personal computer, where data are collected.

Figure 3.

Figure 3

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 Reconstructed cross sections of the scattering coefficient for three different fingers typical for (A) category 1—definitely no synovitis; (B) category 2—probably no synovitis; (C) category 3—possibly synovitis; (D) category 4—probably synovitis; and (E) category 5—definitely synovitis. The fingertip is located to the right of the images that show a 36 mm wide section of the finger with the joint cavity located approximately in the centre. The rectangle in fig 3A indicates the region for which Min(µs), Min(µa), Max(µs), Max(µa), Min(µs)/Max(µs), and Min(µa)/Max(µa), were calculated.

Figure 4.

Figure 4

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 ROC curves with ultrasound scores of 0—unaffected and 3—affected as diagnostic reference (case B) compared with ROC curves with ultrasound scores of (0, 1)—affected and (2,3)—unaffected as diagnostic reference (case A). The numbers in brackets are the area under the curve (AUC). Also given for each curve are the cut off values that result in the largest Youden index.

Figure 5.

Figure 5

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 ROC curves for Min(µa) classifier with clinical scores as diagnostic reference. The two cut off values identify points on the curve for which the Youden index is maximal.

Selected References

These references are in PubMed. This may not be the complete list of references from this article.

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