Analyzing the precision of JSW measurements using 3D scans and statistical models

One of the methods to diagnose rheumatoid arthritis (RA) is measuring joint space narrowing over time. A method is presented to analyze the sensitivity of this measurement to positioning of the hand. Micro-CT scans are used to generate projections of a joint under varying angles of rotation. A semi-automatic method is used to measure the joint space width (JSW) for each projection. A Statistical model is used to investigate whether the rotation can be detected from a 2D radiograph. It is shown that rotation of the hand has a significant influence on the measured JSW

Matching hand radiographs

Biometric verification and identification methods of medical images can be used to find possible inconsistencies in patient records. Such methods may also be useful for forensic research. In this work we present a method for identifying patients by their hand radiographs. We use active appearance model representations presented before [1] to extract 64 shape features per bone from the metacarpals, the proximal, and the middle phalanges. The number of features was reduced to 20 by applying principal component analysis. Subsequently, a likelihood ratio classifier [2] determines whether an image potentially belongs to another patient in the data set. Firstly, to study the symmetry between both hands, we use a likelihood-ratio classifier to match 45 left hand images to a database of 44 (matching) right hand images and vice versa. We found an average equal error probability of 6.4%, which indicates that both hand shapes are highly symmetrical. Therefore, to increase the number of samples per patient, the distinction between left and right hands was omitted. Secondly, we did multiple experiments with randomly selected training images from 24 patients. For several patients there were multiple image pairs available. Test sets were created by using the images of three different patients and 10 other images from patients that were in the training set. We estimated the equal error rate at 0.05%. Our experiments suggest that the shapes of the hand bones contain biometric information that can be used to identify persons

Segmentation of Radiographs of Hands with Joint Damage Using Customized Active Appearance Models

This paper is part of a project that investigates the possibilities of automating the assessment of joint damagein hand radiographs. Our goal is to design a robust segmentationalgorithm for the hand skeleton. The algorithm is\ud based on active appearance models (AAM) [1], which have been used for hand segmentation before [2]. The results will be used in the future for radiographic assessment of rheumatoid arthritis and the early detection of joint damage. New in this work with respect to [2] is the use of multiple object warps for each individual bone in a single AAM. This method prevents modelling and reconstruction defects caused when warping overlapping objects. This makes the algorithm more robust in cases where joint damage is present. The current implementation of the model includes the metacarpals, the phalanges, and the carpal region. For a first experimental evaluation a collection of 50 hand radiographs has been gathered. The image data set was split into a training set (40) and a test set (10) in order to evaluate the algorithm’s performance. First results show that in 8 images from the test set the bone contours are detected correctly within 1.3 mm (1 STD) at 15 pixels/cm resolution. In two images not all contours are detected correctly. Possibly this is caused by extreme deviations in these images that have not yet been incorporated in the model due to a limited training set. More training examples are needed to optimize the AAM and improve the quality and reliability of the results

Spa treatment for primary fibromyalgia syndrome: a combination of thalassotherapy, exercise and patient education improves symptoms and quality of life

Objectives: To study the effect of a combination of thalassotherapy, exercise and patient education in people with fibromyalgia. -\ud Methods: Patients with fibromyalgia, selected from a rheumatology out-patient department and from members of the Dutch fibromyalgia patient association, were pre-randomized to receive either 2 weeks of treatment in a Tunisian spa resort, including thalassotherapy, supervised exercise and group education (active treatment) or treatment as usual (control treatment). Primary outcome measure was health-related quality of life, measured with the RAND-36 questionnaire. Secondary measures included the Fibromyalgia Impact Questionnaire, the McGill Pain Questionnaire, the Beck Depression Inventory, tender point score and a 6-min treadmill walk test. -\ud Results: Fifty-eight participants receiving the active treatment reported significant improvement on RAND-36 physical and mental component summary scales. For physical health, differences from the 76 controls were statistically significant after 3 months, but not after 6 and 12 months. A similar pattern of temporary improvement was seen in the self-reported secondary measures. Tender point scores and treadmill walk tests improved more after active treatment, but did not reach significant between-group differences, except for walk tests after 12 months. -\ud Conclusions: A combination of thalassotherapy, exercise and patient education may temporarily improve fibromyalgia symptoms and health-related quality of life

Adherence to a Treat-to-Target Strategy in Early Rheumatoid Arthritis: Results of the DREAM Remission Induction Cohort

Introduction\ud Clinical trials have demonstrated that treatment-to-target (T2T) is effective in achieving remission in early rheumatoid arthritis (RA). However, the concept of T2T has not been fully implemented yet and the question is whether a T2T strategy is feasible in daily clinical practice. The objective of the study was to evaluate the adherence to a T2T strategy aiming at remission (Disease Activity Score in 28 joints (DAS28) < 2.6) in early RA in daily practice. The recommendations regarding T2T included regular assessment of the DAS28 and advice regarding DAS28-driven treatment adjustments. \ud \ud Methods\ud A medical chart review was performed among a random sample of 100 RA patients of the DREAM remission induction cohort. At all scheduled visits, it was determined whether the clinical decisions were compliant to the T2T recommendations. \ud \ud Results\ud The 100 patients contributed to a total of 1,115 visits. The DAS28 was available in 97.9% (1,092/1,115) of the visits, of which the DAS28 was assessed at a frequency of at least every three months in 88.3% (964/1,092). Adherence to the treatment advice was observed in 69.3% (757/1,092) of the visits. In case of non-adherence when remission was present (19.5%, 108/553), most frequently medication was tapered off or discontinued when it should have been continued (7.2%, 40/553) or treatment was continued when it should have been tapered off or discontinued (6.2%, 34/553). In case of non-adherence when remission was absent (42.1%, 227/539), most frequently medication was not intensified when an intensification step should have been taken (34.9%, 188/539). The main reason for non-adherence was discordance between disease activity status according to the rheumatologist and DAS28. \ud \ud Conclusions\ud The recommendations regarding T2T were successfully implemented and high adherence was observed. This demonstrates that a T2T strategy is feasible in RA in daily clinical practic

Automated analysis of hand radiographs by using multi-level connected active appearance models

Objectives: Joint damage assessment in radiographs of hands is used for monitoring disease progression and outcome in drug trials in rheumatoid arthritis (RA). Current clinical scoring methods are based on manual measurements that are time-consuming and subject to intra and inter-reader variance. A solution may be found in the development of partially or fully automated assessment procedures. This requires reliable segmentation algorithms that recognise individual bones and joints. Methods: For hand x-rays, we adapted a segmentation method based on multiple connected active appearance models (AAM) with multiple search steps using increasing quality levels. The quality level can be regulated by setting the image resolution and the number of landmarks in the AAMs. To test this method we digitized 80 film radiographs of single hands: 50 images were used for training the model and 30 for testing. We performed experiments using two models of different quality levels for shape and texture information. Both models included AAMs for the carpal region, the metacarpals, and all phalanges. Results: By starting an iterative search with the faster, low-quality model, we were able to determine the initial parameters of the second, high-quality model. After the second search, the results showed successful segmentation for 22 of 30 test images. For these images, 70% of the landmarks were found within 1.3 mm difference from manual placement by an expert. The multi-level search approach resulted in a reduction of 50% in calculation time compared to a search using a single model. Results are expected to improve when the model is refined by increasing the number of training examples and the resolution of the models. Conclusion: Although the system is not completed, increasing the training set and further adaptation of the model may help to make automated assessment of joint damage on hand X-rays a reality in the near future. The detection of the contours of individual carpal, metacarpal and interphalangeal bones will be followed by separate algorithms for the measurement of joint space widths. The method we have tested will also enable automated assessment of para-articular and midshaft bone mineral density and erosion. The end goal an objective and sensitive measure of joint damage in arthritis, comparable to the Sharp-van der Heijde and Larsen scores. References: [1] Cootes, T.F., Edwards, G.J., and Taylor, C.J., "Active appearance models,"IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23, no. 6, pp. 681-685, 2001. [2] Thodberg, H.H. Hands-on Experience with Active Appearance Models. Sonka and Fitzpatrick. Medical Imaging 2002: Image Proceedings 4684, 495-506. 2002. SPIE

Ziekenhuisgroep Twente

Contains the raw data used for study titled: Dermatological guidelines for monitoring methotrexate treatment reduce drug-survival compared to rheumatological guidelines Note: Excel file has password to prevent unwanted changes in the data. The file is accessible on Read only mode

Detection of joint space narrowing in hand radiographs

Radiographic assessment of joint space narrowing in hand radiographs is important for determining the progression of rheumatoid arthritis in an early stage. Clinical scoring methods are based on manual measurements that are time consuming and subjected to intra-reader and inter-reader variance. The goal is to design an automated method for measuring the joint space width with a higher sensitivity to change1 than manual methods. The large variability in joint shapes and textures, the possible presence of joint damage, and the interpretation of projection images make it difficult to detect joint margins accurately. We developed a method that uses a modified active shape model to scan for margins within a predetermined region of interest. Possible joint space margin locations are detected using a probability score based on the Mahalanobis distance. To prevent the detection of false edges, we use a dynamic programming approach. The shape model and the Mahalanobis scoring function are trained with a set of 50 hand radiographs, in which the margins have been outlined by an expert. We tested our method on a test set of 50 images. The method was evaluated by calculating the mean absolute difference with manual readings by a trained person. 90% of the joint margins are detected within 0.12 mm. We found that our joint margin detection method has a higher precision considering reproducibility than manual readings. For cases where the joint space has disappeared, the algorithm is unable to estimate the margins. In these cases it would be necessary to use a different method to quantify joint damage