Although problems with the hands are well recognized in SSc, foot problems also occur in the majority of patients, and can be a cause of major disability. Care of the feet is therefore an important part of the management of SSC.

The patient, a 47-year-old man, presented with a 7-year history of forearm pain. He noted that his symptoms were worse after lifting or driving, and he was unable to drive for more than a few minutes without tingling and pain. His symptoms resolved with rest but recurred with physical activity. There was no history of trauma or joint swelling. A left carpal tunnel release had been performed 8 years previously. His medical history was otherwise unremarkable, there were no other current health problems, and he was not taking any medication. He had regularly trained with weights until his symptoms prevented this.Results of a general physical and neurologic examination were normal. His forearms were noted to be well developed and bulky. In view of his symptoms, dynamic (pre-and post-exercise) magnetic resonance imaging (MRI) was performed, and the resultant findings led to the measurement of compartment pressures, via needle intracompartmental pressure monitoring. The left forearm showed a resting pressure of 33 mm Hg, increasing to 144 mm Hg after several minutes of repetitive wrist flexion and extension (which also caused his symptoms to occur). After 2 minutes of rest the pressure decreased to 62 mm Hg. The patient underwent fasciotomy of the forearm extensors (at which the fascia was noted to be thickened), after which his symptoms resolved completely. He later underwent fasciotomy of the right forearm extensors and has resumed unlimited physical activity. Radiologic findingsMRI revealed classic features of a compartment syndrome. Following exercise, there were high signal

Image synthesis methods are based on the hypothesis that a magnetic resonance (MR) image with optimized contrast can be reproduced by synthesis from three calculated basic images of T1, T2 and spin density. This method, however, is limited by noise due to uncertainties in the initial measurements. The principal component analysis (PCA) method is based on an information theory approach that decomposes MR images into a small set of characteristic feature images. PCA images, or eigenimages, show morphology by condensing the structural information from the source images. Eigenimages have also been shown to improve contrast-to-noise ratio (CNR) compared with source images. In this study we have developed a method of synthesizing MR images using a flexible model, comprising a set of eigenimages derived from PCA. A matching process has been carried out to find the best fit between the model and a synthetic image calculated from the Bloch equations. The method has been applied to MR images obtained from a group of patients with intracranial lesions. The images derived from the flexible model show increased lesion conspicuity, reduced artefact and comparable CNR to the directly acquired images while maintaining the MR characteristic information for diagnosis.

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