Scar sarcoidosis on a finger mimicking a rapidly growing soft tissue tumour: a case report

Background: Scar sarcoidosis is a rare and uncommon but specific cutaneous manifestation of sarcoidosis. In general it arises in pre-existing scars deriving from mechanical traumas. As most surgeons dealing with scars might not be aware of cutaneous sarcoidosis and its different types of appearance the appropriate staging and treatment might be missed or at least delayed. To our knowledge this is the first case in literature of scar sarcoidosis on a finger. Case presentation: We present a case of a 33-year-old carpenter who developed scar sarcoidosis on his right index finger 4 years after the tendon of the long digital flexor got accidentally cut by an angle grinder. He was referred due to a swelling of the finger suspected to be a malignant soft tissue tumour. The circumference of the affected finger had almost doubled, adding up to 94 mm. Incision biopsy revealed typical noncaseating granulomas. Further investigation showed a systemic extent of the disease with involvement of the lung. A systemic treatment with oral steroids led to an almost full regression of the swelling with restoration of function and resolution of lung infiltrates. Conclusion: In case of a suspicious and/or progressive swelling a definite diagnosis should be achieved by biopsy within a short time to enable a proper treatment. If scar sarcoidosis is proven further investigation is necessary to exclude a systemical involvement. A surgical treatment of the swelling is not indicated.</p

Small sharp exostosis tip in solitary osteochondroma causing intermittent knee pain due to pseudoaneurysm

Background: Complications of solitary or multiple osteochondromas are rare but have been reported in recent literature. Most reported complications arose in patients with multiple and/or sizable osteochondromas. Case presentation: A 22-year-old, female, Caucasian patient with obesity presented with intermittent knee pain and hematoma of the right calf. The MRI depicted a small, sharp exostosis tip of the dorsal distal femur with a surrounding soft-tissue mass. After profuse bleeding occurred during biopsy of the soft tissue mass, angiography revealed a pseudoaneurysm of the right popliteal artery. In a second-stage surgery the exostosis tip and pseudoaneurysm were resected. Conclusion: Complications can also arise in small, seemingly harmless osteochondromas. Surgical resection should be considered as a preventive measure when exostoses form sharp tips close to neurovascular structures regardless of total osteochondroma size.<br

Studying neuroanatomy using MRI

The study of neuroanatomy using imaging enables key insights into how our brains function, are shaped by genes and environment, and change with development, aging, and disease. Developments in MRI acquisition, image processing, and data modelling have been key to these advances. However, MRI provides an indirect measurement of the biological signals we aim to investigate. Thus, artifacts and key questions of correct interpretation can confound the readouts provided by anatomical MRI. In this review we provide an overview of the methods for measuring macro- and mesoscopic structure and inferring microstructural properties; we also describe key artefacts and confounds that can lead to incorrect conclusions. Ultimately, we believe that, though methods need to improve and caution is required in its interpretation, structural MRI continues to have great promise in furthering our understanding of how the brain works

Predicting age from cortical structure across the lifespan

Despite inter-individual differences in cortical structure, cross-sectional and longitudinal studies have demonstrated a large degree of population-level consistency in age-related differences in brain morphology. The present study assessed how accurately an individual’s age could be predicted by estimates of cortical morphology, comparing a variety of structural measures, including thickness, gyrification, and fractal dimensionality. Structural measures were calculated across up to seven different parcellation approaches, ranging from 1 region to 1000 regions. The age-prediction framework was trained using morphological measures obtained from T1-weighted MRI volumes collected from multiple sites, yielding a training dataset of 1056 healthy adults, aged 18-97. Age predictions were calculated using a machine-learning approach that incorporated non-linear differences over the lifespan. In two independent, held-out test samples, age predictions had a median error of 6-7 years. Age predictions were best when using a combination of cortical metrics, both thickness and fractal dimensionality. Overall, the results reveal that age-related differences in brain structure are systematic enough to enable reliable age prediction based on metrics of cortical morphology