Is sport practice a risk factor for shoulder injuries in tetraplegic individuals?

STUDY DESIGN: A retrospective cohort. OBJECTIVES: To report the incidence rates of shoulder injuries diagnosed with magnetic resonance imaging (MRI) in tetraplegic athletes and sedentary tetraplegic individuals. To evaluate whether sport practice increases the risk of shoulder injuries in tetraplegic individuals. SETTING: Campinas, Sao Paulo, Brazil. METHODS: Ten tetraplegic athletes with traumatic spinal cord injury were selected among quad rugby athletes and had both the shoulders evaluated by MRI. They were compared with 10 sedentary tetraplegic individuals who were submitted to the same radiological protocol. RESULTS: All athletes were male with a mean age of 32.1 years (range 25-44 years, s.d.=6.44). Time since injury ranged from 6 to 17 years, with a mean value of 9.7 years and s.d. of 3.1 years. All sedentary individuals were male with a mean age of 35.9 years (range 22-47 years, s.d.=8.36). Statistical analysis showed a protective effect of sport in the development of shoulder injuries, with a weak correlation for infraspinatus and subscapularis tendinopathy (P=0.09 and P=0.08, respectively) and muscle atrophy (P=0.08). There was a strong correlation for acromioclavicular joint (ACJ) and labrum injuries (P=0.04), with sedentary individuals at a higher risk for these injuries. CONCLUSION: Tetraplegic athletes and sedentary individuals have a high incidence of supraspinatus tendinosis, bursitis and ACJ degeneration. Statistical analysis showed that there is a possible protective effect of sport in the development of shoulder injuries. Weak evidence was encountered for infraspinatus and subscapularis tendinopathy and muscle atrophy (P=0.09, P=0.08 and P=0.08, respectively). Strong evidence with P=0.04 suggests that sedentary tetraplegic individuals are at a greater risk for ACJ and labrum injuries.

Semi-automatic determination of detailed vertebral shape from lumbar radiographs using active appearance models.

SUMMARY: The vertebral endplates in lumbar radiographs were located by a semi-automatic annotation method using statistical shape models. INTRODUCTION: Vertebral fractures are common osteoporotic fractures, but current quantitative detection methods (morphometry) lack specificity. We have previously developed more specific quantitative classifiers of vertebral fracture using shape and appearance models. This method has only been applied to DXA vertebral fracture assessment (VFA) images and not to spinal radiographs. The classifiers require a detailed annotation of the outline of the vertebral endplate, so we investigated the application of similar semi-automated annotation methods to lumbar radiographs as the initial step in the generalisation of the statistical classifiers used in VFA images. METHODS: The vertebral body outlines in a training set of 670 lumbar radiographs were manually annotated by expert radiologists. This training set was used to build statistical models of vertebral shape and appearance using triplets of vertebrae. In order to segment vertebrae, the models were refitted using a sequence of active appearance models of vertebral triplets, using a miss-40-out train/test cross-validation experiment. The accuracy was evaluated against the manual annotation and analysed by fracture grade. RESULTS: Good accuracy was obtained for normal vertebrae (0.82 mm) and fracture grades 1 and 2 (1.19 mm), but the localisation accuracy deteriorated for grade 3 fractures to 2.12 mm. CONCLUSION: Vertebral body shape annotation can be substantially automated on lumbar radiographs. However, an occasional manual correction may be required, typically with either severe fractures, or when there is a high degree of projectional tilting or scoliosis. The located detailed shapes may enable the development of more powerful quantitative classifiers of osteoporotic vertebral fracture.

Detection of vertebral fractures in DXA VFA images using statistical models of appearance and a semi-automatic segmentation.

SUMMARY: Morphometric methods of vertebral fracture diagnosis lack specificity. We used detailed shape and image texture model parameters to improve the specificity of quantitative fracture identification. Two radiologists visually classified all vertebrae for system training and evaluation. The vertebral endplates were located by a semi-automatic segmentation method to obtain classifier inputs. INTRODUCTION: Vertebral fractures are common osteoporotic fractures, but current quantitative detection methods (morphometry) lack specificity. We used detailed shape and texture information to develop more specific quantitative classifiers of vertebral fracture to improve the objectivity of vertebral fracture diagnosis. These classifiers require a detailed segmentation of the vertebral endplate, and so we investigated the use of semi-automated segmentation methods as part of the diagnosis. METHODS: The vertebrae in a training set of 360 dual energy X-ray absorptiometry images were manually segmented. The shape and image texture of vertebrae were statistically modelled using Appearance Models. The vertebrae were given a gold standard classification by two radiologists. Linear discriminant classifiers to detect fractures were trained on the vertebral appearance model parameters. Classifier performance was evaluated by cross-validation for manual and semi-automatic segmentations, the latter derived using Active Appearance Models (AAM). Results were compared with a morphometric algorithm using the signs test. RESULTS: With manual segmentation, the false positive rates (FPR) at 95% sensitivity were: 5% (appearance) and 18% (morphometry). With semi-automatic segmentations the sensitivities at 5% FPR were: 88% (appearance) and 79% (morphometry). CONCLUSION: Specificity and sensitivity are improved by using an appearance-based classifier compared to standard height ratio morphometry. An overall sensitivity loss of 7% occurs (at 95% specificity) when using a semi-automatic (AAM) segmentation compared to expert annotation, due to segmentation error. However, the classifier sensitivity is still adequate for a computer-assisted diagnosis system for vertebral fracture, especially if used in a triage approach.

Detection of osteoporosis by dual energy X-ray absorptiometry (DXA) of the calcaneus: is the WHO criterion applicable?

The study assessed the precision, sensitivity, and specificity of a recently developed peripheral dual-energy X-ray absorptiometry (DXA) scanner, applied to the calcaneus, in the identification of individuals with osteoporosis at axial sites by DXA. Two hundred and two women, aged 55.2 +/- l3.7 years (mean +/- SD), participated in the study. The precisions (coefficient of variation) of measurements in vitro (0.48%) and in vivo (1.40%) were very good. The in vivo precision was independent of the operator, foot size, foot width, weight, height, and body mass index. Calcaneus BMD correlated moderately (r = 0.494-0.690, P <0.001) with axial BMD measurements by DXA. Using the World Health Organization (WHO) criterion for defining osteoporosis (T score ? -2.5) the specificity of the calcaneus to identify patients with osteoporosis at total hip, femoral neck, spine, or any of these axial sites was excellent (97.0%, 97.0%, 96.5%, and 97.1%, respectively); however, the sensitivity was poor (58.8%, 36.4%, 21.8%, and 20.3%, respectively). Therefore, the WHO criterion is not appropriate for DXA calcaneus. Based on femoral neck BMD for detection of osteoporosis, a more appropriate calcaneus T score threshold would be -1.4 by analyses of receiver-operator characteristic curves; this might serve to select those patients who might appropriately be referred for axial DXA.