Longitudinal analysis of vertebral fracture and BMD in a Canadian cohort of adult cystic fibrosis patients

<p>Abstract</p> <p>Background</p> <p>Vertebral fractures in patients with cystic fibrosis (CF) may contribute to an accelerated decline in lung function and can be a contraindication to lung transplantation. In this study, we examined longitudinal change in bone mineral density (BMD) and the prevalence of vertebral fractures in adult CF patients, without lung-transplant, attending a Canadian specialty clinic.</p> <p>Methods</p> <p>Retrospective chart review of all patients attending an Adult Cystic Fibrosis Clinic at Hamilton Health Sciences in Hamilton, Canada. Forty-nine of 56 adults met inclusion criteria. Chest radiographs were graded by consensus approach using Genant's semi-quantitative method to identify and grade fractured vertebrae. Dual x-ray absorptiometry (DXA) scans were also reviewed.</p> <p>Results</p> <p>The mean age of the cohort was 25.2 years (SD 9.4), 43% were male. The mean body mass index (BMI) was 19.8 (2.8) for males and 21.7 (5.1) for females. At baseline, the rate of at least one vertebral fracture was 16.3%; rising to 21.3% (prevalent and incident) after a 3-year follow-up. The mean BMD T-or Z-scores at baseline were -0.80 (SD 1.1) at the lumbar spine, -0.57 (SD 0.97) at the proximal femur, and -0.71 (SD 1.1) at the whole body. Over approximately 4-years, the mean percent change in BMD was -1.93% at the proximal femur and -0.73% at the lumbar spine.</p> <p>Conclusion</p> <p>Approximately one in five CF patients demonstrated at least one or more vertebral fractures. Moderate declines in BMD were observed. Given the high rate of vertebral fractures noted in this cohort of adult CF patients, and the negative impact they have on compromised lung functioning, regular screening for vertebral fractures should be considered on routine chest radiographs.</p

Pediatric DXA: technique and interpretation

This article reviews dual X-ray absorptiometry (DXA) technique and interpretation with emphasis on the considerations unique to pediatrics. Specifically, the use of DXA in children requires the radiologist to be a “clinical pathologist” monitoring the technical aspects of the DXA acquisition, a “statistician” knowledgeable in the concepts of Z-scores and least significant changes, and a “bone specialist” providing the referring clinician a meaningful context for the numeric result generated by DXA. The patient factors that most significantly influence bone mineral density are discussed and are reviewed with respect to available normative databases. The effects the growing skeleton has on the DXA result are also presented. Most important, the need for the radiologist to be actively involved in the technical and interpretive aspects of DXA is stressed. Finally, the diagnosis of osteoporosis should not be made on DXA results alone but should take into account other patient factors

Discovertebral (Andersson) lesions of the spine in ankylosing spondylitis revisited

A well-known complication in patients with ankylosing spondylitis (AS) is the development of localised vertebral or discovertebral lesions of the spine, which was first described by Andersson in 1937. Since then, many different terms are used in literature to refer to these localised lesions of the spine, including the eponym ‘Andersson lesion’ (AL). The use of different terms reflects an ongoing debate on the exact aetiology of the AL. In the current study, we performed an extensive review of the literature in order to align communication on aetiology, diagnosis and management between treating physicians. AL may result from inflammation or (stress-) fractures of the complete ankylosed spine. There is no evidence for an infectious origin. Regardless of the exact aetiology, a final common pathway exists, in which mechanical stresses prevent the lesion from fusion and provoke the development of pseudarthrosis. The diagnosis of AL is established on conventional radiography, but computed tomography and magnetic resonance imaging both provide additional information. There is no indication for a diagnostic biopsy. Surgical instrumentation and fusion is considered the principle management in symptomatic AL that fails to resolve from a conservative treatment. We advise to use the term Andersson lesion for these spinal lesions in patients with AS

Vertebral Body Compression Fractures and Bone Density: Automated Detection and Classification on CT Images

Purpose To create and validate a computer system with which to detect, localize, and classify compression fractures and measure bone density of thoracic and lumbar vertebral bodies on computed tomographic (CT) images. Materials and Methods Institutional review board approval was obtained, and informed consent was waived in this HIPAA-compliant retrospective study. A CT study set of 150 patients (mean age, 73 years; age range, 55-96 years; 92 women, 58 men) with (n = 75) and without (n = 75) compression fractures was assembled. All case patients were age and sex matched with control subjects. A total of 210 thoracic and lumbar vertebrae showed compression fractures and were electronically marked and classified by a radiologist. Prototype fully automated spinal segmentation and fracture detection software were then used to analyze the study set. System performance was evaluated with free-response receiver operating characteristic analysis. Results Sensitivity for detection or localization of compression fractures was 95.7% (201 of 210; 95% confidence interval [CI]: 87.0%, 98.9%), with a false-positive rate of 0.29 per patient. Additionally, sensitivity was 98.7% and specificity was 77.3% at case-based receiver operating characteristic curve analysis. Accuracy for classification by Genant type (anterior, middle, or posterior height loss) was 0.95 (107 of 113; 95% CI: 0.89, 0.98), with weighted κ of 0.90 (95% CI: 0.81, 0.99). Accuracy for categorization by Genant height loss grade was 0.68 (77 of 113; 95% CI: 0.59, 0.76), with a weighted κ of 0.59 (95% CI: 0.47, 0.71). The average bone attenuation for T12-L4 vertebrae was 146 HU ± 29 (standard deviation) in case patients and 173 HU ± 42 in control patients; this difference was statistically significant (P &lt; .001). Conclusion An automated machine learning computer system was created to detect, anatomically localize, and categorize vertebral compression fractures at high sensitivity and with a low false-positive rate, as well as to calculate vertebral bone density, on CT images. © RSNA, 2017 Online supplemental material is available for this article