European radiology
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To evaluate organisational reporting infrastructure and patient-related reporting data in the diagnosis of vertebral fragility fractures (VFFs) as demonstrated on computed tomography (CT). ⋯ • Early detection and diagnosis of vertebral fragility fractures (VFFs) significantly reduce patient morbidity and mortality. This study describes the results of a retrospective UK-wide audit evaluating current radiology reporting practice in the opportunistic diagnosis of VFFs as demonstrated on computed tomography (CT) studies including the spine. • Key audit standards included comment made on bone integrity in primary report (target 100%), comment made on severity of fractures (90%), report used recommended terminology 'fracture' (100%), and report made appropriate recommendations for referral/further assessment (100%). The audit results demonstrated a lack of compliance with all audit standards; lack of compliance was most marked in the use of recommended terminology (achieved 60.3%), in relation to comment on fracture severity (achieved 26.2%) and for recommendation for referral/further assessment (achieved 2.6%). • Solutions are challenging and multifactorial but the opportunity exists for all radiologists to examine their practice and directly improve patient care.
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To delineate the evolution of CT findings in patients with mild COVID-19 pneumonia. ⋯ • Four of 88 (4.5%) patients with COVID-19 had negative initial CT. • Majority of COVID-19 patients had abnormal CT findings in ≥ 3 lobes. • A proportion of patients with pure ground glass opacities decreased over the 3 weeks after symptom onset.
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To demonstrate proof-of-concept for a quantitative MRI method using histographic analysis to assess bone marrow oedema and fat metaplasia in the sacroiliac joints. ⋯ • Quantitative MRI with histographic analysis can identify bone marrow oedema (an active inflammatory lesion) and fat metaplasia (a 'chronic' inflammatory lesion) in patients with spondyloarthritis. • The use of histographic analysis might improve the performance of quantitative MRI for detecting bone marrow oedema and fat metaplasia compared with simple averages such as the mean and median. • Bone marrow oedema and fat metaplasia are known to be of diagnostic and prognostic significance, and the proposed method could support clinical decisions around biologic (and other) therapies in spondyloarthritis.
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Review Meta Analysis
Diagnostic accuracy and potential covariates for machine learning to identify IDH mutations in glioma patients: evidence from a meta-analysis.
To assess the diagnostic accuracy of machine learning (ML) in predicting isocitrate dehydrogenase (IDH) mutations in patients with glioma and to identify potential covariates that could influence the diagnostic performance of ML. ⋯ • Machine learning demonstrated an excellent diagnostic performance for prediction of IDH mutation in glioma (the pooled sensitivity and specificity were 88% and 87%, respectively). • Machine learning that used conventional MRI sequences demonstrated higher specificity in predicting IDH mutation than that based on conventional and advanced MRI sequences (89% vs. 85%). • Integration of clinical and imaging features in machine learning yielded a higher sensitivity (90% vs. 83%) and specificity (90% vs. 82%) than that achieved by using imaging features alone.