Update on sports imaging

Sports Imaging has dramatically increased in the past decade with increasing number of adolescents, young and middle-aged adults participating in non-competitive/hobby sports. Therefore, sports injuries are no longer confined to elite athletes. Furthermore, newer forms of sports such as mountain climbing, pickle ball and curling etc. are gaining popularity. Majority of the injuries in sports medicine are from musculoskeletal trauma. Therefore, it is imperative that the musculoskeletal radiologist becomes familiar with various sports related injury patterns as these are commonly encountered in daily practice. This update aims to briefly encapsulate the major aspects of sports imaging. It includes the imaging manifestations of various types of musculoskeletal injuries on different modalities (commonly US and MRI) and briefly mentions the various image guided interventions, performed both on the sports field and in the hospital setting.     

Comparing the rates of low-value back images ordered by physicians and nurse practitioners for Medicare beneficiaries in primary care

BackgroundLittle is known about the extent of ordering low-value services by.PurposeTo compare the rates of low-value back images ordered by primary care physicians (PCMDs) and primary care nurse practitioners (PCNPs).MethodWe used 2012 and 2013 Medicare Part B claims for all beneficiaries in 18 hospital referral ?regions (HRRs) and a measure of low-value back imaging from Choosing Wisely. Models included random clinician effect and fixed effects for beneficiary age, disability, Elixhauser comorbidities, clinician sex, the emergency department setting, back pain visit volume, organization, and region (HRR).FindingsPCNPs (N = 231) and PCMDs (N = 4,779) order low-value back images at similar rates (NP: all images: 26.5%; MRI/CT: 8.4%; MD: all images: 24.5%; MRI/CT: 7.7%), with no detectable significant difference when controlling for covariates.DiscussionPCNPs and PCMDs order low-value back images at an effectively similar rate.     

Microspheres of essential oil in polylactic acid and poly(methyl methacrylate) matrices and their blends

This study is focussed on micro-encapsulation of essential oils in polylactic acid (PLA) and a poly(methyl methacrylate) (PMMA) matrix as well as blends of the same. Microspheres were prepared by the solvent evaporation technique and characterised by scanning electron microscopy (SEM), differential scanning calorimetry (DSC) and Fourier transform infra-red spectroscopy (FTIR). The encapsulation efficiencies and release profiles of the essential oils were studied by gas chromatography mass spectrometry (GC-MS) and head-space solid-phase microextraction GC-MS, respectively. Furthermore, the microspheres were tested for antibacterial activity against both Gram-negative and Gram-positive bacterial strains.

The results showed that the microspheres compositions (PLA/PMMA ratio) have significant effect on their characteristics. The process adopted for preparing the microspheres promoted formation of spherical particles at the sizes of 1.5–9.5?µm. The highest encapsulation efficiency of the prepared microspheres was observed in systems consisting of linalool (81.10?±?10.0?wt. % for PLA system and 76.0?±?3.3?wt. % for PMMA system). Confirmation was also made that the release rate of the microspheres was affected by the size of the same.     

Utility of Tissue Similarity Maps Based on Relative Cerebral Blood Volume for Grading Gliomas as Validated by Histological Results

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The effect of different statistical approaches on image quality data obtained from radiological examinations

IntroductionSelection of optimal image acquisition protocols in medical imaging remains a grey area, the superimposed use of the Likert scale in radiological image quality evaluations creates an additional challenge for the statistical analysis of image quality data.Using a simulation study, we have trialled a novel approach to analysing radiological image quality Likert scale data.MethodsA simulation study was undertaken where simulated datasets were generated based on the distribution of Likert scale values according to varying image acquisition protocols from a real dataset. Simulated Likert scale values were pooled in four different ways; the mean, median, mode and the summation of patient Likert scale values of which the total was assigned a categorical Likert scale value. Estimates of bias, MAPE and RMSPE were then calculated for all four pooling approaches to determine which method most accurately represented an expert's opinion.ResultsWhen compared to an expert's opinion, the method of summation and categorisation of Likert scale values was most accurate 49 times out of the 114 (43.0%) tests. The mean 28 times out of 114 (24.6%), the median 23 times out of 114 (20.2%) and the mode 17 times out of 114 (14.9%).ConclusionWe conclude that our method of summation and categorisation of Likert scale values is most often the best representation of the simulated data compared to the expert's opinion.Implications for practiceThere is scope to reproduce this simulation study with multiple observers to reflect clinical reality more accurately with the dynamic nature of multiple observers. This also prompts future investigation into other anatomical areas, to see if the same methods produce similar results.