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.     

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

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膀胱肿瘤切除术后尿路感染病原学和危险因素

目的观察膀胱肿瘤切除术后患者尿路感染发生情况与病原学特征,分析诱发尿路感染的危险因素,并提出合理且具备针对性的冲洗对策,为未来膀胱肿瘤切除术后尿路感染的预防提供合理参考。方法回顾性分析连云港市第一人民医院2016年1月-2019年1月接受经尿道膀胱肿瘤切除术治疗的451例膀胱肿瘤患者的临床资料,收集患者病例资料,全部患者术后均定期取尿液标本进行细菌培养,参照相关标准判定患者尿路感染情况,记录患者一般情况,包括一般人口学资料(性别、年龄、体质量、受教育程度等),同时记录患者糖尿病的疾病合并情况,将术后尿路感染可能的危险因素纳入初步分析,Logistic多因素回归分析膀胱肿瘤切除术后发生尿路感染的危险因素。结果451例膀胱肿瘤切除术患者术后第3天尿液中细菌培养阳性例数为80例,阳性率为17.74%,在使用抗菌药物后,患者尿液中细菌培养阳性率逐渐降低,各时点尿液细菌阳性培养率比较,差异有统计学意义(P<0.05);经多因素Logistic回归分析检验证实,高龄、血糖水平控制不佳、术前留置导尿管、多发肿瘤是膀胱肿瘤切除术后尿路感染的危险因素(OR>1,P<0.05);80例术后尿液细菌培养阳性患者共分离出87株菌株,其中革兰阴性菌66株占75.86%,革兰阳性球菌21株占24.14%。结论膀胱肿瘤切除术后患者有较高的尿路感染风险,革兰阴性菌是主要的感染病原菌,年龄、基础疾病、肿瘤位点、术前导尿管留置等是影响因素,这类患者应引起临床高度重视。     

Atypical cutaneous γδ T cell proliferation with morphologic features of lymphoma but with clinical features and course of PLEVA or lymphomatoid papulosis

Reactive lymphoid infiltrates of the skin composed predominantly of gamma‐delta (γδ) T cells are not well described in the literature. Herein we report a case of an otherwise healthy 4‐year‐old male who presented with a waxing and waning papular rash characterized by small, discrete crusted papules spread across his trunk, face and extremities. Clinical evaluation revealed no evidence of systemic disease. Microscopic examination revealed a dermal, perivascular infiltrate of highly atypical lymphocytes with a γδ T cell phenotype, worrisome for primary cutaneous γδ T cell lymphoma. The clinical course, however, was that of a reactive condition and prompted consideration of a diagnosis of pityriasis lichenoides et varioliformis acuta (PLEVA) and lymphomatoid papulosis (LyP). In many ways, this case defies current classification schemes and seems to expand the spectrum of reactive γδ T cell infiltrates of the skin.     

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.