Associations of residential greenspace exposure and fetal growth across four areas in Spain

An accumulating body of evidence has associated exposure to greenspace with improved birth outcomes, including higher birth weight and lower risk of low birth weight; however, evidence on such association with in-utero fetal growth is scarce. We explored the influence of maternal exposure to residential greenspace and fetal growth in four INMA (Infancia y Medio Ambiente) Spanish birth cohorts (2003–2008), with 2,465 participants. Residential greenspace was characterised by the Normalised Difference Vegetation Index (NDVI) average across 100 m, 300 m, and 500 m buffers around the residence. Repeated ultrasound measurements of the abdominal circumference (AC), biparietal diameter (BPD), femur length (FL), and estimated fetal weight (EFW) were used. We created customised-generalised least squares models to evaluate associations of residential greenspace exposure on each fetal growth parameter, controlled for the relevant confounders. There were associations between the 500 m buffer and BPD, FL, and AC. We also found associations in the 300 m buffer and FL and AC. The associations in the 100 m buffer were null. Estimates were higher among participants with lower socioeconomic status. Mediation analyses found that air pollution might explain 15–37% of our associations. Mediation by physical activity was not observed. Greenspace exposure may be beneficial for fetal growth.     

The role of the sonographer – An investigation into the scope of practice for the sonographer internationally

IntroductionThere is global variance in the role of a practicing sonographer. Literature examining global sonographic roles and scope of practice is limited, despite the international applicability of ultrasound imaging. This study aimed to examine the common and divergent features of a practicing sonographer internationally, and their impact upon the development of a global standard of practice.MethodsAn ethically approved mixed-methods online survey was conducted. The purposive sample included all 75 current elected council members of the ISRRT [International Society of Radiographers and Radiological Technologists], an international professional organisation.ResultsThirty-six individuals from at least 32 different countries responded, reflecting the sonography profession in all four ISRRT regions. The results suggest that sonographer education requirements differ widely, from on the job training (16%, 6/36) to undergraduate or postgraduate schooling (44%, 16/36). Registration and accreditation bodies were present in the jurisdiction of 41% (14/34) and 35% (12/33) of respondents respectively, though many were voluntary, physician-focused or non-specific to sonographers. Five of 11 (45%) respondents suggested that the sonographer–radiologist relationship is individual-dependent, and not primarily positive or negative. Ten of 28 (36%) suggested that other professionals do not know the role of the sonographer.ConclusionThe majority of ISRRT council member respondents believe that an international scope of practice could benefit and be implemented in their jurisdiction (26/28, 93% and 22/33, 67%). The key advantages noted were standardisation of education and improved professional mobility. However, lack of sonographer education and radiologist acceptance are important potential barriers.Implications for practiceAn international scope of practice could be beneficial and implementable in most ISRRT jurisdictions. Professional mobility and education standardization are the primary advantages. Insufficient sonographer education and physician acceptance are the key potential obstacles.     

超声引导下辅助诊断和治疗冻结肩的研究进展

冻结肩是常见的肩部疾病,传统非可视化治疗冻结肩效果欠佳。近年来,超声引导具有动态实时定位、无辐射、便携性、低成本等优点在辅助诊断和治疗冻结肩患者中得到成功应用,不仅能提供精确的诊断,也提高了患者中长期的疗效。本文就超声引导辅助诊断和治疗冻结肩的研究进展进行综述。     

Comparing Radiomics features of tumour and healthy liver tissue in a limited CT dataset: A machine learning study

IntroductionLiver cancer lesions on Computed Tomography (CT) withholds a great amount of data, which is not visible to the radiologists and radiographer. Radiomics features can be extracted from the lesions and used to train Machine Learning (ML) algorithms to predict between tumour and liver tissue. The purpose of this study was to investigate and classify Radiomics features extracted from liver tumours and normal liver tissue in a limited CT dataset.MethodsThe Liver Tumour Segmentation Benchmark (LiTS) dataset consisting of 131 CT scans of the liver with segmentations of tumour tissue and healthy liver was used to extract Radiomic features. Extracted Radiomic features included size, shape, and location extracted with morphological and statistical techniques according to the International Symposium on Biomedical Imaging manual. Relevant features was selected with chi2 correlation and principal component analysis (PCA) with tumour and healthy liver tissue as outcome according to a consensus between three experienced radiologists. Logistic regression, random forest and support vector machine was used to train and validate the dataset with a 10-fold cross-validation method and the Grid Search as hyper-parameter tuning. Performance was evaluated with sensitivity, specificity and accuracy.ResultsThe performance of the ML algorithms achieved sensitivities, specificities and accuracy ranging from 96.30% (95% CI: 81.03%–99.91%) to 100.00% (95% CI: 86.77%–100.00%), 91.30% (95% CI: 71.96%–98.93%) to 100.00% (95% CI: 83.89%–100.00%)and 94.00% (95% CI: 83.45%–98.75%) to 100.00% (95% CI: 92.45%–100.00%), respectively.ConclusionML algorithms classifies Radiomics features extracted from healthy liver and tumour tissue with perfect accuracy. The Radiomics signature allows for a prognostic biomarker for hepatic tumour screening on liver CT.Implications for practiceDifferentiation between tumour and liver tissue with Radiomics ML algorithms have the potential to increase the diagnostic accuracy, assist in the decision-making of supplementary multiphasic enhanced medical imaging, as well as for developing novel prognostic biomarkers for liver cancer patients.     

Clinicopathologic factors and preoperative ultrasonographic characteristics for predicting central lymph node metastasis in papillary thyroid microcarcinoma: a single center retrospective study

IntroductionThe treatment of papillary thyroid microcarcinoma remains controversial. Central lymph node metastasis is common in papillary thyroid microcarcinoma and it is an important consideration in treatment strategy selection.ObjectiveThe aim of this study was to investigate clinicopathologic risk factors and thyroid nodule sonographic characteristics for central lymph node metastasis in papillary thyroid microcarcinoma.MethodsWe retrospectively reviewed the data of 599 papillary thyroid microcarcinoma patients who underwent surgery from 2005 to 2017 at a single institution. Univariate and multivariate analyses were used to identify the clinicopathologic factors and preoperative sonographic features of central lymph node metastasis. A receiver-operating characteristic, ROC curve analysis, was performed to identify the efficacy of ultrasonographic features in predicting central lymph node metastasis. A nomogram based on the risk factors was established to predict central lymph node metastasis.ResultsThe incidence of central lymph node metastasis was 22.4%. The univariate and multivariate analyses suggested that gender, age, multifocality, extrathyroidal invasion, and lateral lymph node metastasis were independent risk factors for central lymph node metastasis. The univariate and multivariate analyses revealed that nodular shape, margin, and calcification were independently associated with central lymph node metastasis. The ROC curve analysis revealed that the combination of shape, margin and calcification had excellent accuracy in predicting central lymph node metastasis. The nomogram was developed based on the identified risk factors for predicting central lymph node metastasis, and the calibration plot analysis indicated the good performance and clinical utility of the nomogram.ConclusionsCentral lymph node metastasis is associated with male gender, younger age (<45 years), extrathyroidal invasion, multifocality and lateral lymph node metastasis in papillary thyroid microcarcinoma patients. The ultrasongraphic features, such as irregular shape, ill-defined margin and calcification, may improve the efficacy of predicting central lymph node metastasis. Surgeons and radiologists should pay close attention to the patients who have these risk factors. The nomogram may help guide surgical decision making in papillary thyroid microcarcinoma.     

The use of cadaver models to diagnose rib fractures: A pilot study

Background

In the emergency department, rib fractures are a common finding in patients who sustain chest trauma. Rib fractures may be a sign of significant, underlying pathology, especially in the elderly patients where rib fractures are associated with significant morbidity and mortality. To date, no studies have evaluated the ability of ultrasound to detect rib fractures using cadaver models and subsequently use this model as a teaching tool.

超声多探头检查在新生儿颅脑疾病诊断中的应用

目的研究超声低频探头和低频探头联合高频探头检查在新生儿颅脑疾病诊断中的准确率和敏感性。 方法选取河源市妇幼保健院自2017年1月至2018年12月收治的有颅脑疾病高危因素(早产、低体质量、多胎妊娠、出生过程有缺氧窒息及产时感染)的新生儿90例作为研究对象。采用随机数字表法将所有新生儿平均分为2组，研究组（45例）给予低频探头联合高频探头进行探查，对照组（45例）仅给予低频探头进行探查。结合CT检查结果和临床治疗，比较2种检测方法的准确率和敏感性。 结果研究组检测新生儿缺氧缺血性脑病、脑室内出血和室管膜下出血诊断准确率分别为87.5%、100%、100%，高于相应对照组（15.38%、12.5%、0%），差异有统计学意义（P<0.05）；研究组和对照组检测脑实质内出血和脑积水的诊断准确率分别为87.5%、100%以及42.85%、66.67%，差异无统计学意义（P>0.05）。研究组检测新生儿颅脑疾病的效率为82.22%，高于对照组（22.22%），差异具有统计学意义（P<0.05）。 结论使用超声低频探头联合高频探头的方法提高了缺氧缺血性脑病、脑室内出血、室管膜下出血等新生儿颅脑疾病诊断的准确率，在诊断新生儿脑实质内出血和脑积水的准确率没有差异，且对颅脑疾病诊断的敏感性较高，因此具有较为重要的临床意义。