Predictors of Disease Recurrence after Venoplasty and Stent Placement for May–Thurner Syndrome

PurposeTo identify factors independently associated with disease recurrence after venoplasty and stent placement for May–Thurner syndrome (MTS).Materials and MethodsFifty-nine consecutive patients (age, 47 y ± 15; 93% female) were identified who had undergone endovascular stent placement for MTS. Patient charts were reviewed for demographic data, risk factors for venous thrombosis, comorbidities, and venous inflow or outflow at first follow-up (3 wk to 6 mo after treatment). Logistic regression was used to identify independent predictors of symptom recurrence or repeat intervention, and multivariate analysis of variance and receiver operator characteristic curve analysis were used to assess relationships between degrees of in-stent stenosis and other variables in the 73% of patients with available cross-sectional imaging. Median follow up was 20.7 months (interquartile range, 4.7–49.5 mo).ResultsAll procedures were technically successful. Disease recurrence, defined as symptom recurrence following initial postprocedural resolution, was observed in 38% of patients. No preprocedural variable was found to be independently predictive of disease recurrence; however, poor venous inflow or outflow were both strongly associated with recurrent disease, with adjusted odds ratios and 95% confidence intervals of 38.02 (3.76–384.20; P = .002) and 7.00 (1.15–42.71; P = .04), respectively. Higher degrees of in-stent stenosis were also associated with symptom recurrence, with an area under the curve of 0.93 (P = .000002) and 39%–41% stenosis being 78%–83% sensitive and 88%–92% specific for symptom recurrence.ConclusionsThese results suggest that cross-sectional imaging can help differentiate patients in whom closer follow-up may be warranted after venoplasty and stent placement for MTS and also guide counseling regarding prognosis.     

Radiomics for classification of bone mineral loss: A machine learning study

PurposeThe purpose of this study was to develop predictive models to classify osteoporosis, osteopenia and normal patients using radiomics and machine learning approaches.Materials and methodsA total of 147 patients were included in this retrospective single-center study. There were 12 men and 135 women with a mean age of 56.88 ± 10.6 (SD) years (range: 28–87 years). For each patient, seven regions including four lumbar and three femoral including trochanteric, intertrochanteric and neck were segmented on bone mineral densitometry images and 54 texture features were extracted from the regions. The performance of four feature selection methods, including classifier attribute evaluation (CLAE), one rule attribute evaluation (ORAE), gain ratio attribute evaluation (GRAE) and principal components analysis (PRCA) along with four classification methods, including random forest (RF), random committee (RC), K-nearest neighbor (KN) and logit-boost (LB) were evaluated. Four classification categories, including osteopenia vs. normal, osteoporosis vs. normal, osteopenia vs. osteoporosis and osteoporosis + osteopenia vs. osteoporosis were examined for the defined seven regions. The classification model performances were evaluated using the area under the receiver operator characteristic curve (AUC).ResultsThe AUC values ranged from 0.50 to 0.78. The combination of methods RF + CLAE, RF + ORAE and RC + ORAE yielded highest performance (AUC = 0.78) in discriminating between osteoporosis and normal state in the trochanteric region. The combinations of RF + PRCA and LB + PRCA had the highest performance (AUC = 0.76) in discriminating between osteoporosis and normal state in the neck region.ConclusionThe machine learning radiomic approach can be considered as a new method for bone mineral deficiency disease classification using bone mineral densitometry image features.     

Validation and confirmatory factor analysis of the pediatric Adherence Barriers to Continuous Positive Airway Pressure Questionnaire

ObjectiveTo evaluate and refine a newly proposed factor structure for the Adherence Barriers to Continuous Positive Airway Pressure Questionnaire (ABCQ) and to present psychometric data from a large, geographically diverse sample of children and young adults with sleep disordered breathing (SDB) treated with positive airway pressure (PAP).MethodsA sample of 181 patients prescribed PAP for treatment of SDB, ages 8–21 years, and caregivers (n = 234) of patients ages 2–21 years, completed the ABCQ during routine sleep medicine clinic visits. Adherence data from participants' PAP machines were obtained via electronic download, providing objective data on PAP adherence immediately preceding the clinic visit during which the ABCQ was completed.ResultsA three-factor structure (1. Behavior, Beliefs, Environment, 2. Emotional Barriers, & 3. Physical Barriers) exhibited good model fit in confirmatory factor analysis. Results indicate that the ABCQ has strong psychometric properties, including good internal consistency among subscales and strong convergent validity with objectively measured PAP adherence. Analysis of the Receiver Operator Characteristic Curve (ROC) yielded an ABCQ total cut-off score of 46.5 for patient report and 53.5 for caregiver report. Scores above the cutpoint predicted nonadherence to PAP, defined as failure to use PAP for ≥4 h on 70% of nights.ConclusionsThe three-factor ABCQ appears to be a useful patient- and caregiver-report instrument to measure barriers to PAP treatment in children and young adults with sleep disordered breathing.     

X-ray operators' self-perceived competence,barriers and facilitators in general radiography practice in Western Australia

IntroductionAustralian X-ray operators (XROs) are health workers qualified with a limited radiography licence to perform basic radiography examinations in rural areas of Australia. However, no previous study explored Western Australian (WA) XROs' radiography practice. The purpose of this study was to investigate WA XROs’ self-perceived competence in the general radiography practice, and barriers and facilitators to their competence for determination of appropriate strategies to improve quality and safety of the radiographic service provided by them.MethodsInstitutional review board approval and informed consent from participants were obtained. Interviews were conducted with the WA XROs to obtain demographic information and identify their self-perceived competence in the general radiography practice, and the barriers and facilitators to their competence. A thematic analysis was used to analyse the interview data.ResultsA total of nine interviews were conducted (eight nurses and one paramedic). Participants indicated that they felt highly competent in patient care in radiography and adequately competent in the production of diagnostically acceptable images. The self-perceived barriers include overload of responsibilities, a lack of continuing professional development, and inadequacy of communication, support and XRO courses. The facilitators, post-qualification/course training, support in undertaking examinations, primary professional roles and a small population of the rural and remote areas were identified.ConclusionBased on interview data from nine WA XROs, the perception is that they have competence adequate for providing an acceptable quality radiographic service.Implications for practiceA continuous XRO course review, and provision of a video conference support channel, an online XRO networking forum and additional XROs and/or radiographers working with XROs undertaking the radiography examinations were perceived as the appropriate strategies to improve the WA XROs’ radiography practice. However, these require financial and/or managerial support from governments.     

Geometrical Measurement of Central Tumor Location in cT1N0M0 NSCLC Predicts N1 but Not N2 Upstaging

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Perivascular fat attenuation for predicting adverse cardiac events in stable patients undergoing invasive coronary angiography

BackgroundInflammation surrounding the coronary arteries can be non-invasively assessed using pericoronary adipose tissue attenuation (PCAT). While PCAT holds promise for further risk stratification of patients with low coronary artery disease (CAD) prevalence, its value in higher risk populations remains unknown.MethodsCORE320 enrolled patients referred for invasive coronary angiography with known or suspected CAD. Coronary computed tomography angiography (CCTA) images were collected for 381 patients for whom clinical outcomes were assessed 5 years after enrollment. Using semi-automated image analysis software, PCAT was obtained and normalized for the right coronary (RCA), left anterior descending (LAD), and left circumflex arteries (LCx). The association between PCAT and major adverse cardiovascular events (MACE) during follow up was assessed using Cox regression models.ResultsThirty-seven patients were excluded due to technical failure. For the remaining 344 patients, median age was 62 (interquartile range, 55–68) with 59% having ≥1 coronary artery stenosis of ≥50% by quantitative coronary angiography. Mean attenuation values for PCAT in RCA, LAD, and LCx were ?74.9, ?74.2, and ?71.2, respectively. Hazard ratios and 95% confidence intervals (CI) for normalized PCAT in the RCA, LAD, and LCx for MACE were 0.96 (CI: 0.75–1.22, p ?= ?0.71), 1.31 (95% CI: 0.96–1.78, p ?= ?0.09), and 0.98 (95% CI: 0.78–1.22, p ?= ?0.84), respectively. For death, stroke, or myocardial infarction only, hazard ratios were 0.68 (0.44–1.07), 0.85 (0.56–1.29), and 0.57 (0.41–0.80), respectively.ConclusionsIn patients referred for invasive coronary angiography with suspected CAD, PCAT did not predict MACE during long term follow up. Further studies are needed to understand the relationship of PCAT with CAD risk.