Quality-based pharmacokinetic model selection on DCE-MRI for characterizing orbital lesions.

BACKGROUND: Although several studies have evaluated dynamic contrast-enhanced (DCE) MRI in the orbit, showing its utility when detecting and diagnosing orbital lesions, none have evaluated the pharmacokinetic models. PURPOSE: To provide a quality-based pharmacokinetic model selection for characterizing orbital lesions using DCE-MRI at 3.0T. STUDY TYPE: Prospective. POPULATION: From December 2015 to April 2017, 151 patients with an orbital lesion underwent MRI prior to surgery, including a high temporal resolution DCE sequence, divided into one training and one test dataset with 100 and 51 patients, respectively. FIELD STRENGTH/SEQUENCE: 3T/DCE. ASSESSMENT: Six different pharmacokinetic models were tested. STATISTICAL TESTS: Univariate and multivariate analyses were performed using Wilcoxon-2-sample tests and a logistic regression to compare parameters between malignant and benign tumors for each pharmacokinetic model for the whole cohort. Receiver operating characteristic (ROC) curve analyses were performed on the training dataset to determine area under curve (AUC) and optimal cutoff values for each pharmacokinetic model, then validated on the test dataset to calculate sensitivity, specificity, and accuracy. RESULTS: Regardless of the model, tissue blood flow and tissue blood volume values were significantly higher in malignant vs. benign lesions: 103.8-195.1 vs. 65-113.8, P [<10-4 -2.10-4 ] and 21.3-36.9 vs. 15.6-33.6, P [<10-4 -0.03] respectively. Extracellular volume fraction and permeability-surface area product or transfer constant appeared to be less relevant: 17.3-27.5 vs. 22.8-28.2, P [0.01-0.7], 1.7-4.9, P [0.2-0.9] and 9.5-38.8 vs. 8.1-22.8, P [<10-4 -0.6], respectively. ROC curves showed no significant differences in AUC between the different models. The two-compartment exchange (2CX) model ranked first for quality. DATA CONCLUSION: DCE MRI pharmacokinetic model-derived parameters appeared to be useful for discriminating benign from malignant orbital lesions. The 2CX model provided the best quality of modeling and should be recommended. Perfusion-related DCE parameters appeared to be significantly more relevant to the diagnostic process. Level of Evidence 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:1514-1525.

Effects of circadian cortisol on the development of a health habit.

OBJECTIVE: Given the impact of individuals' habits on health, it is important to study how behaviors can become habitual. Cortisol has been well documented to have a role in habit formation. This study aimed to elucidate the influence of the circadian rhythm of cortisol on habit formation in a real-life setting. METHOD: Forty-eight students were followed for 90 days during which they attempted to adopt a health behavior (psoas iliac stretch). They were randomly assigned to perform the stretch either upon waking in the morning, when cortisol concentrations are high, or before evening bedtime, when cortisol levels approach the nadir. A smartphone application was used to assess the Self-Report Behavioural Automaticity Index every day and to provide reminders for salivary measurements every 30 days. The speed of the health habit formation process was calculated by modeling the learning curves. RESULTS: Extrapolation of the curves indicated that the morning group achieved automaticity at an earlier time point (105.95 days) than did the evening group (154.01 days). In addition, the cortisol level during the performance of the health behavior was identified as a significant mediator of the time point when the health behavior became habitual. CONCLUSION: The present findings suggest that the time course of the development of healthy habits depends on the time of the day and that the effect is mediated through diurnal variation in cortisol levels. Future studies are now needed to determine to what extent cortisol rhythmicity can help individuals to adopt new health behaviors. (PsycINFO Database Record