Response to neoadjuvant chemoradiotherapy for locally advanced rectum cancer: Texture analysis of dynamic contrast-enhanced MRI.

BACKGROUND: Tumor heterogeneity can be assessed by texture analysis (TA). TA has been applied using diffusion-weighted imaging and apparent diffusion coefficient maps to predict pathological responses to preoperative chemoradiation therapy (CRT) in patients with locally advanced rectal cancer (LARC). PURPOSE: To evaluate the texture parameters obtained from K trans maps derived from dynamic contrast-enhanced (DCE)-MRI for predicting pathological responses to preoperative CRT for LARCs. STUDY TYPE: Retrospective. POPULATION: Altogether, 83 patients (26 women, 57 men) with rectal cancer met the inclusion criteria. FIELD STRENGTH/SEQUENCE: 3.0T/T1 -weighted DCE-MRI sequence. ASSESSMENT: After CRT, each tumor was assessed by a pathologist who assigned a tumor regression grade (TRG), thereby identifying pathologically complete responders (pCR; TRG 1) and good responders (GR; TRG1 + TRG2). TA was then applied to the DCE-MRI K trans maps. The K trans value, several TA parameters, and tumor volumes were calculated. STATISTICAL TESTS: The Shapiro-Wilk test was used to verify that the data had normal distribution. Results of parameters measured before and after CRT were compared using paired-sample t-tests. Value changes of each parameter in the combined pCR/GR group were compared using independent sample t-tests. Receiver operating characteristic curves and areas under the curve (AUC) were calculated to assess the diagnostic performance of each parameter related to CRT effectiveness. RESULTS: There were 15 pCR (16.9%) and 21 GR (25.3%) patients. Tumor volume, mean K trans , entropy, and correlation decreased and energy values increased significantly in these groups compared with those of the non-PCR and non-GR groups. ΔCorrelation (Δcorrelation = postcorrelation - precorrelation) was found to be a valuable parameter for identifying pCR/GR patients (AUC 0.895, sensitivity 86.7%, specificity 81.8%). DATA CONCLUSION: TA parameters from the DCE-MRI K trans map can predict the efficacy of CRT for treating LARCs. Also, Δcorrelation may be useful for identifying patients who will be responsive to CRT. LEVEL OF EVIDENCE: 4 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;49:885-893.

Excessive daytime sleepiness in general hospital nurses: prevalence, correlates, and its association with adverse events.

OBJECTIVE: To investigate the prevalence and correlates of excessive daytime sleepiness (EDS) in a population of hospital nurses in South China as well as the influence of EDS on the occurrence of adverse events. METHODS: A total of 1102 nurses working in a large medical center were invited to participate in this cross-sectional study (96.9% females, mean age 29.6 years). They all completed a self-reported questionnaire consisting of items on demographic variables, lifestyle factors, insomnia, anxiety, depression, and both work-related and sleep-related characteristics. RESULTS: A total of 1048 nurses gave a valid response (response rate 95.1%). Among them, 169 (16.1%) reported EDS as defined as an Epworth Sleepiness Scale ≥ 14. Depression (adjusted odds ratio = 2.24, 95% confidence interval 1.51-3.31), anxiety (1.65; 1.02-2.67), insomnia (2.29; 1.56-3.36), rotating shift work (1.98; 1.03-3.83), and low interest in work (1.74; 1.01-2.99) were all independent risk factors of the occurrence of EDS. EDS is associated with the occurrence of adverse events after controlling for confounding factors (adjusted OR 1.83, CI 1.26 to 2.67). CONCLUSIONS: EDS was common among this relatively young and healthy nurse population in south China. There were clear associations between EDS and depression, anxiety, insomnia, rotating shift work, and low work-related interest. Furthermore, EDS was an independent risk factor in the occurrence of adverse events (AEs) in our subjects.

Multivariate empirical mode decomposition approach for adaptive denoising of fringe patterns.

An adaptive approach is presented for noise reduction of optical fringe patterns using multivariate empirical mode decomposition. Adjacent rows and columns of patterns are treated as multichannel signals and are decomposed into multiscale components. Fringe patterns are reconstructed with less noise by simply thresholding coefficients in different scales. The proposed approach can better concentrate local main components of fringe signals into single scale, compared with the conventional multiscale denoising method. A simulated pattern and an actual example are examined. Signal-to-noise ratio (SNR) of the simulated pattern is more than doubled.

Color fringe-projected technique for measuring dynamic objects based on bidimensional empirical mode decomposition.

A triple-frequency color fringe-projected technique is presented to measure dynamic objects. Three fringe patterns with a carrier frequency ratio of 1:3:9 are encoded in red, green, and blue channels of a color fringe pattern and projected onto an object's surface. Bidimensional empirical mode decomposition is used for decoupling the cross talk among color channels and for extracting the fundamental frequency components of the three fringe patterns. The unwrapped phase distribution of the high-frequency fringe is retrieved by a three-step phase unwrapping strategy to recover the object's height distribution. Owing to its use of only a single snapshot, the technique is suitable for measuring dynamically changing objects with large discontinuity or spatially isolated surfaces.