he University of Technology Sydney in January 2020. We plan to begin the trial in October 2020 and expect to publish the results by the end of 2021. This clinical trial using single-case experimental design methodology has been designed to evaluate the effectiveness of a novel brain-computer interface neuromodulative treatment for people with neuropathic pain after spinal cord injury. Single-case experimental designs are considered a viable alternative approach to randomized clinical trials to identify evidence-based practices in the field of technology-based health interventions when recruitment of large samples is not feasible. Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12620000556943; https//bit.ly/2RY1jRx. PRR1-10.2196/20979. PRR1-10.2196/20979. Psychological therapies are effective treatments for hypoactive sexual desire dysfunction (HSDD; formerly hypoactive sexual desire disorder), a common sexual dysfunction among women. Access to evidence-based treatments, however, remains difficult. https://www.selleckchem.com/products/bupivacaine.html Internet-based interventions are effective for a variety of psychological disorders and may be a promising means to close the treatment gap for HSDD. This article describes the treatment protocol and study design of a randomized controlled trial, aiming to study the efficacy of cognitive behavioral and mindfulness-based interventions delivered via the internet for women with HSDD to a waitlist control group. Outcomes are sexual desire (primary) and sexual distress (secondary). Additional variables (eg, depression, mindfulness, rumination) will be assessed as potential moderators or mediators of treatment success. A cognitive behavioral and a mindfulness-based self-help intervention for HSDD will be provided online. Overall, 266 women with HSDD will be recruited and assigned either to one of the intervention groups, or to a waitlist control group (221). Outcome data will be assessed at baseline, at 12 weeks, and at 6 and 12 months after randomization. Intention-to-treat and completer analyses will be conducted. We expect improvements in sexual desire and sexuality-related distress in both intervention groups compared to the waitlist control. Recruitment has begun in January 2019 and is expected to be completed in August 2021. Results will be published in 2022. This study aims to contribute to the improvement and dissemination of psychological treatments for women with HSDD and to clarify whether cognitive behavioral and/or mindfulness-based treatments for HSDD are feasible and effective when delivered via the internet. ClinicalTrials.gov NCT03780751; https//clinicaltrials.gov/ct2/show/NCT03780751. DERR1-10.2196/20326. DERR1-10.2196/20326. Lymphovascular invasion (LVI) and perineural invasion (PNI) are associated with poor prognosis in gastric cancers. In this work, we aimed to investigate the potential role of computed tomography (CT) texture analysis in predicting LVI and PNI in patients with tubular gastric adenocarcinoma (GAC) using a machine learning (ML) approach. Sixty-eight patients who underwent total gastrectomy with curative (R0) resection and D2-lymphadenectomy were included in this retrospective study. Texture features were extracted from the portal venous phase CT images. Dimension reduction was first done with a reproducibility analysis by two radiologists. Then, a feature selection algorithm was used to further reduce the high-dimensionality of the radiomic data. Training and test splits were created with 100 random samplings. ML-based classifications were done using adaptive boosting, k-nearest neighbors, Naive Bayes, neural network, random forest, stochastic gradient descent, support vector machine, and decision tree. Predictive performance of the ML algorithms was mainly evaluated using the mean area under the curve (AUC) metric. Among 271 texture features, 150 features had excellent reproducibility, which were included in the further feature selection process. Dimension reduction steps yielded five texture features for LVI and five for PNI. Considering all eight ML algorithms, mean AUC and accuracy ranges for predicting LVI were 0.777-0.894 and 76%-81.5%, respectively. For predicting PNI, mean AUC and accuracy ranges were 0.482-0.754 and 54%-68.2%, respectively. The best performances for predicting LVI and PNI were achieved with the random forest and Naive Bayes algorithms, respectively. ML-based CT texture analysis has a potential for predicting LVI and PNI of the tubular GACs. Overall, the method was more successful in predicting LVI than PNI. ML-based CT texture analysis has a potential for predicting LVI and PNI of the tubular GACs. Overall, the method was more successful in predicting LVI than PNI. We aimed to evaluate BIRADS-3 breast lesions with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and compare with histopathology, and to investigate the effectiveness of breast MRI for follow-up and management. A total of 84 BIRADS-3 lesions reported by US or mammography and evaluated by DCE-MRI between September 2014 and October 2015 were included in this study. All patients underwent percutaneous or surgical biopsy for histopathologic diagnosis. Morphologic and kinematic features on MRI were compared with histopathologic results. Of the 84 BIRADS-3 breast lesions, 9 (10.7%) had malignant features on DCE-MRI and all were verified with histopathologic results. DCE-MRI had 96.7% sensitivity, 72% specificity, 92% positive predictive value, and 82.5% negative predictive value. MRI and histopathology results were correlated for the diagnosis of malignant lesions. The sensitivity and negative predictive value of MRI for diagnosis of malignant lesions were both 100%. Differentiation of benign versus malignant lesions was accomplished with 100% accuracy with DCE-MRI. We suggest that DCE-MRI should be an additional diagnostic tool and problem-solving modality for BIRADS-3 lesions, particularly in patients with relative risk factors. Differentiation of benign versus malignant lesions was accomplished with 100% accuracy with DCE-MRI. We suggest that DCE-MRI should be an additional diagnostic tool and problem-solving modality for BIRADS-3 lesions, particularly in patients with relative risk factors.