and AW is currently with the NUTECH

Joubert syndrome is often missed clinically and radiologically if not enough attention is paid to its subtle and variable clinical presentation and the imaging findings in the posterior fossa. The purpose of this paper is to illustrate the brain stem and cerebellar imaging findings in Joubert syndrome. Awareness of the clinical and neuroimaging findings in Joubert syndrome and maintenance of a high index of suspicion are essential to correctly diagnose this rare congenital malformation.

Deep learning has been actively investigated for various applications such as image classification, computer vision, and regression tasks, and it has shown state-of-the-art performance. In diffuse optical tomography (DOT), the accurate estimation of the bulk optical properties of a medium is paramount because it directly affects the overall image quality. In this work, we exploit deep learning to propose a novel, to the best of our knowledge, convolutional neural network (CNN)-based approach to estimate the bulk optical properties of a highly scattering medium such as biological tissue in DOT. We validated the proposed method by using experimental, as well as, simulated data. For performance assessment, we compared the results of the proposed method with those of existing approaches. The results demonstrate that the proposed CNN-based approach for bulk optical property estimation outperforms existing methods in terms of estimation accuracy, with lower computation time.

Diffuse optical tomography (DOT) non-invasively measures the functional characteristics of breast lesions using near infrared light to probe tissue optical properties. This study aimed to evaluate a new digital breast tomosynthesis (DBT)/DOT fusion imaging technique and obtain preliminary data for breast cancer detection. Twenty-eight women were prospectively enrolled and underwent both DBT and DOT examinations. DBT/DOT fusion imaging was created after acquisition of both examinations. Two breast radiologists analyzed DBT and DOT images independently, and then finally evaluated the fusion images. The diagnostic performance of each reading session was compared and interobserver agreement was assessed. The technical success rate was 96.4%, with one failure due to an error during DOT data storage. Among the 27 women finally included in the analysis, 13 had breast cancer. The areas under the receiver operating characteristic curve (AUCs) for DBT were 0.783 and 0.854 for readers 1 and 2, respectively. DOT showed comparable diagnostic performance to DBT for both readers. The AUCs were significantly improved (P = 0.004) when the DBT/DOT fusion images were used. Interobserver agreements were highest for the DBT/DOT fusion images. In conclusion, this study suggests that DBT/DOT fusion imaging technique appears to be a promising tool for breast cancer diagnosis.

BackgroundThe ineffective utilization of journal clubs (JCs) for pre-clinical dental students has led to a lack of research into their effectiveness in developing skills such as critical reasoning and evidence-based medicine (EBM) practice. Therefore, we have implemented JCs in first-year undergraduate dental students and measured their effectiveness using the integrated Assessing Competency in Evidence-Based Medicine (ACE) tool. MethodologyWe conducted a quasi-experimental study where EBM was included in the curriculum for pre-clinical students as a hybrid model with a year-long blended learning approach. The 50-student class was divided into five groups of 10 students, with each group participating in seven JCs related to the physiology curriculum. After conducting critical analysis in self-directed learning sessions, students created interactive PowerPoint presentations followed by discussion. Instructors offered feedback after each session based on 1-2 levels in Kirkpatrick's training evaluation model. Inferential statistics were used for comparative analysis of the ACE tool pre-and post-test using SPSS version 26 (IBM Corp., Armonk, NY, USA). ResultsA linear trend in median score from 6 in the pre-test to 9 in the post-test was detected using the box and whisker plot. Using paired sample t-test, the mean difference (95% confidence interval) between the pre-test and post-test responses was -3.14 (-2.32 to -3.96) (p < 0.001). In terms of the post-test responses, each item's difficulty index ranged from 0.3 to 0.9. Internal reliability was in the acceptable range of >0.15 (range = 0.5-0.18). The item discriminatory index was in the range of 0.8 to >0.2. Cronbach's alpha was 0.64, which was deemed acceptable. ConclusionsOur results show that pre-clinical dentistry students appreciated the use of JCs to improve active learning, critical appraisal, analytical, and decision-making skills. The 15-item ACE measure is a useful and reliable tool for assessing dentistry students' EBM proficiency in Pakistan.

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In this work, we report a novel pre-processing technique that improves detectability of lesions in DBT and has potential advantages over the global threshold-based post-reconstruction processing technique. The proposed method not only increased the lesion detectability but also reduced typical image artifacts pronounced in conventional FBP-based DBT.