HAMAMATSU-ICG study: Protocol for a phase III, multicentre, single-arm study to assess the usefulness of indocyanine green fluorescent lymphography in assessing secondary lymphoedema

Introduction Secondary lymphoedema of the extremities is an important quality-of-life issue for patients who were treated for their malignancies. Indocyanine green (ICG) fluorescent lymphography may be helpful for assessing lymphoedema and for planning lymphaticovenular anastomosis (LVA). The objective of the present clinical trial is to confirm whether or not ICG fluorescent lymphography using the near-infrared monitoring camera is useful for assessing the indication for LVA, for the identification of the lymphatic vessels before the conduct of LVA, and for the confirmation of the patency of the anastomosis site during surgery. Methods and analysis This trial is a phase III, multicentre, single-arm, open-label clinical trial to assess the efficacy and safety of ICG fluorescent lymphography when assessing and treating lymphoedema of patients with secondary lymphoedema who are under consideration for LVA. The primary endpoint is the identification rate of the lymphatic vessels at the incision site based on ICG fluorescent lymphograms obtained before surgery. The secondary endpoints are 1) the sensitivity and specificity of dermal back flow determined by ICG fluorescent lymphography as compared with 99mTc lymphoscintigraphy—one of the standard diagnostic methods and 2) the usefulness of ICG fluorescent lymphography when confirming the patency of the anastomosis site after LVA. Ethics and dissemination The protocol for the study was approved by the Institutional Review Board of each institution. The trial was filed for and registered at the Pharmaceuticals and Medical Devices Agency in Japan. The trial is currently on-going and is scheduled to end in June 2020

A monotonic statistical machine translation approach to speaking style transformation

This paper presents a method for automatically transforming faithful transcripts or ASR results into clean transcripts for human consumption using a framework we label speaking style transformation (SST). We perform a detailed analysis of the types of corrections performed by human stenographers when creating clean transcripts, and propose a model that is able to handle the majority of the most common corrections. In particular, the proposed model uses a framework of monotonic statistical machine translation to perform not only the deletion of disfluencies and insertion of punctuation, but also correction of colloquial expressions, insertions of omitted words, and other transformations. We provide a detailed description of the model implementation in the weighted finite state transducer (WFST) framework. An evaluation of the proposed model on both faithful transcripts and speech recognition results of parliamentary and lecture speech demonstrates the effectiveness of the proposed model in performing the wide variety of corrections necessary for creating clean transcripts

Acceptance of a homestay program and attitude toward community medicine among medical students.

BackgroundIn community-based medical education, opportunities for medical students to interact with local residents are important. To facilitate such interaction, we aimed to evaluate acceptance of a homestay program and attitude toward community medicine among medical students.MethodsThe participants (n = 39) were allowed to stay in the local homes of residents for one night in August 2016, 2017, and 2018. Before and after the homestays, the students responded to a self-reported questionnaire using the visual analog scale (VAS; 0-100 mm). The questionnaire included four questions on homestay/community medical training and community medicine and four questions about attitude toward community medicine in the local areas of medical students. Then, we compared the VAS scores before and after training.ResultsThe VAS scores for all questions about homestay/community medical training and community medicine significantly increased: "Is it worthwhile for you to have experience in the field of community medicine," "Did you find the homestay enjoyable," "Does the homestay add educational significance to the program," and "Is direct interaction with residents meaningful?" For the two questions about attitude toward community medicine, the VAS scores significantly increased: "Is there a challenge to practicing community medicine" and "In the future, do you want to work in Tamba area where you stayed?"ConclusionsThe medical students were extremely enthusiastic about the educational program for community medicine involving residential homestays, which improved their attitudes toward practicing community medicine. Moreover, the students appreciated that their training sites could become their future workplaces

Computer-aided diagnosis for screening of lower extremity lymphedema in pelvic computed tomography images using deep learning

Abstract Lower extremity lymphedema (LEL) is a common complication after gynecological cancer treatment, which significantly reduces the quality of life. While early diagnosis and intervention can prevent severe complications, there is currently no consensus on the optimal screening strategy for postoperative LEL. In this study, we developed a computer-aided diagnosis (CAD) software for LEL screening in pelvic computed tomography (CT) images using deep learning. A total of 431 pelvic CT scans from 154 gynecological cancer patients were used for this study. We employed ResNet-18, ResNet-34, and ResNet-50 models as the convolutional neural network (CNN) architecture. The input image for the CNN model used a single CT image at the greater trochanter level. Fat-enhanced images were created and used as input to improve classification performance. Receiver operating characteristic analysis was used to evaluate our method. The ResNet-34 model with fat-enhanced images achieved the highest area under the curve of 0.967 and an accuracy of 92.9%. Our CAD software enables LEL diagnosis from a single CT image, demonstrating the feasibility of LEL screening only on CT images after gynecologic cancer treatment. To increase the usefulness of our CAD software, we plan to validate it using external datasets

The Tokyo subway sarin attack has long-term effects on survivors: A 10-year study started 5 years after the terrorist incident.

ObjectivesThe Tokyo subway sarin attack in 1995 was an unprecedented act of terrorism that killed 13 people and sickened more than 6,000. The long-term somatic and psychological effects on its victims remain unknown.MethodsWe conducted analyses on the self-rating questionnaire collected annually by the Recovery Support Center (RSC) during the period from 2000 to 2009. The RSC is the only organization that has large-scale follow-up data about sarin attack victims. The prevalence of self-reported symptoms was calculated over 10 years. We also evaluated the prevalence of posttraumatic stress response (PTSR), defined as a score ≥ 25 on the Japanese-language version of the Impact of Event Scale-Revised. The multivariate Poisson regression model was applied to estimate the risk ratios of age, gender, and year factor on the prevalence of PTSR.ResultsSubjects were 747 survivors (12% of the total) who responded to the annual questionnaire once or more during the study period. The prevalence of somatic symptoms, especially eye symptoms, was 60-80% and has not decreased. PTSR prevalence was 35.1%, and again there was no change with time. The multivariate Poisson regression model results revealed "old age" and "female" as independent risk factors, but the passage of time did not decrease the risk of PTSR.ConclusionsAlthough symptoms in most victims of the Tokyo subway sarin were transient, this large-scale follow-up data analysis revealed that survivors have been suffering from somatic and psychological long-term effects