Accelerated organ region segmentation by the revised radial basis function network using a graphics processing unit.

This study aimed to accelerate the segmentation of organs in medical imaging with the revised radial basis function (RBF) network, using a graphics processing unit (GPU). We segmented the lung and liver regions from 250 chest x-ray computed tomography (CT) images and 160 abdominal CT images, respectively, using the revised RBF network. We compared the time taken to segment images and their accuracy between serial processing by a single-core central processing unit (CPU), parallel processing using four CPU cores, and GPU processing. Segmentation times for lung and liver organ regions shortened to 57.80 and 35.35 seconds for CPU parallel processing and 20.16 and 11.02 seconds for GPU processing, compared to 211.03 and 124.21 seconds for CPU serial processing, respectively. The concordance rate of the segmented region to the normal region in slices excluding the upper and lower ends (173 lung and 111 liver slices) was 98% for lung and 96% for liver. The use of CPU parallel processing and GPU shortened the organ segmentation time in the revised RBF network without compromising segmentation accuracy. In particular, segmentation time was shortened to less than 10%with GPU. This processing method will contribute to workload reduction in imaging analysis. J. Med. Invest. 66 : 86-92, February, 2019.

Systemic inflammation and family history in relation to the prevalence of type 2 diabetes based on an alternating decision tree.

To investigate unknown patterns associated with type 2 diabetes in the Japanese population, we first used an alternating decision tree (ADTree) algorithm, a powerful classification algorithm from data mining, for the data from 1,102 subjects aged 35-69 years. On the basis of the investigated patterns, we then evaluated the associations of serum high-sensitivity C-reactive protein (hs-CRP) as a biomarker of systemic inflammation and family history of diabetes (negative, positive or unknown) with the prevalence of type 2 diabetes because their detailed associations have been scarcely reported. Elevated serum hs-CRP levels were proportionally associated with the increased prevalence of type 2 diabetes after adjusting for probable covariates, including body mass index and family history of diabetes (P for trend = 0.016). Stratified analyses revealed that elevated serum hs-CRP levels were proportionally associated with increased prevalence of diabetes in subjects without a family history of diabetes (P for trend = 0.020) but not in those with a family history or with an unknown family history of diabetes. Our study demonstrates that systemic inflammation was proportionally associated with increased prevalence of type 2 diabetes even after adjusting for body mass index, especially in subjects without a family history of diabetes.

Predictability of Pressure Ulcers Based on Operation Duration, Transfer Activity, and Body Mass Index Through the Use of an Alternating Decision Tree.

OBJECTIVE: To develop a prediction model for pressure ulcer cases that continue to occur at an acute care hospital with a low occurrence rate of pressure ulcers. METHODS: Analyzing data were collected from patients hospitalized at Tokushima University Hospital during 2012 using an alternating decision tree (ADT) data mining method. RESULTS: The ADT-based analysis revealed transfer activity, operation time, and low body mass index (BMI) as important factors for predicting pressure ulcer development. DISCUSSION: Among the factors identified, only "transfer activity" can be modified by nursing intervention. While shear force and friction are known to lead to pressure ulcers, transfer activity has not been identified as such. Our results suggest that transfer activities creating shear force and friction correlate with pressure ulcer development. The ADT algorithm was effective in determining prediction factors, especially for highly imbalanced data. Our three stumps ADT yielded accuracy, sensitivity, and specificity values of 72.1%±3.7%, 79.3%±18.1%, and 72.1%±3.8%, respectively. CONCLUSION: Transfer activity, identified as an interventional factor, can be modified through nursing interventions to prevent pressure ulcer formation. The ADT method was effective in identifying factors within largely imbalanced data. J. Med. Invest. 63: 248-255, August, 2016.

Predictability of the future development of aggressive behavior of cranial dural arteriovenous fistulas based on decision tree analysis.

OBJECT: The severity of clinical signs and symptoms of cranial dural arteriovenous fistulas (DAVFs) are well correlated with their pattern of venous drainage. Although the presence of cortical venous drainage can be considered a potential predictor of aggressive DAVF behaviors, such as intracranial hemorrhage or progressive neurological deficits due to venous congestion, accurate statistical analyses are currently not available. Using a decision tree data mining method, the authors aimed at clarifying the predictability of the future development of aggressive behaviors of DAVF and at identifying the main causative factors. METHODS: Of 266 DAVF patients, 89 were eligible for analysis. Under observational management, 51 patients presented with intracranial hemorrhage/infarction during the follow-up period. RESULTS: The authors created a decision tree able to assess the risk for the development of aggressive DAVF behavior. Evaluated by 10-fold cross-validation, the decision tree's accuracy, sensitivity, and specificity were 85.28%, 88.33%, and 80.83%, respectively. The tree shows that the main factor in symptomatic patients was the presence of cortical venous drainage. In its absence, the lesion location determined the risk of a DAVF developing aggressive behavior. CONCLUSIONS: Decision tree analysis accurately predicts the future development of aggressive DAVF behavior.

On-admission pressure ulcer prediction using the nursing needs score.

BACKGROUND: Pressure ulcers (PUs) are considered a serious problem in nursing care and require preventive measures. Many risk assessment methods are currently being used, but most require the collection of data not available on admission. Although nurses assess the Nursing Needs Score (NNS) on a daily basis in Japanese acute care hospitals, these data are primarily used to standardize the cost of nursing care in the public insurance system for appropriate nurse staffing, and have never been used for PU risk assessment. OBJECTIVE: The objective of this study was to predict the risk of PU development using only data available on admission, including the on-admission NNS score. METHODS: Logistic regression was used to generate a prediction model for the risk of developing PUs after admission. A random undersampling procedure was used to overcome the problem of imbalanced data. RESULTS: A combination of gender, age, surgical duration, and on-admission total NNS score (NNS group B; NNS-B) was the best predictor with an average sensitivity, specificity, and area under receiver operating characteristic curve (AUC) of 69.2% (6920/100), 82.8% (8280/100), and 84.0% (8400/100), respectively. The model with the median AUC achieved 80% (4/5) sensitivity, 81.3% (669/823) specificity, and 84.3% AUC. CONCLUSIONS: We developed a model for predicting PU development using gender, age, surgical duration, and on-admission total NNS-B score. These results can be used to improve the efficiency of nurses and reduce the number of PU cases by identifying patients who require further examination.

The effectiveness of an interactive 3-dimensional computer graphics model for medical education.

BACKGROUND: Medical students often have difficulty achieving a conceptual understanding of 3-dimensional (3D) anatomy, such as bone alignment, muscles, and complex movements, from 2-dimensional (2D) images. To this end, animated and interactive 3-dimensional computer graphics (3DCG) can provide better visual information to users. In medical fields, research on the advantages of 3DCG in medical education is relatively new. OBJECTIVE: To determine the educational effectiveness of interactive 3DCG. METHODS: We divided 100 participants (27 men, mean (SD) age 17.9 (0.6) years, and 73 women, mean (SD) age 18.1 (1.1) years) from the Health Sciences University of Mongolia (HSUM) into 3DCG (n = 50) and textbook-only (control) (n = 50) groups. The control group used a textbook and 2D images, while the 3DCG group was trained to use the interactive 3DCG shoulder model in addition to a textbook. We conducted a questionnaire survey via an encrypted satellite network between HSUM and Tokushima University. The questionnaire was scored on a 5-point Likert scale from strongly disagree (score 1) to strongly agree (score 5). RESULTS: Interactive 3DCG was effective in undergraduate medical education. Specifically, there was a significant difference in mean (SD) scores between the 3DCG and control groups in their response to questionnaire items regarding content (4.26 (0.69) vs 3.85 (0.68), P = .001) and teaching methods (4.33 (0.65) vs 3.74 (0.79), P < .001), but no significant difference in the Web category. Participants also provided meaningful comments on the advantages of interactive 3DCG. CONCLUSIONS: Interactive 3DCG materials have positive effects on medical education when properly integrated into conventional education. In particular, our results suggest that interactive 3DCG is more efficient than textbooks alone in medical education and can motivate students to understand complex anatomical structures.

Construction and evaluation of e-learning system for medical treatment safety measures.

To consider effective medical treatment safety measures, various factors that lead to malpractice should be understood and analyzed objectively. An incident report system was constructed at the University of Tokushima hospital. A safety management room was set up in the university hospital. The system collected information and analyzed submitted incidents in order to contribute to safer medical treatment. However, the current educating system is not able to effectively teach the incident reports system to the 1,000 or so staff members. This is due to a busy hospital atmosphere which leaves little time for educational instruction. In response to this problem the E-learning system was developed in order to effectively administer the medical treatment safety education. This E-learning system was evaluated by the participating "learners" who were hospital staff members.

Role of CD13/aminopeptidase N in rat lymphocytic alveolitis caused by thoracic irradiation.

CD13/aminopeptidase N is a cell surface glycoprotein that is widely distributed in a variety of mammalian cells. It was recently shown to have chemotactic activity for T lymphocytes. This study examined the role of CD13/aminopeptidase N in lymphocytic alveolitis in radiation-induced lung injury caused by a single-dose thoracic irradiation (15 Gy) in rats. Significantly increased aminopeptidase activity was detected in bronchoalveolar lavage fluid obtained from irradiated rats at 4 weeks after irradiation compared to the activity in unirradiated rats. Significantly higher aminopeptidase activity was detected on alveolar macrophages from irradiated rats at 2 and 4 weeks than on those from unirradiated rats. Western blot analysis showed an increased expression of CD13/aminopeptidase N protein in alveolar macrophages from irradiated rats at 4 weeks. Chemotactic activity for normal rat lymphocytes was detected in bronchoalveolar lavage fluid from irradiated rats at 4 weeks, and approximately 60% of the activity was inhibited by pretreatment of bronchoalveolar lavage fluid with bestatin, a specific aminopeptidase inhibitor. This study suggests that CD13/aminopeptidase N may play an important role as a lymphocyte chemoattractant in lymphocyte-mediated alveolitis in experimental radiation-induced lung injury.