Sonographic classification of testicular tumors by tissue harmonic imaging: experience of 58 cases

13301乙第2088号博士（保健学）金沢大学博士論文要旨Abstract 以下に掲載：Journal of medical ultrasonics 45(1) pp.103-111 2017. Springer. 共著者：Atsuo Kawamoto, Tadashi Hatano, Kazuhiro Saito, Rie Inoue, Toshitaka Nagao, Shigeru Sanad

Quantitative Evaluation of Pain during Electrocutaneous Stimulation using a Log-Linearized Peripheral Arterial Viscoelastic Model

In clinical practice, subjective pain evaluations, e.g., the visual analogue scale and the numeric rating scale, are generally employed, but these are limited in terms of their ability to detect inaccurate reports, and are unsuitable for use in anesthetized patients or those with dementia. We focused on the peripheral sympathetic nerve activity that responds to pain, and propose a method for evaluating pain sensation, including intensity, sharpness, and dullness, using the arterial stiffness index. In the experiment, electrocardiogram, blood pressure, and photoplethysmograms were obtained, and an arterial viscoelastic model was applied to estimate arterial stiffness. The relationships among the stiffness index, self-reported pain sensation, and electrocutaneous stimuli were examined and modelled. The relationship between the stiffness index and pain sensation could be modelled using a sigmoid function with high determination coefficients, where R2 ≥ 0.88, p < 0.01 for intensity, R2 ≥ 0.89, p < 0.01 for sharpness, and R2 ≥ 0.84, p < 0.01 for dullness when the stimuli could appropriately evoke dull pain.This work was supported by the Center of Innovation Program from Japan Science and Technology Agency.Supplementary information accompanies this paper at https://doi.org/10.1038/s41598-018-21223-1

Evaluation of oral immunotherapy efficacy and safety by maintenance dose dependency: A multicenter randomized study

Background Generally, oral immunotherapy (OIT) aims for daily administration. Recently, the efficacy of treatment with OIT at a low dose has been reported. However, the optimal dose and the evaluation of dose-dependent OIT outcome have not been described. Methods A multicenter, parallel, open-labeled, prospective, non-placebo controlled, randomized study enrolled 101 Japanese patients for treatment with OIT. We hypothesized that target dose OIT would induce short-term unresponsiveness (StU) earlier than reduced dose OIT. StU was defined as no response to 6200 mg whole egg, 3400 mg milk, and 2600 mg wheat protein, as evaluated by oral food challenge after 2-week ingestion cessation. To compare the two doses of OIT efficacy, the maximum ingestion doses during the maintenance phase of OIT were divided into 100%-dose or 25%-dose groups against their target StU dose, respectively. A total of 51 patients were assigned to the 100%-dose group [hen's egg (HE) = 26, cow's milk (CM) = 13, wheat = 12] and 50 to the 25%-dose group (HE = 25, CM = 13, wheat = 12). Primary outcome was established by comparing StU at 1 year. Secondary outcome was StU at 2 years and established by comparing allergic symptoms and immunological changes. Results The year 1 StU rates (%) for the 100%- and 25%-dose groups were 26.9 vs. 20.0 (HE), 7.7 vs. 15.4 (CM), and 50.0 vs. 16.7 (wheat), respectively. The year 2 StU rates were 30.8 vs. 36.0 (HE), 7.7 vs. 23.1 (CM), and 58.3 vs. 58.3 (wheat), respectively. There were no statistically significant differences in StU between years 1 and 2. The total allergic symptom rate in the 25%-dose group was lower than that in the 100%-dose group for egg, milk, and wheat. Antigen-specific IgE levels for egg-white, milk, and wheat decreased at 12 months. Conclusions Reduced maintenance dose of egg OIT showed similar therapeutic efficacy to the target dose. However, we were not able to clearly demonstrate the efficacy, particularly for milk and wheat. Reducing the maintenance dose for eggs, milk, and wheat may effectively lower the symptoms associated with their consumption compared to the target OIT dose. Furthermore, aggressive reduction of the maintenance dose might be important for milk and wheat, compared to the 25%-dose OIT

Hungarian Teacher Programme

Background D-index which combines the intensity and duration of neutropenia is reported as a tool for evaluating the dynamics of neutropenia. This study aimed to analyze the relationship between D-index and oral complications (i.e., oral mucositis [OM] and odontogenic infection [OI]) during chemotherapies for hematological malignancies. Methods A total of 421 chemotherapeutic courses in 104 patients were analyzed. Chemotherapeutic courses in patients who finished all of the prophylactic dental treatments were defined as "treatment Finish". Chemotherapeutic courses in patients who did not finish prophylactic dental treatments were defined as "treatment not-Finish". OM was evaluated according to the Common Terminology Criteria for Adverse Events, version 4.0. D-index was compared between chemotherapeutic courses with versus without oral complications. Results D-index was significantly higher in chemotherapeutic courses with grade 1 or 2 OM (p < 0.001) than courses without OM. In contrast, higher D-index did not relate to the development of OI (p = 0.18). The occurrence of OI (p < 0.001) but not OM (p = 0.56) during chemotherapy was significantly higher in chemotherapeutic courses without the completion of dental intervention. Conclusions Higher D-index relates to the development of OM. In contrast, OI occurs due to untreated odontogenic foci, and its occurrence does not relate to higher D-index

Development of an Automatic Ultrasound Image Classification System for Pressure Injury Based on Deep Learning

The classification of ultrasound (US) findings of pressure injury is important to select the appropriate treatment and care based on the state of the deep tissue, but it depends on the operator’s skill in image interpretation. Therefore, US for pressure injury is a procedure that can only be performed by a limited number of highly trained medical professionals. This study aimed to develop an automatic US image classification system for pressure injury based on deep learning that can be used by non-specialists who do not have a high skill in image interpretation. A total 787 training data were collected at two hospitals in Japan. The US images of pressure injuries were assessed using the deep learning-based classification tool according to the following visual evidence: unclear layer structure, cobblestone-like pattern, cloud-like pattern, and anechoic pattern. Thereafter, accuracy was assessed using two parameters: detection performance, and the value of the intersection over union (IoU) and DICE score. A total of 73 images were analyzed as test data. Of all 73 images with an unclear layer structure, 7 showed a cobblestone-like pattern, 14 showed a cloud-like pattern, and 15 showed an anechoic area. All four US findings showed a detection performance of 71.4–100%, with a mean value of 0.38–0.80 for IoU and 0.51–0.89 for the DICE score. The results show that US findings and deep learning-based classification can be used to detect deep tissue pressure injuries