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13. S1P–S1PR2 Axis Mediates Homing of Muse Cells Into Damaged Heart for Long-Lasting Tissue Repair and Functional Recovery After Acute Myocardial Infarction

Author

Yamada, Yoshihisa, primary, Wakao, Shohei, additional, Kushida, Yoshihiro, additional, Minatoguchi, Shingo, additional, Mikami, Atsushi, additional, Higashi, Kenshi, additional, Baba, Shinya, additional, Shigemoto, Taeko, additional, Kuroda, Yasumasa, additional, Kanamori, Hiromitsu, additional, Amin, Mohamad, additional, Kawasaki, Masanori, additional, Nishigaki, Kazuhiko, additional, Taoka, Masato, additional, Isobe, Toshiaki, additional, Muramatsu, Chisako, additional, Dezawa, Mari, additional, and Minatoguchi, Shinya, additional

Published
2018
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14. Classifying breast masses in volumetric whole breast ultrasound data: a 2.5-dimensional approach

Author

Lee, Gobert N, Okada, Toshiaki, Fukuoka, Daisuke, Muramatsu, Chisako, Hara, Takeshi, Morita, Takako, Takada, Etsuo, Endo, Tokiko, and Fujita, Hiroshi

Subjects
Breast cancer, Ultrasound, Echo feature, Classification, Geometric feature
Abstract

The aim of this paper is to investigate a 2.5-dimensional approach in classifying masses as benign or malignant in volumetric anisotropic voxel whole breast ultrasound data. In this paper, the term 2.5-dimensional refers to the use of a series of 2-dimensional images. While mammography is very effective in breast cancer screening in general, it is less sensitive in detecting breast cancer in younger women or women with dense breasts. Breast ultrasonography does not have the same limitation and is a valuable adjunct in breast cancer detection. The current study focuses on a new 2.5-dimensional approach in analyzing the volumetric whole breast ultrasound data for mass classification.

Published
2010

19. Retinopathy Online Challenge: Automatic Detection of Microaneurysms in Digital Color Fundus Photographs.

Author

Niemeijer, Meindert, van Ginneken, Bram, Cree, Michael J., Mizutani, Atsushi, Quellec, Gwénolé, Sánchez, Clara I., Zhang, Bob, Hornero, Roberto, Lamard, Mathieu, Muramatsu, Chisako, Xiangqian Wu, Cazuguel, Guy, You, Jane, Mayo, Agustín, Qin Li, Hatanaka, Yuji, Cochener, Béatrice, Roux, Christian, Karray, Fakhri, and García, María

Subjects
DIABETIC retinopathy, DIABETES complications, COMPUTER algorithms, DATA analysis, NUMERICAL analysis
Abstract

The detection of microaneurysms in digital color fundus photographs is a critical first step in automated screening for diabetic retinopathy (DR), a common complication of diabetes. To accomplish this detection numerous methods have been published in the past but none of these was compared with each other on the same data. In this work we present the results of the first international microaneurysm detection competition, organized in the context of the Retinopathy Online Challenge (ROC), a multiyear online competition for various aspects of DR detection. For this competition, we compare the results of five different methods, produced by five different teams of researchers on the same set of data. The evaluation was performed in a uniform manner using an algorithm presented in this work. The set of data used for the competition consisted of 50 training images with available reference standard and 50 test images where the reference standard was witheld by the organizers (M. Niemeijer, B. van Ginneken, and M. D. Abràmoff). The results obtained on the test data was submitted through a website after which standardized evaluation software was used to determine the performance of each of the methods. A human expert detected microaneurysms in the test set to allow comparison with the performance of the automatic methods. The overall results show that microaneurysm detection is a challenging task for both the automatic methods as well as the human expert. There is room for improvement as the best performing system does not reach the performance of the human expert. The data associated with the ROC microaneurysm detection competition will remain publicly available and the website will continue accepting submissions. [ABSTRACT FROM AUTHOR]

Published
2010
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20. Case report: Characteristics and nature of primary cardiac synovial sarcoma.

Author

Kawasaki T, Nakajima T, Torigoe T, Onohara K, Ishii K, Kanno S, Muramatsu C, Tatsuno R, Jubashi T, and Ichikawa J

Abstract

Primary malignant cardiac tumors rarely occur, and cardiac synovial sarcoma (SS) is especially rare among such tumors. Herein, we present the case of a 35-year-old female with primary cardiac SS treated with surgery, chemotherapy, and radiotherapy. She presented with chest symptoms and underwent imaging examinations. A cardiac tumor was suspected, and an open biopsy was performed. The pathological findings suggested cardiac SS. Next, we performed a resection, and the tumors persisted at a macroscopic level. Immunohistochemistry was negative for SS18-SSX and positive for the SSX C-terminus and cytokeratin CAM5.2, a reduction of SMARCB1/INI1 was observed, and fluorescence in situ hybridization showed positive SS18 split staining. Owing to the FNCLCC grade 3 tumor and R2 margins, adjuvant chemotherapy with ifosfamide, doxorubicin, and radiotherapy was initiated, and the patient was diagnosed with cardiac SS. The differences in patients with cardiac SS compared with general SS include male predominance, larger tumor size, and poorer prognosis. Pathological findings of immunohistochemistry and fluorescence in situ hybridization were found to be more reliable than imaging findings for a correct diagnosis. Additionally, because incomplete resection is frequently performed, adjuvant therapy, including chemotherapy and radiation therapy, may be performed. The findings indicate that multiple therapies, including surgery, chemotherapy, and radiotherapy, are essential treatment strategies for improving the prognosis of patients with cardiac SS., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Kawasaki, Nakajima, Torigoe, Onohara, Ishii, Kanno, Muramatsu, Tatsuno, Jubashi and Ichikawa.)

Published
2024
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