Evaluation of the Microvascular Research Center Training Program for Assessing Microsurgical Skills in Trainee Surgeons

Komatsu, Seiji,Yamada, Kiyoshi,Yamashita, Shuji,Sugiyama, Narushi,Tokuyama, Eijiro,Matsumoto, Kumiko,Takara, Ayumi,Kimata, Yoshihiro Korean Society of Plastic and Reconstructive Surge 2013 Archives of Plastic Surgery Vol.40 No.3

Background We established the Microvascular Research Center Training Program (MRCP) to help trainee surgeons acquire and develop microsurgical skills. Medical students were recruited to undergo the MRCP to assess the effectiveness of the MRCP for trainee surgeons. Methods Twenty-two medical students with no prior microsurgical experience, who completed the course from 2005 to 2012, were included. The MRCP comprises 5 stages of training, each with specific passing requirements. Stages 1 and 2 involve anastomosing silicone tubes and blood vessels of chicken carcasses, respectively, within 20 minutes. Stage 3 involves anastomosing the femoral artery and vein of live rats with a 1-day patency rate of >80%. Stage 4 requires replantation of free superficial inferior epigastric artery flaps in rats with a 7-day success rate of >80%. Stage 5 involves successful completion of one case of rat replantation/transplantation. We calculated the passing rate for each stage and recorded the number of anastomoses required to pass stages 3 and 4. Results The passing rates were 100% (22/22) for stages 1 and 2, 86.4% (19/22) for stage 3, 59.1% (13/22) for stage 4, and 55.0% (11/20) for stage 5. The number of anastomoses performed was $17.2{\pm}12.2$ in stage 3 and $11.3{\pm}8.1$ in stage 4. Conclusions Majority of the medical students who undertook the MRCP acquired basic microsurgical skills. Thus, we conclude that the MRCP is an effective microsurgery training program for trainee surgeons.

Evaluation of the Microvascular Research Center Training Program for Assessing Microsurgical Skills in Trainee Surgeons

Seiji Komatsu,Kiyoshi Yamada,Shuji Yamashita,Narushi Sugiyama,Eijiro Tokuyama,Kumiko Matsumoto1,Ayumi Takara,Yoshihiro Kimata 대한성형외과학회 2013 Archives of Plastic Surgery Vol.40 No.3

Background We established the Microvascular Research Center Training Program (MRCP)to help trainee surgeons acquire and develop microsurgical skills. Medical students were recruited to undergo the MRCP to assess the effectiveness of the MRCP for trainee surgeons. Methods Twenty-two medical students with no prior microsurgical experience, who completed the course from 2005 to 2012, were included. The MRCP comprises 5 stages of training,each with specific passing requirements. Stages 1 and 2 involve anastomosing silicone tubes and blood vessels of chicken carcasses, respectively, within 20 minutes. Stage 3 involves anastomosing the femoral artery and vein of live rats with a 1-day patency rate of >80%. Stage 4 requires replantation of free superficial inferior epigastric artery flaps in rats with a 7-day success rate of >80%. Stage 5 involves successful completion of one case of rat replantation/transplantation. We calculated the passing rate for each stage and recorded the number of anastomoses required to pass stages 3 and 4. Results The passing rates were 100% (22/22) for stages 1 and 2, 86.4% (19/22) for stage 3, 59.1% (13/22) for stage 4, and 55.0% (11/20) for stage 5. The number of anastomoses performed was 17.2±12.2 in stage 3 and 11.3±8.1 in stage 4. Conclusions Majority of the medical students who undertook the MRCP acquired basic microsurgical skills. Thus, we conclude that the MRCP is an effective microsurgery training program for trainee surgeons.

Automatic Detection of Multi Organs on the CT Images Using the Ribs Information and a Level Set Method

Masafumi Komatsu,Shinji Toyota,Hyoungseop Kim,Joo Kooi Tan,Seiji Ishikawa,Akiyoshi Yamamoto 대한전자공학회 2008 ITC-CSCC :International Technical Conference on Ci Vol.2008 No.7

Recently, various imaging equipment such as high resolution computed tomography (HRCT) have been intoroduced into medical fields. Accordingly, many related image processing techniques are proposed into medical fields for extraction of abnormal area. Also, segmentation is one of the most important problems for analyzing the abnormalities and some segmentation techinques have been developed for automatic extraction of region of interest (ROI) before analyzing the abnomalities in the medical image processing field. It is, however, there are still no fully automatic segmantation methods that are generally applicable to ROI based on CT image set. In this paper, we present a technique for automatic extraction of the multi organs on the multi detector row computed tomography (MDCT) images employing the ribs information which is obtained by anatomical information and a level set method. We apply our proposed technique to three image sets and satisfactory segmentation results are achieved.

Extraction of multi organs by use of level set method from CT images

Masafumi Komatsu,Hyoungseop Kim,Joo Kooi Tan,Seiji Ishikawa,Akiyoshi Yamamoto 제어로봇시스템학회 2008 제어로봇시스템학회 국제학술대회 논문집 Vol.2008 No.10

Recently, various imaging equipments have been introduced into medical fields. Especially, HRCT is one of the most useful diagnosis systems because it provides a high resolution image to physicians. Accordingly, many related image processing techniques are proposed into medical fields for extraction of abnormal area. In the medical image processing field, segmentation is one of the most important problems for analyzing the abnormalities and recognition of internal structures before the operation. Many related segmentation techniques have been developed for automatic extraction of regions of interest. Especially, in order to extract multi organs and to understand the structure of them, several approaches have been developed in the past. But there are still no fully automatic segmentation methods that are generally applicable to regions of interest based on CT image set. In this paper, we propose a new technique for automatic extraction of the multi organs on the MDCT images employing the level set method. We apply the proposed technique to three CT cases and satisfactory results are achieved.

앙케이트에 의한 지방자치단체의 공공시설관리에 관한 동향조사

후지와라 세이지(Seiji FUJIWARA),히라이 켄지(Kenji HIRAI),이상준(Sangjun YI),쯔쯔미 히로키(Hiroki TSUTSUMI),코마츠 유키오(Yukio KOMATSU) 대한건축학회 2011 대한건축학회 학술발표대회 논문집 - 계획계/구조계 Vol.31 No.2(구조계)

Currently, many old public facilities expires service life, and its repair costs are increasing. Therefore, local governments have increased the interest in elongation and repair work, so We surveyed to grasp a trend of the whole local government. The questionnaire was sent to local governments throughout the country, and 59%(housing) and 46%(school) were collected. We compared the management of housings and schools. On a national average, interest in both elongation and repair work is high. In particular, the school was found to be positive about the earthquake resistance. However, the classification performed at the financial index, and comparing the results of whether elongation is required, in housing, there was no change by the index, but, in school, it is thought that elongation is necessary like the local government with a higher index. In facilities management, we think its problem is different policies by each local government.

Segmentation Method for Cardiac Region in CT Images Based on Active Shape Model

Hiroki Takahashi,Masafumi Komatsu,Hyoungseop Kim,Joo Kooi Tan,Seiji Ishikawa,Akiyoshi Yamamoto 제어로봇시스템학회 2010 제어로봇시스템학회 국제학술대회 논문집 Vol.2010 No.10

Recently, multi detector row computed tomography (MDCT) has been introduced into medical fields. By the development of MDCT, images with high quality are provided into medical fields. So many related image processing techniques are proposed into medical image processing fields for extraction of abnormal area. In the medical image processing field, segmentation is one of the most important problems for analyzing the abnormalities and recognition of internal structures before the operation. For this reason, many approaches are proposed for detection of abnormal area on CT images. Before detection of abnormal areas, segmentation of organs in CT images is one of the most important problems for analyzing of disease. However, poor contrast, image noises and motion artifacts make this segmentation problem difficult in particular in cardiac region. Moreover, there are still no fully automatic segmentation methods for cardiac region on CT images. In this paper, we present automatic extraction technique for detection of cardiac region. Our proposed technique combines active shape model (ASM) and genetic algorithm (GA). We apply our proposed technique to five real CT images and satisfactory segmentation results are achieved.