Kyushu University Academic Staff Educational and Research Activities Database
List of Presentations
Yoshiyuki Shioyama Last modified date:2019.06.13

Professor / Faculty of Medical Sciences


Presentations
1. Shioyama Y, Terashima K, Suefuji H, Shinoto M, Toyama S, Matsumoto K, Mtasunobu A, Fukunishi K , Results of Hypofractionated Carbon-ion Radiotherapy for Peripherally Located Stage I Non-small-cell Lung Cancer, The 60th Annual Meeting of American Society for Therapeutic Radiology and Oncology, 2018.10.
2. Shioyama Y, Carbon-ion Radiotherapy in SAGA-HIMAT, The 2nd international symposium for high precision radiotherapy, 2018.06.
3. Shioyama Y, Treatment Strategy for Head and Neck Cancer, 日本放射線腫瘍学会第30回学術大会, 2017.11.
4. Shioyama Y, Yamamoto N, Saitoh JI, Fujii O, Matsunobu A, Ohno T, Okimoto T, Tsuji H, Kamada T, Nakano T, Nemoto K , Multi-institutional Retrospective Study of Carbon-ion Radiotherapy for Stage I Non-small cell Lung Cancer: Japan Carbon-ion Radiation Oncology Study Group, The 58th Annual Meeting of American Society for Therapeutic Radiology and Oncology, 2016.09.
5. Shioyama Y, Nagata Y, Komiyama T, Takayama K, Shibamoto Y, Ueki N, Yamada K, Kozuka T, Kimura T, Matsuo Y , Multi-institutional Retrospective Study of Stereotactic Body Radiation Therapy for Stage I Small Cell Lung Cancer: Japanese Radiation Oncology Study Group (JROSG), The 57th Annual Meeting of American Society for Therapeutic Radiology and Oncology, 2015.10.
6. Shioyama Y, Carbon ion radiotherapy in Japan: current status and perspective, International JSPS-DFG workshop on future joint studies in the field of radiation research, 2015.03.
7. Shioyama Y, Carbon Ion Radiotherapy Project at SAGA-HIMAT: Current Status and Perspective, The 12th International Symposium for Future Drug Discovery and Medical Care, 2014.09.
8. Shioyama Y, Carbon-ion Radiotherapy for Early-Stage Lung Cancer: Current Status in Japan, The 15th Asian Oceanian Congress of Radiology, 2014.09.
9. Shioyama Y, Onishi H, Takayama K, Matsuo Y, Takeda A, Yamashita H, Miyakawa A, Murakami N, Aoki M, Matsushita H , Stereotactic Body Radiotherapy for 90 years or Older Patients with Stage I Non -small -cell Lung Cancer, The 56th. Annual Meeting of American Society for Therapeutic Radiology and Oncology, 2014.09.
10. Shioyama Y, Shinoto Y, Suefuji H, Toyama S, Sato H, Endo M, Kudo S, Carbon ion radiotherapy in SAGA-HIMAT, 17th Workshop of the German-Japanese Affiliation, 2014.06.
11. Shioyama Y, Shinoto Y, Suefuji H, Toyama S, Sato H, Himukai T, Tsunashima Y, Endo M, Totoki T, Kudo S , Carbon ion radiotherapy in SAGA-HIMAT, 53rd Annual Conference of the Paticle Therapy Coperative Group, 2014.06.
12. Ayumi Nonaka, Hidetaka Arimura, Katsumasa Nakamura, Yoshiyuki Shioyama, Mazen Soufi, Taiki Magome, Hiroshi Honda, Hideki Hirata, Local image descriptor-based searching framework of usable similar cases in a radiation treatment planning database for stereotactic body radiotherapy, Medical Imaging 2014 - PACS and Imaging Informatics: Next Generation and Innovations, 2014.01, Radiation treatment planning (RTP) of the stereotactic body radiotherapy (SBRT) was more complex compared with conventional radiotherapy because of using a number of beam directions. We reported that similar planning cases could be helpful for determination of beam directions for treatment planners, who have less experiences of SBRT. The aim of this study was to develop a framework of searching for usable similar cases to an unplanned case in a RTP database based on a local image descriptor. This proposed framework consists of two steps searching and rearrangement. In the first step, the RTP database was searched for 10 cases most similar to object cases based on the shape similarity of two-dimensional lung region at the isocenter plane. In the second step, the 5 most similar cases were selected by using geometric features related to the location, size and shape of the planning target volume, lung and spinal cord. In the third step, the selected 5 cases were rearranged by use of the Euclidean distance of a local image descriptor, which is a similarity index based on the magnitudes and orientations of image gradients within a region of interest around an isocenter. It was assumed that the local image descriptor represents the information around lung tumors related to treatment planning. The cases, which were selected as cases most similar to test cases by the proposed method, were more resemble in terms of the tumor location than those selected by a conventional method. For evaluation of the proposed method, we applied a similar-cases-based beam arrangement method developed in the previous study to the similar cases selected by the proposed method based on a linear registration. The proposed method has the potential to suggest the superior beam-arrangements from the treatment point of view..
13. Hidetaka Arimura, Ze Jin, Yoshiyuki Shioyama, Katsumasa Nakamura, Taiki Magome, Masayuki Sasaki, Automated method for extraction of lung tumors using a machine learning classifier with knowledge of radiation oncologists on data sets of planning CT and FDG-PET/CT images, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013, 2013.10, We have developed an automated method for extraction of lung tumors using a machine learning classifier with knowledge of radiation oncologists on data sets of treatment planning computed tomography (CT) and 18F-fluorodeoxyglucose (FDG)-positron emission tomography (PET)/CT images. First, the PET images were registered with the treatment planning CT images through the diagnostic CT images of PET/CT. Second, six voxel-based features including voxel values and magnitudes of image gradient vectors were derived from each voxel in the planning CT and PET /CT image data sets. Finally, lung tumors were extracted by using a support vector machine (SVM), which learned 6 voxel-based features inside and outside each true tumor region determined by radiation oncologists. The results showed that the average DSCs for 3 and 6 features for three cases were 0.744 and 0.899, and thus the SVM may need 6 features to learn the distinguishable characteristics. The proposed method may be useful for assisting treatment planners in delineation of the tumor region..
14. Shioyama Y, Onishi H, Takayama K, Matsuo Y, Takeda A, Yamashita H, Miyakawa A, Murakami N, Aoki M, Matsushita H , Stereotactic Body Radiotherapy for Stage-I Small-cell Lung Cancer: Clinical outcomes in a Japanese Multi-institutional Retrospective Study, 55th. Annual Meeting of American Society for Therapeutic Radiology and Oncology, 2013.09.
15. Sho Kudo, Yoshiyuki Shioyama, Masahiro Endo, Mitsutaka Kanazawa, Hirohiko Tsujii, Tadahide Totoki, Construction of SAGA HIMAT for carbon ion cancer therapy, 22nd International Conference on the Application of Accelerators in Research and Industry, CAARI 2012, 2013.05, SAGA HIMAT is now under construction in Tosu city, Saga prefecture, Kyushu island, Japan. It will open in 2013 and become the fourth carbon ion beam cancer therapy center in Japan. It is a collaborative project among the local governments, industries and universities in northern Kyushu area..
16. Shioyama Y, Carbon-ion Radiotherapy: Current status in Japan, 37th Annual Scientific Meeting the MD Anderson Radiation Oncology, GH Fletcher Society, 2013.04.
17. G. Kakiuchi, Hidetaka Arimura, Yoshiyuki Shioyama, S. Minohara, A. Mizoguchi, Hiroshi Honda, F. Toyofuku, Masafumi Ohki, H. Hirata, Automated determination of robust beam directions against patient setup errors based on electron density spatial distribution in hadron particle therapy, World Congress on Medical Physics and Biomedical Engineering, 2013.04, The precise dose distribution fitted with a tumor shape in a beam direction tend to be more fragile if the beam's eye view (BEV) of the three dimensional (3D) electron density (ED) map in the beam direction changed more abruptly (high frequency) with large variation (large amplitude). This could lead to significant tumor underdose, but fatal overdose in organs at risk. In this study, we developed an automated method for determination of robust beam directions against the patient setup error based on the ED-based BEV in the beam direction in the particle therapy. The basic idea of our approach was to find the robust beam directions, whose ED- based BEV has low special frequency variation with small amplitude. For evaluation of the variation in the ED-based BEV in a beam direction, we calculated power spectra of the ED-based BEVs in all directions (0 to 355 degree) with an interval of 5 degree. We assume that as the spatial frequency and amplitude of the variation in the ED-based BEV in a beam direction is lower and smaller, respectively, the gradient of the power spectrum becomes larger, which means the robust beam direction. The ED-based BEV was produced by projection of a 3D electron density map derived from the computed tomogra- phy (CT) image from a beam source to a planning target volume (PTV) distal end. The gradient of the power spectrum was obtained as the slope of a one-order polynomial with the power spectral values for all frequencies until a Nyquist frequency.The proposed methodology was applied to four head and neck cancer patients for determination of robust beam directions. As a preliminary result, radiation oncologists agreed with most beam directions, which seem to be robust against patient setup errors, suggested by the proposed method..
18. Shioyama Y, Caron-ion Radiotherapy: Current status in Japan, Radiation Oncology, Taiwan-US joint meeting, 2012.12.
19. Taiki Magome, Hidetaka Arimura, Yoshiyuki Shioyama, Asumi Mizoguchi, Chiaki Tokunaga, Katsumasa Nakamura, Hiroshi Honda, Masafumi Ohki, Fukai Toyofuku, Hideki Hirata, Computer-assisted radiation treatment planning system for determination of beam directions based on similar cases in a database for stereotactic body radiotherapy, Photonic Crystal Materials and Devices X, 2012, Similar treatment plans or similar cases in radiotherapy treatment planning (RTP) databases of senior experienced planners could be helpful or educational for treatment planners who have few experiences of stereotactic body radiotherapy (SBRT). The aim of this study was to investigate the feasibility of beam arrangements determined using similar cases in a RTP database including plans designed by experienced treatment planners. Similar cases were automatically selected based on geometrical features and planning evaluation indices from 81 cases with lung cancer who received SBRT. First, the RTP database was searched for the five most similar cases based on geometrical features related to the location, size, and shape of the planning target volume, lung, and spinal cord. Second, the five beam arrangements of an objective case were automatically determined by registering five similar cases to the objective case with respect to lung regions by means of a linear registration technique. For evaluation of the beam arrangements, five plans were designed by applying the beam arrangements determined in the second step to the objective case. The most usable beam arrangement was selected by sorting the five plans based on 11 planning evaluation indices including tumor control probability and normal tissue complication probability. We applied the proposed two-step method to 10 test cases by using an RTP database of 81 cases with lung cancer, and compared the 11 planning evaluation indices between the original plan and the corresponding most usable similar-case-based plan. As a result, there were no statistically significant differences between the original beam arrangements and the most usable similar-case-based beam arrangements (P > 0.05) in terms of the 10 planning evaluation indices. The proposed method suggested usable beam arrangements with little difference from cases in the RTP database, and thus it could be employed as an educational tool for less experienced treatment planners..
20. Shioyama Y, Matsumoto K, Yoshitake T, Nakamura K, Sasaki T, Ohga S, Nonoshita T, Asai K, Hirata H, Honda H , Stereotactic Body Radiotherapy for Histologically Confirmed Stage I Non-small Cell Lung Cancer: Clinical Results and Prognostic Factors, 53rd. Annual Meeting of American Society for Therapeutic Radiology and Oncology , 2011.10.
21. Wataru Itano, Hidetaka Arimura, Yoshiyuki Shioyama, Taiki Magome, Tadamasa Yoshitake, Shigeo Anai, Katsumasa Nakamura, Satoshi Yoshidome, Masayuki Tachibana, Satoshi Nomoto, Hiroshi Honda, Masafumi Ohki, Fukai Toyofuku, Hideki Hirata, Automated verification method for patient setup based on digitally reconstructed radiography and portal image for prostate cancer treatment, 2010 World Automation Congress, WAC 2010, 2010.12, Accurate patient setup is essential in high-precision radiotherapy because deviations in delivered beam geometry may result in decreasing tumor control and increasing complications of adjacent normal tissue. At a majority of clinical facilities, radiation oncologists verify the patient setup by visual comparison in spite of it lacks reproducibility and quantitativity during the radiation treatment. Therefore, the purpose of this study was to develop an automated method for verification of patient setup based on an edge-based template matching between the digitally reconstructed radiography (DRR) and portal images for prostate cancer treatment. First, the actual center of the irradiation field in the portal image was estimated based on the template matching technique with the cross-correlation coefficient. Second, the measuring scales on the DRR and the portal image of an electronic portal imaging device were reduced, and edge portions in two images were enhanced by using a Sobel filter for an accurate template matching. Third, a pelvic template image of the DRR was produced after the registration between the DRR and portal image using an affine transform. Forth, the center of the planned irradiation field in the portal image was estimated based on the template matching technique with the cross-correlation coefficient. Finally, the patient setup error was calculated based on the displacement between the center of the actual irradiation field and planned irradiation field. We applied the proposed method to 14 cases with prostate cancer. The residual error between the patient setup errors obtained by our method and the oncologist was calculated for evaluation of the proposed method. The average residual error of the Euclidian distance was 3.15 mm. The results suggest that the proposed method may be useful for detection of the patient setup error using the DRR and portal image..
22. Shioyama Y, Ohga S, Yoshitake T, Nonoshita T, Ohnishi K, Terashima K, Asai K, Nakamura K, Hirata H, Honda H , Clinical Results of Stereotactic Body Radiotherapy for Stage I Small Cell Lung Cancer: A Single Institutional Experience, 52nd. Annual Meeting of American Society for Therapeutic Radiology and Oncology, 2010.10.
23. Clinical Results of Stereotactic Body Radiotherapy for Oligometastatic Lung Tumors.
24. Visual Feedback-guided Breath-hold Technique For Radiotherapy Using A Machine Vision System With A Charge-coupled Device Camera And A Head-mounted Display: An Evaluation Of Breath-hold Reproducibility In Clinical Use..
25. Hidetaka Arimura, Shigeo Anai, Satoshi Yoshidome, Katsumasa Nakamura, Yoshiyuki Shioyama, Satoshi Nomoto, Hiroshi Honda, Yoshihiko Onizuka, Hiromi Terashima, Computerized method for measurement of displacement vectors of target positions on EPID cine images in stereotactic radiotherapy, Medical Imaging 2007: Image Processing, 2007.11, The purpose of this study was to develop a computerized method for measurement of displacement vectors of target position on electronic portal imaging device (EPID) cine images in a treatment without implanted markers. Our proposed method was based on a template matching technique with cross-correlation coefficient between a reference portal (RP) image and each consecutive portal (CP) image acquired by the EPID. EPID images with 512×384 pixels (pixel size:0.56 mm) were acquired in a cine mode at a sampling rate of 0.5 frame/sec by using an energy of 4, 6, or 10MV on linear accelerators. The displacement vector of the target on each cine image was determined from the position in which took the maximum cross-correlation value between the RP image and each CP image. We applied our method to EPID cine images of a lung phantom with a tumor model simulating respiratory motion, and 5 cases with a non-small cell lung cancer and one case of metastasis. For validation of our proposed method, displacement vectors of a target position calculated by our method were compared with those determined manually by two radiation oncologists. As a result, for lung phantom images, target displacements by our method correlated well with those by the oncologists (r=0.972 - 0.994). Correlation values for 4 cases ranged from 0.854 to 0.991, but the values for the other two cases were 0.609 and 0.644. This preliminary result suggested that our method may be useful for monitoring of displacement vectors of target positions without implanted markers in stereotactic radiotherapy..
26. Clinical outcome and prognostic factors of radiotherapy for mesopharyngeal cancer patients.
27. Proton beam radiotherapy for lung cancer.
28. Clinical results of proton-beam radiotherapy for non-small cell lung cancer..
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