{"id":732,"date":"2023-07-01T12:10:04","date_gmt":"2023-07-01T03:10:04","guid":{"rendered":"https:\/\/www.rt-medphys.med.tohoku.ac.jp\/?page_id=732"},"modified":"2023-07-13T14:40:43","modified_gmt":"2023-07-13T05:40:43","slug":"achievement-2021","status":"publish","type":"page","link":"https:\/\/www.rt-medphys.med.tohoku.ac.jp\/en\/achievement-2021\/","title":{"rendered":"Achievement-2021"},"content":{"rendered":"\n<h2 class=\"wp-block-heading blue-line\">Original Papers<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Ito K, Kadoya N, Katsuta Y, Tanaka S, Dobashi S, Takeda K, Jingu K, \u201cEvaluation of the electron transport algorithm in magnetic field in EGS5 Monte Carlo code\u201d, Phys Med. 2022 Jan;93:46-51.<\/li>\n\n\n\n<li>Katsuta Y, Kadoya N, Mouri S, Tanaka S, Kanai T, Takeda K, Yamamoto T, Ito K, Kajikawa T, Nakajima Y, Jingu K, \u201cPrediction of radiation pneumonitis with machine learning using 4D-CT based dose-function features\u201d, J Radiat Res. 2022 Jan 20;63(1):71-79.<\/li>\n\n\n\n<li>Ishida T, Kadoya N, Tanabe S, Ohashi H, Nemoto H, Dobashi S, Takeda K, Jingu K, \u201cEvaluation of performance of pelvic CT-MR deformable image registration using two software programs\u201d, J Radiat Res. 2021 Sep 9:rrab078.<\/li>\n\n\n\n<li>Kadoya N, Sakulsingharoj S, Kron T, Yao A, Hardcastle N, Bergman A, Okamoto H, Mukumoto N, Nakajima Y, Jingu K, Nakamura M, \u201cDevelopment of a physical geometric phantom for deformable image registration credentialing of radiotherapy centers for a clinical trial\u201d, J Appl Clin Med Phys. 2021 Jul;22(7):255-265.<\/li>\n\n\n\n<li>Kimura Y, Kadoya N, Oku Y, Kajikawa T, Tomori S, Jingu K, \u201cError detection model developed using a multi-task convolutional neural network in patient-specific quality assurance for volumetric-modulated arc therapy\u201d, Med Phys. 2021 Sep;48(9):4769-4783.<\/li>\n\n\n\n<li>Tanaka S, Kadoya N, Umezawa R, Nemoto H, Katsuta Y, Ito K, Takeda K, Jingu K, \u201cEvaluation of the dosimetric impact of heart function-based volumetric modulated arc therapy planning in patients with esophageal cancer\u201d, Radiol Phys Technol. 2021 Sep;14(3):279-287.<\/li>\n\n\n\n<li>Sugai Y, Kadoya N, Tanaka S, Tanabe S, Umeda M, Yamamoto T, Takeda K, Dobashi S, Ohashi H, Takeda K, Jingu K, \u201cImpact of feature selection methods and subgroup factors on prognostic analysis with CT-based radiomics in non-small cell lung cancer patients\u201d, Radiat Oncol. 2021 Apr 30;16(1):80.<\/li>\n\n\n\n<li>Tomori S, Kadoya N, Kajikawa T, Kimura Y, Narazaki K, Ochi T, Jingu K, \u201cSystematic method for a deep learning-based prediction model for gamma evaluation in patient-specific quality assurance of volumetric modulated arc therapy\u201d, Med Phys. 2021 Mar;48(3):1003-1018.<\/li>\n\n\n\n<li>Miyasaka Y, Kadoya N, Umezawa R, Takayama Y, Ito K, Yamamoto T, Tanaka S, Dobashi S, Takeda K, Nemoto K, Iwai T, Jingu K, \u201cComparison of predictive performance for toxicity by accumulative dose of DVH parameter addition and DIR addition for cervical cancer patients\u201d, J Radiat Res. 2021 Jan 1;62(1):155-162.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading blue-line\">Domestic Conference<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u83c5\u4e95\u88d5\u6597\u3001\u89d2\u8c37\u502b\u4e4b\u3001\u6238\u68ee\u8056\u6cbb\u3001\u6728\u6751\u7950\u5229\u3001\u68b6\u5ddd\u667a\u535a\u3001\u8096\u7389\u6749\u3001\u9f4a\u85e4 \u7f8e\u54b2\u3001\u6238\u585a\u51cc\u592a\u3001\u6b66\u7530\u8ce2\u3001\u795e\u5bae\u5553\u4e00. \u201c\u6df1\u5c64\u5b66\u7fd2\u3092\u7528\u3044\u305f\u60a3\u8005\u500b\u5225QA\u4e88\u6e2c\u306e\u305f\u3081\u306e\u7dda\u91cf\u5206\u5e03\u3068\u8907\u96d1\u6027\u6307\u6a19\u3092\u7528\u3044\u305f\u6df7\u5408\u30e2\u30c7\u30eb\u958b\u767a\u201d. \u7b2c34\u56de\u65e5\u672c\u653e\u5c04\u7dda\u816b\u760d\u5b66\u4f1a\u5b66\u8853\u5927\u4f1a. 2021.11 \u30d0\u30fc\u30c1\u30e3\u30eb<\/li>\n\n\n\n<li>\u7530\u4e2d\u7965\u5e73\u3001\u89d2\u8c37\u502b\u4e4b\u3001\u83c5\u4e95\u88d5\u6597\u3001\u6885\u7530\u771f\u68a8\u5b50\u3001\u77f3\u6fa4\u7f8e\u512a\u3001\u52dd\u7530\u7fa9\u4e4b\u3001\u4f0a\u85e4\u8b19\u543e\u3001\u4f50\u85e4\u6e05\u548c\u3001\u6b66\u7530\u8ce2\u3001\u571f\u6a4b\u5353\u3001\u795e\u5bae\u5553\u4e00. \u201cDeep learning based radiomics\u30a2\u30d7\u30ed\u30fc\u30c1\u306b\u3088\u308b\u982d\u981a\u90e8\u816b\u760d\u7e2e\u5c0f\u306e\u4e88\u6e2c\u201d. \u7b2c34\u56de\u65e5\u672c\u653e\u5c04\u7dda\u816b\u760d\u5b66\u4f1a\u5b66\u8853\u5927\u4f1a. 2021.11 \u30d0\u30fc\u30c1\u30e3\u30eb<\/li>\n\n\n\n<li>\u6238\u585a\u51cc\u592a\u3001\u89d2\u8c37\u502b\u4e4b\u3001\u6238\u68ee\u8056\u6cbb\u3001\u6728\u6751\u7950\u5229\u3001\u68b6\u5ddd\u667a\u535a\u3001\u83c5\u4e95\u88d5\u6597\u3001\u8096\u7389\u6749\u3001\u9f4a\u85e4\u7f8e\u54b2\u3001\u6b66\u7530\u8ce2\u3001\u795e\u5bae\u5553\u4e00. \u201c\u6df1\u5c64\u5b66\u7fd2\u3092\u7528\u3044\u305f\u30ac\u30f3\u30de\u30d1\u30b9\u7387\u4e88\u6e2c\u306e\u5b66\u7fd2\u30c7\u30fc\u30bf\u4f9d\u5b58\u6027\u306e\u691c\u8a0e\u201d. \u7b2c34\u56de\u65e5\u672c\u653e\u5c04\u7dda\u816b\u760d\u5b66\u4f1a\u5b66\u8853\u5927\u4f1a. 2021.11 \u30d0\u30fc\u30c1\u30e3\u30eb<\/li>\n\n\n\n<li>Mouri S, Kadoya N, Katsuta Y, Takeda K, Yamamoto T, Kanai T, Nakajima Y, Tanaka S, Tanabe S, Sugai Y, Umeda M, Ishida T, Dobashi S, Takeda K, Jingu K, \u201cEvaluation of machine learning-based prediction model with combination of conventional and functional dosimetric parameters for radiation pneumonitis in NSCLC patients\u201d, \u7b2c121\u56de\u65e5\u672c\u533b\u5b66\u7269\u7406\u5b66\u4f1a\u5b66\u8853\u5927\u4f1a. 2021.4 \u6a2a\u6d5c&nbsp;<\/li>\n\n\n\n<li>Umeda M, Kadoya N, Tanaka S, Tanabe S, Sugai Y, Ohashi H, Dobashi S, Takeda K, Jingu K, \u201cDevelopment of prognostic prediction method with the novel radiomic feature based on graph theory\u201d, \u7b2c121\u56de\u65e5\u672c\u533b\u5b66\u7269\u7406\u5b66\u4f1a\u5b66\u8853\u5927\u4f1a. 2021.4 \u6a2a\u6d5c<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading blue-line\">International Conference<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Mouri S, Kadoya N, Katsuta Y, Takeda K, Yamamoto T, Kanai T, Nakajima Y, Tanaka S, Tanabe S, Sugai Y, Umeda M, Ishida T, Dobashi S, Takeda K, Jingu K, \u201cDevelopment of machine learning-based radiation pneumonitis prediction model with combination of conventional, functional dosimetric parameters and clinical factors in NSCLC patients\u201d,The 9th Korea-Japan joint meeting on medical physics . 2021.9 virtual&nbsp;<\/li>\n\n\n\n<li>Ishida T, Kadoya N, Tanabe S, Ohashi H, Nemoto H, Dobashi S, Takeda K, Jingu K, \u201cAccuracy of pelvic CT-MR deformable image registration: Comparison of open-source and commercial software\u201d, 63th annual meeting of AAPM, 2021.7. virtual&nbsp;<\/li>\n\n\n\n<li>Sugai Y, Kadoya N, Tanaka S, Tanabe S, Umeda M, Yamamoto T, Takeda K, Dobashi S, Ohashi H, Takeda K, Jingu K, \u201cCan unified data improve the performance of radiomics-based prognostic prediction in lung cancer patients?\u201d, 63th annual meeting of AAPM, 2021.7. virtual<\/li>\n\n\n\n<li>Tanaka S, Kadoya N, Sugai Y, Umeda M, Katsuta Y, Ito K, Yamamoto T, Takahashi N, Takeda K, Dobashi S, Jingu K, \u201cA deep learning-based radiomics approach to identify patient with early tumor regression utilizing planning CT images for adaptive radiotherapy\u201d, 63th annual meeting of AAPM, 2021.7. virtual&nbsp;<\/li>\n\n\n\n<li>Umeda M, Kadoya N, Tanaka S, Tanabe S, Sugai Y, Ishida T, Ohashi H, Dobashi S, Takeda K, Jingu K, \u201cGraph Theory-Based Radiomics Features: Application of Tumor Network Structures On CT-Based Radiomics for Prognostic Prediction\u201d, 63th annual meeting of AAPM, 2021.7. virtual&nbsp;<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading blue-line\">Award<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u5bb6\u5b50\u7fa9\u6717. \u201cRadiological physics and technology\u201d \u8ad6\u6587\u8cde(\u571f\u4e95\u8cde). 2021.4<\/li>\n\n\n\n<li>Yoshiro Ieko. AFOMP Journal Prize 2021 (Best Paper Award). 2021.12&nbsp;<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading blue-line\">Book<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u6709\u6751 \u79c0\u5b5d \u7de8\u3001\u89d2\u8c37 \u502b\u4e4b \u7de8. \u201c\u30ec\u30c7\u30a3\u30aa\u30df\u30af\u30b9\u5165\u9580\u201d, \u30aa\u30fc\u30e0\u793e<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading blue-line\">Patent<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u89d2\u8c37\u502b\u4e4b\u3001\u6885\u7530\u771f\u68a8\u5b50\u3001\u83c5\u4e95\u88d5\u6597\u3001\u7530\u4e2d\u7965\u5e73\u3001\u795e\u5bae\u5553\u4e00\u3001\u4e88\u5f8c\u4e88\u6e2c\u88c5\u7f6e\u3001\u4e88\u5f8c\u4e88\u6e2c\u65b9\u6cd5\u53ca\u3073\u30d7\u30ed\u30b0\u30e9\u30e0, \u7279\u9858\uff12\uff10\uff12\uff11\uff0d\uff10\uff16\uff10\uff12\uff16\uff18\u53f7<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading blue-line\">Invited talk &amp; Symposium<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u89d2\u8c37\u502b\u4e4b. \u201c\u753b\u50cf\u30ec\u30b8\u30b9\u30c8\u30ec\u30fc\u30b7\u30e7\u30f3\u306e\u6700\u524d\u7dda\u201d. \u533b\u5b66\u7269\u7406\u5b66\u4f1a\u533b\u5b66\u7269\u7406\u6559\u80b2\u30bb\u30df\u30ca\u30fc2021. 2021.12 \u30aa\u30f3\u30e9\u30a4\u30f3<\/li>\n\n\n\n<li>\u89d2\u8c37\u502b\u4e4b. \u201c\u975e\u525b\u4f53\u30ec\u30b8\u30b9\u30c8\u30ec\u30fc\u30b7\u30e7\u30f3\u306e\u6d3b\u7528\u3068\u305d\u306e\u5b89\u5168\u6027\u201d. \u7b2c34\u56de\u65e5\u672c\u653e\u5c04\u7dda\u816b\u760d\u5b66\u4f1a\u5b66\u8853\u5927\u4f1aAI\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0. 2021.11 \u30aa\u30f3\u30e9\u30a4\u30f3<\/li>\n\n\n\n<li>\u5bb6\u5b50\u7fa9\u6717. AFOMP Journal Prize \u53d7\u8cde\u8b1b\u6f14. \u7b2c10 \u56deJBMP \u653e\u5c04\u7dda\u6cbb\u7642\u54c1\u8cea\u7ba1\u7406\u30fb\u533b\u5b66\u7269\u7406\u8b1b\u7fd2\u4f1a\uff08\u300c\u56fd\u969b\u533b\u5b66\u7269\u7406\u306e\u65e5\u300d\u4f01\u753b\u8b1b\u6f14\uff09. 2021.11 \u30aa\u30f3\u30e9\u30a4\u30f3<\/li>\n\n\n\n<li>\u89d2\u8c37\u502b\u4e4b. \u201c\u6df1\u5c64\u5b66\u7fd2\u306b\u3088\u308b\u60a3\u8005QA\u7d50\u679c\u4e88\u6e2c\u201d.\u3000 2021\u5e74\u5ea6\u6771\u5317\u5927\u5b66\u533b\u5b66\u7269\u7406\u30bb\u30df\u30ca\u30fc. 2021.10 \u30aa\u30f3\u30e9\u30a4\u30f3<\/li>\n\n\n\n<li>\u89d2\u8c37\u502b\u4e4b. \u201c\u6cbb\u7642\u8a08\u753b\u306e\u30c1\u30a7\u30c3\u30af\u201d.\u3000\u533b\u5b66\u7269\u7406\u58eb\u4f1a\u4e3b\u50ac\u533b\u5b66\u7269\u7406\u58eb\u30bb\u30df\u30ca\u30fc\u2462. 2021.10 \u30aa\u30f3\u30e9\u30a4\u30f3<\/li>\n\n\n\n<li>\u89d2\u8c37\u502b\u4e4b. \u201cAI \u306b\u3088\u308b\u80ba\u764c\u653e\u5c04\u7dda\u6cbb\u7642\u306e\u52b9\u679c\u3068\u526f\u4f5c\u7528\u4e88\u6e2c\u306e\u9032\u5c55\u201d.\u80ba\u764c\u653e\u5c04\u7dda\u6cbb\u7642\u30bb\u30df\u30ca\u30fc. 2021.9 \u30aa\u30f3\u30e9\u30a4\u30f3<\/li>\n\n\n\n<li>\u89d2\u8c37\u502b\u4e4b. \u201c\u6280\u8853\u7684\u5074\u9762\u304b\u3089\u898b\u305f\u8ee2\u79fb\u6027\u8133\u816b\u760d\u306b\u5bfe\u3059\u308b SRS\u201d. \u7b2c33\u56de\u57fc\u7389\u770c\u653e\u5c04\u7dda\u816b\u760d\u7814\u7a76\u4f1a<\/li>\n\n\n\n<li>\u89d2\u8c37\u502b\u4e4b. \u201c\u653e\u5c04\u7dda\u6cbb\u7642\u306b\u5411\u3051\u305fMRI\u753b\u50cf\u304b\u3089\u4eee\u60f3CT\u753b\u50cf\u751f\u6210\u201d. JSMRM2021 \u30b7\u30f3\u30dd\u30b8\u30a6\u30e0. 2021.9 \u6a2a\u6d5c<\/li>\n\n\n\n<li>\u89d2\u8c37\u502b\u4e4b. \u201cMR-Linac\u306e\u73fe\u72b6\u3068\u5f53\u9662\u3067\u306e\u53d6\u308a\u7d44\u307f\u201d. \u7b2c25\u56de\u5317\u5965\u7fbd\u653e\u5c04\u7dda\u6cbb\u7642\u61c7\u8a71\u4f1a. 2021.9 \u30aa\u30f3\u30e9\u30a4\u30f3&nbsp;<\/li>\n\n\n\n<li>Kadoya N. \u201cMR-Linac research focuses\u201d. The 9th Korea-Japan joint meeting on medical physics AI Symposium. 2021.9 virtual&nbsp;<\/li>\n\n\n\n<li>\u89d2\u8c37\u502b\u4e4b. \u201cReport of AAPM Task Group 275 \uff5e\u30ec\u30dd\u30fc\u30c8\u306e\u8a73\u7d30\u3068\u5b9f\u81e8\u5e8a\u306b\u304a\u3051\u308b\u653e\u5c04\u7dda\u6cbb\u7642\u8a08\u753b\u306e\u30c0\u30d6\u30eb\u30c1\u30a7\u30c3\u30af\u306e\u5b9f\u65bd\uff5e\u201d. \u7b2c121\u56de\u65e5\u672c\u533b\u5b66\u7269\u7406\u5b66\u4f1a\u5b66\u8853\u5927\u4f1a\u6559\u80b2\u8b1b\u6f14. 2021.4 \u6a2a\u6d5c&nbsp;<\/li>\n\n\n\n<li>\u89d2\u8c37\u502b\u4e4b. \u201c\u653e\u5c04\u7dda\u533b\u5b66\u306b\u304a\u3051\u308bAI\u306e\u9032\u6b69\uff5e\u653e\u5c04\u7dda\u6cbb\u7642\uff5e\u201d.\u7b2c34\u56deJCR\u30df\u30c3\u30c9\u30a6\u30a3\u30f3\u30bf\u30fc\u30bb\u30df\u30ca\u30fc. 2021. 1 \u4ed9\u53f0<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading blue-line\">Grant<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u6771\u5317\u5927\u5b66BIP\uff08\u30d3\u30b8\u30cd\u30b9\uff65\u30a4\u30f3\u30ad\u30e5\u30d9\u30fc\u30b7\u30e7\u30f3\uff65\u30d7\u30ed\u30b0\u30e9\u30e0\uff09\u300c\u300cAI \u306b\u3088\u308b\u653e\u5c04\u7dda\u6cbb\u7642\u8a08\u753b\u306e\u54c1\u8cea\u30fb\u5b89\u5168\u6027\u691c\u8a3c\u30b7\u30b9\u30c6\u30e0\u300d\u306e\u30d7\u30ed\u30c8\u30bf\u30a4\u30d7\u958b\u767a\u3068\u4e8b\u696d\u5316\u691c\u8a3c\u300d(2021\u5e744\u6708\uff5e2022\u5e743\u6708\u3001\u7814\u7a76\u4ee3\u8868\u8005\u3000\u89d2\u8c37\u502b\u4e4b 500\u4e07\u5186\uff09<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Original Papers Domestic Conference International Conference Award Book Patent Invited talk &amp; Symposium Grant<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"page-achievement.php","meta":{"_locale":"en_US","_original_post":"https:\/\/www.rt-medphys.med.tohoku.ac.jp\/?page_id=730","footnotes":""},"class_list":["post-732","page","type-page","status-publish","hentry","en-US"],"_links":{"self":[{"href":"https:\/\/www.rt-medphys.med.tohoku.ac.jp\/wp-json\/wp\/v2\/pages\/732","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.rt-medphys.med.tohoku.ac.jp\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.rt-medphys.med.tohoku.ac.jp\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.rt-medphys.med.tohoku.ac.jp\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.rt-medphys.med.tohoku.ac.jp\/wp-json\/wp\/v2\/comments?post=732"}],"version-history":[{"count":3,"href":"https:\/\/www.rt-medphys.med.tohoku.ac.jp\/wp-json\/wp\/v2\/pages\/732\/revisions"}],"predecessor-version":[{"id":1248,"href":"https:\/\/www.rt-medphys.med.tohoku.ac.jp\/wp-json\/wp\/v2\/pages\/732\/revisions\/1248"}],"wp:attachment":[{"href":"https:\/\/www.rt-medphys.med.tohoku.ac.jp\/wp-json\/wp\/v2\/media?parent=732"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}