Achievement 2020

Original Papers

  • Tomori S, Kadoya N, Kajikawa T, Kimura Y, Narazaki K, Ochi T, Jingu K. “Systematic method for a deep learning-based prediction model for gamma evaluation in patient-specific quality assurance of volumetric modulated arc therapy”, Med Phys. 2020 Dec 26.
  • Umezawa R, Kadoya N, Ota H, Nakajima Y, Saito M, Takagi H, Takanami K, Takahashi N, Ishikawa Y, Yamamoto T, Matsushita H, Takeda K, Takase K, Jingu K. “Dose-Dependent Radiation-Induced Myocardial Damage in Esophageal Cancer Treated With Chemoradiotherapy: A Prospective Cardiac Magnetic Resonance Imaging Study”, Adv Radiat Oncol. 2020 Aug 5;5(6):1170-1178.
  • Miyasaka Y, Kadoya N, Umezawa R, Takayama Y, Ito K, Yamamoto T, Tanaka S, Dobashi S, Takeda K, Nemoto K, Iwai T, Jingu K. “Comparison of predictive performance for toxicity by accumulative dose of DVH parameter addition and DIR addition for cervical cancer patients”, J Radiat Res. 2021 Jan 1;62(1):155-162.
  • Kajikawa T, Kadoya N, Tanaka S, Nemoto H, Takahashi N, Chiba T, Ito K, Katsuta Y, Dobashi S, Takeda K, Yamada K, Jingu K. “Dose distribution correction for the influence of magnetic field using a deep convolutional neural network for online MR-guided adaptive radiotherapy”, Phys Med. 2020 Dec;80:186-192.
  • Sugawara Y, Kadoya N, Kotabe K, Nakajima Y, Ikeda R, Tanabe S, Ohashi H, Jingu K. “Development of a dynamic deformable thorax phantom for the quality management of deformable image registration”, Phys Med. 2020 Sep;77:100-107.
  • Kadoya N, Nemoto H, Kajikawa T, Nakajima Y, Kanai T, Ieko Y, Ikeda R, Sato K, Dobashi S, Takeda K, Jingu K. “Evaluation of four-dimensional cone beam computed tomography ventilation images acquired with two different linear accelerators at various gantry speeds using a deformable lung phantom”, Phys Med. 2020 Sep;77:75-83.
  • Ieko Y, Kadoya N, Kanai T, Nakajima Y, Arai K, Kato T, Ito K, Miyasaka Y, Takeda K, Iwai T, Nemoto K, Jingu K. “The impact of 4DCT-ventilation imaging-guided proton therapy on stereotactic body radiotherapy for lung cancer”, Radiol Phys Technol. 2020 Sep;13(3):230-237.
  • Miyasaka Y, Kadoya N, Ito K, Umezawa R, Kubozono M, Yamamoto T, Nakajima Y, Saito M, Takayama Y, Nemoto K, Iwai T, Jingu K, “Quantitative Analysis of Intra-Fractional Variation in CT-based Image Guided Brachytherapy for Cervical Cancer Patients”, Phys Med. 2020 Apr 30;73:164-172
  • Kimura Y, Kadoya N, Tomori S, Oku Y, Jingu K, “Error Detection Using a Convolutional Neural Network With Dose Difference Maps in Patient-Specific Quality Assurance for Volumetric Modulated Arc Therapy”, Phys Med. 2020 Apr 21;73:57-64
  • Takagi H, Kadoya N, Kajikawa T, Tanaka S, Takayama Y, Chiba T, Ito K, Dobashi S, Takeda K, Jingu K, “Multi-atlas-based Auto-Segmentation for Prostatic Urethra Using Novel Prediction of Deformable Image Registration Accuracy”, Med Phys. 2020 Mar 22
  • Parishan M, Faghihi R, Kadoya N, Jingu K, “The Effects of a Transverse Magnetic Field on the Dose Enhancement of Nanoparticles in a Proton Beam: A Monte Carlo Simulation”, Phys Med Biol. 2020 Apr 17;65(8):085002
  • Nakajima Y, Kadoya N, Kimura T, Hioki K, Jingu K, Yamamoto T, “Variations between dose-ventilation and dose-perfusion metrics in radiotherapy planning for lung cancer”, Adv Radiat Oncol. 2020 Mar 20
  • Kadoya N, Tanaka S, Kajikawa T, Tanabe S, Abe K, Nakajima Y, Yamamoto T, Takahashi N, Takeda K, Dobashi S, Takeda K, Nakane K, Jingu K, “Homology-based Radiomic Features for Prediction of the Prognosis of Lung Cancer Based on CT-based Radiomics”, Med Phys. 2020 Feb 25
  • Nakajima Y, Kadoya N, Kanai T, Saito M, Kito S, Hashimoto S, Karasawa K, Jingu K, “Evaluation of the Effect of User-Guided Deformable Image Registration of Thoracic Images on Registration Accuracy Among Users”, Med Dosim. 2020 Jan 31:S0958-3947(19)30130-X

Domestic Conference

  • Tanabe S, Kadoya N, Tanaka S, Kajikawa T, Abe K, Takeda K, Dobashi S, Jingu K, “Effect of type of input image on prognostic prediction accuracy using deep learning radiomics in lung cancer patients”, 第119回日本医学物理学会学術大会. 2020.5 オンライン
  • Takeuchi T, Kadoya N, Tanabe S, Tanaka S, Matsuda S, Jingu K, “Development of GAN-based synthetic brain CT image: What impact does increasing the training data have on the accuracy?”, 第119回日本医学物理学会学術大会. 2020.5 オンライン
  • 木村祐利、角谷倫之、奥洋平、神宮 啓一. “VMAT患者線量検証におけるConvolutional neural networkを用いたMLCエラー検出モデルの開発”. 第33回高精度放射線外部照射部会学術大会. 2020.5 オンライン

International Conference

  • Ishida T, Kadoya K, Tanabe S, Ohashi H, Takeda K, Dobashi S, Jingu K, “Evaluate of the accuracy of pelvic CT-MR deformable image registration using various cost functions”, 20th Asia-Oceania Congress of Medical Physics (AOCMP), 2020. 12 Phuket, Thailand.
  • Mouri S, Kadoya N, Katsuta Y, Kanai T, Nakajima Y, Tanabe S, Sugai Y, Umeda M, Dobashi S, Takeda K, Jingu K, “Evaluation of machine learning-based prediction model for radiation pneumonitis in NSCLC patients”, 20th Asia-Oceania Congress of Medical Physics (AOCMP), 2020. 12 Phuket, Thailand.
  • Sugai Y, Kadoya N, Tanaka S, Tanabe S, Umeda M, Yamamoto T, Takeda K, Dobashi S, Ohashi H, Takeda K, Jingu K, “Prognostic analysis of CT-based radiomics focusing on a subgroup of NSCLC patients”, 20th Asia-Oceania Congress of Medical Physics (AOCMP), 2020. 12 Phuket, Thailand.
  • Tanabe S, Kadoya N, Tanaka S, Takeda K, Dobashi S, Jingu K, “Impact of image type and deep learning architecture in deep learning radiomics on the accuracy of lung cancer prediction”, 20th Asia-Oceania Congress of Medical Physics (AOCMP), 2020. 12 Phuket, Thailand.
  • Ieko Y, Kadoya N, Abe K, Tanaka S, Takagi H, Kanai T, Ichiji K, Yamamoto T, Ariga H, Jingu K, "Evaluation of CT-Based Radiomics Features for Predicting Parameters Measured Using a Pulmonary Function Test", 2020 Joint AAPM | COMP Meeting 2020. 7. VIRTUAL


  • 角谷倫之. “Radiological physics and technology” 論文賞(土井賞). 2020.5


  • 角谷倫之、梶川智博、田中祥平、土橋卓、神宮啓一. 磁場影響を考慮した線量分布作成プログラム、磁場影響を考慮した線量分布作成方法、および線量分布作成装置, 特願2020-1851160

Invited talk & Symposium

  • 勝田義之. “Templateによる効率化(Monaco)”. 令和2年度東北大学医学物理セミナー. 2020.12 オンライン
  • 角谷倫之. “MR-Linac”. 第9回JBMP放射線治療品質管理・医学物理講習会. 2020.11 オンライン
  • 角谷倫之. “Adaptive radiotherapy解剖学的変化に対する放射線治療”, 日本放射線腫瘍学会第33回学術大会 (教育講演)
  • 角谷倫之. “On-line adaptive radiotherapy with AI technology”, 日本放射線腫瘍学会第33回学術大会 (AIシンポジウム)
  • 角谷倫之. “医学物理士になるには“. 医学物理士になろうセミナー. 2020.10 オンライン
  • 角谷倫之. “高精度な患者個別放射線治療を実現するレディオミクス技術”. 第117回日本医学物理学会学術大会 シンポジウム. 2019.5 オンライン


  • 科学研究費補助金 研究活動スタート支援 「患者個別化医療に向けた治療前の医療画像のみから腫瘍の縮小を予測する手法の開発」(2020年10月~2021年3月、研究代表者 田中祥平 273万円)
  • 科学研究費補助金 若手研究 「肺の機能と形態の線量評価を融合した放射線肺臓炎予測モデルの構築」(2020年4月~2023年3月、研究代表者 勝田義之 350万円)
  • AMED医工連携事業化推進事業 東北大学(代表:角谷助教)、京都大学(代表:溝脇教授)、東京女子医大(代表:西尾教授)の3大学が参画する研究プロジェクト(四次元放射線治療に対応した放射線治療計画装置の開発) (2020年2月~2022年3月:プロジェクト全体総額: 約1億8000万円).
Division of Medical Physics, Department of Radiation Oncology, Tohoku University Graduate School of Medicine,
1-1 Seiryo-cho, Aoba-ku, Sendai, 980-8574, Japan MAP
Tel:+81-22-717-7433 Email: kadoya.n(at)