Utility of an Artificial Neural Network for Prediction of Survival in patients with Esophageal Cancer treated with Radiotherapy

• Project/Area Number: 24791313
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Multi-year Fund
• Research Field: Radiation science
• Research Institution: Kyushu University
• Principal Investigator: ATSUMI Kazushige 九州大学, 大学病院, 助教 (70625805)
• Project Period (FY): 2012-04-01 – 2015-03-31
• Project Status: Completed (Fiscal Year 2014)
• Budget Amount: ¥3,510,000 (Direct Cost: ¥2,700,000、Indirect Cost: ¥810,000); Fiscal Year 2013: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000); Fiscal Year 2012: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
• Keywords: 食道癌 / 放射線治療 / 放射線腫瘍学 / ニューラルネットワーク / 人口ニューラルネットワーク / 化学放射線療法 / 人工ニューラルネットワーク

Outline of Final Research Achievements

We constructed the ANN model to be useful to predict tumor response and survival in patients with esophageal cancer treated with radiotherapy. This ANN model could be used for determination of an optimal treatment strategy for esophageal cancer.

Research Products

• [Journal Article] Prediction of outcome with FDG-PET in definitive chemoradiotherapy for esophageal cancer (2013)
  • Author(s): Kazushige ATSUMI, K. NAKAMURA, K. ABE, M. HIRAKAWA, Y. SHIOYAMA, T. SASAKI, S. BABA, T. ISODA, S. OHGA, T.YOSHITAKE, M. SHINOTO, K. ASAI and Hiroshi HONDA.
  • Journal Title: Journal of Radiation Research Volume: 21 Issue: 5 Pages: 1-9
  • DOI: 10.1093/jrr/rrt021
  • Peer Reviewed
• [Presentation] Utillity of an Artificial Network for Prediction of Survival on patients with Esophageal Cancer Treated with Radiotherapy. (2014)
  • Author(s): 渥美和重
  • Organizer: 第56回米国放射線腫瘍学会(ASTRO)
  • Place of Presentation: Mosconeセンター
  • Year and Date: 2014-09-14
• [Presentation] 食道癌化学放射線療法における予後予測因子としてのFDG-PETの有用性 (2012)
  • Author(s): 渥美和重
  • Organizer: 第５４回米国放射線腫瘍学会
  • Place of Presentation: ボストン コンベンション&エキシビションセンター