Artificial intelligence for response prediction and personalisation in radiation oncology

被引：1
|
作者：
Zwanenburg, Alex [1 ,2 ,3 ,4 ,5 ,6 ,7 ,8 ]
Price, Gareth [9 ,10 ]
Loeck, Steffen [1 ,2 ,6 ,11 ]
机构：
[1] TUD Dresden Univ Technol, Fac Med, OncoRay Natl Ctr Radiat Res Oncol, Fetscherstr 74,PF 41, D-01307 Dresden, Germany
[2] TUD Dresden Univ Technol, Univ Hosp Carl Gustav Carus, Helmholtz Zentrum Dresden Rossendorf, Fetscherstr 74,PF 41, D-01307 Dresden, Germany
[3] Natl Ctr Tumor Dis Dresden NCT UCC, Dresden, Germany
[4] German Canc Res Ctr, Heidelberg, Germany
[5] TUD Dresden Univ Technol, Fac Med, Dresden, Germany
[6] TUD Dresden Univ Technol, Univ Hosp Carl Gustav Carus, Dresden, Germany
[7] Helmholtz Zentrum Dresden Rossendorf HZDR, Dresden, Germany
[8] German Canc Res Ctr DKFZ Heidelberg, Heidelberg, Germany
[9] Univ Manchester, Div Canc Sci, Manchester, England
[10] Christie NHS Fdn Trust, Manchester, England
[11] TUD Dresden Univ Technol, Fac Med, Dept Radiotherapy & Radiat Oncol, Dresden, Germany
来源：
STRAHLENTHERAPIE UND ONKOLOGIE | 2025年 / 201卷 / 03期
关键词：
Radiotherapy; Artificial intelligence; Tumour control probability; Treatment response; Normal tissue complication probability; SOCIOECONOMIC-STATUS; RADIOTHERAPY; CANCER; RECOMMENDATIONS; THERAPY; QUANTEC;
D O I：
10.1007/s00066-024-02281-z
中图分类号：
R73 [肿瘤学];
学科分类号：
100214 ;
摘要：
Artificial intelligence (AI) systems may personalise radiotherapy by assessing complex and multifaceted patient data and predicting tumour and normal tissue responses to radiotherapy. Here we describe three distinct generations of AI systems, namely personalised radiotherapy based on pretreatment data, response-driven radiotherapy and dynamically optimised radiotherapy. Finally, we discuss the main challenges in clinical translation of AI systems for radiotherapy personalisation.
引用
收藏
页码：266 / 273
页数：8
相关论文
共 50 条
  • [1] Artificial Intelligence in Radiation Oncology
    Deig, Christopher R.
    Kanwar, Aasheesh
    Thompson, Reid F.
    HEMATOLOGY-ONCOLOGY CLINICS OF NORTH AMERICA, 2019, 33 (06) : 1095 - +
  • [2] Artificial intelligence in radiation oncology
    Elizabeth Huynh
    Ahmed Hosny
    Christian Guthier
    Danielle S. Bitterman
    Steven F. Petit
    Daphne A. Haas-Kogan
    Benjamin Kann
    Hugo J. W. L. Aerts
    Raymond H. Mak
    Nature Reviews Clinical Oncology, 2020, 17 : 771 - 781
  • [3] Artificial intelligence in radiation oncology
    Huynh, Elizabeth
    Hosny, Ahmed
    Guthier, Christian
    Bitterman, Danielle S.
    Petit, Steven E.
    Haas-Kogan, Daphne A.
    Kann, Benjamin
    Aert, Hugo J. W. L.
    Mak, Raymond H.
    NATURE REVIEWS CLINICAL ONCOLOGY, 2020, 17 (12) : 771 - 781
  • [4] Artificial intelligence applied to radiation oncology
    Bibault, J. -E.
    Burgun, A.
    Giraud, P.
    CANCER RADIOTHERAPIE, 2017, 21 (03): : 256 - +
  • [5] Artificial intelligence and radiomics for radiation oncology
    Kocher, Martin
    STRAHLENTHERAPIE UND ONKOLOGIE, 2020, 196 (10) : 847 - 847
  • [6] Artificial intelligence and radiomics for radiation oncology
    Martin Kocher
    Strahlentherapie und Onkologie, 2020, 196 : 847 - 847
  • [7] The Future of Artificial Intelligence in Radiation Oncology
    Thompson, Reid F.
    Valdes, Gilmer
    Fuller, Clifton David
    Carpenter, Colin M.
    Morin, Olivier
    Aneja, Sanjay
    Lindsay, William D.
    Aerts, Hugo J. W. L.
    Agrimson, Barbara
    Deville, Curtiland
    Rosenthal, Seth A.
    Yu, James B.
    Thomas, Charles R., Jr.
    INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2018, 102 (02): : 247 - 248
  • [8] Responsible Artificial Intelligence in Radiation Oncology
    Teng, C. L.
    Bhullar, A. S.
    Jermain, P.
    Jordon, D.
    Nawfel, R.
    Patel, P.
    Sean, R.
    Shang, M.
    Wu, D. H.
    INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2024, 120 (02): : E659 - E659
  • [9] Artificial Intelligence Applications in Radiation Oncology
    Dinapoli, N.
    Lenkowicz, J.
    Masciocchi, C.
    Damiani, A.
    Boldrini, L.
    Cusumano, D.
    Valentini, V.
    RADIOTHERAPY AND ONCOLOGY, 2019, 133 : S1 - S1
  • [10] Artificial Intelligence in Radiation Oncology Imaging
    Thompson, Reid F.
    Valdes, Gilmer
    Fuller, Clifton David
    Carpenter, Colin M.
    Morin, Olivier
    Aneja, Sanjay
    Lindsay, William D.
    Aerts, Hugo J. W. L.
    Agrimson, Barbara
    Deville, Curtiland, Jr.
    Rosenthal, Seth A.
    Yu, James B.
    Thomas, Charles R., Jr.
    INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2018, 102 (04): : 1159 - 1161
12345