Predicting doses to organs-at-risk in prostate cancer intensity modulated radiotherapy

被引：0
|
作者：
Mallick, I. [1 ]
Saha, S. [1 ]
Arunsingh, M. [1 ]
Sarkar, A. [2 ]
Adhya, D. Guha [3 ]
Achari, R. [1 ]
机构：
[1] Tata Med Ctr, Dept Radiat Oncol, Kolkata, India
[2] Indian Inst Technol, Dept Mech Engn, Varanasi, Uttar Pradesh, India
[3] Indian Inst Technol, Sch Med Sci & Technol, Kharagpur, W Bengal, India
来源：
RADIOTHERAPY AND ONCOLOGY | 2020年 / 152卷
关键词：
D O I：
暂无
中图分类号：
R73 [肿瘤学];
学科分类号：
100214 ;
摘要：
PO-1575
引用
收藏
页码：S854 / S854
页数：1
相关论文
共 50 条
  • [31] Managed Care and the Diffusion of Intensity-modulated Radiotherapy for Prostate Cancer
    Jacobs, Bruce L.
    Zhang, Yun
    Skolarus, Ted A.
    Wei, John T.
    Montie, James E.
    Schroeck, Florian R.
    Hollenbeck, Brent K.
    UROLOGY, 2012, 80 (06) : 1236 - 1242
  • [32] Acute toxicity of hypofractionated intensity-modulated radiotherapy for prostate cancer
    Drodge, C. S.
    Boychak, O.
    Patel, S.
    Usmani, N.
    Amanie, J.
    Parliament, M. B.
    Murtha, A.
    Field, C.
    Ghosh, S.
    Pervez, N.
    Current Oncology, 2015, 22 (02) : E76 - E84
  • [33] Inverse planning and intensity-modulated radiotherapy in patients with prostate cancer
    Debus, J
    Zierhut, D
    Didinger, B
    Schlegel, W
    Wannenmacher, M
    CONTROVERSIES IN URO-ONCOLOGY, 2002, 36 : 25 - 34
  • [34] Conventional versus hypofractionated intensity-modulated radiotherapy for Prostate cancer
    Pahl, R.
    STRAHLENTHERAPIE UND ONKOLOGIE, 2012, 188 (09) : 841 - 842
  • [35] Image-guided intensity-modulated radiotherapy of prostate cancer
    Rudat, Volker
    Nour, A.
    Hammoud, M.
    Alaradi, A.
    Mohammed, A.
    STRAHLENTHERAPIE UND ONKOLOGIE, 2016, 192 (02) : 109 - 117
  • [36] Clinical implementation of MRI-based organs-at-risk auto-segmentation with convolutional networks for prostate radiotherapy
    Mark H. F. Savenije
    Matteo Maspero
    Gonda G. Sikkes
    Jochem R. N. van der Voort van Zyp
    Alexis N. T. J. Kotte
    Gijsbert H. Bol
    Cornelis A. T. van den Berg
    Radiation Oncology, 15
  • [37] A Deep-Learning-Based Model for Predicting Dose Volume Histograms of Organs-At-Risk in Radiotherapy Treatment Plans
    Liu, Z.
    Chen, X.
    Men, K.
    Yi, J.
    Dai, J.
    MEDICAL PHYSICS, 2020, 47 (06) : E446 - E446
  • [38] Artificial intelligence contouring in radiotherapy for organs-at-risk and lymph node areas
    Meyer, Celine
    Huger, Sandrine
    Bruand, Marie
    Leroy, Thomas
    Palisson, Jeremy
    Retif, Paul
    Sarrade, Thomas
    Barateau, Anais
    Renard, Sophie
    Jolnerovski, Maria
    Demogeot, Nicolas
    Marcel, Johann
    Martz, Nicolas
    Stefani, Anais
    Sellami, Selima
    Jacques, Juliette
    Agnoux, Emma
    Gehin, William
    Trampetti, Ida
    Margulies, Agathe
    Golfier, Constance
    Khattabi, Yassir
    Olivier, Cravereau
    Alizee, Renan
    Py, Jean-Francois
    Faivre, Jean-Christophe
    RADIATION ONCOLOGY, 2024, 19 (01)
  • [39] Assessment of the Second Cancer Risk after Prostate Cancer Treatment: Comparison of 3D Conformal Radiotherapy and Intensity Modulated Radiotherapy
    Hassana I.M.
    Attalla E.M.
    El-Gohary M.I.
    Iranian Journal of Medical Physics, 2022, 19 (04) : 222 - 233
  • [40] Stochastic Frontier Analysis to predict sparing of organs-at-risk for VMAT-treated prostate cancer
    Kroshko, A.
    Morin, O.
    Archambault, L.
    RADIOTHERAPY AND ONCOLOGY, 2019, 133 : S510 - S510
12345