Serial tumor radiomic features predict response of head and neck cancer treated with Radiotherapy

被引：0
|
作者：
Elhalawani, H. E. [1 ]
Mohamed, A. S. R. [1 ]
Volpe, S. [1 ]
Yang, P. [1 ]
Campbell, S. [1 ]
Granberry, R. [1 ]
Ger, R. [1 ]
Fave, X. [1 ]
Zhang, L. [1 ]
Marai, G. E. [2 ]
Vock, D. [3 ]
Canahuate, G. M. [4 ]
Mackin, D. [1 ]
Court, L. [1 ]
Gunn, G. B. [1 ]
Rao, A. [1 ]
Fuller, C. D. [1 ]
机构：
[1] Univ Texas MD Anderson Canc Ctr, Radiat Oncol, Houston, TX 77030 USA
[2] Univ Illinois, Comp Sci, Chicago, IL USA
[3] Univ Minnesota Publ Hlth, Biostat, Minneapolis, MN USA
[4] Univ Iowa, Elect & Comp Engn, Iowa City, IA USA
来源：
RADIOTHERAPY AND ONCOLOGY | 2018年 / 127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-0991
引用
收藏
页码：E551 / E551
页数：1
相关论文
共 50 条
  • [1] Radiomics Features Predict Tumor Volume Change During Head and Neck Cancer Radiotherapy
    Surucu, M.
    Mescioglu, I.
    Cozzi, F.
    Hurst, N.
    Emami, B.
    Roeske, J.
    MEDICAL PHYSICS, 2018, 45 (06) : E464 - E465
  • [2] Machine learning based on ct radiomic features predicts residual tumor in head and neck cancer patients treated with chemoradiotherapy
    Florez E.
    Thomas T.V.
    Howard C.M.
    Khosravi H.R.
    Lirette S.T.
    Fatemi A.
    Biomedical Sciences Instrumentation, 2021, 57 (02) : 199 - 211
  • [3] Pre-treatment radiomic features predict individual nodal failure in head and neck cancer
    Zhai, T.
    Steenbakkers, R. J. H. M.
    Van Dijk, L. V.
    Vemer-van den Hoek, J. G. M.
    Bijl, H. P.
    Dieters, M.
    Noordzij, W.
    Van der Schaaf, A.
    Sijtsema, N. M.
    Langendijk, J. A.
    RADIOTHERAPY AND ONCOLOGY, 2019, 133 : S204 - S204
  • [4] Machine Learning Based On CT Radiomic Features Can Predict Residual Tumor From Radiation Changes in Head and Neck Cancer Patients Treated with Definitive Chemoradiotherapy
    Florez, E.
    Thomas, T.
    Howard, C. M.
    Khosravi, H.
    Storrs, J.
    Lirette, S.
    Fatemi, A.
    MEDICAL PHYSICS, 2020, 47 (06) : E542 - E542
  • [5] Delta-Radiomics Features Predict Response and Outcome in Head and Neck Cancer Patients Treated with Chemoradiation
    Florez, E.
    Thomas, T.
    Lirette, S.
    Fatemi, A.
    MEDICAL PHYSICS, 2019, 46 (06) : E242 - E242
  • [6] Pre-treatment radiomic features predict individual lymph node failure for head and neck cancer patients
    Zhai, Tian-Tian
    Langendijk, Johannes A.
    van Dijk, Lisanne, V
    van Der Schaaf, Arjen
    Sommers, Linda
    Vemer-van Den Hoek, Johanna G. M.
    Bijl, Henk P.
    Halmos, Gyorgy B.
    Witjes, Max J. H.
    Oosting, Sjoukje F.
    Noordzij, Walter
    Sijtsema, Nanna M.
    Steenbakkers, Roel J. H. M.
    RADIOTHERAPY AND ONCOLOGY, 2020, 146 : 58 - 65
  • [7] Significance of Clinical and Radiomic Parameters in Predicting Tumor Volume Change in Head and Neck Radiotherapy
    Surucu, M.
    Cozzi, F.
    Mescioglu, I.
    Block, A. M.
    Emami, B.
    Roeske, J. C.
    INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2019, 105 (01): : E799 - E799
  • [8] Imaging perfusion and hypoxia with pet to predict radiotherapy response in head-and-neck cancer
    Lehtiö, K
    Eskola, O
    Viljanen, T
    Oikonen, V
    Grönroos, T
    Sillanmäki, L
    Grénman, R
    Minn, H
    INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2004, 59 (04): : 971 - 982
  • [9] The Use of Radiomic Features to Predict Human Papillomavirus (HPV) Status in Head and Neck Tumors: A Review
    Glogauer, Judah
    Kohanzadeh, Avraham
    Feit, Avery
    Fournier, Jeffrey E.
    Zians, Avraham
    Somogyi, Dafna Z.
    CUREUS JOURNAL OF MEDICAL SCIENCE, 2023, 15 (08)
  • [10] Tumor response after palliative radiotherapy in head and neck cancer and its influence on survival
    Cruz, M.
    Sousa, C.
    Branco, D.
    Khouri, L.
    Brandao, J.
    Melo, G.
    RADIOTHERAPY AND ONCOLOGY, 2017, 123 : S594 - S595
12345