21-month survival prediction using ensemble machine learning based on [18F]FDG PET/CT derived textural and clinical features in patients with treatment naive pancreas tumors

被引:0
|
作者
Nakuz, Thomas [3 ]
Papp, Laszlo [3 ]
Wadsak, Wolfgang [2 ]
Haug, Alexander [1 ]
Hacker, Marcus [4 ]
Karanikas, Georgios [3 ]
机构
[1] Div Nucl Med, Vienna, Austria
[2] Med Univ Vienna, Vienna, Austria
[3] Med Univ Vienna, Dept Biomed Imaging & Image Guided Therapy, Vienna, Austria
[4] Univ Klin Radiol & Nukl Med, Vienna, Austria
关键词
D O I
暂无
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
390
引用
收藏
页数:2
相关论文
共 46 条
  • [1] Prognosis Prediction of Pancreas Cancer using Textural Analysis Parameters derived from F-18 FDG PET/CT
    So, Min-kyung
    Lee, Won Woo
    Yoo, Min Young
    Yoon, Yoo-Seok
    Cho, Jai Young
    Han, Ho-Seong
    Kim, Sang Eun
    [J]. JOURNAL OF NUCLEAR MEDICINE, 2015, 56 (03)
  • [2] Robustness of radiomic features in supervised machine learning prediction models of survival using varying segmentation methods in [18F]FDG PET/CT in patients with pancreatic and esophageal cancer
    Nakuz, Thomas
    Papp, Laszlo
    Raidl, Markus
    Grahovac, Marko
    Haug, Alexander
    Hacker, Marcus
    Karanikas, Georgios
    [J]. JOURNAL OF NUCLEAR MEDICINE, 2019, 60
  • [3] Exploratory analysis of using supervised machine learning in [18F] FDG PET/CT images to predict treatment response in patients with metastatic and recurrent ENT tumors
    Leisser, A.
    Papp, L.
    Grahovac, M.
    Hacker, M.
    Beyer, T.
    Nejabat, M.
    Haug, A. R.
    [J]. EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, 2018, 45 : S200 - S201
  • [4] Textural and Conventional Pretherapeutic [18F]FDG PET/CT Parameters for Survival Outcome Prediction in Stage III and IV Oropharyngeal Cancer Patients
    Palomino-Fernandez, David
    Milara, Eva
    Galiana, Alvaro
    Sanchez-Ortiz, Miguel
    Seiffert, Alexander P.
    Jimenez-Almonacid, Justino
    Gomez-Grande, Adolfo
    Ruiz-Solis, Sebastian
    Ruiz-Alonso, Ana
    Gomez, Enrique J.
    Tabuenca, Maria Jose
    Sanchez-Gonzalez, Patricia
    [J]. APPLIED SCIENCES-BASEL, 2024, 14 (04):
  • [5] Prediction of survival outcome based on clinical features and pretreatment 18FDG-PET/CT for HNSCC patients
    Ghosh, Sayantani
    Maulik, Shaurav
    Chatterjee, Sanjoy
    Mallick, Indranil
    Chakravorty, Nishant
    Mukherjee, Jayanta
    [J]. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2020, 195
  • [6] 18F‑FDG PET/CT based radiomics features improve prediction of prognosis: multiple machine learning algorithms and multimodality applications for multiple myeloma
    Haoshu Zhong
    Delong Huang
    Junhao Wu
    Xiaomin Chen
    Yue Chen
    Chunlan Huang
    [J]. BMC Medical Imaging, 23
  • [7] Application of a Machine Learning Approach for the Analysis of Clinical and Radiomic Features of Pretreatment [18F]-FDG PET/CT to Predict Prognosis of Patients with Endometrial Cancer
    Masatoyo Nakajo
    Megumi Jinguji
    Atsushi Tani
    Hidehiko Kikuno
    Daisuke Hirahara
    Shinichi Togami
    Hiroaki Kobayashi
    Takashi Yoshiura
    [J]. Molecular Imaging and Biology, 2021, 23 : 756 - 765
  • [8] Application of a Machine Learning Approach for the Analysis of Clinical and Radiomic Features of Pretreatment [18F]-FDG PET/CT to Predict Prognosis of Patients with Endometrial Cancer
    Nakajo, Masatoyo
    Jinguji, Megumi
    Tani, Atsushi
    Kikuno, Hidehiko
    Hirahara, Daisuke
    Togami, Shinichi
    Kobayashi, Hiroaki
    Yoshiura, Takashi
    [J]. MOLECULAR IMAGING AND BIOLOGY, 2021, 23 (05) : 756 - 765
  • [9] The Usefulness of Machine Learning–Based Evaluation of Clinical and Pretreatment [18F]-FDG-PET/CT Radiomic Features for Predicting Prognosis in Hypopharyngeal Cancer
    Masatoyo Nakajo
    Kodai Kawaji
    Hiromi Nagano
    Megumi Jinguji
    Akie Mukai
    Hiroshi Kawabata
    Atsushi Tani
    Daisuke Hirahara
    Masaru Yamashita
    Takashi Yoshiura
    [J]. Molecular Imaging and Biology, 2023, 25 : 303 - 313
  • [10] The Usefulness of Machine Learning-Based Evaluation of Clinical and Pretreatment [18F]-FDG-PET/CT Radiomic Features for Predicting Prognosis in Hypopharyngeal Cancer
    Nakajo, Masatoyo
    Kawaji, Kodai
    Nagano, Hiromi
    Jinguji, Megumi
    Mukai, Akie
    Kawabata, Hiroshi
    Tani, Atsushi
    Hirahara, Daisuke
    Yamashita, Masaru
    Yoshiura, Takashi
    [J]. MOLECULAR IMAGING AND BIOLOGY, 2023, 25 (02) : 303 - 313