Radiomics: Extracting more information from medical images using advanced feature analysis

被引:4269
作者
Lambin, Philippe [1 ]
Rios-Velazquez, Emmanuel
Leijenaar, Ralph
Carvalho, Sara
van Stiphout, Ruud G. P. M.
Granton, Patrick
Zegers, Catharina M. L.
Gillies, Robert [2 ]
Boellard, Ronald [3 ]
Dekker, Andre
Aerts, Hugo J. W. L. [4 ]
机构
[1] Maastricht Univ, Maastricht Radiat Oncol MAASTRO, Dept Radiat Oncol MAASTRO, GROW Sch Oncol & Dev Biol,Med Ctr, NL-6200 MD Maastricht, Netherlands
[2] Univ S Florida, Coll Med, H Lee Moffitt Canc Ctr & Res Inst, Tampa, FL 33612 USA
[3] Vrije Univ Amsterdam Med Ctr, Dept Nucl Med & PET Res, Amsterdam, Netherlands
[4] Harvard Univ, Sch Publ Hlth, Computat Biol & Funct Genom Lab, Dept Biostat & Computat Biol,Dana Farber Canc Ins, Cambridge, MA 02138 USA
关键词
Imaging; Radiomics; Tumour; Intra tumour heterogeneity; CELL LUNG-CANCER; POSITRON-EMISSION-TOMOGRAPHY; GENE-EXPRESSION PROGRAMS; PROGNOSTIC VALUE; PET IMAGES; FDG-PET; TUMOR; SURVIVAL; HETEROGENEITY; CARCINOMA;
D O I
10.1016/j.ejca.2011.11.036
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Solid cancers are spatially and temporally heterogeneous. This limits the use of invasive biopsy based molecular assays but gives huge potential for medical imaging, which has the ability to capture intra-tumoural heterogeneity in a non-invasive way. During the past decades, medical imaging innovations with new hardware, new imaging agents and standardised protocols, allows the field to move towards quantitative imaging. Therefore, also the development of automated and reproducible analysis methodologies to extract more information from image-based features is a requirement. Radiomics - the high-throughput extraction of large amounts of image features from radiographic images - addresses this problem and is one of the approaches that hold great promises but need further validation in multi-centric settings and in the laboratory. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:441 / 446
页数:6
相关论文
共 21 条
[1]   Disparity Between In Vivo EGFR Expression and 89Zr-Labeled Cetuximab Uptake Assessed with PET [J].
Aerts, Hugo J. W. L. ;
Dubois, Ludwig ;
Perk, Lars ;
Vermaelen, Peter ;
van Dongen, Guus A. M. S. ;
Wouters, Bradly G. ;
Lambin, Philippe .
JOURNAL OF NUCLEAR MEDICINE, 2009, 50 (01) :123-131
[2]   Primary tumor standardized uptake value (SUVmax) measured on fluorodeoxyglucose positron emission tomography (FDG-PET) is of prognostic value for survival in non-small cell lung cancer (NSCLC) -: A systematic review and meta-analysis (MA) by the European lung cancer working party for the IASLC lung cancer staging project [J].
Berghmans, Thierry ;
Dusart, Michele ;
Paesmans, Marianne ;
Hossein-Foucher, Claude ;
Buvat, Irene ;
Castaigne, Catherine ;
Scherpereel, Arnaud ;
Mascaux, Celine ;
Moreau, Michel ;
Roelandts, Martine ;
Alard, Stphane ;
Meert, Anne-Pascale ;
Patz, Edward F., Jr. ;
Lafitte, Jean-Jacques ;
Sculier, Jean-Paul .
JOURNAL OF THORACIC ONCOLOGY, 2008, 3 (01) :6-12
[3]   The patterns and dynamics of genomic instability in metastatic pancreatic cancer [J].
Campbell, Peter J. ;
Yachida, Shinichi ;
Mudie, Laura J. ;
Stephens, Philip J. ;
Pleasance, Erin D. ;
Stebbings, Lucy A. ;
Morsberger, Laura A. ;
Latimer, Calli ;
McLaren, Stuart ;
Lin, Meng-Lay ;
McBride, David J. ;
Varela, Ignacio ;
Nik-Zainal, Serena A. ;
Leroy, Catherine ;
Jia, Mingming ;
Menzies, Andrew ;
Butler, Adam P. ;
Teague, Jon W. ;
Griffin, Constance A. ;
Burton, John ;
Swerdlow, Harold ;
Quail, Michael A. ;
Stratton, Michael R. ;
Iacobuzio-Donahue, Christine ;
Futreal, P. Andrew .
NATURE, 2010, 467 (7319) :1109-1113
[4]   DEVELOPMENT AND VALIDATION OF A PROGNOSTIC MODEL USING BLOOD BIOMARKER INFORMATION FOR PREDICTION OF SURVIVAL OF NON SMALL-CELL LUNG CANCER PATIENTS TREATED WITH COMBINED CHEMOTHERAPY AND RADIATION OR RADIOTHERAPY ALONE (NCT00181519, NCT00573040, AND NCT00572325) [J].
Dehing-Oberije, Cary ;
Aerts, Hugo ;
Yu, Shipeng ;
De Ruysscher, Dirk ;
Menheere, Paul ;
Hilvo, Mika ;
van der Weide, Hiska ;
Rao, Bharat ;
Lambin, Philippe .
INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2011, 81 (02) :360-368
[5]   Identification of noninvasive imaging surrogates for brain tumor gene-expression modules [J].
Diehn, Maximilian ;
Nardini, Christine ;
Wang, David S. ;
McGovern, Susan ;
Jayaraman, Mahesh ;
Liang, Yu ;
Alclape, Kenneth ;
Cha, Soonmee ;
Kuo, Michael D. .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2008, 105 (13) :5213-5218
[6]   New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1) [J].
Eisenhauer, E. A. ;
Therasse, P. ;
Bogaerts, J. ;
Schwartz, L. H. ;
Sargent, D. ;
Ford, R. ;
Dancey, J. ;
Arbuck, S. ;
Gwyther, S. ;
Mooney, M. ;
Rubinstein, L. ;
Shankar, L. ;
Dodd, L. ;
Kaplan, R. ;
Lacombe, D. ;
Verweij, J. .
EUROPEAN JOURNAL OF CANCER, 2009, 45 (02) :228-247
[7]   Exploring feature-based approaches in PET images for predicting cancer treatment outcomes [J].
El Naqa, I. ;
Grigsby, P. W. ;
Apte, A. ;
Kidd, E. ;
Donnelly, E. ;
Khullar, D. ;
Chaudhari, S. ;
Yang, D. ;
Schmitt, M. ;
Laforest, Richard ;
Thorstad, W. L. ;
Deasy, J. O. .
PATTERN RECOGNITION, 2009, 42 (06) :1162-1171
[8]   Imaging and cancer: A review [J].
Fass, Leonard .
MOLECULAR ONCOLOGY, 2008, 2 (02) :115-152
[9]   Variability of textural features in FDG PET images due to different acquisition modes and reconstruction parameters [J].
Galavis, Paulina E. ;
Hollensen, Christian ;
Jallow, Ngoneh ;
Paliwal, Bhudatt ;
Jeraj, Robert .
ACTA ONCOLOGICA, 2010, 49 (07) :1012-1016
[10]   Magnetic resonance image-guided proteomics of human glioblastoma multiforme [J].
Hobbs, SK ;
Shi, GY ;
Homer, R ;
Harsh, G ;
Atlas, SW ;
Bednarski, MD .
JOURNAL OF MAGNETIC RESONANCE IMAGING, 2003, 18 (05) :530-536