TY - JOUR
T1 - The image biomarker standardization initiative: Standardized quantitative radiomics for high-throughput image-based phenotyping
AU - Zwanenburg, Alex
AU - Vallières, Martin
AU - Abdalah, Mahmoud A.
AU - Aerts, Hugo J.W.L.
AU - Andrearczyk, Vincent
AU - Apte, Aditya
AU - Ashrafinia, Saeed
AU - Bakas, Spyridon
AU - Beukinga, Roelof J.
AU - Boellaard, Ronald
AU - Bogowicz, Marta
AU - Boldrini, Luca
AU - Buvat, Irène
AU - Cook, Gary J.R.
AU - Davatzikos, Christos
AU - Depeursinge, Adrien
AU - Desseroit, Marie-Charlotte
AU - Dinapoli, Nicola
AU - Dinh, Cuong Viet
AU - Echegaray, Sebastian
AU - El Naqa, Issam
AU - Fedorov, Andriy Y.
AU - Gatta, Roberto
AU - Gillies, Robert J.
AU - Goh, Vicky
AU - Götz, Michael
AU - Guckenberger, Matthias
AU - Ha, Sung Min
AU - Hatt, Mathieu
AU - Isensee, Fabian
AU - Lambin, Philippe
AU - Leger, Stefan
AU - Leijenaar, Ralph T.H.
AU - Lenkowicz, Jacopo
AU - Lippert, Fiona
AU - Losnegård, Are
AU - Maier-Hein, Klaus H.
AU - Morin, Olivier
AU - Müller, Henning
AU - Napel, Sandy
AU - Nioche, Christophe
AU - Orlhac, Fanny
AU - Pati, Sarthak
AU - Pfaehler, Elisabeth A.G.
AU - Rahmim, Arman
AU - Rao, Arvind U.K.
AU - Scherer, Jonas
AU - Siddique, Muhammad Musib
AU - Sijtsema, Nanna M.
AU - Socarras Fernandez, Jairo
AU - Spezi, Emiliano
AU - Steenbakkers, Roel J.H.M.
AU - Tanadini-Lang, Stephanie
AU - Thorwarth, Daniela
AU - Troost, Esther G.C.
AU - Upadhaya, Taman
AU - Valentini, Vincenzo
AU - Van Dijk, Lisanne V.
AU - Van Griethuysen, Joost
AU - Van Velden, Floris H.P.
AU - Whybra, Philip
AU - Richter, Christian
AU - Löck, Steffen
PY - 2020
Y1 - 2020
N2 - Background: Radiomic features may quantify characteristics present in medical imaging. However, the lack of standardized definitions and validated reference values have hampered clinical use. Purpose: To standardize a set of 174 radiomic features. Materials and Methods: Radiomic features were assessed in three phases. In phase I, 487 features were derived from the basic set of 174 features. Twenty-five research teams with unique radiomics software implementations computed feature values directly from a digital phantom, without any additional image processing. In phase II, 15 teams computed values for 1347 derived features using a CT image of a patient with lung cancer and predefined image processing configurations. In both phases, consensus among the teams on the validity of tentative reference values was measured through the frequency of the modal value and classified as follows: less than three matches, weak; three to five matches, moderate; six to nine matches, strong; 10 or more matches, very strong. In the final phase (phase III), a public data set of multimodality images (CT, fluorine 18 fluorodeoxyglucose PET, and T1-weighted MRI) from 51 patients with soft-tissue sarcoma was used to prospectively assess reproducibility of standardized features. Results: Consensus on reference values was initially weak for 232 of 302 features (76.8%) at phase I and 703 of 1075 features (65.4%) at phase II. At the final iteration, weak consensus remained for only two of 487 features (0.4%) at phase I and 19 of 1347 features (1.4%) at phase II. Strong or better consensus was achieved for 463 of 487 features (95.1%) at phase I and 1220 of 1347 features (90.6%) at phase II. Overall, 169 of 174 features were standardized in the first two phases. In the final validation phase (phase III), most of the 169 standardized features could be excellently reproduced (166 with CT; 164 with PET; and 164 with MRI). Conclusion: A set of 169 radiomics features was standardized, which enabled verification and calibration of different radiomics software.
AB - Background: Radiomic features may quantify characteristics present in medical imaging. However, the lack of standardized definitions and validated reference values have hampered clinical use. Purpose: To standardize a set of 174 radiomic features. Materials and Methods: Radiomic features were assessed in three phases. In phase I, 487 features were derived from the basic set of 174 features. Twenty-five research teams with unique radiomics software implementations computed feature values directly from a digital phantom, without any additional image processing. In phase II, 15 teams computed values for 1347 derived features using a CT image of a patient with lung cancer and predefined image processing configurations. In both phases, consensus among the teams on the validity of tentative reference values was measured through the frequency of the modal value and classified as follows: less than three matches, weak; three to five matches, moderate; six to nine matches, strong; 10 or more matches, very strong. In the final phase (phase III), a public data set of multimodality images (CT, fluorine 18 fluorodeoxyglucose PET, and T1-weighted MRI) from 51 patients with soft-tissue sarcoma was used to prospectively assess reproducibility of standardized features. Results: Consensus on reference values was initially weak for 232 of 302 features (76.8%) at phase I and 703 of 1075 features (65.4%) at phase II. At the final iteration, weak consensus remained for only two of 487 features (0.4%) at phase I and 19 of 1347 features (1.4%) at phase II. Strong or better consensus was achieved for 463 of 487 features (95.1%) at phase I and 1220 of 1347 features (90.6%) at phase II. Overall, 169 of 174 features were standardized in the first two phases. In the final validation phase (phase III), most of the 169 standardized features could be excellently reproduced (166 with CT; 164 with PET; and 164 with MRI). Conclusion: A set of 169 radiomics features was standardized, which enabled verification and calibration of different radiomics software.
KW - Biomarkers
KW - Calibration
KW - Fluorodeoxyglucose F18
KW - Humans
KW - Image Processing, Computer-Assisted
KW - Lung Neoplasms
KW - Magnetic Resonance Imaging
KW - Phantoms, Imaging
KW - Phenotype
KW - Positron-Emission Tomography
KW - Radiopharmaceuticals
KW - Reproducibility of Results
KW - Sarcoma
KW - Software
KW - Tomography, X-Ray Computed
KW - Biomarkers
KW - Calibration
KW - Fluorodeoxyglucose F18
KW - Humans
KW - Image Processing, Computer-Assisted
KW - Lung Neoplasms
KW - Magnetic Resonance Imaging
KW - Phantoms, Imaging
KW - Phenotype
KW - Positron-Emission Tomography
KW - Radiopharmaceuticals
KW - Reproducibility of Results
KW - Sarcoma
KW - Software
KW - Tomography, X-Ray Computed
UR - http://hdl.handle.net/10807/207092
U2 - 10.1148/radiol.2020191145
DO - 10.1148/radiol.2020191145
M3 - Article
SN - 0033-8419
VL - 295
SP - 328
EP - 338
JO - Radiology
JF - Radiology
ER -