Prospective Evaluation of Repeatability and Robustness of Radiomic Descriptors in Healthy Brain Tissue Regions In Vivo Across Systematic Variations in T2-Weighted Magnetic Resonance Imaging Acquisition Parameters.


Journal

Journal of magnetic resonance imaging : JMRI
ISSN: 1522-2586
Titre abrégé: J Magn Reson Imaging
Pays: United States
ID NLM: 9105850

Informations de publication

Date de publication:
09 2021
Historique:
revised: 25 03 2021
received: 19 01 2021
accepted: 26 03 2021
pubmed: 17 4 2021
medline: 14 8 2021
entrez: 16 4 2021
Statut: ppublish

Résumé

Radiomic descriptors from magnetic resonance imaging (MRI) are promising for disease diagnosis and characterization but may be sensitive to differences in imaging parameters. To evaluate the repeatability and robustness of radiomic descriptors within healthy brain tissue regions on prospectively acquired MRI scans; in a test-retest setting, under controlled systematic variations of MRI acquisition parameters, and after postprocessing. Prospective. Fifteen healthy participants. A 3.0 T, axial T One hundred and forty-six radiomic descriptors were extracted from a contiguous 2D region of white matter in each scan, before and after postprocessing. Repeatability was assessed in a test/retest setting and between manual and automated annotations for the reference scan. Robustness was evaluated between the reference scan and each group of variant scans (contrast weighting, resolution, and acceleration). Both repeatability and robustness were quantified as the proportion of radiomic descriptors that fell into distinct ranges of the concordance correlation coefficient (CCC): excellent (CCC > 0.85), good (0.7 ≤ CCC ≤ 0.85), moderate (0.5 ≤ CCC < 0.7), and poor (CCC < 0.5); for unprocessed and postprocessed scans separately. Good to excellent repeatability was observed for 52% of radiomic descriptors between test/retest scans and 48% of descriptors between automated vs. manual annotations, respectively. Contrast weighting (TR/TE) changes were associated with the largest proportion of highly robust radiomic descriptors (21%, after processing). Image resolution changes resulted in the largest proportion of poorly robust radiomic descriptors (97%, before postprocessing). Postprocessing of images with only resolution/acceleration differences resulted in 73% of radiomic descriptors showing poor robustness. Many radiomic descriptors appear to be nonrobust across variations in MR contrast weighting, resolution, and acceleration, as well in test-retest settings, depending on feature formulation and postprocessing. 2 TECHNICAL EFFICACY: Stage 2.

Sections du résumé

BACKGROUND
Radiomic descriptors from magnetic resonance imaging (MRI) are promising for disease diagnosis and characterization but may be sensitive to differences in imaging parameters.
OBJECTIVE
To evaluate the repeatability and robustness of radiomic descriptors within healthy brain tissue regions on prospectively acquired MRI scans; in a test-retest setting, under controlled systematic variations of MRI acquisition parameters, and after postprocessing.
STUDY TYPE
Prospective.
SUBJECTS
Fifteen healthy participants.
FIELD STRENGTH/SEQUENCE
A 3.0 T, axial T
ASSESSMENT
One hundred and forty-six radiomic descriptors were extracted from a contiguous 2D region of white matter in each scan, before and after postprocessing.
STATISTICAL TESTS
Repeatability was assessed in a test/retest setting and between manual and automated annotations for the reference scan. Robustness was evaluated between the reference scan and each group of variant scans (contrast weighting, resolution, and acceleration). Both repeatability and robustness were quantified as the proportion of radiomic descriptors that fell into distinct ranges of the concordance correlation coefficient (CCC): excellent (CCC > 0.85), good (0.7 ≤ CCC ≤ 0.85), moderate (0.5 ≤ CCC < 0.7), and poor (CCC < 0.5); for unprocessed and postprocessed scans separately.
RESULTS
Good to excellent repeatability was observed for 52% of radiomic descriptors between test/retest scans and 48% of descriptors between automated vs. manual annotations, respectively. Contrast weighting (TR/TE) changes were associated with the largest proportion of highly robust radiomic descriptors (21%, after processing). Image resolution changes resulted in the largest proportion of poorly robust radiomic descriptors (97%, before postprocessing). Postprocessing of images with only resolution/acceleration differences resulted in 73% of radiomic descriptors showing poor robustness.
DATA CONCLUSIONS
Many radiomic descriptors appear to be nonrobust across variations in MR contrast weighting, resolution, and acceleration, as well in test-retest settings, depending on feature formulation and postprocessing.
EVIDENCE LEVEL
2 TECHNICAL EFFICACY: Stage 2.

Identifiants

pubmed: 33860966
doi: 10.1002/jmri.27635
pmc: PMC8376104
mid: NIHMS1711002
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

1009-1021

Subventions

Organisme : NCI NIH HHS
ID : 1U01CA239055-01
Pays : United States
Organisme : Biomedical Laboratory Research and Development, VA Office of Research and Development
ID : NCI R01CA249992-01A1
Organisme : NCI NIH HHS
ID : 1U01CA248226-01
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL094557
Pays : United States
Organisme : NCI NIH HHS
ID : U24 CA199374
Pays : United States
Organisme : NIAMS NIH HHS
ID : T32 AR007505
Pays : United States
Organisme : Biomedical Laboratory Research and Development, VA Office of Research and Development
ID : IBX004121A
Organisme : NIBIB NIH HHS
ID : R43 EB028736
Pays : United States
Organisme : NCRR NIH HHS
ID : 1C06RR12463-01
Pays : United States
Organisme : V Foundation for Cancer Research
ID : Translational Research Award
Organisme : Dana Foundation
ID : David Mahoney Neuroimaging Program
Organisme : Case Western Reserve University
ID : the Wallace H. Coulter Foundation Program
Organisme : NCATS NIH HHS
ID : UL1 TR002548
Pays : United States
Organisme : NIBIB NIH HHS
ID : 1R43EB028736-01
Pays : United States
Organisme : NCI NIH HHS
ID : R01CA216579-01A1
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA216579
Pays : United States
Organisme : NCI NIH HHS
ID : R01CA220581-01A1
Pays : United States
Organisme : Johnson and Johnson
ID : WiSTEM2D Award
Organisme : NCI NIH HHS
ID : 1U24CA199374-01
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA202752
Pays : United States
Organisme : Congressionally Directed Medical Research Programs
ID : W81XWH-18-1-0440
Organisme : NCI NIH HHS
ID : R01 CA208236
Pays : United States
Organisme : Congressionally Directed Medical Research Programs
ID : W81XWH-19-1-0668
Organisme : NIDDK NIH HHS
ID : U2C DK114886
Pays : United States
Organisme : NIAMS NIH HHS
ID : 5T32AR007505-32
Pays : United States
Organisme : NCI NIH HHS
ID : R01CA208236-01A1
Pays : United States
Organisme : Kidney Precision Medicine Project (KPMP) Glue Grant
Organisme : NCRR NIH HHS
ID : C06 RR012463
Pays : United States
Organisme : NHLBI NIH HHS
ID : 1R01HL151277-01A1
Pays : United States
Organisme : Congressionally Directed Medical Research Programs
ID : W81XWH-20-1-0851
Organisme : Congressionally Directed Medical Research Programs
ID : W81XWH-18-1-0404
Organisme : NCI NIH HHS
ID : 1U54CA254566-01
Pays : United States
Organisme : NCI NIH HHS
ID : R01CA249992-01A1
Pays : United States
Organisme : BLRD VA
ID : I01 BX004121
Pays : United States
Organisme : NCI NIH HHS
ID : U01 CA248226
Pays : United States
Organisme : the Ohio Third Frontier Technology Validation Fund
Organisme : Congressionally Directed Medical Research Programs
ID : W81XWH-15-1-0558
Organisme : NCI NIH HHS
ID : U54 CA254566
Pays : United States
Organisme : NHLBI NIH HHS
ID : 2R01HL094557-06
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL153034
Pays : United States
Organisme : Congressionally Directed Medical Research Programs
ID : W81XWH-16-1-0329
Organisme : NCI NIH HHS
ID : U01 CA239055
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1TR0002548
Pays : United States
Organisme : NCI NIH HHS
ID : R01CA202752-01A1
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL151277
Pays : United States
Organisme : Congressionally Directed Medical Research Programs
ID : W81XWH-20-1-0595
Organisme : Division of Chemical, Bioengineering, Environmental, and Transport Systems
ID : 1553441
Organisme : NCI NIH HHS
ID : R01 CA220581
Pays : United States
Organisme : NIBIB NIH HHS
ID : 5T32EB00750912
Pays : United States
Organisme : NIBIB NIH HHS
ID : R21 EB030208
Pays : United States

Informations de copyright

© 2021 International Society for Magnetic Resonance in Medicine.

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Auteurs

Brendan Eck (B)

Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.
Imaging Institute, Cleveland Clinic, Cleveland, Ohio, USA.

Prathyush V Chirra (PV)

Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.

Avani Muchhala (A)

Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.

Sophia Hall (S)

Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.

Kaustav Bera (K)

Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.

Pallavi Tiwari (P)

Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.

Anant Madabhushi (A)

Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.
Louis Stokes VA Medical Center, Cleveland, Ohio, USA.

Nicole Seiberlich (N)

Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.
Michigan Institute for Imaging Technology and Translation, Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA.

Satish E Viswanath (SE)

Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.

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