Reproducibility of Segmentation-based Myocardial Radiomic Features with Cardiac MRI.


Journal

Radiology. Cardiothoracic imaging
ISSN: 2638-6135
Titre abrégé: Radiol Cardiothorac Imaging
Pays: United States
ID NLM: 101748663

Informations de publication

Date de publication:
25 Jun 2020
Historique:
received: 10 10 2019
revised: 19 02 2020
accepted: 04 03 2020
entrez: 1 8 2020
pubmed: 1 8 2020
medline: 1 8 2020
Statut: epublish

Résumé

To investigate reproducibility of myocardial radiomic features with cardiac MRI. Test-retest studies were performed with a 3-T MRI system using commonly used cardiac MRI sequences of cine balanced steady-state free precession (cine bSSFP), T1-weighted and T2-weighted imaging, and quantitative T1 and T2 mapping in phantom experiments and 10 healthy participants (mean ± standard deviation age, 29 years ± 13). In addition, this study assessed repeatability in 51 patients (56 years ± 14) who underwent imaging twice during the same session. Three readers independently delineated the myocardium to investigate inter- and intraobserver reproducibility of radiomic features. A total of 1023 radiomic features were extracted by using PyRadiomics ( Different reproducibility patterns were observed among sequences in in vivo test-retest studies. In cine bSSFP, the gray-level run-length matrix was the most reproducible feature family, and the wavelet low-pass filter applied horizontally and vertically was the most reproducible image filter. In T1 and T2 maps, intensity-based statistics (first-order) and gray-level co-occurrence matrix features were the most reproducible feature families, without a dominant reproducible image filter. Across all sequences, gray-level nonuniformity was the most frequently identified reproducible feature name. In inter- and intraobserver reproducibility studies, respectively, only 32%-47% and 61%-73% of features were identified as reproducible. Only a small subset of myocardial radiomic features was reproducible, and these reproducible radiomic features varied among different sequences.

Identifiants

pubmed: 32734275
doi: 10.1148/ryct.2020190216
pmc: PMC7377242
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e190216

Subventions

Organisme : NHLBI NIH HHS
ID : R01 HL127015
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL129157
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL129185
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL154744
Pays : United States

Commentaires et corrections

Type : CommentIn

Informations de copyright

2020 by the Radiological Society of North America, Inc.

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Auteurs

Jihye Jang (J)

Cardiovascular Division, Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 (J.J., L.H.N., J.M., S.K., J.R., P.P., B.G., R.N.); Department of Computer Science, Technical University of Munich, Munich, Germany (J.J.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Mass (L.H.N.).

Long H Ngo (LH)

Cardiovascular Division, Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 (J.J., L.H.N., J.M., S.K., J.R., P.P., B.G., R.N.); Department of Computer Science, Technical University of Munich, Munich, Germany (J.J.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Mass (L.H.N.).

Jennifer Mancio (J)

Cardiovascular Division, Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 (J.J., L.H.N., J.M., S.K., J.R., P.P., B.G., R.N.); Department of Computer Science, Technical University of Munich, Munich, Germany (J.J.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Mass (L.H.N.).

Selcuk Kucukseymen (S)

Cardiovascular Division, Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 (J.J., L.H.N., J.M., S.K., J.R., P.P., B.G., R.N.); Department of Computer Science, Technical University of Munich, Munich, Germany (J.J.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Mass (L.H.N.).

Jennifer Rodriguez (J)

Cardiovascular Division, Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 (J.J., L.H.N., J.M., S.K., J.R., P.P., B.G., R.N.); Department of Computer Science, Technical University of Munich, Munich, Germany (J.J.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Mass (L.H.N.).

Patrick Pierce (P)

Cardiovascular Division, Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 (J.J., L.H.N., J.M., S.K., J.R., P.P., B.G., R.N.); Department of Computer Science, Technical University of Munich, Munich, Germany (J.J.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Mass (L.H.N.).

Beth Goddu (B)

Cardiovascular Division, Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 (J.J., L.H.N., J.M., S.K., J.R., P.P., B.G., R.N.); Department of Computer Science, Technical University of Munich, Munich, Germany (J.J.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Mass (L.H.N.).

Reza Nezafat (R)

Cardiovascular Division, Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 (J.J., L.H.N., J.M., S.K., J.R., P.P., B.G., R.N.); Department of Computer Science, Technical University of Munich, Munich, Germany (J.J.); and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Mass (L.H.N.).

Classifications MeSH