Impact of ComBat harmonization on PET radiomics-based tissue classification: A dual-center PET/MRI and PET/CT study Journal Article

   

Authors:	Leithner, D.; Schöder, H.; Haug, A.; Vargas, H. A.; Gibbs, P.; Häggström, I.; Rausch, I.; Weber, M.; Becker, A. S.; Schwartz, J.; Mayerhoefer, M. E.
Article Title:	Impact of ComBat harmonization on PET radiomics-based tissue classification: A dual-center PET/MRI and PET/CT study
Abstract:	Our purpose was to determine whether ComBat harmonization improves 18F-FDG PET radiomics-based tissue classification in pooled PET/MRI and PET/CT datasets. Methods: Two hundred patients who had undergone 18F-FDG PET/MRI (2 scanners and vendors; 50 patients each) or PET/CT (2 scanners and vendors; 50 patients each) were retrospectively included. Gray-level histogram, gray-level cooccurrence matrix, gray-level run-length matrix, gray-level size-zone matrix, and neighborhood gray-tone difference matrix radiomic features were calculated for volumes of interest in the disease-free liver, spleen, and bone marrow. For individual feature classes and a multiclass radiomic signature, tissue was classified on ComBat-harmonized and unharmonized pooled data, using a multilayer perceptron neural network. Results: Median accuracies in training and validation datasets were 69.5% and 68.3% (harmonized), respectively, versus 59.5% and 58.9% (unharmonized), respectively, for gray-level histogram; 92.1% and 86.1% (harmonized), respectively, versus 53.6% and 50.0% (unharmonized), respectively, for gray-level cooccurrence matrix; 84.8% and 82.8% (harmonized), respectively, versus 62.4% and 58.3% (unharmonized), respectively, for gray-level run-length matrix; 87.6% and 85.6% (harmonized), respectively, versus 56.2% and 52.8% (unharmonized), respectively, for gray-level size-zone matrix; 79.5% and 77.2% (harmonized), respectively, versus 54.8% and 53.9% (unharmonized), respectively, for neighborhood gray-tone difference matrix; and 86.9% and 84.4% (harmonized), respectively, versus 62.9% and 58.3% (unharmonized), respectively, for radiomic signature. Conclusion: ComBat harmonization may be useful for multicenter 18F-FDG PET radiomics studies using pooled PET/MRI and PET/CT data. © 2022 by the Society of Nuclear Medicine and Molecular Imaging.
Keywords:	retrospective studies; clinical trial; nuclear magnetic resonance imaging; positron emission tomography; magnetic resonance imaging; retrospective study; multicenter study; fluorodeoxyglucose f 18; fluorodeoxyglucose f18; positron-emission tomography; harmonization; pet/mri; humans; human; radiomics; positron emission tomography-computed tomography; positron emission tomography computed tomography
Journal Title:	Journal of Nuclear Medicine
Volume:	63
Issue:	10
ISSN:	0161-5505
Publisher:	Society of Nuclear Medicine
Date Published:	2022-10-01
Start Page:	1611
End Page:	1616
Language:	English
DOI:	10.2967/jnumed.121.263102
PUBMED:	35210300
PROVIDER:	scopus
PMCID:	PMC9536705
DOI/URL:	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139201011&doi=10.2967%2fjnumed.121.263102&partnerID=40&md5=164c0db62eafa845ce434de4f447ba52
Notes:	Article -- Export Date: 1 November 2022 -- Source: Scopus

https://synapse.mskcc.org/synapse/works/has_related_data_chk/199193