@article {Leithner1611, author = {Doris Leithner and Heiko Sch{\"o}der and Alexander Haug and H. Alberto Vargas and Peter Gibbs and Ida H{\"a}ggstr{\"o}m and Ivo Rausch and Michael Weber and Anton S. Becker and Jazmin Schwartz and Marius E. Mayerhoefer}, title = {Impact of ComBat Harmonization on PET Radiomics-Based Tissue Classification: A Dual-Center PET/MRI and PET/CT Study}, volume = {63}, number = {10}, pages = {1611--1616}, year = {2022}, doi = {10.2967/jnumed.121.263102}, publisher = {Society of Nuclear Medicine}, 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.}, issn = {0161-5505}, URL = {https://jnm.snmjournals.org/content/63/10/1611}, eprint = {https://jnm.snmjournals.org/content/63/10/1611.full.pdf}, journal = {Journal of Nuclear Medicine} }