<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Wu WF</submitter><funding>Ministry of Science and Technology of Taiwan (MOST)</funding><funding>Ditmanson Medical Foundation Chia-Yi Christian Hospital</funding><pagination>1276</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC9409920</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>12(8)</volume><pubmed_abstract>&lt;h4>Background&lt;/h4>While magnetic resonance imaging (MRI) is the imaging modality of choice for the evaluation of patients with brain tumors, it may still be challenging to differentiate glioblastoma multiforme (GBM) from solitary brain metastasis (SBM) due to their similar imaging features. This study aimed to evaluate the features extracted of dual-tree complex wavelet transform (DTCWT) from routine MRI protocol for preoperative differentiation of glioblastoma (GBM) and solitary brain metastasis (SBM).&lt;h4&gt;Methods&lt;/h4>A total of 51 patients were recruited, including 27 GBM and 24 SBM patients. Their contrast-enhanced T1-weighted images (CET1WIs), T2 fluid-attenuated inversion recovery (T2FLAIR) images, diffusion-weighted images (DWIs), and apparent diffusion coefficient (ADC) images were </pubmed_abstract><journal>Journal of personalized medicine</journal><pubmed_title>The Application of DTCWT on MRI-Derived Radiomics for Differentiation of Glioblastoma and Solitary Brain Metastases.</pubmed_title><pmcid>PMC9409920</pmcid><funding_grant_id>109-2113-M-194-010-MY3</funding_grant_id><funding_grant_id>R110-039</funding_grant_id><pubmed_authors>Lin EC</pubmed_authors><pubmed_authors>Shen CW</pubmed_authors><pubmed_authors>Chen YJ</pubmed_authors><pubmed_authors>Lai KM</pubmed_authors><pubmed_authors>Chen CC</pubmed_authors><pubmed_authors>Wu WF</pubmed_authors></additional><is_claimable>false</is_claimable><name>The Application of DTCWT on MRI-Derived Radiomics for Differentiation of Glioblastoma and Solitary Brain Metastases.</name><description>&lt;h4>Background&lt;/h4>While magnetic resonance imaging (MRI) is the imaging modality of choice for the evaluation of patients with brain tumors, it may still be challenging to differentiate glioblastoma multiforme (GBM) from solitary brain metastasis (SBM) due to their similar imaging features. This study aimed to evaluate the features extracted of dual-tree complex wavelet transform (DTCWT) from routine MRI protocol for preoperative differentiation of glioblastoma (GBM) and solitary brain metastasis (SBM).&lt;h4&gt;Methods&lt;/h4>A total of 51 patients were recruited, including 27 GBM and 24 SBM patients. Their contrast-enhanced T1-weighted images (CET1WIs), T2 fluid-attenuated inversion recovery (T2FLAIR) images, diffusion-weighted images (DWIs), and apparent diffusion coefficient (ADC) images were </description><dates><release>2022-01-01T00:00:00Z</release><publication>2022 Aug</publication><modification>2025-05-29T19:22:28.65Z</modification><creation>2025-05-29T19:22:28.65Z</creation></dates><accession>S-EPMC9409920</accession><cross_references><pubmed>36013225</pubmed><doi>10.3390/jpm12081276</doi></cross_references></HashMap>