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The LUMIERE dataset: Longitudinal Glioblastoma MRI with expert RANO evaluation
Publicly available Glioblastoma (GBM) datasets predominantly include pre-operative Magnetic Resonance Imaging (MRI) or contain few follow-up images for each patient. Access to fully longitudinal datasets is critical to advance the refinement of treatment response assessment. We release a single-cent...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9755255/ https://www.ncbi.nlm.nih.gov/pubmed/36522344 http://dx.doi.org/10.1038/s41597-022-01881-7 |
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author | Suter, Yannick Knecht, Urspeter Valenzuela, Waldo Notter, Michelle Hewer, Ekkehard Schucht, Philippe Wiest, Roland Reyes, Mauricio |
author_facet | Suter, Yannick Knecht, Urspeter Valenzuela, Waldo Notter, Michelle Hewer, Ekkehard Schucht, Philippe Wiest, Roland Reyes, Mauricio |
author_sort | Suter, Yannick |
collection | PubMed |
description | Publicly available Glioblastoma (GBM) datasets predominantly include pre-operative Magnetic Resonance Imaging (MRI) or contain few follow-up images for each patient. Access to fully longitudinal datasets is critical to advance the refinement of treatment response assessment. We release a single-center longitudinal GBM MRI dataset with expert ratings of selected follow-up studies according to the response assessment in neuro-oncology criteria (RANO). The expert rating includes details about the rationale of the ratings. For a subset of patients, we provide pathology information regarding methylation of the O(6)-methylguanine-DNA methyltransferase (MGMT) promoter status and isocitrate dehydrogenase 1 (IDH1), as well as the overall survival time. The data includes T1-weighted pre- and post-contrast, T2-weighted, and fluid-attenuated inversion recovery (FLAIR) MRI. Segmentations from state-of-the-art automated segmentation tools, as well as radiomic features, complement the data. Possible applications of this dataset are radiomics research, the development and validation of automated segmentation methods, and studies on response assessment. This collection includes MRI data of 91 GBM patients with a total of 638 study dates and 2487 images. |
format | Online Article Text |
id | pubmed-9755255 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-97552552022-12-17 The LUMIERE dataset: Longitudinal Glioblastoma MRI with expert RANO evaluation Suter, Yannick Knecht, Urspeter Valenzuela, Waldo Notter, Michelle Hewer, Ekkehard Schucht, Philippe Wiest, Roland Reyes, Mauricio Sci Data Data Descriptor Publicly available Glioblastoma (GBM) datasets predominantly include pre-operative Magnetic Resonance Imaging (MRI) or contain few follow-up images for each patient. Access to fully longitudinal datasets is critical to advance the refinement of treatment response assessment. We release a single-center longitudinal GBM MRI dataset with expert ratings of selected follow-up studies according to the response assessment in neuro-oncology criteria (RANO). The expert rating includes details about the rationale of the ratings. For a subset of patients, we provide pathology information regarding methylation of the O(6)-methylguanine-DNA methyltransferase (MGMT) promoter status and isocitrate dehydrogenase 1 (IDH1), as well as the overall survival time. The data includes T1-weighted pre- and post-contrast, T2-weighted, and fluid-attenuated inversion recovery (FLAIR) MRI. Segmentations from state-of-the-art automated segmentation tools, as well as radiomic features, complement the data. Possible applications of this dataset are radiomics research, the development and validation of automated segmentation methods, and studies on response assessment. This collection includes MRI data of 91 GBM patients with a total of 638 study dates and 2487 images. Nature Publishing Group UK 2022-12-15 /pmc/articles/PMC9755255/ /pubmed/36522344 http://dx.doi.org/10.1038/s41597-022-01881-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Data Descriptor Suter, Yannick Knecht, Urspeter Valenzuela, Waldo Notter, Michelle Hewer, Ekkehard Schucht, Philippe Wiest, Roland Reyes, Mauricio The LUMIERE dataset: Longitudinal Glioblastoma MRI with expert RANO evaluation |
title | The LUMIERE dataset: Longitudinal Glioblastoma MRI with expert RANO evaluation |
title_full | The LUMIERE dataset: Longitudinal Glioblastoma MRI with expert RANO evaluation |
title_fullStr | The LUMIERE dataset: Longitudinal Glioblastoma MRI with expert RANO evaluation |
title_full_unstemmed | The LUMIERE dataset: Longitudinal Glioblastoma MRI with expert RANO evaluation |
title_short | The LUMIERE dataset: Longitudinal Glioblastoma MRI with expert RANO evaluation |
title_sort | lumiere dataset: longitudinal glioblastoma mri with expert rano evaluation |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9755255/ https://www.ncbi.nlm.nih.gov/pubmed/36522344 http://dx.doi.org/10.1038/s41597-022-01881-7 |
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