Imaging tumor habitats with PET-MRI HYPERDIrect maps to decode the spatial heterogeneity of malignant gliomas
Motivation: Malignant gliomas are characterized by considerable intra-tumor heterogeneity directly related to treatment failure. Habitat imaging allows to visualize in vivo such heterogeneity. Goal(s): Investigating a novel approach based on 3T PET/MRI acquisitions for assessing HYpoxia, PErfusion, DIffusion, and methionine-PET for tissue metabolism in malignant gliomas. Approach: Quantitative data from PET/MRI are combined in a unique HYPERDIrect map to identify discrete radiomic clusters or `habitats', possibly reflecting diverse genetic and biological features, to be proven by image-guided tissue sampling. Results: Preliminary analysis showed high habitat imaging reproducibility and a reliable correlation between the expected microenvironment of the different habitats and the actual histopathological characteristics. Impact: The HYPERDIrect map may represent a tool for decoding pattern of glioma heterogeneity and a new biomarker for stratifying prognosis and selecting patients for personalized approaches.
Authors
- Maria Picchio (ORCID: https://orcid.org/0000-0002-7532-6211)
- Nicolò Pecco (ORCID: https://orcid.org/0000-0002-6367-7903)
- Gianluca Nocera (ORCID: https://orcid.org/0000-0002-8499-5257)
- Michele Bailo (ORCID: https://orcid.org/0000-0003-4151-2873)
- Antonella Castellano (ORCID: https://orcid.org/0000-0002-4137-9016)
- Filippo Gagliardi (ORCID: https://orcid.org/0000-0002-2296-1764)
- Andrea Falini (ORCID: https://orcid.org/0000-0002-1461-8755)
- Federico Fallanca (ORCID: https://orcid.org/0000-0001-7375-520X)
- Paola Scifo (ORCID: https://orcid.org/0000-0001-5135-8086)
- Pietro Mortini (ORCID: https://orcid.org/0000-0003-2320-2281)
- Ilaria Neri (ORCID: https://orcid.org/0000-0002-0235-3454)
- Pasquale Anthony Della Rosa (ORCID: https://orcid.org/0000-0002-3137-1731)
- Marcella Callea (ORCID: https://orcid.org/0000-0003-0890-6651)
Publication Details
- Journal
- Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
- Published
- 2024-11-26
- DOI
- https://doi.org/10.58530/2024/0376
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00