Visualising spatial heterogeneity in glioblastoma using imaging habitats
Glioblastoma is a high-grade aggressive neoplasm characterised by significant intra-tumoral spatial heterogeneity. Personalising therapy for this tumour requires non-invasive tools to visualise its heterogeneity to monitor treatment response on a regional level. To date, efforts to characterise glio...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-11-01
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| Series: | Frontiers in Oncology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2022.1037896/full |
| _version_ | 1811186588831449088 |
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| author | Mueez Waqar Mueez Waqar Petra J. Van Houdt Eline Hessen Ka-Loh Li Xiaoping Zhu Alan Jackson Alan Jackson Mudassar Iqbal James O’Connor James O’Connor Ibrahim Djoukhadar Uulke A. van der Heide David J. Coope David J. Coope Gerben R. Borst Gerben R. Borst |
| author_facet | Mueez Waqar Mueez Waqar Petra J. Van Houdt Eline Hessen Ka-Loh Li Xiaoping Zhu Alan Jackson Alan Jackson Mudassar Iqbal James O’Connor James O’Connor Ibrahim Djoukhadar Uulke A. van der Heide David J. Coope David J. Coope Gerben R. Borst Gerben R. Borst |
| author_sort | Mueez Waqar |
| collection | DOAJ |
| description | Glioblastoma is a high-grade aggressive neoplasm characterised by significant intra-tumoral spatial heterogeneity. Personalising therapy for this tumour requires non-invasive tools to visualise its heterogeneity to monitor treatment response on a regional level. To date, efforts to characterise glioblastoma’s imaging features and heterogeneity have focussed on individual imaging biomarkers, or high-throughput radiomic approaches that consider a vast number of imaging variables across the tumour as a whole. Habitat imaging is a novel approach to cancer imaging that identifies tumour regions or ‘habitats’ based on shared imaging characteristics, usually defined using multiple imaging biomarkers. Habitat imaging reflects the evolution of imaging biomarkers and offers spatially preserved assessment of tumour physiological processes such perfusion and cellularity. This allows for regional assessment of treatment response to facilitate personalised therapy. In this review, we explore different methodologies to derive imaging habitats in glioblastoma, strategies to overcome its technical challenges, contrast experiences to other cancers, and describe potential clinical applications. |
| first_indexed | 2024-04-11T13:49:02Z |
| format | Article |
| id | doaj.art-04932a6b6fd0422188ec508b96921eaa |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-04-11T13:49:02Z |
| publishDate | 2022-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj.art-04932a6b6fd0422188ec508b96921eaa2022-12-22T04:20:48ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2022-11-011210.3389/fonc.2022.10378961037896Visualising spatial heterogeneity in glioblastoma using imaging habitatsMueez Waqar0Mueez Waqar1Petra J. Van Houdt2Eline Hessen3Ka-Loh Li4Xiaoping Zhu5Alan Jackson6Alan Jackson7Mudassar Iqbal8James O’Connor9James O’Connor10Ibrahim Djoukhadar11Uulke A. van der Heide12David J. Coope13David J. Coope14Gerben R. Borst15Gerben R. Borst16Department of Neurosurgery, Geoffrey Jefferson Brain Research Centre, Manchester Centre for Clinical Neurosciences, Northern Care Alliance NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, United KingdomDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health and Manchester Cancer Research Centre, University of Manchester, Manchester, United KingdomDepartment of Radiation Oncology, the Netherlands Cancer Institute, Amsterdam, NetherlandsDepartment of Radiation Oncology, the Netherlands Cancer Institute, Amsterdam, NetherlandsDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health and Manchester Cancer Research Centre, University of Manchester, Manchester, United KingdomDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health and Manchester Cancer Research Centre, University of Manchester, Manchester, United KingdomDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health and Manchester Cancer Research Centre, University of Manchester, Manchester, United KingdomDepartment of Neuroradiology, Geoffrey Jefferson Brain Research Centre, Manchester Centre for Clinical Neurosciences, Northern Care Alliance NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, United KingdomDivision of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health and Manchester Cancer Research Centre, University of Manchester, Manchester, United KingdomDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health and Manchester Cancer Research Centre, University of Manchester, Manchester, United KingdomDepartment of Radiology, The Christie NHS Foundation Trust, Manchester, United KingdomDepartment of Neuroradiology, Geoffrey Jefferson Brain Research Centre, Manchester Centre for Clinical Neurosciences, Northern Care Alliance NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, United KingdomDepartment of Radiation Oncology, the Netherlands Cancer Institute, Amsterdam, NetherlandsDepartment of Neurosurgery, Geoffrey Jefferson Brain Research Centre, Manchester Centre for Clinical Neurosciences, Northern Care Alliance NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, United KingdomDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health and Manchester Cancer Research Centre, University of Manchester, Manchester, United KingdomDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health and Manchester Cancer Research Centre, University of Manchester, Manchester, United KingdomDepartment of Clinical Oncology, The Christie NHS Foundation Trust, Manchester, United KingdomGlioblastoma is a high-grade aggressive neoplasm characterised by significant intra-tumoral spatial heterogeneity. Personalising therapy for this tumour requires non-invasive tools to visualise its heterogeneity to monitor treatment response on a regional level. To date, efforts to characterise glioblastoma’s imaging features and heterogeneity have focussed on individual imaging biomarkers, or high-throughput radiomic approaches that consider a vast number of imaging variables across the tumour as a whole. Habitat imaging is a novel approach to cancer imaging that identifies tumour regions or ‘habitats’ based on shared imaging characteristics, usually defined using multiple imaging biomarkers. Habitat imaging reflects the evolution of imaging biomarkers and offers spatially preserved assessment of tumour physiological processes such perfusion and cellularity. This allows for regional assessment of treatment response to facilitate personalised therapy. In this review, we explore different methodologies to derive imaging habitats in glioblastoma, strategies to overcome its technical challenges, contrast experiences to other cancers, and describe potential clinical applications.https://www.frontiersin.org/articles/10.3389/fonc.2022.1037896/fullglioblastomaimagingbiomarkerhabitatsMRIpreoperative |
| spellingShingle | Mueez Waqar Mueez Waqar Petra J. Van Houdt Eline Hessen Ka-Loh Li Xiaoping Zhu Alan Jackson Alan Jackson Mudassar Iqbal James O’Connor James O’Connor Ibrahim Djoukhadar Uulke A. van der Heide David J. Coope David J. Coope Gerben R. Borst Gerben R. Borst Visualising spatial heterogeneity in glioblastoma using imaging habitats Frontiers in Oncology glioblastoma imaging biomarker habitats MRI preoperative |
| title | Visualising spatial heterogeneity in glioblastoma using imaging habitats |
| title_full | Visualising spatial heterogeneity in glioblastoma using imaging habitats |
| title_fullStr | Visualising spatial heterogeneity in glioblastoma using imaging habitats |
| title_full_unstemmed | Visualising spatial heterogeneity in glioblastoma using imaging habitats |
| title_short | Visualising spatial heterogeneity in glioblastoma using imaging habitats |
| title_sort | visualising spatial heterogeneity in glioblastoma using imaging habitats |
| topic | glioblastoma imaging biomarker habitats MRI preoperative |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2022.1037896/full |
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