Quantification and visualization of lipid landscape in glioma using in -and opposed-phase imaging
Objectives: This study maps the lipid distributions based on magnetic resonance imaging (MRI) in-and opposed-phase (IOP) sequence and correlates the findings generated from lipid map to histological grading of glioma. Methods: Forty histologically proven glioma patients underwent a standard MRI tumo...
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| Format: | Article |
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Elsevier
2018
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| author | Seow, Poh Choo Narayanan, Vairavan Hernowo, Aditya Tri Wong, Jeannie Hsiu Ding Ramli, Norlisah |
| author_facet | Seow, Poh Choo Narayanan, Vairavan Hernowo, Aditya Tri Wong, Jeannie Hsiu Ding Ramli, Norlisah |
| author_sort | Seow, Poh Choo |
| collection | UM |
| description | Objectives: This study maps the lipid distributions based on magnetic resonance imaging (MRI) in-and opposed-phase (IOP) sequence and correlates the findings generated from lipid map to histological grading of glioma. Methods: Forty histologically proven glioma patients underwent a standard MRI tumour protocol with the addition of IOP sequence. The regions of tumour (solid enhancing, solid non-enhancing, and cystic regions) were delineated using snake model (ITK-SNAP) with reference to structural and diffusion MRI images. The lipid distribution map was constructed based on signal loss ratio (SLR) obtained from the IOP imaging. The mean SLR values of the regions were computed and compared across the different glioma grades. Results: The solid enhancing region of glioma had the highest SLR for both Grade II and III. The mean SLR of solid non-enhancing region of tumour demonstrated statistically significant difference between the WHO grades (grades II, III & IV) (mean SLRII = 0.04, mean SLRIII = 0.06, mean SLRIV = 0.08, & p <.01). A strong positive correlation was seen between WHO grades with mean SLR on lipid map of solid non-enhancing (ρ=0.68, p <.01). Conclusion: Lipid quantification via lipid map provides useful information on lipid landscape in tumour heterogeneity characterisation of glioma. This technique adds to the surgical diagnostic yield by identifying biopsy targets. It can also be used as an adjunct grading tool for glioma as well as to provide information about lipidomics landscape in glioma development. |
| first_indexed | 2024-03-06T05:52:09Z |
| format | Article |
| id | um.eprints-20740 |
| institution | Universiti Malaya |
| last_indexed | 2024-03-06T05:52:09Z |
| publishDate | 2018 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | um.eprints-207402019-03-19T02:30:50Z http://eprints.um.edu.my/20740/ Quantification and visualization of lipid landscape in glioma using in -and opposed-phase imaging Seow, Poh Choo Narayanan, Vairavan Hernowo, Aditya Tri Wong, Jeannie Hsiu Ding Ramli, Norlisah R Medicine Objectives: This study maps the lipid distributions based on magnetic resonance imaging (MRI) in-and opposed-phase (IOP) sequence and correlates the findings generated from lipid map to histological grading of glioma. Methods: Forty histologically proven glioma patients underwent a standard MRI tumour protocol with the addition of IOP sequence. The regions of tumour (solid enhancing, solid non-enhancing, and cystic regions) were delineated using snake model (ITK-SNAP) with reference to structural and diffusion MRI images. The lipid distribution map was constructed based on signal loss ratio (SLR) obtained from the IOP imaging. The mean SLR values of the regions were computed and compared across the different glioma grades. Results: The solid enhancing region of glioma had the highest SLR for both Grade II and III. The mean SLR of solid non-enhancing region of tumour demonstrated statistically significant difference between the WHO grades (grades II, III & IV) (mean SLRII = 0.04, mean SLRIII = 0.06, mean SLRIV = 0.08, & p <.01). A strong positive correlation was seen between WHO grades with mean SLR on lipid map of solid non-enhancing (ρ=0.68, p <.01). Conclusion: Lipid quantification via lipid map provides useful information on lipid landscape in tumour heterogeneity characterisation of glioma. This technique adds to the surgical diagnostic yield by identifying biopsy targets. It can also be used as an adjunct grading tool for glioma as well as to provide information about lipidomics landscape in glioma development. Elsevier 2018 Article PeerReviewed Seow, Poh Choo and Narayanan, Vairavan and Hernowo, Aditya Tri and Wong, Jeannie Hsiu Ding and Ramli, Norlisah (2018) Quantification and visualization of lipid landscape in glioma using in -and opposed-phase imaging. NeuroImage: Clinical, 20. pp. 531-536. ISSN 2213-1582, DOI https://doi.org/10.1016/j.nicl.2018.08.003 <https://doi.org/10.1016/j.nicl.2018.08.003>. https://doi.org/10.1016/j.nicl.2018.08.003 doi:10.1016/j.nicl.2018.08.003 |
| spellingShingle | R Medicine Seow, Poh Choo Narayanan, Vairavan Hernowo, Aditya Tri Wong, Jeannie Hsiu Ding Ramli, Norlisah Quantification and visualization of lipid landscape in glioma using in -and opposed-phase imaging |
| title | Quantification and visualization of lipid landscape in glioma using in -and opposed-phase imaging |
| title_full | Quantification and visualization of lipid landscape in glioma using in -and opposed-phase imaging |
| title_fullStr | Quantification and visualization of lipid landscape in glioma using in -and opposed-phase imaging |
| title_full_unstemmed | Quantification and visualization of lipid landscape in glioma using in -and opposed-phase imaging |
| title_short | Quantification and visualization of lipid landscape in glioma using in -and opposed-phase imaging |
| title_sort | quantification and visualization of lipid landscape in glioma using in and opposed phase imaging |
| topic | R Medicine |
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