BIOM-18. MAPPING TUMOR HABITATS IN IDH-WILD TYPE GLIOBLASTOMA: INTEGRATING MR IMAGING, PATHOLOGIC, AND RNA DATA FROM IVY GLIOBLASTOMA ATLAS PROJECT

Abstract BACKGROUND To identify biologic correlates and spatially validate intratumoral subregions (tumor habitat) using diffusion-weighted and dynamic susceptibility contrast-imaging on a comprehensive pathology map of the isocitrate dehydrogenase (IDH)-wild type whole glioblastoma sample using the Ivy Glioblastoma Atlas Project (Ivy GAP). METHODS Complete data of 20 patients with 168 slides of IDH-wild type glioblastoma were obtained from the IvyGAP (http://glioblastoma.alleninstitute.org/). On MRI, tumor habitats were defined using voxel-wise clustering of apparent diffusion coefficient (ADC) and cerebral blood volume (CBV) maps for contrast-enhancing lesion (CEL) and peritumoral non-enhancing lesion (NEL). On pathology slides, normalized areas of leading edge (LE), infiltrating tumor (IT), cellular tumor (CT), hypervascular lesion (CThypervascular), and perinecrotic lesion (CTperinecrotic) were obtained. Gross specimen pictures were co-registered on MRI images for co-localization and correlation between MRI tumor habitats. Pathologic areas were calculated using Pearson’s correlation coefficient. RNA sequencing of 67 RNA-seq samples was assessed using 4 Neftel subtypes and further correlated with pathology. RESULTS Six tumor habitats were correlated: hypervascular, hypovascular cellular, and hypovascular hypocellular habitats for CEL and NEL. CT was strongly correlated with hypovascular cellular habitat in CEL (C2, r = 0.238, p =.005). IT was strongly correlated with hypovascular cellular habitat in NEL (C5, r = 0.294, p =.017). CThypervascular was correlated with hypervascular habitat in NEL (r = 0.195, p =.023). CTperinecrotic was correlated with imaging necrosis (r = 0.199, p =.005). Astrocyte-like subtypes were positively correlated with IT (r = 0.256, p <.001), while mesenchymal-like subtypes were positively correlated with CTperinecrotic area (r = 0.246, p <.001). CONCLUSION Pathologically matched tumor subregions were cellular tumor with hypovascular cellular habitat in CEL and infiltrative tumor with hypovascular cellular habitat in NEL. Identification of the most aggressive tumor portion, and infiltrative tumor portion using non-invasive imaging can be achieved using MRI tumor habitats.

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Journal
Neuro-Oncology
Published
2024-11-01
DOI
https://doi.org/10.1093/neuonc/noae165.0091
Primary Topic
Glioma Diagnosis and Treatment
Type
article
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article

BIOM-18. MAPPING TUMOR HABITATS IN IDH-WILD TYPE GLIOBLASTOMA: INTEGRATING MR IMAGING, PATHOLOGIC, AND RNA DATA FROM IVY GLIOBLASTOMA ATLAS PROJECT

Sang Woo Song, Shinkyo Yoon, Ho‐Su Lee, Ho Sung Kim et al.
Neuro-Oncology
Glioma Diagnosis and Treatment
article

BIOM-18. MAPPING TUMOR HABITATS IN IDH-WILD TYPE GLIOBLASTOMA: INTEGRATING MR IMAGING, PATHOLOGIC, AND RNA DATA FROM IVY GLIOBLASTOMA ATLAS PROJECT

Sang Woo Song, Shinkyo Yoon, Ho‐Su Lee, Ho Sung Kim, Young‐Hoon Kim, Dongjun Lee, Jeong Hoon Kim, Ji Eun Park, Chang Ki Hong
article en

Abstract

Abstract BACKGROUND To identify biologic correlates and spatially validate intratumoral subregions (tumor habitat) using diffusion-weighted and dynamic susceptibility contrast-imaging on a comprehensive pathology map of the isocitrate dehydrogenase (IDH)-wild type whole glioblastoma sample using the Ivy Glioblastoma Atlas Project (Ivy GAP). METHODS Complete data of 20 patients with 168 slides of IDH-wild type glioblastoma were obtained from the IvyGAP (http://glioblastoma.alleninstitute.org/). On MRI, tumor habitats were defined using voxel-wise clustering of apparent diffusion coefficient (ADC) and cerebral blood volume (CBV) maps for contrast-enhancing lesion (CEL) and peritumoral non-enhancing lesion (NEL). On pathology slides, normalized areas of leading edge (LE), infiltrating tumor (IT), cellular tumor (CT), hypervascular lesion (CThypervascular), and perinecrotic lesion (CTperinecrotic) were obtained. Gross specimen pictures were co-registered on MRI images for co-localization and correlation between MRI tumor habitats. Pathologic areas were calculated using Pearson’s correlation coefficient. RNA sequencing of 67 RNA-seq samples was assessed using 4 Neftel subtypes and further correlated with pathology. RESULTS Six tumor habitats were correlated: hypervascular, hypovascular cellular, and hypovascular hypocellular habitats for CEL and NEL. CT was strongly correlated with hypovascular cellular habitat in CEL (C2, r = 0.238, p =.005). IT was strongly correlated with hypovascular cellular habitat in NEL (C5, r = 0.294, p =.017). CThypervascular was correlated with hypervascular habitat in NEL (r = 0.195, p =.023). CTperinecrotic was correlated with imaging necrosis (r = 0.199, p =.005). Astrocyte-like subtypes were positively correlated with IT (r = 0.256, p <.001), while mesenchymal-like subtypes were positively correlated with CTperinecrotic area (r = 0.246, p <.001). CONCLUSION Pathologically matched tumor subregions were cellular tumor with hypovascular cellular habitat in CEL and infiltrative tumor with hypovascular cellular habitat in NEL. Identification of the most aggressive tumor portion, and infiltrative tumor portion using non-invasive imaging can be achieved using MRI tumor habitats.

Neuro-OncologyVol. 26(Supplement_8)
Asan Medical Center (KR)
Life in Land
Openalex Percentile: Top 64%
Glioma Diagnosis and Treatment
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