Multiparameter MRI Predictors of Long-Term Survival in Glioblastoma Multiforme

Olya Stringfield, John A. Arrington, Sandra K. Johnston, Nicolas G. Rognin, Noah C. Peeri, Yoganand Balagurunathan, Pamela R. Jackson, Kamala R. Clark-Swanson, Kristin Swanson, Kathleen M. Egan, Robert A. Gatenby, Natarajan Raghunand

Research output: Contribution to journalArticle

Abstract

Standard-of-care multiparameter magnetic resonance imaging (MRI) scans of the brain were used to objectively subdivide glioblastoma multiforme (GBM) tumors into regions that correspond to variations in blood flow, interstitial edema, and cellular density. We hypothesized that the distribution of these distinct tumor ecological "habitats" at the time of presentation will impact the course of the disease. We retrospectively analyzed initial MRI scans in 2 groups of patients diagnosed with GBM, a long-term survival group comprising subjects who survived >36 month postdiagnosis, and a short-term survival group comprising subjects who survived ≤19 month postdiagnosis. The single-institution discovery cohort contained 22 subjects in each group, while the multi-institution validation cohort contained 15 subjects per group. MRI voxel intensities were calibrated, and tumor voxels clustered on contrast-enhanced T1-weighted and fluid-attenuated inversion-recovery (FLAIR) images into 6 distinct "habitats" based on low- to medium- to high-contrast enhancement and low-high signal on FLAIR scans. Habitat 6 (high signal on calibrated contrast-enhanced T1-weighted and FLAIR sequences) comprised a significantly higher volume fraction of tumors in the long-term survival group (discovery cohort, 35% ± 6.5%; validation cohort, 34% ± 4.8%) compared with tumors in the short-term survival group (discovery cohort, 17% ± 4.5%, P < .03; validation cohort, 16 ± 4.0%, P < .007). Of the 6 distinct MRI-defined habitats, the fractional tumor volume of habitat 6 at diagnosis was significantly predictive of long- or short-term survival. We discuss a possible mechanistic basis for this association and implications for habitat-driven adaptive therapy of GBM.

Original languageEnglish (US)
Pages (from-to)135-144
Number of pages10
JournalTomography (Ann Arbor, Mich.)
Volume5
Issue number1
DOIs
StatePublished - Mar 1 2019

Fingerprint

Glioblastoma
Ecosystem
Magnetic Resonance Imaging
Survival
Tumor Burden
Neoplasms
Sequence Inversion
Standard of Care
Edema
Brain

Keywords

  • cancer evolution
  • glioblastoma
  • habitats
  • MRI
  • survival

Cite this

Stringfield, O., Arrington, J. A., Johnston, S. K., Rognin, N. G., Peeri, N. C., Balagurunathan, Y., ... Raghunand, N. (2019). Multiparameter MRI Predictors of Long-Term Survival in Glioblastoma Multiforme. Tomography (Ann Arbor, Mich.), 5(1), 135-144. https://doi.org/10.18383/j.tom.2018.00052

Multiparameter MRI Predictors of Long-Term Survival in Glioblastoma Multiforme. / Stringfield, Olya; Arrington, John A.; Johnston, Sandra K.; Rognin, Nicolas G.; Peeri, Noah C.; Balagurunathan, Yoganand; Jackson, Pamela R.; Clark-Swanson, Kamala R.; Swanson, Kristin; Egan, Kathleen M.; Gatenby, Robert A.; Raghunand, Natarajan.

In: Tomography (Ann Arbor, Mich.), Vol. 5, No. 1, 01.03.2019, p. 135-144.

Research output: Contribution to journalArticle

Stringfield, O, Arrington, JA, Johnston, SK, Rognin, NG, Peeri, NC, Balagurunathan, Y, Jackson, PR, Clark-Swanson, KR, Swanson, K, Egan, KM, Gatenby, RA & Raghunand, N 2019, 'Multiparameter MRI Predictors of Long-Term Survival in Glioblastoma Multiforme', Tomography (Ann Arbor, Mich.), vol. 5, no. 1, pp. 135-144. https://doi.org/10.18383/j.tom.2018.00052
Stringfield O, Arrington JA, Johnston SK, Rognin NG, Peeri NC, Balagurunathan Y et al. Multiparameter MRI Predictors of Long-Term Survival in Glioblastoma Multiforme. Tomography (Ann Arbor, Mich.). 2019 Mar 1;5(1):135-144. https://doi.org/10.18383/j.tom.2018.00052
Stringfield, Olya ; Arrington, John A. ; Johnston, Sandra K. ; Rognin, Nicolas G. ; Peeri, Noah C. ; Balagurunathan, Yoganand ; Jackson, Pamela R. ; Clark-Swanson, Kamala R. ; Swanson, Kristin ; Egan, Kathleen M. ; Gatenby, Robert A. ; Raghunand, Natarajan. / Multiparameter MRI Predictors of Long-Term Survival in Glioblastoma Multiforme. In: Tomography (Ann Arbor, Mich.). 2019 ; Vol. 5, No. 1. pp. 135-144.
@article{6d5bea6313d94c6db80fea7f77d447ad,
title = "Multiparameter MRI Predictors of Long-Term Survival in Glioblastoma Multiforme",
abstract = "Standard-of-care multiparameter magnetic resonance imaging (MRI) scans of the brain were used to objectively subdivide glioblastoma multiforme (GBM) tumors into regions that correspond to variations in blood flow, interstitial edema, and cellular density. We hypothesized that the distribution of these distinct tumor ecological {"}habitats{"} at the time of presentation will impact the course of the disease. We retrospectively analyzed initial MRI scans in 2 groups of patients diagnosed with GBM, a long-term survival group comprising subjects who survived >36 month postdiagnosis, and a short-term survival group comprising subjects who survived ≤19 month postdiagnosis. The single-institution discovery cohort contained 22 subjects in each group, while the multi-institution validation cohort contained 15 subjects per group. MRI voxel intensities were calibrated, and tumor voxels clustered on contrast-enhanced T1-weighted and fluid-attenuated inversion-recovery (FLAIR) images into 6 distinct {"}habitats{"} based on low- to medium- to high-contrast enhancement and low-high signal on FLAIR scans. Habitat 6 (high signal on calibrated contrast-enhanced T1-weighted and FLAIR sequences) comprised a significantly higher volume fraction of tumors in the long-term survival group (discovery cohort, 35{\%} ± 6.5{\%}; validation cohort, 34{\%} ± 4.8{\%}) compared with tumors in the short-term survival group (discovery cohort, 17{\%} ± 4.5{\%}, P < .03; validation cohort, 16 ± 4.0{\%}, P < .007). Of the 6 distinct MRI-defined habitats, the fractional tumor volume of habitat 6 at diagnosis was significantly predictive of long- or short-term survival. We discuss a possible mechanistic basis for this association and implications for habitat-driven adaptive therapy of GBM.",
keywords = "cancer evolution, glioblastoma, habitats, MRI, survival",
author = "Olya Stringfield and Arrington, {John A.} and Johnston, {Sandra K.} and Rognin, {Nicolas G.} and Peeri, {Noah C.} and Yoganand Balagurunathan and Jackson, {Pamela R.} and Clark-Swanson, {Kamala R.} and Kristin Swanson and Egan, {Kathleen M.} and Gatenby, {Robert A.} and Natarajan Raghunand",
year = "2019",
month = "3",
day = "1",
doi = "10.18383/j.tom.2018.00052",
language = "English (US)",
volume = "5",
pages = "135--144",
journal = "Tomography (Ann Arbor, Mich.)",
issn = "2379-1381",
publisher = "Grapho Publications LLC",
number = "1",

}

TY - JOUR

T1 - Multiparameter MRI Predictors of Long-Term Survival in Glioblastoma Multiforme

AU - Stringfield, Olya

AU - Arrington, John A.

AU - Johnston, Sandra K.

AU - Rognin, Nicolas G.

AU - Peeri, Noah C.

AU - Balagurunathan, Yoganand

AU - Jackson, Pamela R.

AU - Clark-Swanson, Kamala R.

AU - Swanson, Kristin

AU - Egan, Kathleen M.

AU - Gatenby, Robert A.

AU - Raghunand, Natarajan

PY - 2019/3/1

Y1 - 2019/3/1

N2 - Standard-of-care multiparameter magnetic resonance imaging (MRI) scans of the brain were used to objectively subdivide glioblastoma multiforme (GBM) tumors into regions that correspond to variations in blood flow, interstitial edema, and cellular density. We hypothesized that the distribution of these distinct tumor ecological "habitats" at the time of presentation will impact the course of the disease. We retrospectively analyzed initial MRI scans in 2 groups of patients diagnosed with GBM, a long-term survival group comprising subjects who survived >36 month postdiagnosis, and a short-term survival group comprising subjects who survived ≤19 month postdiagnosis. The single-institution discovery cohort contained 22 subjects in each group, while the multi-institution validation cohort contained 15 subjects per group. MRI voxel intensities were calibrated, and tumor voxels clustered on contrast-enhanced T1-weighted and fluid-attenuated inversion-recovery (FLAIR) images into 6 distinct "habitats" based on low- to medium- to high-contrast enhancement and low-high signal on FLAIR scans. Habitat 6 (high signal on calibrated contrast-enhanced T1-weighted and FLAIR sequences) comprised a significantly higher volume fraction of tumors in the long-term survival group (discovery cohort, 35% ± 6.5%; validation cohort, 34% ± 4.8%) compared with tumors in the short-term survival group (discovery cohort, 17% ± 4.5%, P < .03; validation cohort, 16 ± 4.0%, P < .007). Of the 6 distinct MRI-defined habitats, the fractional tumor volume of habitat 6 at diagnosis was significantly predictive of long- or short-term survival. We discuss a possible mechanistic basis for this association and implications for habitat-driven adaptive therapy of GBM.

AB - Standard-of-care multiparameter magnetic resonance imaging (MRI) scans of the brain were used to objectively subdivide glioblastoma multiforme (GBM) tumors into regions that correspond to variations in blood flow, interstitial edema, and cellular density. We hypothesized that the distribution of these distinct tumor ecological "habitats" at the time of presentation will impact the course of the disease. We retrospectively analyzed initial MRI scans in 2 groups of patients diagnosed with GBM, a long-term survival group comprising subjects who survived >36 month postdiagnosis, and a short-term survival group comprising subjects who survived ≤19 month postdiagnosis. The single-institution discovery cohort contained 22 subjects in each group, while the multi-institution validation cohort contained 15 subjects per group. MRI voxel intensities were calibrated, and tumor voxels clustered on contrast-enhanced T1-weighted and fluid-attenuated inversion-recovery (FLAIR) images into 6 distinct "habitats" based on low- to medium- to high-contrast enhancement and low-high signal on FLAIR scans. Habitat 6 (high signal on calibrated contrast-enhanced T1-weighted and FLAIR sequences) comprised a significantly higher volume fraction of tumors in the long-term survival group (discovery cohort, 35% ± 6.5%; validation cohort, 34% ± 4.8%) compared with tumors in the short-term survival group (discovery cohort, 17% ± 4.5%, P < .03; validation cohort, 16 ± 4.0%, P < .007). Of the 6 distinct MRI-defined habitats, the fractional tumor volume of habitat 6 at diagnosis was significantly predictive of long- or short-term survival. We discuss a possible mechanistic basis for this association and implications for habitat-driven adaptive therapy of GBM.

KW - cancer evolution

KW - glioblastoma

KW - habitats

KW - MRI

KW - survival

UR - http://www.scopus.com/inward/record.url?scp=85071579408&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85071579408&partnerID=8YFLogxK

U2 - 10.18383/j.tom.2018.00052

DO - 10.18383/j.tom.2018.00052

M3 - Article

C2 - 30854451

AN - SCOPUS:85071579408

VL - 5

SP - 135

EP - 144

JO - Tomography (Ann Arbor, Mich.)

JF - Tomography (Ann Arbor, Mich.)

SN - 2379-1381

IS - 1

ER -