Volumetric assessment of glioblastoma and its predictive value for survival.


Journal

Acta neurochirurgica
ISSN: 0942-0940
Titre abrégé: Acta Neurochir (Wien)
Pays: Austria
ID NLM: 0151000

Informations de publication

Date de publication:
08 2019
Historique:
received: 21 04 2019
accepted: 29 05 2019
pubmed: 30 6 2019
medline: 23 5 2020
entrez: 30 6 2019
Statut: ppublish

Résumé

The objective of this study was to evaluate the morphology of glioblastoma on structural pretreatment magnetic resonance imaging (MRI), defining imaging prognostic factors. We conducted a retrospective analysis of MR images from 114 patients harboring a primary glioblastoma, derived from two neurosurgical departments. Tumor segmentation was carried out in a semi-automated fashion. Tumor compartments comprised contrast-enhancing volume (CEV+), perifocal hyperintensity on fluid-attenuated inversion recovery (FLAIR) images (FLAIR+) excluding CEV+, and a non-enhancing area within the CEV+ lesion (CEV-). Additionally, two ratios were calculated from these volumes, the edema-tumor ratio (ETR) and necrosis-tumor ratio (NTR). All patients received surgical resection, followed by concomitant radiation and chemotherapy. Tumor segmentation revealed the strongest correlation between the CEV+ volume and the CEV-, presenting intratumoral necrosis (p < 0.001). The relation between the tumor surrounding the FLAIR+ area and the CEV+ volume and the ETR is inversely correlated (p = 0.001). The most important prognostic factor in multivariable analysis was NTR (HR 2.63, p = 0.016). The cut-off value in our cohort for NTR was 0.33, equivalent to a decrease in survival if the necrotic core of the tumor (CEV-) accounts for more than 33% of the tumor mass itself (CEV+). Our data emphasizes the importance of the necrosis-tumor ratio as a biomarker in glioblastoma imaging, rather than single tumor compartment volumes. NTR can help to identify a subset of tumors with a higher resistance to therapy and a dismal prognosis.

Sections du résumé

BACKGROUND
The objective of this study was to evaluate the morphology of glioblastoma on structural pretreatment magnetic resonance imaging (MRI), defining imaging prognostic factors.
METHOD
We conducted a retrospective analysis of MR images from 114 patients harboring a primary glioblastoma, derived from two neurosurgical departments. Tumor segmentation was carried out in a semi-automated fashion. Tumor compartments comprised contrast-enhancing volume (CEV+), perifocal hyperintensity on fluid-attenuated inversion recovery (FLAIR) images (FLAIR+) excluding CEV+, and a non-enhancing area within the CEV+ lesion (CEV-). Additionally, two ratios were calculated from these volumes, the edema-tumor ratio (ETR) and necrosis-tumor ratio (NTR). All patients received surgical resection, followed by concomitant radiation and chemotherapy.
RESULTS
Tumor segmentation revealed the strongest correlation between the CEV+ volume and the CEV-, presenting intratumoral necrosis (p < 0.001). The relation between the tumor surrounding the FLAIR+ area and the CEV+ volume and the ETR is inversely correlated (p = 0.001). The most important prognostic factor in multivariable analysis was NTR (HR 2.63, p = 0.016). The cut-off value in our cohort for NTR was 0.33, equivalent to a decrease in survival if the necrotic core of the tumor (CEV-) accounts for more than 33% of the tumor mass itself (CEV+).
CONCLUSIONS
Our data emphasizes the importance of the necrosis-tumor ratio as a biomarker in glioblastoma imaging, rather than single tumor compartment volumes. NTR can help to identify a subset of tumors with a higher resistance to therapy and a dismal prognosis.

Identifiants

pubmed: 31254065
doi: 10.1007/s00701-019-03966-6
pii: 10.1007/s00701-019-03966-6
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1723-1732

Auteurs

Christian Henker (C)

Department of Neurosurgery, University Medicine of Rostock, Schillingallee 35, 18055, Rostock, Germany. Christian.Henker@med.uni-rostock.de.

Marie Cristin Hiepel (MC)

Department of Neurosurgery, University Medicine of Rostock, Schillingallee 35, 18055, Rostock, Germany.

Thomas Kriesen (T)

Department of Neurosurgery, University Medicine of Rostock, Schillingallee 35, 18055, Rostock, Germany.

Moritz Scherer (M)

Department of Neurosurgery, Heidelberg University Hospital, Heidelberg, Germany.

Änne Glass (Ä)

Institute for Biostatistics and Informatics in Medicine, University Medicine of Rostock, Rostock, Germany.

Christel Herold-Mende (C)

Department of Neurosurgery, Heidelberg University Hospital, Heidelberg, Germany.

Martin Bendszus (M)

Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany.

Sönke Langner (S)

Institute of Diagnostic and Interventional Radiology, Pediatric Radiology and Neuroradiology, University Medicine of Rostock, Rostock, Germany.

Marc-André Weber (MA)

Institute of Diagnostic and Interventional Radiology, Pediatric Radiology and Neuroradiology, University Medicine of Rostock, Rostock, Germany.

Björn Schneider (B)

Institute for Pathology, University Medicine of Rostock, Rostock, Germany.

Andreas Unterberg (A)

Department of Neurosurgery, Heidelberg University Hospital, Heidelberg, Germany.

Jürgen Piek (J)

Department of Neurosurgery, University Medicine of Rostock, Schillingallee 35, 18055, Rostock, Germany.

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