Literature DB >> 32938221

Quantitative volumetric assessment of baseline enhancing tumor volume as an imaging biomarker predicts overall survival in patients with glioblastoma.

Timo A Auer1, Marta Della Seta1, Federico Collettini1, Julius Chapiro2, Sebastian Zschaeck3, Pirus Ghadjar3, Harun Badakhshi4, Julian Florange3, Bernd Hamm1, Volker Budach3, David Kaul3.   

Abstract

BACKGROUND: Glioblastoma multiforme (GBM) is the commonest malignant primary brain tumor and still has one of the worst prognoses among cancers in general. There is a need for non-invasive methods to predict individual prognosis in patients with GBM.
PURPOSE: To evaluate quantitative volumetric tissue assessment of enhancing tumor volume on cranial magnetic resonance imaging (MRI) as an imaging biomarker for predicting overall survival (OS) in patients with GBM.
MATERIAL AND METHODS: MRI scans of 49 patients with histopathologically confirmed GBM were analyzed retrospectively. Baseline contrast-enhanced (CE) MRI sequences were transferred to a segmentation-based three-dimensional quantification tool, and the enhancing tumor component was analyzed. Based on a cut-off percentage of the enhancing tumor volume (PoETV) of >84.78%, samples were dichotomized, and the OS and intracranial progression-free survival (PFS) were evaluated. Univariable and multivariable analyses, including variables such as sex, Karnofsky Performance Status score, O6-methylguanine-DNA-methyltransferase status, age, and resection status, were performed using the Cox regression model.
RESULTS: The median OS and PFS were 16.9 and 7 months in the entire cohort, respectively. Patients with a CE tumor volume of >84.78% showed a significantly shortened OS (12.9 months) compared to those with a CE tumor volume of ≤84.78% (17.7 months) (hazard ratio [HR] 2.72; 95% confidence interval [CI] 1.22-6.03; P = 0.01). Multivariable analysis confirmed that PoETV had a significant prognostic role (HR 2.47; 95% CI 1.08-5.65; P = 0.03).
CONCLUSION: We observed a correlation between PoETV and OS. This imaging biomarker may help predict the OS of patients with GBM.

Entities:  

Keywords:  Glioblastoma; brain; prognostic index; segmentation; tumor

Year:  2020        PMID: 32938221     DOI: 10.1177/0284185120953796

Source DB:  PubMed          Journal:  Acta Radiol        ISSN: 0284-1851            Impact factor:   1.990


  4 in total

1.  Machine Learning of Dose-Volume Histogram Parameters Predicting Overall Survival in Patients with Cervical Cancer Treated with Definitive Radiotherapy.

Authors:  Zhiyuan Xu; Li Yang; Qin Liu; Hao Yu; Longhua Chen
Journal:  J Oncol       Date:  2022-06-14       Impact factor: 4.501

Review 2.  Standard clinical approaches and emerging modalities for glioblastoma imaging.

Authors:  Joshua D Bernstock; Sam E Gary; Neil Klinger; Pablo A Valdes; Walid Ibn Essayed; Hannah E Olsen; Gustavo Chagoya; Galal Elsayed; Daisuke Yamashita; Patrick Schuss; Florian A Gessler; Pier Paolo Peruzzi; Asim K Bag; Gregory K Friedman
Journal:  Neurooncol Adv       Date:  2022-05-26

Review 3.  Advanced Imaging and Computational Techniques for the Diagnostic and Prognostic Assessment of Malignant Gliomas.

Authors:  Jayapalli Rajiv Bapuraj; Nicholas Wang; Ashok Srinivasan; Arvind Rao
Journal:  Cancer J       Date:  2021 Sep-Oct 01       Impact factor: 3.360

4.  Advanced MR techniques in glioblastoma imaging-upcoming challenges and how to face them.

Authors:  Timo A Auer
Journal:  Eur Radiol       Date:  2021-04-22       Impact factor: 5.315

  4 in total

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