Literature DB >> 29357274

Glioblastoma: Vascular Habitats Detected at Preoperative Dynamic Susceptibility-weighted Contrast-enhanced Perfusion MR Imaging Predict Survival.

Javier Juan-Albarracín1, Elies Fuster-Garcia1, Alexandre Pérez-Girbés1, Fernando Aparici-Robles1, Ángel Alberich-Bayarri1, Antonio Revert-Ventura1, Luis Martí-Bonmatí1, Juan M García-Gómez1.   

Abstract

Purpose To determine if preoperative vascular heterogeneity of glioblastoma is predictive of overall survival of patients undergoing standard-of-care treatment by using an unsupervised multiparametric perfusion-based habitat-discovery algorithm. Materials and Methods Preoperative magnetic resonance (MR) imaging including dynamic susceptibility-weighted contrast material-enhanced perfusion studies in 50 consecutive patients with glioblastoma were retrieved. Perfusion parameters of glioblastoma were analyzed and used to automatically draw four reproducible habitats that describe the tumor vascular heterogeneity: high-angiogenic and low-angiogenic regions of the enhancing tumor, potentially tumor-infiltrated peripheral edema, and vasogenic edema. Kaplan-Meier and Cox proportional hazard analyses were conducted to assess the prognostic potential of the hemodynamic tissue signature to predict patient survival. Results Cox regression analysis yielded a significant correlation between patients' survival and maximum relative cerebral blood volume (rCBVmax) and maximum relative cerebral blood flow (rCBFmax) in high-angiogenic and low-angiogenic habitats (P < .01, false discovery rate-corrected P < .05). Moreover, rCBFmax in the potentially tumor-infiltrated peripheral edema habitat was also significantly correlated (P < .05, false discovery rate-corrected P < .05). Kaplan-Meier analysis demonstrated significant differences between the observed survival of populations divided according to the median of the rCBVmax or rCBFmax at the high-angiogenic and low-angiogenic habitats (log-rank test P < .05, false discovery rate-corrected P < .05), with an average survival increase of 230 days. Conclusion Preoperative perfusion heterogeneity contains relevant information about overall survival in patients who undergo standard-of-care treatment. The hemodynamic tissue signature method automatically describes this heterogeneity, providing a set of vascular habitats with high prognostic capabilities. © RSNA, 2018.

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Year:  2018        PMID: 29357274     DOI: 10.1148/radiol.2017170845

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  10 in total

1.  Multiparameter MRI Predictors of Long-Term Survival in Glioblastoma Multiforme.

Authors:  Olya Stringfield; John A Arrington; Sandra K Johnston; Nicolas G Rognin; Noah C Peeri; Yoganand Balagurunathan; Pamela R Jackson; Kamala R Clark-Swanson; Kristin R Swanson; Kathleen M Egan; Robert A Gatenby; Natarajan Raghunand
Journal:  Tomography       Date:  2019-03

2.  Local detection of microvessels in IDH-wildtype glioblastoma using relative cerebral blood volume: an imaging marker useful for astrocytoma grade 4 classification.

Authors:  María Del Mar Álvarez-Torres; Elies Fuster-García; Javier Juan-Albarracín; Gaspar Reynés; Fernando Aparici-Robles; Jaime Ferrer-Lozano; Juan Miguel García-Gómez
Journal:  BMC Cancer       Date:  2022-01-06       Impact factor: 4.430

Review 3.  Hemodynamic Imaging in Cerebral Diffuse Glioma-Part B: Molecular Correlates, Treatment Effect Monitoring, Prognosis, and Future Directions.

Authors:  Vittorio Stumpo; Lelio Guida; Jacopo Bellomo; Christiaan Hendrik Bas Van Niftrik; Martina Sebök; Moncef Berhouma; Andrea Bink; Michael Weller; Zsolt Kulcsar; Luca Regli; Jorn Fierstra
Journal:  Cancers (Basel)       Date:  2022-03-05       Impact factor: 6.639

4.  Decoding the Heterogeneity of Malignant Gliomas by PET and MRI for Spatial Habitat Analysis of Hypoxia, Perfusion, and Diffusion Imaging: A Preliminary Study.

Authors:  Michele Bailo; Nicolò Pecco; Marcella Callea; Paola Scifo; Filippo Gagliardi; Luca Presotto; Valentino Bettinardi; Federico Fallanca; Paola Mapelli; Luigi Gianolli; Claudio Doglioni; Nicoletta Anzalone; Maria Picchio; Pietro Mortini; Andrea Falini; Antonella Castellano
Journal:  Front Neurosci       Date:  2022-07-13       Impact factor: 5.152

5.  The Impact of MRI Features and Observer Confidence on the Treatment Decision-Making for Patients with Untreated Glioma.

Authors:  Paulina Due-Tønnessen; Marco C Pinho; Kyrre E Emblem; John K Hald; Masafumi Kanoto; Andreas Abildgaard; Donatas Sederevicius; Inge R Groote; Otto Rapalino; Atle Bjørnerud
Journal:  Sci Rep       Date:  2019-12-27       Impact factor: 4.379

6.  The wavelet power spectrum of perfusion weighted MRI correlates with tumor vascularity in biopsy-proven glioblastoma samples.

Authors:  Lukas T Rotkopf; Benedikt Wiestler; Christine Preibisch; Friederike Liesche-Starnecker; Thomas Pyka; Dominik Nörenberg; Stefanie Bette; Jens Gempt; Kolja M Thierfelder; Claus Zimmer; Thomas Huber
Journal:  PLoS One       Date:  2020-01-23       Impact factor: 3.240

7.  A practical method for multimodal registration and assessment of whole-brain disease burden using PET, MRI, and optical imaging.

Authors:  Matthew L Scarpelli; Debbie R Healey; Shwetal Mehta; Vikram D Kodibagkar; Christopher C Quarles
Journal:  Sci Rep       Date:  2020-10-14       Impact factor: 4.379

8.  MGMT methylation may benefit overall survival in patients with moderately vascularized glioblastomas.

Authors:  Elies Fuster-Garcia; David Lorente Estellés; María Del Mar Álvarez-Torres; Javier Juan-Albarracín; Eduard Chelebian; Alex Rovira; Cristina Auger Acosta; Jose Pineda; Laura Oleaga; Enrique Mollá-Olmos; Silvano Filice; Paulina Due-Tønnessen; Torstein R Meling; Kyrre E Emblem; Juan M García-Gómez
Journal:  Eur Radiol       Date:  2020-10-01       Impact factor: 5.315

9.  DCE-MRI in Glioma, Infiltration Zone and Healthy Brain to Assess Angiogenesis: A Biopsy Study.

Authors:  Vera C Keil; Gerrit H Gielen; Bogdan Pintea; Peter Baumgarten; Angeliki Datsi; Kanishka Hittatiya; Matthias Simon; Elke Hattingen
Journal:  Clin Neuroradiol       Date:  2021-04-26       Impact factor: 3.649

Review 10.  Electrotherapies for Glioblastoma.

Authors:  Elise P W Jenkins; Alina Finch; Magda Gerigk; Iasonas F Triantis; Colin Watts; George G Malliaras
Journal:  Adv Sci (Weinh)       Date:  2021-07-22       Impact factor: 16.806

  10 in total

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