Literature DB >> 32244208

Quantifying eloquent locations for glioblastoma surgery using resection probability maps.

Domenique M J Müller1, Pierre A Robe2, Hilko Ardon3, Frederik Barkhof4,5, Lorenzo Bello6, Mitchel S Berger7, Wim Bouwknegt8, Wimar A Van den Brink9, Marco Conti Nibali6, Roelant S Eijgelaar10, Julia Furtner11, Seunggu J Han12, Shawn L Hervey-Jumper7, Albert J S Idema13, Barbara Kiesel14, Alfred Kloet15, Jan C De Munck4, Marco Rossi6, Tommaso Sciortino6, W Peter Vandertop1, Martin Visser4, Michiel Wagemakers16, Georg Widhalm14, Marnix G Witte10, Aeilko H Zwinderman17, Philip C De Witt Hamer1.   

Abstract

OBJECTIVE: Decisions in glioblastoma surgery are often guided by presumed eloquence of the tumor location. The authors introduce the "expected residual tumor volume" (eRV) and the "expected resectability index" (eRI) based on previous decisions aggregated in resection probability maps. The diagnostic accuracy of eRV and eRI to predict biopsy decisions, resectability, functional outcome, and survival was determined.
METHODS: Consecutive patients with first-time glioblastoma surgery in 2012-2013 were included from 12 hospitals. The eRV was calculated from the preoperative MR images of each patient using a resection probability map, and the eRI was derived from the tumor volume. As reference, Sawaya's tumor location eloquence grades (EGs) were classified. Resectability was measured as observed extent of resection (EOR) and residual volume, and functional outcome as change in Karnofsky Performance Scale score. Receiver operating characteristic curves and multivariable logistic regression were applied.
RESULTS: Of 915 patients, 674 (74%) underwent a resection with a median EOR of 97%, functional improvement in 71 (8%), functional decline in 78 (9%), and median survival of 12.8 months. The eRI and eRV identified biopsies and EORs of at least 80%, 90%, or 98% better than EG. The eRV and eRI predicted observed residual volumes under 10, 5, and 1 ml better than EG. The eRV, eRI, and EG had low diagnostic accuracy for functional outcome changes. Higher eRV and lower eRI were strongly associated with shorter survival, independent of known prognostic factors.
CONCLUSIONS: The eRV and eRI predict biopsy decisions, resectability, and survival better than eloquence grading and may be useful preoperative indices to support surgical decisions.

Entities:  

Keywords:  extent of resection; glioma; neurosurgery; oncology; reproducibility of results; residual volume

Mesh:

Year:  2020        PMID: 32244208     DOI: 10.3171/2020.1.JNS193049

Source DB:  PubMed          Journal:  J Neurosurg        ISSN: 0022-3085            Impact factor:   5.115


  4 in total

1.  Robust Deep Learning-based Segmentation of Glioblastoma on Routine Clinical MRI Scans Using Sparsified Training.

Authors:  Roelant S Eijgelaar; Martin Visser; Domenique M J Müller; Frederik Barkhof; Hugo Vrenken; Marcel van Herk; Lorenzo Bello; Marco Conti Nibali; Marco Rossi; Tommaso Sciortino; Mitchel S Berger; Shawn Hervey-Jumper; Barbara Kiesel; Georg Widhalm; Julia Furtner; Pierre A J T Robe; Emmanuel Mandonnet; Philip C De Witt Hamer; Jan C de Munck; Marnix G Witte
Journal:  Radiol Artif Intell       Date:  2020-09-30

2.  Defining the impact of adjuvant treatment on the prognosis of patients with inoperable glioblastoma undergoing biopsy only: does the survival benefit outweigh the treatment effort?

Authors:  Ronja Löber-Handwerker; Katja Döring; Christoph Bock; Veit Rohde; Vesna Malinova
Journal:  Neurosurg Rev       Date:  2022-02-23       Impact factor: 2.800

Review 3.  Quantification of amyloid PET for future clinical use: a state-of-the-art review.

Authors:  Hugh G Pemberton; Lyduine E Collij; Fiona Heeman; Ariane Bollack; Mahnaz Shekari; Gemma Salvadó; Isadora Lopes Alves; David Vallez Garcia; Mark Battle; Christopher Buckley; Andrew W Stephens; Santiago Bullich; Valentina Garibotto; Frederik Barkhof; Juan Domingo Gispert; Gill Farrar
Journal:  Eur J Nucl Med Mol Imaging       Date:  2022-04-07       Impact factor: 10.057

4.  TMS Seeded Diffusion Tensor Imaging Tractography Predicts Permanent Neurological Deficits.

Authors:  Matthew Muir; Sarah Prinsloo; Hayley Michener; Jeffrey I Traylor; Rajan Patel; Ron Gadot; Dhiego Chaves de Almeida Bastos; Vinodh A Kumar; Sherise Ferguson; Sujit S Prabhu
Journal:  Cancers (Basel)       Date:  2022-01-11       Impact factor: 6.639

  4 in total

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