Predicting the Extent of Resection of Motor-Eloquent Gliomas Based on TMS-Guided Fiber Tracking.
extent of resection
fiber tracking
glioma
nTMS
outcome
Journal
Brain sciences
ISSN: 2076-3425
Titre abrégé: Brain Sci
Pays: Switzerland
ID NLM: 101598646
Informations de publication
Date de publication:
16 Nov 2021
16 Nov 2021
Historique:
received:
30
09
2021
revised:
05
11
2021
accepted:
13
11
2021
entrez:
27
11
2021
pubmed:
28
11
2021
medline:
28
11
2021
Statut:
epublish
Résumé
Surgical planning with nTMS-based tractography is proven to increase safety during surgery. A preoperative risk stratification model has been published based on the M1 infiltration, RMT ratio, and tumor to corticospinal tract distance (TTD). The correlation of TTD with corticospinal tract to resection cavity distance (TRD) and outcome is needed to further evaluate the validity of the model. To use the postop MRI-derived resection cavity to measure how closely the resection cavity approximated the preoperatively calculated corticospinal tract (CST) and how this correlates with the risk model and the outcome. We included 183 patients who underwent nTMS-based DTI and surgical resection for presumed motor-eloquent gliomas. TTD, TRD, and motor outcome were recorded and tested for correlations. The intraoperative monitoring documentation was available for a subgroup of 48 patients, whose responses were correlated to TTD and TRD. As expected, TTD and TRD showed a good correlation (Spearman's ρ = 0.67, The TTD approximates the TRD well, confirming the best predictive parameter and giving strength to the nTMS-based risk stratification model. Our analysis of TRD supports the use of the nTMS-based TTD measurement to estimate the resection preoperatively, also confirming the 8 mm cutoff. Nevertheless, the TRD proved to have a slightly stronger correlation with the outcome as the surgeon's experience, anatomofunctional knowledge, and MEP observations influence the expected EOR.
Sections du résumé
BACKGROUND
BACKGROUND
Surgical planning with nTMS-based tractography is proven to increase safety during surgery. A preoperative risk stratification model has been published based on the M1 infiltration, RMT ratio, and tumor to corticospinal tract distance (TTD). The correlation of TTD with corticospinal tract to resection cavity distance (TRD) and outcome is needed to further evaluate the validity of the model.
AIM OF THE STUDY
OBJECTIVE
To use the postop MRI-derived resection cavity to measure how closely the resection cavity approximated the preoperatively calculated corticospinal tract (CST) and how this correlates with the risk model and the outcome.
METHODS
METHODS
We included 183 patients who underwent nTMS-based DTI and surgical resection for presumed motor-eloquent gliomas. TTD, TRD, and motor outcome were recorded and tested for correlations. The intraoperative monitoring documentation was available for a subgroup of 48 patients, whose responses were correlated to TTD and TRD.
RESULTS
RESULTS
As expected, TTD and TRD showed a good correlation (Spearman's ρ = 0.67,
CONCLUSIONS
CONCLUSIONS
The TTD approximates the TRD well, confirming the best predictive parameter and giving strength to the nTMS-based risk stratification model. Our analysis of TRD supports the use of the nTMS-based TTD measurement to estimate the resection preoperatively, also confirming the 8 mm cutoff. Nevertheless, the TRD proved to have a slightly stronger correlation with the outcome as the surgeon's experience, anatomofunctional knowledge, and MEP observations influence the expected EOR.
Identifiants
pubmed: 34827516
pii: brainsci11111517
doi: 10.3390/brainsci11111517
pmc: PMC8615964
pii:
doi:
Types de publication
Journal Article
Langues
eng
Subventions
Organisme : italian society of neurosurgery
ID : Premio Melitta Grasso Tomasello
Références
Acta Neurochir Suppl. 2017;124:251-261
pubmed: 28120081
J Neurosurg. 2017 Apr;126(4):1227-1237
pubmed: 27257834
J Neurosurg. 2009 Jan;110(1):156-62
pubmed: 18847342
Clin Neurophysiol. 2015 Jun;126(6):1071-1107
pubmed: 25797650
Neurosurgery. 2012 Aug;71(2):331-40; discussion 340
pubmed: 22534425
Front Oncol. 2019 May 29;9:426
pubmed: 31192130
Neurosurgery. 2008 Apr;62(4):753-64; discussion 264-6
pubmed: 18496181
Prog Nucl Magn Reson Spectrosc. 2019 Jun - Aug;112-113:1-16
pubmed: 31481155
J Neurosurg. 2012 May;116(5):994-1001
pubmed: 22304452
Neuro Oncol. 2015 Jun;17(6):868-81
pubmed: 25556920
Neuro Oncol. 2014 Sep;16(9):1274-82
pubmed: 24516237
Neurosurgery. 2017 Feb 1;80(2):193-200
pubmed: 28173590
Lancet. 1985 May 11;1(8437):1106-7
pubmed: 2860322
J Neurol Neurosurg Psychiatry. 2005 Jun;76(6):845-51
pubmed: 15897509
Neuro Oncol. 2014 Oct;16(10):1365-72
pubmed: 24923875
Brain Struct Funct. 2018 Jul;223(6):2841-2858
pubmed: 29663135
Nat Commun. 2017 Nov 7;8(1):1349
pubmed: 29116093
Neuroimage Clin. 2017 Aug 12;16:276-285
pubmed: 28840099
Neuroimage Clin. 2021;29:102541
pubmed: 33401138
Neuroimage. 2012 Sep;62(3):1600-9
pubmed: 22659445
Neurosurgery. 2009 Dec;65(6 Suppl):93-8; discussion 98-9
pubmed: 19935007
Neurosurgery. 2011 Sep;69(3):581-8; discussion 588
pubmed: 21430587
Neurosurgery. 2014 Dec;10 Suppl 4:542-54; discussion 554
pubmed: 25072115
J Clin Oncol. 2012 Jul 10;30(20):2559-65
pubmed: 22529254
Neurosurgery. 2012 May;70(5):1248-56; discussion 1256-7
pubmed: 22127045
Neurosurgery. 2008 Mar;62(3):564-76; discussion 564-76
pubmed: 18425006
Clin Neurol Neurosurg. 2019 Aug;183:105387
pubmed: 31228706
Ann Neurol. 1999 Feb;45(2):265-9
pubmed: 9989633
J Neurosurg. 2012 Aug;117(2):354-62
pubmed: 22702484
JAMA. 2012 Nov 14;308(18):1881-8
pubmed: 23099483
Acta Neuropathol. 2016 Jun;131(6):803-20
pubmed: 27157931
Neuroimage. 2019 Jan 15;185:1-11
pubmed: 30317017
J Clin Neurophysiol. 2009 Dec;26(6):422-5
pubmed: 19952567
Acta Neurochir (Wien). 2013 Mar;155(3):389-97
pubmed: 23325516