Dose-dependent volume loss in subcortical deep grey matter structures after cranial radiotherapy.
Amygdala
Brain neoplasms
CAT12, computational anatomy toolbox 12
CT, computed tomography
Caudate nucleus
FWER, family-wise error rate
GM, grey matter
Globus pallidus
Gray matter
Hippocampus
MRI, magnetic resonance imaging
Nucleus accumbens
PALM, permutation analysis of linear models
PTV, planning target volume
Putamen
RT, radiotherapy
Radiotherapy
SPM, statistical parametric mapping
TFE, turbo fast echo
Thalamus
WBRT, whole-brain radiotherapy
Journal
Clinical and translational radiation oncology
ISSN: 2405-6308
Titre abrégé: Clin Transl Radiat Oncol
Pays: Ireland
ID NLM: 101713416
Informations de publication
Date de publication:
Jan 2021
Jan 2021
Historique:
received:
22
09
2020
revised:
09
11
2020
accepted:
10
11
2020
entrez:
9
12
2020
pubmed:
10
12
2020
medline:
10
12
2020
Statut:
epublish
Résumé
The relation between radiotherapy (RT) dose to the brain and morphological changes in healthy tissue has seen recent increased interest. There already is evidence for changes in the cerebral cortex and white matter, as well as selected subcortical grey matter (GM) structures. We studied this relation in all deep GM structures, to help understand the aetiology of post-RT neurocognitive symptoms. We selected 31 patients treated with RT for grade II-IV glioma. Pre-RT and 1 year post-RT 3D T1-weighted MRIs were automatically segmented, and the changes in volume of the following structures were assessed: amygdala, nucleus accumbens, caudate nucleus, hippocampus, globus pallidus, putamen, and thalamus. The volumetric changes were related to the mean RT dose received by each structure. Hippocampal volumes were entered into a population-based nomogram to estimate hippocampal age. A significant relation between RT dose and volume loss was seen in all examined structures, except the caudate nucleus. The volume loss rates ranged from 0.16 to 1.37%/Gy, corresponding to 4.9-41.2% per 30 Gy. Hippocampal age, as derived from the nomogram, was seen to increase by a median of 11 years. Almost all subcortical GM structures are susceptible to radiation-induced volume loss, with higher volume loss being observed with increasing dose. Volume loss of these structures is associated with neurological deterioration, including cognitive decline, in neurodegenerative diseases. To support a causal relationship between radiation-induced deep GM loss and neurocognitive functioning in glioma patients, future studies are needed that directly correlate volumetrics to clinical outcomes.
Sections du résumé
BACKGROUND AND PURPOSE
OBJECTIVE
The relation between radiotherapy (RT) dose to the brain and morphological changes in healthy tissue has seen recent increased interest. There already is evidence for changes in the cerebral cortex and white matter, as well as selected subcortical grey matter (GM) structures. We studied this relation in all deep GM structures, to help understand the aetiology of post-RT neurocognitive symptoms.
MATERIALS AND METHODS
METHODS
We selected 31 patients treated with RT for grade II-IV glioma. Pre-RT and 1 year post-RT 3D T1-weighted MRIs were automatically segmented, and the changes in volume of the following structures were assessed: amygdala, nucleus accumbens, caudate nucleus, hippocampus, globus pallidus, putamen, and thalamus. The volumetric changes were related to the mean RT dose received by each structure. Hippocampal volumes were entered into a population-based nomogram to estimate hippocampal age.
RESULTS
RESULTS
A significant relation between RT dose and volume loss was seen in all examined structures, except the caudate nucleus. The volume loss rates ranged from 0.16 to 1.37%/Gy, corresponding to 4.9-41.2% per 30 Gy. Hippocampal age, as derived from the nomogram, was seen to increase by a median of 11 years.
CONCLUSION
CONCLUSIONS
Almost all subcortical GM structures are susceptible to radiation-induced volume loss, with higher volume loss being observed with increasing dose. Volume loss of these structures is associated with neurological deterioration, including cognitive decline, in neurodegenerative diseases. To support a causal relationship between radiation-induced deep GM loss and neurocognitive functioning in glioma patients, future studies are needed that directly correlate volumetrics to clinical outcomes.
Identifiants
pubmed: 33294645
doi: 10.1016/j.ctro.2020.11.005
pii: S2405-6308(20)30092-6
pmc: PMC7691672
doi:
Types de publication
Journal Article
Langues
eng
Pagination
35-41Informations de copyright
© 2020 The Author(s).
Déclaration de conflit d'intérêts
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Références
Neuroimage. 2010 Jul 1;51(3):1047-56
pubmed: 20226258
Front Neurol. 2017 Aug 24;8:428
pubmed: 28883807
Eur Radiol. 2019 Mar;29(3):1355-1364
pubmed: 30242503
Int J Radiat Oncol Biol Phys. 2012 Jul 15;83(4):e487-93
pubmed: 22209148
Neuroimage. 2018 Feb 1;166:400-424
pubmed: 29079522
J Clin Oncol. 2014 Dec 1;32(34):3810-6
pubmed: 25349290
J Cereb Blood Flow Metab. 1996 Jan;16(1):7-22
pubmed: 8530558
Neuro Oncol. 2012 Sep;14 Suppl 4:iv37-44
pubmed: 23095829
Neuroimage Clin. 2019;23:101904
pubmed: 31254939
JAMA Oncol. 2020 Jul 1;6(7):981-983
pubmed: 32407497
Radiother Oncol. 2019 Jul;136:44-49
pubmed: 31015128
Front Neurol. 2017 Aug 15;8:399
pubmed: 28861033
Acta Oncol. 2019 Jan;58(1):57-65
pubmed: 30474448
Brain. 2014 Apr;137(Pt 4):1120-9
pubmed: 24613932
Brain. 2008 Dec;131(Pt 12):3277-85
pubmed: 19022861
J Neurosci Methods. 2015 Sep 30;253:254-61
pubmed: 26057114
Int J Radiat Oncol Biol Phys. 2016 Feb 1;94(2):297-304
pubmed: 26853338
Nat Rev Neurol. 2017 Jan;13(1):52-64
pubmed: 27982041
Neuroimage. 2014 May 15;92:381-97
pubmed: 24530839
Radiother Oncol. 2019 Jun;135:33-42
pubmed: 31015168
Neuroimage. 2012 Nov 15;63(3):1134-42
pubmed: 22846656
Clin Neurophysiol. 2019 Aug;130(8):1208-1217
pubmed: 31163365
Int J Radiat Oncol Biol Phys. 2017 Apr 1;97(5):910-918
pubmed: 28333012
J Clin Oncol. 2020 Apr 1;38(10):1019-1029
pubmed: 32058845
Neuroradiol J. 2018 Aug;31(4):350-355
pubmed: 29869576
Int J Radiat Oncol Biol Phys. 2017 Feb 1;97(2):263-269
pubmed: 28068234
J Huntingtons Dis. 2013;2(4):477-89
pubmed: 25062732
Int J Radiat Oncol Biol Phys. 2019 Nov 15;105(4):773-783
pubmed: 31408667
Neuroimage. 2008 Jun;41(2):371-9
pubmed: 18394925
Neurotox Res. 2020 Apr;37(4):788-799
pubmed: 31900898
Neuroimage Clin. 2020;25:102158
pubmed: 31918064
J Neurol Neurosurg Psychiatry. 2016 Apr;87(4):425-32
pubmed: 25904810
Neuroimage Clin. 2019;21:101581
pubmed: 30606656
Neurooncol Adv. 2020 May 21;2(1):vdaa060
pubmed: 32642712
Front Aging Neurosci. 2017 Mar 07;9:50
pubmed: 28326035
Front Neurosci. 2020 Jun 05;14:585
pubmed: 32581699
Neuroimage. 2019 Nov 1;201:116018
pubmed: 31319182
Neuroimage. 2013 Dec;83:472-84
pubmed: 23668971