Maria Ljungberg1,2, Oscar Jalnefjord1,2, Isabelle Rydén3, Erik Fernström4, Linnea Andersson1,2, Justin Schneiderman3, Malin Blomstrand4, Marie Kalm5, Isabella Björkman-Burtscher6, and Marianne Jarfelt4
1Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden, 2Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden, 3Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden, 4Department of Oncology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden, 5Department of Pharmacology, Institute of Neuroscience and Physiology , Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden, 6Department of Radiology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
Synopsis
Keywords: Tumors, Radiotherapy, DTI, MR spectroscopy
Cranial radiotherapy (CRT) is effective; however, survivors of
childhood cancer often suffer from cognitive deficits. Two adult patient groups
that received different CRT exposures as children were included, as well as healthy
volunteers. The MR-examination comprised of anatomical imaging, DTI and MR
spectroscopy of the hippocampus. Differences were found between the group that
received highest CRT dose and the control group in hippocampal volume,
tNAA/tCr-ratio of hippocampus and several DTI-measures in e.g., corpus
callosum. Correlations was found between DTI-measures (MD/RD/AD) in some of the
studied white matter tracts and several of the used neuropsychological tests, e.g.,
BVMT-R Sum and Coding.
INTRODUCTION
Modern cranial radiotherapy (CRT), together with
improvements in other treatment modalities has resulted in an increased
population of long-term survivors of childhood cancer. However, for tumours in
the brain or head-and-neck (H&N) region, the CRT causes radiation exposure
also to the healthy brain tissue, which can result in cognitive deficits1. Late effects
have been studied histologically, showing e.g. vascular abnormality,
demyelination and white matter necrosis2, however, the pathogenesis of these damages is still poorly
understood.
Neuroimaging using magnetic resonance (MR) methods can
provide information on tissue morphology, physiology and metabolism and have
thereby a great potential to provide imaging biomarkers for in vivo brain
applications regarding late effects due to CRT.
This study aimed to evaluate very late effects of CRT on
neuroimaging biomarkers in adult survivors of malignant childhood posterior
fossa tumours, mainly medulloblastoma (MB), and nasopharyngeal tumours (NP), representing
two groups with different RT exposures to different parts of the brain, and to
compare the neuroimaging results of these survivors to healthy controls (C). A second aim was to study if
alterations in neuroimaging biomarkers correlated with reduced cognitive function.METHODS
Adult
childhood cancer survivors treated for two different types of tumours were
studied: childhood posterior fossa tumours, mostly medulloblastoma (n=10), nasophayngeal
tumours (n=6), as well as a group
of age and sex-matched healthy volunteers (n=11). Characteristic data regarding
the subjects and their treatment are summarized in table 1. The study was approved by the local
ethical committee (ref numbers: 721-2015 with amendment 2021-03732 and 1067-16 with
amendment T1068-17).
All MR
measurements were performed on a Philips Gyroscan Achieva 3T release 5.1.7 to
5.7.1 (Philips Medical systems, Eindhoven, the Netherlands) using the 32
channel headcoil. The MR protocol comprised of a 3D T1-weighted turbo field echo sequence, DTI (32 directions TE/TR 86/4075 ms, voxel size 23mm3)
and MRS separately in the left and right anterior hippocampus (PRESS, TE/TR
40/2000 ms, VOI size= 10*15*30 mm3).
Hippocampus
volumes and intracranial volumes were obtained from FreeSurfer segmentations3.
DTI parameters (fractional anisotropy (FA), mean diffusivity (MD), radial
diffusivity (RD) and axial diffusivity (AD)) were estimated with FSL4
and evaluated in the following tracts generated by TractSeg5: cingulum,
fornix , superior longitudinal fascicle part I, II and III, uncinate fascicle and
corpus callosum (CC; both full tract and all seven subdivisions). MRS data was
evaluated with LCModel6 using in house simulated basis sets7.
A preliminary evaluation of the MRS data has been presented at ISMRM
20208.
The evaluation
of the neurocognitive function of the cohort has been published9.
The tests included in the evaluation were: Rey Auditory Verbal Learning Test
(RAVLT, measuring verbal learning (RAVLT-Sum) and memory (RAVLT-Ret)), Brief
Visuospatial Memory Test-Revised (BVMT-R, measuring visuo-spatial learning
(BVMT-R sum) and memory (BVMT-R ret)), Trail Making Test (TMT A and B,
measuring visual attention, process speed and mental flexibility(B)), D-KEFS
Color-Word Interference Test ((CWIT) 1 to 4, measuring verbal speed and
interference, 4 also adds a measure of cognitive flexibility) and WAIS-IV Coding
(Coding, measuring mental speed, sustained attention, and visuo-motor
co-ordination).
Mann-Whitney
U-test was used to test for group differences. Given the exploratory focus of this
study, no correction for multiple correlations was performed. Statistical
significance was set to p≤0.05 for evaluation of
hippocampal volume and MRS, and p≤0.005 for the DTI-measures (FA/MD/RA/AD). The correlation analysis was performed
using linear regression and R2 is given by the square of the Pearson
correlation coefficient.RESULTS & DISCUSSION
Hippocampal volume was
lower in MB compared to NP and controls, figure 1, as expected10. MRS showed lower mean tNAA/tCr ratio in
both hippocampi compared to controls and NP. There was also a not statistically
significant tendency for a lower Glu/tCr ratio for MB as compared to NP and
controls (fig 2). Lowered tNAA indicates long-term neuronal damage and
dysfunction11 while lowered Glu could be caused by neuronal and
glial damage and dysfunction12.
Eight out of 60
possible combinations of evaluated white matter tracts and DTI-measures (FA,
MD, AD & RD) differed between MB and controls (fig 3). The only significant
difference between MB and NP was found in the CC tract for MD, AD, and RD.
Correlations
between neurocognitive measures and
DTI measures were primarily found between each of the tests: BVMT-R Sum (visual
learning), RAVLT Sum (verbal learning) and Coding (processing speed), and the CC
and its subdivisions (fig 4). The R2-coefficient was moderate
(R2<0.4), but a general pattern could be seen where MB separated
from the other two groups in both neurocognitive performance and DTI measures. CONCLUSION
This study found differences more than 20 years after CRT
between the group that received highest CRT dose and the control group
regarding hippocampal volume, tNAA/tCr-ratio in the hippocampus and in several
DTI-measures, e.g in corpus callosum. A correlation between e.g. lower mean
diffusivity in the studied white matter tracts and several of the
neuropsychological tests, e.g. BVMT-R Sum and Coding, was also found.
These results indicate associations between the MR-derived neuroimaging
biomarkers and impairments in psychomotor speed, learning and memory following
radiation to the brain during childhood. Thus, MRI and MRS could add valuable
information to increase the understanding of the pathogenesis of
radiation-induced brain damage.Acknowledgements
The study was financed by grants from the Swedish Cancer
Society, the King Gustav V Jubilee Clinic Cancer Research Foundation, The
Swedish Childhood Cancer Foundation, Lion's Cancer Research Fund of Western
Sweden and the Swedish state under the agreement between the Swedish government
and the county councils, the ALF-agreement.
The authors thank Philips
Healthcare Clinical Science Group for support.
References
1. Makale MT,
McDonald CR, Hattangadi-Gluth JA et al. Mechanisms of radiotherapy-associated
cognitive disability in patients with brain tumours. Nat Rev Neurol. 2017;
13(1):52-64.
2. Lumniczky
K, Szatmári T, Sáfrány G. Ionizing Radiation-Induced Immune and Inflammatory
Reactions in the Brain. Front Immunol. 2017; 8(517):1-13
3. Reuter,
M., Schmansky, N.J., Rosas, H.D., Fischl, B. Within-Subject Template Estimation
for Unbiased Longitudinal Image Analysis. Neuroimage. 2012; 61(4): 1402-1418
4. Jenkinson M, Beckmann C F, Behrens
T.E. et al. FSL. NeuroImage, 2012; 62:782-790
5. Wasserthalab
J, Nehera P, Maier-Heinac K H. TractSeg - Fast and accurate white matter tract.
NeuroImage. 2018; 183: 239-253
6. Provencher
S W. Estimation of metabolite concentrations from localized in vivo proton NMR
spectra. Magn Reson Med. 1993; 30(6):672-629
7. Jalnefjord O, Pettersson P, Lundholm L
et al. Simulated basis sets for semi‑LASER: the impact of including
shaped RF pulses and magnetic field gradients. Magnetic Resonance Materials in
Physics, Biology and Medicine. 2021; 34:545–554
8. 6.Ljungberg
M, Fernström E, Jalnefjord O, et al. Hippocampal MR Spectroscopy show chronic
metabolic effects following cranial radiotherapy in childhood cancer survivors.
Annual Meeting for International Society of Magnetic Resonance in Medicine
(ISMRM), 2020, #284.
9. Rydén I,
Fernström E, Lannering B, et al. Neuropsychological functioning in childhood
cancer survivors following cranial radiotherapy – results from a long-term
follow-up clinic, Neurocase, 2022; 28(2): 163-172
10. Seibert T
M, Karunamuni R, Bartsch H. Radiation dose-dependent hippocampal atrophy
detected with longitudinal volumetric MRI, Int J Radiat Oncol Biol Phys. 2017;
97(2): 263–269
11. Sundgren
P, Cao Y. Brain irradiation: Effects on normal brain parenchyma and radiation
injury Neuroimaging Clin N Am. 2009; 19(4): 657–668
12. Chang L, Munsaka
S M, Kraft-Terry S. Magnetic Resonance Spectroscopy to Assess NeuroInflammation
and Neuropathic Pain J Neuroimmune Pharmacol. 2013; 8(3): 576–593