DTI Measurements for Huntington Disease Using Mricloud

Yıl 2024, Cilt: 6 Sayı: 2, 302 - 311, 16.05.2024

Ayla Arslan , Mehtap Nisari , Emel Güler , Gökçe Bağcı Uzun , Murat Gültekin , Halil Dönmez , Keziban Bağcı , Niyazi Acer

https://doi.org/10.37990/medr.1421420

Öz

Aim: Neurodegenerative diseases are important health problems that affect many people. In this study, it was aimed to examine the brain regions of Huntington's patients by performing brain parcellation.
Material and Method: 8 controls and 8 Huntington's patients participated in the study. We measured four Diffusion Tensor Imaging metrics which were axial diffusivity, mean diffusivity, radial diffusivity and fractional anisotropy performing brain parcellation over Diffusion Tensor Imaging for control and patient groups. We used a full automated data-driven approach to study the whole brain, divided in regions of interest using mricloud.
Results: When the huntington disease group compared to control group, We found that mean diffusivity and axial diffusivity increased frontal, parietal, temporal, occipital, corpus callosum, white matter, limbic and subcortical structures, and radial diffusivity increased corpus callosum, capsula interna (p<0.05). The fractional anisotropy value was higher in nucleus caudatus, putamen and a significant difference was observed (p<0.05).
Conclusion: The increase of axial diffusivity and mean diffusivity values axonal degeneration and demyelination of frontal, parietal, temporal, occipital, corpus callosum, white matter, limbic, subcortical structures; increased radial diffusivity values dysmyelination of the corpus callosum and capsula interna; fractional anisotropy increased values in nucleus caudatus and putamen may indicate a degenerative process, axon loss and inflammation.

Anahtar Kelimeler

Huntington disease, neurodegenerative disease, brain, magnetic resonance imaging

Kaynakça

• MacDonald ME, Ambrose CM, Duyao MP, et al. Huntington Study Group. A novel gene containing a trinucleotide repeat that is expanded and unstable on Huntington's disease chromosomes. Cell. 1993;72:971-83.
• Ross CA, Aylward EH, Wild EJ, et al. Huntington disease: natural history, biomarkers and prospects for therapeutics. Nat Rev Neurol. 2014;10:204-16.
• Assaf Y, Pasternak O. Diffusion tensor imaging (DTI)-based white matter mapping in brain research: a review. J Mol Neurosci. 2008;34:51-61.
• Sprengelmeyer R, Orth M, Muller HP, et al. The neuroanatomy of subthreshold depressive symptoms in Huntington's disease: a combined diffusion tensor imaging (DTI) and voxel-based morphometry (VBM) study. Psychol Med. 2014;44:1867-78.
• Kurtoğlu E, Payas A, Düz S, et al. Analysis of changes in brain morphological structure of taekwondo athletes by diffusion tensor imaging. J Chem Neuroanat. 2023;129:102250.
• Müller HP, Grön G, Sprengelmeyer R, et al. Evaluating multicenter DTI data in Huntington's disease on site specific effects: An ex post facto approach. Neuroimage Clin. 2013;32:161-7.
• Douaud G, Behrens TE, Poupon C, et al. In vivo evidence for the selective subcortical degeneration in Huntington's disease. NeuroImage. 2009;46:958-66.
• Andica C, Kamagata K, Hatano T, et al. MR biomarkers of degenerative brain disorders derived from diffusion imagin. J Magn Reson Imaging. 2020;52:1620-36.
• Muhlau M, Weindl A, Wolschlager AM, et al. Voxel-based morphometry indicates relative preservation of the limbic prefrontal cortex in early Huntington disease. J Neural. Transm. 2007;114:367-72.
• Zhang J, Gregory S, Scahill RI, et al. In vivo characterization of white matter pathology in pre-manifest Huntington’s disease. Ann Neurol. 2018;84:497-504.
• Saba RA, Yared JH, Doring TM, et al. Diffusion tensor imaging of brain white matter in Huntington gene mutation individuals. Arq Neuropsiquiatr. 2017;75:503-8.
• Faul F, Erdfelder E, Buchner A, Lang AG. Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses. Behavior Research Methods, 2009;41:1149-60.
• Mori S, Wu D, Ceritoglu C, et al. Mricloud: delivering high-throughput mri neuroinformatics as cloud-based software as a service. Computing in Science & Engineering. 2016;18:21-35.
• Soysal H, Acer N, Özdemir M, et al. A volumetric study of the corpus callosum in the Turkish population. J Neurol Surg B Skull Base. 2021;83:443-50.
• Turamanlar O, Kundakci YE, Saritas A, et al. Automatic segmentation of the cerebellum using volBrain software in normal paediatric population. Int J Dev Neurosci. 2023;83:323-32.
• Ceritoglu C, Tang X, Chow M, et al. Computational analysis of LDDMM for brain mapping. Front Neurosci. 2013;7:15.
• Tang X, Oishi K, Faria AV, et al. Bayesian parameter estimation and segmentation in the multi-atlas random orbit model. PloS One. 2013;8;e65591.
• Acer N, Kamaşak B, Karapınar B, et al. A comparison of automated segmentation and manual tracing of magnetic resonance imaging to quantify lateral ventricle volumes. Erciyes Med J. 2022;44:148-55.
• Mukherjee P, Berman JI, Chung SW, et al. Diffusion tensor MR imaging and fiber tractography: theoretic underpinnings. AJNR Am J Neuroradiol. 2008;29:632-41.
• Öz F, Acer N, Ceviz Y, et al. Volumetric analysis of the brain structures of children with Down’s Syndrome: a 3D MRI study. J Exp Clin Med. 2021;38:197-203.
• Yoshida S, Oishi K, Faria AV, et al. Diffusion tensor imaging of normal brain development. Pediatr Radiol. 2013; 43:15-27.
• Sweidan W, Bao F, Bozorgzad NS, et al. White and gray matter abnormalities in manifest Guntington’s disease: cross-sectional and longitudinal analysis. J Neuroimaging. 2020;30:351-8.
• Ciarmiello A, Cannella M, Lastoria S, et al. Brain white-matter volume loss and glucose hypometabolism precede the clinical symptoms of Huntington’s disease. J Nucl Med. 2006;47:215-22.
• Matsui JT, Vaidya, JG, Johnson HJ, et al. Diffusion weighted imaging of prefrontal cortex in prodromal Huntington’s disease. Hum Brain Mapp. 2014;35:1562-73.
• Klöppel S, Draganski B, Golding CV, et al. White matter connections reflect changes in voluntary-guided saccades in pre-symptomatic Huntington’s disease. Brain. 2008;13:196-204.
• Novak MJU, Seunarine KK, Gibbard CR, et al. White matter integrity in premanifest and early Huntington’s disease is related to caudate loss and disease progression. Cortex. 2014;52:98-112.
• Di Carlo DT, Benedetto N, Duffau H, et al. Microsurgical anatomy of the sagittal stratum. Acta Neurochirurgica. 2019;161:2319-27.
• Harrington DL, Smith MM, Zhang Y, et al. Cognitive domains that predict time to diagnosis in prodromal Huntington disease. J Neurol Neurosurg Psychiatry. 2012;83:612-9.
• Rosas HD, Tuch DS, Hevelone ND, et al. Diffusion tensor imaging in presymptomatic and early Huntington's disease: Selective white matter pathology and its relationship to clinical measures. Mov Disord. 2006;21:1317-25.
• Rosas HD, Lee SY, Bender AC, et al. Altered white matter microstructure in the corpus callosum in Huntington's disease: Implications for cortical “disconnection”. NeuroImage. 2010;49:2995-3004.
• Mazerolle E, D’Arcy RC, Beyea SD. Detecting functional magnetic resonance imaging activation in white matter: interhemispheric transfer across the corpus callosum. BMC Neurosci. 2008;9:84.
• Liu W, Yang J, Burgunder J, et al. Diffusion imaging studies of Huntington's disease: a meta-analysis. Parkinsonism & Related Disorders, 2016;32:94-101.
• Odish OFF, Reijntjes RHAM, van den Bogaard SJA, et al. Progressive microstructural changes of the occipital cortex in Huntington’s disease. Brain Imaging and Behavior, 2018;12:1786-94.