Magnetic Resonance Imaging (MRI) has revolutionized our ability to non-invasively study the brain's structural and functional properties. However, detecting myelin, a crucial component of white matter, remains challenging due to its indirect visibility on conventional MRI scans. Myelin plays a vital role in neural signal transmission and is associated with various neurological conditions. Understanding myelin distribution and content is crucial for insights into brain development, aging, and neurological disorders. Although specialized MRI sequences can estimate myelin content, these are time-consuming. Also, many patients sent to specialized neurological centers have an MRI of the brain already scanned. In this study, we focused on techniques utilizing standard MRI T1-weighted (T1w) and T2 weighted (T2w) sequences commonly used in brain imaging protocols. We evaluated the applicability of the T1w/T2w ratio in assessing myelin content by comparing it to quantitative T1 mapping (qT1). Our study included 1 healthy adult control and 7 neurologic patients (comprising both pediatric and adult populations) with epilepsy originating from focal epileptogenic lesions visible on MRI structural scans. Following image acquisition on a 3T Siemens Vida scanner, datasets were co registered, and segmented into anatomical regions using the Fastsurfer toolbox, and T1w/T2w ratio maps were calculated in Matlab software. We further assessed interhemispheric differences in volumes of individual structures, their signal intensity, and the correlation of the T1w/T2w ratio to qT1. Our data demonstrate that in situations where a dedicated myelin-sensing sequence such as qT1 is not available, the T1w/T2w ratio provides significantly better information than T1w alone. By providing indirect information about myelin content, this technique offers a valuable tool for understanding the neurobiology of myelin-related conditions using basic brain scans.

Department of Pathophysiology 2nd Faculty of Medicine Charles University Praha 5 Czech Republic

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Chang WC, Kudlacek J, Hlinka J, Chvojka J, Hadrava M, Kumpost V, Powell AD, et al. Loss of neuronal network resilience precedes seizures and determines the ictogenic nature of interictal synaptic perturbations. Nat Neurosci. 2018;21:1742–1752. doi: 10.1038/s41593-018-0278-y. PubMed DOI

Noda AH, Hermsen A, Berkenfeld R, Dennig D, Endrass G, Kaltofen J, Safavi A, et al. Evaluation of costs of epilepsy using an electronic practice management software in Germany. Seizure. 2015;26:49–55. doi: 10.1016/j.seizure.2015.01.010. PubMed DOI

West S, Nolan SJ, Cotton J, Gandhi S, Weston J, Sudan A, Ramirez R, Newton R. Surgery for epilepsy. Cochrane Database Syst Rev. 2015;(7):CD010541. doi: 10.1002/14651858.CD010541.pub2. PubMed DOI

Blumcke I, Spreafico R, Haaker G, Coras R, Kobow K, Bien CG, Pfäfflin M, et al. Histopathological findings in brain tissue obtained during epilepsy surgery. New Engl J Med. 2017;377:1648–1656. doi: 10.1056/NEJMoa1703784. PubMed DOI

Krsek P, Maton B, Jayakar P, Dean P, Korman B, Rey G, Dunoyer C, et al. Incomplete resection of focal cortical dysplasia is the main predictor of poor postsurgical outcome. Neurology. 2009;72:217–223. doi: 10.1212/01.wnl.0000334365.22854.d3. PubMed DOI

Blümcke I, Thom M, Aronica E, Armstrong DD, Vinters HV, Palmini A, Jacques TS, et al. The clinicopathologic spectrum of focal cortical dysplasias: a consensus classification proposed by an ad hoc Task Force of the ILAE Diagnostic Methods Commission. Epilepsia. 2011;52:158–174. doi: 10.1111/j.1528-1167.2010.02777.x. PubMed DOI PMC

Krsek P, Pieper T, Karlmeier A, Hildebrandt M, Kolodziejczyk D, Winkler P, Pauli E, et al. Different presurgical characteristics and seizure outcomes in children with focal cortical dysplasia type I or II. Epilepsia. 2009;50:125–137. doi: 10.1111/j.1528-1167.2008.01682.x. PubMed DOI

Kreilkamp BAK, Das K, Wieshmann UC, Biswas S, Marson AG, Keller SS. Neuroradiological findings in patients with “non-lesional” focal epilepsy revealed by research protocol. Clin Radiol. 2018;74:78.e1–78.e11. doi: 10.1016/j.crad.2018.08.013. PubMed DOI

Wong-Kisiel LC, Blauwblomme T, Ho ML, Boddaert N, Parisi J, Wirrell E, Nabbout R. Challenges in managing epilepsy associated with focal cortical dysplasia in children. Epilepsy Res. 2018;145:1–17. doi: 10.1016/j.eplepsyres.2018.05.006. PubMed DOI

Shepherd C, Liu J, Goc J, Martinian L, Jacques TS, Sisodiya SM, Thom M. A quantitative study of white matter hypomyelination and oligodendroglial maturation in focal cortical dysplasia type II. Epilepsia. 2013;54:898–908. doi: 10.1111/epi.12143. PubMed DOI PMC

Scholl T, Mühlebner A, Ricken G, Gruber V, Fabing A, Samueli S, Gröppel G, et al. Impaired oligodendroglial turnover is associated with myelin pathology in focal cortical dysplasia and tuberous sclerosis complex. Brain Pathol. 2017;27:770–780. doi: 10.1111/bpa.12452. PubMed DOI PMC

van der Weijden CWJ, García DV, Borra RJH, Thurner P, Meilof JF, van Laar P-J, Dierckx RAJO, et al. Myelin quantification with MRI: A systematic review of accuracy and reproducibility. Neuroimage. 2021;226:117561. doi: 10.1016/j.neuroimage.2020.117561. PubMed DOI

Kynčl M, Holubová Z, Tintěra J, Profantova N, Šanda J, Kala D, Prysiazhniuk Y, et al. Recommendations for structural brain MRI in the diagnosis of epilepsy. Ceska a Slovenska Neurologie a Neurochirurgie. 2023;86:18–24.

Ganzetti M, Wenderoth N, Mantini D. Whole brain myelin mapping using T1- and T2-weighted MR imaging data. Front Hum Neurosci. 2014;8:671. doi: 10.3389/fnhum.2014.00671. PubMed DOI PMC

Ganzetti M, Wenderoth N, Mantini D. Mapping pathological changes in brain structure by combining T1- and T2-weighted MR imaging data. Neuroradiology. 2015;57:917. doi: 10.1007/s00234-015-1550-4. PubMed DOI PMC

Iwatani J, Ishida T, Donishi T, Ukai S, Shinosaki K, Terada M, Kaneoke Y. Use of T1-weighted/T2-weighted magnetic resonance ratio images to elucidate changes in the schizophrenic brain. Brain Behav. 2015;5:399. doi: 10.1002/brb3.399. PubMed DOI PMC

Chen H, Budin F, Noel J, Prieto JC, Gilmore J, Rasmussen J, Wadhwa PD, et al. White matter fiber-based analysis of T1w/T2w ratio map. Proc SPIE Int Soc Opt Eng. 2017;10133:101330P. doi: 10.1117/12.2254467. PubMed DOI PMC

Scott KT. SPACE: An Innovative Solution to Rapid, Low SAR, T2-Weighted Contrast in 3D Spin Echo Imaging. Siemens Medical Solutions; Published online 2009.

Henschel L, Conjeti S, Estrada S, Diers K, Fischl B, Reuter M. FastSurfer - A fast and accurate deep learning based neuroimaging pipeline. Neuroimage. 2020;219:117012. doi: 10.1016/j.neuroimage.2020.117012. PubMed DOI PMC

Kazemi K, Noorizadeh N. Quantitative Comparison of SPM, FSL, and Brainsuite for Brain MR Image Segmentation. J Biomed Phys Eng. 2014;4:13–26. PubMed PMC

Glasser MF, van Essen DC. Mapping Human Cortical Areas In Vivo Based on Myelin Content as Revealed by T1- and T2-Weighted MRI. J Neurosci. 2011;31:11597–11616. doi: 10.1523/JNEUROSCI.2180-11.2011. PubMed DOI PMC

Uddin MN, Figley TD, Marrie RA, Figley CR. Can T1w/T2w ratio be used as a myelin-specific measure in subcortical structures? Comparisons between FSE-based T1w/T2w ratios, GRASE-based T1w/T2w ratios and multi-echo GRASE-based myelin water fractions. NMR Biomed. 2018;31:e3868. doi: 10.1002/nbm.3868. PubMed DOI

Margaret Cheng HL, Stikov N, Ghugre NR, Wright GA. Practical medical applications of quantitative MR relaxometry. J Magn Reson Imaging. 2012;36:805–824. doi: 10.1002/jmri.23718. PubMed DOI

Luzzi S, Elia A, Del Maestro M, Elbabaa SK, Carnevale S, Guerrini F, Caulo M, et al. Dysembryoplastic Neuroepithelial Tumors: What You Need to Know. World Neurosurg. 2019;127:255–265. doi: 10.1016/j.wneu.2019.04.056. PubMed DOI

Scelsi CL, Rahim TA, Morris JA, Kramer GJ, Gilbert BC, Forseen SE. The Lateral Ventricles: A Detailed Review of Anatomy, Development, and Anatomic Variations. AJNR Am J Neuroradiol. 2020;41:566–572. doi: 10.3174/ajnr.A6456. PubMed DOI PMC

Piredda GF, Hilbert T, Thiran JP, Kober T. Probing myelin content of the human brain with MRI: A review. Magn Reson Med. 2021;85:627–652. doi: 10.1002/mrm.28509. PubMed DOI

Kala D, Šulc V, Olšerová A, Svoboda J, Prysiazhniuk Y, Pošusta A, Kynčl M, et al. Evaluation of blood-brain barrier integrity by the analysis of dynamic contrast-enhanced MRI - a comparison of quantitative and semi-quantitative methods. Physiol Res. 2022;71(Suppl 2):S259–S275. doi: 10.33549/physiolres.934998. PubMed DOI PMC