Magnetic resonance imaging of postmortem human brain specimens: methodological considerations and prospects in psychoradiology

Abstract

Ex vivo magnetic resonance imaging (MRI) has revolutionized psychoradiological research by enabling detailed structural and pathological assessments of the brain in conditions ranging from psychiatric disorders to neurodegenerative diseases. By providing high-resolution images of postmortem brain tissue, ex vivo MRI overcomes several limitations inherent in in vivo imaging, offering unparalleled insights into the underlying pathophysiology of mental disorders. This review critically summarizes the state-of-the-art ex vivo MRI methodologies for neuroanatomical mapping and pathological characterization in psychoradiology, while also establishing standardized specimen processing protocols. Furthermore, we explore the prospects of application in ex vivo MRI in schizophrenia, major depressive disorder and bipolar disorder, highlighting its role in understanding neuroanatomical alterations, disease progression, and the validation of in vivo neuroimaging biomarkers.

Keywords

psychoradiology / magnetic resonance imaging / ex vivo brain / psychiatric disorders

Supplementary data

Supplementary data are available at PSYRAD Journal online.

Author contributions

Junye Yao (Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Resources, Validation, Visualization, Writing - original draft, Writing - review & editing), Zihan Zhou (Data curation, Investigation), Qiqi Tong (Data curation, Investigation), Lingyu Li (Investigation), Jintao Wei (Investigation), Jing Lu (Writing - review & editing), Shaohua Hu (Writing - review & editing), Aimin Bao (Supervision, Writing - review & editing), and Hongjian He (Conceptualization, Funding acquisition, Project administration, Supervision, Writing - review & editing).

Conflict of interests

The authors declare no conflicts of interest.

Acknowledgments

This work was supported by the National Natural Science Foundation of China (82372036), “Leading Goose” R&D Program of Zhejiang (2023C03094), and Open Research Fund of the State Key Laboratory of Cognitive Neuroscience and Learning (CNLZD2001).

References

[1] Alkemade A, Großmann R, Bazin PL., et al. (2023) Mixed methodology in human brain research: integrating MRI and histology. Brain Struct Funct. 228:1399-410. https://doi.org/10.1007/s00429-023-02675-2.

[2] Alkemade A, Pine K, Kirilina E., et al. (2020) 7 Tesla MRI followed by histological 3D reconstructions in whole-brain specimens. Front Neuroanat. 14:536838. https://doi.org/10.3389/fnana.2020.536838.

[3] Anderson KM, Collins MA, Kong R., et al. (2020) Convergent molecular, cellular, and cortical neuroimaging signatures of major depressive disorder. Proc Nat Acad Sci USA. 117:25138-49. https://doi.org/10.1073/pnas.2008004117.

[4] Arnatkeviciute A, Fulcher BD, Bellgrove MA., et al. (2021) Where the genome meets the connectome: understanding how genes shape human brain connectivity. Neuroimage. 244:118570.

[5] Arnatkeviciute A, Markello RD, Fulcher BD., et al. (2023) Toward best practices for imaging transcriptomics of the human brain. Biol Psychiatry. 93:391-404.

[6] Bilgic B, Pfefferbaum A, Rohlfing T., et al. (2012) MRI estimates of brain iron concentration in normal aging using quantitative susceptibility mapping. Neuroimage. 59:2625-35. https://doi.org/10.1016/j.neuroimage.2011.08.077.

[7] Busch JR, Lundemose SB, Lynnerup N., et al. (2019) Post-mortem MRI-based volumetry of the hippocampus in forensic cases of decedents with severe mental illness. Forensic Sci Med Pathol. 15:213-7. https://doi.org/10.1007/s12024-019-00101-w.

[8] Correll CU, Detraux J, De Lepeleire J, et al. (2015) Effects of antipsychotics, antidepressants and mood stabilizers on risk for physical diseases in people with schizophrenia, depression and bipolar disorder. World Psychiatry. 14:119-36. doi: 10.1002/wps.20204

[9] D'Arceuil H, De Crespigny A. (2007) The effects of brain tissue decomposition on diffusion tensor imaging and tractography. Neuroimage. 36:64-8. https://doi.org/10.1016/j.neuroimage.2007.02.039.

[10] Dawe RJ, Bennett DA, Schneider JA., et al. (2009) Postmortem MRI of human brain hemispheres: t 2 relaxation times during formaldehyde fixation. Magn Reson Med. 61:810-8. https://doi.org/10.1002/mrm.21909.

[11] Deramecourt V, Slade JY, Oakley AE., et al. (2012) Staging and natural history of cerebrovascular pathology in dementia. Neurology. 78:1043-50. 10.1212/WNL.0b013e31824e8e7f

[12] Di Biase MA, Zalesky A, Cetin-Karayumak S., et al. (2021) Large-scale evidence for an association between peripheral inflammation and white matter free water in schizophrenia and healthy individuals. Schizophr Bull. 47:542-51. https://doi.org/10.1093/schbul/sbaa134.

[13] Dickson DW, Braak H, Duda JE., et al. (2009) Neuropathological assessment of Parkinson's disease: refining the diagnostic criteria. Lancet Neurol. 8:1150-7. https://doi.org/10.1016/S1474-4422(09)70238-8.

[14] Dyrby TB, Søgaard LV, Hall MG., et al. (2013) Contrast and stability of the axon diameter index from microstructure imaging with diffusion MRI. Magn Reson Med. 70:711-21.

[15] Elliott LT, Sharp K, Alfaro-Almagro F., et al. (2018) Genome-wide association studies of brain imaging phenotypes in UK Biobank. Nature. 562:210-6. https://doi.org/10.1038/s41586-018-0571-7.

[16] Foxley S, Jbabdi S, Clare S., et al. (2014) Improving diffusion-weighted imaging of post-mortem human brains: SSFP at 7T. Neuroimage. 102:579-89. https://doi.org/10.1016/j.neuroimage.2014.08.014.

[17] Gigante AD, Young LT, Yatham LN., et al. (2011) Morphometric post-mortem studies in bipolar disorder : possible association with oxidative stress and apoptosis. Int J Neuropsychopharmacol. 14:1075-89. https://doi.org/10.1017/S146114571000146X.

[18] Giridharan VV, Sayana P, Pinjari OF., et al. (2020) Postmortem evidence of brain inflammatory markers in bipolar disorder: a systematic review. Mol Psychiatry. 25:94-113. https://doi.org/10.1038/s41380-019-0448-7.

[19] Hawrylycz MJ, Lein ES, Guillozet-Bongaarts AL., et al. (2012) An anatomically comprehensive atlas of the adult human brain transcriptome. Nature. 489:391-9.

[20] Heij J, Van Der Zwaag W, Knapen T., et al. (2024) Quantitative MRI at 7-tesla reveals novel frontocortical myeloarchitecture anomalies in major depressive disorder. Transl Psychiatry. 14. 262. https://doi.org/10.1038/s41398-024-02976-y.

[21] Howes OD, Cummings C, Chapman GE., et al. (2023) Neuroimaging in schizophrenia: an overview of findings and their implications for synaptic changes. Neuropsychopharmacology. 48:151-67. https://doi.org/10.1038/s41386-022-01426-x.

[22] Howes OD, Williams M, Ibrahim K., et al. (2013) Midbrain dopamine function in schizophrenia and depression: a post-mortem and positron emission tomographic imaging study. Brain. 136:3242-51. https://doi.org/10.1093/brain/awt264.

[23] Hyman BT, Phelps CH, Beach TG., et al. (2012) National Institute on Aging-Alzheimer's Association guidelines for the neuropathologic assessment of Alzheimer's disease. Alzheimers Dementia. 8:1-13. https://doi.org/10.1016/j.jalz.2011.10.007.

[24] Jonkman LE, de Graaf YG, Bulk M., et al. (2019) Normal Aging Brain Collection Amsterdam (NABCA): a comprehensive collection of postmortem high-field imaging, neuropathological and morphometric datasets of non-neurological controls. NeuroImage: Clinical. 22:101698. https://doi.org/10.1016/j.nicl.2019.101698.

[25] Kelm ND, West KL, Carson RP., et al. (2016) Evaluation of diffusion kurtosis imaging in ex vivo hypomyelinated mouse brains. Neuroimage. 124:612-26. https://doi.org/10.1016/j.neuroimage.2015.09.028.

[26] Kumar J, Liddle EB, Fernandes CC., et al. (2020) Glutathione and glutamate in schizophrenia:a 7T MRS study. Mol Psychiatry. 25:873-82. https://doi.org/10.1038/s41380-018-0104-7.

[27] Lerch JP, Van Der Kouwe AJW, Raznahan A., et al. (2017) Studying neuroanatomy using MRI. Nat Neurosci. 20:314-26.

[28] Mabry SJ, McCollum LA, Farmer CB., et al. (2020) Evidence for altered excitatory and inhibitory tone in the post-mortem substantia nigra in schizophrenia. World J Biol Psychiatry. 21:339-56. https://doi.org/10.1080/15622975.2019.1615638.

[29] Marques JP, Kober T, Krueger G., et al. (2010) MP2RAGE, a self bias-field corrected sequence for improved segmentation and T1-mapping at high field. Neuroimage. 49:1271-81. https://doi.org/10.1016/j.neuroimage.2009.10.002.

[30] McCutcheon RA, Abi-Dargham A, Howes OD. (2019) Schizophrenia, dopamine and the striatum: from biology to symptoms. Trends Neurosci. 42:205-20. https://doi.org/10.1016/j.tins.2018.12.004.

[31] McKenna FF, Miles L, Babb JS., et al. (2019) Diffusion kurtosis imaging of gray matter in schizophrenia. Cortex. 121:201-24. https://doi.org/10.1016/j.cortex.2019.08.013.

[32] McRobbie DW, Moore EA, Graves MJ., et al. (2017) MRI from Picture to Proton. Cambridge University PressCambridge

[33] Miller JA, Ding S-L, Sunkin SM., et al. (2014) Transcriptional landscape of the prenatal human brain. Nature. 508:199-206.

[34] Miller KL, Stagg CJ, Douaud G., et al. (2011) Diffusion imaging of whole, post-mortem human brains on a clinical MRI scanner. Neuroimage. 57:167-81. https://doi.org/10.1016/j.neuroimage.2011.03.070.

[35] Monosov IE, Haber SN, Leuthardt EC., et al. (2020) Anterior cingulate cortex and the control of dynamic behavior in primates. Current Biol: CB. 30:R1442-54. https://doi.org/10.1016/j.cub.2020.10.009.

[36] Naaldijk YM, Bittencourt MC, Sack U., et al. (2016) Kinins and microglial responses in bipolar disorder: a neuroinflammation hypothesis. Biol Chem. 397:283-96. https://doi.org/10.1515/hsz-2015-0257.

[37] Oestreich LKL, Sullivan MJO. (2022) Transdiagnostic In vivo magnetic resonance imaging markers of neuroinflammation. Biol Psychiatry Cogn Neurosci Neuroimaging. 7:638-58. https://doi.org/10.1016/j.bpsc.2022.01.003.

[38] Osimo EF, Beck K, et al. (2019) Synaptic loss in schizophrenia: a meta-analysis and systematic review of synaptic protein and mRNA measures. Mol Psychiatry. 24:549-61. https://doi.org/10.1038/s41380-018-0041-5.

[39] Pizzagalli DA, Roberts AC. (2022) Prefrontal cortex and depression. Neuropsychopharmacology. 47:225-46. https://doi.org/10.1038/s41386-021-01101-7.

[40] Qiu W, Zhang H, Bao A., et al. (2019) Standardized operational protocol for Human brain banking in China. Neurosci Bull. 35:270-6. https://doi.org/10.1007/s12264-018-0306-7.

[41] Ramaker RC, Bowling KM, Lasseigne BN., et al. (2017) Post-mortem molecular profiling of three psychiatric disorders. Genome Med. 9:72. https://doi.org/10.1186/s13073-017-0458-5.

[42] Reichenbach JR, Schweser F, Serres B., et al. (2015) Quantitative susceptibility mapping: concepts and applications. Clin Neuroradiol. 25:225-30. https://doi.org/10.1007/s00062-015-0432-9.

[43] Roebroeck A, Miller KL, Aggarwal M. (2019) Ex vivo diffusion MRI of the human brain: technical challenges and recent advances. NMR Biomed. 32:1-14. https://doi.org/10.1002/nbm.3941.

[44] Saccaro LF, Crokaert J, Perroud N., et al. (2023) Structural and functional MRI correlates of inflammation in bipolar disorder: a systematic review. J Affect Disord. 325:83-92. https://doi.org/10.1016/j.jad.2022.12.162.

[45] Schmaal L, Hibar DP, Sämann PG., et al. (2017) Cortical abnormalities in adults and adolescents with major depression based on brain scans from 20 cohorts worldwide in the ENIGMA Major Depressive Disorder Working Group. Mol Psychiatry. 22:900-9. https://doi.org/10.1038/mp.2016.60.

[46] Shepherd TM, Flint JJ, Thelwall PE., et al. (2009a) Postmortem interval alters the water relaxation and diffusion properties of rat nervous tissue—Implications for MRI studies of human autopsy samples. Neuroimage. 44:820-6.

[47] Shibukawa S, Kan H, Honda S., et al. (2024) Alterations in subcortical magnetic susceptibility and disease-specific relationship with brain volume in major depressive disorder and schizophrenia. Transl Psychiatry. 14:164. https://doi.org/10.1038/s41398-024-02862-7.

[48] Sneeboer MAM, Snijders GJLJ, Berdowski WM., et al. (2019) Microglia in post-mortem brain tissue of patients with bipolar disorder are not immune activated. Transl Psychiatry. 9. 153. https://doi.org/10.1038/s41398-019-0490-x.

[49] Tendler BC, Foxley S, Cottaar M., et al. (2020) Modeling an equivalent b-value in diffusion-weighted steady-state free precession. Magn Reson Med. 84:873-84. https://doi.org/10.1002/mrm.28169.

[50] van der Pluijm M, Wengler K, Reijers PN., et al. (2024) Neuromelanin-sensitive MRI as candidate marker for treatment resistance in first-episode schizophrenia. Am J Psychiatry. 181:512-9. https://doi.org/10.1176/appi.ajp.20220780.

[51] van Hooijdonk CFM, van der Pluijm M, Bosch I., et al. (2023) The substantia nigra in the pathology of schizophrenia: a review on post-mortem and molecular imaging findings. Eur Neuropsychopharmacol. 68:57-77. https://doi.org/10.1016/j.euroneuro.2022.12.008.

[52] van Wijk BCM, Alkemade A, Forstmann BU. (2020) Functional segregation and integration within the human subthalamic nucleus from a micro- and meso-level perspective. Cortex. 131:103-13. https://doi.org/10.1016/j.cortex.2020.07.004.

[53] Wang Y, Liu T. (2015) Quantitative susceptibility mapping (QSM): decoding MRI data for a tissue magnetic biomarker. Magn Reson Med. 73:82-101. https://doi.org/10.1002/mrm.25358.

[54] Yao J, Li Z, Zhou Z., et al. (2024) Distinct regional vulnerability to Aβ and iron accumulation in post mortem AD brains. Alzheimers Dementia. 20:6984-97. https://doi.org/10.1002/alz.14188.

[55] Yao J, Tendler BC, Zhou Z., et al. (2023) Both noise-floor and tissue compartment difference in diffusivity contribute to FA dependence on b -value in diffusion MRI. Hum Brain Mapp. 44:1371-88. https://doi.org/10.1002/hbm.26121.

[56] Yao S, Zhong Y, Xu Y., et al. (2017) Quantitative susceptibility mapping reveals an association between brain iron load and depression severity. Front Hum Neurosci. 11. 442. https://doi.org/10.3389/fnhum.2017.00442.

[57] Zhang D, Zhou L, Shi Y., et al. (2023) Increased free water in the substantia nigra in asymptomatic LRRK2 G2019S mutation carriers. Mov Disord. 38:138-42.

[58] Zhou Z, Tong Q, Zhang L., et al. (2020) Evaluation of the diffusion MRI white matter tract integrity model using myelin histology and Monte-Carlo simulations. Neuroimage. 223:117313. https://doi.org/10.1016/j.neuroimage.2020.117313.

[59] Zhu J, Chen X, Lu B., et al. (2024) Transcriptomic decoding of regional cortical vulnerability to major depressive disorder. Commun Biol. 7. 960. https://doi.org/10.1038/s42003-024-06665-w.