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source-based morphometry reveals structural brain pattern abnormalities in 22q11.2 deletion syndrome

HUMAN BRAIN MAPPING 2024年第1期45卷 e26553-e26553页

作者： Ge, Ruiyang Ching, Christopher R. K. Bassett, Anne S. Kushan, Leila Antshel, Kevin M. van Amelsvoort, Therese Bakker, Geor Butcher, Nancy J. Campbell, Linda E. Chow, Eva W. C. Craig, Michael Crossley, Nicolas A. Cunningham, Adam Daly, Eileen Doherty, Joanne L. Durdle, Courtney A. Emanuel, Beverly S. Fiksinski, Ania Forsyth, Jennifer K. Fremont, Wanda Goodrich-Hunsaker, Naomi J. Gudbrandsen, Maria Gur, Raquel E. Jalbrzikowski, Maria Kates, Wendy R. Lin, Amy Linden, David E. J. Mccabe, Kathryn L. McDonald-McGinn, Donna Moss, Hayley Murphy, Declan G. Murphy, Kieran C. Owen, Michael J. Villalon-Reina, Julio E. Repetto, Gabriela M. Roalf, David R. Ruparel, Kosha Schmitt, J. Eric Schuite-Koops, Sanne Angkustsiri, Kathleen Sun, Daqiang Vajdi, Ariana van den Bree, Marianne Vorstman, Jacob Thompson, Paul M. Vila-Rodriguez, Fidel Bearden, Carrie E. Univ British Columbia Dept Psychiat Vancouver BC Canada Univ British Columbia Djavad Mowafaghian Ctr Brain Hlth Vancouver BC Canada Univ Southern Calif Imaging Genet Ctr Los Angeles CA 90007 USA Ctr Addict & Mental Hlth Clin Genet Res Program Toronto ON Canada Univ Hlth Network Toronto Gen Hosp Res Inst Dept Psychiat Dept MedDalglish Family 22q Clin Toronto ON Canada Campbell Family Mental Hlth Res Inst Ctr Addict & Mental Hlth Toronto ON Canada Univ Toronto Dept Psychiat Toronto ON Canada Univ Calif Los Angeles Semel Inst Neurosci & Human Behav Dept Psychiat & Biobehav Sci Los Angeles CA USA Syracuse Univ Dept Psychol Syracuse NY USA Maastricht Univ Dept Psychiat & Neuropsychol Maastricht Netherlands Hosp Sick Children Child Hlth Evaluat Sci Toronto ON Canada Univ Newcastle Sch Psychol Sci Callaghan Australia Kings Coll London Dept Forens & Neurodev Sci Sackler Inst Translat Neurodev Inst Psychiat Psychol & Neurosci London England Bethlem Royal & Maudsley Hosp Beckenham Kent England Periodista Pontificia Univ Catol Chile Santiago Chile Cardiff Univ MRC Ctr Neuropsychiat Genet & Genom Div Psychol Med & Clin Neurosci Cardiff Wales Cardiff Univ Cardiff Univ Brain Res Imaging Ctr CUBRIC Sch Psychol Cardiff Wales UC Davis MIND Inst Davis CA USA UC Santa Barbara Dept Psychol & Brain Sci Santa Barbara CA USA Childrens Hosp Philadelphia Div Human Genet Philadelphia PA USA Univ Penn Perelman Sch Med Dept Pediat Philadelphia PA USA Univ Med Ctr Utrecht Wilhelmina Childrens Hosp Dept Pediat Utrecht Netherlands Maastricht Univ Dept Psychiat & Neuropsychol Sch Mental Hlth & Neurosci MHeNS Maastricht Netherlands Univ Washington Dept Psychol Seattle WA USA State Univ New York Upstate Med Univ Dept Psychiat & Behav Sci Syracuse NY 13210 USA Univ Utah Dept Neurol Salt Lake City UT USA Univ Roehampton Sch Psychol Psychol London England Univ Penn Childrens Hosp Philadelphia Perelman Sch Med Dept Radiol Philadelphia PA USA Harvard

22q11.2 deletion syndrome (22q11DS) is the most frequently occurring microdeletion in humans. It is associated with a significant impact on brain structure, including prominent reductions in gray matter volume (GMV), and neuropsychiatric manifestations, including cognitive impairment and psychosis. It is unclear whether GMV alterations in 22q11DS occur according to distinct structural patterns. Then, 783 participants (470 with 22q11DS: 51% females, mean age [SD] 18.2 [9.2];and 313 typically developing [TD] controls: 46% females, mean age 18.0 [8.6]) from 13 datasets were included in the present study. We segmented structural T1-weighted brain MRI scans and extracted GMV images, which were then utilized in a novel source-based morphometry (SBM) pipeline (SS-Detect) to generate structural brain patterns (SBPs) that capture co-varying GMV. We investigated the impact of the 22q11.2 deletion, deletion size, intelligence quotient, and psychosis on the SBPs. Seventeen GMV-SBPs were derived, which provided spatial patterns of GMV covariance associated with a quantitative metric (i.e., loading score) for analysis. Patterns of topographically widespread differences in GMV covariance, including the cerebellum, discriminated individuals with 22q11DS from healthy controls. The spatial extents of the SBPs that revealed disparities between individuals with 22q11DS and controls were consistent with the findings of the univariate voxel-based morphometry analysis. Larger deletion size was associated with significantly lower GMV in frontal and occipital SBPs;however, history of psychosis did not show a strong relationship with these covariance patterns. 22q11DS is associated with distinct structural abnormalities captured by topographical GMV covariance patterns that include the cerebellum. Findings indicate that structural anomalies in 22q11DS manifest in a nonrandom manner and in distinct covarying anatomical patterns, rather than a diffuse global process. These SBP abnormalities co

关键词： 22q11 deletion syndrome gray matter volume magnetic resonnance imaging source-based morphometry

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Gray matter morphometric biomarkers for distinguishing manganese-exposed welders from healthy adults revealed by source-based morphometry

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NEUROTOXICOLOGY 2024年 103卷 222-229页

作者： Wu, Jiayu Zhang, Qiaoying Ma, Mingyue Dong, Yan Sun, Pengfeng Gao, Ming Liu, Peng Wu, Xiaoping Xi An Jiao Tong Univ Affiliated Xian Cent Hosp Dept Radiol Xian Peoples R China Xidian Univ Life Sci Res Ctr Sch Life Sci & Technol Xian Shaanxi Peoples R China Xidian Univ Engn Res Ctr Mol & Neuro Imaging Sch Life Sci & Technol Minist Educ Xian Shaanxi Peoples R China

Background: Chronic overexposure to manganese (Mn) may result in neurotoxicity, which is characterized by motor and cognitive dysfunctions. This study aimed to utilize multivariate source-based morphometry (SBM) to explore the biomarkers for distinguishing Mn-exposed welders from healthy controls (HCs). Methods: High-quality 3D T1-weighted MRI scans were obtained from 45 Mn-exposed full-time welders and 33 age-matched HCs in this study. After extracting gray matter structural covariation networks by SBM, multiple classic interaction linear models were applied to investigate distinct patterns in welders compared to HCs, and Ztransformed loading coefficients were compared between the two groups. A receiver operating characteristic (ROC) curve was used to identify potential biomarkers for distinguishing Mn-exposed welders from HCs. Additionally, we assessed the relationships between clinical features and gray matter volumes in the welders group. Results: A total of 78 subjects (45 welders, mean age 46.23 +/- 4.93 years;33 HCs, mean age 45.55 +/- 3.40 years) were evaluated. SBM identified five components that differed between the groups. These components displayed lower loading weights in the basal ganglia, thalamus, default mode network (including the lingual gyrus and precuneus), and temporal lobe network (including the temporal pole and parahippocampus), as well as higher loading weights in the sensorimotor network (including the supplementary motor cortex). ROC analysis identified the highest classification power in the thalamic network. Conclusions: Altered brain structures might be implicated in Mn overexposure-related disturbances in motivative modulation, cognitive control and information integration. These results encourage further studies that focus on the interaction mechanisms, including the basal ganglia network, thalamic network and default mode network. Our study identified potential neurobiological markers in Mn-exposed welders and illustrated the utilit

关键词： Manganese exposure Magnetic resonance imaging Biomarkers source-based morphometry Neurotoxicity

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Brain structural abnormalities in adult major depressive disorder revealed by voxel- and source-based morphometry: evidence from the REST-meta-MDD Consortium

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PSYCHOLOGICAL MEDICINE 2023年第8期53卷 3672-3682页

作者： Wang, KangCheng Hu, YuFei Yan, ChaoGan Li, MeiLing Wu, YanJing Qiu, Jiang Zhu, XingXing Shandong Normal Univ Sch Psychol Jinan Shandong Peoples R China Inst Psychol CAS Key Lab Behav Sci Beijing Peoples R China Univ Chinese Acad Sci Dept Psychol Beijing Peoples R China Chinese Acad Sci Magnet Resonance Imaging Res Ctr Inst Psychol Beijing Peoples R China Chinese Acad Sci Int Big Data Ctr Depress Res Inst Psychol Beijing Peoples R China Harvard Med Sch Athinoula A Martinos Ctr Biomed Imaging Massachusetts Gen Hosp Dept Radiol Charlestown MA 02129 USA Ningbo Univ Fac Foreign Languages Ningbo Zhejiang Peoples R China Southwest Univ Fac Psychol Chongqing 400716 Peoples R China Univ Glasgow Inst Hlth & Wellbeing Glasgow Lanark Scotland

Background Neuroimaging studies on major depressive disorder (MDD) have identified an extensive range of brain structural abnormalities, but the exact neural mechanisms associated with MDD remain elusive. Most previous studies were performed with voxel- or surface-based morphometry which were univariate methods without considering spatial information across voxels/vertices. Methods Brain morphology was investigated using voxel-based morphometry (VBM) and source-based morphometry (SBM) in 1082 MDD patients and 990 healthy controls (HCs) from the REST-meta-MDD Consortium. We first examined group differences in regional grey matter (GM) volumes and structural covariance networks between patients and HCs. We then compared first-episode, drug-naive (FEDN) patients, and recurrent patients. Additionally, we assessed the effects of symptom severity and illness duration on brain alterations. Results VBM showed decreased GM volume in various regions in MDD patients including the superior temporal cortex, anterior and middle cingulate cortex, inferior frontal cortex, and precuneus. SBM returned differences only in the prefrontal network. Comparisons between FEDN and recurrent MDD patients showed no significant differences by VBM, but SBM showed greater decreases in prefrontal, basal ganglia, visual, and cerebellar networks in the recurrent group. Moreover, depression severity was associated with volumes in the inferior frontal gyrus and precuneus, as well as the prefrontal network. Conclusions Simultaneous application of VBM and SBM methods revealed brain alterations in MDD patients and specified differences between recurrent and FEDN patients, which tentatively provide an effective multivariate method to identify potential neurobiological markers for depression.

关键词： Brain structure major depressive disorder source-based morphometry structural covariance network voxel-based morphometry

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Gray matter volume covariance networks are associated with altered emotional processing in bipolar disorder: a source-based morphometry study

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BRAIN IMAGING AND BEHAVIOR 2022年第2期16卷 738-747页

作者： Miola, Alessandro Trevisan, Nicolo Merola, Arcangelo Comini, Francesco Folena Olivo, Daniele Minerva, Matteo Valeggia, Silvia Toffanin, Tommaso Favaro, Angela Manara, Renzo Sambataro, Fabio Univ Padua Dept Neurosci DNS Via Giustiniani 5 Padua Italy Univ Padua Padova Neurosci Ctr Padua Italy

Widespread regional gray matter volume (GMV) alterations have been reported in bipolar disorder (BD). Structural networks, which are thought to better reflect the complex multivariate organization of the brain, and their clinical and psychological function have not been investigated yet in BD. 24 patients with BD type-I (BD-I), and 30 with BD type-II (BD-II), and 45 controls underwent MRI scan. Voxel-based morphometry and source-based morphometry (SBM) were performed to extract structural covariation patterns of GMV. SBM components associated with morphometric differences were compared among diagnoses. Executive function and emotional processing correlated with morphometric characteristics. Compared to controls, BD-I showed reduced GMV in the temporo-insular-parieto-occipital cortex and in the culmen. An SBM component spanning the prefrontal-temporal-occipital network exhibited significantly lower GMV in BD-I compared to controls, but not between the other groups. The structural network covariance in BD-I was associated with the number of previous manic episodes and with worse executive performance. Compared to BD-II, BD-I showed a loss of GMV in the temporal-occipital regions, and this was correlated with impaired emotional processing. Altered prefrontal-temporal-occipital network structure could reflect a neural signature associated with visuospatial processing and problem-solving impairments as well as emotional processing and illness severity in BD-I.

关键词： Bipolar disorder Voxel-based morphometry source-based morphometry Cognition Emotional processing

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Investigating sexual dimorphism in human brain structure by combining multiple indexes of brain morphology and source-based morphometry

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BRAIN STRUCTURE & FUNCTION 2022年第1期227卷 11-21页

作者： Del Mauro, Gianpaolo Del Maschio, Nicola Sulpizio, Simone Fedeli, Davide Perani, Daniela Abutalebi, Jubin Univ Vita Salute San Raffaele Fac Psychol Ctr Neurolinguist & Psycholinguist CNPL Via Olgettina 58 I-20132 Milan Italy Univ Vita Salute San Raffaele Fac Psychol Milan Italy Univ Milano Bicocca Dept Psychol Milan Italy Univ Milano Bicocca Milan Ctr Neurosci NeuroMi Milan Italy IRCCS San Raffaele Sci Inst Div Neurosci In Vivo Human Mol & Struct Neuroimaging Unit Milan Italy Osped San Raffaele Nucl Med Unit Milan Italy Arctic Univ Norway Tromso Norway

Computational morphometry of magnetic resonance images represents a powerful tool for studying macroscopic differences in human brains. In the present study (N participants = 829), we combined different techniques and measures of brain morphology to investigate one of the most compelling topics in neuroscience: sexual dimorphism in human brain structure. When accounting for overall larger male brains, results showed limited sex differences in gray matter volume (GMV) and surface area. On the other hand, we found larger differences in cortical thickness, favoring both males and females, arguably as a result of region-specific differences. We also observed higher values of fractal dimension, a measure of cortical complexity, for males versus females across the four lobes. In addition, we applied source-based morphometry, an alternative method for measuring GMV based on the independent component analysis. Analyses on independent components revealed higher GMV in fronto-parietal regions, thalamus and caudate nucleus for females, and in cerebellar- temporal cortices and putamen for males, a pattern that is largely consistent with previous findings.

关键词： Sex differences source-based morphometry Gray matter volume Surface area Cortical thickness Fractal dimension

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Amyloid-β prediction machine learning model using source-based morphometry across neurocognitive disorders

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SCIENTIFIC REPORTS 2024年第1期14卷 1-12页

作者： Momota, Yuki Bun, Shogyoku Hirano, Jinichi Kamiya, Kei Ueda, Ryo Iwabuchi, Yu Takahata, Keisuke Yamamoto, Yasuharu Tezuka, Toshiki Kubota, Masahito Seki, Morinobu Shikimoto, Ryo Mimura, Yu Kishimoto, Taishiro Tabuchi, Hajime Jinzaki, Masahiro Ito, Daisuke Mimura, Masaru Keio Univ Sch Med Dept Neuropsychiat 35 ShinanomachiShinjuku Ku Tokyo 1608582 Japan Keio Univ Hosp Off Radiat Technol 35 ShinanomachiShinjuku Ku Tokyo 1608582 Japan Keio Univ Sch Med Dept Radiol 35 ShinanomachiShinjuku Ku Tokyo 1608582 Japan Natl Inst Quantum Sci & Technol Inst Quantum Med Sci Dept Funct Brain Imaging Res 4-9-1 AnagawaInage Ku Chiba Shi Chiba 2638555 Japan Keio Univ Sch Med Dept Neurol 35 ShinanomachiShinjuku Ku Tokyo 1608582 Japan Keio Univ Sch Med Dept Physiol 35 ShinanomachiShinjuku Ku Tokyo 1608582 Japan Keio Univ Memory Ctr Sch Med 35 ShinanomachiShinjuku Ku Tokyo 1608582 Japan Donald & Barbara Zucker Sch Med Psychiat Dept Hempstead NY 11549 USA Keio Univ Sch Med Hills Joint Res Lab Future Prevent Med & Wellness Mori JP Tower 7F1-3-1 AzabudaiMinato Ku Tokyo 1060041 Japan Keio Univ Ctr Prevent Med Mori JP Tower 7th Floor1-3-1 AzabudaiMinato Ku Tokyo 1060041 Japan

Previous studies have developed and explored magnetic resonance imaging (MRI)-based machine learning models for predicting Alzheimer's disease (AD). However, limited research has focused on models incorporating diverse patient populations. This study aimed to build a clinically useful prediction model for amyloid-beta (A beta) deposition using source-based morphometry, using a data-driven algorithm based on independent component analyses. Additionally, we assessed how the predictive accuracies varied with the feature combinations. Data from 118 participants clinically diagnosed with various conditions such as AD, mild cognitive impairment, frontotemporal lobar degeneration, corticobasal syndrome, progressive supranuclear palsy, and psychiatric disorders, as well as healthy controls were used for the development of the model. We used structural MR images, cognitive test results, and apolipoprotein E status for feature selection. Three-dimensional T1-weighted images were preprocessed into voxel-based gray matter images and then subjected to source-based morphometry. We used a support vector machine as a classifier. We applied SHapley Additive exPlanations, a game-theoretical approach, to ensure model accountability. The final model that was based on MR-images, cognitive test results, and apolipoprotein E status yielded 89.8% accuracy and a receiver operating characteristic curve of 0.888. The model based on MR-images alone showed 84.7% accuracy. A beta-positivity was correctly detected in non-AD patients. One of the seven independent components derived from source-based morphometry was considered to represent an AD-related gray matter volume pattern and showed the strongest impact on the model output. A beta-positivity across neurological and psychiatric disorders was predicted with moderate-to-high accuracy and was associated with a probable AD-related gray matter volume pattern. An MRI-based data-driven machine learning approach can be beneficial as a diagnostic aid

关键词： Alzheimer's disease Amyloid-beta Machine learning Magnetic resonance imaging source-based morphometry

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Association of Serum Kynurenine Levels and Neural Networks in Patients with First-Episode, Drug-Naive Major Depression: A source-based morphometry Study

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NEUROPSYCHIATRIC DISEASE AND TREATMENT 2020年 16卷 2569-2577页

作者： Okamoto, Naomichi Watanabe, Keita Nguyen, LeHoa Ikenouchi, Atsuko Kishi, Taro Iwata, Nakao Kakeda, Shingo Korogi, Yukunori Yoshimura, Reiji Univ Occupat & Environm Hlth Dept Psychiat Kitakyushu Fukuoka 8078555 Japan Kyoto Univ Open Innovat Inst Kyoto Japan Vietnam Natl Univ Sch Med & Pharm Hanoi Vietnam Fujita Med Univ Dept Psychiat Toyoake Aichi Japan Hirosaki Univ Grad Sch Med Dept Radiol Hirosaki Aomori Japan Univ Occupat & Environm Hlth Dept Radiol Kitakyushu Fukuoka Japan

Purpose: The kynurenine (KYN) pathway can directly or indirectly influence cerebral volume and neural integrity in patients with major depression (MD). The aim of the present study was to investigate neural network systems and the KYN pathway in patients with firstepisode, drug-naive MD. Patients and Methods: Twenty right-handed drug-naive patients, with MD diagnosed using the Diagnostic and Statistical Manual for Mental Disorders, Fourth Edition, Text Revision, Research Version, were included in this study. Magnetic resonance imaging scans and scores on the Hamilton Rating Scale for Depression were assessed, and serum sampling was performed prior to the start of pharmacological treatment. Image processing and data analysis were performed according to our recently published procedure. Serum metabolomes were measured in the cation and anion modes of CE-FTMS-based metabolome analysis. Results: We found that serum KYN levels were positively correlated with the Z-scores of the salience network but not with those of the central executive network or default mode network. No associations were observed between serum glutamate levels and the Z-score of any of the three networks. Conclusion: Our results indicate that serum KYN levels might affect the activity of the salience network in first-episode, drug-naive patients with MD.

关键词： kynurenine major depression neural network source-based morphometry

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Common and different gray and white matter alterations in bipolar and borderline personality disorder: A source-based morphometry study

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BRAIN RESEARCH 2021年第0期1762卷 147401-147401页

作者： Lapomarda, Gaia Grecucci, Alessandro Messina, Irene Pappaianni, Edoardo Dadomo, Harold Univ Trento Dept Psychol & Cognit Sci Clin & Affect Neurosci Lab Rovereto Italy Univ Mercatorum Rome Italy Univ Geneva Fac Med Dept Psychiat Geneva Switzerland Univ Parma Dept Neurosci Parma Italy

According to the nosological classification, Bipolar Disorder (BD) and Borderline Personality Disorder (BPD) are different syndromes. However, these pathological conditions share a number of affective symptoms that make the diagnosis difficult. Affective symptoms range from abnormal mood swings, characterizing both BD and BPD, to regulation dysfunctions, more specific to BPD. To shed light on the neural bases of these aspects, and to better understand differences and similarities between the two disorders, we analysed for the first time gray and white matter features of both BD and BPD. Structural T1 images from 30 patients with BD, 20 with BPD, and 45 controls were analysed by capitalizing on an innovative whole-brain multivariate method known as source-based morphometry. Compared to controls, BD patients showed increased gray matter concentration (p = .003) in a network involving mostly subcortical structures and cerebellar areas, possibly related to abnormal mood experiences. Notably, BPD patients showed milder alterations in the same circuit, standing in the middle of a continuum between BD and controls. In addition to this, we found an altered white matter network specific to BPD (p = .018), including frontal-parietal and temporal regions possibly associated with dysfunctional top-down emotion regulation. These findings may shed light on a better understanding of affective disturbances behind the two disorders, with BD patients more characterized by abnormalities in neural structures involved in mood oscillations, and BPD by deficits in the cognitive regulation of emotions. These results may help developing better treatments tailored to the specific affective disturbances displayed by these patients.

关键词： source-based morphometry Emotion regulation Bipolar Disorder Borderline Personality Disorder Biomarkers

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Heritability of Gray Matter Structural Covariation and Tool Use Skills in Chimpanzees (Pan troglodytes): A source-based morphometry and Quantitative Genetic Analysis

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CEREBRAL CORTEX 2019年第9期29卷 3702-3711页

作者： Hopkins, William D. Latzman, Robert D. Mareno, Mary Catherine Schapiro, Steven J. Gomez-Robles, Aida Sherwood, Chet C. Georgia State Univ Neurosci Inst POB 5030 Atlanta GA 30302 USA Yerkes Natl Primate Res Ctr Div Dev & Cognit Neurosci Atlanta GA 30322 USA Georgia State Univ Dept Psychol Atlanta GA 30302 USA Univ Texas MD Anderson Canc Ctr Dept Vet Sci Bastrop TX 78602 USA George Washington Univ Dept Anthropol Washington DC 20052 USA George Washington Univ Ctr Adv Study Human Paleobiol Washington DC 20052 USA

Nonhuman primates, and great apes in particular, possess a variety of cognitive abilities thought to underlie human brain and cognitive evolution, most notably, the manufacture and use of tools. In a relatively large sample (N = 226) of captive chimpanzees (Pan troglodytes) for whom pedigrees are well known, the overarching aim of the current study was to investigate the source of heritable variation in brain structure underlying tool use skills. Specifically, using source-based morphometry (SBM), a multivariate analysis of naturally occurring patterns of covariation in gray matter across the brain, we investigated (1) the genetic contributions to variation in SBM components, (2) sex and age effects for each component, and (3) phenotypic and genetic associations between SBM components and tool use skill. Results revealed important sexand age-related differences across largely heritable SBM components and associations between structural covariation and tool use skill. Further, shared genetic mechanisms appear to account for a heritable link between variation in both the capacity to use tools and variation in morphology of the superior limb of the superior temporal sulcus and adjacent parietal cortex. Findings represent the first evidence of heritability of structural covariation in gray matter among nonhuman primates.

关键词： chimpanzee gray matter covariation heritability source-based morphometry tool use

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source-based morphometry Multivariate Approach to Analyze [¹²³I]FP-CIT SPECT Imaging

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MOLECULAR IMAGING AND BIOLOGY 2017年第5期19卷 772-778页

作者： Premi, Enrico Calhoun, V. D. Garibotto, V. Turrone, R. Alberici, A. Cottini, E. Pilotto, A. Gazzina, S. Magoni, M. Paghera, B. Borroni, B. Padovani, A. Univ Brescia Dept Clin & Expt Sci Neurol Unit Brescia Italy Spedali Civili Hosp Stroke Unit Azienda Osped Spedali Civili Brescia Italy Mind Res Network Albuquerque NM 87106 USA Univ New Mexico Dept Elect & Comp Engn Albuquerque NM 87131 USA Geneva Univ Hosp Dept Med Imaging Geneva Switzerland Spedali Civili Hosp Nucl Med Unit Azienda Azienda Osped Spedali Civili Brescia Italy

[I-123]FP-CIT (DaTSCANA (R)) single-photon emission computed tomography (SPECT) imaging is widely used to study neurodegenerative parkinsonism, by measuring presynaptic dopamine transporter (DAT) in striatal regions. Beyond DAT, [I-123]FP-CIT may be considered for other monoaminergic systems, in particular the serotonin transporter (SERT). Independent component analysis (ICA) implemented in source-based morphometry (SBM) could represent an alternative method to explore monoaminergic pathways, studying the relationship among voxels and grouping them into "neurotransmission" networks. One hundred forty-three subjects [84 with Parkinson's disease (PD) and 59 control individuals (CG)] underwent DATSCANA (R) imaging. The [I-123]FP-CIT binding was evaluated by multivariate SBM approach, as well as by a whole-brain voxel-wise univariate (statistical parametric mapping, SPM) approach. As compared to the univariate whole-brain approach (SPM) (only demonstrating striatal [I-123]FP-CIT binding reduction in PD group), SBM identified six sources of non-artefactual origin, including basal ganglia and cortical regions as well as brainstem. Among them, three sources (basal ganglia and cortical regions) presented loading scores (as index of [I-123]FP-CIT binding) significantly different between PD and CG. Notably, even if not significantly different between PD and CG, the remaining three non-artefactual sources were characterized by a predominant frontal, brainstem, and occipito-temporal involvement. The concept of source blind separation by the application of ICA (as implemented in SBM) represents a feasible approach to be considered in [I-123]FP-CIT (DaTSCAN(A (R))) SPECT imaging. Taking advantage of this multivariate analysis, specific patterns of variance can be identified (involving either striatal than extrastriatal regions) that could be useful in differentiating neurodegenerative parkinsonisms.

关键词： Parkinson's disease [I-123]FP-CIT imaging Statistical parametric mapping source-based morphometry

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