scholarly journals Sex Matters: A Multivariate Pattern Analysis of Sex- and Gender-Related Neuroanatomical Differences in Cis- and Transgender Individuals Using Structural Magnetic Resonance Imaging

2019 ◽  
Vol 30 (3) ◽  
pp. 1345-1356 ◽  
Author(s):  
Pia Baldinger-Melich ◽  
Maria F Urquijo Castro ◽  
René Seiger ◽  
Anne Ruef ◽  
Dominic B Dwyer ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Pattern Analysis ◽  
Transgender Women ◽  
Sex And Gender ◽  
Multivariate Pattern Analysis ◽  
Resonance Imaging ◽  
Structural Magnetic Resonance Imaging ◽  
And Gender ◽  
Multivariate Pattern

Abstract Univariate analyses of structural neuroimaging data have produced heterogeneous results regarding anatomical sex- and gender-related differences. The current study aimed at delineating and cross-validating brain volumetric surrogates of sex and gender by comparing the structural magnetic resonance imaging data of cis- and transgender subjects using multivariate pattern analysis. Gray matter (GM) tissue maps of 29 transgender men, 23 transgender women, 35 cisgender women, and 34 cisgender men were created using voxel-based morphometry and analyzed using support vector classification. Generalizability of the models was estimated using repeated nested cross-validation. For external validation, significant models were applied to hormone-treated transgender subjects (n = 32) and individuals diagnosed with depression (n = 27). Sex was identified with a balanced accuracy (BAC) of 82.6% (false discovery rate [pFDR] < 0.001) in cisgender, but only with 67.5% (pFDR = 0.04) in transgender participants indicating differences in the neuroanatomical patterns associated with sex in transgender despite the major effect of sex on GM volume irrespective of the self-identification as a woman or man. Gender identity and gender incongruence could not be reliably identified (all pFDR > 0.05). The neuroanatomical signature of sex in cisgender did not interact with depressive features (BAC = 74.7%) but was affected by hormone therapy when applied in transgender women (P < 0.001).

scholarly journals Characterizing the Structural Pattern of Heavy Smokers Using Multivoxel Pattern Analysis

2021 ◽  
Vol 11 ◽  
Author(s):  
Yufeng Ye ◽  
Jian Zhang ◽  
Bingsheng Huang ◽  
Xun Cai ◽  
Panying Wang ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Pattern Analysis ◽  
Healthy Controls ◽  
Voxel Based Morphometry ◽  
Resonance Imaging ◽  
Structural Magnetic Resonance Imaging ◽  
Multivoxel Pattern Analysis ◽  
Smoking Addiction ◽  
Heavy Smokers

Background: Smoking addiction is a major public health issue which causes a series of chronic diseases and mortalities worldwide. We aimed to explore the most discriminative gray matter regions between heavy smokers and healthy controls with a data-driven multivoxel pattern analysis technique, and to explore the methodological differences between multivoxel pattern analysis and voxel-based morphometry.Methods: Traditional voxel-based morphometry has continuously contributed to finding smoking addiction-related regions on structural magnetic resonance imaging. However, voxel-based morphometry has its inherent limitations. In this study, a multivoxel pattern analysis using a searchlight algorithm and support vector machine was applied on structural magnetic resonance imaging to identify the spatial pattern of gray matter volume in heavy smokers.Results: Our proposed method yielded a voxel-wise accuracy of at least 81% for classifying heavy smokers from healthy controls. The identified regions were primarily located at the temporal cortex and prefrontal cortex, occipital cortex, thalamus (bilateral), insula (left), anterior and median cingulate gyri, and precuneus (left).Conclusions: Our results suggested that several regions, which were seldomly reported in voxel-based morphometry analysis, might be latently correlated with smoking addiction. Such findings might provide insights for understanding the mechanism of chronic smoking and the creation of effective cessation treatment. Multivoxel pattern analysis can be efficient in locating brain discriminative regions which were neglected by voxel-based morphometry.

scholarly journals Measurement of Anteroposterior diameters of normal brainstem by Magnetic Resonance Imaging

2019 ◽  
Vol 12 (2) ◽  
pp. 53-58
Author(s):  
S. Singh ◽  
BR Sharma ◽  
M. Bhatta ◽  
N. Poudel
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Resonance Imaging ◽  
Cross Sectional ◽  
Medical College ◽  
Average Ratio ◽  
Sagittal Diameter ◽  
Anteroposterior Diameter ◽  
Normal Ranges ◽  
And Gender

Aim: The aim of this study is to assess the anteroposterior diameter of brainstem (midbrain, pons and medulla) of normal Nepalese people to establish normal ranges and to correlate the measurement with pa­tient’s age and gender. Method: The study is a cross-sectional prospective study which is per­formed in Gandaki Medical College, Pokhara. The data is collected over the period of 5 months from May 2018 to September 2018. The data of total 103 patients are collected who underwent (Magnetic Resonance Imaging) MRI head. Measurements of sagittal diameter at predefined levels i.e. distance between upper border of pons to midway between superior and inferior colliculi (A) for midbrain, distance between an­terior surface of pons to the floor of fourth ventricle (B) for pons and anteroposterior diameter perpendicular to the long axis of medulla just above the posterior kink at cervicomedullary junction for medulla ob­longata were made and noted. Result: The mean anteroposterior diameter of midbrain, pons and me­dulla oblongata was found to be 1.7048 ± 0.12 cm, 2.27 ± 0.13cm and 1.3 ± 0.088 cm respectively. The average ratio of sagittal diameter of pons to sagittal diameter of midbrain was 1.34 ± 0.099 cm and average ratio of sagittal diameter of pons to medulla oblongata was 1.75 ± 0.123 cm. Conclusion: There was no statistically significant correlation of the sagittal diameter of midbrain, pons and medulla with patient’s gender. The sagittal diameter of brainstem reached maximum at the age 20 and stopped increasing. The sagittal diameter of midbrain and medulla ob­longata decreased slightly after the age of 50 and decreased significant­ly after the age of 70. There was no decrease in the sagittal diameter of pons after age.

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