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Structural magnetic resonance imaging in poor prognosis bipolar illness — a voxel based study
NemoImage
13, Number
6, 2001,
Part 2 of 2 Parts ID
E bL@
PSYCHIATRY
Structural magnetic resonance imaging in poor prognosis bipolar illness a voxel based study Klaus Ebmeier*$, Alan Doris*, Michael Glabust, Emma Belton*, Ian Marshall+, Joanna WardlawS *Department of Psychiatry, University of Edinburgh (http://www.pst.ed.ac.uk) tNationa1 Institute of Mental Health, Bethesda $3HEFC Brain Imaging Research Centre for Scotland (http://www.dcn.ed.ac.z&bic/) Introduction: This paper aims to address the question: in particular, in cases that are of poor SPM-voxel based analysis, an automated,
what are the structural brain abnormalities that are associated with bipolar disorder and, prognosis as measured by the McGlashan scale? Object map data are compared with operator independent process, and will hence be used to help validate this new technique.
Methods: The first stage was to determine the volumes of specific brain areas and structures in both control (n=15) and patient (n=16) groups. This was done blind to group and also to laterality, and included the analysis of - 5 brains before and after that of the main data set to obtain a measure of intra-rater reliability. MRI field inhomogeneity was controlled for, if necessary, using phantom data. The anatomical volumes to be measured were determined using a review of the medical literature, and included the hippocampal formation, temporal and frontal lobe measures as well as global brain volume (this latter measure was used as a statistical confounding covariate). The results from this analysis was compared between groups, controlling for confounders, such as age, sex, premorbid intelligence, years of education and neuropsychological impairment. Results: Controls and, in particular, poor prognosis patients were well matched for age, sex and IQ. CVLT performance was reduced in patients, as were scores in the digit symbol substitution test. Digits and spatial forwards and backwards tests were not significantly different, as was verbal fluency. This is likely to be an effect of insufficient power, as patients performed on average worse than controls in all tests. Irma-class correlation coefficients for repeat object mapping ranged from 0.57 for left amygdala-hippocampal complex to 0.99 for the left lateral ventricle. Right amygdala-hippocampal complex was reduced in the bipolar group as a whole, while both right amygdala-hippocampal complex and left temporal horn were marginally abnormal (pcO.06) in the poor prognosis group. statistical parametric mapping reveiled abnormal grey matter density mainly in fronto-limbic cortex. Comments: Clinical studies, by their nature, have many more confounding factors to consider than experimental work, and in that respect it will be difficult to draw any firm conclusions from this study. The issue of causality will be difficult to resolve, as changes in the brain may be due to the progression of the disorder itself, as a result of medication or disease process, or instead be of developmental origin. However, the results offer useful insights into the neural correlates of bipolar disorder and may have important methodological implications with regards to the analysis of structural MRI data.
s1045
13, Number
6, 2001,
Part 2 of 2 Parts ID
E bL@
PSYCHIATRY
Structural magnetic resonance imaging in poor prognosis bipolar illness a voxel based study Klaus Ebmeier*$, Alan Doris*, Michael Glabust, Emma Belton*, Ian Marshall+, Joanna WardlawS *Department of Psychiatry, University of Edinburgh (http://www.pst.ed.ac.uk) tNationa1 Institute of Mental Health, Bethesda $3HEFC Brain Imaging Research Centre for Scotland (http://www.dcn.ed.ac.z&bic/) Introduction: This paper aims to address the question: in particular, in cases that are of poor SPM-voxel based analysis, an automated,
what are the structural brain abnormalities that are associated with bipolar disorder and, prognosis as measured by the McGlashan scale? Object map data are compared with operator independent process, and will hence be used to help validate this new technique.
Methods: The first stage was to determine the volumes of specific brain areas and structures in both control (n=15) and patient (n=16) groups. This was done blind to group and also to laterality, and included the analysis of - 5 brains before and after that of the main data set to obtain a measure of intra-rater reliability. MRI field inhomogeneity was controlled for, if necessary, using phantom data. The anatomical volumes to be measured were determined using a review of the medical literature, and included the hippocampal formation, temporal and frontal lobe measures as well as global brain volume (this latter measure was used as a statistical confounding covariate). The results from this analysis was compared between groups, controlling for confounders, such as age, sex, premorbid intelligence, years of education and neuropsychological impairment. Results: Controls and, in particular, poor prognosis patients were well matched for age, sex and IQ. CVLT performance was reduced in patients, as were scores in the digit symbol substitution test. Digits and spatial forwards and backwards tests were not significantly different, as was verbal fluency. This is likely to be an effect of insufficient power, as patients performed on average worse than controls in all tests. Irma-class correlation coefficients for repeat object mapping ranged from 0.57 for left amygdala-hippocampal complex to 0.99 for the left lateral ventricle. Right amygdala-hippocampal complex was reduced in the bipolar group as a whole, while both right amygdala-hippocampal complex and left temporal horn were marginally abnormal (pcO.06) in the poor prognosis group. statistical parametric mapping reveiled abnormal grey matter density mainly in fronto-limbic cortex. Comments: Clinical studies, by their nature, have many more confounding factors to consider than experimental work, and in that respect it will be difficult to draw any firm conclusions from this study. The issue of causality will be difficult to resolve, as changes in the brain may be due to the progression of the disorder itself, as a result of medication or disease process, or instead be of developmental origin. However, the results offer useful insights into the neural correlates of bipolar disorder and may have important methodological implications with regards to the analysis of structural MRI data.
s1045