Age related preservation and loss in optimized brain SPECT

BackgroundRecent single photon emission computed tomography (SPECT) studies have reported age related increases in regional brain perfusion (called preservation here) as well as losses. AimTo apply optimized SPECT processing to better define and understand both age related preservation and loss in brain SPECT. MethodsBrain SPECT was performed on 85 healthy subjects using 99mTc hexamethylpropylene amine oxime (HMPAO), processed using findings from recent optimization work, and subjected to voxel based statistical analysis. ResultsSPECT preservation was seen in white matter. This distribution differs from other SPECT reports, but is similar to that for preservation observed with structural magnetic resonance imaging (MRI). This suggests that SPECT preservation may arise from age related changes in brain anatomy, not regional cerebral blood flow (rCBF), and we demonstrate that it can arise from the partial-volume effect in areas where white matter contracts with age. Age related losses extended over the whole pre-frontal midline area and an extended pattern of focal losses was seen in the peripheral cortex that was consistent with major sulci. There were also focal losses in the cerebellum. The most significant SPECT loss was in the anterior cingulate, although no structural changes were observed there in the MRI study. A model of sulcal widening at the junction of the inter-hemispheric fissure and cingulate sulcus, when degraded by the partial-volume effect, could explain this anterior cingulate loss. ConclusionOptimized processing has revealed spatial patterns for age related preservation and losses in brain SPECT that indicate their origin is primarily structural. Correction for structural effects in optimized SPECT is needed to confirm whether any regional ageing effects derive from changes in rCBF.

[1]  R. Jaszczak,et al.  Improved SPECT quantification using compensation for scattered photons. , 1984, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[2]  R. L. Rogers,et al.  Cerebral blood flow changes in benign aging and cerebrovascular disease , 1984, Neurology.

[3]  S. Levine,et al.  The effects of aging on cerebral blood flow in migraine , 1989, Neurology.

[4]  J. Risberg,et al.  Regional cerebral blood flow characteristics and variations with age in resting normal subjects , 1989, Brain and Cognition.

[5]  Karl J. Friston,et al.  Comparing Functional (PET) Images: The Assessment of Significant Change , 1991, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[6]  Karl J. Friston,et al.  Decreases in Regional Cerebral Blood Flow with Normal Aging , 1991, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[7]  Alan C. Evans,et al.  A Three-Dimensional Statistical Analysis for CBF Activation Studies in Human Brain , 1992, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[8]  Anand Rangarajan,et al.  Bayesian reconstruction of functional images using anatomical information as priors , 1993, IEEE Trans. Medical Imaging.

[9]  J. Meyer,et al.  Cerebral circulation in the elderly. , 1993, Cerebrovascular and brain metabolism reviews.

[10]  Karl J. Friston,et al.  Assessing the significance of focal activations using their spatial extent , 1994, Human brain mapping.

[11]  G. Frisoni,et al.  Linear measures of atrophy in mild Alzheimer disease. , 1996, AJNR. American journal of neuroradiology.

[12]  J. Ashburner,et al.  Multimodal Image Coregistration and Partitioning—A Unified Framework , 1997, NeuroImage.

[13]  B. Landeau,et al.  Effects of Healthy Aging on the Regional Cerebral Metabolic Rate of Glucose Assessed with Statistical Parametric Mapping , 1996, NeuroImage.

[14]  J. Ashburner,et al.  Nonlinear spatial normalization using basis functions , 1999, Human brain mapping.

[15]  S. Laureys,et al.  Comparison of Impaired Subcortico-Frontal Metabolic Networks in Normal Aging, Subcortico-Frontal Dementia, and Cortical Frontal Dementia , 1999, NeuroImage.

[16]  Karl J. Friston,et al.  A Voxel-Based Morphometric Study of Ageing in 465 Normal Adult Human Brains , 2001, NeuroImage.

[17]  K. Van Laere,et al.  Brain perfusion SPECT: age- and sex-related effects correlated with voxel-based morphometric findings in healthy adults. , 2001, Radiology.

[18]  Michel Koole,et al.  99mTc-ECD brain perfusion SPET: variability, asymmetry and effects of age and gender in healthy adults , 2001, European Journal of Nuclear Medicine.

[19]  N. Tzourio-Mazoyer,et al.  Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain , 2002, NeuroImage.

[20]  et al.,et al.  Discrimination between Alzheimer Dementia and Controls by Automated Analysis of Multicenter FDG PET , 2002, NeuroImage.

[21]  B. Hutton,et al.  Optimisation of brain SPET and portability of normal databases , 2004, European Journal of Nuclear Medicine and Molecular Imaging.

[22]  Takashi Asada,et al.  Correction for partial-volume effects on brain perfusion SPECT in healthy men. , 2003, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[23]  Data based optimization of brain SPECT processing for voxel-based statistical analysis , 2004, IEEE Symposium Conference Record Nuclear Science 2004..