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T. Ernst, E. Itti, L. Itti, L. Chang, Changes in cerebral metabolism are detected prior to perfusion changes in early HIV-CMC: A coregistered (1)H MRS and SPECT study, Journal of Magnetic Resonance Imaging, Vol. 12, No. 6, pp. 859-865, Dec 2000. [1999 impact factor: 2.106] (Cited by 52)
Abstract: Human immunodeficiency virus-cognitive motor complex (HIV-CMC), a common complication of the acquired immunodeficiency syndrome (AIDS), is characterized by progressive cognitive impairment and motor dysfunction. Functional imaging methods, such as single-photon emission computed tomography (SPECT) and proton magnetic resonance spectroscopy ((1)H-MRS), have been applied to assess the severity of brain injury. However, it is unclear which of these two methods is more sensitive in detecting brain abnormalities in patients with early HIV-CMC. Twenty-four HIV-CMC patients were compared with 34 healthy subjects; each had quantitative SPECT ((133)Xenon-calibrated (99m)Tc-HMPAO) and quantitative (1)H-MRS. Both modalities were co-registered in order to assess regional cerebral blood flow (rCBF) and metabolite concentrations within the same voxel of interest in four brain regions (midfrontal and midparietal gray matter, temporoparietal white matter, and basal ganglia). On SPECT, only the temporoparietal white matter showed a trend for decreased rCBF in HIV-CMC patients (-13%, P = 0.06). On MRS, HIV-CMC patients showed significantly reduced creatine concentration in the basal ganglia (-8%, P = 0.008), as well as increased myoinositol concentrations in the basal ganglia (+25%, P = 0.01) and the temporoparietal white matter (+18%, P = 0.08). There was no significant correlation between SPECT and MRS variables in the patients in any region. (1)H MRS showed abnormal neurochemistry in the basal ganglia, whereas rCBF on SPECT was normal in the same region. This finding suggests that metabolite concentrations on (1)H MRS are better surrogate markers than rCBF measurements with SPECT for the evaluation of brain injury in early HIV-CMC.
Themes: Medical Image Processing, Medical Research
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