Abstract

Background: SPECT (single-photon emission-computed tomography) is used for the detection of hypoperfusion in cognitive impairment and dementia but is not widely available and related to radiation dose exposure. We compared the performance of DSC (dynamic susceptibility contrast) perfusion using semi- and fully adaptive deconvolution models to HMPAO-SPECT (99mTc-hexamethylpropyleneamine oxime-SPECT). Material and Methods: Twenty-seven patients with dementia of different subtypes including frontotemporal dementia (FTD) and mild cognitive impairment (MCI) received a multimodal diagnostic work-up including DSC perfusion at a clinical 3T high-field scanner and HMPAO-SPECT. Nineteen healthy control individuals received DSC perfusion. For calculation of the hemodynamic parameter maps, oscillation-index standard truncated singular value decomposition (oSVD, semi-adaptive) as well as Bayesian parameter estimation (BAY, fully adaptive) were performed. Results: Patients showed decreased cortical perfusion in the left frontal lobe compared to controls (relative cerebral blood volume corrected, rBVc: 0.37 vs. 0.27, p = 0.048, adjusted for age and sex). Performance of rBVc (corrected for T1 effects) was highest compared to SPECT for detection of frontal hypoperfusion (sensitivity 83%, specificity 80% for oSVD and BAY, area under curve (AUC) = 0.833 respectively, p < 0.05) in FTD and MCI. For nonleakage-corrected rBV and for rBF (relative cerebral blood flow), sensitivity of frontal hypoperfusion was above 80% for oSVD and for BAY (rBV: sensitivity 83%, specificity 75%, AUC = 0.908 for oSVD and 0.917 for BAY, p < 0.05 respectively; rBF: sensitivity 83%, specificity 65%, AUC = 0.825, p < 0.05 for oSVD). Conclusion: Advanced deconvolution DSC can reliably detect pathological perfusion alterations in FTD and MCI. Hence, this widely accessible technique has the potential to improve the diagnosis of dementia and MCI as part of an interdisciplinary multimodal imaging work-up. Advances in knowledge: Advanced DSC perfusion has a high potential in the work-up of suspected dementia and correlates with SPECT brain perfusion results in dementia and MCI.

Highlights

  • Prevalence of dementia is rather high in the elderly population (>60 years) with about 5–7% worldwide [1]

  • Performance of rBVc was highest compared to SPECT for detection of frontal hypoperfusion (sensitivity 83%, specificity 80% for oSVD and Bayesian hemodynamic parameter estimation (BAY), area under curve (AUC) = 0.833 respectively, p < 0.05) in frontotemporal dementia (FTD) and mild cognitive impairment (MCI)

  • Structural MRI already plays an important role in the diagnosis of early dementia [6], but perfusion imaging helps identifying subtypes, which is important for therapy decisions and further care of patients [3,7]. 99mTc-hexamethylpropyleneamine oxime single-photon emission-computed tomography (HMPAO-SPECT) is used in the diagnostic work-up as specific regional patterns of hypoperfusion have been described for different subtypes of dementia [8]

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Summary

Introduction

Prevalence of dementia is rather high in the elderly population (>60 years) with about 5–7% worldwide [1]. 99mTc-hexamethylpropyleneamine oxime single-photon emission-computed tomography (HMPAO-SPECT) is used in the diagnostic work-up as specific regional patterns of hypoperfusion have been described for different subtypes of dementia [8]. SPECT (single-photon emission-computed tomography) is used for the detection of hypoperfusion in cognitive impairment and dementia but is not widely available and related to radiation dose exposure. Material and Methods: Twenty-seven patients with dementia of different subtypes including frontotemporal dementia (FTD) and mild cognitive impairment (MCI) received a multimodal diagnostic work-up including DSC perfusion at a clinical 3T high-field scanner and HMPAO-SPECT. Conclusion: Advanced deconvolution DSC can reliably detect pathological perfusion alterations in FTD and MCI This widely accessible technique has the potential to improve the diagnosis of dementia and MCI as part of an interdisciplinary multimodal imaging work-up.

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