David Fällmar1, Johan Lilja2, Vilma Velickaite1, Torsten Danfors2, Mark Lubberink2, André Ahlgren3, Matthias J P van Osch4, Lena Kilander5, Elna-Marie Larsson1. 1. Department of Surgical Sciences/Radiology, Uppsala University, Uppsala, Sweden. 2. Department of Surgical Sciences/Nuclear Medicine and PET, Uppsala University, Uppsala, Sweden. 3. Department of Medical Radiation Physics, Lund University, Lund, Sweden. 4. C.J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands. 5. Department of Public Health and Caring Sciences/Geriatrics, Uppsala University, Uppsala, Sweden.
Abstract
PURPOSE: Functional imaging is becoming increasingly important for the detection of neurodegenerative disorders. Perfusion MRI with arterial spin labeling (ASL) has been reported to provide promising diagnostic possibilities but is not yet widely used in routine clinical work. The aim of this study was to compare, in a clinical setting, the visual assessment of subtracted ASL CBF maps with and without additional smoothing, to FDG-PET data. METHODS: Ten patients with a clinical diagnosis of dementia and 11 age-matched cognitively healthy controls were examined with pseudo-continuous ASL (pCASL) and 18F-Fluorodeoxyglucose positron emission tomography (FDG-PET). Three diagnostic physicians visually assessed the pCASL maps after subtraction only, and after postprocessing using Gaussian smoothing and GLM-based beta estimate functions. The assessment scores were compared to FDG PET values. Furthermore, the ability to discriminate patients from healthy elderly controls was assessed. RESULTS: Smoothing improved the correlation between visually assessed regional ASL perfusion scores and the FDG PET SUV-r values from the corresponding regions. However, subtracted pCASL maps discriminated patients from healthy controls better than smoothed maps. Smoothing increased the number of false-positive patient identifications. Application of beta estimate functions had only a marginal effect. CONCLUSION: Spatial smoothing of ASL images increased false positive results in the discrimination of hypoperfusion conditions from healthy elderly. It also decreased interreader agreement. However, regional characterization and subjective perception of image quality was improved.
PURPOSE: Functional imaging is becoming increasingly important for the detection of neurodegenerative disorders. Perfusion MRI with arterial spin labeling (ASL) has been reported to provide promising diagnostic possibilities but is not yet widely used in routine clinical work. The aim of this study was to compare, in a clinical setting, the visual assessment of subtracted ASL CBF maps with and without additional smoothing, to FDG-PET data. METHODS: Ten patients with a clinical diagnosis of dementia and 11 age-matched cognitively healthy controls were examined with pseudo-continuous ASL (pCASL) and 18F-Fluorodeoxyglucose positron emission tomography (FDG-PET). Three diagnostic physicians visually assessed the pCASL maps after subtraction only, and after postprocessing using Gaussian smoothing and GLM-based beta estimate functions. The assessment scores were compared to FDG PET values. Furthermore, the ability to discriminate patients from healthy elderly controls was assessed. RESULTS: Smoothing improved the correlation between visually assessed regional ASL perfusion scores and the FDG PET SUV-r values from the corresponding regions. However, subtracted pCASL maps discriminated patients from healthy controls better than smoothed maps. Smoothing increased the number of false-positive patient identifications. Application of beta estimate functions had only a marginal effect. CONCLUSION: Spatial smoothing of ASL images increased false positive results in the discrimination of hypoperfusion conditions from healthy elderly. It also decreased interreader agreement. However, regional characterization and subjective perception of image quality was improved.
Authors: David Fällmar; Johan Lilja; Torsten Danfors; Lena Kilander; Victor Iyer; Mark Lubberink; Elna-Marie Larsson; Jens Sörensen Journal: Am J Nucl Med Mol Imaging Date: 2018-08-20
Authors: David Fällmar; Sven Haller; Johan Lilja; Torsten Danfors; Lena Kilander; Nelleke Tolboom; Karl Egger; Elias Kellner; Philip M Croon; Sander C J Verfaillie; Bart N M van Berckel; Rik Ossenkoppele; Frederik Barkhof; Elna-Marie Larsson Journal: Eur Radiol Date: 2017-04-03 Impact factor: 5.315