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Michael Schöll

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5 papers

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YNICL Journal 2025 Journal Article

Amyloid PET predicts atrophy in older adults without dementia: Results from the AMYPAD Prognostic & Natural History study

Leonard Pieperhoff
Luigi Lorenzini
Sophie Mastenbroek
Mario Tranfa
Mahnaz Shekari
Alle Meije Wink
Robin Wolz
Sylke Grootoonk

Highlights • Aβ-PET predicts atrophy in key brain regions in older adults without dementia.• Fusiform volumetric loss is linked to Aβ independent of CSF tau levels.• Temporal atrophy is stronger in women with higher Aβ burden.• APOE-ε4 carriers show larger Aβ-driven frontal & hippocampal atrophy.

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YNIMG Journal 2024 Journal Article

Partial volume correction in longitudinal tau PET studies: is it really needed?

Alejandro Costoya-Sánchez
Alexis Moscoso
Tomás Sobrino
Álvaro Ruibal
Michel J. Grothe
Michael Schöll
Jesús Silva-Rodríguez
Pablo Aguiar

BACKGROUND: F]flortaucipir (FTP) tau PET quantification is known to be affected by non-specific binding in off-target regions. Although partial volume correction (PVC) techniques partially account for this effect, their inclusion may also introduce noise and variability into the quantification process. While the impact of these effects has been studied in cross-sectional designs, the benefits and drawbacks of PVC on longitudinal FTP studies is still under scrutiny. The aim of this work was to study the performance of the most common PVC techniques for longitudinal FTP imaging. METHODS: A cohort of 247 individuals from the Alzheimer's Disease Neuroimaging Initiative with concurrent baseline FTP-PET, amyloid-beta (Aβ) PET and structural MRI, as well as with follow-up FTP-PET and MRI were included in the study. FTP-PET scans were corrected for partial volume effects using Meltzer's, a simple and popular analytical PVC, and both the region-based voxel-wise (RBV) and the iterative Yang (iY) corrections. FTP SUVR values and their longitudinal rates of change were calculated for regions of interest (ROI) corresponding to Braak Areas I-VI, for a temporal meta-ROI and for regions typically displaying off-target FTP binding (caudate, putamen, pallidum, thalamus, choroid plexus, hemispheric white matter, cerebellar white matter, and cerebrospinal fluid). The longitudinal correlation between binding in off-target and target ROIs was analysed for the different PVCs. Additionally, group differences in longitudinal FTP SUVR rates of change between Aβ-negative (A-) and Aβ-positive (A+), and between cognitively unimpaired (CU) and cognitively impaired (CI) individuals, were studied. Finally, we compared the ability of different partial-volume-corrected baseline FTP SUVRs to predict longitudinal brain atrophy and cognitive decline. RESULTS: =0.00-0.07 for hemispheric white matter). PVC also increased group differences between CU and CI individuals in FTP SUVR rates of change across all target regions, with RBV again performing best (No PVC: Cohen's d = 0.26-0.66; RBV: Cohen's d = 0.43-0.74). These improvements were not observed for differentiating A- from A+ groups. Additionally, voxel-wise PVC techniques strengthened the correlation between baseline FTP SUVR and longitudinal grey matter atrophy and cognitive decline. CONCLUSION: Quantification of longitudinal FTP SUVR rates of change is affected by signal from off-target regions, especially the hemispheric white matter and the CSF. Voxel-wise PVC techniques significantly reduce this effect. PVC provided a significant but modest benefit for tasks involving the measurement of group-level longitudinal differences. These findings are particularly relevant for the estimations of sample sizes and analysis methodologies of longitudinal group studies.

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YNIMG Journal 2021 Journal Article

Deep learning from MRI-derived labels enables automatic brain tissue classification on human brain CT

Meera Srikrishna
Joana B. Pereira
Rolf A. Heckemann
Giovanni Volpe
Danielle van Westen
Anna Zettergren
Silke Kern
Lars-Olof Wahlund

Automatic methods for feature extraction, volumetry, and morphometric analysis in clinical neuroscience typically operate on images obtained with magnetic resonance (MR) imaging equipment. Although CT scans are less expensive to acquire and more widely available than MR scans, their application is currently limited to the visual assessment of brain integrity and the exclusion of co-pathologies. CT has rarely been used for tissue classification because the contrast between grey matter and white matter was considered insufficient. In this study, we propose an automatic method for segmenting grey matter (GM), white matter (WM), cerebrospinal fluid (CSF), and intracranial volume (ICV) from head CT images. A U-Net deep learning model was trained and validated on CT images with MRI-derived segmentation labels. We used data from 744 participants of the Gothenburg H70 Birth Cohort Studies for whom CT and T1-weighted MR images had been acquired on the same day. Our proposed model predicted brain tissue classes accurately from unseen CT images (Dice coefficients of 0.79, 0.82, 0.75, 0.93 and 0.98 for GM, WM, CSF, brain volume and ICV, respectively). To contextualize these results, we generated benchmarks based on established MR-based methods and intentional image degradation. Our findings demonstrate that CT-derived segmentations can be used to delineate and quantify brain tissues, opening new possibilities for the use of CT in clinical practice and research.

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YNIMG Journal 2017 Journal Article

Amyloid and tau PET demonstrate region-specific associations in normal older people

Samuel N. Lockhart
Michael Schöll
Suzanne L. Baker
Nagehan Ayakta
Kaitlin N. Swinnerton
Rachel K. Bell
Taylor J. Mellinger
Vyoma D. Shah

β-amyloid (Aβ) and tau pathology become increasingly prevalent with age, however, the spatial relationship between the two pathologies remains unknown. We examined local (same region) and non-local (different region) associations between these 2 aggregated proteins in 46 normal older adults using [18F]AV-1451 (for tau) and [11C]PiB (for Aβ) positron emission tomography (PET) and 1. 5T magnetic resonance imaging (MRI) images. While local voxelwise analyses showed associations between PiB and AV-1451 tracer largely in the temporal lobes, k-means clustering revealed that some of these associations were driven by regions with low tracer retention. We followed this up with a whole-brain region-by-region (local and non-local) partial correlational analysis. We calculated each participant's mean AV-1451 and PiB uptake values within 87 regions of interest (ROI). Pairwise ROI analysis demonstrated many positive PiB—AV-1451 associations. Importantly, strong positive partial correlations (controlling for age, sex, and global gray matter fraction, p<. 01) were identified between PiB in multiple regions of association cortex and AV-1451 in temporal cortical ROIs. There were also less frequent and weaker positive associations of regional PiB with frontoparietal AV-1451 uptake. Particularly in temporal lobe ROIs, AV-1451 uptake was strongly predicted by PiB across multiple ROI locations. These data indicate that Aβ and tau pathology show significant local and non-local regional associations among cognitively normal elderly, with increased PiB uptake throughout the cortex correlating with increased temporal lobe AV-1451 uptake. The spatial relationship between Aβ and tau accumulation does not appear to be specific to Aβ location, suggesting a regional vulnerability of temporal brain regions to tau accumulation regardless of where Aβ accumulates.

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YNIMG Journal 2014 Journal Article

Radial, spiral and reverberating waves of spreading depolarization occur in the gyrencephalic brain

Edgar Santos
Michael Schöll
Renán Sánchez-Porras
Markus A. Dahlem
Humberto Silos
Andreas Unterberg
Hartmut Dickhaus
Oliver W. Sakowitz

Objectives The detection of the hemodynamic and propagation patterns of spreading depolarizations (SDs) in the gyrencephalic brain using intrinsic optical signal imaging (IOS). Methods The convexity of the brain surface was surgically exposed in fourteen male swine. Within the boundaries of this window, brains were immersed and preconditioned with an elevated K+ concentration (7mmol/l) in the standard Ringer lactate solution for 30–40min. SDs were triggered using 3–5μl of 1mol/l KCl solution. Changes in tissue absorbency or reflection were registered with a CCD camera at a wavelength of 564nm (14nm FWHM), which was mounted 25cm above the exposed cortex. Additional monitoring by electrocorticography and laser-Doppler was used in a subset of animals (n=7) to validate the detection of SD. Results Of 198 SDs quantified in all of the experiments, 187 SDs appeared as radial waves that developed semi-planar fronts. The morphology was affected by the surface of the gyri, the sulci and the pial vessels. Other SD patterns such as spirals and reverberating waves, which have not been described before in gyrencephalic brains, were also observed. Diffusion gradients created in the cortex surface (i. e. , KCl concentrations), sulci, vessels and SD–SD interactions make the gyrencephalic brain prone to the appearance of irregular SD waves. Conclusion The gyrencephalic brain is capable of irregular SD propagation patterns. The irregularities of the gyrencephalic brain cortex may promote the presence of re-entrance waves, such as spirals and reverberating waves.

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