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Ronald Boellaard

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YNIMG Journal 2026 Journal Article

Decreased functional connectivity in post-COVID syndrome patients with high neuroinflammatory activity

  • Denise Visser
  • Leo Pieperhoff
  • Luigi Lorenzini
  • Sandeep S.V. Golla
  • Sander C.J. Verfaillie
  • Anouk Verveen
  • Elsmarieke van de Giessen
  • Marijke E. den Hollander

INTRODUCTION: Previous research suggests some post-COVID patients with neurocognitive complaints (NCC) show neuroinflammation. Like in inflammatory diseases, this may affect network connectivity. This study aimed to compare resting-state functional connectivity in individuals with and without i) neuroinflammation and ii) persistent post-COVID NCC. METHODS: F]DPA-714 PET scan with arterial sampling for neuroinflammation, and 3T MRI scan for resting-state functional connectivity. Twenty resting-state networks (RSNs) were identified using independent component analysis. Group differences in within-RSN connectivity were analyzed using general linear models. Differences in subcortico-cortical between-RSN connectivity-between brainstem or thalamus and cortical RSNs-were assessed using interaction models. RESULTS: F]DPA-714 binding in participants with NCC. Lastly, thalamic-somatomotor and brainstem-control network connectivity (between-RSN) was altered in both individuals with persistent NCC and those with neuroinflammation, with thalamic-somatomotor changes mainly driven by NCC and brainstem-control changes by neuroinflammation. CONCLUSION: Our results suggest that neuroinflammation in individuals with persistent NCC after SARS-CoV-2 infection is linked to altered functional connectivity in RSNs central to higher-order cognitive functions.

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YNICL Journal 2021 Journal Article

Feasibility of pharmacokinetic parametric PET images in scaled subprofile modelling using principal component analysis

  • Débora E. Peretti
  • Remco J. Renken
  • Fransje E. Reesink
  • Bauke M. de Jong
  • Peter P. De Deyn
  • Rudi A.J.O. Dierckx
  • Janine Doorduin
  • Ronald Boellaard

Scaled subprofile model using principal component analysis (SSM/PCA) is a multivariate analysis technique used, mainly in [18F]-2-fluoro-2-deoxy-d-glucose (FDG) PET studies, for the generation of disease-specific metabolic patterns (DP) that may aid with the classification of subjects with neurological disorders, like Alzheimer’s disease (AD). The aim of this study was to explore the feasibility of using quantitative parametric images for this type of analysis, with dynamic [11C]-labelled Pittsburgh Compound B (PIB) PET data as an example. Therefore, 15 AD patients and 15 healthy control subjects were included in an SSM/PCA analysis to generate four AD-DPs using relative cerebral blood flow (R 1), binding potential (BP ND) and SUVR images derived from dynamic PIB and static FDG-PET studies. Furthermore, 49 new subjects with a variety of neurodegenerative cognitive disorders were tested against these DPs. The AD-DP was characterized by a reduction in the frontal, parietal, and temporal lobes voxel values for R 1 and SUVR-FDG DPs; and by a general increase of values in cortical areas for BP ND and SUVR-PIB DPs. In conclusion, the results suggest that the combination of parametric images derived from a single dynamic scan might be a good alternative for subject classification instead of using 2 independent PET studies.

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YNICL Journal 2020 Journal Article

Hippocampal [18F]flortaucipir BPND corrected for possible spill-in of the choroid plexus retains strong clinico-pathological relationships

  • Emma E Wolters
  • Rik Ossenkoppele
  • Sandeep SV Golla
  • Sander CJ Verfaillie
  • Tessa Timmers
  • Denise Visser
  • Hayel Tuncel
  • Emma M Coomans

BACKGROUND: F]flortaucipir signal using a semi-automated technique, and assessed correlations with cognitive performance across methods. METHODS: VOIs and MMSE/delayed recall adjusted for age, sex and education. RESULTS: =-0.59[CI=-0.75-0.44]; all p<0.001), with comparable effect sizes for all hippocampal VOIs. CONCLUSIONS: and memory were comparable for all methods. The non-optimized 100% hippocampal VOI may be sufficient for clinical interpretation. However, proper correction for choroid plexus spillover and may be required in case of smaller effect sizes between subject groups or for longitudinal studies.

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YNICL Journal 2017 Journal Article

Subtle alterations in cerebrovascular reactivity in mild cognitive impairment detected by graph theoretical analysis and not by the standard approach

  • Carlos A. Sánchez-Catasús
  • Gretel Sanabria-Diaz
  • Antoon Willemsen
  • Eduardo Martinez-Montes
  • Juan Samper-Noa
  • Angel Aguila-Ruiz
  • Ronald Boellaard
  • Peter P. De Deyn

There is growing support that cerebrovascular reactivity (CVR) in response to a vasodilatory challenge, also defined as the cerebrovascular reserve, is reduced in Alzheimer's disease dementia. However, this is less clear in patients with mild cognitive impairment (MCI). The current standard analysis may not reflect subtle abnormalities in CVR. In this study, we aimed to investigate vasodilatory-induced changes in the topology of the cerebral blood flow correlation (CBFcorr) network to study possible network-related CVR abnormalities in MCI. For this purpose, four CBFcorr networks were constructed: two using CBF SPECT data at baseline and under the vasodilatory challenge of acetazolamide (ACZ), obtained from a group of 26 MCI patients; and two equivalent networks from a group of 26 matched cognitively normal controls. The mean strength of association (SA) and clustering coefficient (C) were used to evaluate ACZ-induced changes on the topology of CBFcorr networks. We found that cognitively normal adults and MCI patients show different patterns of C and SA changes. The observed differences included the medial prefrontal cortices and inferior parietal lobe, which represent areas involved in MCI's cognitive dysfunction. In contrast, no substantial differences were detected by standard CVR analysis. These results suggest that graph theoretical analysis of ACZ-induced changes in the topology of the CBFcorr networks allows the identification of subtle network-related CVR alterations in MCI, which couldn't be detected by the standard approach.

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YNIMG Journal 2011 Journal Article

Kinetic analysis in human brain of [11C](R)-rolipram, a positron emission tomographic radioligand to image phosphodiesterase 4: A retest study and use of an image-derived input function

  • Paolo Zanotti-Fregonara
  • Sami S. Zoghbi
  • Jeih-San Liow
  • Elise Luong
  • Ronald Boellaard
  • Robert L. Gladding
  • Victor W. Pike
  • Robert B. Innis

[11C](R)-rolipram provides a measure of the density of phosphodiesterase 4 (PDE4) in brain, an enzyme that metabolizes cAMP. The aims of this study were to perform kinetic modeling of [11C](R)-rolipram in healthy humans using an arterial input function and to replace this arterial input in humans with an image-derived input function. Methods Twelve humans had two injections of [11C](R)-rolipram. An image-derived input function was obtained from the carotid arteries and four blood samples. The samples were used for partial volume correction and for estimating the parent concentration using HPLC analysis. Results An unconstrained two-compartment model and Logan analysis measured distribution volume V T, with good identifiability but with moderately high retest variability (15%). Similar results were obtained using the image input (ratio image/arterial V T =1. 00±0. 06). Conclusions Binding of [11C](R)-rolipram to PDE4 can be quantified in human brain using kinetic modeling and an arterial input function. Image input function from carotid arteries provides an equally accurate and reproducible method to quantify PDE4.

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YNIMG Journal 2010 Journal Article

Simplified parametric methods for [18F]FDDNP studies

  • Maqsood Yaqub
  • Nelleke Tolboom
  • Bart N.M. van Berckel
  • Philip Scheltens
  • Adriaan A. Lammertsma
  • Ronald Boellaard

The purpose of the present study was to evaluate the performance of various parametric methods for quantification of [18F]FDDNP studies. All parametric methods tested were based on the use of a reference tissue and they were compared with the simplified reference tissue model (SRTM), as previously it has been shown that SRTM is the method of choice for analysing [18F]FDDNP studies, even when an arterial plasma input function is available. The following parametric methods were evaluated: receptor parametric mapping (basis function implementation of SRTM; with and without fixing the reference tissue efflux rate constant k′2), reference Logan and several multi-linear reference tissue methods (again with and without fixing k′2). Simulations were used to assess the effects of variation in relative flow (R 1), fractional blood volume (V b ) and binding potential (BP ND ) on precision and accuracy of estimated BP ND. For clinical data, best performance was obtained using receptor parametric mapping (RPM2) and one of the multi-linear reference tissue models (MRTM2), with k′2 being fixed in both methods. These models showed good correlation with SRTM, their BP ND results were less affected by noise and images showed good contrast. Furthermore, in simulations, RPM2 and MRTM2 provided the most accurate and precise BP ND estimates. RPM2 and MRTM2 are the methods of choice for parametric analysis of [18F]FDDNP studies.

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YNIMG Journal 2008 Journal Article

Image derived input functions for dynamic High Resolution Research Tomograph PET brain studies

  • Jurgen E.M. Mourik
  • Floris H.P. van Velden
  • Mark Lubberink
  • Reina W. Kloet
  • Bart N.M. van Berckel
  • Adriaan A. Lammertsma
  • Ronald Boellaard

The High Resolution Research Tomograph (HRRT) is a dedicated human brain positron emission tomography (PET) scanner. The aim of the present study was to validate the use of image derived input functions (IDIF) as an alternative for arterial sampling for HRRT human brain studies. To this end, IDIFs were extracted from 3D ordinary Poisson ordered subsets expectation maximization (OP-OSEM) and reconstruction based partial volume corrected (PVC) OP-OSEM images. IDIFs, either derived directly from regions of interest or further calibrated using manual samples taken during scans, were evaluated for dynamic [11C]flumazenil data (n =6). Results obtained with IDIFs were compared with those obtained using blood sampler input functions (BSIF). These comparisons included areas under the curve (AUC) for peak (0–3. 3 min) and tail (3. 3–55. 0 min). In addition, slope, intercept and Pearson's correlation coefficient of tracer kinetic analysis results based on IDIF and BSIF were calculated for each subject. Good peak AUC ratios (0. 83±0. 21) between IDIF and BSIF were found for calibrated IDIFs extracted from OP-OSEM images. This combination of IDIFs and images also provided good slope values (1. 07±0. 11). Improved resolution, as obtained with PVC OP-OSEM, changed AUC ratios to 1. 14±0. 35 and, for tracer kinetic analysis, slopes changed to 0. 95±0. 13. For all reconstructions, non-calibrated IDIFs gave poorer results (>61±34% higher slopes) compared with calibrated IDIFs. The results of this study indicate that the use of IDIFs, extracted from OP-OSEM or PVC OP-OSEM images, is feasible for dynamic HRRT data, thereby obviating the need for online arterial sampling.

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YNIMG Journal 2008 Journal Article

Partial volume corrected image derived input functions for dynamic PET brain studies: Methodology and validation for [11C]flumazenil

  • Jurgen E.M. Mourik
  • Mark Lubberink
  • Ursula M.H. Klumpers
  • Emile F. Comans
  • Adriaan A. Lammertsma
  • Ronald Boellaard

Extraction of arterial input functions from dynamic brain scans may obviate the need for arterial sampling and would increase the clinical applicability of quantitative PET studies. The aim of the present study was to evaluate applicability and accuracy of image derived input functions (IDIFs) following reconstruction based partial volume correction (PVC). Settings for the PVC ordered subset expectation maximization (PVC-OSEM) reconstruction algorithm were varied. In addition, different methods for defining arterial regions of interest (ROI) in order to extract IDIFs were evaluated. [11C]flumazenil data of 10 subjects were used in the present study. Results obtained with IDIFs were compared with those using standard on-line measured arterial input functions. These included areas under the curve (AUC) for peak (1–2 min) and tail (2–60 min), volume of distribution (V T) obtained using Logan analysis, and V T and K 1 obtained with a basis function implementation of a single tissue compartment model. Best results were obtained with PVC-OSEM using 4 iterations and 16 subsets. Based on 11C point source measurements, a 4. 5 mm FWHM (full width at half maximum) resolution kernel was used to correct for partial volume effects. A ROI consisting of the four hottest pixels per plane (over the carotid arteries) was the best method to extract IDIFs. Excellent peak AUC ratios (0. 99±0. 09) between IDIF and blood sampler input function (BSIF) were found. Furthermore, extracted IDIFs provided V T and K 1 values that were very similar to those obtained using BSIFs. The proposed method appears to be suitable for analysing [11C]flumazenil data without the need for online arterial sampling.

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YNIMG Journal 2008 Journal Article

Simplified parametric methods for [11C]PIB studies

  • Maqsood Yaqub
  • Nelleke Tolboom
  • Ronald Boellaard
  • Bart N.M. van Berckel
  • Erica W. van Tilburg
  • Gert Luurtsema
  • Philip Scheltens
  • Adriaan A. Lammertsma

The purpose of the present study was to evaluate the performance of various parametric reference tissue models for quantification of [11C]PIB studies. Several models with and without fixing the reference tissue efflux rate constant (k′2) were investigated using both simulations and clinical data. The following parametric methods were evaluated: receptor parametric mapping (basis function implementation of the simplified reference tissue model with and without fixed k′2), reference Logan, and several multi-linear reference tissue methods (again with and without fixed k′2). In addition, standardised uptake value ratios with cerebellum (SUVr) were evaluated. Simulations were used to assess the effects of variation in flow (R 1), fractional blood volume (V b) and binding potential (BP ND ) itself on precision and accuracy of parametric BP ND. For clinical studies, most parametric methods showed comparable performance, with poorest results for SUVr. Best performance was obtained for receptor parametric mapping (RPM2) and one of the multi-linear reference tissue models (MRTM2), both with fixed k′2: BPND outcome was less affected by noise and the images showed better contrast than other tested methods. RPM2 and MRTM2 also provided best accuracy and precision in the simulation studies and are therefore the methods of choice for parametric analysis of clinical [11C]PIB studies.

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YNIMG Journal 2007 Journal Article

SPM analysis of parametric (R)-[11C]PK11195 binding images: Plasma input versus reference tissue parametric methods

  • Alie Schuitemaker
  • Bart N.M. van Berckel
  • Marc A. Kropholler
  • Dick J. Veltman
  • Philip Scheltens
  • Cees Jonker
  • Adriaan A. Lammertsma
  • Ronald Boellaard

(R)-[11C]PK11195 has been used for quantifying cerebral microglial activation in vivo. In previous studies, both plasma input and reference tissue methods have been used, usually in combination with a region of interest (ROI) approach. Definition of ROIs, however, can be labourious and prone to interobserver variation. In addition, results are only obtained for predefined areas and (unexpected) signals in undefined areas may be missed. On the other hand, standard pharmacokinetic models are too sensitive to noise to calculate (R)-[11C]PK11195 binding on a voxel-by-voxel basis. Linearised versions of both plasma input and reference tissue models have been described, and these are more suitable for parametric imaging. The purpose of this study was to compare the performance of these plasma input and reference tissue parametric methods on the outcome of statistical parametric mapping (SPM) analysis of (R)-[11C]PK11195 binding. Dynamic (R)-[11C]PK11195 PET scans with arterial blood sampling were performed in 7 younger and 11 elderly healthy subjects. Parametric images of volume of distribution (V d) and binding potential (BP) were generated using linearised versions of plasma input (Logan) and reference tissue (Reference Parametric Mapping) models. Images were compared at the group level using SPM with a two-sample t-test per voxel, both with and without proportional scaling. Parametric BP images without scaling provided the most sensitive framework for determining differences in (R)-[11C]PK11195 binding between younger and elderly subjects. V d images could only demonstrate differences in (R)-[11C]PK11195 binding when analysed with proportional scaling due to intersubject variation in K 1/k 2 (blood–brain barrier transport and non-specific binding).

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YNIMG Journal 2003 Journal Article

Attenuation correction of PET activation studies in the presenceof task-related motion

  • Odile A van den Heuvel
  • Ronald Boellaard
  • Dick J Veltman
  • Catalina Mesina
  • Adriaan A Lammertsma

Motion-induced misalignment between transmission and emission scans can result in erroneous estimation of regional tissue activity concentrations. If this motion is of a random nature, mismatch between transmission and emission scans is likely to result in diminished signal-to-noise ratios. In the case of task-related motion, however, corresponding systematic reconstruction artefacts may lead to false-positive or false-negative results. The purpose of the present study was to investigate whether implementation of an image registration (IR) method, which allows for motion-corrected attenuation correction, would improve accuracy of H2 15O PET activation studies. To evaluate the performance of this method, phantom studies as well as studies in human subjects were performed. Results were compared with three alternative methods: standard attenuation correction without motion correction, calculated attenuation correction, and no attenuation correction. The phantom measurements showed that, for quantitative assessment of regional activity concentrations, the IR method was superior to the other attenuation correction methods. In a single-subject study with intentional task-related motion during a visual stimulation paradigm, false-positive results, obtained with the standard attenuation correction method, disappeared after attenuation correction using the IR method. Finally, a group analysis of 11 patients indicated that an increase in signal-to-noise ratio was obtained with the IR method. Therefore, in our view, the IR method should be considered as a first choice for attenuation correction in PET activation studies.

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YNIMG Journal 2003 Journal Article

Effects of attenuation correction and reconstruction method on PET activation studies

  • Catalina T Mesina
  • Ronald Boellaard
  • Odile A van den Heuvel
  • Dick J Veltman
  • Geurt Jongbloed
  • Aad W van der Vaart
  • Adriaan A Lammertsma

The outcome of Statistical Parametric Mapping (SPM) analyses of PET activation studies depends among others, on the quality of reconstructed data. In general, filtered back-projection (FBP) is used for reconstruction in PET activation studies. There is, however, increasing interest in iterative reconstruction algorithms such as ordered subset expectation maximization (OSEM) algorithms. The aim of the present study was to investigate the effects of reconstruction techniques and attenuation correction (AC) on the detection of activation foci following statistical analysis with SPM. First, a replicate study was performed to assess the effects of the reconstruction method on pixel variance. Second, a phantom study was performed to evaluate the influence of both locations of an activated area and applied reconstruction method on SPM outcome. A volumetric method was used to compute the number of false positive voxels for all reconstructions. In addition, average t values within activation foci and for false positive voxels were calculated. For the assessment of the effects of reconstruction on clinical data, a group of 11 patients was studied. For all reconstructions SPM maps were created and compared. Both the clinical and the phantom data showed that use of iterative reconstruction methods reduced false positive results, while showing similar SPM results within activated areas as FBP. Reconstruction of data without attenuation correction reduced noise for FBP only, but did not affect the quality of SPM results for OSEM. It is concluded that OSEM is a good alternative for FBP reconstructions providing SPM results with less noise.

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YNIMG Journal 2003 Journal Article

Experimental evaluation of iterative reconstruction versus filtered back projection for 3D [15O]water PET activation studies using statistical parametric mapping analysis

  • Catalina T. Mesina
  • Ronald Boellaard
  • Geurt Jongbloed
  • Aad W. van der Vaart
  • Adriaan A. Lammertsma

Iterative reconstructions are increasingly used for clinical PET studies owing to the better noise properties compared with filtered backprojection (FBP). The purpose of the present study was to compare ordered subsets expectation maximization (OSEM) iterative reconstruction with FBP as input for statistical parametric mapping (SPM) analysis of PET activation studies. Two phantom studies were performed simulating both motor and cognitive tasks and acquiring data with both high and low statistics. In contrast to clinical studies, where no a priori information is known, phantom studies allow for an accurate and detailed comparison between different reconstruction techniques. The significance of “activations” during “tasks” was determined using SPM99 software. Using region of interest analysis of SPM results, it was found that the maximum and average t values within each hot spot of the phantom were higher for OSEM than for FBP. In addition, OSEM4 × 16 (4 iterations, 16 subsets) produced fewer false-positive voxels than FBP, OSEM1 × 16 and OSEM2 × 16. In conclusion, for PET activation studies use of OSEM4 × 16 seems to give the best tradeoff between signal detection and noise reduction.

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v2026.09.13