Background: Paired cerebral blood flow (CBF) measurement is usually acquired before and after vasoactive stimulus to estimate cerebrovascular reserve (CVR). However, CVR may be confounded because of variations in time-to-maximum CBF response (t_max) following acetazolamide injection. With a mathematical model, CVR can be calculated insensitive to variations in t_max, and a model offers the possibility to calculate additional model-derived parameters. A model that describes the temporal CBF response following a vasodilating acetazolamide injection is proposed and evaluated.

Methods: A bi-exponential model was adopted and fitted to four CBF measurements acquired using arterial spin labelling before and initialised at 5, 15 and 25 min after acetazolamide injection in a total of fifteen patients with Moyamoya disease. Curve fitting was performed using a non-linear least squares method with a priori constraints based on simulations.

Results: Goodness of fit (mean absolute error) varied between 0.30 and 0.62 ml·100 g^-1·min^-1. Model-derived CVR was significantly higher compared to static CVR measures. Maximum CBF increase occurred earlier in healthy- compared to diseased vascular regions.

Conclusions: The proposed mathematical model offers the possibility to calculate CVR insensitive to variations in time to maximum CBF response which gives a more detailed characterisation of CVR compared to static CVR measures. Although the mathematical model adapts generally well to this dataset of patients with MMD it should be considered as experimental; hence, further studies in healthy populations and other patient cohorts are warranted.

Hybrid PET/magnetic resonance (MR) can provide physiological, functional, and structural information simultaneously, facilitating research in neurological disorders. For quantitative PET, correction for photon attenuation (AC) is necessary. However, in contrast to dedicated PET and PET/computed tomography (CT) systems, PET/MR has no direct possibility to measure photon attenuation. As such, MR-based methods are required for AC (MRAC), and these need to be thoroughly validated before clinical implementation.

The primary aim of this thesis was to evaluate two vendor-provided MRAC methods (single-atlas and zero echo time, ZTE), a previously published maximum probability (MaxProb) method, and a composite transmission scan atlas (CTR) method for a SIGNA PET/MR. This evaluation was done both in terms of absolute quantification in static scans and of outcome measures of tracer kinetic modelling based on dynamic scans. The secondary aim was to compare quantitative brain PET measurements acquired on the SIGNA PET/MR with those acquired on a dedicated PET scanner. Ten patients with parkinsonism who underwent dynamic dopamine transporter scans using 11C-PE2I in a PET/MR and dedicated PET were included. Standardized uptake values (SUV), binding potential (BPND), and relative delivery (R1) were assessed at volume of interest (VOI) and voxel level to compare the various MRAC methods with the gold-standard, a 68Ge transmission scan, and to compare quantitative outcomes between scanners.

In general, ZTE provided the highest precision in SUV, R1 and BPND, showing the least inter-subject variability in bias compared to 68Ge-transmission AC, whereas MaxProb and CTR showed the lowest precision. Contrary to this, accuracy of absolute SUV values was best for CTR followed by MaxProb, with ZTE showing a homogeneous positive bias of about 10%. ZTE provided the highest accuracy in outcome measures of tracer kinetic analysis. Differences in quantitative results between stand-alone PET and PET/MR exceeded what can be explained by difference in AC alone, although they were still comparable to previously published test-retest variability of 11C-PE2I. Additionally, an activation in the auditory cortex was seen in PET data from the PET/MR because of the noise produced by the MR gradients.

ZTE-MRAC appears to be the best method for dynamic scanning and tracer kinetic analysis using reference methods, while CTR- and MaxProb-MRAC appear the most appropriate for absolute quantification. Also, attention should be taken to the auditory cortex activation in R1 images when comparing data from PET/MR and other PET- systems.

PET/MR systems demanded great efforts for accurate attenuation correction (AC) but differences in technology, geometry and hardware attenuation may also affect quantitative results. Dedicated PET systems using transmission-based AC are regarded as the gold standard for quantitative brain PET. The study aim was to investigate the agreement between quantitative PET outcomes from a PET/MR scanner against a stand-alone PET system.Nine patients with Parkinsonism underwent two 80-min dynamic PET scans with the dopamine transporter ligand [11C]PE2I. Images were reconstructed with resolution-matched settings using 68Ge-transmission (standalone PET), and zero-echo-time MR (PET/MR) scans for AC. Non-displaceable binding potential (BPND) and relative delivery (R1) were evaluated using volumes of interest and voxel-wise analysis.Correlations between systems were high (r >= 0.85) for both quantitative outcome parameters in all brain regions. Striatal BPND was significantly lower on PET/MR than on stand-alone PET (-7%). R1 was significantly overestimated in posterior cortical regions (9%) and underestimated in striatal (-9%) and limbic areas (-6%). The voxel-wise evaluation revealed that the MR-safe headphones caused a negative bias in both parametric BPND and R1 images. Additionally, a significant positive bias of R1 was found in the auditory cortex, most likely due to the acoustic background noise during MR imaging. The relative bias of the quantitative [11C]PE2I PET data acquired from a SIGNA PET/MR system was in the same order as the expected test-retest reproducibility of [11C]PE2I BPND and R1, compared to a stand-alone ECAT PET scanner. MR headphones and background noise are potential sources of error in functional PET/MR studies.

Accurate attenuation correction (AC) in positron emission tomography (PET) imaging is a prerequisite for obtaining quantitatively correct images and ⁶⁸Ge-AC is considered the gold standard for PET AC. In this study we developed an alternative AC method for PET/MR, based on the registration of a database of ⁶⁸Ge-AC maps and T1-weighted MR image pairs. The present work aimed to evaluate this composite ⁶⁸Ge transmission AC (CTR-AC) method’s reliability compared to 68Ge-AC. The CTR database comprised 125 pairs of previously acquired ⁶⁸Ge-AC maps and T1-MRI scans. Ten patients underwent 80-min dynamic PET scans with the dopamine transporter ligand [¹¹C]PE2I on a SIGNA PET/MR. Images were reconstructed using a CTR-AC map and a previously acquired patient-specific ⁶⁸Ge-AC map on a stand-alone PET scanner. SUV as well as outcome parameters of [¹¹C]PE2I kinetic analysis, i.e., relative delivery (R₁) and dopamine transporter availability (BP_ND), were compared on a VOI and voxel-by-voxel basis.

CTR-AC showed high accuracy, with a mean bias of 0 ± 3% for whole-brain SUV, -0.1 ± 3.2% for whole-brain R₁, and 3.7 ± 8.1% for striatal BP_ND. The precision of SUV and R1 was modest and lowest in the anterior cortex, with an R₁ bias of -1.1 ± 6.4%.

CTR-AC is straightforward and provides MRAC maps with continuous linear attenuation coefficient values. The method’s accuracy is comparable to the best MRAC methods published so far, with a near-zero bias in SUV and a bias similar to that previously found for ZTE-AC in outcome parameters of kinetic modelling.

Dedicated PET systems using transmission-based attenuation correction (AC) are regarded as the gold standard for quantitative brain PET. PET/MR systems demanded great efforts for accurate AC but differences in technology, geometry and hardware attenuation may also affect quantitative results. This study compares PET quantitative outcomes between a stand-alone PET and PET/MR scanner.

Ten patients with parkinsonism underwent two 80-min dynamic PET scans with the dopamine transporter ligand [11C]PE2I. Images were reconstructed using resolution-matched settings and transmission scans (stand-alone PET) and zero-echo-time (PET/MR) for AC. SUV, relative delivery (R1), and dopamine transporter availability (BPND) were compared on a VOI- and voxel-basis. 

Correlations between systems were high (≥ 0.85) for all quantitative parameters. On VOI-basis, striatal BPND was significantly lower on PET/MR than on stand-alone PET (-7%). R1 was significantly overestimated in posterior cortical regions (9%) and underestimated in striatal (-9%) and limbic areas (-6%). SUV showed a similar pattern as R1. Voxel-by-voxel analysis showed significant positive bias of R1 in the auditory cortex.

PET/MR significantly underestimated striatal BPND, similar to previously reported [11C]PE2I BPND  test-retest variability. The acoustic noise in the PET/MR environment may attribute to an overestimation of R1 in the auditory cortex, which needs consideration when using PET/MR data.

In positron emission tomography (PET), ⁶⁸Ge-transmission scanning is considered the gold standard in attenuation correction (AC) though not available in current dual imaging systems. In this experimental study we evaluated a novel AC method for PET/magnetic resonance (MR) imaging which is essentially based on a composite database of multiple ⁶⁸Ge-transmission maps and T1-weighted (T1w) MR image-pairs (composite transmission, CTR-AC). This proof-of-concept study used retrospectively a database with 125 pairs of co-registered ⁶⁸Ge-AC maps and T1w MR images from anatomical normal subjects and a validation dataset comprising dynamic [¹¹C]PE2I PET data from nine patients with Parkinsonism. CTR-AC maps were generated by non-rigid image registration of all database T1w MRI to each subject's T1w, applying the same transformation to every ⁶⁸Ge-AC map, and averaging the resulting ⁶⁸Ge-AC maps. [¹¹C]PE2I PET images were reconstructed using CTR-AC and a patient-specific ⁶⁸Ge-AC map as the reference standard. Standardized uptake values (SUV) and quantitative parameters of kinetic analysis were compared, i.e., relative delivery (R₁) and non-displaceable binding potential (BP_ND). CTR-AC showed high accuracy for whole-brain SUV (mean %bias ± SD: 0.5 ± 3.5%), whole-brain R₁ (-0.1 ± 3.2%), and putamen BP_ND (3.7 ± 8.1%). SUV and R₁ precision (SD of %bias) were modest and lowest in the anterior cortex, with an R₁ %bias of -1.1 ± 6.4%). The prototype CTR-AC is capable of providing accurate MRAC-maps with continuous linear attenuation coefficients though still experimental. The method's accuracy is comparable to the best MRAC methods published so far, both in SUV and as found for ZTE-AC in quantitative parameters of kinetic modelling.

Background: MRI does not offer a direct method to obtain attenuation correction maps as its predecessors (stand-alone PET and PET/CT), and bone visualisation is particularly challenging. Recently, zero-echo-time (ZTE) was suggested for MR-based attenuation correction (AC). The aim of this work was to evaluate ZTE- and atlas-AC by comparison to ⁶⁸Ge-transmission scan-based AC.

Nine patients underwent brain PET/MR and stand-alone PET scanning using the dopamine transporter ligand ¹¹C-PE2I. For each of them, two AC maps were obtained from the MR images: an atlas-based, obtained from T1-weighted LAVA-FLEX imaging with cortical bone inserted using a CT-based atlas, and an AC map generated from proton-density-weighted ZTE images. Stand-alone PET ⁶⁸Ge-transmission AC map was used as gold standard. PET images were reconstructed using the three AC methods and standardised uptake value (SUV) values for the striatal, limbic and cortical regions, as well as the cerebellum (VOIs) were compared. SUV ratio (SUVR) values normalised for the cerebellum were also assessed. Bias, precision and agreement were calculated; statistical significance was evaluated using Wilcoxon matched-pairs signed-rank test.

Results: Both ZTE- and atlas-AC showed a similar bias of 6–8% in SUV values across the regions. Correlation coefficients with ⁶⁸Ge-AC were consistently high for ZTE-AC (r 0.99 for all regions), whereas they were lower for atlas-AC, varying from 0.99 in the striatum to 0.88 in the posterior cortical regions. SUVR showed an overall bias of 2.9 and 0.5% for atlas-AC and ZTE-AC, respectively. Correlations with ⁶⁸Ge-AC were higher for ZTE-AC, varying from 0.99 in the striatum to 0.96 in the limbic regions, compared to atlas-AC (0.99 striatum to 0.77 posterior cortex).

Conclusions: Absolute SUV values showed less variability for ZTE-AC than for atlas-AC when compared to ⁶⁸Ge-AC, but bias was similar for both methods. This bias is largely caused by higher linear attenuation coefficients in atlas- and ZTE-AC image compared to ⁶⁸Ge-images. For SUVR, bias was lower when using ZTE-AC than for atlas-AC. ZTE-AC shows to be a more robust technique than atlas-AC in terms of both intra- and inter-patient variability.

BACKGROUND: A valid photon attenuation correction (AC) method is instrumental for obtaining quantitatively correct PET images. Integrated PET/MR systems provide no direct information on attenuation, and novel methods for MR-based AC (MRAC) are still under investigation. Evaluations of various AC methods have mainly focused on static brain PET acquisitions. In this study, we determined the validity of three MRAC methods in a dynamic PET/MR study of the brain.

METHODS: Nine participants underwent dynamic brain PET/MR scanning using the dopamine transporter radioligand [¹¹C]PE2I. Three MRAC methods were evaluated: single-atlas (Atlas), multi-atlas (MaxProb) and zero-echo-time (ZTE). The ⁶⁸Ge-transmission data from a previous stand-alone PET scan was used as reference method. Parametric relative delivery (R₁) images and binding potential (BP_ND) maps were generated using cerebellar grey matter as reference region. Evaluation was based on bias in MRAC maps, accuracy and precision of [¹¹C]PE2I BP_ND and R₁ estimates, and [¹¹C]PE2I time-activity curves. BP_ND was examined for striatal regions and R₁ in clusters of regions across the brain.

RESULTS: For BP_ND, ZTE-MRAC showed the highest accuracy (bias < 2%) in striatal regions. Atlas-MRAC exhibited a significant bias in caudate nucleus (- 12%) while MaxProb-MRAC revealed a substantial, non-significant bias in the putamen (9%). R₁ estimates had a marginal bias for all MRAC methods (- 1.0-3.2%). MaxProb-MRAC showed the largest intersubject variability for both R₁ and BP_ND. Standardized uptake values (SUV) of striatal regions displayed the strongest average bias for ZTE-MRAC (~ 10%), although constant over time and with the smallest intersubject variability. Atlas-MRAC had highest variation in bias over time (+10 to - 10%), followed by MaxProb-MRAC (+5 to - 5%), but MaxProb showed the lowest mean bias. For the cerebellum, MaxProb-MRAC showed the highest variability while bias was constant over time for Atlas- and ZTE-MRAC.

CONCLUSIONS: Both Maxprob- and ZTE-MRAC performed better than Atlas-MRAC when using a ⁶⁸Ge transmission scan as reference method. Overall, ZTE-MRAC showed the highest precision and accuracy in outcome parameters of dynamic [¹¹C]PE2I PET analysis with use of kinetic modelling.