Quantitative myelin imaging with MRI and PET: an overview of techniques and their validation status.

Myelin is the protective sheath wrapped around axons, consisting of a phospholipid bilayer with water between the wraps. The measurement of damage to the myelin sheaths, the evaluation of the efficacy of therapies aiming to promote remyelination and monitoring the degree of brain maturation in children all require non-invasive quantitative myelin imaging methods. To date, various myelin imaging techniques have been developed. Five different MRI approaches can be distinguished based on their biophysical principles: (i) imaging of the water between the lipid bilayers directly (e.g. myelin water imaging); (ii) imaging the non-aqueous protons of the phospholipid bilayer directly with ultra-short echo-time techniques; (iii) indirect imaging of the macromolecular content (e.g. magnetization transfer; inhomogeneous magnetization transfer); (iv) mapping of the effects of the myelin sheath's magnetic susceptibility on the MRI signal (e.g. quantitative susceptibility mapping); and (v) mapping of the effects of the myelin sheath on water diffusion. Myelin imaging with PET uses radioactive molecules with high affinity to specific myelin components, in particular myelin basic protein. This review aims to give an overview of the various myelin imaging techniques, their biophysical principles, image acquisition, data analysis and their validation status.

Non-invasive kinetic modelling approaches for quantitative analysis of brain PET studies.

Pharmacokinetic modelling with arterial sampling is the gold standard for analysing dynamic PET data of the brain. However, the invasive character of arterial sampling prevents its widespread clinical application. Several methods have been developed to avoid arterial sampling, in particular reference region methods. Unfortunately, for some tracers or diseases, no suitable reference region can be defined. For these cases, other potentially non-invasive approaches have been proposed: (1) a population based input function (PBIF), (2) an image derived input function (IDIF), or (3) simultaneous estimation of the input function (SIME). This systematic review aims to assess the correspondence of these non-invasive methods with the gold standard. Studies comparing non-invasive pharmacokinetic modelling methods with the current gold standard methods using an input function derived from arterial blood samples were retrieved from PubMed/MEDLINE (until December 2021). Correlation measurements were extracted from the studies. The search yielded 30 studies that correlated outcome parameters (VT, DVR, or BPND for reversible tracers; Ki or CMRglu for irreversible tracers) from a potentially non-invasive method with those obtained from modelling using an arterial input function. Some studies provided similar results for PBIF, IDIF, and SIME-based methods as for modelling with an arterial input function (R2 = 0.59-1.00, R2 = 0.71-1.00, R2 = 0.56-0.96, respectively), if the non-invasive input curve was calibrated with arterial blood samples. Even when the non-invasive input curve was calibrated with venous blood samples or when no calibration was applied, moderate to good correlations were reported, especially for the IDIF and SIME (R2 = 0.71-1.00 and R2 = 0.36-0.96, respectively). Overall, this systematic review illustrates that non-invasive methods to generate an input function are still in their infancy. Yet, IDIF and SIME performed well, not only with arterial blood calibration, but also with venous or no blood calibration, especially for some tracers without plasma metabolites, which would potentially make these methods better suited for clinical application. However, these methods should still be properly validated for each individual tracer and application before implementation.

Quantification of P-glycoprotein function at the human blood-brain barrier using [18F]MC225 and PET.

INTRODUCTION: P-glycoprotein (P-gp) is one of the most studied efflux transporters at the blood-brain barrier. It plays an important role in brain homeostasis by protecting the brain from a variety of endogenous and exogeneous substances. Changes in P-gp function are associated both with the onset of neuropsychiatric diseases, including Alzheimer's disease and Parkinson's disease, and with drug-resistance, for example in treatment-resistant depression. The most widely used approach to measure P-gp function in vivo is (R)-[11C]verapamil PET. (R)-[11C]verapamil is, however, an avid P-gp substrate, which complicates the use of this tracer to measure an increase in P-gp function as its baseline uptake is already very low. [18F]MC225 was developed to measure both increases and decreases in P-gp function. AIM: The aim of this study was (1) to identify the pharmacokinetic model that best describes [18F]MC225 kinetics in the human brain and (2) to determine test-retest variability. METHODS: Five (2 male, 3 female) of fourteen healthy subjects (8 male, 6 female, age 67 ± 5 years) were scanned twice (injected dose 201 ± 47 MBq) with a minimum interval of 2 weeks between scans. Each scanning session consisted of a 60-min dynamic [18F]MC225 scan with continuous arterial sampling. Whole brain grey matter data were fitted to a single tissue compartment model, and to reversible and irreversible two tissue-compartment models to obtain various outcome parameters (in particular the volume of distribution (VT), Ki, and the rate constants K1 and k2). In addition, a reversible two-tissue compartment model with fixed k3/k4 was included. The preferred model was selected based on the weighted Akaike Information Criterion (AIC) score. Test-retest variability (TRTV) was determined to assess reproducibility. RESULTS: Sixty minutes post-injection, the parent fraction was 63.8 ± 4.0%. The reversible two tissue compartment model corrected for plasma metabolites with an estimated blood volume (VB) showed the highest AIC weight score of 34.3 ± 17.6%. The TRVT of the VT for [18F]MC225 PET scans was 28.3 ± 20.4% for the whole brain grey matter region using this preferred model. CONCLUSION: [18F]MC225 VT, derived using a reversible two-tissue compartment model, is the preferred parameter to describe P-gp function in the human BBB. This outcome parameter has an average test-retest variability of 28%. TRIAL REGISTRATION: EudraCT 2020-001564-28 . Registered 25 May 2020.

Investigation of image-derived input functions for non-invasive quantification of myelin density using [11C]MeDAS PET.

Multiple sclerosis (MS) is an inflammatory demyelinating disease. Current treatments are focussed on immune suppression to modulate pathogenic activity that causes myelin damage. New treatment strategies are needed to prevent demyelination and promote remyelination. Development of such myelin repair therapies require a sensitive and specific biomarker for efficacy evaluation. Recently, it has been shown that quantification of myelin density is possible using [11C]MeDAS PET. This method, however, requires arterial blood sampling to generate an arterial input function (AIF). As the invasive nature of arterial sampling will reduce clinical applicability, the purpose of this study was to assess whether an image-derived input function (IDIF) can be used as an alternative way to facilitate its routine clinical use. Six healthy controls and 11 MS patients underwent MRI and [11C]MeDAS PET with arterial blood sampling. The application of both population-based whole blood-to-plasma conversion and metabolite corrections were assessed for the AIF. Next, summed images of the early time frames (0-70 s) and the frame with the highest blood-brain contrast were used to generate IDIFs. IDIFs were created using either the hottest 2, 4, 6 or 12 voxels, or an isocontour of the hottest 10% voxels of the carotid artery. This was followed by blood-to-plasma conversion and metabolite correction of the IDIF. The application of a population-based metabolite correction of the AIF resulted in high correlations of tracer binding (Ki) within subjects, but variable bias across subjects. All IDIFs had a sharper and higher peak in the blood curves than the AIF, most likely due to dispersion during blood sampling. All IDIF methods resulted in similar high correlations within subjects (r = 0.95-0.98), but highly variable bias across subjects (mean slope=0.90-1.09). Therefore, both the use of population based blood-plasma and metabolite corrections and the generation of the image-derived whole-blood curve resulted in substantial bias in [11C]MeDAS PET quantification, due to high inter-subject variability. Consequently, when unbiased quantification of [11C]MeDAS PET data is required, individual AIF needs to be used.

Quantitative assessment of myelin density using [11C]MeDAS PET in patients with multiple sclerosis: a first-in-human study.

PURPOSE: Multiple sclerosis (MS) is a disease characterized by inflammatory demyelinated lesions. New treatment strategies are being developed to stimulate myelin repair. Quantitative myelin imaging could facilitate these developments. This first-in-man study aimed to evaluate [11C]MeDAS as a PET tracer for myelin imaging in humans. METHODS: Six healthy controls and 11 MS patients underwent MRI and dynamic [11C]MeDAS PET scanning with arterial sampling. Lesion detection and classification were performed on MRI. [11C]MeDAS time-activity curves of brain regions and MS lesions were fitted with various compartment models for the identification of the best model to describe [11C]MeDAS kinetics. Several simplified methods were compared to the optimal compartment model. RESULTS: Visual analysis of the fits of [11C]MeDAS time-activity curves showed no preference for irreversible (2T3k) or reversible (2T4k) two-tissue compartment model. Both volume of distribution and binding potential estimates showed a high degree of variability. As this was not the case for 2T3k-derived net influx rate (Ki), the 2T3k model was selected as the model of choice. Simplified methods, such as SUV and MLAIR2 correlated well with 2T3k-derived Ki, but SUV showed subject-dependent bias when compared to 2T3k. Both the 2T3k model and the simplified methods were able to differentiate not only between gray and white matter, but also between lesions with different myelin densities. CONCLUSION: [11C]MeDAS PET can be used for quantification of myelin density in MS patients and is able to distinguish differences in myelin density within MS lesions. The 2T3k model is the optimal compartment model and MLAIR2 is the best simplified method for quantification. TRIAL REGISTRATION: NL7262. Registered 18 September 2018.

Imaging of neuroinflammation due to repetitive head injury in currently active kickboxers.

PURPOSE: Chronic traumatic encephalopathy refers to a neurodegenerative disease resulting from repetitive head injury of participants in contact sports. Similar to other neurodegenerative diseases, neuroinflammation is thought to play a role in the onset and progression of the disease. Limited knowledge is available regarding the neuroinflammatory consequences of repetitive head injury in currently active contact sports athletes. PET imaging of the 18-kDa translocator protein (TSPO) allows quantification of microglial activation in vivo, a marker of neuroinflammation. METHODS: Eleven rank A kickboxers and 11 age-matched controls underwent TSPO PET using [11C]-PK11195, anatomical MRI, diffusion tensor imaging, and neuropsychological testing. Relevant imaging parameters were derived and correlated with the outcomes of the neuropsychological testing. RESULTS: On a group level, no statistically significant differences were detected in non-displaceable binding potential (BPND) using PET. Individually, 3 kickboxers showed increased BPNDs in widespread regions of the brain without a correlation with other modalities. Increased FA was observed in the superior corona radiata bilaterally. DTI parameters in other regions did not differ between groups. CONCLUSION: Despite negative results on a group level, individual results suggest that neuroinflammation may be present as a consequence of repetitive head injury in active kickboxers. Future studies using a longitudinal design may determine whether the observed TSPO upregulation is related to the future development of neuropsychiatric symptoms.

Myelin quantification with MRI: A systematic review of accuracy and reproducibility.

OBJECTIVES: Currently, multiple sclerosis is treated with anti-inflammatory therapies, but these treatments lack efficacy in progressive disease. New treatment strategies aim to repair myelin damage and efficacy evaluation of such new therapies would benefit from validated myelin imaging techniques. Several MRI methods for quantification of myelin density are available now. This systematic review aims to analyse the performance of these MRI methods. METHODS: Studies comparing myelin quantification by MRI with histology, the current gold standard, or assessing reproducibility were retrieved from PubMed/MEDLINE and Embase (until December 2019). Included studies assessed both myelin histology and MRI quantitatively. Correlation or variance measurements were extracted from the studies. Non-parametric tests were used to analyse differences in study methodologies. RESULTS: The search yielded 1348 unique articles. Twenty-two animal studies and 13 human studies correlated myelin MRI with histology. Eighteen clinical studies analysed the reproducibility. Overall bias risk was low or unclear. All MRI methods performed comparably, with a mean correlation between MRI and histology of R2=0.54 (SD=0.30) for animal studies, and R2=0.54 (SD=0.18) for human studies. Reproducibility for the MRI methods was good (ICC=0.75-0.93, R2=0.90-0.98, COV=1.3-27%), except for MTR (ICC=0.05-0.51). CONCLUSIONS: Overall, MRI-based myelin imaging methods show a fairly good correlation with histology and a good reproducibility. However, the amount of validation data is too limited and the variability in performance between studies is too large to select the optimal MRI method for myelin quantification yet.

Pharmacokinetic Analysis of [18F]FES PET in the Human Brain and Pituitary Gland.

PURPOSE: Estrogen receptors (ER) are implicated in psychiatric disorders. We assessed if ER availability in the human brain could be quantified using 16α-[18F]-fluoro-17ß-estradiol ([18F]FES) positron emission tomography (PET). PROCEDURES: Seven post­menopausal women underwent a dynamic [18F]FES PET scan with arterial blood sampling. A T1-weighted MRI was acquired for anatomical information. After one week, four subjects received a selective ER degrader (SERD), four hours before the PET scan. Pharmacokinetic analysis was performed using a metabolite-corrected plasma curve as the input function. The optimal kinetic model was selected based on the Akaike information criterion and standard error of estimated parameters. Accuracy of Logan graphical analysis and standardized uptake value (SUV) was determined via correlational analyses. RESULTS: The reversible two-tissue compartment model (2T4k) model with fixed K1/k2 was preferred. The total volume of distribution (VT) could be more reliably estimated than the binding potential (BPND). A high correlation of VT with Logan graphical analysis was observed, but only a moderate correlation with SUV. SERD administration resulted in a reduced VT in the pituitary gland, but not in other regions. CONCLUSIONS: The optimal quantification method for [18F]FES was the 2T4k with fixed K1/k2 or Logan graphical analysis, but specific binding was only observed in the pituitary gland.

Can Internal Carotid Arteries Be Used for Noninvasive Quantification of Brain PET Studies?

Because of the limited axial field of view of conventional PET scanners, the internal carotid arteries are commonly used to obtain an image-derived input function (IDIF) in quantitative brain PET. However, time-activity curves extracted from the internal carotids are prone to partial-volume effects due to the limited PET resolution. This study aimed to assess the use of the internal carotids for quantifying brain glucose metabolism before and after partial-volume correction. Methods: Dynamic [18F]FDG images were acquired on a 106-cm-long PET scanner, and quantification was performed with a 2-tissue-compartment model and Patlak analysis using an IDIF extracted from the internal carotids. An IDIF extracted from the ascending aorta was used as ground truth. Results: The internal carotid IDIF underestimated the area under the curve by 37% compared with the ascending aorta IDIF, leading to Ki values approximately 17% higher. After partial-volume correction, the mean relative Ki differences calculated with the ascending aorta and internal carotid IDIFs dropped to 7.5% and 0.05%, when using a 2-tissue-compartment model and Patlak analysis, respectively. However, microparameters (K 1, k 2, k 3) derived from the corrected internal carotid curve differed significantly from those obtained using the ascending aorta. Conclusion: These results suggest that partial-volume-corrected internal carotids may be used to estimate Ki but not kinetic microparameters. Further validation in a larger patient cohort with more variable kinetics is needed for more definitive conclusions.

Unsupervised Pattern Analysis to Differentiate Multiple Sclerosis Phenotypes Using Principal Component Analysis on Various MRI Sequences.

Background: Multiple sclerosis (MS) has two main phenotypes: relapse-remitting MS (RRMS) and progressive MS (PMS), distinguished by disability profiles and treatment response. Differentiating them using conventional MRI is challenging. Objective: This study explores the use of scaled subprofile modelling using principal component analysis (SSM/PCA) on MRI data to distinguish between MS phenotypes. Methods: MRI scans were performed on patients with RRMS (n = 30) and patients with PMS (n = 20), using the standard sequences T1w, T2w, T2w-FLAIR, and the myelin-sensitive sequences magnetisation transfer (MT) ratio (MTR), quantitative MT (qMT), inhomogeneous MT ratio (ihMTR), and quantitative inhomogeneous MT (qihMT). Results: SSM/PCA analysis of qihMT images best differentiated PMS from RRMS, with the highest specificity (87%) and positive predictive value (PPV) (83%), but a lower sensitivity (67%) and negative predictive value (NPV) (72%). Conversely, T1w data analysis showed the highest sensitivity (93%) and NPV (89%), with a lower PPV (67%) and specificity (53%). Phenotype classification agreement between T1w and qihMT was observed in 57% of patients. In the subset with concordant classifications, the sensitivity, specificity, PPV, and NPV were 100%, 88%, 90%, and 100%, respectively. Conclusions: SSM/PCA on MRI data revealed distinctive patterns for MS phenotypes. Optimal discrimination occurred with qihMT and T1w sequences, with qihMT identifying PMS and T1w identifying RRMS. When qihMT and T1w analyses align, MS phenotype prediction improves.

The effect of lesion filling on brain network analysis in multiple sclerosis using structural magnetic resonance imaging.

BACKGROUND: Graph theoretical network analysis with structural magnetic resonance imaging (MRI) of multiple sclerosis (MS) patients can be used to assess subtle changes in brain networks. However, the presence of multiple focal brain lesions might impair the accuracy of automatic tissue segmentation methods, and hamper the performance of graph theoretical network analysis. Applying "lesion filling" by substituting the voxel intensities of a lesion with the voxel intensities of nearby voxels, thus creating an image devoid of lesions, might improve segmentation and graph theoretical network analysis. This study aims to determine if brain networks are different between MS subtypes and healthy controls (HC) and if the assessment of these differences is affected by lesion filling. METHODS: The study included 49 MS patients and 19 HC that underwent a T1w, and T2w-FLAIR MRI scan. Graph theoretical network analysis was performed from grey matter fractions extracted from the original T1w-images and T1w-images after lesion filling. RESULTS: Artefacts in lesion-filled T1w images correlated positively with total lesion volume (r = 0.84, p < 0.001) and had a major impact on grey matter segmentation accuracy. Differences in sensitivity for network alterations were observed between original T1w data and after application of lesion filling: graph theoretical network analysis obtained from lesion-filled T1w images produced more differences in network organization in MS patients. CONCLUSION: Lesion filling might reduce variability across subjects resulting in an increased detection rate of network alterations in MS, but also induces significant artefacts, and therefore should be applied cautiously especially in individuals with higher lesions loads.

Amyloid PET and cognitive decline in cognitively normal individuals: the SCIENCe project.

We examined the relationships between amyloid-ß PET and concurrent and longitudinal cognitive performance in 107 cognitively normal individuals with subjective cognitive decline (age: 64 ± 8 years, 44% female, Mini-Mental State Examination score 29 ± 1). All underwent 90-minute dynamic [18F]florbetapir PET scanning and longitudinal neuropsychological tests with a mean follow-up of 3.4 ± 3.0 years. Receptor parametric mapping was used to calculate [18F]florbetapir binding potential (BPND), and we performed linear mixed models to assess the relationships between global [18F]florbetapir BPND and neuropsychological performance. Higher [18F]florbetapir BPND was related to lower concurrent Mini-Mental State Examination (ß ± SE: -1.69 ± 0.63 p < 0.01) and to steeper rate of decline on tasks capturing memory (Rey Auditory Verbal Learning Task immediate [ß ± SE -1.81 ± 0.81, p < 0.05] and delayed recall [ß ± SE -1.19 ± 0.34, p < 0.01]), attention/executive functions (Stroop II [color] [ß ± SE -0.02 ± 0.01, p < 0.05], Stroop III [word-color] [ß ± SE -0.03 ± 0.02, p < 0.05]), and language (category fluency [ß ± SE -0.04 ± 0.01, p < 0.01]). These findings suggest that higher amyloid-ß load in cognitively normal individuals with subjective cognitive decline from a memory clinic is associated with lower concurrent global cognition and with faster rate of decline in a variety of cognitive domains.

Amyloid-ß Load Is Related to Worries, but Not to Severity of Cognitive Complaints in Individuals With Subjective Cognitive Decline: The SCIENCe Project.

Objective: Subjective cognitive decline (SCD) is associated with an increased risk of Alzheimer's Disease (AD). Early disease processes, such as amyloid-ß aggregation measured with quantitative PET, may help to explain the phenotype of SCD. The aim of this study was to investigate whether quantitative amyloid-ß load is associated with both self- and informant-reported cognitive complaints and memory deficit awareness in individuals with SCD. Methods: We included 106 SCD patients (mean ± SD age: 64 ± 8, 45%F) with 90 min dynamic [18F]florbetapir PET scans. We used the following questionnaires to assess SCD severity: cognitive change index (CCI, self and informant reports; 2 × 20 items), subjective cognitive functioning (SCF, four items), and five questions "Do you have complaints?" (yes/no) for memory, attention, organization and language), and "Does this worry you? (yes/no)." The Rivermead Behavioral Memory Test (RBMT)-Stories (immediate and delayed recall) was used to assess objective episodic memory. To investigate the level of self-awareness, we calculated a memory deficit awareness index (Z-transformed (inverted self-reported CCI minus episodic memory); higher index, heightened self-awareness) and a self-proxy index (Z-transformed self- minus informant-reported CCI). Mean cortical [18F]florbetapir binding potential (BPND) was derived from the PET data. Logistic and linear regression analyses, adjusted for age, sex, education, and depressive symptoms, were used to investigate associations between BPND and measures of SCD. Results: Higher mean cortical [18F]florbetapir BPND was associated with SCD-related worries (odds ratio = 1.76 [95%CI = 1.07 ± 2.90]), but not with other SCD questionnaires (informant and self-report CCI or SCF, total scores or individual items, all p > 0.05). In addition, higher mean cortical [18F]florbetapir BPND was associated with a higher memory deficit awareness index (Beta = 0.55), with an interaction between BPND and education (p = 0.002). There were no associations between [18F]florbetapir BPND and self-proxy index (Beta = 0.11). Conclusion: Amyloid-ß deposition was associated with SCD-related worries and heightened memory deficit awareness (i.e., hypernosognosia), but not with severity of cognitive complaints. Our findings indicate that worries about self-perceived decline may reflect an early symptom of amyloid-ß related pathology rather than subjective cognitive functioning.

A novel partial volume correction method for accurate quantification of [18F] flortaucipir in the hippocampus.

BACKGROUND: Off-target binding in the choroid plexus (CP) may cause spill-in of the tau PET tracer [18F] flortaucipir into the adjacent hippocampus region. The impact of this spill-in on hippocampal uptake was assessed using a novel partial volume correction method (PVC). METHODS: PVC was performed on 20 [18F] flortaucipir dynamic PET scans (10 probable AD and 10 controls). Volumes of interest (VOIs) were defined for both hippocampus and CP. The correlation between hippocampal and CP distribution volume (VT), with and without PVC, was determined. Both anatomically defined and eroded VOIs were used. RESULTS: For controls, the correlation between hippocampal and CP VT was significantly reduced after using PVC along with an eroded VOI (r2 = 0.59, slope = 0.80 versus r2 = 0.15, slope = 0.15; difference: p < 0.05). The same was true for AD patients (p < 0.05). CONCLUSION: PVC together with an optimized hippocampal VOI resulted in effective reduction of CP spill-in and improved accuracy of hippocampal VT.