A prospective clinical study of the influence of oral protein intake on [18F]FET-PET uptake and test-retest repeatability in glioma.

BACKGROUND: O-(2-[18F]fluoroethyl)-L-tyrosine positron emission tomography ([18F]FET PET) scanning is used in routine clinical management and evaluation of gliomas with a recommended 4 h prior fasting. Knowledge of test-retest variation of [18F]FET PET imaging uptake metrics and the impact of accidental protein intake can be critical for interpretation. The aim of this study was to investigate the repeatability of [18F]FET-PET metrics and to assess the impact of protein-intake prior to [18F]FET PET scanning of gliomas. RESULTS: Test-retest variability in the non-protein group was good with absolute (and relative) upper and lower limits of agreement of + 0.15 and - 0.13 (+ 9.7% and - 9.0%) for mean tumour-to-background ratio (TBRmean), + 0.43 and - 0.28 (+ 19.6% and - 11.8%) for maximal tumour-to-background ratio (TBRmax), and + 2.14 cm3 and - 1.53 ml (+ 219.8% and - 57.3%) for biological tumour volume (BTV). Variation was lower for uptake ratios than for BTV. Protein intake was associated with a 27% increase in the total sum of plasma concentration of the L-type amino acid transporter 1 (LAT1) relevant amino acids and with decreased standardized uptake value (SUV) in both healthy appearing background brain tissue (mean SUV - 25%) and in tumour (maximal SUV - 14%). Oral intake of 24 g of protein 1 h prior to injection of tracer tended to increase variability, but the effects on derived tumour metrics TBRmean and TBRmax were only borderline significant, and changes generally within the variability observed in the group with no protein intake. CONCLUSION: The test-retest repeatability was found to be good, and better for TBRmax and TBRmean than BTV, with the methodological limitation that tumour growth may have influenced results. Oral intake of 24 g of protein one hour before a [18F]FET PET scan decreases uptake of [18F]FET in both tumour and in healthy appearing brain, with no clinically significant difference on the most commonly used tumour metrics.

The cingulate island sign in a mixed memory clinical cohort: Prevalence and diagnostic accuracy.

INTRODUCTION: Visual rating of the cingulate island sign (CIS) on [18F]fluorodeoxyglucose ([18F]FDG) positron emission tomography (PET) has a high specificity for dementia with Lewy bodies (DLB) in selected cohorts such as DLB versus Alzheimer's disease (AD). In a mixed memory clinical population this study aimed to uncover the prevalence of CIS, the diagnostic accuracy for DLB, and the relationship between CIS and disease severity. METHODS: CIS on [18F]FDG-PET was retrospectively assessed with the visual CIS rating scale (CISRs) in 1000 patients with a syndrome diagnosis of mild cognitive impairment (MCI) or dementia with no restrictions in etiological diagnosis. RESULTS: In this cohort 24.3 % had a CISRs score ≥1 and 3.5 % had a CISRs score = 4. The prevalence of a CISRs score ≥1 was highest in DLB (74.0 %, n = 57). A CISRs score ≥1 was present in at least 9 % in other diagnostic groups. The prevalence of CIS across disease severities showed no statistically significant difference (p = 0.23). To differentiate DLB from non-DLB the optimal cut-off was a CISRs score ≥1 (balanced accuracy = 77.1 %) in MCI/mild dementia and a CISRs score ≥2 (balanced accuracy = 80.6 %) in moderate/severe dementia. The positive predictive value of a CISRs score = 4 for DLB was 57.7 % in MCI/mild dementia and 33.3 % in moderate/severe dementia. CONCLUSION: The CISRs is useful in differentiating DLB from other etiologies in a mixed memory clinical population. Balanced accuracy and positive predictive value may vary across disease severities in the population studied.

Expanding the Spectrum of Stress-Induced Childhood-Onset Neurodegeneration with Variable Ataxia and Seizures (CONDSIAS).

Stress-induced childhood-onset neurodegeneration with variable ataxia and seizures (CONDSIAS) is an extremely rare, autosomal recessive neurodegenerative disorder. It is caused by biallelic pathogenic variants in the ADPRS gene, which encodes an enzyme involved in DNA repair, and is characterized by exacerbations in relation to physical or emotional stress, and febrile illness. We report a 24-year-old female, who was compound heterozygous for two novel pathogenic variants revealed by whole exome sequencing. Additionally, we summarize the published cases of CONDSIAS. In our patient, onset of symptoms occurred at 5 years of age and consisted of episodes of truncal dystonic posturing, followed half a year later by sudden diplopia, dizziness, ataxia, and gait instability. Progressive hearing loss, urinary urgency, and thoracic kyphoscoliosis ensued. Present neurological examination revealed dysarthria, facial mini-myoclonus, muscle weakness and atrophy of hands and feet, leg spasticity with clonus, truncal and appendicular ataxia, and spastic-ataxic gait. Hybrid [18F]-fluorodeoxyglucose (FDG) positron emission tomography/magnetic resonance imaging (PET/MRI) of the brain revealed cerebellar atrophy, particularly of the vermis, with corresponding hypometabolism. MRI of the spinal cord showed mild atrophy. After informed consent from the patient, we initiated experimental, off-label treatment with minocycline, a poly-ADP-polymerase (PARP) inhibitor, which has shown beneficial effects in a Drosophila fly model. The present case report expands the list of known pathogenic variants in CONDIAS and presents details of the clinical phenotype. Future studies will reveal whether PARP inhibition is an effective treatment strategy for CONDIAS.

Long-term prognostic value of [15O]H2O PET imaging in patients suspected for cerebral hemodynamic insufficiency.

OBJECTIVES: Quantitative regional cerebral perfusion (rCBF) measurements using [15O]H2O PET with arterial cannulation and acetazolamide (ACZ) challenge have been reserved to identify high-risk patients that are candidates for by-pass operation. We aimed to assess the prognostic value of various parameters in quantitative [15O]H2O PET measurements in patients not subsequently undergoing surgery. METHODS: We identified 32 eligible patients who underwent [15O]H2O brain PET imaging for suspicion of hemodynamic insufficiency between 2009 and 2020. Cerebrovascular events were defined as new ischemic lesions on MRI, stroke, transient ischemic attack, vascular dementia. Follow-up period was 91 months (range: 26-146). rCBF before (rCBFbase) and after (rCBFacz) ACZ challenge and the relative increase (CVR), were examined in the anterior (ACA), middle (MCA), and posterior (PCA) cerebral artery territories of the affected hemisphere, and the most recent MRI scans were scored for infarcts and white matter lesions. RESULTS: Receiver operating characteristic (ROC) curve analysis showed higher prognostic accuracy for rCBFacz(AUC:0.82) compared to CVR (AUC:0.72) and rCBFbase (AUC:0.77). ROC AUC, optimal thresholds (and corresponding sensitivity/specificity/accuracy) for rCBFacz after ACZ in individual territories were 0.79 and 37.8 mL 100g-1 min-1 (0.81/0.63/0.72) for the ACA, 0.84 and 32 mL 100g-1 min-1 (0.81/0.75/0.78) for the MCA, and 0.70 and 43.9 ml/(mL 100g-1 min-1 (0.81/0.43/0,62) for the PCA. Kaplan Meier survival curve showed longer event-free survival in patients with rCBFacz below cut-off (p=0.007). In multivariate analysis rCBFacz remained a significant predictor when correcting for age. CONCLUSION: Quantitative rCBF measurements after ACZ challenge with [15O]H2O PET provided high prognostic value for future cerebrovascular events.

Estimation of brain amyloid accumulation using deep learning in clinical [11C]PiB PET imaging.

INTRODUCTION: Estimation of brain amyloid accumulation is valuable for evaluation of patients with cognitive impairment in both research and clinical routine. The development of high throughput and accurate strategies for the determination of amyloid status could be an important tool in patient selection for clinical trials and amyloid directed treatment. Here, we propose the use of deep learning to quantify amyloid accumulation using standardized uptake value ratio (SUVR) and classify amyloid status based on their PET images. METHODS: A total of 1309 patients with cognitive impairment scanned with [11C]PIB PET/CT or PET/MRI were included. Two convolutional neural networks (CNNs) for reading-based amyloid status and SUVR prediction were trained using 75% of the PET/CT data. The remaining PET/CT (n = 300) and all PET/MRI (n = 100) data was used for evaluation. RESULTS: The prevalence of amyloid positive patients was 61%. The amyloid status classification model reproduced the expert reader's classification with 99% accuracy. There was a high correlation between reference and predicted SUVR (R2 = 0.96). Both reference and predicted SUVR had an accuracy of 97% compared to expert classification when applying a predetermined SUVR threshold of 1.35 for binary classification of amyloid status. CONCLUSION: The proposed CNN models reproduced both the expert classification and quantitative measure of amyloid accumulation in a large local dataset. This method has the potential to replace or simplify existing clinical routines and can facilitate fast and accurate classification well-suited for a high throughput pipeline.

Clinical validation of the cingulate island sign visual rating scale in dementia with Lewy bodies.

INTRODUCTION: The cingulate island sign (CIS) is a metabolic pattern on [18F]fluorodeoxyglucose ([18F]FDG) positron emission tomography (PET) associated with dementia with Lewy bodies (DLB). The aim of this study was to validate the visual CIS rating scale (CISRs) for the diagnosis of DLB and to explore the clinical correlates. METHODS: This single-center study included 166 DLB patients and 161 patients with Alzheimer's disease (AD). The CIS on [18F]FDG-PET scans was rated using the CISRs independently by three blinded raters. RESULTS: The optimal cut-off to differentiate DLB from AD was a CISRs score ≥ 1 (sensitivity = 66%, specificity = 84%) whereas a CISRs score ≥ 2 (sensitivity = 58%, specificity = 92%) was optimal to differentiate amyloid positive DLB (n = 43 (82.7%)) and AD. To identify DLB with abnormal (n = 53 (72.6%)) versus normal (n = 20 (27.4%)) dopamine transporter imaging, a CISRs cut-off of 4 had a specificity of 95%. DLB with a CISRs score of 4 performed significantly better in tests on free verbal recall and picture based cued recall, but worse on processing speed compared to DLB with a CISRs score of 0. CONCLUSION: This study confirms the CISRs as a valid marker for the diagnosis of DLB with a high specificity and a lower, but acceptable, sensitivity. Concomitant AD pathology does not influence diagnostic accuracy of the CISRs. In DLB patients, presence of CIS is associated with relative preserved memory function and impaired processing speed.

DeepDixon synthetic CT for [18F]FET PET/MRI attenuation correction of post-surgery glioma patients with metal implants.

Purpose: Conventional magnetic resonance imaging (MRI) can for glioma assessment be supplemented by positron emission tomography (PET) imaging with radiolabeled amino acids such as O-(2-[18F]fluoroethyl)-L-tyrosine ([18F]FET), which provides additional information on metabolic properties. In neuro-oncology, patients often undergo brain and skull altering treatment, which is known to challenge MRI-based attenuation correction (MR-AC) methods and thereby impact the simplified semi-quantitative measures such as tumor-to-brain ratio (TBR) used in clinical routine. The aim of the present study was to examine the applicability of our deep learning method, DeepDixon, for MR-AC in [18F]FET PET/MRI scans of a post-surgery glioma cohort with metal implants. Methods: The MR-AC maps were assessed for all 194 included post-surgery glioma patients (318 studies). The subgroup of 147 patients (222 studies, 200 MBq [18F]FET PET/MRI) with tracer uptake above 1 ml were subsequently reconstructed with DeepDixon, vendor-default atlas-based method, and a low-dose computed tomography (CT) used as reference. The biological tumor volume (BTV) was delineated on each patient by isocontouring tracer uptake above a TBR threshold of 1.6. We evaluated the MR-AC methods using the recommended clinical metrics BTV and mean and maximum TBR on a patient-by-patient basis against the reference with CT-AC. Results: Ninety-seven percent of the studies (310/318) did not have any major artifacts using DeepDixon, which resulted in a Dice coefficient of 0.89/0.83 for tissue/bone, respectively, compared to 0.84/0.57 when using atlas. The average difference between DeepDixon and CT-AC was within 0.2% across all clinical metrics, and no statistically significant difference was found. When using DeepDixon, only 3 out of 222 studies (1%) exceeded our acceptance criteria compared to 72 of the 222 studies (32%) with the atlas method. Conclusion: We evaluated the performance of a state-of-the-art MR-AC method on the largest post-surgical glioma patient cohort to date. We found that DeepDixon could overcome most of the issues arising from irregular anatomy and metal artifacts present in the cohort resulting in clinical metrics within acceptable limits of the reference CT-AC in almost all cases. This is a significant improvement over the vendor-provided atlas method and of particular importance in response assessment.

A zero-dose synthetic baseline for the personalized analysis of [18F]FDG-PET: Application in Alzheimer's disease.

Purpose: Brain 2-Deoxy-2-[18F]fluoroglucose ([18F]FDG-PET) is widely used in the diagnostic workup of Alzheimer's disease (AD). Current tools for uptake analysis rely on non-personalized templates, which poses a challenge as decreased glucose uptake could reflect neuronal dysfunction, or heterogeneous brain morphology associated with normal aging. Overcoming this, we propose a deep learning method for synthesizing a personalized [18F]FDG-PET baseline from the patient's own MRI, and showcase its applicability in detecting AD pathology. Methods: We included [18F]FDG-PET/MRI data from 123 patients of a local cohort and 600 patients from ADNI. A supervised, adversarial model with two connected Generative Adversarial Networks (GANs) was trained on cognitive normal (CN) patients with transfer-learning to generate full synthetic baseline volumes (sbPET) (192 × 192 × 192) which reflect healthy uptake conditioned on brain anatomy. Synthetic accuracy was measured by absolute relative %-difference (Abs%), relative %-difference (RD%), and peak signal-to-noise ratio (PSNR). Lastly, we deployed the sbPET images in a fully personalized method for localizing metabolic abnormalities. Results: The model achieved a spatially uniform Abs% of 9.4%, RD% of 0.5%, and a PSNR of 26.3 for CN subjects. The sbPET images conformed to the anatomical information dictated by the MRI and proved robust in presence of atrophy. The personalized abnormality method correctly mapped the pathology of AD subjects while showing little to no anomalies for CN subjects. Conclusion: This work demonstrated the feasibility of synthesizing fully personalized, healthy-appearing [18F]FDG-PET images. Using these, we showcased a promising application in diagnosing AD, and theorized the potential value of sbPET images in other neuroimaging routines.

Diagnostic yield of simultaneous dynamic contrast-enhanced magnetic resonance perfusion measurements and [18F]FET PET in patients with suspected recurrent anaplastic astrocytoma and glioblastoma.

PURPOSE: Both amino acid positron emission tomography (PET) and magnetic resonance imaging (MRI) blood volume (BV) measurements are used in suspected recurrent high-grade gliomas. We compared the separate and combined diagnostic yield of simultaneously acquired dynamic contrast-enhanced (DCE) perfusion MRI and O-(2-[18F]-fluoroethyl)-L-tyrosine ([18F]FET) PET in patients with anaplastic astrocytoma and glioblastoma following standard therapy. METHODS: A total of 76 lesions in 60 hybrid [18F]FET PET/MRI scans with DCE MRI from patients with suspected recurrence of anaplastic astrocytoma and glioblastoma were included retrospectively. BV was measured from DCE MRI employing a 2-compartment exchange model (2CXM). Diagnostic performances of maximal tumour-to-background [18F]FET uptake (TBRmax), maximal BV (BVmax) and normalised BVmax (nBVmax) were determined by ROC analysis using 6-month histopathological (n = 28) or clinical/radiographical follow-up (n = 48) as reference. Sensitivity and specificity at optimal cut-offs were determined separately for enhancing and non-enhancing lesions. RESULTS: In progressive lesions, all BV and [18F]FET metrics were higher than in non-progressive lesions. ROC analyses showed higher overall ROC AUCs for TBRmax than both BVmax and nBVmax in both lesion-wise (all lesions, p = 0.04) and in patient-wise analysis (p < 0.01). Combining TBRmax with BV metrics did not increase ROC AUC. Lesion-wise positive fraction/sensitivity/specificity at optimal cut-offs were 55%/91%/84% for TBRmax, 45%/77%/84% for BVmax and 59%/84%/72% for nBVmax. Combining TBRmax and best-performing BV cut-offs yielded lesion-wise sensitivity/specificity of 75/97%. The fraction of progressive lesions was 11% in concordant negative lesions, 33% in lesions only BV positive, 64% in lesions only [18F]FET positive and 97% in concordant positive lesions. CONCLUSION: The overall diagnostic accuracy of DCE BV imaging is good, but lower than that of [18F]FET PET. Adding DCE BV imaging did not improve the overall diagnostic accuracy of [18F]FET PET, but may improve specificity and allow better lesion-wise risk stratification than [18F]FET PET alone.

Deep learning based low-activity PET reconstruction of [11C]PiB and [18F]FE-PE2I in neurodegenerative disorders.

PURPOSE: Positron Emission Tomography (PET) can support a diagnosis of neurodegenerative disorder by identifying disease-specific pathologies. Our aim was to investigate the feasibility of using activity reduction in clinical [18F]FE-PE2I and [11C]PiB PET/CT scans, simulating low injected activity or scanning time reduction, in combination with AI-assisted denoising. METHODS: A total of 162 patients with clinically uncertain Alzheimer's disease underwent amyloid [11C]PiB PET/CT and 509 patients referred for clinically uncertain Parkinson's disease underwent dopamine transporter (DAT) [18F]FE-PE2I PET/CT. Simulated low-activity data were obtained by random sampling of 5% of the events from the list-mode file and a 5% time window extraction in the middle of the scan. A three-dimensional convolutional neural network (CNN) was trained to denoise the resulting PET images for each disease cohort. RESULTS: Noise reduction of low-activity PET images was successful for both cohorts using 5% of the original activity with improvement in visual quality and all similarity metrics with respect to the ground-truth images. Clinically relevant metrics extracted from the low-activity images deviated < 2% compared to ground-truth values, which were not significantly changed when extracting the metrics from the denoised images. CONCLUSION: The presented models were based on the same network architecture and proved to be a robust tool for denoising brain PET images with two widely different tracer distributions (delocalized, ([11C]PiB, and highly localized, [18F]FE-PE2I). This broad and robust application makes the presented network a good choice for improving the quality of brain images to the level of the standard-activity images without degrading clinical metric extraction. This will allow for reduced dose or scan time in PET/CT to be implemented clinically.

High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 1: Perfusion and Diffusion Techniques.

Objective: Summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and highlight the latest bench-to-bedside developments. Methods: Experts in advanced MRI techniques applied to high-grade glioma treatment response assessment convened through a European framework. Current evidence regarding the potential for monitoring biomarkers in adult high-grade glioma is reviewed, and individual modalities of perfusion, permeability, and microstructure imaging are discussed (in Part 1 of two). In Part 2, we discuss modalities related to metabolism and/or chemical composition, appraise the clinic readiness of the individual modalities, and consider post-processing methodologies involving the combination of MRI approaches (multiparametric imaging) or machine learning (radiomics). Results: High-grade glioma vasculature exhibits increased perfusion, blood volume, and permeability compared with normal brain tissue. Measures of cerebral blood volume derived from dynamic susceptibility contrast-enhanced MRI have consistently provided information about brain tumor growth and response to treatment; it is the most clinically validated advanced technique. Clinical studies have proven the potential of dynamic contrast-enhanced MRI for distinguishing post-treatment related effects from recurrence, but the optimal acquisition protocol, mode of analysis, parameter of highest diagnostic value, and optimal cut-off points remain to be established. Arterial spin labeling techniques do not require the injection of a contrast agent, and repeated measurements of cerebral blood flow can be performed. The absence of potential gadolinium deposition effects allows widespread use in pediatric patients and those with impaired renal function. More data are necessary to establish clinical validity as monitoring biomarkers. Diffusion-weighted imaging, apparent diffusion coefficient analysis, diffusion tensor or kurtosis imaging, intravoxel incoherent motion, and other microstructural modeling approaches also allow treatment response assessment; more robust data are required to validate these alone or when applied to post-processing methodologies. Conclusion: Considerable progress has been made in the development of these monitoring biomarkers. Many techniques are in their infancy, whereas others have generated a larger body of evidence for clinical application.

Widening the spectrum of spinocerebellar ataxia autosomal recessive type 10 (SCAR10).

Biallelic pathogenic variants in the ANO10 gene cause spinocerebellar ataxia recessive type 10. We report two patients, both compound heterozygous for ANO10 variants, including two novel variants. Both patients had onset of cerebellar ataxia in adulthood with slow progression and presented corticospinal tract signs, eye movement abnormalities and cognitive executive impairment. One of them had temporal lobe epilepsy and she also carried a heterozygous variant in CACNB4, a potential risk gene for epilepsy. Both patients had pronounced cerebellar atrophy on cerebral magnetic resonance imaging (MRI) and reduced metabolic activity in cerebellum as well as in the frontal lobes on 2-deoxy-2-(18F)fluoro-D-glucose positron emission tomography ((18F)FDG PET) scans. We provide comprehensive clinical, radiological and genetic data on two patients carrying likely pathogenic ANO10 gene variants. Furthermore, we provide evidence for a cerebellar as well as a frontal involvement on brain (18F)FDG PET scans which has not previously been reported.

Automated ictal EEG source imaging: A retrospective, blinded clinical validation study.

OBJECTIVE: EEG source imaging (ESI) is a validated tool in the multimodal workup of patients with drug resistant focal epilepsy. However, it requires special expertise and it is underutilized. To circumvent this, automated analysis pipelines have been developed and validated for the interictal discharges. In this study, we present the clinical validation of an automated ESI for ictal EEG signals. METHODS: We have developed an automated analysis pipeline of ictal EEG activity, based on spectral analysis in source space, using an individual head model of six tissues. The analysis was done blinded to all other data. As reference standard, we used the concordance with the resected area and one-year postoperative outcome. RESULTS: We analyzed 50 consecutive patients undergoing epilepsy surgery (34 temporal and 16 extra-temporal). Thirty patients (60%) became seizure-free. The accuracy of the automated ESI was 74% (95% confidence interval: 59.66-85.37%). CONCLUSIONS: Automated ictal ESI has a high accuracy for localizing the seizure onset zone. SIGNIFICANCE: Automating the ESI of the ictal EEG signals will facilitate implementation of this tool in the presurgical evaluation.

Deep-learning-based attenuation correction in dynamic [15O]H2O studies using PET/MRI in healthy volunteers.

Quantitative [15O]H2O positron emission tomography (PET) is the accepted reference method for regional cerebral blood flow (rCBF) quantification. To perform reliable quantitative [15O]H2O-PET studies in PET/MRI scanners, MRI-based attenuation-correction (MRAC) is required. Our aim was to compare two MRAC methods (RESOLUTE and DeepUTE) based on ultrashort echo-time with computed tomography-based reference standard AC (CTAC) in dynamic and static [15O]H2O-PET. We compared rCBF from quantitative perfusion maps and activity concentration distribution from static images between AC methods in 25 resting [15O]H2O-PET scans from 14 healthy men at whole-brain, regions of interest and voxel-wise levels. Average whole-brain CBF was 39.9 ± 6.0, 39.0 ± 5.8 and 40.0 ± 5.6 ml/100 g/min for CTAC, RESOLUTE and DeepUTE corrected studies respectively. RESOLUTE underestimated whole-brain CBF by 2.1 ± 1.50% and rCBF in all regions of interest (range -2.4%- -1%) compared to CTAC. DeepUTE showed significant rCBF overestimation only in the occipital lobe (0.6 ± 1.1%). Both MRAC methods showed excellent correlation on rCBF and activity concentration with CTAC, with slopes of linear regression lines between 0.97 and 1.01 and R2 over 0.99. In conclusion, RESOLUTE and DeepUTE provide AC information comparable to CTAC in dynamic [15O]H2O-PET but RESOLUTE is associated with a small but systematic underestimation.

Diagnostic accuracy and clinical impact of [18F]FET PET in childhood CNS tumors.

BACKGROUND: Central nervous system (CNS) tumors cause the highest death rates among childhood cancers, and survivors frequently have severe late effects. Magnetic resonance imaging (MRI) is the imaging modality of choice, but its specificity can be challenged by treatment-induced signal changes. In adults, O-(2-[18F]fluoroethyl)-l-tyrosine ([18F]FET) PET can assist in interpreting MRI findings. We assessed the clinical impact and diagnostic accuracy of adding [18F]FET PET to MRI in children with CNS tumors. METHODS: A total of 169 [18F]FET PET scans were performed in 97 prospectively and consecutively included patients with known or suspected childhood CNS tumors. Scans were performed at primary diagnosis, before or after treatment, or at relapse. RESULTS: Adding [18F]FET PET to MRI impacted clinical management in 8% [95% confidence interval (CI): 4%-13%] of all scans (n = 151) and in 33% [CI: 17%-53%] of scans deemed clinically indicated due to difficult decision making on MRI alone (n = 30). Using pathology or follow-up as reference standard, the addition of [18F]FET PET increased specificity (1.00 [0.82-1.00] vs 0.48 [0.30-0.70], P = .0001) and accuracy (0.91 [CI: 0.87-0.96] vs 0.81 [CI: 0.75-0.89], P = .04) in 83 treated lesions and accuracy in 58 untreated lesions (0.96 [CI: 0.91-1.00] vs 0.90 [CI: 0.82-0.92], P < .001). Further, in a subset of patients (n = 15) [18F]FET uptake correlated positively with genomic proliferation index. CONCLUSIONS: The addition of [18F]FET PET to MRI helped discriminate tumor from non-tumor lesions in the largest consecutive cohort of pediatric CNS tumor patients presented to date.

Regional and interindividual relationships between cerebral perfusion and oxygen metabolism.

Quantitative measurements of resting cerebral blood flow (CBF) and metabolic rate of oxygen (CMRO2) show large between-subject and regional variability, but the relationships between CBF and CMRO2 measurements regionally and globally are not fully established. Here, we investigated the between-subject and regional associations between CBF and CMRO2 measures with independent and quantitative PET techniques. We included resting CBF and CMRO2 measurements from 50 healthy volunteers (aged 22-81 yr), and calculated the regional and global values of oxygen delivery (Do2) and oxygen extraction fraction (OEF). Linear mixed-model analysis showed that CBF and CMRO2 measurements were closely associated regionally, but no significant between-subject association could be demonstrated, even when adjusting for arterial Pco2 and hemoglobin concentration. The analysis also showed regional differences of OEF, reflecting variable relationship between Do2 and CMRO2, resulting in lower estimates of OEF in thalami, brainstem, and mesial temporal cortices and higher estimates of OEF in occipital cortex. In the present study, we demonstrated no between-subject association of quantitative measurements of CBF and CMRO2 in healthy subjects. Thus, quantitative measurements of CBF did not reflect the underlying between-subject variability of oxygen metabolism measures, mainly because of large interindividual OEF variability not accounted for by Pco2 and hemoglobin concentration.NEW & NOTEWORTHY Using quantitative PET-measurements in healthy human subjects, we confirmed a regional association of CBF and CMRO2, but did not find an association of these values across subjects. This suggests that subjects have an individual coupling between perfusion and metabolism and shows that absolute perfusion measurements does not serve as a surrogate measure of individual measures of oxygen metabolism. The analysis further showed smaller, but significant regional differences of oxygen extraction fraction at rest.

Validation of kinetic modeling of [15O]H2O PET using an image derived input function on hybrid PET/MRI.

In present study we aimed to validate the use of image-derived input functions (IDIF) in the kinetic modeling of cerebral blood flow (CBF) measured by [15O]H2O PET by comparing with the accepted reference standard arterial input function (AIF). Additional comparisons were made to mean cohort AIF and CBF values acquired by methodologically independent phase-contrast mapping (PCM) MRI. Using hybrid PET/MRI an IDIF was generated by measuring the radiotracer concentration in the internal carotid arteries and correcting for partial volume effects using the intravascular volume measured from MRI-angiograms. Seven patients with carotid steno-occlusive disease and twelve healthy controls were examined at rest, after administration of acetazolamide, and, in the control group, during hyperventilation. Agreement between the techniques was examined by linear regression and Bland-Altman analysis. Global CBF values modeled using IDIF correlated with values from AIF across perfusion states in both patients (p<10-6, R2=0.82, 95% limits of agreement (LoA)=[-11.3-9.9] ml/100 g/min) and controls (p<10-6, R2=0.87, 95% LoA=[-17.1-13.7] ml/100 g/min). The reproducibility of gCBF using IDIF was identical to AIF (15.8%). Values from IDIF and AIF had equally good correlation to measurements by PCM MRI, R2=0.86 and R2=0.84, (p<10-6), respectively. Mean cohort AIF performed substantially worse than individual IDIFs (p<10-6, R2=0.63, LoA=[-12.8-25.3] ml/100 g/min). In the patient group, use of IDIF provided similar reactivity maps compared to AIF. In conclusion, global CBF values modeled using IDIF correlated with values modeled by AIF and similar perfusion deficits could be established in a patient group.

Comparison of the clinical impact of 2-[18F]FDG-PET and cerebrospinal fluid biomarkers in patients suspected of Alzheimer's disease.

BACKGROUND: The two biomarkers 2-[18F]FDG-PET and cerebrospinal fluid biomarkers are both recommended to support the diagnosis of Alzheimer's disease. However, there is a lack of knowledge for the comparison of the two biomarkers in a routine clinical setting. OBJECTIVE: The aim was to compare the clinical impact of 2-[18F]FDG-PET and cerebrospinal fluid biomarkers on diagnosis, prognosis, and patient management in patients suspected of Alzheimer's disease. METHODS: Eighty-one patients clinically suspected of Alzheimer's disease were retrospectively included from the Copenhagen Memory Clinic. As part of the clinical work-up all patients had a standard diagnostic program examination including MRI and ancillary investigations with 2-[18F]FDG-PET and cerebrospinal fluid biomarkers. An incremental study design was used to evaluate the clinical impact of the biomarkers. First, the diagnostic evaluation was based on the standard diagnostic program, then the diagnostic evaluation was revised after addition of either cerebrospinal fluid biomarkers or 2-[18F]FDG-PET. At each diagnostic evaluation, two blinded dementia specialists made a consensus decision on diagnosis, prediction of disease course, and change in patient management. Confidence in the decision was measured on a visual analogue scale (0-100). After 6 months, the diagnostic evaluation was performed with addition of the other biomarker. A clinical follow-up after 12 months was used as reference for diagnosis and disease course. RESULTS: The two biomarkers had a similar clinical value across all diagnosis when added individually to the standard diagnostic program. However, for the correctly diagnosed patient with Alzheimer's disease cerebrospinal fluid biomarkers had a significantly higher impact on diagnostic confidence (mean scores±SD: 88±11 vs. 82±11, p = 0.046) and a significant reduction in the need for ancillary investigations (23 vs. 18 patients, p = 0.049) compared to 2-[18F]FDG-PET. CONCLUSION: The two biomarkers had similar clinical impact on diagnosis, but cerebrospinal fluid biomarkers had a more significant value in corroborating the diagnosis of Alzheimer's disease compared to 2-[18F]FDG-PET.

High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 2: Spectroscopy, Chemical Exchange Saturation, Multiparametric Imaging, and Radiomics.

Objective: To summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and to highlight the latest bench-to-bedside developments. Methods: The current evidence regarding the potential for monitoring biomarkers was reviewed and individual modalities of metabolism and/or chemical composition imaging discussed. Perfusion, permeability, and microstructure imaging were similarly analyzed in Part 1 of this two-part review article and are valuable reading as background to this article. We appraise the clinic readiness of all the individual modalities and consider methodologies involving machine learning (radiomics) and the combination of MRI approaches (multiparametric imaging). Results: The biochemical composition of high-grade gliomas is markedly different from healthy brain tissue. Magnetic resonance spectroscopy allows the simultaneous acquisition of an array of metabolic alterations, with choline-based ratios appearing to be consistently discriminatory in treatment response assessment, although challenges remain despite this being a mature technique. Promising directions relate to ultra-high field strengths, 2-hydroxyglutarate analysis, and the use of non-proton nuclei. Labile protons on endogenous proteins can be selectively targeted with chemical exchange saturation transfer to give high resolution images. The body of evidence for clinical application of amide proton transfer imaging has been building for a decade, but more evidence is required to confirm chemical exchange saturation transfer use as a monitoring biomarker. Multiparametric methodologies, including the incorporation of nuclear medicine techniques, combine probes measuring different tumor properties. Although potentially synergistic, the limitations of each individual modality also can be compounded, particularly in the absence of standardization. Machine learning requires large datasets with high-quality annotation; there is currently low-level evidence for monitoring biomarker clinical application. Conclusion: Advanced MRI techniques show huge promise in treatment response assessment. The clinical readiness analysis highlights that most monitoring biomarkers require standardized international consensus guidelines, with more facilitation regarding technique implementation and reporting in the clinic.

C9ORF72 hexanucleotide repeat expansion with Alzheimer's disease-like clinical phenotype: A case report with results from neuropsychology, CSF, FDG-PET, and PiB-PET.

A thorough family history and relevant investigation program are essential to settle accurate diagnosis when clinical presentation is atypical or with a mixed picture.