Current state and guidance on arterial spin labeling perfusion MRI in clinical neuroimaging.

This article focuses on clinical applications of arterial spin labeling (ASL) and is part of a wider effort from the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group to update and expand on the recommendations provided in the 2015 ASL consensus paper. Although the 2015 consensus paper provided general guidelines for clinical applications of ASL MRI, there was a lack of guidance on disease-specific parameters. Since that time, the clinical availability and clinical demand for ASL MRI has increased. This position paper provides guidance on using ASL in specific clinical scenarios, including acute ischemic stroke and steno-occlusive disease, arteriovenous malformations and fistulas, brain tumors, neurodegenerative disease, seizures/epilepsy, and pediatric neuroradiology applications, focusing on disease-specific considerations for sequence optimization and interpretation. We present several neuroradiological applications in which ASL provides unique information essential for making the diagnosis. This guidance is intended for anyone interested in using ASL in a routine clinical setting (i.e., on a single-subject basis rather than in cohort studies) building on the previous ASL consensus review.

Application of frozen Thiel-embalmed specimens for radiotherapy delineation guideline development: a method to create accurate MRI-enhanced CT datasets.

PURPOSE: Thiel embalming followed by freezing in the desired position and acquiring CT + MRI scans is expected to be the ideal approach to obtain accurate, enhanced CT data for delineation guideline development. The effect of Thiel embalming and freezing on MRI image quality is not known. This study evaluates the above-described process to obtain enhanced CT datasets, focusing on the integration of MRI data obtained from frozen, Thiel-embalmed specimens. METHODS: Three Thiel-embalmed specimens were frozen in prone crawl position and MRI scanning protocols were evaluated based on contrast detail and structural conformity between 3D renderings from corresponding structures, segmented on corresponding MRI and CT scans. The measurement error of the dataset registration procedure was also assessed. RESULTS: Scanning protocol T1 VIBE FS enabled swift differentiation of soft tissues based on contrast detail, even allowing a fully detailed segmentation of the brachial plexus. Structural conformity between the reconstructed structures on CT and MRI was excellent, with nerves and blood vessels imported into the CT scan never intersecting with the bones. The mean measurement error for the image registration procedure was consistently in the submillimeter range (range 0.77-0.94 mm). CONCLUSION: Based on the excellent MRI image quality and the submillimeter error margin, the procedure of scanning frozen Thiel-embalmed specimens in the treatment position to obtain enhanced CT scans is recommended. The procedure can be used to support the postulation of delineation guidelines, or for training deep learning algorithms, considering automated segmentations.

Modeling brain dynamics after tumor resection using The Virtual Brain.

Brain tumor patients scheduled for tumor resection often face significant uncertainty, as the outcome of neurosurgery is difficult to predict at the individual patient level. Recently, simulation of the activity of neural populations connected according to the white matter fibers, producing personalized brain network models, has been introduced as a promising tool for this purpose. The Virtual Brain provides a robust open source framework to implement these models. However, brain network models first have to be validated, before they can be used to predict brain dynamics. In prior work, we optimized individual brain network model parameters to maximize the fit with empirical brain activity. In this study, we extend this line of research by examining the stability of fitted parameters before and after tumor resection, and compare it with baseline parameter variability using data from healthy control subjects. Based on these findings, we perform the first "virtual neurosurgery", mimicking patient's actual surgery by removing white matter fibers in the resection mask and simulating again neural activity on this new connectome. We find that brain network model parameters are relatively stable over time in brain tumor patients who underwent tumor resection, compared with baseline variability in healthy control subjects. Concerning the virtual neurosurgery analyses, use of the pre-surgery model implemented on the virtually resected structural connectome resulted in improved similarity with post-surgical empirical functional connectivity in some patients, but negligible improvement in others. These findings reveal interesting avenues for increasing interactions between computational neuroscience and neuro-oncology, as well as important limitations that warrant further investigation.

Optimization of PET protocol and interrater reliability of 18F-PSMA-11 imaging of prostate cancer.

BACKGROUND: Several scan parameters for PET imaging with 18F-PSMA-11 such as dosage, acquisition time and scan duration were evaluated to determine the most appropriate scan protocol, as well as the effect of furosemide administration on lesion visualization. Forty-four patients were randomly assigned to a dosage group (2.0 ± 0.2 or 4.0 ± 0.4 MBq/kg 18F-PSMA-11). All patients received a full-body PET/CT 1 h and 3 h after radiotracer injection with a scan duration of 3 min/bed position. For comparison of the scan duration, images were reconstructed for 1.5 and 3 min/bed position. Patients were intravenously administered 0.5 mg/kg furosemide with a maximum dose of 40 mg. To evaluate the furosemide effect, 22 additional patients were recruited and received one full-body PET/CT 1 h after administration of 2.0 ± 0.2 MBq/kg 18F-PSMA-11 with a scan duration of 3 min/bed position. To this group, no furosemide was administered. Images were scored on image quality using a 7-point scale and each suspicious lesion was described. To assess interrater reliability, two nuclear physicians scored all scans independently and described all observed suspicious lesions. RESULTS: The 4 MBq/kg group received for all reconstructed images (60 min p.i., 1.5 and 3 min/bed position and 180 min p.i., 1.5 and 3 min/bed position) the highest median image quality score compared to the 2 MBq/kg group (p values < 0.01). When comparing all reconstructed images, the highest image quality score was given to images at 60 min p.i., 3 min/bed position for both dosage groups (score 5 and 6 for 2 and 4 MBq/kg, respectively). The addition of furosemide administration decreased the interference score with one point (p = 0.01106) and facilitated the evaluation of lesions in proximity to the ureters. The interrater reliability for the comparison of each lesion separately after more than 40 18F-PSMA-11 scan readings showed an increasing κ value from 0.78 (95% CI, 0.65-0.92) to 0.94 (95% CI, 0.87-1). CONCLUSION: Although the results indicate an administered activity of 4.0 ± 0.4 MBq/kg, preference will be given to 2.0 ± 0.2 MBq/kg due to the small difference in absolute score (max 1 point) and the ALARA principle. For evaluation of lesions in proximity to the ureters, the co-administration of a diuretic can be useful. The increase of the κ value from 0.78 to 0.94 suggests a learning curve in the interpretation of 18F-PSMA-11 images. TRIAL REGISTRATION: Clinicaltrials.gov, NCT03573011. Retrospectively registered 28 June 2018.

Validated imaging biomarkers as decision-making tools in clinical trials and routine practice: current status and recommendations from the EIBALL* subcommittee of the European Society of Radiology (ESR).

Observer-driven pattern recognition is the standard for interpretation of medical images. To achieve global parity in interpretation, semi-quantitative scoring systems have been developed based on observer assessments; these are widely used in scoring coronary artery disease, the arthritides and neurological conditions and for indicating the likelihood of malignancy. However, in an era of machine learning and artificial intelligence, it is increasingly desirable that we extract quantitative biomarkers from medical images that inform on disease detection, characterisation, monitoring and assessment of response to treatment. Quantitation has the potential to provide objective decision-support tools in the management pathway of patients. Despite this, the quantitative potential of imaging remains under-exploited because of variability of the measurement, lack of harmonised systems for data acquisition and analysis, and crucially, a paucity of evidence on how such quantitation potentially affects clinical decision-making and patient outcome. This article reviews the current evidence for the use of semi-quantitative and quantitative biomarkers in clinical settings at various stages of the disease pathway including diagnosis, staging and prognosis, as well as predicting and detecting treatment response. It critically appraises current practice and sets out recommendations for using imaging objectively to drive patient management decisions.

Radiation Dosimetry and Biodistribution of 18F-PSMA-11 for PET Imaging of Prostate Cancer.

Prostate-specific membrane antigen (PSMA) is highly overexpressed in prostate cancer. Many PSMA analog radiotracers for PET/CT prostate cancer staging have been developed, such as 68Ga-PSMA-11. This radiotracer has achieved good results in multiple clinical trials, but because of the superior imaging characteristics of 18F-fluoride, 18F-PSMA-11 was developed. The aim of this study was to evaluate the administration safety and radiation dosimetry of 18F-PSMA-11. Methods: Six patients (aged 62-68 y; mean, 66 ± 2 y) with suspected prostate cancer recurrence after previous treatment were administered 2 MBq of 18F-PSMA-11 per kilogram of body weight and then underwent low-dose PET/CT imaging at 0, 20, 50, 90, and 300 min after injection. To evaluate the safety of administration, vital parameters were monitored. To assess toxicity, full blood count and biochemical parameters were determined. According to the latest International Commission on Radiological Protection recommendations, radiation dosimetry analysis was performed using IDAC-Dose 2.1. For blood activity measurement, small samples of venous blood were collected at various time points after injection. The unbound 18F-fluoride fraction was determined in plasma at 20, 50, and 90 min after administration to evaluate the defluorination rate of 18F-PSMA-11. Results: After injection, 18F-PSMA-11 cleared rapidly from the blood. At 5 h after injection, 29.0% ± 5.9% of the activity was excreted in urine. The free 18F fraction in plasma increased from 9.7% ± 1.0% 20 min after injection to 22.2% ± 1.5% 90 min after injection. The highest tracer uptake was observed in kidneys, bladder, spleen, and liver. No study drug-related adverse events were observed. The calculated mean effective dose was 12.8 ± 0.6 µSv/MBq. Conclusion:18F-PSMA-11 can be safely administered and results in a mean effective dose of 12.8 ± 0.6 µSv/MBq. Therefore, the total radiation dose is lower than for other PSMA PET agents and in the same range as 18F-DCFPyL.

Modeling Brain Dynamics in Brain Tumor Patients Using the Virtual Brain.

Presurgical planning for brain tumor resection aims at delineating eloquent tissue in the vicinity of the lesion to spare during surgery. To this end, noninvasive neuroimaging techniques such as functional MRI and diffusion-weighted imaging fiber tracking are currently employed. However, taking into account this information is often still insufficient, as the complex nonlinear dynamics of the brain impede straightforward prediction of functional outcome after surgical intervention. Large-scale brain network modeling carries the potential to bridge this gap by integrating neuroimaging data with biophysically based models to predict collective brain dynamics. As a first step in this direction, an appropriate computational model has to be selected, after which suitable model parameter values have to be determined. To this end, we simulated large-scale brain dynamics in 25 human brain tumor patients and 11 human control participants using The Virtual Brain, an open-source neuroinformatics platform. Local and global model parameters of the Reduced Wong-Wang model were individually optimized and compared between brain tumor patients and control subjects. In addition, the relationship between model parameters and structural network topology and cognitive performance was assessed. Results showed (1) significantly improved prediction accuracy of individual functional connectivity when using individually optimized model parameters; (2) local model parameters that can differentiate between regions directly affected by a tumor, regions distant from a tumor, and regions in a healthy brain; and (3) interesting associations between individually optimized model parameters and structural network topology and cognitive performance.

Estimating the Patient-specific Dose to the Thyroid and Breasts and Overall Risk in Chest CT When Using Organ-based Tube Current Modulation.

Purpose To assess the potential dose reduction to the thyroid and breasts in chest computed tomography (CT) with organ-based tube current modulation (OBTCM). Materials and Methods In this retrospective study (from January 2015 to December 2016), the location of the breasts with respect to the reduced tube current zone was determined. With Monte Carlo simulations, patient-specific dose distributions of chest CT scans were calculated for 50 female patients (mean age, 53.7 years ± 17.5; range, 20-80 years). The potential dose reduction with OBTCM was assessed. In addition, simulations of clinical OBTCM scans were made for 17 of the 50 female patients (mean age, 43.8 years ± 17.1; range, 20-69 years). Posterior organs in the field of view were analyzed and lifetime attributable risk (LAR) of cancer incidence and mortality was estimated. Image quality between standard CT and OBTCM scans was compared. Results No women had all breast tissue within the reduced tube current zone. Dose reductions of 18% in the thyroid and 9% in the breasts were observed, whereas the doses in lung, liver, and kidney were 17%, 11%, and 26% higher. Overall, the LAR for cancer incidence was not significantly different between conventional and OBTCM scanning (P = .06). Image quality improved with OBTCM (P < .002). Conclusion The potential benefit of OBTCM to the female breast in chest CT is overestimated because of a limited reduced tube current zone; despite a 9% dose reduction to the female breast, posterior organs will absorb up to 26% more radiation, resulting in no reduction in radiation-induced malignancies. © RSNA, 2018.

The successive projection algorithm as an initialization method for brain tumor segmentation using non-negative matrix factorization.

Non-negative matrix factorization (NMF) has become a widely used tool for additive parts-based analysis in a wide range of applications. As NMF is a non-convex problem, the quality of the solution will depend on the initialization of the factor matrices. In this study, the successive projection algorithm (SPA) is proposed as an initialization method for NMF. SPA builds on convex geometry and allocates endmembers based on successive orthogonal subspace projections of the input data. SPA is a fast and reproducible method, and it aligns well with the assumptions made in near-separable NMF analyses. SPA was applied to multi-parametric magnetic resonance imaging (MRI) datasets for brain tumor segmentation using different NMF algorithms. Comparison with common initialization methods shows that SPA achieves similar segmentation quality and it is competitive in terms of convergence rate. Whereas SPA was previously applied as a direct endmember extraction tool, we have shown improved segmentation results when using SPA as an initialization method, as it allows further enhancement of the sources during the NMF iterative procedure.

Semi-automated brain tumor segmentation on multi-parametric MRI using regularized non-negative matrix factorization.

BACKGROUND: Segmentation of gliomas in multi-parametric (MP-)MR images is challenging due to their heterogeneous nature in terms of size, appearance and location. Manual tumor segmentation is a time-consuming task and clinical practice would benefit from (semi-) automated segmentation of the different tumor compartments. METHODS: We present a semi-automated framework for brain tumor segmentation based on non-negative matrix factorization (NMF) that does not require prior training of the method. L1-regularization is incorporated into the NMF objective function to promote spatial consistency and sparseness of the tissue abundance maps. The pathological sources are initialized through user-defined voxel selection. Knowledge about the spatial location of the selected voxels is combined with tissue adjacency constraints in a post-processing step to enhance segmentation quality. The method is applied to an MP-MRI dataset of 21 high-grade glioma patients, including conventional, perfusion-weighted and diffusion-weighted MRI. To assess the effect of using MP-MRI data and the L1-regularization term, analyses are also run using only conventional MRI and without L1-regularization. Robustness against user input variability is verified by considering the statistical distribution of the segmentation results when repeatedly analyzing each patient's dataset with a different set of random seeding points. RESULTS: Using L1-regularized semi-automated NMF segmentation, mean Dice-scores of 65%, 74 and 80% are found for active tumor, the tumor core and the whole tumor region. Mean Hausdorff distances of 6.1 mm, 7.4 mm and 8.2 mm are found for active tumor, the tumor core and the whole tumor region. Lower Dice-scores and higher Hausdorff distances are found without L1-regularization and when only considering conventional MRI data. CONCLUSIONS: Based on the mean Dice-scores and Hausdorff distances, segmentation results are competitive with state-of-the-art in literature. Robust results were found for most patients, although careful voxel selection is mandatory to avoid sub-optimal segmentation.

"Unforgettable" - a pictorial essay on anatomy and pathology of the hippocampus.

The hippocampus is a small but complex anatomical structure that plays an important role in spatial and episodic memory. The hippocampus can be affected by a wide range of congenital variants and degenerative, inflammatory, vascular, tumoral and toxic-metabolic pathologies. Magnetic resonance imaging is the preferred imaging technique for evaluating the hippocampus. The main indications requiring tailored imaging sequences of the hippocampus are medically refractory epilepsy and dementia. The purpose of this pictorial review is threefold: (1) to review the normal anatomy of the hippocampus on MRI; (2) to discuss the optimal imaging strategy for the evaluation of the hippocampus; and (3) to present a pictorial overview of the most common anatomic variants and pathologic conditions affecting the hippocampus. TEACHING POINTS: • Knowledge of normal hippocampal anatomy helps recognize anatomic variants and hippocampal pathology. • Refractory epilepsy and dementia are the main indications requiring dedicated hippocampal imaging. • Pathologic conditions centered in and around the hippocampus often have similar imaging features. • Clinical information is often necessary to come to a correct diagnosis or an apt differential.

Optimal number of atlases and label fusion for automatic multi-atlas-based brachial plexus contouring in radiotherapy treatment planning.

BACKGROUND: The present study aimed to define the optimal number of atlases for automatic multi-atlas-based brachial plexus (BP) segmentation and to compare Simultaneous Truth and Performance Level Estimation (STAPLE) label fusion with Patch label fusion using the ADMIRE® software. The accuracy of the autosegmentations was measured by comparing all of the generated autosegmentations with the anatomically validated gold standard segmentations that were developed using cadavers. MATERIALS AND METHODS: Twelve cadaver computed tomography (CT) atlases were used for automatic multi-atlas-based segmentation. To determine the optimal number of atlases, one atlas was selected as a patient and the 11 remaining atlases were registered onto this patient using a deformable image registration algorithm. Next, label fusion was performed by using every possible combination of 2 to 11 atlases, once using STAPLE and once using Patch. This procedure was repeated for every atlas as a patient. The similarity of the generated automatic BP segmentations and the gold standard segmentation was measured by calculating the average Dice similarity (DSC), Jaccard (JI) and True positive rate (TPR) for each number of atlases. These similarity indices were compared for the different number of atlases using an equivalence trial and for the two label fusion groups using an independent sample-t test. RESULTS: DSC's and JI's were highest when using nine atlases with both STAPLE (average DSC = 0,532; JI = 0,369) and Patch (average DSC = 0,530; JI = 0,370). When comparing both label fusion algorithms using 9 atlases for both, DSC and JI values were not significantly different. However, significantly higher TPR values were achieved in favour of STAPLE (p < 0,001). When fewer than four atlases were used, STAPLE produced significantly lower DSC, JI and TPR values than did Patch (p = 0,0048). CONCLUSIONS: Using 9 atlases with STAPLE label fusion resulted in the most accurate BP autosegmentations (average DSC = 0,532; JI = 0,369 and TPR = 0,760). Only when using fewer than four atlases did the Patch label fusion results in a significantly more accurate autosegmentation than STAPLE.

The role of Size-Specific Dose Estimate (SSDE) in patient-specific organ dose and cancer risk estimation in paediatric chest and abdominopelvic CT examinations.

OBJECTIVES: To develop a clinically applicable method to estimate patient-specific organ and blood doses and lifetime attributable risks (LAR) from paediatric torso CT examinations. METHODS: Individualized voxel models were created from full-body CT data of 10 paediatric patients (2-18 years). Patient-specific dose distributions of chest and abdominopelvic CT scans were simulated using Monte Carlo methods. Blood dose was calculated as a weighted sum of simulated organ doses. LAR of cancer incidence and mortality were estimated, according to BEIR-VII. A second simulation and blood dose calculation was performed using only the thoracic and abdominopelvic region of the original voxel models. For each simulation, the size-specific dose estimate (SSDE) was calculated. RESULTS: SSDE showed a significant strong linear correlation with organ dose (r > 0.8) and blood dose (r > 0.9) and LAR (r > 0.9). No significant differences were found between blood dose calculations with the full-body voxel models and the thoracic or abdominopelvic models. CONCLUSION: Even though clinical CT images mostly do not cover the whole body of the patient, they can be used as a voxel model for blood dose calculation. In addition, SSDE can estimate patient-specific organ and blood doses and LAR in paediatric torso CT examinations. KEY POINTS: • Blood dose can be simulated using the patient's clinical CT images. • SSDE estimates patient-specific organ/blood dose and LAR in paediatric CAP CT-examinations. • SSDE makes on-the-spot dose and LAR estimations possible in routine clinical practice.

The effect of morphometric atlas selection on multi-atlas-based automatic brachial plexus segmentation.

PURPOSE: The present study aimed to measure the effect of a morphometric atlas selection strategy on the accuracy of multi-atlas-based BP autosegmentation using the commercially available software package ADMIRE® and to determine the optimal number of selected atlases to use. Autosegmentation accuracy was measured by comparing all generated automatic BP segmentations with anatomically validated gold standard segmentations that were developed using cadavers. MATERIALS AND METHODS: Twelve cadaver computed tomography (CT) atlases were included in the study. One atlas was selected as a patient in ADMIRE®, and multi-atlas-based BP autosegmentation was first performed with a group of morphometrically preselected atlases. In this group, the atlases were selected on the basis of similarity in the shoulder protraction position with the patient. The number of selected atlases used started at two and increased up to eight. Subsequently, a group of randomly chosen, non-selected atlases were taken. In this second group, every possible combination of 2 to 8 random atlases was used for multi-atlas-based BP autosegmentation. For both groups, the average Dice similarity coefficient (DSC), Jaccard index (JI) and Inclusion index (INI) were calculated, measuring the similarity of the generated automatic BP segmentations and the gold standard segmentation. Similarity indices of both groups were compared using an independent sample t-test, and the optimal number of selected atlases was investigated using an equivalence trial. RESULTS: For each number of atlases, average similarity indices of the morphometrically selected atlas group were significantly higher than the random group (p < 0,05). In this study, the highest similarity indices were achieved using multi-atlas autosegmentation with 6 selected atlases (average DSC = 0,598; average JI = 0,434; average INI = 0,733). CONCLUSIONS: Morphometric atlas selection on the basis of the protraction position of the patient significantly improves multi-atlas-based BP autosegmentation accuracy. In this study, the optimal number of selected atlases used was six, but for definitive conclusions about the optimal number of atlases and to improve the autosegmentation accuracy for clinical use, more atlases need to be included.

Organ Doses and Radiation Risk of Computed Tomographic Coronary Angiography in a Clinical Patient Population: How Do Low-Dose Acquisition Modes Compare?

OBJECTIVE: To compare the organ doses and lifetime-attributable risk of cancer for electrocardiogram-triggered sequential and high-pitch helical scanning in a clinical patient population. METHODS: Phantom thermoluminiscence dosimeter measurements were used as a model for the organ dose assessment of 314 individual patients who underwent coronary computed tomographic angiography. Patient-specific lifetime-attributable cancer risks were calculated. RESULTS: Phantom measurements showed that heart rate had a significant influence on the delivered radiation exposure in sequential mode, and calcium scoring and contrast bolus tracking scans make a nonnegligible contribution to patients' dose. Therefore, they should be taken into account for patients' organ dose estimations. Median cancer induction risks are low, with 0.008% (0.0016%) and 0.022% (0.056%) for high-pitch and sequential scanning for men (women), respectively. CONCLUSIONS: The use of high-pitch helical scanning leads to 65% and 72% lower lifetime-attributable risk values for men and women, respectively, compared with sequential scanning.

An anatomically validated brachial plexus contouring method for intensity modulated radiation therapy planning.

PURPOSE: To develop contouring guidelines for the brachial plexus (BP) using anatomically validated cadaver datasets. Magnetic resonance imaging (MRI) and computed tomography (CT) were used to obtain detailed visualizations of the BP region, with the goal of achieving maximal inclusion of the actual BP in a small contoured volume while also accommodating for anatomic variations. METHODS AND MATERIALS: CT and MRI were obtained for 8 cadavers positioned for intensity modulated radiation therapy. 3-dimensional reconstructions of soft tissue (from MRI) and bone (from CT) were combined to create 8 separate enhanced CT project files. Dissection of the corresponding cadavers anatomically validated the reconstructions created. Seven enhanced CT project files were then automatically fitted, separately in different regions, to obtain a single dataset of superimposed BP regions that incorporated anatomic variations. From this dataset, improved BP contouring guidelines were developed. These guidelines were then applied to the 7 original CT project files and also to 1 additional file, left out from the superimposing procedure. The percentage of BP inclusion was compared with the published guidelines. RESULTS: The anatomic validation procedure showed a high level of conformity for the BP regions examined between the 3-dimensional reconstructions generated and the dissected counterparts. Accurate and detailed BP contouring guidelines were developed, which provided corresponding guidance for each level in a clinical dataset. An average margin of 4.7 mm around the anatomically validated BP contour is sufficient to accommodate for anatomic variations. Using the new guidelines, 100% inclusion of the BP was achieved, compared with a mean inclusion of 37.75% when published guidelines were applied. CONCLUSION: Improved guidelines for BP delineation were developed using combined MRI and CT imaging with validation by anatomic dissection.

Structural and metabolic features of two different variants of multiple sclerosis: a PET/MRI study.

BACKGROUND: Multimodality imaging such as proton magnetic resonance spectroscopy (MRS) and positron emission tomography (PET) have provided information specific to the underlying mechanisms of many brain diseases, including multiple sclerosis (MS). PURPOSE: To determine the structural and metabolic characterization of two particular variants of MS, namely tumefactive MS and Balo's concentric sclerosis (BCS). METHODS: Conventional MR imaging, diffusion and perfusion MR, MR spectroscopy and PET imaging with F-18 fluorodeoxyglucose (FDG) and F-18 fluoromethylcholine (FCho) were performed. RESULTS: In a case with pathologically proven tumefactive MS, magnetic resonance imaging (MRI) showed a pseudotumoral lesion with incomplete ring enhancement, peripheral diffusion restriction, and high choline and lactate peaks on MRS. On follow-up, the lesion showed significant growth. In a case of BCS, MRI showed an onion-like lesion without contrast enhancement or diffusion restriction, and only a moderate increase in choline on MRS. The lesion remained stable on follow-up. On PET, there was no uptake of F-18 FDG in either type of MS lesion. Conversely, uptake of F-18 FCho was moderate in tumefactive MS, whereas no F-18 FCho uptake was noted in the lesion with, on MRI, typical features of BCS. CONCLUSIONS: Our findings illustrate that metabolic features may differ between variants of MS possibly signifying different disease activity.

Magnetic resonance spectroscopy in migraine: what have we learned so far?

OBJECTIVE: To summarize and evaluate proton ((1)H) and phosphorus ((31)P) magnetic resonance spectroscopy (MRS) findings in migraine. METHODS: A thorough review of (1)H and/or (31)P-MRS studies in any form of migraine published up to September 2011. RESULTS: Some findings were consistent in all studies, such as a lack of ictal/interictal brain pH change and a disturbed energy metabolism, the latter of which is reflected in a drop in phosphocreatine content, both in the resting brain and in muscle following exercise. In a recent interictal study ATP was found to be significantly decreased in the occipital lobe of migraine with aura patients, reinforcing the concept of a mitochondrial component to the migraine threshold, at least in a subgroup of patients. In several studies a correlation between the extent of the energy disturbance and the clinical phenotype severity was apparent. Less consistent but still congruent with a disturbed energy metabolism is an observed lactate increase in the occipital cortex of several migraine subtypes (MwA, migraine with prolonged aura). No increases in brain glutamate levels were found. CONCLUSION: The combined abnormalities found in MRS studies imply a mitochondrial component in migraine neurobiology. This could be due to a primary mitochondrial dysfunction or be secondary to, for example, alterations in brain excitability. The extent of variation in the data can be attributed to both the variable clinical inclusion criteria used and the variation in applied methodology. Therefore it is necessary to continue to optimize MRS methodology to gain further insights, especially concerning lactate and glutamate.

Progressive multifocal leukoencephalopathy (PML) mimicking high-grade glioma on delayed F-18 FDG PET imaging.

The purpose of our study was to determine the increase in F-18 fluorodeoxyglucose (FDG) uptake in a patient with progressive multifocal leukoencephalopathy (PML) between early and late scan times using positron emission tomography (PET) imaging with F-18 FDG at conventional (60 minutes [min] after injection, PET(60)) and delayed (300 min after injection, PET(300)) intervals. PET(60) and PET(300) imaging was performed on a pathologically proven PML lesion. The PML lesion in the posterior fossa exhibited an increase in F-18 FDG uptake of 52% between early and late times, which was in the range of that in high-grade gliomas. Thus, dual-time-point PET with F-18 FDG may not be able to differentiate between infectious and malignant brain lesions.