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Purpose No consensus exists regarding follow-up recommendations for suspected pituitary microadenoma in children. To address this knowledge gap, we investigated the growth potential of pituitary solid and cystic lesions Methods The children included were Results In total, 74 children, median age 12 years (range 3–17), had a non-functioning microadenoma, probable microadenoma, or cyst. Of these, 55 underwent repeated MRI (median 3, range 2–7) with a median follow-up of 37 months (range 4–189). None of the pituitary lesions without hormonal disturbances increased significantly during follow-up. Two radiologists agreed that no lesion could be identified in 38/269 (14%) MRI examinations, and in 51/231 (22%) they disagreed about lesion location. In 34/460 (7%) MRI measurements size differed >2 mm, which had been considered significant progression. Conclusion Non-functioning pituitary microadenoma in children has small size variations, often below the spatial resolution of the scanners. We suggest lesions

Diagnostic information about cell density variations and microscopic tissue anisotropy can be gained from tensor-valued diffusion magnetic resonance imaging (MRI). These properties of tissue microstructure have the potential to become novel imaging biomarkers for radiotherapy response. However, tensor-valued diffusion encoding is more demanding than conventional encoding, and its compatibility with MR scanners that are dedicated to radiotherapy has not been established. Thus, our aim was to investigate the feasibility of tensor-valued diffusion MRI with radiotherapy dedicated MR equipment.A tensor-valued diffusion protocol was implemented, and five healthy volunteers were scanned with different resolutions using conventional head coil and radiotherapy coil setup with fixation masks. Signal-to-noise-ratio (SNR) was evaluated to assess the risk of signal bias due to rectified noise floor. We also evaluated the repeatability and reproducibility of the microstructure parameters. One patient with brain metastasis was scanned to investigate the image quality and the transferability of the setup to diseased tissue.A resolution of 3 × 3 × 3 mmWe demonstrate that tensor-valued diffusion MRI is compatible with radiotherapy fixation masks and coil setup for investigations of microstructure parameters. The reported reproducibility may be used to plan future investigations of imaging biomarkers in brain cancer radiotherapy.

Background Magnetic resonance (MR) safety procedures are designed to allow patients, research subjects and personnel to enter the MR-scanner room under controlled conditions and without the risk to be harmed during the examination. Ferromagnetic objects in the MR-environment or inside the human body represent the main safety risks potentially leading to human injuries. Screening for MR-safety risks with dedicated procedures is therefore mandatory. As human errors during the screening procedure might align and lead to an incident compliance is essential. Purpose To evaluate compliance with a documented structured MR-safety screening process. Method Written and signed MR-safety screening documentation collected at a national 7T MR facility during a four-year period was evaluated for compliance of trained personnel with multi-step MR-safety routines. We analysed whether examinations were performed or why they were not performed. Data analysis further included descriptive statistics of the study population (age, gender and patient or healthy volunteer status), identification of missing documents and omitted or incorrect answers, and whether these compliance shortcomings concerned predominantly administrative or MR-safety related issues. Results Documentation of the screening process in 1819 subjects was incomplete in 19% of subjects. The most common documentation shortcoming was omitted fields. Out of 478 omitted answer-fields in 307 subjects, 36% were of administrative nature and 64% related directly to MR-safety issues. Conclusion Compliance with MR-safety screening procedures cannot be taken for granted and deficiencies to comply with screening routines were revealed. Documentation shortcomings concerned both administrative and MR-safety related issues.

The underlying mechanisms of many pain conditions are not known and many conditions have no effective treatment. Modern dynamic neuroimaging have increased the understanding of altered CNS processing in different pain conditions. This chapter describes the use of advanced MR imaging techniques like fMRI, MR spectroscopy, and diffusion-weighted imaging as well as more established techniques like PET and SPECT in pain conditions in general with more focused attention to fibromyalgia.

BackgroundMean diffusivity (MD) and fractional anisotropy (FA) obtained with diffusion MRI (dMRI) have been associated with cell density and tissue anisotropy across tumors, but it is unknown whether these associations persist at the microscopic level.PurposeTo quantify the degree to which cell density (CD) and structure anisotropy (SA), as determined from histology, account for the intra-tumor variability of MD and FA in meningioma tumors. Furthermore, to clarify whether histological features other than cell density account for additional intra-tumor variability of MD.Materials and MethodsWe performed ex-vivo dMRI at 200 μm isotropic resolution and histological imaging on 16 excised meningioma tumor samples. Diffusion tensor imaging (DTI) was used to map MD and FA, as well as the in-plane FA (FAIP). Histology images were analyzed in terms of cell nuclei density and structure anisotropy (obtained from structure tensor analysis) and were used separately in a regression analysis to predict MD and FAIP, respectively. A convolutional neural network (CNN) was also trained to predict the dMRI maps from histology patches. The association between MRI and histology was analyzed in terms of coefficient of determination (R2). Regions showing unexplained variance (large residuals) were analyzed to identify features apart from cell density and structure anisotropy that could influence MD and FAIP.ResultsCell density assessed by histology poorly explained intra-tumor variability at the mesoscopic level (200 μm) in MD (median R2= 0.06, interquartile range 0.01 - 0.29) or FAIP(median R2= 0.19, 0.09 - 0.29). Samples with low R2for FAIPexhibited low variations throughout the samples and thus low explainable variability, however, this was not the case for MD. Across tumors, cell density and structure anisotropy were associated with MD (R2= 0.58) and FAIP(R2= 0.82), respectively. In 37% of the samples (6 out of 16), cell density did not explain intra-tumor variability of MD when compared to the degree explained by the CNN. Tumor vascularization, psammoma bodies, microcysts, and tissue cohesivity were associated with bias in MD prediction when solely CD was considered. Our results support that FAIPis high in the presence of elongated and aligned cell structures, but low otherwise.ConclusionCell density and structure anisotropy account for variability in MD and FAIPacross tumors but cell density does not explain MD variations within the tumor, which means that low or high values of MD locally may not always reflect high or low tumor cell density. Features beyond cell density need to be considered when interpreting MD.HighlightsCell density accounts for MD variability across but not within meningioma tumors.Structure anisotropy accounts for in-plane FA variability across and within tumorsVascularization, psammoma bodies, and microcysts influence the MD.High and low meningioma tumor cell density can yield similar MD.Features beyond cell density need to be considered when interpreting MD.

Background: Childhood acute lymphoblastic leukemia (ALL) is associated with cognitive impairment in adulthood. Cognitive interference processing and its correlated functional magnetic resonance imaging (fMRI) activity in the brain have not yet been studied in this patient group.Material: Twenty-six adult childhood ALL survivors (median [interquartile range {IQR}] age, 40.0 [37.0-42.3] years) were investigated at median age (IQR), 35.0 (32.0-37.0) years after treatment with intrathecal and intravenous chemotherapy as well as cranial radiotherapy (24 Gy) and compared with 26 matched controls (median [IQR] age, 37.5 [33.0-41.5] years).Methods: Cognitive interference processing was investigated in terms of behavioral performance (response times [ms] and accuracy performance [%]) and fMRI activity in the cingulo-fronto-parietal (CFP) attention network as well as other parts of the brain using the multisource interference task (MSIT).Results: ALL survivors had longer response times and reduced accuracy performance during cognitive interference processing (median [IQR] interference effect, 371.9 [314.7-453.3] ms and 6.7 [4.2-14.7]%, respectively) comparedwith controls (303.7 [275.0-376.7] ms and 2.3 [1.6-4.3]%, respectively), but did not exhibit altered fMRI activity in the CFP attention network or elsewhere in the brain.Conclusion: Adult childhood ALL survivors demonstrated impaired behavioral performance but no altered fMRI activity when performing cognitive interference processing when compared with controls. The results can be used to better characterize this patient group and to optimize follow-up care and support for these individuals. (Less)

Dynamic glucose-enhanced (DGE) MRI is used to study the signal intensity time course (tissue response curve) after D-glucose injection. D-glucose has potential as a biodegradable alternative or complement to gadolinium-based contrast agents, with DGE being comparable with dynamic contrast-enhanced (DCE) MRI. However, the tissue uptake kinetics as well as the detection methods of DGE differ from DCE MRI, and it is relevant to compare these techniques in terms of spatiotemporal enhancement patterns. This study aims to develop a DGE analysis method based on tissue response curve shapes, and to investigate whether DGE MRI provides similar or complementary information to DCE MRI. Eleven patients with suspected gliomas were studied. Tissue response curves were measured for DGE and DCE MRI at 7 T and the area under the curve (AUC) was assessed. Seven types of response curve shapes were postulated and subsequently identified by deep learning to create color-coded "curve maps" showing the spatial distribution of different curve types. DGE AUC values were significantly higher in lesions than in normal tissue (p 0.007). Furthermore, the distribution of curve types differed between lesions and normal tissue for both DGE and DCE. The DGE and DCE response curves in a 6-min postinjection time interval were classified as the same curve type in 20% of the lesion voxels, which increased to 29% when a 12-min DGE time interval was considered. While both DGE and DCE tissue response curve-shape analysis enabled differentiation of lesions from normal brain tissue in humans, their enhancements were neither temporally identical nor confined entirely to the same regions. Curve maps can provide accessible and intuitive information about the shape of DGE response curves, which is expected to be useful in the continued work towards the interpretation of DGE uptake curves in terms of D-glucose delivery, transport, and metabolism.

Purpose To assess cognitive interference processing in adults with childhood craniopharyngioma (CP), with and without hypothalamic injury, respectively, in terms of behavioral performance and functional magnetic resonance imaging (fMRI) activity, using the multi-source interference task (MSIT). Methods Twenty-eight CP patients (median age 34.5 [29.0–39.5] years) were investigated at median 20.5 (16.3–28.8) years after treatment with surgical resection and in some cases additional radiotherapy (n = 10) and compared to 29 matched controls (median age 37.0 [32.5–42.0] years). The subjects performed the MSIT during fMRI acquisition and behavioral performance in terms of response times (ms) and accuracy performance (%) were recorded. Results The MSIT activated the cingulo-fronto-parietal (CFP) attention network in both CP patients and controls. No differences were found in behavioral performance nor fMRI activity between CP patients (interference effect 333.9 [287.3–367.1] ms and 3.1 [1.6–5.6]%, respectively) and controls (309.1 [276.4–361.0] ms and 2.6 [1.6–4.9]%). No differences were found in behavioral performance nor fMRI activity between the two subgroups with (332.0 [283.6–353.4] ms and 4.2 [2.3–5.7]%, respectively) and without hypothalamic injury (355.7 [293.7–388.7] ms and 2.1 [1.0–5.2]%, respectively), respectively, and controls. Conclusion Adults with childhood CP performed cognitive interference processing equally well as controls and demonstrated no compensatory fMRI activity in the CFP attention network compared to controls. This was also true for the two subgroups with and without hypothalamic injury. The results can be useful to better characterize this condition, and to optimize treatment and support for these individuals.

Background Neuropsychiatric (NP) involvement and fatigue are major problems in systemic lupus erythematosus (SLE). S100A8/A9 is a marker of inflammation and responds to therapy in SLE patients. S100A8/A9 has an immunopathogenic role in various neurological diseases. We investigated S100A8/A9 in relation to NP-involvement and fatigue in SLE. Methods 72 consecutive SLE outpatients at a tertiary centre and 26 healthy controls were included in this cross-sectional study. NPSLE was determined by specialists in rheumatology and neurology and defined according to three attribution models: “ACR”, “SLICC A” and “SLICC B”. Cerebral MRI was assessed by a neuroradiologist and neurocognitive testing by a neuropsychologist. The individuals were assessed by scores of pain (VAS), fatigue (VAS and FSS), and depression (MADRS-S). Concentrations of S100A8/A9 in serum and cerebrospinal fluid were measured with ELISA. Statistical calculations were performed using non-parametric methods. Results Serum concentrations of S100A8/A9 were higher in SLE patients compared with controls (medians 1230 ng/ml; 790 ng/ml, p = 0.023). The concentrations were higher in NPSLE patients compared with non-NPSLE patients when applying the SLICC A and ACR models, but not significant when applying the SLICC B model (medians 1400 ng/ml; 920 ng/ml, p = 0.011; 1560 ng/ml; 1090 ng/ml, p = 0.050; 1460 ng/ml; 1090 ng/ml, p = 0.083, respectively). No differences of CSF S100A8/A9 concentrations were observed between NPSLE and non-NPSLE patients. SLE patients with depression or cognitive dysfunction as an ACR NPSLE manifestation had higher serum S100A8/A9 concentrations than non-NPSLE patients (median 1460 ng/ml, p = 0.007 and 1380 ng/ml, p = 0.013, respectively). Higher serum S100A8/A9 correlated with higher VAS fatigue (r = 0.31; p = 0.008) and VAS pain (r = 0.27, p = 0.021) in SLE patients. Serum S100A8/A9 was not independently associated with NPSLE when adjusting for scores of fatigue (FSS) and pain (VAS) (OR 1.86, 95% CI 0.93–3.73, p = 0.08). Conclusions Serum S100A8/A9 concentrations may be associated with NPSLE and fatigue. S100A8/A9 may be of interest in evaluating NPSLE, although further investigations are needed.

Introduction: Cognitive function is an important outcome measure in patients with brain tumor, providing information about the patient’s clinical situation, treatment effects and possible progressi...

Background Neuronal damage in systemic lupus erythematosus (SLE) is common, but the extent and mechanisms are unclear. Neurofilament light (NfL) concentrations rise in plasma and cerebrospinal fluid (CSF) during neuronal damage in various neurological disorders. In this cross-sectional study, plasma and CSF concentrations of NfL were explored as a marker of neuronal damage in SLE. Methods Seventy-two consecutive SLE out-patients and 26 healthy controls, all female, aged Results Plasma and CSF NfL concentrations correlated strongly (r = 0.72, p p = 0.003), non-NPSLE (0.83 (0.18), p = 0.005); SLICC B model: NPSLE (0.87 (0.14), p = 0.001), non-NPSLE (0.83 (0.18), p = 0.008); ACR model: NPSLE (0.86 (0.16), p p = 0.044)). Plasma and CSF NfL concentrations did not differ between NPSLE and non-NPSLE patients. Higher plasma NfL concentrations correlated with larger CSF volumes on MRI (r = 0.34, p = 0.005), and was associated with poorer cognitive performance in the domains of simple attention, psychomotor speed and verbal memory. SLICC/ACR-Damage Index ≥1 was independently associated with higher plasma NfL concentrations (β = 0.074, p = 0.038). Higher plasma creatinine concentrations, anti-dsDNA-positivity, low complement C3 levels, or a history of renal involvement were associated with higher plasma NfL concentrations (β = 0.003, p = 0.009; β = 0.072, p = 0.031; β = 0.077, p = 0.027; β = 0.069, p = 0.047, respectively). Conclusions Higher plasma NfL concentrations in NPSLE and non-NPSLE patients may indicate a higher degree of neuronal damage in SLE in general, corresponding to cognitive impairment and organ damage development. Furthermore, our results may indicate a higher degree of neuronal breakdown in patients with active SLE, also without overt clinical symptoms. NfL may serve as an indicator of neuronal damage in SLE in further studies.

Currently, little is known about the spatial distribution of white matter hyperintensities (WMH) in the brain of patients with Systemic Lupus erythematosus (SLE). Previous lesion markers, such as number and volume, ignore the strategic location of WMH. The goal of this work was to develop a fully-automated method to identify predominant patterns of WMH across WM tracts based on cluster analysis. A total of 221 SLE patients with and without neuropsychiatric symptoms from two different sites were included in this study. WMH segmentations and lesion locations were acquired automatically. Cluster analysis was performed on the WMH distribution in 20 WM tracts. Our pipeline identified five distinct clusters with predominant involvement of the forceps major, forceps minor, as well as right and left anterior thalamic radiations and the right inferior fronto-occipital fasciculus. The patterns of the affected WM tracts were consistent over the SLE subtypes and sites. Our approach revealed distinct and robust tract-based WMH patterns within SLE patients. This method could provide a basis, to link the location of WMH with clinical symptoms. Furthermore, it could be used for other diseases characterized by presence of WMH to investigate both the clinical relevance of WMH and underlying pathomechanism in the brain.

Amide proton transfer-weighted (APTw) MR imaging shows promise as a biomarker of brain tumor status. Currently used APTw MRI pulse sequences and protocols vary substantially among different institutes, and there are no agreed-on standards in the imaging community. Therefore, the results acquired from different research centers are difficult to compare, which hampers uniform clinical application and interpretation. This paper reviews current clinical APTw imaging approaches and provides a rationale for optimized APTw brain tumor imaging at 3 T, including specific recommendations for pulse sequences, acquisition protocols, and data processing methods. We expect that these consensus recommendations will become the first broadly accepted guidelines for APTw imaging of brain tumors on 3 T MRI systems from different vendors. This will allow more medical centers to use the same or comparable APTw MRI techniques for the detection, characterization, and monitoring of brain tumors, enabling multi-center trials in larger patient cohorts and, ultimately, routine clinical use.

Tumor-related hyperintensities in highTo investigate whether DWI with spherical b-tensor encoding (STE) can be used to suppress white matter and enhance the conspicuity of glioma hyperintensities unrelated to white matter.Twenty-five patients with a glioma tumor and at least one pathology-related hyperintensity on DWI underwent conventional MRI at 3 T. The DWI was performed both with linear and spherical tensor encoding (LTE-DWI and STE-DWI). The LTE-DWI here refers to the DWI obtained with conventional diffusion encoding and averaged across diffusion-encoding directions. Retrospectively, the differences in contrast between LTE-DWI and STE-DWI, obtained at aThe spherical tensor encoding DWI was more effective than LTE-DWI at suppressing signals from white matter and improved conspicuity of pathology-related hyperintensities. The median SIR improved in all cases and on average by 28%. The median (interquartile range) SIR was 1.9 (1.6 - 2.1) for STE and 1.4 (1.3 - 1.7) for LTE, with a significant difference of 0.4 (0.3 -0.5) (The contrast mechanism of high

There are many ways to acquire and process diffusion MRI (dMRI) data for group studies, but it is unknown which maximizes the sensitivity to white matter (WM) pathology. Inspired by this question, we analyzed data acquired for diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) at 3T (3T-DTI and 3T-DKI) and DTI at 7T in patients with systemic lupus erythematosus (SLE) and healthy controls (HC). Parameter estimates in 72 WM tracts were obtained using TractSeg. The impact on the sensitivity to WM pathology was evaluated for the diffusion protocol, the magnetic field strength, and the processing pipeline. Sensitivity was quantified in terms of Cohen's

Background Neuropsychiatric (NP) involvement and fatigue are major problems in systemic lupus erythematosus (SLE). S100A8/A9 is a marker of inflammation and responds to therapy in SLE patients. S100A8/A9 has an immunopathogenic role in various neurological diseases. We investigated S100A8/A9 in relation to NP-involvement and fatigue in SLE. Methods 72 consecutive SLE outpatients at a tertiary centre and 26 healthy controls were included in this cross-sectional study. NPSLE was determined by specialists in rheumatology and neurology and defined according to three attribution models: “ACR”, “SLICC A” and “SLICC B”. Cerebral MRI was assessed by a neuroradiologist and neurocognitive testing by a neuropsychologist. The individuals were assessed by scores of pain (VAS), fatigue (VAS and FSS), depression (MADRS-S), and health-related life quality (EQ5D). Concentrations of S100A8/A9 in serum and cerebrospinal fluid were measured with ELISA. Statistical calculations were performed using non-parametric methods. Results Serum concentrations of S100A8/A9 were higher in NPSLE patients compared with non-NPSLE patients when applying the ACR and SLICC A models, but not significant when applying the SLICC B model (medians 1400 ng/ml; 920 ng/ml, p=0.011; 1560 ng/ml; 1090 ng/ml, p=0.050; 1460 ng/ml; 1090 ng/ml, p=0.083, respectively). The concentrations were higher in SLE patients compared with controls (medians 1230 ng/ml; 790 ng/ml, p=0.023). No differences of CSF S100A8/A9 concentrations were observed between NPSLE and non-NPSLE patients. SLE patients with depression or cognitive dysfunction as an ACR NPSLE manifestation had higher serum S100A8/A9 concentrations than non-NPSLE patients (median 1460 ng/ml, p=0.007 and 1380 ng/ml, p=0.013, respectively). Higher serum S100A8/A9 correlated with higher VAS fatigue (r=0.31; p=0.008), VAS pain (r=0.27, p=0.021), and lower EQ5D (r=-0.29, p=0.014) in SLE patients. NPSLE was associated with higher plasma CRP concentrations, higher scores of fatigue and pain, lower EQ5D, and fewer weekly work hours. Serum S100A8/A9 was not independently associated with NPSLE when adjusting for plasma CRP, and scores of fatigue (FSS) and pain (VAS), (OR 1.70, 95% CI 0.82-3.53, p=0.15). Conclusions Serum S100A8/A9 concentrations may be associated with NPSLE and fatigue. S100A8/A9 may be of interest in evaluating NPSLE, although further investigations are needed.

Background: Differentiation between glioblastoma and brain metastasis may be challenging in conventional contrast-enhanced MRI. Purpose: To investigate if perfusion-weighted MRI is able to differentiate glioblastoma from metastasis and, as a second aim was to see if it was possible in the latter group, to predict the primary site of neoplasm. Material and methods: Hundred and fourteen patients with newly discovered tumor lesion (76 metastases and 38 glioblastomas) underwent conventional contrast-enhanced MRI including dynamic susceptibility contrast perfusion sequence. The calculated relative cerebral blood volumes were analyzed in the solid tumor area, peritumoral area, area adjacent to peritumoral area, and normal appearing white matter in contralateral semioval center. The Student t-test was used to detect statistically significant differences in relative cerebral blood volume between glioblastomas and metastases in the aforementioned areas. Furthermore, the metastasis group was divided in four sub groups (lung-, breast-, melanoma-, and gastrointestinal origin) and using one-way ANOVA test. P-values < 0.05 were considered significant. Results: Relative cerebral blood volume (rCBV) in the peritumoral edema was significantly higher in glioblastomas than in metastases (mean 3.2 ± 1.4 and mean 0.9 ± 0.7), respectively, (P < 0.0001). No significant differences in the solid tumor area or the area adjacent to edema were found, (P = 0.28 and 0.21 respectively). There were no significant differences among metastases in the four groups. Conclusion: It is possible to differentiate glioblastomas from metastases by measuring the CBV in the peritumoral edema. It is not possible to differentiate between brain metastases from different primaries (lung-, breast-, melanoma or gastrointestinal) using CBV-measurements in the solid tumor area, peritumoral edema or area adjacent to edema.

Dynamic glucose-enhanced (DGE) magnetic resonance imaging (MRI) has shown potential for tumor imaging using D-glucose as a biodegradable contrast agent. The DGE signal change is small at 3 T (around 1%) and accurate detection is hampered by motion. The intravenous D-glucose injection is associated with transient side effects that can indirectly generate subject movements. In this study, the aim was to study DGE arterial input functions (AIFs) in healthy volunteers at 3 T for different scanning protocols, as a step towards making the D-glucose weighted chemical exchange saturation transfer (glucoCEST) protocol more robust. Two different infusion durations (1.5 and 4.0 minutes) and saturation frequency offsets (1.2 and 2.0 ppm) were used. The effect of subject motion on the DGE signal was studied by using motion estimates retrieved from standard retrospective motion correction to create pseudo-DGE maps, where the apparent DGE signal changes were entirely caused by motion. Furthermore, the DGE AIFs were compared to venous blood glucose levels. A significant difference (p=0.03) between arterial baseline and post-infusion DGE signal was found after D-glucose infusion. The results indicate that the measured DGE AIF signal change depends on both motion and blood glucose concentration change, emphasizing the need for sufficient motion correction in glucoCEST imaging. Finally, we conclude that a longer infusion duration (e.g. 3-4 minutes) should preferably be used in glucoCEST experiments, since it can minimize the glucose infusion side effects without negatively affecting the DGE signal change.

Highlights • Tensor-valued dMRI facilitates prediction of meningioma consistency, grade and type. • Tensor-valued dMRI corroborates findings of diffusion tensor and kurtosis imaging. • MK and MKA is associated with firm and MD with variable meningioma consistency. • Variability of MKI in the vicinity of the tumor is associated with meningioma grade. • MKA 50 and MKI 50 separates psammomatous meningiomas from other meningioma types., Background Preoperative radiological assessment of meningioma characteristics is of value for pre- and post-operative patient management, counselling, and surgical approach. Purpose To investigate whether tensor-valued diffusion MRI can add to the preoperative prediction of meningioma consistency, grade and type. Materials and methods 30 patients with intracranial meningiomas (22 WHO grade I, 8 WHO grade II) underwent MRI prior to surgery. Diffusion MRI was performed with linear and spherical b-tensors with b-values up to 2000 s/mm2. The data were used to estimate mean diffusivity (MD), fractional anisotropy (FA), mean kurtosis (MK) and its components—the anisotropic and isotropic kurtoses (MKA and MKI). Meningioma consistency was estimated for 16 patients during resection based on ultrasonic aspiration intensity, ease of resection with instrumentation or suction. Grade and type were determined by histopathological analysis. The relation between consistency, grade and type and dMRI parameters was analyzed inside the tumor (“whole-tumor”) and within brain tissue in the immediate periphery outside the tumor (“rim”) by histogram analysis. Results Lower 10th percentiles of MK and MKA in the whole-tumor were associated with firm consistency compared with pooled soft and variable consistency (n = 7 vs 9; U test, p = 0.02 for MKA 10 and p = 0.04 for MK10) and lower 10th percentile of MD with variable against soft and firm (n = 5 vs 11; U test, p = 0.02). Higher standard deviation of MKI in the rim was associated with lower grade (n = 22 vs 8; U test, p = 0.04) and in the MKI maps we observed elevated rim-like structure that could be associated with grade. Higher median MKA and lower median MKI distinguished psammomatous type from other pooled meningioma types (n = 5 vs 25; U test; p = 0.03 for MKA 50 and p = 0.03 and p = 0.04 for MKI 50). Conclusion Parameters from tensor-valued dMRI can facilitate prediction of consistency, grade and type.

The purpose of this study is to investigate possible differences in brain structure, as measured by T1-weighted MRI, between patients with systemic lupus erythematosus (SLE) and healthy controls (HC), and whether any observed differences were in turn more severe in SLE patients with neuropsychiatric manifestations (NPSLE) than those without (non-NPSLE). Structural T1-weighted MRI was performed on 69 female SLE patients (mean age = 35.8 years, range = 18–51 years) and 24 age-matched female HC (mean age = 36.8 years, range = 23–52 years) in conjunction with neuropsychological assessment using the CNS Vital Signs test battery. T1-weighted images were preprocessed and analyzed by FSL-VBM. The results show that SLE patients had lower grey matter probability values than the control group in the VIIIa of the cerebellum bilaterally, a region that has previously been implied in sensorimotor processing in human and non-human primates. No structural differences for this region were found between NPSLE and non-NPSLE patients. VBM values from the VIIIa region showed a weak positive correlation with the psychomotor speed domain from CNS Vital Signs (p = 0.05, r = 0.21), which is in line with its presumed role as a sensorimotor processing area.

To investigate core resting state networks in SLE patients with and without neuropsychiatric symptoms by examining functional connectivity changes correlating with results of cognitive testing. Structural MRI and resting state-fMRI (rs-fMRI) were performed in 61 female SLE patients (mean age: 36.8 years, range 18.2-52.0 years) and 20 healthy controls (HC) (mean age 36.2 years, range 23.3-52.2 years) in conjunction with clinical examination and cognitive testing. Alterations in core resting state networks, not found in our healthy controls sample, correlated with cognitive performance gauged by neuropsychological tests in non-neuropsychiatric SLE (nNP) as well as in neuropsychiatric SLE patients (NP). The observed pattern of increased functional connectivity in core resting state networks correlated with reduced cognitive performance on all cognitive domains tested and with a heavy focus on DM, CE, and DM-CE in the NP subgroup. Furthermore, we found that the observed alterations in memory and psychomotor speed correlated with disease duration. In SLE patients both with and without clinically overt neuropsychiatric manifestations, we found changes in the functional connectivity of core resting state networks essential to cognitive functions. These findings may represent a rewiring of functional architecture in response to neuronal damage and could indicate suboptimal compensatory mechanisms at play.

ObjectiveTo investigate the association between longitudinal changes in proton magnetic resonance spectroscopy (MRS) metabolites and amyloid pathology in individuals without dementia, and to explore the relationship between MRS and cognitive decline.MethodsIn this longitudinal multiple time point study (a subset of the Swedish BioFINDER), we included cognitively healthy participants, individuals with subjective cognitive decline, and individuals with mild cognitive impairment. MRS was acquired serially in 294 participants (670 individual spectra) from the posterior cingulate/precuneus. Using mixed-effects models, we assessed the association between MRS and baseline β-amyloid (Aβ), and between MRS and the longitudinal Mini-Mental State Examination, accounting forAPOE, age, and sex.ResultsWhile baseline MRS metabolites were similar in Aβ positive (Aβ+) and negative (Aβ−) individuals, in the Aβ+ group, the estimated rate of change was +1.9%/y for myo-inositol (mI)/creatine (Cr) and −2.0%/y forN-acetylaspartate (NAA)/mI. In the Aβ− group, mI/Cr and NAA/mI yearly change was −0.05% and +1.2%; however, this was not significant across time points. The mild cognitive impairment Aβ+ group showed the steepest MRS changes, with an estimated rate of +2.93%/y (p= 0.07) for mI/Cr and −3.55%/y (p< 0.01) for NAA/mI. Furthermore, in the entire cohort, we found that Aβ+ individuals with low baseline NAA/mI had a significantly higher rate of cognitive decline than Aβ+ individuals with high baseline NAA/mI.ConclusionWe demonstrate that the longitudinal change in mI/Cr and NAA/mI is associated with underlying amyloid pathology. MRS may be a useful noninvasive marker of Aβ-related processes over time. In addition, we show that in Aβ+ individuals, baseline NAA/mI may predict the rate of future cognitive decline.

Background/Purpose Neuropsychiatric (NP) involvement and fatigue are both major problems in SLE. S100A8/A9 is a marker of inflammation, which responds to therapy in SLE patients. S100A8/A9 is expressed in the CNS. We investigated S100A8/A9 in relation to NPSLE and fatigue. Methods In this cross-sectional study we used ELISA (Bhulmann MRP8/14 ELISA kit, Switzerland) to measure the concentration of S100A8/A9 in serum in 72 SLE patients and 26 healthy controls and in cerebrospinal fluid (CSF) in 33 SLE patients. NP involvement was determined according to ACR case definitions for NPSLE. An MRI was performed in SLE patients and controls assessing white matter abnormalities and cerebral atrophy. Measurements of fatigue were performed using the Fatigue Severity Scale (FSS) and the Visual Analogue Scale (100 mm) (VAS). Statistical calculations were performed using non-parametric methods. Results In all, 72 female SLE patients (median age 38, range 18–52) and 26 female healthy controls (median age 40, range 23–52) were included in this study. Forty-four (61%) patients had NP involvement. NPSLE patients had higher serum S100A8/A9 concentrations (median 1.40 µg/ml) than the non-NPSLE patients (median 0.92 µg/ml; p=0.011) and the control group (median 0.79 µg/ml; p=0.004). Serum S100A8/A9 correlated with increased VAS fatigue in SLE patients (r=0.311; p=0.008), but not with FSS (r=0.184; p=0.124). Serum S100A8/A9 did not correlate with the extent of white matter lesions, atrophy of brain segments, or disease activity (SLEDAI-2K). S100A8/A9 was not detected in the CSF. Conclusions Higher serum S100A8/A9 concentrations in NPSLE patients and patients with fatigue may indicate that S100A8/A9 is involved in the pathogenesis of these manifestations, although further investigation is needed.

Hypothalamic obesity (HO) occurs in 50% of patients with the pituitary tumor craniopharyngioma (CP). Attempts have been made to predict the risk of HO based on hypothalamic (HT) damage on magnetic resonance imaging (MRI), but none have included volumetry. We performed qualitative and quantitative volumetric analyses of HT damage. The results were explored in relation to feeding related peptides and body fat. A cross-sectional study of childhood onset CPs involving 3 Tesla MRI, was performed at median 22 years after first operation; 41 CPs, median age 35 (range: 17–56), of whom 23 had HT damage, were compared to 32 controls. After exclusions, 35 patients and 31 controls remained in the MRI study. Main outcome measures were the relation of metabolic parameters to HT volume and qualitative analyses of HT damage. Metabolic parameters scored persistently very high in vascular risk particularly among HT damaged patients. Patients had smaller HT volumes compared to controls 769 (35–1168) mm3 vs. 879 (775–1086) mm3; P

Background Residual tumor volume (RTV) and extent of resection (EOR) have previously been shown to affect survival in glioblastoma (GB) patients. Quantitative radiological assessment (QRA) of these factors could potentially affect clinical decision-making in the postoperative period. Purpose The first aim was to evaluate the reproducibility of different volume estimation methods of RTV and EOR by comparing QRA with subjective visual estimation and with objective volume estimations. The second aim was to clarify whether QRA of RTV and EOR would provide accuracy in predicting progression-free survival (PFS) and overall survival (OS) in GB patients. Material and Methods Seventy GB patients were studied retrospectively. Reproducibility of QRA was compared to conventional visual analysis. Intra-rater agreement between two repeated measurements of 25 patients was calculated. QRA for RTV and EOR was made for the entire study population. Survival analysis was performed by multivariate cox-regression analysis. Results QRA of RTV and EOR gave superior intra-rater agreement compared to subjective evaluation. Multivariate survival analysis showed prognostic significance on 18 months PFS (hazard ratio [HR] = 0.44, P = 0.003) and OS (HR = 0.42, P = 0.012) at RTV 96% on PFS (HR = 2.152, P = 0.005) but not on OS (HR = 1.92, P = 0.053). Conclusion QRA of tumor volumes is more robust compared to standard evaluation methods. Since EOR and RTV are correlated to the prognosis in GB, quantitative analysis of tumor volumes could aid decision-making and patient management postoperatively.

Background and aims Chronic pain including temporomandibular disorder (TMD) pain involves a complex interplay between peripheral and central sensitization, endogenous modulatory pathways, cortical processing and integration and numerous psychological, behavioral and social factors. The aim of this study was to compare spectroscopic patterns of N-Acetyl-aspartate (NAA), total creatine (tCr), choline (Cho), myo-inositol (MI), glutamate (Glu), and the combination of Glu and glutamine in the posterior insula in patients with chronic generalized or regional chronic TMD pain (gTMD and rTMD, respectively) compared to healthy individuals (HI) in relation to clinical findings of TMD pain. Methods Thirty-six female patients with chronic rTMD or gTMD with at least 3 months duration were included in the study. Ten healthy women were included as controls. All participants completed a questionnaire that comprised assessment of degrees of depression, anxiety, stress, catastrophizing, pain intensity, disability and locations. A clinical Diagnostic Criteria for Temporomandibular Disorders examination that comprised assessment of pain locations, headache, mouth opening capacity, pain on mandibular movement, pain on palpation and temporomandibular joint noises was performed. Pressure-pain threshold (PPT) over the masseter muscle and temporal summation to pressure stimuli were assessed with an algometer. Within a week all participants underwent non-contrast enhanced MRI on a 3T MR scanner assessing T1-w and T2-w fluid attenuation inversion recovery. A single-voxel 1H-MRS examination using point-resolved spectroscopy was performed. The metabolite concentrations of NAA, tCr, Cho, MI, Glu and Glx were analyzed with the LC model. Metabolite levels were calculated as absolute concentrations, normalized to the water signal. Metabolite concentrations were used for statistical analysis from the LC model if the Cramér–Rao bounds were less than 20%. In addition, the ratios NAA/tCr, Cho/tCr, Glu/tCr and MI/tCr were calculated. Results The results showed significantly higher tCr levels within the posterior insula in patients with rTMD or gTMD pain than in HI (p=0.029). Cho was negatively correlated to maximum mouth opening capacity with or without pain (rs=−0.42, n=28, p=0.031 and rs=−0.48, n=28, p=0.034, respectively) as well as pressure-pain threshold on the hand (rs=−0.41, n=28, p=0.031). Glu was positively correlated to temporal summation to painful mechanical stimuli (rs=0.42, n=26, p=0.034). Conclusions The present study found that increased concentrations of Cho and Glu in the posterior insular cortex is related to clinical characteristics of chronic TMD pain, including generalized pain. These findings provide new evidence about the critical involvement of the posterior insular cortex and the neurobiology underlying TMD pain in both regional and generalized manifestations. Implications The findings in this study have indirect implications for the diagnosis and management of TMD patients. That said, the findings provide new evidence about the critical involvement of the posterior insular cortex and the neurobiology underlying TMD pain in both regional and generalized manifestations. It is also a further step towards understanding and accepting chronic pain as a disorder in itself.