Lifespan normative data on rates of brain volume changes.

We provide here normative values of yearly percentage brain volume change (PBVC/y) as obtained with Structural Imaging Evaluation, using Normalization, of Atrophy, a widely used open-source software, developing a PBVC/y calculator for assessing the deviation from the expected PBVC/y in patients with neurological disorders. We assessed multicenter (34 centers, 11 acquisition protocols) magnetic resonance imaging data of 720 healthy participants covering the whole adult lifespan (16-90 years). Data of 421 participants with a follow-up > 6 months were used to obtain the normative values for PBVC/y and data of 392 participants with a follow-up <1 month were selected to assess the intrasubject variability of the brain volume measurement. A mixed model evaluated PBVC/y dependence on age, sex, and magnetic resonance imaging parameters (scan vendor and magnetic field strength). PBVC/y was associated with age (p < 0.001), with 60- to 70-year-old participants showing twice more volume decrease than participants aged 30-40 years. PBVC/y was also associated with magnetic field strength, with higher decreases when measured by 1.5T than 3T scanners (p < 0.001). The variability of PBVC/y normative percentiles was narrower as the interscan interval was longer (e.g., 80th normative percentile was 50% smaller for participants with 2-year than with 1-year follow-up). The use of these normative data, eased by the freely available calculator, might help in better discriminating pathological from physiological conditions in the clinical setting.

Summarizing the 4D image stack of ultrafast dynamic contrast enhancement MRI of breast cancer in 3D using color intensity projections.

BACKGROUND: Each ultrafast dynamic contrast-enhanced (DCE) MRI sequence for breast cancer generates thousands of images in a 4D stack that need to be reviewed by a radiologist. PURPOSE: To assess whether color intensity projections (CIP) effectively summarizes-using only the time of arrival (ToA) and amount of signal enhancement (AoE) of the contrast agent-the thousands of ultrafast images. STUDY TYPE: Retrospective cohort clinical trial. SUBJECTS: The study included 89 patients who had been scanned with an MRI beast protocol, of which 26 had breast cancer and 63 did not. FIELD STRENGTH/SEQUENCE: The 115-second ultrafast DCE sequence at 3T acquired 19 consecutive frames every 4.26 seconds with 152 slices per frame, yielding a 4D stack with 2888 2D images for each of water and fat. ASSESSMENT: For each slice of the water 4D stack a single CIP image was generated that encoded the ToA in the hue (red, orange, yellow, green, cyan, blue) and AoE in the brightness. Each of three experienced radiologists assigned a Breast Imaging and Reporting Data System (BI-RADS) score for each patient, first using only the CIP images, and subsequently using both CIP and the full 4D stack. STATISTICAL TESTS: The one-sided Fisher's exact test was used to determine statistical significance of both the sensitivity and specificity between the CIP alone and the CIP plus 4D stack. RESULTS: All malignancies were detected using only CIP by at least one of the radiologists. The CIP and CIP+4D sensitivities for reader 1 were 96% and 96% (P = 0.57), specificities were 59% and 65% (P = 0.29). For reader 2, the values were 96% and 100% (P = 0.51) with 62% and 71% (P = 0.17). For reader 3 the values were 92% and 96% (P = 0.50) with 51% and 62% (P = 0.07). DATA CONCLUSION: With a 95% sensitivity, CIP provides an effective summary of ultrafast DCE images of breast cancer. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1391-1399.

Can measuring hippocampal atrophy with a fully automatic method be substantially less noisy than manual segmentation over both 1 and 3 years?

To quantify the "segmentation noise" of several widely used fully automatic methods for measuring longitudinal hippocampal atrophy in Alzheimer's disease and compare the results to the segmentation noise of manual segmentation over both 1 and 3 years. The segmentation noise of 5 longitudinal hippocampal atrophy measurement methods was quantified, including checking its Gaussianity, using 264 subjects from the ADNI1 back-to-back (BTB) data set over both 1 year and 3 year intervals. The segmentation methods were FreeSurfer 5.3.0 both cross sectional and longitudinal, FreeSurfer 6.0.0 longitudinal, MAPS-HBSI and FSL/FIRST 5.0.8. The BTB manual segmentation of 75 ADNI subjects from a previous study provided the manual distributions for comparison. All methods, including the manual segmentation, violated the Gaussianity assumption. Two methods, FreeSurfer 6.0.0 and MAPS-HBSI, had a segmentation noise substantially less than a surrogate for manual segmentation. FreeSurfer 5.3.0 longitudinal was confirmed as a surrogate for manual segmentation. The violation of the Gaussian assumption by the segmentation methods assessed, including manual, suggests results of previous studies that assumed Gaussian statistics without confirmation may need review. Fully automatic FreeSurfer 6.0.0 and MAPS-HBSI both have lower segmentation noise than manual requiring less than two thirds of the subjects to detect the same treatment effect.

Performance of five research-domain automated WM lesion segmentation methods in a multi-center MS study.

BACKGROUND AND PURPOSE: In vivoidentification of white matter lesions plays a key-role in evaluation of patients with multiple sclerosis (MS). Automated lesion segmentation methods have been developed to substitute manual outlining, but evidence of their performance in multi-center investigations is lacking. In this work, five research-domain automated segmentation methods were evaluated using a multi-center MS dataset. METHODS: 70 MS patients (median EDSS of 2.0 [range 0.0-6.5]) were included from a six-center dataset of the MAGNIMS Study Group (www.magnims.eu) which included 2D FLAIR and 3D T1 images with manual lesion segmentation as a reference. Automated lesion segmentations were produced using five algorithms: Cascade; Lesion Segmentation Toolbox (LST) with both the Lesion growth algorithm (LGA) and the Lesion prediction algorithm (LPA); Lesion-Topology preserving Anatomical Segmentation (Lesion-TOADS); and k-Nearest Neighbor with Tissue Type Priors (kNN-TTP). Main software parameters were optimized using a training set (N = 18), and formal testing was performed on the remaining patients (N = 52). To evaluate volumetric agreement with the reference segmentations, intraclass correlation coefficient (ICC) as well as mean difference in lesion volumes between the automated and reference segmentations were calculated. The Similarity Index (SI), False Positive (FP) volumes and False Negative (FN) volumes were used to examine spatial agreement. All analyses were repeated using a leave-one-center-out design to exclude the center of interest from the training phase to evaluate the performance of the method on 'unseen' center. RESULTS: Compared to the reference mean lesion volume (4.85 ± 7.29 mL), the methods displayed a mean difference of 1.60 ± 4.83 (Cascade), 2.31 ± 7.66 (LGA), 0.44 ± 4.68 (LPA), 1.76 ± 4.17 (Lesion-TOADS) and -1.39 ± 4.10 mL (kNN-TTP). The ICCs were 0.755, 0.713, 0.851, 0.806 and 0.723, respectively. Spatial agreement with reference segmentations was higher for LPA (SI = 0.37 ± 0.23), Lesion-TOADS (SI = 0.35 ± 0.18) and kNN-TTP (SI = 0.44 ± 0.14) than for Cascade (SI = 0.26 ± 0.17) or LGA (SI = 0.31 ± 0.23). All methods showed highly similar results when used on data from a center not used in software parameter optimization. CONCLUSION: The performance of the methods in this multi-center MS dataset was moderate, but appeared to be robust even with new datasets from centers not included in training the automated methods.

Reproducibility of hippocampal atrophy rates measured with manual, FreeSurfer, AdaBoost, FSL/FIRST and the MAPS-HBSI methods in Alzheimer's disease.

The purpose of this study is to assess the reproducibility of hippocampal atrophy rate measurements of commonly used fully-automated algorithms in Alzheimer disease (AD). The reproducibility of hippocampal atrophy rate for FSL/FIRST, AdaBoost, FreeSurfer, MAPS independently and MAPS combined with the boundary shift integral (MAPS-HBSI) were calculated. Back-to-back (BTB) 3D T1-weighted MPRAGE MRI from the Alzheimer's Disease Neuroimaging Initiative (ADNI1) study at baseline and year one were used. Analysis on 3 groups of subjects was performed - 562 subjects at 1.5T, a 75 subject group that also had manual segmentation and 111 subjects at 3T. A simple and novel statistical test based on the binomial distribution was used that handled outlying data points robustly. Median hippocampal atrophy rates were -1.1%/year for healthy controls, -3.0%/year for mildly cognitively impaired and -5.1%/year for AD subjects. The best reproducibility was observed for MAPS-HBSI (1.3%), while the other methods tested had reproducibilities at least 50% higher at 1.5T and 3T which was statistically significant. For a clinical trial, MAPS-HBSI should require less than half the subjects of the other methods tested. All methods had good accuracy versus manual segmentation. The MAPS-HBSI method has substantially better reproducibility than the other methods considered.

The SIENA/FSL whole brain atrophy algorithm is no more reproducible at 3T than 1.5 T for Alzheimer's disease.

The back-to-back (BTB) acquisition of MP-RAGE MRI scans of the Alzheimer׳s Disease Neuroimaging Initiative (ADNI1) provides an excellent data set with which to check the reproducibility of brain atrophy measures. As part of ADNI1, 131 subjects received BTB MP-RAGEs at multiple time points and two field strengths of 3T and 1.5 T. As a result, high quality data from 200 subject-visit-pairs was available to compare the reproducibility of brain atrophies measured with FSL/SIENA over 12 to 18 month intervals at both 3T and 1.5 T. Although several publications have reported on the differing performance of brain atrophy measures at 3T and 1.5 T, no formal comparison of reproducibility has been published to date. Another goal was to check whether tuning SIENA options, including -B, -S, -R and the fractional intensity threshold (f) had a significant impact on the reproducibility. The BTB reproducibility for SIENA was quantified by the 50th percentile of the absolute value of the difference in the percentage brain volume change (PBVC) for the BTB MP-RAGES. At both 3T and 1.5 T the SIENA option combination of "-B f=0.2", which is different from the default values of f=0.5, yielded the best reproducibility as measured by the 50th percentile yielding 0.28 (0.23-0.39)% and 0.26 (0.20-0.32)%. These results demonstrated that in general 3T had no advantage over 1.5 T for the whole brain atrophy measure - at least for SIENA. While 3T MRI is superior to 1.5 T for many types of measurements, and thus worth the additional cost, brain atrophy measurement does not seem to be one of them.

Hippocampal volume change measurement: quantitative assessment of the reproducibility of expert manual outlining and the automated methods FreeSurfer and FIRST.

BACKGROUND: To measure hippocampal volume change in Alzheimer's disease (AD) or mild cognitive impairment (MCI), expert manual delineation is often used because of its supposed accuracy. It has been suggested that expert outlining yields poorer reproducibility as compared to automated methods, but this has not been investigated. AIM: To determine the reproducibilities of expert manual outlining and two common automated methods for measuring hippocampal atrophy rates in healthy aging, MCI and AD. METHODS: From the Alzheimer's Disease Neuroimaging Initiative (ADNI), 80 subjects were selected: 20 patients with AD, 40 patients with mild cognitive impairment (MCI) and 20 healthy controls (HCs). Left and right hippocampal volume change between baseline and month-12 visit was assessed by using expert manual delineation, and by the automated software packages FreeSurfer (longitudinal processing stream) and FIRST. To assess reproducibility of the measured hippocampal volume change, both back-to-back (BTB) MPRAGE scans available for each visit were analyzed. Hippocampal volume change was expressed in µL, and as a percentage of baseline volume. Reproducibility of the 1-year hippocampal volume change was estimated from the BTB measurements by using linear mixed model to calculate the limits of agreement (LoA) of each method, reflecting its measurement uncertainty. Using the delta method, approximate p-values were calculated for the pairwise comparisons between methods. Statistical analyses were performed both with inclusion and exclusion of visibly incorrect segmentations. RESULTS: Visibly incorrect automated segmentation in either one or both scans of a longitudinal scan pair occurred in 7.5% of the hippocampi for FreeSurfer and in 6.9% of the hippocampi for FIRST. After excluding these failed cases, reproducibility analysis for 1-year percentage volume change yielded LoA of ±7.2% for FreeSurfer, ±9.7% for expert manual delineation, and ±10.0% for FIRST. Methods ranked the same for reproducibility of 1-year µL volume change, with LoA of ±218 µL for FreeSurfer, ±319 µL for expert manual delineation, and ±333 µL for FIRST. Approximate p-values indicated that reproducibility was better for FreeSurfer than for manual or FIRST, and that manual and FIRST did not differ. Inclusion of failed automated segmentations led to worsening of reproducibility of both automated methods for 1-year raw and percentage volume change. CONCLUSION: Quantitative reproducibility values of 1-year microliter and percentage hippocampal volume change were roughly similar between expert manual outlining, FIRST and FreeSurfer, but FreeSurfer reproducibility was statistically significantly superior to both manual outlining and FIRST after exclusion of failed segmentations.

Validation of the automated method VIENA: an accurate, precise, and robust measure of ventricular enlargement.

BACKGROUND: In many retrospective studies and large clinical trials, high-resolution, good-contrast 3DT1 images are unavailable, hampering detailed analysis of brain atrophy. Ventricular enlargement then provides a sensitive indirect measure of ongoing central brain atrophy. Validated automated methods are required that can reliably measure ventricular enlargement and are robust across magnetic resonance (MR) image types. AIM: To validate the automated method VIENA for measuring the percentage ventricular volume change (PVVC) between two scans. MATERIALS AND METHODS: Accuracy was assessed using four image types, acquired in 15 elderly patients (five with Alzheimer's disease, five with mild cognitive impairment, and five cognitively normal elderly) and 58 patients with multiple sclerosis (MS), by comparing PVVC values from VIENA to manual outlining. Precision was assessed from data with three imaging time points per MS patient, by measuring the difference between the direct (one-step) and indirect (two-step) measurement of ventricular volume change between the first and last time points. The stringent concordance correlation coefficient (CCC) was used to quantify absolute agreement. RESULTS: CCC of VIENA with manual measurement was 0.84, indicating good absolute agreement. The median absolute difference between two-step and one-step measurement with VIENA was 1.01%, while CCC was 0.98. Neither initial ventricular volume nor ventricular volume change affected performance of the method. DISCUSSION: VIENA has good accuracy and good precision across four image types. VIENA therefore provides a useful fully automated method for measuring ventricular volume change in large datasets. CONCLUSION: VIENA is a robust, accurate, and precise method for measuring ventricular volume change.

Assessing the reproducibility of the SienaX and Siena brain atrophy measures using the ADNI back-to-back MP-RAGE MRI scans.

SienaX and Siena are widely used and fully automated algorithms for measuring whole brain volume and volume change in cross-sectional and longitudinal MRI studies and are particularly useful in studies of brain atrophy. The reproducibility of the algorithms was assessed using the 3D T1 weighted MP-RAGE scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. The back-to-back (BTB) MP-RAGE scans in the ADNI data set makes it a valuable benchmark against which to assess the performance of algorithms of measuring atrophy in the human brain with MRI scans. A total of 671 subjects were included for SienaX and 385 subjects for Siena. The annual percentage brain volume change (PBVC) rates were -0.65±0.82%/year for the healthy controls, -1.15±1.21%/year for mild cognitively impairment (MCI) and -1.84±1.33%/year for AD, in line with previous findings. The median of the absolute value of the reproducibility of SienaX's normalized brain volume (NBV) was 0.96% while the 90th percentile was 5.11%. The reproducibility of Siena's PBVC had a median of 0.35% and a 90th percentile of 1.37%. While the median reproducibility for SienaX's NBV was in line with the values previously reported in the literature, the median reproducibility of Siena's PBVC was about twice that reported. Also, the 90th percentiles for both SienaX and Siena were about twice the size that would be expected for a Gaussian distribution. Because of the natural variation of the disease among patients over a year, a perfectly reproducible whole brain atrophy algorithm would reduce the estimated group size needed to detect a specified treatment effect by only 30% to 40% as compared to Siena's.

Use of megavoltage cine-images for studying intra-thoracic motion during radiotherapy for locally advanced lung cancer.

BACKGROUND AND PURPOSE: Use of planning 4-dimensional CT (4DCT) scans often permits use of smaller target volumes for thoracic tumors but this assumes a reproducible pattern of motion during radiotherapy. We compared cranio-caudal (CC) motion on MV cine-images acquired during treatment with that seen on planning 4DCT. METHODS AND MATERIALS: A pre-programmable respiratory motion phantom and a software tool for motion assessment were used to validate the use of MV cine-images for motion detection. MV cine-images acquired in 20 patients with node-positive lung cancer were analyzed using the same software. Intra-fraction CC motion on 6 MV cine-images from each patient was compared with CC motion on their planning 4DCT. RESULTS: Software-based motion measurement on MV cine-images from the phantom corresponded to actual motion. Mean CC motion of primary tumor, carina and hilus on 4DCT was 7.3mm (range 2-13.8mm), 6.8mm (1.8-21.2) and 11.0mm (4.2-15.1), respectively. Corresponding intra-fraction motion on MV cine was 4.1mm (0.6-13.6mm); 2.7mm (0-10mm) and 6.0mm (1.8-14.4mm), respectively. The tumor, hilus and carina could be tracked in 95%, 88% and 38% of the MV cine-images, respectively. CONCLUSIONS: Intra-fraction motion can be reliably measured using MV-cine images from a phantom. Motion discrepancies identified on MV cine-images can identify patients in whom planning 4DCT scans are not representative.

Accelerating regional atrophy rates in the progression from normal aging to Alzheimer's disease.

We investigated progression of atrophy in vivo, in Alzheimer's disease (AD), and mild cognitive impairment (MCI). We included 64 patients with AD, 44 with MCI and 34 controls with serial MRI examinations (interval 1.8 ± 0.7 years). A nonlinear registration algorithm (fluid) was used to calculate atrophy rates in six regions: frontal, medial temporal, temporal (extramedial), parietal, occipital lobes and insular cortex. In MCI, the highest atrophy rate was observed in the medial temporal lobe, comparable with AD. AD patients showed even higher atrophy rates in the extramedial temporal lobe. Additionally, atrophy rates in frontal, parietal and occipital lobes were increased. Cox proportional hazard models showed that all regional atrophy rates predicted conversion to AD. Hazard ratios varied between 2.6 (95% confidence interval (CI) = 1.1-6.2) for occipital atrophy and 15.8 (95% CI = 3.5-71.8) for medial temporal lobe atrophy. In conclusion, atrophy spreads through the brain with development of AD. MCI is marked by temporal lobe atrophy. In AD, atrophy rate in the extramedial temporal lobe was even higher. Moreover, atrophy rates also accelerated in parietal, frontal, insular and occipital lobes. Finally, in nondemented elderly, medial temporal lobe atrophy was most predictive of progression to AD, demonstrating the involvement of this region in the development of AD.

A robust and reliable method for detecting signals of interest in multiexponential decays.

The concept of rejecting the null hypothesis for definitively detecting a signal was extended to relaxation spectrum space for multiexponential reconstruction. The novel test was applied to the problem of detecting the myelin signal, which is believed to have a time constant below 40 ms, in T2 decays from magnetic resonance imagining of the human brain. It was demonstrated that the test allowed the detection of a signal in a relaxation spectrum by using only the information in the data, thus avoiding any potentially unreliable prior information. The test was implemented both explicitly and implicitly for simulated T2 measurements. For the explicit implementation, the null hypothesis was that a relaxation spectrum existed that had no signal below 40 ms and that was consistent with the T2 decay. The confidence level by which the null hypothesis could be rejected gave the confidence level that there was signal below the 40 ms time constant. The explicit implementation assessed the test's performance with and without prior information where the prior information was the non-negative relaxation spectrum assumption. The test was also implemented implicitly with a data conserving multiexponential reconstruction algorithm that used left invertible matrices and that has been published previously. The implicit and explicit implementations demonstrated similar characteristics in detecting the myelin signal in both the simulated and experimental T2 decays, providing additional evidence to support the close link between the two tests. When the relaxation spectrum was assumed to be non-negative, the novel test required signal to noise ratios (SNRs) approaching 1000 in the T2 decays for detection of the myelin signal with high confidence. When the relaxation spectrum was not assumed to be non-negative, the SNR requirements for a detection with high confidence increased by a factor of 25. The application of the test to a T2 decay from human white matter, measured in vivo with a SNR of 650, demonstrated a solid detection of the signal below 40 ms believed to be due to the myelin water. This study demonstrated the robustness and reliability of extending the concept of rejecting the null hypothesis to relaxation spectrum space. The study also raised serious questions about the susceptibility to false positive detection of the myelin signal of the multiexponential reconstruction algorithms currently in use.

Color intensity projection of digitally subtracted angiography for the visualization of brain arteriovenous malformations.

OBJECTIVE: Reliable and rapid delineation of arteriovenous malformations enables the application of effective treatments such as stereotactic radiosurgery. We describe a new method to improve the speed and reliability of visualizing the flow of contrast images with digital subtraction angiography. METHODS: In line with current practices, digital subtraction angiography was used to produce a sequence of grayscale images. The new method combines the standard grayscale images produced by digital subtraction angiography into a single composite color image that encodes the contrast arrival time at each point of the brain's circulatory system. The algorithm is simple, fast, and easy to implement. RESULTS: The technique allows the flow of contrast from a series of angiography images to be summarized in a single color image. CONCLUSION: This visualization method promises to improve the speed of manual delineation of arteriovenous malformations. Further studies are required to evaluate the clinical value of the use of color intensity projection images, supplemented by grayscale images as necessary, in comparison with contouring on grayscale images only.

Disturbed functional connectivity in brain tumour patients: evaluation by graph analysis of synchronization matrices.

OBJECTIVE: Cerebral functions are based on the functional interactions between multiple distinct specialized regions of the brain. Functional interactions require anatomical connections as well as the synchronization of brain oscillations. The present work aims at evaluating the impact of brain tumours on spatial patterns of functional connectivity of the brain measured at rest by MEG. METHODS: We analyzed the statistical dependency (by computing the synchronization likelihood (SL, a measure of generalized synchronization)) between MEG signals at rest, in 17 patients with a brain tumour and in 15 healthy controls. Following an approach that derives from graph theory, we also analyzed the architectural properties of the networks by computing two parameters from the SL matrix, the cluster coefficient C and the characteristic path length L. RESULTS: Alterations in synchronization levels were found in the patients and were not focal but involved intra-hemispheric connectivity. Effects were different considering the frequencies sub-bands, predominating in a decrease in high frequencies bands for long-distance connections and an increase in slower bands for local connectivity. In addition, graph analysis reveals changes in the normal "small-world" network architecture in addition to changes in synchronization levels with some differences according to the studied frequency sub-bands. CONCLUSIONS: Brain tumours alter the functional connectivity and the "network" architecture of the brain. These alterations are not focal and effects are different considering the frequencies sub-bands. SIGNIFICANCE: These neurophysiological changes may contribute to the cognitive alterations observed in patients with brain tumours.

Color intensity projections: a rapid approach for evaluating four-dimensional CT scans in treatment planning.

PURPOSE: Four-dimensional computerized tomography scans (4DCT) enable intrafractional motion to be determined. Because more than 1500 images can be generated with each 4DCT study, tools for efficient data visualization and evaluation are needed. We describe the use of color intensity projections (CIP) for visualizing mobility. METHODS: Four-dimensional computerized tomography images of each patient slice were combined into a CIP composite image. Pixels largely unchanged over the component images appear unchanged in the CIP image. However, pixels whose intensity changes over the phases of the 4DCT appear in the CIP image as colored pixels, and the hue encodes the percentage of time the tissue was in each location. CIPs of 18 patients were used to study tumor and surrogate markers, namely the diaphragm and an abdominal marker block. RESULTS: Color intensity projections permitted mobility of high-contrast features to be quickly visualized and measured. In three selected expiratory phases ("gating phases") that were reviewed in the sagittal plane, gating would have reduced mean tumor mobility from 6.3 +/- 2.0 mm to 1.4 +/- 0.5 mm. Residual tumor mobility in gating phases better correlated with residual mobility of the marker block than that of the diaphragm. CONCLUSION: CIPs permit immediate visualization of mobility in 4DCT images and simplify the selection of appropriate surrogates for gated radiotherapy.

Multiple sclerosis patients show a highly significant decrease in alpha band interhemispheric synchronization measured using MEG.

MEG data were acquired from a group of relapsing-remitting multiple sclerosis (MS) patients and a group of healthy controls, using an eyes-closed no-task condition. An interhemispheric coherence measure (IHCM), reflecting the synchronization between the left and right hemispheres, showed a decrease in the patients, particularly in the alpha band. No comparable differences were seen in the alpha band power or its distribution over the head. The observed difference is in agreement with a reduced long-range connectivity in the brains of MS patients. The IHCM was found to be reproducible in controls over a period of more than 15 months. Further studies should investigate whether MEG derived synchronization measures may be useful as markers for MS disease load.

How do brain tumors alter functional connectivity? A magnetoencephalography study.

OBJECTIVE: This study was undertaken to test the hypothesis that brain tumors interfere with normal brain function by disrupting functional connectivity of brain networks. METHODS: Functional connectivity was assessed by computing the synchronization likelihood in a broad band (0.5-60Hz) or in the gamma band (30-60Hz) between all pairwise combinations of magnetoencephalography signals. Magnetoencephalography recordings were made at rest in 17 brain tumor patients and 15 healthy control subjects. For a given threshold of synchronization likelihood values, graphs of the suprathreshold connections between each magnetoencephalography channel and the others channels were built. RESULTS: In some regions, a variable number of channels without connectivity (missing connective points) at this threshold was found. The number of missing connective points was higher in patients with brain tumors than in control subjects (p < 0.0001, broad and gamma band) and was higher for left-sided than right-sided tumors (p = 0.008, broad band; p < 0.0001, gamma band). Individual results analysis indicates that the majority of brain tumor patients display several regions with missing connective point alterations in the affected and in the contralateral hemisphere. INTERPRETATION: Our findings suggest that brain tumors induce a loss of functional connectivity that affects multiple brain regions, and that left side brain tumors have the more severe consequences in this respect.