Structural and resting-state MRI detects regional brain differences in young and mid-age healthy APOE-e4 carriers compared with non-APOE-e4 carriers.

The presence of the e4 allele of the apolipoprotein E (APOE) gene is the best-known genetic risk factor for Alzheimer's disease. In this study, we investigated the link between functional and behavioural differences and regional brain volume and cortical thickness differences in those who carry the e4 allele (e4+) and those who only carry the e3 allele (e3/e3). We studied these genotype populations in two age groups: a young group (average age, 21 years) and a mid-age group (average age, 50 years). High-resolution T1 -weighted MRI scans were analysed with Freesurfer to measure regional white matter brain volume and cortical thickness differences between genotype groups at each age. These data were correlated with behavioural findings in the same cohort. Resting-state MRI was also conducted to identify differences in underlying brain functional connectivity. We found that there was a positive correlation between the thickness of the parahippocampal cortex in young e4+ individuals and performance on an episodic memory task. Young e4+ individuals also showed a positive correlation between white matter volume in the left anterior cingulate and performance on a covert attention task. At mid-age, e4+ individuals had structural differences relative to e3/e3 individuals in these areas: the parahippocampal cortex was thicker and white matter volume in the left anterior cingulate was greater than in e3/e3 individuals. We discuss the possibility that an over-engagement with these regions by e4+ individuals in youth may have a neurogenic effect that is observable later in life. The cuneus appears to be an important region for APOE-driven differences in the brain, with greater functional connectivity among young e3/e3 individuals and greater white matter volume in young e4+ individuals.

MRI of carriers of the apolipoprotein E e4 allele-evidence for structural differences in normal-appearing brain tissue in e4+ relative to e4- young adults.

Apolipoprotein E is a protein involved in cholesterol and lipid transport. The gene coding for this protein has three different alleles: e2, e3 and e4. The e4 allele is recognised as a significant risk factor for the development of Alzheimer's disease in later life. Paradoxically, behavioural and functional evidence has demonstrated that the e4 allele may confer a cognitive advantage to the carrier in youth. In this article, a range of sophisticated and novel structural imaging techniques were used to identify subtle differences in the brain tissue of groups of young e4 and homozygous e3 carriers that might support this paradox. Using voxel-based morphometry of high-resolution structural MR images, we identified a higher white matter volume ratio in e4 relative to homozygous e3 carriers. Furthermore, diffusion tensor imaging and tract-based spatial statistics studies identified increases in axial diffusivity and mode of anisotropy in carriers of the e4 allele. In addition, quantitative magnetisation transfer data were analysed using tract-based spatial statistics. Evidence of a trend towards an increased transverse relaxation time of the bound proton pool was detected in e4 carriers, indicative of altered white matter composition. These changes were found to correlate with indices of cognitive performance across the two groups, supporting the notion that such subtle differences in white matter integrity may confer neural advantages that contribute to cognitive outcomes and, potentially, to performance differences, such as observed here in a test of verbal fluency and reported previously by other researchers. Copyright © 2013 John Wiley & Sons, Ltd.

Comprehensive brain analysis with automated high-resolution magnetization transfer measurements.

PURPOSE: To enhance the reliability and spatial resolution of magnetization transfer ratio (MTR) measurements for interrogation of subcortical brain regions with an automated volume of interest (VOI) approach. MATERIALS AND METHODS: A 3D magnetization transfer (MT) sequence was acquired using a scan-rescan imaging protocol in nine healthy volunteers. VOI definition masks for the MTR measurements were generated using FreeSurfer and compared to a manual region of interest (ROI) approach. (The longitudinal stability of MTR was monitored using agar gel phantom over a 5-month period.) Intraclass correlation coefficients (ICCs), coefficients of variation (CVs), and instrumental standard deviation (ISD) were determined. RESULTS: CVs ranged from 1.29%-2.64% (automated) vs. 1.30%-3.40% (manual). ISDs ranged from 0.62-1.10 pu (automated) vs. 0.68-1.67 pu (manual). The SD of the running difference was 1.70% for the phantom scans. The Bland-Altman method indicated interchangeability of the automated VOI and manual ROI measurements. CONCLUSION: The automated VOI approach for MTR measurement yielded higher ICCs, lower CVs, and lower ISDs compared to the manual method, supporting the utility of this strategy. These results demonstrate the feasibility of obtaining reliable MTR measurements in hippocampus and other critical subcortical regions.

Precise measurement of renal filtration and vascular parameters using a two-compartment model for dynamic contrast-enhanced MRI of the kidney gives realistic normal values.

OBJECTIVE: To model the uptake phase of T(1)-weighted DCE-MRI data in normal kidneys and to demonstrate that the fitted physiological parameters correlate with published normal values. METHODS: The model incorporates delay and broadening of the arterial vascular peak as it appears in the capillary bed, two distinct compartments for renal intravascular and extravascular Gd tracer, and uses a small-vessel haematocrit value of 24%. Four physiological parameters can be estimated: regional filtration K ( trans ) (ml min(-1) [ml tissue](-1)), perfusion F (ml min(-1) [100 ml tissue](-1)), blood volume v ( b ) (%) and mean residence time MRT (s). From these are found the filtration fraction (FF; %) and total GFR (ml min(-1)). Fifteen healthy volunteers were imaged twice using oblique coronal slices every 2.5 s to determine the reproducibility. RESULTS: Using parenchymal ROIs, group mean values for renal biomarkers all agreed with published values: K ( trans ): 0.25; F: 219; v ( b ): 34; MRT: 5.5; FF: 15; GFR: 115. Nominally cortical ROIs consistently underestimated total filtration (by ~50%). Reproducibility was 7-18%. Sensitivity analysis showed that these fitted parameters are most vulnerable to errors in the fixed parameters kidney T(1), flip angle, haematocrit and relaxivity. CONCLUSIONS: These renal biomarkers can potentially measure renal physiology in diagnosis and treatment. KEY POINTS: • Dynamic contrast-enhanced magnetic resonance imaging can measure renal function. • Filtration and perfusion values in healthy volunteers agree with published normal values. • Precision measured in healthy volunteers is between 7 and 15%.

The perfect qMR machine: Measurement variance much less than biological variance.

Implementing quantitative MR (qMR) methodology can be a time-consuming task, sometimes seemingly without an end. The concept of the Perfect qMR Machine offers the possibility that the implementation is complete and that no further improvements are needed. This is achieved by making the measurement repeatability variance much less than the biological variance. Thus the proposal is: A Perfect Quantitative MR machine is one that, in making a measurement, contributes no significant extra variation to that which already exists from biological variation. A medal system (platinum, gold, silver and bronze) recognises different sources of biological variance, depending on the type of measurement being carried out (whether a serial study or a group comparison), and different kinds of measurement variance (single machine or multi-centre). A perfect machine can in principle be demonstrated for each quantitative measure (T1, ADC etc).

Quantitative magnetisation transfer imaging in glioma: preliminary results.

Quantitative magnetisation transfer imaging (qMTI) is an extension of conventional MT techniques and allows the measurement of parameters that reflect tissue ultrastructure through the properties of macromolecule-bound protons; these include the bound proton fraction and the relaxation times of free and bound proton pools. It has been used in multiple sclerosis and Alzheimer's disease, and has shown changes in some of the parameters, particularly the bound proton fraction. The purpose of this pilot study was to assess whether qMTI could distinguish between gliomas and normal brain tissue, and provide proof of principle for its use in tumour characterisation. Eight subjects [three men, five women; mean age, 44 years; range, 27-66 years; seven World Health Organization (WHO) Grade II, one Grade III] with biopsy-proven glioma were imaged with a structural MRI protocol that included three-dimensional qMTI. qMTI parameters were extracted from regions of interest selected from different tumour components visible on conventional MR sequences, normal-appearing peritumoral tissue and distant normal-appearing white matter. All patients gave informed consent and the study was approved by the Local Research Ethics Committee. Almost all of the qMTI parameters detected abnormalities in both glioma and the peritumoral region relative to the distant white matter. In particular, the bound proton fraction was reduced significantly from 6.0 percentage units (pu) [standard deviation (SD), 0.5 pu] in normal-appearing white matter to 1.7 pu (SD = 0.5 pu) in solid tumour and 2.2 pu (SD = 0.5 pu) in peritumoral areas. This work shows that qMTI reveals abnormalities, not only in glioma, but also in the apparently normal tissue surrounding the conventionally defined tumour. Thus, qMTI shows promise for tumour characterisation and for studying tumour boundaries. These preliminary data justify larger studies in a range of different tumour types and grades.

Simulation-based comparison of two approaches frequently used for dynamic contrast-enhanced MRI.

PURPOSE: The purpose was to compare two approaches for the acquisition and analysis of dynamic-contrast-enhanced MRI data with respect to differences in the modelling of the arterial input-function (AIF), the dependency of the model parameters on physiological parameters and their numerical stability. Eight hundred tissue concentration curves were simulated for different combinations of perfusion, permeability, interstitial volume and plasma volume based on two measured AIFs and analysed according to the two commonly used approaches. The transfer constants (Approach 1) K (trans) and (Approach 2) k (ep) were correlated with all tissue parameters. K (trans) showed a stronger dependency on perfusion, and k (ep) on permeability. The volume parameters (Approach 1) v (e) and (Approach 2) A were mainly influenced by the interstitial and plasma volume. Both approaches allow only rough characterisation of tissue microcirculation and microvasculature. Approach 2 seems to be somewhat more robust than 1, mainly due to the different methods of CA administration.

Low-grade gliomas: six-month tumor growth predicts patient outcome better than admission tumor volume, relative cerebral blood volume, and apparent diffusion coefficient.

PURPOSE: To prospectively compare tumor volume, relative cerebral blood volume (rCBV), and apparent diffusion coefficient (ADC) and short-term changes of these parameters as predictors of time to malignant transformation and time to death in patients with low-grade gliomas (LGGs). MATERIALS AND METHODS: Patients gave written informed consent for this institutional ethics committee-approved study. Patients with histologically proved LGGs underwent conventional, perfusion-weighted, and diffusion-weighted magnetic resonance (MR) imaging at study entry and at 6 months. At both time points, tumor volume, maximum rCBV, and ADC histogram measures were calculated. Patient follow-up consisted of MR imaging every 6 months and clinical examinations. To investigate the association between MR imaging variables and time to progression and time to death, a Cox regression curve was applied at study entry and at 6 months. The models were corrected for age, sex, and histologic findings. RESULTS: Thirty-four patients (22 men, 12 women; mean age, 42 years) with histologically proved LGGs (eight oligodendrogliomas, 20 astrocytomas, and six oligoastrocytomas) were followed up clinically and radiologically for a median of 2.6 years (range, 0.4-5.5 years). Tumor growth over the course of 6 months was the best predictor of time to transformation, independent of rCBV, diffusion histogram parameters, age, sex, and histologic findings. When only single-time-point measurements were compared, tumor volume helped predict outcome best and was the only independent predictor of time to death (P < .02). CONCLUSION: Six-month tumor growth helps predict outcome in patients with LGG better than parameters derived from perfusion- or diffusion-weighed MR imaging. Tumor growth can readily be calculated from volume measurements on images acquired with standard MR imaging protocols and may well prove most useful among various MR imaging findings in clinical practice.

Low-grade gliomas: do changes in rCBV measurements at longitudinal perfusion-weighted MR imaging predict malignant transformation?

PURPOSE: To prospectively perform longitudinal magnetic resonance (MR) perfusion imaging of conservatively treated low-grade gliomas to determine whether relative cerebral blood volume (rCBV) changes precede malignant transformation as defined by conventional MR imaging and clinical criteria. MATERIALS AND METHODS: All patients gave written informed consent for this institutional ethics committee-approved study. Thirteen patients (seven men, six women; age range, 29-69 years) with biopsy-proved low-grade glioma treated only with antiepileptic drugs were examined longitudinally with susceptibility-weighted perfusion, T2-weighted, fluid-attenuated inversion recovery, and high-dose contrast material-enhanced T1-weighted MR imaging at 6-month intervals to date or until malignant transformation was diagnosed. Student t tests were used to determine differences in rCBV values between "transformers" and "nontransformers" at defined time points throughout study follow-up. RESULTS: Seven patients showed progression to high-grade tumors between 6 and 36 months (mean, 22.3 months), and disease in six patients remained stable over a period of 12-36 months (mean, 23 months). Transformers had a slightly (but not statistically significantly) higher group mean rCBV than nontransformers at the point of study entry (1.93 vs 1.31). In nontransformers, the rCBV remained relatively stable and increased to only 1.52 over a mean follow-up of 23 months. In contrast, transformers showed a continuous increase in rCBV up to the point of transformation, when contrast enhancement became apparent on T1-weighted images. The group mean rCBV was 5.36 at transformation but also showed a significant increase from the initial study at 12 months (3.14, P = .022) and at 6 months (3.65, P = .049) before transformation. Rates of rCBV change between two successive time points were also significantly higher in transformers than in nontransformers. CONCLUSION: In transforming low-grade glioma, susceptibility-weighted MR perfusion imaging can demonstrate significant increases in rCBV up to 12 months before contrast enhancement is apparent on T1-weighted MR images.

A simple correction for B1 field errors in magnetization transfer ratio measurements.

B1 errors are a problem in magnetization transfer ratio (MTR) measurements because the MTR value is dependent on the amplitude of the magnetization transfer (MT) pulse. B1 errors can arise from radiofrequency (RF) nonuniformity (caused by the RF coil, or skin effect and dielectric resonance in the subject's head) and also from inaccurate setting of the transmitter output when compensating for varying amounts of loading of the RF coil. B1 errors, and hence MTR errors, may be up to 5-10%, a large source of error in quantitative MR measurements. Radiofrequency nonuniformity may cause MTR histograms to be broadened. The dependence of MTR on B1 was modeled using binary spin bath theory, with a continuous wave (CW) approximation. For B1 reductions of up to 20%, normalized plots for different brain tissue types could be approximated by a single line, indicating that a systematic correction could be applied to MTR measurements with a known B1 error, regardless of tissue type. On a 1.5-T scanner with a birdcage coil, MTR was measured in 18 tissue types in five controls. The MT pulse amplitude was reduced in steps from its nominal value by up to 20%. Averaging data over all controls and tissue types resulted in a line fitting mtr(normalized)=0.812b(1normalized)+0.193, where mtr(normalized) is the normalized value of MTR (relative to its value at the nominal B1) and b(1normalized) is the normalized value of B1 (relative to its nominal value). For a 20% reduction in MT pulse amplitude (i.e., b(1normalized)=0.80), the mean MTR value for the 18 tissue types was 7.0 percent units (pu) below the correct value. After correction using the single equation above for all tissue types, all MTR values were within 1.5 pu of their correct value [root mean square (rms) error=0.7 pu]. Magnetization transfer ratio values tended to be slightly overcorrected because the simple linear correction scheme is only an approximation to the true MTR dependence on B1. A B1 field mapping technique was implemented, based on the double angle method (DAM), with fast spin-echo (FSE) readout, and TR=15 s; this took a total of 6 min of imaging time. This was used to quantify B(1) errors and correct MTR maps and histograms. However, the cerebrospinal fluid (CSF) T1 is very long (approximately 4.2 s); thus, to achieve complete longitudinal relaxation (a requirement of the DAM B1 mapping method), an increase in TR and, hence, acquisition time would be required. In general, however, we are not interested in calculating the B1 in the CSF, although it is important that the B1 is determined in partial volume voxels around the CSF. Using our birdcage head coil, whole-brain B1 histograms were found to have full-width half maximums (FWHMs) ranging from just 6.8% to 11.5% of the nominal B1 value. The FSE DAM B1 field mapping technique was shown to be robust, although a longer TR time may be desirable to ensure complete elimination of CSF partial volume errors. The procedure can be applied on any scanner where the Euro-MT sequence is available, or alternatively, where the amplitude of B1 or of the MT pulse can be manually reduced in order to perform this type of "calibration" experiment for the particular MTR sequence used. The MTR is known to be highly dependent on the parameters of the sequence used, in particular, the MT pulse shape, flip angle, duration, and offset frequency, and the repetition time TR' between successive MT pulses. Therefore, correction schemes will differ for different MTR sequences, and new data sets would be required to calculate these different correction schemes.

Principal component and linear discriminant analysis of T1 histograms of white and grey matter in multiple sclerosis.

Twenty-three relapsing remitting multiple sclerosis (RRMS) patients and 14 controls were imaged to produce normal-appearing white and grey matter T1 histograms. These were used to assess whether histogram measures from principal component analysis (PCA) and linear discriminant analysis (LDA) out-perform traditional histogram metrics in classification of T1 histograms into control and RRMS subject groups and in correlation with the expanded disability status score (EDSS). The histograms were classified into one of two groups using a leave-one-out analysis. In addition, the patients were scanned serially, and the calculated parameters correlated with the EDSS. The classification results showed that the more complex techniques were at least as good at classifying the subjects as histogram mean, peak height and peak location, with PCA/LDA having success rates of 76% for white matter and 68%/65% for grey matter. No significant correlations were found with EDSS for any histogram parameter. These results indicate that there is much information contained within the grey matter as well as the white matter histograms. Although in these histograms PCA and LDA did not add greatly to the discriminatory power of traditional histogram parameters, they provide marginally better performance, while relying only on data-driven feature selection.

Unbiased segmentation of diffusion-weighted magnetic resonance images of the brain using iterative clustering.

Segmentation of diffusion-weighted echo-planar imaging (DW-EPI) is challenging because of concerns regarding spatial resolution and distortion. Methods commonly used require manual input and often need thresholding measures to segment white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF). This may introduce operator bias and misclassification error. When comparing patients with a diffuse disease process-such as multiple sclerosis (MS)--with healthy controls, although information from all images may be biased due to disease effect, this is more so if the data set employed to perform segmentation is also used as a measured outcome for the study, for example, fractional anisotropy maps. Presented in this work is an unbiased method for segmenting DW-EPI data sets using the b=0 and single-shot inversion recovery EPI into WM, GM and CSF. The method employs an iterative clustering technique to account for partial volume effects and signal variation caused by radiofrequency inhomogeneity. The technique is evaluated with both real and synthetic brain data and results compared with statistical parametric mapping (SPM02). With synthetic brain data, where a gold standard of segmentation exists, the presented method showed less misclassification compared to SPM02. The unbiased method proposed may provide a more accurate methodology of segmentation in the analysis of DWI-EPI images in conditions such as MS.

Cognitive and neural signatures of the APOE E4 allele in mid-aged adults.

The apolipoprotein E (APOE) e4 allele is strongly associated with increased risk of cognitive impairments in older adulthood. There is also a possible link to enhanced cognitive performance in younger adults, and the APOE e4 allele may constitute an example of antagonistic pleiotropy. The aim of this work was to investigate the cognitive and neural (functional) effects of the APOE e4 allele during mid-age (45-55 years), where a transition toward cognitive deficit might be expected. APOE e4 carriers (e4+) were compared with non-e4 carriers (e4-) on tasks of sustained and covert attention and prospective memory, and functional magnetic resonance imaging data acquired. Performance by e4+ was equivalent or better than e4- on all 3 tasks, although performance benefits were less pronounced than in youth. Neurally, e4+ showed less task-related recruitment of extrastriate and parietal areas. This became more evident when neural activation data were compared with that of young adults acquired in a parallel study. As expected, mid-age participants showed more diffuse neural activation. Notable was the fact that e4+ showed a relative inability to recruit parietal regions as they aged. This was coupled with a tendency to show greater recruitment of frontal regions, and underactivation of extrastriate visual regions. Thus, mid-age e4+ show a pattern of neural recruitment usually seen later in life, possibly reflecting the source of an accelerated aging profile that describes the e4 genotype.

Nicotine effects on attentional reorienting in mid-age adults, and interactions with apolipoprotein E status.

Nicotine has been shown to speed attentional reorienting in cued target detection tasks, and work in young adults suggest that individuals carrying the apolipoprotein E (APOE) e4 allele might show greater sensitivity to the cognitive effects of nicotine. The APOE e4 allele is associated with increased risk of Alzheimer's disease (AD), and increased sensitivity to nicotine might reflect early cholinergic differences that relate to an enhanced risk of AD. The aim of this study was to investigate effects of nicotine and APOE on attentional reorienting in mid-age participants. APOE e4 (e4+) were compared to non-APOE e4 (e4-) carriers, and functional magnetic resonance imaging (fMRI) data acquired. Neural data showed that nicotine effects, and the network involved in reorienting, was consistent with studies in young adults. Nicotine improved attentional reorienting at the trend level. Although there were no behavioural effects of genotype, genotype effects were present neurally: e4+ showed decreased extrastriate activation, and enhanced effects of nicotine on reorienting in right middle frontal regions. Drug by genotype interactions were present in hippocampal and anterior cingulate regions. These results are consistent with differential sensitivity to nicotine according to APOE status, possibly reflecting abnormal cholinergic function and accelerated cognitive ageing in mid-age e4+.

Measuring the effect of pars plana vitrectomy on vitreous oxygenation using magnetic resonance imaging.

PURPOSE: To study the effect of pars plana vitrectomy (PPV) on vitreous oxygenation (pO2) using magnetic resonance imaging (MRI). METHODS: Patients due to undergo PPV for either macular hole or epiretinal membrane were recruited. MRI scanning was performed 1 week before and at least 3 months after PPV. MRI T1 mapping was performed using an inversion recovery-true fast imaging with steady-state precession (TrueFISP) sequence at several inversion times, from a single slice positioned through the center of both eyes in the axial oblique plane. Additional phantom data were measured in porcine vitreous, to define the relationships between T1 relaxation times and balanced salt solution (BSS), to simulate human vitreous and aqueous, respectively, for a suitable pO2 range (5-70 mm Hg). Pre-PPV pO2 was also measured intraoperatively using a polarographic oxygen probe. RESULTS: Eleven participants (age range 59-84) were recruited; two declined the post-PPV scan. Corrected T1 times indicated that the mean (±SD) pO2 increased significantly following PPV, from 13.2 ± 5.8 to 34.5 ± 8.0 mm Hg (P < 0.001). In the nonsurgical (control) eye, pO2 did not change significantly from the first to second MRI scan (13.7 ± 7.8 vs. 16.3 ± 8.7 mm Hg, P = 0.239). Mean pO2 measured intraoperatively was 7.2 ± 0.6 mm Hg (n = 10). CONCLUSIONS: These results confirm that vitrectomy substantially increases vitreous pO2. MRI is a noninvasive technique that can be used to study vitreous oxygenation in both vitrectomized and nonvitrectomized eyes.

APOE E4 Carriers show prospective memory enhancement under nicotine, and evidence for specialisation within medial BA10.

There is evidence to suggest that the APOE ɛ4 allele (which confers an increased risk of developing dementia) might be associated with cognitive advantages earlier in life. Further, nicotine might selectively benefit ɛ4 carriers. We used fMRI to explore performance on a prospective memory (PM) task in young adults (age 18-30) with and without nicotine using a within-subjects design. Participants performed an ongoing task while retaining a PM instruction to respond to specific stimuli embedded in the task. Nicotine effects varied according to APOE status. Reaction times to the PM cue were improved under nicotine in ɛ4 carriers, but not in ɛ3 carriers. In an event-related analysis, extrastriate responses to PM trials were enhanced by nicotine only in ɛ4 carriers. These differences in early visual processing may contribute to the behavioral findings. Activity in medial BA10 (previously implicated in PM) differentiated ɛ4 from ɛ3 carriers. One BA10 subregion showed greater deactivation in ɛ4 carriers during PM trials. Activity in other BA10 subregions was modulated by PM reaction time, pointing to region-specific effects within medial BA10. In addition, activity in right hippocampal formation was only seen in ɛ4 carriers receiving nicotine. These results demonstrate that cognitive enhancement by nicotine can selectively benefit APOE ɛ4 carriers, and point to genotype-specific differences in neural activity during PM. In addition, these results show that the role of medial BA10 in PM likely involves varying contributions from functionally specific subregions.

Toward clinical application of manganese-enhanced MRI of retinal function.

PURPOSE: The application of manganese-enhanced MRI (MEMRI) to measure retinal function in humans is unclear. To begin to address this gap, we tested the hypothesis that an FDA-approved manganese-based MRI contrast agent, Teslascan, is useful for measuring functional intraretinal ionic regulation. METHODS: Anesthetized dark- or light-adapted male healthy Sprague-Dawley rats were infused for 30 min with 10 micromol/kg of Teslascan (clinically relevant dose; n = 5), 100 micromol/kg Teslascan (n = 5), or saline (n = 5). Four hours post-administration, high resolution MEMRI data were collected. Intraretinal signal intensities and enhancements were measured. Modelling was performed to estimate apparent retinal transfer constant K(i) and to determine optimal data acquisition parameters. RESULTS: In light-adapted rats, intraretinal enhancements responded in a dose-response manner. In addition, in the outer retina the effect of light-adaptation was to reduce significantly Mn(2+) uptake and K(i) compared to dark-adaptation. A non-significant change was also observed in the inner retina. Modelling shows Mn(2+) plasma concentration reaching a plateau after about 2 h. Apparent K(i) values for the clinically relevant dose are 3-6 x 10(-3) min(-1), decreasing to 0.5-0.6 x 10(-3) min(-1) at the higher dose. Intraretinal signal is almost linear with K(i). Optimal TR for a spin-echo sequence is 0.4-1.4s. CONCLUSION: First time evidence is presented that a clinically relevant dose and route of Teslascan can be used to measure intraretinal function. The potential for future clinical application of MEMRI in a broad range of retinopathies is high.

Quantitative imaging biomarkers in neuro-oncology.

Conventional structural imaging provides limited information on tumor characterization and prognosis. Advances in neurosurgical techniques, radiotherapy planning and novel drug treatments for brain tumors have generated increasing need for reproducible, noninvasive, quantitative imaging biomarkers. This Review considers the role of physiological MRI and PET molecular imaging in understanding metabolic processes associated with tumor growth, blood flow and ultrastructure. We address the utility of various techniques in distinguishing between tumors and non-neoplastic processes, in tumor grading, in defining anatomical relationships between tumor and eloquent brain regions and in determining the biological substrates of treatment response. Much of the evidence is derived from limited case series in individual centers. Despite their 'added value', the effect of these techniques as an adjunct to structural imaging in clinical research and practice remains limited.

Quantitative magnetic resonance of postmortem multiple sclerosis brain before and after fixation.

Unfixed and fixed postmortem multiple sclerosis (MS) brain is being used to probe pathology underlying quantitative MR (qMR) changes. Effects of fixation on qMR indices in MS brain are unknown. In 15 postmortem MS brain slices T(1), T(2), MT ratio (MTR), macromolecular proton fraction (f(B)), fractional anisotropy (FA), and mean, axial, and radial diffusivity (MD, D(ax), and D(rad)) were assessed in white matter (WM) lesions (WML) and normal appearing WM (NAWM) before and after fixation in formalin. Myelin content, axonal count, and gliosis were quantified histologically. Student's t-test and regression were used for analysis. T(1), T(2), MTR, and f(B) obtained in unfixed MS brain were similar to published values obtained in patients with MS in vivo. Following fixation T(1), T(2) (NAWM, WML) and MTR (NAWM) dropped, whereas f(B) (NAWM, WML) increased. Compared to published in vivo data all diffusivity measures were lower in unfixed MS brain, and dropped further following fixation (except for FA). MTR was the best predictor of T(myelin) (inversely related to myelin) in unfixed MS brain (r = -0.83; P < 0.01) whereas postfixation T(2) (r = 0.92; P < 0.01), T(1) (r = 0.89; P < 0.01), and f(B) (r = -0.86; P < 0.01) were superior. All diffusivity measures (except for D(ax) in unfixed tissue) were predictors of myelin content.