Demonstration of a mitochondrial DNA-compatible workflow for genetically variant peptide identification from human hair samples.

Hair is an evidentiary sample that typically does not provide sufficient nuclear DNA for forensic analysis. Therefore, state-of-the-art forensic examination for hair samples include subjective microscopic evaluation, mitochondrial DNA (mtDNA) analysis, and more recently, proteomic genotyping that uses protein variation in the form of genetically variant peptides (GVPs) to infer single nucleotide polymorphism (SNP) alleles. Since many cases involve limited sample amounts (approximately 2 cm or less), any additional destructive testing (besides mtDNA) would be excluded. If a mtDNA-compatible protein extraction workflow could be developed, GVPs would provide additional forensic value without sacrificing any portion of the original hair sample. Here, we demonstrate an optimized method that can be used to obtain both whole genome mtDNA and putative GVP profiles from a single limited hair sample. The method involves urea-based extraction of proteins from hair, followed by buffer exchange and protease digestion. Peptides are eluted through a 30 kDa membrane and analyzed using traditional proteomic techniques. DNA is subsequently extracted from the filter and analyzed using whole mt-genome analysis. The method was verified with a range of hair sample types (head, pubic, and arm hair) from a diverse cohort of 22 individuals. Specifically, putative GVP profiles and mtDNA haplotypes concordant with buccal swab samples from the same donor were obtained from 22 individuals. Further, the utility of the method was verified across two different laboratories. The method is applicable for proteomic-based GVP analysis and mt-genome analysis for forensic research applications.

Multidimensional diffusion MRI with spectrally modulated gradients reveals unprecedented microstructural detail.

Characterization of porous media is essential in a wide range of biomedical and industrial applications. Microstructural features can be probed non-invasively by diffusion magnetic resonance imaging (dMRI). However, diffusion encoding in conventional dMRI may yield similar signatures for very different microstructures, which represents a significant limitation for disentangling individual microstructural features in heterogeneous materials. To solve this problem, we propose an augmented multidimensional diffusion encoding (MDE) framework, which unlocks a novel encoding dimension to assess time-dependent diffusion specific to structures with different microscopic anisotropies. Our approach relies on spectral analysis of complex but experimentally efficient MDE waveforms. Two independent contrasts to differentiate features such as cell shape and size can be generated directly by signal subtraction from only three types of measurements. Analytical calculations and simulations support our experimental observations. Proof-of-concept experiments were applied on samples with known and distinctly different microstructures. We further demonstrate substantially different contrasts in different tissue types of a post mortem brain. Our simultaneous assessment of restriction size and shape may be instrumental in studies of a wide range of porous materials, enable new insights into the microstructure of biological tissues or be of great value in diagnostics.

Delivering Functional Imaging on the MRI-Linac: Current Challenges and Potential Solutions.

Magnetic resonance imaging (MRI) is a highly versatile imaging modality that can be used to measure features of the tumour microenvironment including cell death, proliferation, metabolism, angiogenesis, and hypoxia. Mapping and quantifying these pathophysiological features has the potential to alter the use of adaptive radiotherapy planning. Although these methods are available for use on diagnostic machines, several challenges exist for implementing these functional MRI methods on the MRI-linear accelerators (linacs). This review considers these challenges and potential solutions.

Correction to: Volumetric dynamic oxygen-enhanced MRI (OE-MRI): comparison with CT Brody score and lung function in cystic fibrosis patients.

The original version of this article, published on 13 April 2018, unfortunately contained a mistake.

Microstructural imaging of the human brain with a 'super-scanner': 10 key advantages of ultra-strong gradients for diffusion MRI.

The key component of a microstructural diffusion MRI 'super-scanner' is a dedicated high-strength gradient system that enables stronger diffusion weightings per unit time compared to conventional gradient designs. This can, in turn, drastically shorten the time needed for diffusion encoding, increase the signal-to-noise ratio, and facilitate measurements at shorter diffusion times. This review, written from the perspective of the UK National Facility for In Vivo MR Imaging of Human Tissue Microstructure, an initiative to establish a shared 300 mT/m-gradient facility amongst the microstructural imaging community, describes ten advantages of ultra-strong gradients for microstructural imaging. Specifically, we will discuss how the increase of the accessible measurement space compared to a lower-gradient systems (in terms of Δ, b-value, and TE) can accelerate developments in the areas of 1) axon diameter distribution mapping; 2) microstructural parameter estimation; 3) mapping micro-vs macroscopic anisotropy features with gradient waveforms beyond a single pair of pulsed-gradients; 4) multi-contrast experiments, e.g. diffusion-relaxometry; 5) tractography and high-resolution imaging in vivo and 6) post mortem; 7) diffusion-weighted spectroscopy of metabolites other than water; 8) tumour characterisation; 9) functional diffusion MRI; and 10) quality enhancement of images acquired on lower-gradient systems. We finally discuss practical barriers in the use of ultra-strong gradients, and provide an outlook on the next generation of 'super-scanners'.

Volumetric dynamic oxygen-enhanced MRI (OE-MRI): comparison with CT Brody score and lung function in cystic fibrosis patients.

OBJECTIVES: To demonstrate, in patients with cystic fibrosis (CF), the correlation between three-dimensional dynamic oxygen-enhanced magnetic resonance imaging (OE-MRI) measurements and computed tomography Brody score (CF-CT) and lung function testing (LFT). METHODS: Twenty-one patients (median age, 25 years; female, n = 8) with a range of CF lung disease and five healthy volunteers (median age, 31 years; female, n = 2) underwent OE-MRI performed on a 1.5-T MRI scanner. Coronal volumes were acquired while patients alternately breathed room air and 100% oxygen. Pre-oxygen T1 was measured. Dynamic series of T1-weighted volumes were then obtained while breathing oxygen. T1-parameter maps were generated and the following OE-MRI parameters were measured: oxygen uptake (ΔPO2max), wash-in time and wash-out time. High-resolution CT and LFT were performed. The relationship between CF-CT, LFT and OE-MRI parameters were evaluated using Pearson correlation for the whole lung and regionally. RESULTS: Mean CF-CT was 24.1±17.1. Mean ΔPO2max and mean wash-in as well as skewness of wash-out showed significant correlation with CF-CT (ΔPO2max: r = -0.741, p < 0.001; mean wash-in: r = 0.501, p = 0.017; skewness of wash-out: r = 0.597, p = 0.001). There was significant correlation for the whole lung and regionally between LFT parameters and OE-MR (ΔPO2max: r = 0.718, p < 0.001; wash-in: r = -0.576, p = 0.003; wash-out skewness: r = -0.552, p = 0.004). CONCLUSIONS: Functional lung imaging using OE-MRI has the capability to assess the severity of CF lung disease and shows a significant correlation with LFT and CF-CT. KEY POINTS: • Oxygen-enhanced MRI might play a future role in evaluation and follow-up of cystic fibrosis. • Heterogeneity of parameter maps reflects localised functional impairment in cystic fibrosis. • Avoidance of cumulative radiation burden in CF is feasible using OE-MRI.

Mitotic Activity in Glioblastoma Correlates with Estimated Extravascular Extracellular Space Derived from Dynamic Contrast-Enhanced MR Imaging.

BACKGROUND AND PURPOSE: A number of parameters derived from dynamic contrast-enhanced MR imaging and separate histologic features have been identified as potential prognosticators in high-grade glioma. This study evaluated the relationships between dynamic contrast-enhanced MRI-derived parameters and histologic features in glioblastoma multiforme. MATERIALS AND METHODS: Twenty-eight patients with newly presenting glioblastoma multiforme underwent preoperative imaging (conventional imaging and T1 dynamic contrast-enhanced MRI). Parametric maps of the initial area under the contrast agent concentration curve, contrast transfer coefficient, estimate of volume of the extravascular extracellular space, and estimate of blood plasma volume were generated, and the enhancing fraction was calculated. Surgical specimens were used to assess subtype and were graded (World Health Organization classification system) and were assessed for necrosis, cell density, cellular atypia, mitotic activity, and overall vascularity scores. Quantitative assessment of endothelial surface area, vascular surface area, and a vascular profile count were made by using CD34 immunostaining. The relationships between MR imaging parameters and histopathologic features were examined. RESULTS: High values of contrast transfer coefficient were associated with the presence of frank necrosis (P = .005). High values of the estimate of volume of the extravascular extracellular space were associated with a fibrillary histologic pattern (P < .01) and with increased mitotic activity (P < .05). No relationship was found between mitotic activity and histologic pattern, suggesting that the correlation between the estimate of volume of the extravascular extracellular space and mitotic activity was independent of the histologic pattern. CONCLUSIONS: A correlation between the estimate of volume of the extravascular extracellular space and mitotic activity is reported. Further work is warranted to establish how dynamic contrast-enhanced MRI parameters relate to more quantitative histologic measurements, including markers of proliferation and measures of vascular endothelial growth factor expression.

Mutual information as a measure of image quality for 3D dynamic lung imaging with EIT.

We report on a pilot study of dynamic lung electrical impedance tomography (EIT) at the University of Manchester. Low-noise EIT data at 100 frames per second were obtained from healthy male subjects during controlled breathing, followed by magnetic resonance imaging (MRI) subsequently used for spatial validation of the EIT reconstruction. The torso surface in the MR image and electrode positions obtained using MRI fiducial markers informed the construction of a 3D finite element model extruded along the caudal-distal axis of the subject. Small changes in the boundary that occur during respiration were accounted for by incorporating the sensitivity with respect to boundary shape into a robust temporal difference reconstruction algorithm. EIT and MRI images were co-registered using the open source medical imaging software, 3D Slicer. A quantitative comparison of quality of different EIT reconstructions was achieved through calculation of the mutual information with a lung-segmented MR image. EIT reconstructions using a linear shape correction algorithm reduced boundary image artefacts, yielding better contrast of the lungs, and had 10% greater mutual information compared with a standard linear EIT reconstruction.

Anatomical brain connectivity can assess cognitive dysfunction in multiple sclerosis.

BACKGROUND: Brain disconnection plays a major role in determining cognitive disabilities in multiple sclerosis (MS). We recently developed a novel diffusion-weighted magnetic resonance imaging (DW-MRI) tractography approach, namely anatomical connectivitity mapping (ACM), that quantifies structural brain connectivity. OBJECTIVE: Use of ACM to assess structural connectivity modifications in MS brains and ascertain their relationship with the patients' Paced-Auditory-Serial-Addition-Test (PASAT) scores. METHODS: Relapsing-remitting MS (RRMS) patients (n = 25) and controls (n = 25) underwent MRI at 3T, including conventional images, T1-weighted volumes and DW-MRI. Volumetric scans were coregistered to fractional anisotropy (FA) images, to obtain parenchymal FA maps for both white and grey matter. We initiated probabilistic tractography from all parenchymal voxels, obtaining ACM maps by counting the number of streamlines passing through each voxel, then normalizing by the total number of streamlines initiated. The ACM maps were transformed into standard space, for statistical use. RESULTS: RRMS patients had reduced grey matter volume and FA, consistent with previous literature. Also, we showed reduced ACM in the thalamus and in the head of the caudate nucleus, bilaterally. In our RRMS patients, ACM was associated with PASAT scores in the corpus callosum, right hippocampus and cerebellum. CONCLUSIONS: ACM opens a new perspective, clarifying the contribution of anatomical brain disconnection to clinical disabilities in MS.

Magnetic resonance imaging relaxation time measurements of the placenta at 1.5 T.

UNLABELLED: Placental insufficiency is a major cause of fetal growth restriction (FGR) and accumulating evidence indicates several aspects of placental morphology are altered in this condition. MRI provides quantitative indices that may be used in non-invasive assessment of the human placenta, such as relaxation time measurements, T1 and T2. We hypothesised that placental relaxation times relate to alterations in placental tissue morphology and hence may be useful in identifying the changes associated with FGR. We report on the first phase of testing this hypothesis, in a study of women in normal pregnancy. AIMS: To assess relaxation time measurements in the placenta in normal pregnancy and correlate these with gestational age and stereological analyses of placental morphology following delivery. METHODS: 30 women underwent MRI examination (1.5 T) between 20 and 41 weeks gestation. Placental T1 and T2 measurements were acquired from a mid-depth placental region, co-localised to a structural scan. Fixed, wax-embedded sections of these placentas collected at delivery were stained with hematoxylin/eosin and subjected to stereological analysis. RESULTS: Placental T1 and T2 show a significant negative correlation with gestation, (Pearson correlation p=0.01, 0.03 respectively). 17 placentas were analysed stereologically. In the group as a whole there was no significant correlation between T1 and T2 and morphological features. However, in a subset of 7 pregnancies scanned within a week of delivery, a significant positive correlation was observed between the fibrin volume density and the ratio of fibrin: villous volume densities and T2 (Spearman correlation p=0.02, 0.03 respectively). DISCUSSION: The correlations between placental T1 and T2 and gestation show that these variables are clearly influenced by changes in placental structure. Fibrin might be a key component but further work is needed to fully elucidate the major structural influences on placental T1 and T2.

DCE-MRI biomarkers of tumour heterogeneity predict CRC liver metastasis shrinkage following bevacizumab and FOLFOX-6.

BACKGROUND: There is limited evidence that imaging biomarkers can predict subsequent response to therapy. Such prognostic and/or predictive biomarkers would facilitate development of personalised medicine. We hypothesised that pre-treatment measurement of the heterogeneity of tumour vascular enhancement could predict clinical outcome following combination anti-angiogenic and cytotoxic chemotherapy in colorectal cancer (CRC) liver metastases. METHODS: Ten patients with 26 CRC liver metastases had two dynamic contrast-enhanced MRI (DCE-MRI) examinations before starting first-line bevacizumab and FOLFOX-6. Pre-treatment biomarkers of tumour microvasculature were computed and a regression analysis was performed against the post-treatment change in tumour volume after five cycles of therapy. The ability of the resulting linear model to predict tumour shrinkage was evaluated using leave-one-out validation. Robustness to inter-visit variation was investigated using data from a second baseline scan. RESULTS: In all, 86% of the variance in post-treatment tumour shrinkage was explained by the median extravascular extracellular volume (v(e)), tumour enhancing fraction (E(F)), and microvascular uniformity (assessed with the fractal measure box dimension, d(0)) (R(2)=0.86, P<0.00005). Other variables, including baseline volume were not statistically significant. Median prediction error was 12%. Equivalent results were obtained from the second scan. CONCLUSION: Traditional image analyses may over-simplify tumour biology. Measuring microvascular heterogeneity may yield important prognostic and/or predictive biomarkers.

Comparison of dynamic contrast-enhanced MRI and dynamic contrast-enhanced CT biomarkers in bladder cancer.

Dynamic contrast-enhanced MRI (DCE-MRI) is frequently used to provide response biomarkers in clinical trials of novel cancer therapeutics but assessment of their physiological accuracy is difficult. DCE-CT provides an independent probe of similar pharmacokinetic processes and may be modeled in the same way as DCE-MRI to provide purportedly equivalent physiological parameters. In this study, DCE-MRI and DCE-CT were directly compared in subjects with primary bladder cancer to assess the degree to which the model parameters report modeled physiology rather than artefacts of the measurement technique and to determine the interchangeability of the techniques in a clinical trial setting. The biomarker K(trans) obtained by fitting an extended version of the Kety model voxelwise to both DCE-MRI and DCE-CT data was in excellent agreement (mean across subjects was 0.085 ± 0.030 min(-1) for DCE-MRI and 0.087 ± 0.033 min(-1) for DCE-CT, intermodality coefficient of variation 9%). The parameter v(p) derived from DCE-CT was significantly greater than that derived from DCE-MRI (0.018 ± 0.006 compared to 0.009 ± 0.008, P = 0.0007) and v(e) was in reasonable agreement only for low values. The study provides evidence that the biomarker K(trans) is a robust parameter indicative of the underlying physiology and relatively independent of the method of measurement.

A two-part phase II study of cediranib in patients with advanced solid tumours: the effect of food on single-dose pharmacokinetics and an evaluation of safety, efficacy and imaging pharmacodynamics.

BACKGROUND: Cediranib (RECENTIN™) is an oral, highly potent VEGF inhibitor. This study evaluated the effect of food on the pharmacokinetics of cediranib and compared the administration of continual cediranib via two dosing strategies using this as a platform to investigate pharmacodynamic imaging biomarkers. METHODS: Sixty patients were randomised to receive two single doses of cediranib in either fed/fasted or fasted/fed state (Part A). In continual dosage phase (Part B), patients were randomised to a fixed-dose or dose-escalation arm. Exploratory pharmacodynamic assessments were performed using DCE-MRI and CT enhancing fraction (EnF). RESULTS: In part A, plasma AUC and C (max) of cediranib were lower in the presence of food by a mean of 24 and 33%, respectively (94% CI: AUC, 12-34% and C (max), 20-43%), indicating food reduces cediranib plasma exposure. In part B, cediranib 30 mg/day appeared to be the most sustainable for chronic dosing. Continuous cediranib therapy was associated with sustained antivascular effects up to 16 weeks, with significant reductions in DCE-MRI parameters and CT EnF. CONCLUSIONS: It is recommended that cediranib be administered at least 1 h before or 2 h after food. Evidence of antitumour activity was observed, with significant sustained effects upon imaging vascular parameters.

Cross-visit tumor sub-segmentation and registration with outlier rejection for dynamic contrast-enhanced MRI time series data.

Clinical trials of anti-angiogenic and vascular-disrupting agents often use biomarkers derived from DCE-MRI, typically reporting whole-tumor summary statistics and so overlooking spatial parameter variations caused by tissue heterogeneity. We present a data-driven segmentation method comprising tracer-kinetic model-driven registration for motion correction, conversion from MR signal intensity to contrast agent concentration for cross-visit normalization, iterative principal components analysis for imputation of missing data and dimensionality reduction, and statistical outlier detection using the minimum covariance determinant to obtain a robust Mahalanobis distance. After applying these techniques we cluster in the principal components space using k-means. We present results from a clinical trial of a VEGF inhibitor, using time-series data selected because of problems due to motion and outlier time series. We obtained spatially-contiguous clusters that map to regions with distinct microvascular characteristics. This methodology has the potential to uncover localized effects in trials using DCE-MRI-based biomarkers.

Multiple-bolus dynamic contrast-enhanced MRI in the pancreas during a glucose challenge.

PURPOSE: To assess the feasibility of multiple-bolus dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) in the pancreas; to optimize the analysis; and to investigate application of the method to a glucose challenge in type 2 diabetes. MATERIALS AND METHODS: A 4-bolus DCE-MRI protocol was performed on five patients with type 2 diabetes and 11 healthy volunteers during free-breathing. Motion during the dynamic time series was corrected for using a model-driven nonlinear registration. A glucose challenge was administered intravenously between the first and second DCE-MRI acquisition in all patients and in seven of the healthy controls. RESULTS: Image registration improved the reproducibility of the DCE-MRI model parameters across the repeated bolus-acquisitions in the healthy controls with no glucose challenge (eg, coefficient of variation for K(trans) improved from 38% to 28%). Native tissue T(1) was significantly lower in patients (374 +/- 68 msec) compared with volunteers (519 +/- 41 msec) but there was no significant difference in any of the baseline DCE-MRI parameters. No effect of glucose challenge was observed in either the patients or healthy volunteers. CONCLUSION: Multiple bolus DCE-MRI is feasible in the pancreas and is improved by nonlinear image registration but is not sensitive to the effects of an intravenous glucose challenge.

Identification of early predictive imaging biomarkers and their relationship to serological angiogenic markers in patients with ovarian cancer with residual disease following cytotoxic therapy.

BACKGROUND: Patients with recurrent ovarian cancer often achieve partial response following chemotherapy, resulting in persistent small volume disease. After completion of treatment, the dilemma of when to initiate subsequent chemotherapy arises. Identification of biomarkers that could be used to predict when subsequent treatment is needed would be of significant benefit. DESIGN: Twenty-three patients with advanced ovarian cancer and residual asymptomatic disease following chemotherapy underwent dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) at study entry, 4, 8, 12, 18 and 26 weeks or disease progression. A subgroup of patients provided plasma samples within which a panel of angiogenic biomarkers was quantified. RESULTS: By 4 weeks, significant differences in whole tumour volume, enhancing fraction and Ca125 were observed between patients whose disease progressed by 26 weeks and those who remained stable. Significant correlations between plasma soluble vascular endothelial growth factor receptor-1 (sVEGFR-1) and sVEGFR-2 concentrations, and blood volume and tumour endothelial permeability surface area product measured by DCE-MRI were observed. CONCLUSIONS: Imaging markers have a potential role in early prediction of disease progression in patients with residual ovarian cancer and may supplement current measures of progression. The correlation of DCE-MRI and serological biomarkers suggests that tumour angiogenesis affects these markers through common biological means and warrants further investigation.

The inferior, anterior temporal lobes and semantic memory clarified: novel evidence from distortion-corrected fMRI.

The neural basis of semantic memory generates considerable debate. Semantic dementia results from bilateral anterior temporal lobe (ATL) atrophy and gives rise to a highly specific impairment of semantic memory, suggesting that this region is a critical neural substrate for semantic processing. Recent rTMS experiments with neurologically-intact participants also indicate that the ATL are a necessary substrate for semantic memory. Exactly which regions within the ATL are important for semantic memory are difficult to detect from these methods (because the damage in SD covers a large part of the ATL). Functional neuroimaging might provide important clues about which specific areas exhibit activation that correlates with normal semantic performance. Neuroimaging studies, however, have not consistently found anterior temporal lobe activation in semantic tasks. A recent meta-analysis indicates that this inconsistency may be due to a collection of technical limitations associated with previous studies, including a reduced field-of-view and magnetic susceptibility artefacts associated with standard gradient echo fMRI. We conducted an fMRI study of semantic memory using a combination of techniques which improve sensitivity to ATL activations whilst preserving whole-brain coverage. As expected from SD patients and ATL rTMS experiments, this method revealed bilateral temporal activation extending from the inferior temporal lobe along the fusiform gyrus to the anterior temporal regions, bilaterally. We suggest that the inferior, anterior temporal lobe region makes a crucial contribution to semantic cognition and utilising this version of fMRI will enable further research on the semantic role of the ATL.

Enhancing fraction in glioma and its relationship to the tumoral vascular microenvironment: A dynamic contrast-enhanced MR imaging study.

BACKGROUND AND PURPOSE: EnF is a newly described measure of proportional tumor enhancement derived from DCE-MR imaging. The aim of this study was to assess the relationship between EnF and the more established DCE-MR imaging parameters: K(trans), v(e), and v(p). MATERIALS AND METHODS: Forty-two patients with 43 gliomas (16 grade II, 3 grade III, and 24 grade IV) were studied. Imaging included pre- and postcontrast T1-weighted sequences through the lesion and T1-weighted DCE-MR imaging. Parametric maps of EnF, K(trans), v(e), and v(p) were generated. Voxels were classified as enhancing if the IAUC was positive (EnF(IAUC)(60>0)). A threshold of IAUC > 2.5 mmol.s was used to generate EnF(IAUC)(60>2.5). Both measures of EnF were compared with the DCE-MR imaging parameters (K(trans), v(e), and v(p)). RESULTS: In grade II gliomas, EnF(IAUC60>0) and EnF(IAUC60>2.5) correlated with v(p) (R(2) = 0.6245, P < .0005; and R(2) = 0.4727, P = .003) but not with K(trans) or v(e). In grade IV tumors, both EnF(IAUC60>0) and EnF(IAUC60>2.5) correlated with K(trans) (R(2) = 0.3501, P = .001; and R(2) = 0.4699, P < .0005) and v(p) (R(2) = 0.1564, P = .01; and R(2) = 0.2429, P = .007), but not with v(e). Multiple regression analysis showed K(trans) as the only independent correlate of both EnF(IAUC60>0) and EnF(IAUC60>2.5) for grade IV tumors. CONCLUSIONS: This study suggests that in grade II tumors, EnF reflects v(p) and varies due to changes in vascular density. In grade IV gliomas, EnF is affected by K(trans) with secondary associated changes in v(p).

Candidate biomarkers of extravascular extracellular space: a direct comparison of apparent diffusion coefficient and dynamic contrast-enhanced MR imaging--derived measurement of the volume of the extravascular extracellular space in glioblastoma multiforme.

BACKGROUND AND PURPOSE: ADC measurements have been shown to have an inverse relationship with tumor cell density. DCE-MR imaging modeling techniques can produce a measurement of the v(e), which would also be expected to have an inverse relationship with cell density. The objective of this study was to test the hypothesis that areas of increased cellularity, and therefore low ADC, would be expected to have a small EES (low v(e)). MATERIALS AND METHODS: Nineteen patients with GBM were recruited. All imaging was performed before surgery on a 3T MR imaging scanner. Imaging included diffusion tensor imaging, T1-weighted DCE-MR imaging, and anatomic sequences. Tumor VOIs were defined on the anatomic images and modified to contain only enhancing voxels. Parametric maps of ADC and v(e) were generated. Statistical analysis of ADC and v(e) was performed on both a voxel-by-voxel basis and comparison of median values. RESULTS: No correlation was demonstrated between ADC and v(e) in either a voxel-by-voxel analysis or comparison of median values (P = .124). CONCLUSIONS: This study failed to demonstrate a correlation between ADC and v(e). This is important because it suggests that though the mechanisms underlying these parameters are theoretically similar, they actually reflect different aspects of tumor microenvironment. Consequently ADC and v(e) should be considered to provide independent information about the properties of the EES.

Defining Meyer's loop-temporal lobe resections, visual field deficits and diffusion tensor tractography.

Anterior temporal lobe resection is often complicated by superior quadrantic visual field deficits (VFDs). In some cases this can be severe enough to prohibit driving, even if a patient is free of seizures. These deficits are caused by damage to Meyer's loop of the optic radiation, which shows considerable heterogeneity in its anterior extent. This structure cannot be distinguished using clinical magnetic resonance imaging sequences. Diffusion tensor tractography is an advanced magnetic resonance imaging technique that enables the parcellation of white matter. Using seed voxels antero-lateral to the lateral geniculate nucleus, we applied this technique to 20 control subjects, and 21 postoperative patients. All patients had visual fields assessed with Goldmann perimetry at least three months after surgery. We measured the distance from the tip of Meyer's loop to the temporal pole and horn in all subjects. In addition, we measured the size of temporal lobe resection using postoperative T(1)-weighted images, and quantified VFDs. Nine patients suffered VFDs ranging from 22% to 87% of the contralateral superior quadrant. In patients, the range of distance from the tip of Meyer's loop to the temporal pole was 24-43 mm (mean 34 mm), and the range of distance from the tip of Meyer's loop to the temporal horn was -15 to +9 mm (mean 0 mm). In controls the range of distance from the tip of Meyer's loop to the temporal pole was 24-47 mm (mean 35 mm), and the range of distance from the tip of Meyer's loop to the temporal horn was -11 to +9 mm (mean 0 mm). Both quantitative and qualitative results were in accord with recent dissections of cadaveric brains, and analysis of postoperative VFDs and resection volumes. By applying a linear regression analysis we showed that both distance from the tip of Meyer's loop to the temporal pole and the size of resection were significant predictors of the postoperative VFDs. We conclude that there is considerable variation in the anterior extent of Meyer's loop. In view of this, diffusion tensor tractography of the optic radiation is a potentially useful method to assess an individual patient's risk of postoperative VFDs following anterior temporal lobe resection.