Diffusion tensor imaging in primary brain tumors: reproducible quantitative analysis of corpus callosum infiltration and contralateral involvement using a probabilistic mixture model

Diffusion tensor imaging in detecting gliomas sub-regions of infiltration, local and remote recurrences: a systematic review

Given that glioma cells tend to infiltrate and migrate along WM tracts, leading to demyelination and axonal injuries, Diffusion Tensor Imaging (DTI) emerged as a promising tool for identifying major "high-risk areas" of recurrence within the peritumoral brain zone (PBZ) or at a distance throughout the adjacents white matter tracts. Of our systematic review is to answer the following research question: In patients with brain tumor, is DTI able to recognizes within the peri-tumoral brain zone (PBZ) areas more prone to local (near the surgical cavity) or remote recurrence compared to the conventional imaging techniques?. We conducted a comprehensive literature search to identify relevant studies in line with the PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) guidelines. 15 papers were deemed compatible with our research question and included. To enhance the paper's readability, we have categorized our findings into two distinct groups: the first delves into the role of DTI in detecting PBZ sub-regions of infiltration and local recurrences (n = 8), while the second group explores the feasibility of DTI in detecting white matter tract infiltration and remote recurrences (n = 7). DTI values and, within a broader framework, radiomics investigations can provide precise, voxel-by-voxel insights into the state of PBZ and recurrences. Better defining the regions at risk for potential recurrence within the PBZ and along WM bundles will allow targeted therapy.

Changes in Brain Energy and Membrane Metabolism in Glioblastoma following Chemoradiation

Brain parenchyma infiltration with glioblastoma (GB) cannot be entirely visualized by conventional magnetic resonance imaging (MRI). The aim of this study was to investigate changes in the energy and membrane metabolism measured with phosphorous MR spectroscopy (31P-MRS) in the presumably “normal-appearing” brain following chemoradiation therapy (CRT) in GB patients in comparison to healthy controls. Twenty (seven female, thirteen male) GB patients underwent a 31P-MRS scan prior to surgery (baseline) and after three months of standard CRT (follow-up examination. The regions of interest “contrast-enhancing (CE) tumor” (if present), “adjacent to the (former) tumor”, “ipsilateral distant” hemisphere, and “contralateral” hemisphere were compared, differentiating between patients with stable (SD) and progressive disease (PD). Metabolite ratios PCr/ATP, Pi/ATP, PCr/Pi, PME/PDE, PME/PCr, and PDE/ATP were investigated. In PD, energy and membrane metabolism in CE tumor areas have a tendency to “normalize” under therapy. In different “normal-appearing” brain areas of GB patients, the energy and membrane metabolism either “normalized” or were “disturbed”, in comparison to baseline or controls. Differences were also detected between patients with SD and PD. 31P-MRS might contribute as an additional imaging biomarker for outcome measurement, which remains to be investigated in a larger cohort.

Design of a high-performance non-linear gradient coil for diffusion weighted MRI of the breast

Diffusion-weighted imaging (DWI) in the female breast is a magnetic resonance imaging (MRI) technique that complements clinical routine protocols, and that might provide an independent diagnostic value for specific clinical tasks in breast imaging. To further improve specificity of DWI in the breast, stronger and faster diffusion weighting is advantageous. Here, a dedicated gradient coil is designed, targeted at diffusion weighting in the female breast, with the peak gradient magnitude exceeding that of the current clinical MR scanners by an order of a magnitude. Design of application-tailored gradient coils in MRI has recently attracted increased attention. With the target application in mind, the gradient coil is designed on an irregularly shaped semi-open current-carrying surface. Due to the coil former closely fitting the non-spherical target region, non-linear encoding fields become particularly advantageous for achieving locally exceptionally high gradient strengths. As breast tissue has a predominantly isotropic cellular microstructure, the direction of the diffusion-weighting gradient may be allowed to vary within the target volume. However, due to the quadratic dependency of the b-factor on the gradient strength, variation of the gradient magnitude should be carefully controlled. To achieve the above design goals the corresponding multi-objective optimization problem is reformulated as a constrained optimization, allowing for flexible and precise control of the coil properties. A novel constraint is proposed, limiting gradient magnitude variation within every slice while allowing for variations in both the direction of the gradient within the slice and the magnitude across the slices. These innovations enable the design of a unilateral coil for diffusion weighting in the female breast with local gradient strengths exceeding 1 T/m with highly homogeneous diffusion weighting for imaging in the coronal slice orientation.

Prediction of Lower Grade Insular Glioma Molecular Pathology Using Diffusion Tensor Imaging Metric-Based Histogram Parameters

Objectives

To explore whether a simplified lesion delineation method and a set of diffusion tensor imaging (DTI) metric-based histogram parameters (mean, 25th percentile, 75th percentile, skewness, and kurtosis) are efficient at predicting the molecular pathology status (MGMT methylation, IDH mutation, TERT promoter mutation, and 1p19q codeletion) of lower grade insular gliomas (grades II and III).

Methods

40 lower grade insular glioma patients in two medical centers underwent preoperative DTI scanning. For each patient, the entire abnormal area in their b-non (b0) image was defined as region of interest (ROI), and a set of histogram parameters were calculated for two DTI metrics, fractional anisotropy (FA) and mean diffusivity (MD). Then, we compared how these DTI metrics varied according to molecular pathology and glioma grade, with their predictive performance individually and jointly assessed using receiver operating characteristic curves. The reliability of the combined prediction was evaluated by the calibration curve and Hosmer and Lemeshow test.

Results

The mean, 25th percentile, and 75th percentile of FA were associated with glioma grade, while the mean, 25th percentile, 75th percentile, and skewness of both FA and MD predicted IDH mutation. The mean, 25th percentile, and 75th percentile of FA, and all MD histogram parameters significantly distinguished TERT promoter status. Similarly, all MD histogram parameters were associated with 1p19q status. However, none of the parameters analyzed for either metric successfully predicted MGMT methylation. The 25th percentile of FA yielded the highest prediction efficiency for glioma grade, IDH mutation, and TERT promoter mutation, while the 75th percentile of MD gave the best prediction of 1p19q codeletion. The combined prediction could enhance the discrimination of grading, IDH and TERT mutation, and also with a good fitness.

Conclusions

Overall, more invasive gliomas showed higher FA and lower MD values. The simplified ROI delineation method presented here based on the combination of appropriate histogram parameters yielded a more practical and efficient approach to predicting molecular pathology in lower grade insular gliomas. This approach could help clinicians to determine the extent of tumor resection required and reduce complications, enabling more precise treatment of insular gliomas in combination with radiotherapy and chemotherapy.

Diffusion Tensor Imaging Color-Coded Maps: An Alternative to Tractography

INTRODUCTION

White matter tracts can be observed using tractograms generated from diffusion tensor imaging (DTI). However, the dependence of these white matter tract images on subjective variables, including how seed points are placed and the preferred level of fractional anisotropy, introduces interobserver inconsistency and potential lack of reliability. We propose that color-coded maps (CCM) generated from DTI can be a preferred method for the visualization of important white matter tracts, circumventing bias in preoperative brain tumor resection planning.

METHODS

DTI was acquired retrospectively in 25 patients with brain tumors. Lesions included 15 tumors of glial origin, 9 metastatic tumors, 2 meningiomas, and 1 cavernous angioma. Tractograms of the pyramidal tract and/or optic radiations, based on tumor location, were created by marking seed regions of interest using known anatomical locations. We compared the degree of tract involvement and white matter alteration between CCMs and tractograms. Neurological outcomes were obtained from chart reviews.

RESULTS

The pyramidal tract was evaluated in 20/25 patients, the visual tracts were evaluated in 10/25, and both tracts were evaluated in 5/25. In 19/25 studies, the same patterns of white matter alternations were found between the CCMs and tractograms. In the 6 patients where patterns differed, 2 tractograms were not useful in determining pattern alteration; in the remaining 4/6, no practical difference was seen in comparing the studies. Two patients were lost to follow-up. Thirteen patients were neurologically improved or remained intact after intervention. In these, 10 of the 13 patients showed tumor-induced white matter tract displacement on CCM. Twelve patients had no improvement of their preoperative deficit. In 9 of these 12 patients, CCM showed white matter disruption.

CONCLUSION

CCMs provide a convenient, practical, and objective method of visualizing white matter tracts, obviating the need for potentially subjective and time-consuming tractography. CCMs are at least as reliable as tractograms in predicting neurological outcomes after neurosurgical intervention.

Manganese-Enhanced MRI in Patients with Multiple Sclerosis

BACKGROUND AND PURPOSE

Cellular uptake of the manganese ion, when administered as a contrast agent for MR imaging, can noninvasively highlight cellular activity and disease processes in both animals and humans. The purpose of this study was to explore the enhancement profile of manganese in patients with multiple sclerosis.

MATERIALS AND METHODS

Mangafodipir is a manganese chelate that was clinically approved for MR imaging of liver lesions. We present a case series of 6 adults with multiple sclerosis who were scanned at baseline with gadolinium, then injected with mangafodipir, and followed at variable time points thereafter.

RESULTS

Fourteen new lesions formed during or shortly before the study, of which 10 demonstrated manganese enhancement of varying intensity, timing, and spatial pattern. One gadolinium-enhancing extra-axial mass, presumably a meningioma, also demonstrated enhancement with manganese. Most interesting, manganese enhancement was detected in lesions that formed in the days after mangafodipir injection, and this enhancement persisted for several weeks, consistent with contrast coming from intracellular uptake of manganese. Some lesions demonstrated a diffuse pattern of manganese enhancement in an area larger than that of both gadolinium enhancement and T2-FLAIR signal abnormality.

CONCLUSIONS

This work demonstrates the first use of a manganese-based contrast agent to enhance MS lesions on MR imaging. Multiple sclerosis lesions were enhanced with a temporal and spatial profile distinct from that of gadolinium. Further experiments are necessary to uncover the mechanism of manganese contrast enhancement as well as cell-specific uptake.

On PTV definition for glioblastoma based on fiber tracking of diffusion tensor imaging data

Radiotherapy (RT) is commonly applied for the treatment of glioblastoma multiforme (GBM). Following the planning target volume (PTV) definition procedure standardized in guidelines, a 20% risk of missing non-local recurrences is present. Purpose of this study was to evaluate whether diffusion tensor imaging (DTI)-based fiber tracking may be beneficial for PTV definition taking into account the prediction of distant recurrences. 56 GBM patients were examined with magnetic resonance imaging (MRI) including DTI performed before RT after resection of the primary tumor. Follow-up MRIs were acquired in three month intervals. For the seven patients with a distant recurrence, fiber tracking was performed with three algorithms and it was evaluated whether connections existed from the primary tumor region to the distant recurrence. It depended strongly on the used tracking algorithm and the used tracking parameters whether a connection was observed. Most of the connections were weak and thus not usable for PTV definition. Only in one of the seven patients with a recurring tumor, a clear connection was present. It seems unlikely that DTI-based fiber tracking can be beneficial for predicting distant recurrences in the planning of PTVs for glioblastoma multiforme.

Early postoperative delineation of residual tumor after low-grade glioma resection by probabilistic quantification of diffusion-weighted imaging

OBJECTIVE

In WHO grade II low-grade gliomas (LGGs), early postoperative MRI (epMRI) may overestimate residual tumor on FLAIR sequences. Consequently, MRI at 3-6 months follow-up (fuMRI) is used for delineation of residual tumor. This study sought to evaluate if integration of apparent diffusion coefficient (ADC) maps permits an accurate estimation of residual tumor early on epMRI.

METHODS

From a consecutive cohort, 43 cases with an initial surgery for an LGG, and complete epMRI (< 72 hours after resection) and fuMRI including ADC maps, were retrospectively identified. Residual FLAIR hyperintense tumor was manually segmented on epMRI and corresponding ADC maps were coregistered. Using an expectation maximization algorithm, residual tumor segments were probabilistically clustered into areas of residual tumor, ischemia, or normal white matter (NWM) by fitting a mixture model of superimposed Gaussian curves to the ADC histogram. Tumor volumes from epMRI, clustering, and fuMRI were statistically compared and agreement analysis was performed.

RESULTS

Mean FLAIR hyperintensity suggesting residual tumor was significantly larger on epMRI compared to fuMRI (19.4 ± 16.5 ml vs 8.4 ± 10.2 ml, p < 0.0001). Probabilistic clustering of corresponding ADC histograms on epMRI identified subsegments that were interpreted as mean residual tumor (7.6 ± 10.2 ml), ischemia (8.1 ± 5.9 ml), and NWM (3.7 ± 4.9 ml). Therefore, mean tumor quantification error between epMRI and fuMRI was significantly reduced (11.0 ± 10.6 ml vs -0.8 ± 3.7 ml, p < 0.0001). Mean clustered tumor volumes on epMRI were no longer significantly different from the fuMRI reference (7.6 ± 10.2 ml vs 8.4 ± 10.2 ml, p = 0.16). Correlation (Pearson r = 0.96, p < 0.0001), concordance correlation coefficient (0.89, 95% confidence interval 0.83), and Bland-Altman analysis suggested strong agreement between both measures after clustering.

CONCLUSIONS

Probabilistic segmentation of ADC maps facilitates accurate assessment of residual tumor within 72 hours after LGG resection. Multiparametric image analysis detected FLAIR signal alterations attributable to surgical trauma, which led to overestimation of residual LGG on epMRI compared to fuMRI. The prognostic value and clinical impact of this method has to be evaluated in larger case series in the future.

Emerging Applications of Artificial Intelligence in Neuro-Oncology

Due to the exponential growth of computational algorithms, artificial intelligence (AI) methods are poised to improve the precision of diagnostic and therapeutic methods in medicine. The field of radiomics in neuro-oncology has been and will likely continue to be at the forefront of this revolution. A variety of AI methods applied to conventional and advanced neuro-oncology MRI data can already delineate infiltrating margins of diffuse gliomas, differentiate pseudoprogression from true progression, and predict recurrence and survival better than methods used in daily clinical practice. Radiogenomics will also advance our understanding of cancer biology, allowing noninvasive sampling of the molecular environment with high spatial resolution and providing a systems-level understanding of underlying heterogeneous cellular and molecular processes. By providing in vivo markers of spatial and molecular heterogeneity, these AI-based radiomic and radiogenomic tools have the potential to stratify patients into more precise initial diagnostic and therapeutic pathways and enable better dynamic treatment monitoring in this era of personalized medicine. Although substantial challenges remain, radiologic practice is set to change considerably as AI technology is further developed and validated for clinical use.

Detection of occult neoplastic infiltration in the corpus callosum and prediction of overall survival in patients with glioblastoma using diffusion tensor imaging

OBJECTIVE

Corpus callosum (CC) involvement is a poor prognostic factor in patients with glioblastoma (GBM). The purpose of this study was to determine whether diffusion tensor imaging (DTI) can quantify occult tumor infiltration in the CC and predict the overall survival in GBM patients.

METHODS

Forty-eight patients with pathologically proven GBM and 17 normal subjects were included in this retrospective study. Patients were divided into four groups based on CC invasion and overall survival: long survivors without CC invasion; short survivors without CC invasion; long survivors with CC invasion; short survivors with CC invasion. All patients underwent DTI at 3T MRI scanner. Fractional anisotropy (FA) and mean diffusivity (MD) values were measured from genu, mid-body, and splenium of the CC. The mean values of these parameters were compared between different groups and Kaplan Meier curves were used for prediction of overall survival.

RESULTS

Patients with short survival and CC invasion had the lowest FA values (0.64 ± 0.05) from the CC compared with other groups (p < 0.05). Receiver operator characteristic curve (ROC) analysis indicated that a FA cutoff value of 0.70 was the best predictor for overall survival with an area under the curve (AUC) of 0.77, sensitivity 1, specificity 0.59. Kaplan-Meier survival curves demonstrated that the mean survival time was significantly longer for patients with high FA (>0.70) compared with those with low FA (<0.70) (p < 0.001).

CONCLUSIONS

FA values from the CC can quantify occult tumor infiltration and serve as a sensitive prognostic marker for prediction of overall survival in GBM patients.

MITK Diffusion Imaging

Background: Diffusion-MRI provides a unique window on brain anatomy and insights into aspects of tissue structure in living humans that could not be studied previously. There is a major effort in this rapidly evolving field of research to develop the algorithmic tools necessary to cope with the complexity of the datasets.

Objectives: This work illustrates our strategy that encompasses the development of a modularized and open software tool for data processing, visualization and interactive exploration in diffusion imaging research and aims at reinforcing sustainable evaluation and progress in the field.

Methods: In this paper, the usability and capabilities of a new application and toolkit component of the Medical Imaging and Interaction Toolkit (MITK, www.mitk.org), MITKDI, are demonstrated using in-vivo datasets.

Results: MITK-DI provides a comprehensive software framework for high-performance data processing, analysis and interactive data exploration, which is designed in a modular, extensible fashion (using CTK) and in adherence to widely accepted coding standards (e.g. ITK, VTK). MITK-DI is available both as an open source software development toolkit and as a ready-to-use in stallable application.

Conclusions: The open source release of the modular MITK-DI tools will increase verifiability and comparability within the research community and will also be an important step towards bringing many of the current techniques towards clinical application.

Cancer Metabolism and Tumor Heterogeneity: Imaging Perspectives Using MR Imaging and Spectroscopy

Cancer cells reprogram their metabolism to maintain viability via genetic mutations and epigenetic alterations, expressing overall dynamic heterogeneity. The complex relaxation mechanisms of nuclear spins provide unique and convertible tissue contrasts, making magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) pertinent imaging tools in both clinics and research. In this review, we summarized MR methods that visualize tumor characteristics and its metabolic phenotypes on an anatomical, microvascular, microstructural, microenvironmental, and metabolomics scale. The review will progress from the utilities of basic spin-relaxation contrasts in cancer imaging to more advanced imaging methods that measure tumor-distinctive parameters such as perfusion, water diffusion, magnetic susceptibility, oxygenation, acidosis, redox state, and cell death. Analytical methods to assess tumor heterogeneity are also reviewed in brief. Although the clinical utility of tumor heterogeneity from imaging is debatable, the quantification of tumor heterogeneity using functional and metabolic MR images with development of robust analytical methods and improved MR methods may offer more critical roles of tumor heterogeneity data in clinics. MRI/MRS can also provide insightful information on pharmacometabolomics, biomarker discovery, disease diagnosis and prognosis, and treatment response. With these future directions in mind, we anticipate the widespread utilization of these MR-based techniques in studying in vivo cancer biology to better address significant clinical needs.

Early Detection of Malignant Transformation in Resected WHO II Low-Grade Glioma Using Diffusion Tensor-Derived Quantitative Measures

OBJECTIVE

Here, we retrospectively investigate the value of voxel-wisely plotted diffusion tensor-derived (DTI) axial, radial and mean diffusivity for the early detection of malignant transformation (MT) in WHO II glioma compared to contrast-enhanced images.

MATERIALS AND METHODS

Forty-seven patients underwent brain magnetic resonance imaging follow-up between 2006-2014 after gross-tumor resection of intra-axial WHO II glioma. Axial/Mean/Radial diffusivity maps (AD/MD/RD) were generated from DTI data. ADmin/MDmin/RDmin values were quantified within tumor regions-of-interest generated by two independent readers including tumor contrast-to-noise (CNR). Sensitivity/specificity and area-under-the-curve (AUC) were calculated using receiver-operating-characteristic analysis. Inter-reader agreement was assessed (Cohen's kappa).

RESULTS

Eighteen patients demonstrated malignant transformation (MT) confirmed in 8/18 by histopathology and in 10/18 through imaging follow-up. Twelve of 18 patients (66.6%) with MT showed diffusion restriction timely coincidental with contrast-enhancement (CE). In the remaining six patients (33.3%), the diffusion restriction preceded the CE. The mean gain in detection time using DTI was (0.8±0.5 years, p = 0.028). Compared to MDmin and RDmin, ROC-analysis showed best diagnostic value for ADmin (sensitivity/specificity 94.94%/89.7%, AUC 0.96; p<0.0001) to detect MT. CNR was highest for AD (1.83±0.14), compared to MD (1.31±0.19; p<0.003) and RD (0.90±0.23; p<0.0001). Cohen's Kappa was 0.77 for ADmin, 0.71 for MDmin and 0.65 for RDmin (p<0.0001, respectively).

CONCLUSION

MT is detectable at the same time point or earlier compared to T1w-CE by diffusion restriction in diffusion-tensor-derived maps. AD demonstrated highest sensitivity/specificity/tumor-contrast compared to radial or mean diffusivity (= apparent diffusion coefficient) to detect MT.

Diffusion and perfusion weighted magnetic resonance imaging for tumor volume definition in radiotherapy of brain tumors

Accurate target volume delineation is crucial for the radiotherapy of tumors. Diffusion and perfusion magnetic resonance imaging (MRI) can provide functional information about brain tumors, and they are able to detect tumor volume and physiological changes beyond the lesions shown on conventional MRI. This review examines recent studies that utilized diffusion and perfusion MRI for tumor volume definition in radiotherapy of brain tumors, and it presents the opportunities and challenges in the integration of multimodal functional MRI into clinical practice. The results indicate that specialized and robust post-processing algorithms and tools are needed for the precise alignment of targets on the images, and comprehensive validations with more clinical data are important for the improvement of the correlation between histopathologic results and MRI parameter images.

Innovative anisotropic phantoms for calibration of diffusion tensor imaging sequences

The paper describes a novel type of anisotropic phantoms designed for b-matrix spatial distribution diffusion tensor imaging (BSD-DTI). Cubic plate anisotropic phantom, cylinder capillary phantom and water reference phantom are described as a complete set necessary for calibration, validation and normalization of BSD-DTI. An innovative design of the phantoms basing on enclosing the anisotropic cores in glass balls filled with liquid made for the first time possible BSD calibration with usage of echo planar imaging (EPI) sequence. Susceptibility artifacts prone to occur in EPI sequences were visibly reduced in the central region of the phantoms. The phantoms were designed for usage in a clinical scanner's head coil, but can be scaled for other coil or scanner types. The phantoms can be also used for a pre-calibration of imaging of other types of phantoms having more specific applications.

Sparse Reconstruction Challenge for diffusion MRI: Validation on a physical phantom to determine which acquisition scheme and analysis method to use?

Diffusion magnetic resonance imaging (dMRI) is the modality of choice for investigating in-vivo white matter connectivity and neural tissue architecture of the brain. The diffusion-weighted signal in dMRI reflects the diffusivity of water molecules in brain tissue and can be utilized to produce image-based biomarkers for clinical research. Due to the constraints on scanning time, a limited number of measurements can be acquired within a clinically feasible scan time. In order to reconstruct the dMRI signal from a discrete set of measurements, a large number of algorithms have been proposed in recent years in conjunction with varying sampling schemes, i.e., with varying b-values and gradient directions. Thus, it is imperative to compare the performance of these reconstruction methods on a single data set to provide appropriate guidelines to neuroscientists on making an informed decision while designing their acquisition protocols. For this purpose, the SPArse Reconstruction Challenge (SPARC) was held along with the workshop on Computational Diffusion MRI (at MICCAI 2014) to validate the performance of multiple reconstruction methods using data acquired from a physical phantom. A total of 16 reconstruction algorithms (9 teams) participated in this community challenge. The goal was to reconstruct single b-value and/or multiple b-value data from a sparse set of measurements. In particular, the aim was to determine an appropriate acquisition protocol (in terms of the number of measurements, b-values) and the analysis method to use for a neuroimaging study. The challenge did not delve on the accuracy of these methods in estimating model specific measures such as fractional anisotropy (FA) or mean diffusivity, but on the accuracy of these methods to fit the data. This paper presents several quantitative results pertaining to each reconstruction algorithm. The conclusions in this paper provide a valuable guideline for choosing a suitable algorithm and the corresponding data-sampling scheme for clinical neuroscience applications.

State-of-the-art MRI techniques in neuroradiology: principles, pitfalls, and clinical applications

This article reviews the most relevant state-of-the-art magnetic resonance (MR) techniques, which are clinically available to investigate brain diseases. MR acquisition techniques addressed include notably diffusion imaging (diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), and diffusion kurtosis imaging (DKI)) as well as perfusion imaging (dynamic susceptibility contrast (DSC), arterial spin labeling (ASL), and dynamic contrast enhanced (DCE)). The underlying models used to process these images are described, as well as the theoretic underpinnings of quantitative diffusion and perfusion MR imaging-based methods. The technical requirements and how they may help to understand, classify, or follow-up neurological pathologies are briefly summarized. Techniques, principles, advantages but also intrinsic limitations, typical artifacts, and alternative solutions developed to overcome them are discussed. In this article, we also review routinely available three-dimensional (3D) techniques in neuro MRI, including state-of-the-art and emerging angiography sequences, and briefly introduce more recently proposed 3D quantitative neuro-anatomy sequences, and new technology, such as multi-slice and multi-transmit imaging.

Use of diffusion tensor imaging in glioma resection

Diffusion tensor imaging (DTI) is increasingly used in the resection of both high- and low-grade gliomas. Whereas conventional MRI techniques provide only anatomical information, DTI offers data on CNS connectivity by enabling visualization of important white matter tracts in the brain. Importantly, DTI allows neurosurgeons to better guide their surgical approach and resection. Here, the authors review basic scientific principles of DTI, include a primer on the technology and image acquisition, and outline the modality's evolution as a frequently used tool for glioma resection. Current literature supporting its use is summarized, highlighting important clinical studies on the application of DTI in preoperative planning for glioma resection, preoperative diagnosis, and postoperative outcomes. The authors conclude with a review of future directions for this technology.

Definition of K(trans) and FA thresholds for better assessment of experimental glioma using high-field MRI: a feasibility study

PURPOSE

To define K(trans) and fractional anisotropy (FA) thresholds in correlation to histology for improved magnetic resonance imaging (MRI) tumor assessment in an animal model of brain glioma.

METHODS

Twelve rats underwent 4.7 T MRI at day 10 after tumor implantation. Anatomical scans (T2, T1 at 8 min after double dose contrast application) as well as dynamic contrast-enhanced (DCE) imaging with calculation of K(trans) and diffusion tensor imaging (DTI) with calculation of FA were performed. T2- and T1-derived tumor volumes were calculated and thresholds for K(trans) and FA were defined for best MRI tumor assessment correlated to histology.

RESULTS

Tumor volumes were 159 ± 14 mm(3) (histology), 126 ± 26 mm(3) (T1 with contrast, r=0.76), and 153 ± 12 mm(3) (T2, r=0.84), respectively. K(trans)- and FA-derived tumor volumes were 160 ± 16 mm(3) (for K(trans ≥ 0.04 min(-1), r=0.94), and 159 ± 14 mm(3) (for FA £0.14, r=0.96), respectively.

CONCLUSIONS

DCE-MRI and DTI with calculation of K(trans) and FA maps allow very precise brain glioma assessment comparable to histology if established thresholds for the given tumor model are used.

The Corpus Callosum Wallerian Degeneration in the Unilateral Brain Tumors: Evaluation with Diffusion Tensor Imaging (DTI)

PURPOSE

The purpose of this study was to evaluate whether DTI could demonstrate the water diffusivity changes in the corpus callosum (CC), which were not visible on the morphologic imaging in patients with glioblastoma multiforme (GBM) and brain metastases with no midline CC infiltration.

MATERIALS AND METHODS

Twenty-seven patients with treatment naïve unilateral GBM and eleven patients with a solitary brain metastasis with no midline CC infiltration underwent DTI. Ten controls with normal brain MRI were also included. Based on the tensors, the principal diffusion directions, the anisotropy values, and the prior information about the diffusivity pattern in CC, a similarity measure was proposed. Subsequently, the CC was automatically divided into the Witelson subdivisions.

RESULTS

We observed significantly decreased fractional anisotropy values in all the regions of CC in the patients with GBM and metastases as compared to those in the controls. The mean diffusivity values showed a significant increase in all the regions of CC, except the splenium in patients with GBM and the isthmus in the patients with metastases, as compared to that in the controls respectively.

CONCLUSION

In conclusion, DTI is more sensitive than the morphologic MR imaging in the evaluation of changes within the CC, in brain tumours which do not infiltrate the CC. However, these changes of the DTI metrics in the CC are due to a Wallerian degeneration rather than a tumour infiltration, as was shown by our results, as similar changes were seen in the GBM as well as the non-infiltrating metastases patients.

Perspectives of 3 T magnetic resonance imaging in radiosurgical treatment planning

The introduction of 3 T magnetic resonance imaging (MRI) scanners for neuro-oncological diagnostics showed a general improvement of image quality, especially in terms of the detection and differentiation of intracranial tumors. Among the advantages of 3 T scanners compared to 1.5 T scanners are the possibility of higher spatial image resolution or shorter investigation times and the availability of functional imaging in sufficient quality. Consequently, the use of 3 T MRI for radiosurgery planning is highly desired. Functional MRI techniques (perfusion-weighted imaging, dynamic contrast-enhanced MRI, MR spectroscopy, diffusion-weighted imaging, and diffusion tensor imaging) available at 3 T scanners provide not only better detection and differentiation but also significantly better delineation of intracranial tumors, which is a crucial feature for successful radiosurgical treatment planning. The use of multimodal morphological and functional MRI methods allows identification of the biologically most active parts of the tumors with consecutive changes in therapy planning. On the other hand, there are increased geometric distortions on MRI scans obtained at 3 T compared to 1.5 T, which makes their use limited for now. However, the newest studies show an acceptable degree of geometric distortion on the 3 T planning images using special imaging protocols, while additional investigations on this issue are needed to find the optimal technical solution.

NMR-based diffusion pore imaging

Nuclear magnetic resonance (NMR) diffusion experiments offer a unique opportunity to study boundaries restricting the diffusion process. In a recent Letter [Phys. Rev. Lett. 107, 048102 (2011)], we introduced the idea and concept that such diffusion experiments can be interpreted as NMR imaging experiments. Consequently, images of closed pores, in which the spins diffuse, can be acquired. In the work presented here, an in-depth description of the diffusion pore imaging technique is provided. Image artifacts due to gradient profiles of finite duration, field inhomogeneities, and surface relaxation are considered. Gradients of finite duration lead to image blurring and edge enhancement artifacts. Field inhomogeneities have benign effects on diffusion pore images, and surface relaxation can lead to a shrinkage and shift of the pore image. The relation between boundary structure and the imaginary part of the diffusion weighted signal is analyzed, and it is shown that information on pore coherence can be obtained without the need to measure the phase of the diffusion weighted signal. Moreover, it is shown that quite arbitrary gradient profiles can be used for diffusion pore imaging. The matrices required for numerical calculations are stated and provided as supplemental material.

Diffusion-weighted imaging-based probabilistic segmentation of high- and low-proliferative areas in high-grade gliomas

The apparent diffusion coefficient (ADC) derived from diffusion-weighted imaging (DWI) correlates inversely with tumor proliferation rates. High-grade gliomas are typically heterogeneous and the delineation of areas of high and low proliferation is impeded by partial volume effects and blurred borders. Commonly used manual delineation is further impeded by potential overlap with cerebrospinal fluid and necrosis. Here we present an algorithm to reproducibly delineate and probabilistically quantify the ADC in areas of high and low proliferation in heterogeneous gliomas, resulting in a reproducible quantification in regions of tissue inhomogeneity. We used an expectation maximization (EM) clustering algorithm, applied on a Gaussian mixture model, consisting of pure superpositions of Gaussian distributions. Soundness and reproducibility of this approach were evaluated in 10 patients with glioma. High- and low-proliferating areas found using the clustering correspond well with conservative regions of interest drawn using all available imaging data. Systematic placement of model initialization seeds shows good reproducibility of the method. Moreover, we illustrate an automatic initialization approach that completely removes user-induced variability. In conclusion, we present a rapid, reproducible and automatic method to separate and quantify heterogeneous regions in gliomas.

Fronto-temporal disconnectivity and symptom severity in children with autism spectrum disorder

OBJECTIVES

There is increasing evidence that many of the core behavioural impairments in autism spectrum disorders (ASD) emerge from disconnectivity of networks that are important for social communication. The present study aimed at investigating which specific fibre tracts are impaired in ASD and if possible alterations of white matter are associated with clinical symptomatology.

METHODS

Eighteen children with ASD and 18 carefully matched typically developing controls aged 6-12 years were examined using diffusion tensor imaging (DTI) and voxel-based morphometry (VBM). Fractional anisotropy (FA) values were correlated with symptom severity as indexed by the children's scores on the Autisms Diagnostic Observation Schedule (ADOS) and the Autism Diagnostic Interview-Revised (ADI-R).

RESULTS

Decreased FA values were identified for the fornix (FO), the superior longitudinal fasciculus (SLF) the corpus callosum and the uncinate fasciculus (UF) in the ASD group compared to controls, with most prominent differences in the UF bilaterally and the right SLF. FA values of affected fibre tracts were negatively associated with clinical measures of autistic symptomatology. We did not observe significantly altered grey or white matter concentration after correction for multiple comparisons.

CONCLUSION

Our findings support the hypothesis of abnormal white matter microstructure of fronto-temporal cortical networks in ASD, which are associated with core symptoms of the disorder.

White matter alterations in the corpus callosum of adolescents with first-admission schizophrenia

Several diffusion tensor imaging (DTI) studies involving adults and adolescents with schizophrenia have examined fractional anisotropy (FA) in the corpus callosum (CC) with conflicting findings. This may be due to confounding factors such as the chronicity of the disorder, long-term medication with psychotropics or methodological differences. To provide a clearer picture of early alterations, we examined 13 adolescents with first-admission schizophrenia and 13 healthy controls using a region-of-interest approach based on probabilistic voxel classification. We quantified FA in four subdivisions of the CC and hypothesized that adolescents with schizophrenia display a reduced FA in the genu associated with 'hypofrontality' and a reduced FA in the body of the CC linked to the heteromodal association cortex. Fiber integrity measurements revealed significant FA decreases in the genu and body of the CC in adolescents with schizophrenia compared to healthy controls. These findings emphasize the central role of the CC in even the early stages of schizophrenia and lend weight to hypotheses about frontal alterations and the central role of the heteromodal association cortex in the aetiopathogenesis of the disorder.

Diffusion tensor imaging of the anal canal at 3 tesla: feasibility and reproducibility of anisotropy measures

PURPOSE

To assess the feasibility and reproducibility of 3-tesla diffusion tensor imaging (DTI) of the anal canal.

MATERIALS AND METHODS

DTI was performed in 25 men with no clinical history of anal canal disease undergoing MRI for prostate cancer. Analysis of fractional anisotropy (FA), relative anisotropy (RA), and apparent diffusion coefficient (ADC) were determined for the epithelial/subepithelial layer, internal sphincter, external sphincter, and puborectalis. The directionality of diffusion was recorded from color-coded tractography maps. Obturator internus and gluteus maximus served as reference muscles. Mean (SD) of values for FA, RA, and ADC were compared using analysis of variance. Intra and inter-rater agreement and test reproducibility (n = 5) was assessed by Bland-Altman statistics.

RESULTS

Mean (SD) for the epithelial/subepithelial layer, internal, external sphincter, and puborectalis were as follows: FA: 0.283 (0.099); 0.337 (0.049); 0.415 (0.072); and 0.407 (0.062), respectively. RA: 0.241 (0.094); 0.292 (0.050); 0.371 (0.083); 0.361 (0.067), respectively; and ADC: 1.49 (0.23); 1.59 (0.19); 1.51 (0.28); and 1.54 (0.29) × 10(-3) mm(2) /s, respectively. Good overall intra and inter-rater agreement and test-retest reproducibility was noted (coefficient of variation of 4.8-19.4% and 5.9-12.9%, respectively).

CONCLUSION

Anisotropy is evident in the anal canal with good inter-rater agreement and test reproducibility.

Perception-based visualization of manifold-valued medical images using distance-preserving dimensionality reduction

A method for visualizing manifold-valued medical image data is proposed. The method operates on images in which each pixel is assumed to be sampled from an underlying manifold. For example, each pixel may contain a high dimensional vector, such as the time activity curve (TAC) in a dynamic positron emission tomography (dPET) or a dynamic single photon emission computed tomography (dSPECT) image, or the positive semi-definite tensor in a diffusion tensor magnetic resonance image (DTMRI). A nonlinear mapping reduces the dimensionality of the pixel data to achieve two goals: distance preservation and embedding into a perceptual color space. We use multidimensional scaling distance-preserving mapping to render similar pixels (e.g., DT or TAC pixels) with perceptually similar colors. The 3D CIELAB perceptual color space is adopted as the range of the distance preserving mapping, with a final similarity transform mapping colors to a maximum gamut size. Similarity between pixels is either determined analytically as geodesics on the manifold of pixels or is approximated using manifold learning techniques. In particular, dissimilarity between DTMRI pixels is evaluated via a Log-Euclidean Riemannian metric respecting the manifold of the rank 3, second-order positive semi-definite DTs, whereas the dissimilarity between TACs is approximated via ISOMAP. We demonstrate our approach via artificial high-dimensional, manifold-valued data, as well as case studies of normal and pathological clinical brain and heart DTMRI, dPET, and dSPECT images. Our results demonstrate the effectiveness of our approach in capturing, in a perceptually meaningful way, important features in the data.

Novel spherical phantoms for Q-ball imaging under in vivo conditions

For the validation of complex diffusion imaging techniques like q-ball imaging that aim to resolve multiple fiber directions, appropriate phantoms are highly desirable. However, previous q-ball imaging phantoms had diffusion anisotropies well below those of in vivo white matter. In this work, fiber phantoms of well-defined geometry are presented. The fibers are wound on a spherical spindle yielding high packing densities and consequently high diffusion anisotropies (fractional anisotropy 0.93 ± 0.02 at b = 500 s/mm(2)). Phantoms with 90° and 45° crossing angle were constructed both with two crossing types. In the "stacked" crossing, two fiber strings were wound consecutively to simulate two touching fibers, in the "interleaved" crossing, fibers were wound alternately. The stacked crossing allows the alteration of partial volumes, whereas the interleaved crossing provides constant partial volumes, allowing e.g. the easy alteration of the SNR by varying the slice thickness. Exemplary q-ball imaging validation measurements using different b-values and slice thicknesses are presented.

Intravoxel incoherent motion MRI for the differentiation between mass forming chronic pancreatitis and pancreatic carcinoma

PURPOSE

To determine which of the quantitative parameters obtained from intravoxel incoherent motion diffusion weighted imaging (DWI) is the most significant for the differentiation between pancreatic carcinoma and mass-forming chronic pancreatitis.

MATERIALS AND METHODS

Twenty-nine patients with pancreatic masses were included, 9 proved to have a mass-forming pancreatitis and 20 had a pancreatic carcinoma. The patients were studied using intravoxel incoherent motion DWI with 11 b-values and the apparent diffusion coefficient (ADC), the true diffusion constant (D) and the perfusion fraction (f) were calculated. The diagnostic strength of the parameters was evaluated using receiver operating characteristic analysis.

RESULTS

The ADC in chronic pancreatitis was higher than in pancreatic carcinoma with significant differences at b = 50, 75, 100, 150, 200, 300 s/mm (ADC50 = 3.17 ± 0.67 vs. 2.55 ± 1.09, ADC75 = 2.46 ± 0.4 vs. 1.93 ± 0.52, ADC100 = 2.28 ± 0.48 vs. 1.73 ± 0.45, ADC150 = 1.97 ± 0.26 vs. 1.63 ± 0.40, ADC200 = 1.98 ± 0.24 vs. 1.53 ± 0.28, and ADC300 = 1.76 ± 0.19 vs. 1.46 ± 0.31 × 10(-3) mm2/s). No significant differences were found at b = 25, 400, 600, and 800 s/mm (ADC25 = 4.69 ± 0.65 vs. 4.04 ± 1.35, ADC400 = 1.57 ± 0.21 vs. 1.37 ± 0.30, ADC600 = 1.38 ± 0.18 vs. 1.24 ± 0.25, and ADC800 = 1.27 ± 0.10 vs. 1.18 ± 0.19 × 10(-3) mm2/s) nor using ADCtot (1.42 ± 0.23 vs. 1.28 ± 0.12 × 10(-3) mm2/s). The perfusion fraction f was significantly higher in pancreatitis compared with pancreatic carcinoma (16.3% ± 5.30% vs. 8.2% ± 4.00%, P = 0.0001). There was no significant difference between groups for D (1.07 ± 0.224 × 10(-3) mm2/s for chronic pancreatitis and 1.09 ± 0.3 × 10(-3) mm2/s for pancreatic carcinoma, P = 0.66). For f, the highest area under the curve (0.894) and combined sensitivity (80%) and specificity (89.9%) were found.

CONCLUSIONS

There were significant differences in ADC50-300 between chronic pancreatitis and pancreatic carcinoma. Because D is not significantly different between groups, differences in ADC can be attributed mainly to differences in perfusion. The perfusion fraction f proved to be the superior DWI-derived parameter for differentiation of mass-forming pancreatitis and pancreatic carcinoma.

[Mild cognitive impairment: diagnostic value of different MR techniques]

In view of an increasingly aging population the prevalence of dementia is also expected to increase rapidly. As well as clinical, neuropsychological and laboratory procedures magnetic resonance imaging (MRI) plays an important role in the early diagnosis of dementia which is important in the precursor stage of mild cognitive impairment (MCI). On the one hand this stage is associated with an increased risk of dementia and on the other hand an early treatment in this stage could attenuate development of the disease. In addition to morphological changes different functional MRI techniques can help in the early diagnosis of dementia and the precursor stages. Moreover, it is important to detect those MCI patients who are at particularly risk for developing dementia. In the differentiation of converters to non-converters initial studies suggest that particularly voxel-based morphometry, MR spectroscopy and diffusion tensor imaging can provide important additional information.

Imaging of brain tumors: functional magnetic resonance imaging and diffusion tensor imaging

The eloquent brain can be identified using functional MR (fMR) imaging for the gray matter and diffusion tensor (DT) imaging for the white matter. fMR imaging and DT imaging are especially important for patients with tumors near the important motor and language centers of the brain, where the normal anatomic references may be distorted by the tumor and associated edema. This article explains fMR imaging and DT imaging techniques and illustrates their clinical applications and limitations.

Advanced Contrast-Enhanced MR Imaging of the CNS

One of the most frequent uses of magnetic resonance imaging (MRI) since its introduction has been in the assessment of the CNS for neoplasm. In recent years there has been a substantial improvement in the MR protocol for tumors that includes the use of functional imaging techniques. As shown in multiple experimental and clinical studies an optimized use of high quality contrast media and the introduction of these functional MRI methods has improved the detection and delineation of CNS tumors. This results not only in more confident diagnoses, but also in a substantially improved differential diagnostic process. The article reviews and summarizes the technical advances in functional techniques and their impact on the assessment of cerebral pathologies, namely brain tumors, and gives practical information on how to optimize sequence parameters to achieve the optimal tissue and pathology contrast.

DTI and PWI analysis of peri-enhancing tumoral brain tissue in patients treated for glioblastoma

To analyse the role of MR diffusion-tensor imaging (DTI) and perfusion-weighted imaging (PWI) in characterising tumour boundaries in patients with glioblastoma multiforme. Seventeen patients with surgically treated WHO IV grade gliomas who were candidates for adjuvant chemo-radiotherapy were enrolled. Before (T0) and after radiation treatment (T1), they underwent DTI and PWI, and the apparent diffusion coefficient (ADC), fractional anisotropy (FA) and relative cerebral blood volume (rCBV) in the enhancing tumour, the hyperintense tissue adjacent to the enhancing tumour, and the normal-appearing white matter (NAWM) adjacent to the hyperintense areas were analysed. The enhancing tissue at T1 was retrospectively divided on the basis of whether or not it was also enhancing at T0. The controls were the corresponding contralateral areas, on which we normalized the rCBV values, calculating the rCBV ratio. In NAWM, we did not find any significant differences in FA, ADC or rCBV. In the hyperintense perilesional regions, FA was significantly lower and ADC significantly higher than in the unaffected contralateral tissue; there were no significant differences in the rCBV maps. The values of FA, ADC and rCBV in enhancing neoplastic tissue were all significantly different from those observed in the contralateral tissue. There was no significant difference in rCBV values between the areas enhancing at T0 and those not enhancing at T0 but enhancing at T1, which may indicate the neoplastic transformation of apparently normal brain tissue. DTI metrics identify ultrastructural changes in hyperintense perilesional areas, but these are not specific for neoplastic tissue. rCBV seemed to reflect an ultrastructural alteration that was not visible at T0, but became visible (as neoplastic progression) on conventional MR images at T1. These findings could help identify tissue at risk of tumour infiltration.

Saturn: a software application of tensor utilities for research in neuroimaging

We present an advanced software tool designed for visualization and quantitative analysis of Diffusion Tensor Imaging (DTI) called Saturn. The software is specially developed to help clinicians and researchers in neuroimaging, and includes a complete set of visualization capabilities to browse and analyze efficiently DTI data, making this application a powerful tool also for diagnosis purposes. The software includes a robust quantification method for DTI data, using an atlas-based method to automatically obtain equivalent anatomical fiber bundles and regions of interest among different DTI data sets. Consequently, a set of measurements is also implemented to perform robust group studies among subjects affected by neurological disorders and control groups in order to look for significant differences. Finally, a comparison study with five similar DTI applications is presented, showing the advantages offered by this tool.

Reproducible evaluation of spinal cord DTI using an optimized inner volume sequence in combination with probabilistic ROI analysis

The purpose of this work was to reliably acquire and evaluate diffusion tensor data of the cervical spine. Thereto, we describe an optimized, time-efficient inner-volume echo planar imaging sequence. Multislice capability is achieved by restoring the magnetization in neighbouring slices early during the twice refocused diffusion preparation. The acquired diffusion images showed compelling image quality. To reduce the arbitrariness of conventional region of interest (ROI) analysis, a tissue classification algorithm was applied. The classification was independent of the ROI shape and hence, a reliable and stable evaluation of the diffusion tensor could be achieved. The mean fractional anisotropy (FA) of five healthy subjects decreased from C1 (FA = 0.81 +/- 0.03) to C7 (FA = 0.60 +/- 0.03), while the mean apparent diffusion coefficient (ADC) increased from C1 (ADC= 0.78 +/- 0.08 microm2/ms) to C7 (ADC = 1.08 +/- 0.08 microm2/ms). In subsequent measurements of the individual healthy subjects, the standard deviation of the FA was 0.024 +/- 0.011 and the standard deviation of the ADC was 0.045 +/- 0.017 microm2/ms. The FA values of a patient with acute ischemic spinal trauma were significantly lower and changed more drastically than ADC values. Here, absolute FA ranged from 0.23 to 0.42, showing that DTI of the spine may serve as surrogate marker for tissue integrity and therapy monitoring.

Visualization of the protective ability of a free radical trapping compound against rat C6 and F98 gliomas with diffusion tensor fiber tractography

PURPOSE

To apply fiber tractography to assess the effect of a possible antiglioma drug, phenyl N-tert-butyl nitrone (PBN), on glioma-affected neuronal fibers. The fiber tractography method was able to differentiate between different tumor types, such as the C6 and F98 rat glioma models.

MATERIALS AND METHODS

C6 or F98 cells were intracranially injected into the cortex of male Fischer 344 rats. PBN treatment was initiated before or after cell implantation. Tumor growth was monitored with diffusion tensor imaging (DTI) and fiber tractography using diffusion-weighting gradients in 30 noncolinear directions.

RESULTS

Although proton density-weighted (PDw) and T2-weighted (T2w) images did not show any difference between C6 and F98 gliomas without edema, the apparent diffusion coefficient (ADC) and fractional anisotropy (FA) maps were able to discriminate between these two tumor models. Fiber tractography was used to visualize C6 glioma-induced ischemia of tumor-surrounding tissues, whereas F98 glioma was found to infiltrate and penetrate into the corpus callosum (CC). During glioma growth, neuronal fibers were found to disappear at the border regions between the tumor and surrounding tissues. PBN treatment was shown to inhibit glioma growth with accompanying changes in the surrounding tissue.

CONCLUSION

By noninvasively monitoring the degree of neuronal fiber integrity and connectivity with the use of neuronal fiber tractography, we were able to evaluate the protective effect of PBN against invasive glioma growth in rat brains. PBN provided protection of the neuronal fibers against tumor-induced ischemia and tumor invasion.

Diffusion tensor imaging and fiber tractography of C6 rat glioma

PURPOSE

To apply diffusion tensor images using 30 noncollinear directions for diffusion-weighted gradient schemes to characterize diffusion tensor imaging (DTI) features associated with C6 glioma-bearing rat brains, and ideally visualize fiber tractography datasets.

MATERIALS AND METHODS

Fiber tractographies of normal male Fischer 344 rat brains were constructed from DTI datasets acquired with a 30 noncollinear diffusion gradient scheme. Cultured C6 cell were intracranially injected into the cortex of male Fischer 344 rats. The time course of the tumor growth was monitored with DTI and fiber tractography using diffusion-weighting gradients in 30 noncollinear directions.

RESULTS

Fiber tractographies through the corpus callosum (CC) were easily visualized with the 30-direction gradient scheme, and the fiber trajectories of the motor cortex and striatum were well represented in normal rats. Fiber tractography indicated that the neuronal fibers of the CC were compressed or disappeared by growing C6 glioma, which affected surrounding brain tissue.

CONCLUSION

We have demonstrated in this study that fiber tractography with the 30 noncollinear diffusion gradient scheme method can be used to help provide a better understanding regarding the influence of a tumor on the surrounding regions of normal brain tissue in vivo.

MRI for identification of progression in brain tumors: from morphology to function

For monitoring of brain tumors, it is crucial to identify progression or treatment failure early during follow-up to change treatment schemes and, thereby, optimize patient outcome. In the past years, several areas within the field of magnetic resonance (MR) have seen considerable advances: modern contrast media, advanced morphologic approaches and several functional techniques, for example, in the visualization of tumor perfusion or tumor cell metabolism. This review presents these recent advances by introducing the different techniques and outlining their benefit for identification of progression in brain tumors, with a focus on gliomas, metastases and meningiomas. After radiotherapy, MR spectroscopy helps to more accurately discriminate between radiation necrosis and glioma progression. In low-grade gliomas, perfusion MR techniques enable a more sensitive detection of anaplastic transformation than conventional MRI. Modern contrast media, as well as diffusion tensor imaging, allow for an improved tumor delineation and assessment of tumor extension. We will also highlight the biological background of these techniques, their applicability and current limitations. In conclusion, modern MRI techniques have been developed that are on the doorstep to be integrated in clinical routine.

How background noise shifts eigenvectors and increases eigenvalues in DTI

INTRODUCTION

The signal-to-noise ratio of in vivo diffusion tensor imaging (DTI) is usually very limited, especially if high resolution data is acquired. In a variety of settings, the signal of diffusion weighted images can drop below the background noise level yielding an underestimated diffusion constant. In this work, we report two new artefacts in DTI that are important in this regime.

METHODS

Both artifacts are described analytically and numerically and are demonstrated in DTI phantoms and in subjects in vivo.

RESULTS

First, eigenvectors are systematically shifted towards distinct 'attractive' orientations of the gradient scheme. Second, certain eigenvalues can be overestimated due to the underestimation of the measured diffusion, which can result in the misordering of eigenvalues.

DISCUSSION

We show that these effects are relevant for current clinical settings of DTI.

On the effects of dephasing due to local gradients in diffusion tensor imaging experiments: relevance for diffusion tensor imaging fiber phantoms

The effect of susceptibility differences between fluid and fibers on the properties of DTI fiber phantoms was investigated. Thereto, machine-made, easily producible and inexpensive DTI fiber phantoms were constructed by winding polyamide fibers of 15 microm diameter around a circular acrylic glass spindle. The achieved fractional anisotropy was 0.78+/-0.02. It is shown by phantom measurements and Monte Carlo simulations that the transversal relaxation time T(2) strongly depends on the angle between the fibers and the B(0) field if the susceptibilities of the fibers and fluid are not identical. In the phantoms, the measured T(2) time at 3 T decreased by 60% for fibers running perpendicular to B(0). Monte Carlo simulations confirmed this result and revealed that the exact relaxation time depends strongly on the exact packing of the fibers. In the phantoms, the measured diffusion was independent of fiber orientation. Monte Carlo simulations revealed that the measured diffusion strongly depends on the exact fiber packing and that field strength and -orientation dependencies of measured diffusion may be minimal for hexagonal packing while the diffusion can be underestimated by more than 50% for cubic packing at 3 T. To overcome these effects, the susceptibilities of fibers and fluid were matched using an aqueous sodium chloride solution (83 g NaCl per kilogram of water). This enables an orientation independent and reliable use of DTI phantoms for evaluation purposes.

Longitudinal diffusion tensor imaging in a rat brain glioma model

In order to investigate the properties of water motion within and around brain tumors as a function of tumor growth, longitudinal diffusion tensor imaging (DTI) was carried out in a rat brain glioma (C6) model. As tumors grew in size, significant anisotropy of water diffusion was seen both within and around the tumor. The tissue water surrounding the tumor exhibited high planar anisotropy, as opposed to the linear anisotropy normally seen in white matter, indicating that cells were experiencing stress in a direction normal to the tumor border. When tumors were sufficiently large, significant anisotropy was also seen within the tumor because of longer-range organization of cancer cells within the tumor borders. These findings have important implications for diffusion-weighted MRI experiments examining tumor growth and response to therapy.

Multiparametric tissue characterization of brain neoplasms and their recurrence using pattern classification of MR images

RATIONALE AND OBJECTIVES

Treatment of brain neoplasms can greatly benefit from better delineation of bulk neoplasm boundary and the extent and degree of more subtle neoplastic infiltration. Magnetic resonance imaging (MRI) is the primary imaging modality for evaluation before and after therapy, typically combining conventional sequences with more advanced techniques such as perfusion-weighted imaging and diffusion tensor imaging (DTI). The purpose of this study is to quantify the multiparametric imaging profile of neoplasms by integrating structural MRI and DTI via statistical image analysis methods to potentially capture complex and subtle tissue characteristics that are not obvious from any individual image or parameter.

MATERIALS AND METHODS

Five structural MRI sequences, namely, B0, diffusion-weighted images, fluid-attenuated inversion recovery, T1-weighted, and gadolinium-enhanced T1-weighted, and two scalar maps computed from DTI (ie, fractional anisotropy and apparent diffusion coefficient) are used to create an intensity-based tissue profile. This is incorporated into a nonlinear pattern classification technique to create a multiparametric probabilistic tissue characterization, which is applied to data from 14 patients with newly diagnosed primary high-grade neoplasms who have not received any therapy before imaging.

RESULTS

Preliminary results demonstrate that this multiparametric tissue characterization helps to better differentiate among neoplasm, edema, and healthy tissue, and to identify tissue that is likely to progress to neoplasm in the future. This has been validated on expert assessed tissue.

CONCLUSION

This approach has potential applications in treatment, aiding computer-assisted surgery by determining the spatial distributions of healthy and neoplastic tissue, as well as in identifying tissue that is relatively more prone to tumor recurrence.

Reproducibility, interrater agreement, and age-related changes of fractional anisotropy measures at 3T in healthy subjects: effect of the applied b-value

BACKGROUND AND PURPOSE

There is no reproducibility study of fractional anisotropy (FA) measurements at 3T using regions of interest (ROIs). Our purpose was to establish the extent and statistical significance of the interrater variability, the variability observed with 2 different b-values, and in 2 separate scanning sessions.

MATERIALS AND METHODS

Twelve healthy volunteers underwent MR imaging twice. MR imaging was performed on a 3T unit, and FA maps were analyzed independently by 2 observers using ROIs positioned in the corpus callosum, internal capsules, corticospinal tracts, and right thalamus. Changes in FA values (x10(3)) measured with 2 b-values (700 and 1000 s/mm(2)), age-related differences, interobserver agreement, and measurement reproducibility were assessed.

RESULTS

In the right internal capsule genu (FA = 702/728; b = 1000/700 s/mm(2)) and the left anterior limb of the internal capsule (AIC; FA = 617/745; b = 1000/700 s/mm(2)), the FA values were significantly different between the 2 b-values (P = .02 and .05, respectively). Significant age-related differences in FA were observed in the genu of the corpus callosum and in the left AIC. Interrater measurements showed fair-to-moderate agreement for most anatomic structures. The lowest significant change for a single subject regarding any FA values between the 2 sessions was in the corpus callosum (4%), whereas the highest one was in the corticospinal tracts (27%). The Bland-Altman plot analysis showed that the 1000-s/mm(2) b-value gave satisfactorily reproducible measurements equally good or better than the 700-s/mm(2) b-value.

CONCLUSION

The reproducibility of FA estimates using ROIs was satisfactory. Measurements with a b-value at 1000 s/mm(2) showed superior reproducibility in most anatomic locations.

Incidental acute infarcts identified on diffusion-weighted images: a university hospital-based study

BACKGROUND AND PURPOSE

Pathogenesis of leukoaraiosis is incompletely understood and accumulation of small infarctions may be one of the possible sources of such white matter lesions. Thus, the purpose of this study was to identify the rate of incident infarction as depicted on diffusion-weighted images (DWIs) obtained from a general patient population.

MATERIALS AND METHODS

During the 4-year study period, a total of 60 patients (36 men and 24 women) had an incidental DWI-defined infarction without overt clinical symptoms suggestive of a stroke or a transient ischemic attack. All of the MR images were obtained by using a similar protocol on 2 identical 1.5T whole-body scanners. The patient's vascular risk factors, as well as the presence of white matter lesions (WMLs) on MR imaging and atheromatous changes on MR angiography, were assessed retrospectively. The incidental DWI-defined infarcts were also characterized in terms of their lateralization, lobe, and specific location.

RESULTS

A total of 16,206 consecutive brain MR images were done during the study period; the overall incidence of incidental infarcts was 0.37%. Most of these patients with an incidental infarct had vascular risk factors and WMLs on MR images. Most of these patients (80%) had a single lesion on DWI. A total of 88 lesions were identified; most were located in the white matter of the supratentorial brain, primarily in the frontoparietal lobes. There were also lesions involving the brain stem (n = 2). The lesions involving cerebrum were more commonly located in the right side (right to left = 52:34).

CONCLUSION

Small, DWI-defined acute brain infarctions can be found incidentally in an asymptomatic population; this finding may account, at least in part, for the pathogenesis of WMLs identified on MR imaging.

Preserved structural integrity of white matter adjacent to low-grade tumors

BACKGROUND AND PURPOSE

Brain tumors may dislocate, infiltrate, or disrupt the adjacent fiber tracts. We examined (1) microstructural changes of white matter (WM) adjacent to supratentorial low grade tumors in children and (2) WM tracts of the affected hemisphere using diffusion tensor imaging (DTI). We hypothesized that the structural integrity of the adjacent WM tracts would be preserved in these slow-growing tumors.

MATERIALS AND METHODS

DTI was performed in 11 children with low grade tumors diagnosed by magnetic resonance imaging (MRI). Regions of interest were placed in the tumor, in WM adjacent to tumor, and on the normal contralateral side. Fractional anisotropy (FA), trace, and eigenvalues were measured. Color-coded maps and tractography were used to grade the WM tracts: Grade one was normal tract size and color hue; grade two was reduced tract size but preserved color hue; and grade three was loss of color hue or failure to track on tractography. Grades one and two were subcategorized as "a" or "b," depending on the absence or presence of tract displacement.

RESULTS

There were no significant differences in FA, trace, and eigenvalues between WM adjacent to tumor and the contralateral side. One patient had grade 1a changes, six grade 1b, and four grade 2b.

CONCLUSION

We found preserved microstructural integrity of WM adjacent to low grade tumors in children. Color vector maps and tractography demonstrated displacement of the WM tracts in all but one patient. Our findings could be useful for neurosurgical planning to minimize injury to the WM tracts and improve preoperative risk analysis.