MR Diffusion Imaging in Ischemic Stroke

In vivo assessment of white matter damage in neuromyelitis optica: a diffusion tensor and diffusion kurtosis MR imaging study

BACKGROUND AND PURPOSE

In patients with neuromyelitis optica (NMO), damage to extensive regions of normal-appearing WM has been observed. To investigate the possibility that microstructural alterations are present in these WM tracts, DTI and diffusion kurtosis imaging (DKI) techniques were applied and compared.

MATERIAL AND METHODS

Thirteen patients with NMO and 13 demographically and gender-matched controls underwent MRI using a 3T MR scanner, with DTI/DKI sequence acquired jointly fitted. Parametric fractional anisotropy maps were derived from diffusion tensor (FADTI) values using b-values of 0s/mm(2) and 1000s/mm(2). Parametric fractional anisotropy maps derived from diffusion kurtosis tensor (FADKI) values were also acquired using b-values of 0, 1000, and 2000s/mm(2). Mean FADTI and FADKI values were also calculated. A ROI analysis of the genu and splenium of the corpus callosum (CC), cerebral peduncle (CP), and optic radiation (OR) was also performed. Student's t-test and corrections for multiple comparisons were used to evaluate the data obtained.

RESULTS

A significant decrease in the FADTI values obtained for NMO patients versus controls was observed for the splenium of the CC and the left OR (p<0.05). However, just a positive trend was observed for the FADKI values associated with the same WM tracts.

CONCLUSIONS

To our knowledge, this is the first study to analyze WM tracts of NMO patients using DTI and DKI. These data indicate that DKI could have limitations in evaluating the WM integrity in NMO patients. Furthermore, the results obtained are consistent with the hypothesis that diffuse brain involvement characterizes NMO.

Leading non-Gaussian corrections for diffusion orientation distribution function

An analytical representation of the leading non-Gaussian corrections for a class of diffusion orientation distribution functions (dODFs) is presented. This formula is constructed from the diffusion and diffusional kurtosis tensors, both of which may be estimated with diffusional kurtosis imaging (DKI). By incorporating model-independent non-Gaussian diffusion effects, it improves on the Gaussian approximation used in diffusion tensor imaging (DTI). This analytical representation therefore provides a natural foundation for DKI-based white matter fiber tractography, which has potential advantages over conventional DTI-based fiber tractography in generating more accurate predictions for the orientations of fiber bundles and in being able to directly resolve intra-voxel fiber crossings. The formula is illustrated with numerical simulations for a two-compartment model of fiber crossings and for human brain data. These results indicate that the inclusion of the leading non-Gaussian corrections can significantly affect fiber tractography in white matter regions, such as the centrum semiovale, where fiber crossings are common.

Visualization, imaging and new preclinical diagnostics in radiation oncology

Innovative strategies in cancer radiotherapy are stimulated by the growing knowledge on cellular and molecular tumor biology, tumor pathophysiology, and tumor microenvironment. In terms of tumor diagnostics and therapy monitoring, the reliable delineation of tumor boundaries and the assessment of tumor heterogeneity are increasingly complemented by the non-invasive characterization of functional and molecular processes, moving preclinical and clinical imaging from solely assessing tumor morphology towards the visualization of physiological and pathophysiological processes. Functional and molecular imaging techniques allow for the non-invasive characterization of tissues in vivo, using different modalities, including computed tomography (CT), magnetic resonance imaging (MRI), ultrasound, positron emission tomography (PET) and optical imaging (OI). With novel therapeutic concepts combining optimized radiotherapy with molecularly targeted agents focusing on tumor cell proliferation, angiogenesis, and cell death, the non-invasive assessment of tumor microcirculation and tissue water diffusion, together with strategies for imaging the mechanisms of cellular injury and repair is of particular interest. Characterizing the tumor microenvironment prior to and in response to irradiation will help to optimize the outcome of radiotherapy. These novel concepts of personalized multi-modal cancer therapy require careful pre-treatment stratification as well as a timely and efficient therapy monitoring to maximize patient benefit on an individual basis. Functional and molecular imaging techniques are key in this regard to open novel opportunities for exploring and understanding the underlying mechanisms with the perspective to optimize therapeutic concepts and translate them into a personalized form of radiotherapy in the near future.

Visualizing non-Gaussian diffusion: clinical application of q-space imaging and diffusional kurtosis imaging of the brain and spine

Recently, non-Gaussian diffusion-weighted imaging (DWI) techniques, including q-space imaging (QSI) and diffusional kurtosis imaging (DKI), have emerged as advanced methods to evaluate tissue microstructure in vivo using water diffusion. QSI and DKI have shown promising results in clinical applications, such as in the evaluation of brain tumors (e.g., grading gliomas), degenerative diseases (e.g., specific diagnosis of Parkinson disease), demyelinating diseases (e.g., assessment of normal-appearing tissue of multiple sclerosis), and cerebrovascular diseases (e.g., assessment of the microstructural environment of fresh infarctions). Representative metrics in clinical use are the full width at half maximum, also known as the mean displacement of the probability density function curve, which is derived from QSI, and diffusional kurtosis, which is derived from DKI. These new metrics may provide information on tissue structure in addition to that provided by conventional Gaussian DWI investigations that use the apparent diffusion coefficient and fractional anisotropy, recognized indices for evaluating disease and normal development in the brain and spine. In some clinical situations, sensitivity for detecting pathological conditions is higher using QSI and DKI than conventional DWI and diffusion tensor imaging (DTI) because DWI and DTI calculations are based on the assumption that water molecules follow a Gaussian distribution, whereas hindrance of the distribution of water molecules by complex and restricted structures in actual neural tissues produces distributions that are far from Gaussian. We review the technical aspects and clinical applications of QSI and DKI, focusing on clinical use and in vivo studies and highlighting differences from conventional diffusional metrics.

Effects of diffusional kurtosis imaging parameters on diffusion quantification

Diffusional kurtosis imaging (DKI) is a new technique based on non-Gaussian water diffusion analysis. However, the original DKI protocol (six b values and 30 motion-probing gradient (MPG) directions) requires more than 10 min of scanning time, which is too long for daily clinical use. We aimed to find suitable b value, MPG direction, and diffusion time settings for faster DKI. Four normal healthy subjects participated in the study. All DKI data sets were acquired on a clinical 3T-MRI scanner (Philips Medical Systems) with use of three protocols of 0-7500 s/mm(2) b values, 6-32 MPG directions, and 23-80 ms diffusion time. There was a remarkable difference in the standard deviation (SD) of the mean DK values in the number of MPG directions. The mean DK values were significantly higher in the posterior limb of the internal capsule (p = 0.003, r = 0.924) and thalamus (p = 0.005, r = 0.903), whereas the mean DK values of the cerebrospinal fluid (CSF) (p = 0.001, r = -0.976) were significantly lower when we used a longer diffusion time. Our results indicate that the SD of the mean DK values was higher in 15 MPG directions than in 20 MPG directions and more. Because the mean DK values of the CSF were significantly lower when we used longer diffusion times, we expect longer diffusion times to be useful for DKI. We propose the following imaging parameters for clinical use: 0, 1000, and 2000 s/mm(2) b values; 20 MPG directions; Δ/δ 45.3/13.3 ms.

Non-Gaussian diffusion MRI assessment of brain microstructure in mild cognitive impairment and Alzheimer's disease

We report the first application of a novel diffusion-based MRI method, called diffusional kurtosis imaging (DKI), to investigate changes in brain tissue microstructure in patients with mild cognitive impairment (MCI) and AD and in cognitively intact controls. The subject groups were characterized and compared in terms of DKI-derived metrics for selected brain regions using analysis of covariance with a Tukey multiple comparison correction. Receiver operating characteristic (ROC) and binary logistic regression analyses were used to assess the utility of regional diffusion measures, alone and in combination, to discriminate each pair of subject groups. ROC analyses identified mean and radial kurtoses in the anterior corona radiata as the best individual discriminators of MCI from controls, with the measures having an area under the ROC curve (AUC) of 0.80 and 0.82, respectively. The next best discriminators of MCI from controls were diffusivity and kurtosis (both mean and radial) in the prefrontal white matter (WM), with each measure having an AUC between 0.77 and 0.79. Finally, the axial diffusivity in the hippocampus was the best overall discriminator of MCI from AD, having an AUC of 0.90. These preliminary results suggest that non-Gaussian diffusion MRI may be beneficial in the assessment of microstructural tissue damage at the early stage of MCI and may be useful in developing biomarkers for the clinical staging of AD.

A hitchhiker's guide to diffusion tensor imaging

Diffusion Tensor Imaging (DTI) studies are increasingly popular among clinicians and researchers as they provide unique insights into brain network connectivity. However, in order to optimize the use of DTI, several technical and methodological aspects must be factored in. These include decisions on: acquisition protocol, artifact handling, data quality control, reconstruction algorithm, and visualization approaches, and quantitative analysis methodology. Furthermore, the researcher and/or clinician also needs to take into account and decide on the most suited software tool(s) for each stage of the DTI analysis pipeline. Herein, we provide a straightforward hitchhiker's guide, covering all of the workflow's major stages. Ultimately, this guide will help newcomers navigate the most critical roadblocks in the analysis and further encourage the use of DTI.

Potential blood biomarkers for stroke

Stroke is one of the most common causes of death worldwide and a major cause of acquired disability in adults. Despite advances in research during the last decade, prevention and treatment strategies still suffer from significant limitations, and therefore new theoretical and technical approaches are required. Technological advances in the proteomic and metabolomic areas, during recent years, have permitted a more effective search for novel biomarkers and therapeutic targets that may allow for effective risk stratification and early diagnosis with subsequent rapid treatment. This review provides a comprehensive overview of the latest candidate proteins and metabolites proposed as new potential biomarkers in stroke.

Effect of cerebral spinal fluid suppression for diffusional kurtosis imaging

PURPOSE

To evaluate the cerebral spinal fluid (CSF) partial volume effect on diffusional kurtosis imaging (DKI) metrics in white matter and cortical gray matter.

MATERIALS AND METHODS

Four healthy volunteers participated in this study. Standard DKI and fluid-attenuated inversion recovery (FLAIR) DKI experiments were performed using a twice-refocused-spin-echo diffusion sequence. The conventional diffusion tensor imaging (DTI) metrics of fractional anisotropy (FA), mean, axial, and radial diffusivity (MD, D[symbol in text], D[symbol in text] together with DKI metrics of mean, axial, and radial kurtosis (MK, K[symbol in text], K[symbol in text], were measured and compared. Single image slices located above the lateral ventricles, with similar anatomical features for each subject, were selected to minimize the effect of CSF from the ventricles.

RESULTS

In white matter, differences of less than 10% were observed between diffusion metrics measured with standard DKI and FLAIR-DKI sequences, suggesting minimal CSF contamination. For gray matter, conventional DTI metrics differed by 19% to 52%, reflecting significant CSF partial volume effects. Kurtosis metrics, however, changed by 11% or less, indicating greater robustness with respect to CSF contamination.

CONCLUSION

Kurtosis metrics are less sensitive to CSF partial voluming in cortical gray matter than conventional diffusion metrics. The kurtosis metrics may then be more specific indicators of changes in tissue microstructure, provided the effect sizes for the changes are comparable.

Stroke assessment with diffusional kurtosis imaging

BACKGROUND AND PURPOSE

Despite being the gold standard technique for stroke assessment, conventional diffusion MRI provides only partial information about tissue microstructure. Diffusional kurtosis imaging is an advanced diffusion MRI method that yields, in addition to conventional diffusion information, the diffusional kurtosis, which may help improve characterization of tissue microstructure. In particular, this additional information permits the description of white matter (WM) in terms of WM-specific diffusion metrics. The goal of this study is to elucidate possible biophysical mechanisms underlying ischemia using these new WM metrics.

METHODS

We performed a retrospective review of clinical and diffusional kurtosis imaging data of 44 patients with acute/subacute ischemic stroke. Patients with a history of brain neoplasm or intracranial hemorrhages were excluded from this study. Region of interest analysis was performed to measure percent change of diffusion metrics in ischemic WM lesions compared with the contralateral hemisphere.

RESULTS

Kurtosis maps exhibit distinct ischemic lesion heterogeneity that is not apparent on apparent diffusion coefficient maps. Kurtosis metrics also have significantly higher absolute percent change than complementary conventional diffusion metrics. Our WM metrics reveal an increase in axonal density and a larger decrease in the intra-axonal (Da) compared with extra-axonal diffusion microenvironment of the ischemic WM lesion.

CONCLUSIONS

The well-known decrease in the apparent diffusion coefficient of WM after ischemia is found to be mainly driven by a significant drop in the intra-axonal diffusion microenvironment. Our results suggest that ischemia preferentially alters intra-axonal environment, consistent with a proposed mechanism of focal enlargement of axons known as axonal swelling or beading.

[Preclinical imaging in animal models of radiation therapy]

CLINICAL/METHODICAL ISSUE

Modern radiotherapy benefits from precise and targeted diagnostic and pretherapeutic imaging.

STANDARD RADIOLOGICAL METHODS

Standard imaging modalities, such as computed tomography (CT) offer high morphological detail but only limited functional information on tumors.

METHODICAL INNOVATIONS

Novel functional and molecular imaging modalities provide biological information about tumors in addition to detailed morphological information.

PERFORMANCE

Perfusion magnetic resonance imaging (MRI) CT or ultrasound-based perfusion imaging as well as hybrid modalities, such as positron emission tomography (PET) CT or MRI-PET have the potential to identify and precisely delineate viable and/or perfused tumor areas, enabling optimization of targeted radiotherapy. Functional information on tissue microcirculation and/or glucose metabolism allow a more precise definition and treatment of tumors while reducing the radiation dose and sparing the surrounding healthy tissue.

ACHIEVEMENTS

In the development of new imaging methods for planning individualized radiotherapy, preclinical imaging and research plays a pivotal role, as the value of multimodality imaging can only be assessed, tested and adequately developed in a preclinical setting, i.e. in animal tumor models.

PRACTICAL RECOMMENDATIONS

New functional imaging modalities will play an increasing role for the surveillance of early treatment response during radiation therapy and in the assessment of the potential value of new combination therapies (e.g. combining anti-angiogenic drugs with radiotherapy).

Spatiotemporal dynamics of diffusional kurtosis, mean diffusivity and perfusion changes in experimental stroke

Diffusional kurtosis imaging (DKI), which measures the non-Gaussianity of water diffusion, has been demonstrated to be a sensitive biomarker in many neuropathologies. The goal of this study was to longitudinally examine the spatiotemporal dynamics of DKI in cerebral ischemia in an animal model of permanent and transient (45 min) middle cerebral artery occlusion (MCAO) during the hyperacute, acute and chronic phases. Diffusional kurtosis showed different spatiotemporal dynamics. In particular, mean kurtosis (MK) was sensitive to hyperacute and acute stroke changes, and exhibited different contrast than mean diffusivity (MD) and higher contrast than fractional anisotropy (FA) and T2. MK contrast persisted 1 to 7 days post-occlusion, whereas MD showed renormalization at day 1-2 and reversed contrast at day 7. The current study showed that DKI has the potential to complement existing stroke imaging techniques, particularly in the assessment of subacute to early chronic stroke evolution.

A new diffusion metric, diffusion kurtosis imaging, used in the serial examination of a patient with stroke

We report a case of a patient who developed a cerebral infarction, which was assessed using a new and advanced diffusion technique: diffusional kurtosis (DK) imaging. The signal changes on DK images were different from those on apparent diffusion coefficient (ADC) maps, and they seem to be useful for the prediction of early-stage tissue infarction. Although diffusion-weighted imaging and its metric, the ADC, have been widely used in the evaluation of stroke, DK imaging will provide additional and useful information, including a more detailed evaluation of pathologic tissue changes. This information can be predictive of the prognosis.