Diffusion Tensor Imaging of the Brain: Background and Review of Clinical Applications

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75192/1/j.1617-0830.2005.00036.x.pd

Value of MRI of the brain in patients with systemic lupus erythematosus and neurologic disturbance

Our objective was to review the frequency and pattern of signal abnormalities seen on conventional MRI in patients with suspected neuropsychiatric systemic lupus erythematosus (NP-SLE). We reviewed 116 MRI examinations of the brain performed on 85 patients with SLE, (81 women, four men, aged 21–78 years, mean 40.6 years) presenting with neurological disturbances. MRI was normal or nearly normal in 34%. In 60% high-signal lesions were observed on T2-weighted images, frequently in the frontal and parietal subcortical white matter. Infarct-like lesions involving gray and white matter were demonstrated in 21 of cases. Areas of restricted diffusion were seen in 12 of the 67 patients who underwent diffusion-weighted imaging. Other abnormalities included loss of brain volume, hemorrhage, meningeal enhancement, and bilateral high signal in occipital white-matter. The MRI findings alone did not allow us to distinguish between thromboembolic and inflammatory events in many patients. Some patients with normal MRI improved clinically while on immunosuppressive therapy. More sensitive and/or specific imaging methods, such as spectroscopy and perfusion-weighted imaging, should be investigated in these subgroups of patients with suspected NP-SLE.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46662/1/234_2003_Article_1049.pd

Tensor-valued diffusion MRI in under 3 minutes: An initial survey of microscopic anisotropy and tissue heterogeneity in intracranial tumors

Purpose: To evaluate the feasibility of a 3-minute b-tensor encoding protocol for diffusion MRI-based assessment of the microscopic anisotropy and tissue heterogeneity in a wide range of intracranial tumors. Methods: B-tensor encoding was performed in 42 patients with intracranial tumors (gliomas, meningiomas, adenomas, metastases). Microscopic anisotropy and tissue heterogeneity were evaluated by estimating the anisotropic kurtosis ($MK_A$) and isotropic kurtosis ($MK_I$), respectively. An extensive imaging protocol was compared with a faster 3-minute protocol. Results: The fast imaging protocol yielded parameters with characteristics in terms of bias and precision similar to the full protocol. Glioblastomas had lower microscopic anisotropy than meningiomas $(MK_A = 0.29 \pm 0.06$ versus $0.45\pm0.08, p = 0.003)$. Metastases had higher tissue heterogeneity $(MK_I = 0.57\pm0.07)$ than both the glioblastomas $(0.44\pm0.06, p < 0.001)$ and meningiomas $(0.46\pm0.06, p = 0.03)$. Conclusion: Evaluation of the microscopic anisotropy and tissue heterogeneity in intracranial tumor patients is feasible in clinically relevant times frames.Comment: Submitted to Magnetic Resonance in Medicin

MR spectroscopy in the evaluation of recurrent contrast-enhancing lesions in the posterior fossa after tumor treatment

Recurrent contrast-enhancing lesions arising within foci of prior brain neoplasms treated with chemotherapy and/or radiation therapy pose a significant diagnostic dilemma, as they may represent recurrent or residual tumor, treatment-related changes, or a combination of both. Those lesions specifically in the posterior fossa are even more difficult to assess, given the technical limitations of 2D CSI in the infratentorial compartment. We explored the feasibility of 2D-CSI MR spectroscopy in the evaluation of recurrent contrast-enhancing lesions in eight consecutive patients who had undergone treatment for posterior fossa or brainstem tumors. Mean Cho/Cr (choline/creatine) ratios obtained by 2D-CSI in recurrent tumor, treatment-related changes, and normal white matter were 2.93, 1.62, and 0.97, respectively, mean Cho/NAA (choline/N-Acetyl aspartate) ratios were 4.34, 1.74, and 0.93, and mean NAA/Cr (N-acetyl aspartate/creatine) ratios were 0.74, 0.92, and 1.26, respectively. In conclusion, also in the posterior fossa, MR spectroscopy is likely to be useful as an adjunct to conventional imaging characteristics in distinguishing recurrent tumor from treatment-related changes, irrespectively of the MRS technique used. In most cases spectra of diagnostic quality can be obtained using 2D-CSI to include coverage of both the lesion and its vicinity.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46664/1/234_2004_Article_1195.pd

Diffusion tensor imaging of the brain: review of clinical applications

We review the theoretical background to diffusion tensor imaging (DTI) and some of its commoner clinical applications, such as cerebral ischemia, brain maturation and traumatic brain injury. We also review its potential use in diseases such as epilepsy, multiple sclerosis, and Alzheimer’s disease. The value of DTI in the investigation of brain tumors and metabolic disorders is assessed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46663/1/234_2003_Article_1114.pd

Comparison of voxel-wise and histogram analyses of glioma ADC maps for prediction of early therapeutic change

Noninvasive imaging methods are sought to objectively predict early response to therapy for high-grade glioma tumors. Quantitative metrics derived from diffusion-weighted imaging, such as apparent diffusion coefficient (ADC), have previously shown promise when used in combination with voxel-based analysis reflecting regional changes. The functional diffusion mapping (fDM) metric is hypothesized to be associated with volume of tumor exhibiting an increasing ADC owing to effective therapeutic action. In this work, the reference fDM-predicted survival (from previous study) for 3 weeks from treatment initiation (midtreatment) is compared to multiple histogram-based metrics using Kaplan-Meier estimator for 80 glioma patients stratified to responders and nonresponders based on the population median value for the given metric. The ADC histogram metric reflecting reduction in midtreatment volume of solid tumor (ADC 8% population-median with respect to pretreatment is found to have the same predictive power as the reference fDM of increasing midtreatment ADC volume above 4%. This study establishes the level of correlation between fDM increase and low-ADC tumor volume shrinkage for prediction of early response to radiation therapy in patients with glioma malignancies

Development of a multiparametric voxel-based magnetic resonance imaging biomarker for early cancer therapeutic response assessment

Quantitative magnetic resonance imaging (MRI)-based biomarkers, which capture physiological and functional tumor processes, were evaluated as imaging surrogates of early tumor response following chemoradiotherapy in glioma patients. A multiparametric extension of a voxel-based analysis, referred as the parametric response map (PRM), was applied to quantitative MRI maps to test the predictive potential of this metric for detecting response. Fifty-six subjects with newly diagnosed high-grade gliomas treated with radiation and concurrent temozolomide were enrolled in a single-site prospective institutional review board-approved MRI study. Apparent diffusion coefficient (ADC) and relative cerebral blood volume (rCBV) maps were acquired before therapy and 3 weeks after therapy was initiated. Multiparametric PRM (mPRM) was applied to both physiological MRI maps and evaluated as an imaging biomarker of patient survival. For comparison, single-biomarker PRMs were also evaluated in this study. The simultaneous analysis of ADC and rCBV by the mPRM approach was found to improve the predictive potential for patient survival over single PRM measures. With an array of quantitative imaging parameters being evaluated as biomarkers of therapeutic response, mPRM shows promise as a new methodology for consolidating physiologically distinct imaging parameters into a single interpretable and quantitative metric

Quantification of microscopic diffusion anisotropy disentangles effects of orientation dispersion from microstructure: Applications in healthy volunteers and in brain tumors

AbstractThe anisotropy of water diffusion in brain tissue is affected by both disease and development. This change can be detected using diffusion MRI and is often quantified by the fractional anisotropy (FA) derived from diffusion tensor imaging (DTI). Although FA is sensitive to anisotropic cell structures, such as axons, it is also sensitive to their orientation dispersion. This is a major limitation to the use of FA as a biomarker for “tissue integrity”, especially in regions of complex microarchitecture. In this work, we seek to circumvent this limitation by disentangling the effects of microscopic diffusion anisotropy from the orientation dispersion.The microscopic fractional anisotropy (μFA) and the order parameter (OP) were calculated from the contrast between signal prepared with directional and isotropic diffusion encoding, where the latter was achieved by magic angle spinning of the q-vector (qMAS). These parameters were quantified in healthy volunteers and in two patients; one patient with meningioma and one with glioblastoma. Finally, we used simulations to elucidate the relation between FA and μFA in various micro-architectures.Generally, μFA was high in the white matter and low in the gray matter. In the white matter, the largest differences between μFA and FA were found in crossing white matter and in interfaces between large white matter tracts, where μFA was high while FA was low. Both tumor types exhibited a low FA, in contrast to the μFA which was high in the meningioma and low in the glioblastoma, indicating that the meningioma contained disordered anisotropic structures, while the glioblastoma did not. This interpretation was confirmed by histological examination.We conclude that FA from DTI reflects both the amount of diffusion anisotropy and orientation dispersion. We suggest that the μFA and OP may complement FA by independently quantifying the microscopic anisotropy and the level of orientation coherence

Sonographically Guided Lumbar Puncture in Pediatric Patients

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135581/1/jum201332122191.pd