Quantifying hepatic fibrosis using a biexponential model of diffusion weighted imaging in ex vivo liver specimens

The purpose of this study was to evaluate the non-Gaussian behavior of diffusion related signal decay of the ex vivo murine liver tissues from a dietary model of hepatic fibrosis. To this end, a biexponential formalism was used to model high b-value diffusion imaging (up to 3500 s/mm²), the findings of which were correlated with liver histopathology and compared to a simple monoexponential model. The presence of a major, fast diffusing component and a minor, slow diffusing component was demonstrated. With increasing hepatic fibrosis, the fractional contribution of the fast diffusing component decreased, as did the diffusion coefficient of the fast diffusing component. Strong correlation between the degrees of liver fibrosis and a two-predictor regression model incorporating parameters of the biexponential model was found. Using Akaike's Information Criterion analyses, the biexponential model resulted in an improved fit of the high b-value diffusion data when compared to the monoexponential model.     

Diffusion configuration of water molecules in diffusion weighted imaging

In the studying of fibers microstructure of brain white matter, many reconstruction methods have been proposed to interpret the diffusion-weighted signal. Those methods can be categorized into model-based and model-free methods. In this paper, the diffusion configuration of water molecules are discussed, and two questions are put forward to analyze the performance of the current algorithms about diffusion configuration. The first question is what the diffusion profile looks like in voxel? The second question is what is the location of fibers in a voxel? As a result, firstly, most of model-based algorithms ignore much information coming from the isotropic diffusion, which will lead to an inaccurate estimation. Secondly, model-free algorithms just provide direction information of fibers, ignore or cannot provide location information of fibers. So unfortunately, neither model-based methods nor model-free methods can resolve those two questions very well. How to resolve those questions is still an open problem, and it may be an interesting direction in the future research.     

Central neurocytoma: proton MR spectroscopy and diffusion weighted MR imaging findings

Purpose

To present proton magnetic resonance spectroscopy and diffusion-weighted imaging (DWI) findings of central neurocytoma (CN).

Methods and Materials

Imaging findings of seven patients with the histopathological diagnosis of CN (five male and two female; age range, 21–28 years of age) were evaluated retrospectively. In addition to conventional magnetic resonance imaging features, we also assessed the metabolite ratios and tumor normalized apparent diffusion coefficient (NADC), which was calculated by dividing the tumor apparent diffusion coefficient (ADC) values by normal ADC. Approval from our institutional review board was obtained for this review.

Results

The tumor choline/creatine ratios were 5.17±2.38, while N-acetyl aspartate/choline and N-acetyl aspartate/creatine ratios were 0.33±0.15 and 1.84±1.38, respectively. On DWI, tumors had heterogeneous hyperintense appearances when compared with the contralateral parietal lobe white matter and tumor NADC values were 0.63±0.05.

Conclusion

Significantly increased choline/creatine and decreased N-acetyl aspartate/choline ratios with lower NADC values in CN resemble high-grade gliomas and complicate the diagnosis. Familarity its physiologic features would help to presurgical diagnosis of ventricular and exraventricular CNs.     

Complimentary aspects of diffusion imaging and fMRI: II. Elucidating contributions to the fMRI signal with diffusion sensitization

Tissue water molecules reside in different biophysical compartments. For example, water molecules in the vasculature reside for variable periods of time within arteries, arterioles, capillaries, venuoles and veins, and may be within blood cells or blood plasma. Water molecules outside of the vasculature, in the extravascular space, reside, for a time, either within cells or within the interstitial space between cells. Within these different compartments, different types of microscopic motion that water molecules may experience have been identified and discussed. These range from Brownian diffusion to more coherent flow over the time scales relevant to functional magnetic resonance imaging (fMRI) experiments, on the order of several 10s of milliseconds. How these different types of motion are reflected in magnetic resonance imaging (MRI) methods developed for "diffusion" imaging studies has been an ongoing and active area of research. Here we briefly review the ideas that have developed regarding these motions within the context of modern "diffusion" imaging techniques and, in particular, how they have been accessed in attempts to further our understanding of the various contributions to the fMRI signal changes sought in studies of human brain activation.     

Intra-voxel incoherent motion MRI in rodent model of diethylnitrosamine-induced liver fibrosis

Rationale and Objectives

To compare the apparent diffusion coefficient (ADC) and the perfusion fraction measured by intra-voxel incoherent motion (IVIM) Magnetic Resonance Imaging (MRI) with liver fibrosis degrees in a rodent model.

Materials and Methods

All experiments received approval from our institutional animal care and use committee. Liver fibrosis was induced in 13 rats by oral gavage with diethylnitrosamine; 4 untreated rats with normal livers were used as controls. Diffusion Weighted MRI was performed and 8 gradient factors (0, 50, 100, 150, 200, 300, 400 and 500 s/mm²) were acquired. The values of ADC, true diffusion coefficient D and perfusion fraction f were measured based on Li Bihan’s method. The percentage of liver fibrosis was assessed via quantitative analysis of Masson trichrome staining using an average of 30 fields per section. The MRI measurements were compared to the histological fibrotic grade to evaluate the correlation between them.

Results

ADC contained the contribution of diffusion and perfusion. The ADC and f values decreased significantly with the increasing fibrosis level (correlation coefficient: ADC: ρ = − 0.781, p < 0.001; f: ρ = − 0.720, p = 0.001); but D was poorly correlated with fibrosis level (ρ = − 0.502, p = 0.040).

Conclusion

The hepatic ADC and the perfusion fraction f were significantly correlated with the liver fibrosis level; however, D was not. This might suggest that hepatic perfusion is altered during the progression of hepatic fibrosis.     

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.     

High resolution diffusion weighted magnetic resonance imaging of the pancreas using reduced field of view single-shot echo-planar imaging at 3 T

Diffusion weighted magnetic resonance imaging (DWI) has been mostly acquired using single-shot echo-planar imaging (ss EPI) to minimize motion induced artifacts. The spatial resolution, however, is inherently limited in ss EPI especially for abdominal imaging, even with the advances in parallel imaging. A novel method of reduced Field of View ss EPI (rFOV ss EPI) has achieved high resolution DWI in human carotid artery, spinal cord with reduced blurring and higher spatial resolution than conventional ss EPI, but it has not been used to pancreas imaging. In the work, comparisons between the full FOV ss-DW EPI and rFOV ss-DW EPI in image qualities and ADC values of pancreatic tumors and normal pancreatic tissues were performed to demonstrate the feasibility of pancreatic high resolution rFOV DWI. There were no significant differences in the mean ADC values between full FOV DWI and rFOV DWI for the 17 subjects using b = 600 s/mm² (P = 0.962). However, subjective scores of image quality was significantly higher at rFOV ss DWI (P = 0.008 and 0.000 for b-value = 0 s/mm² and 600 s/mm² respectively). The spatial resolution of DWI for pancreas was increased by a factor of over 2.0 (from almost 3.0 mm/pixel to 1.25 mm/pixel) using rFOV ss EPI technique. Reduced FOV ss EPI can provide good DW images and is promising to benefit applications for pancreatic diseases.     

Assessment of hepatocellular carcinoma using apparent diffusion coefficient and diffusion kurtosis indices: preliminary experience in fresh liver explants

Objectives

The objective was to perform ex vivo evaluation of non-Gaussian diffusion kurtosis imaging (DKI) for assessment of hepatocellular carcinoma (HCC), including presence of treatment-related necrosis, using fresh liver explants.

Methods

Twelve liver explants underwent 1.5-T magnetic resonance imaging using a DKI sequence with maximal b-value of 2000 s/mm². A standard monoexponential fit was used to calculate apparent diffusion coefficient (ADC), and a non-Gaussian kurtosis fit was used to calculate K, a measure of excess kurtosis of diffusion, and D, a corrected diffusion coefficient accounting for this non-Gaussian behavior. The mean value of these parameters was measured for 16 HCCs based upon histologic findings. For each metric, HCC-to-liver contrast was calculated, and coefficient of variation (CV) was computed for voxels within the lesion as an indicator of heterogeneity. A single hepatopathologist determined HCC necrosis and cellularity.

Results

The 16 HCCs demonstrated intermediate-to-substantial excess diffusional kurtosis, and mean corrected diffusion coefficient D was 23% greater than mean ADC (P=.002). HCC-to-liver contrast and CV of HCC were greater for K than ADC or D, although these differences were significant only for CV of HCCs (P≤.046). ADC, D and K all showed significant differences between non-, partially and completely necrotic HCCs (P≤.004). Among seven nonnecrotic HCCs, cellularity showed a strong inverse correlation with ADC (r=−0.80), a weaker inverse correlation with D (− 0.24) and a direct correlation with K (r= 0.48).

Conclusions

We observed non-Gaussian diffusion behavior for HCCs ex vivo; this DKI model may have added value in HCC characterization in comparison with a standard monoexponential model of diffusion-weighted imaging.     

Simultaneous magnetic resonance imaging of diffusion anisotropy and diffusion gradient

The theory of diffusion gradient-weighted MRI (DGWI) is presented in this paper. The Bloch-Torrey equation was modified to include the effect of intravoxel spatial-location variation of water diffusion (diffusion gradient) on MRI signal, in addition to the effect of intravoxel spatial-direction variation of water diffusion (diffusion anisotropy). An analytical solution for a diffusion-encoding spin-echo pulse sequence was derived. Unlike water diffusion which attenuates the image signal intensity, this newly derived solution relates the spatial gradient of the water diffusion with the phase of the image signal. This novel MRI technique directly measures both the water diffusion and its spatial gradient, and thus offers a noninvasive imaging tool to simultaneously investigate the intravoxel inhomogeneity and anisotropy of tissue structures. In addition, as demonstrated with our preliminary data, this new method may be utilized to delineate the interfaces of tissues with different diffusion. This method is an extension of the successful diffusion tensor MRI (DTI), but requires no additional data acquisition. In addition to the measured diffusion tensor, this new method provides measurements of the spatial derivatives of the three principal diffusivities of the tensor, thereby providing additional information for improving white matter fiber tractography.     

Evaluation of diffusion models of fiber tracts using diffusion tensor magnetic resonance imaging

Modeling of water diffusion in white matter is useful for revealing microstructure of the brain tissue and hence diagnosis and evaluation of white matter diseases. Researchers have modeled diffusion in white matter using mathematical and mechanical analysis at the cellular level. However, less work has been devoted to evaluate these models using macroscopic real data such as diffusion tensor magnetic resonance imaging (DTMRI) data. DTMRI is a noninvasive tool for evaluating white matter microstructure by measuring random motion of water molecules referred to as diffusion. It reflects directional information of microscopic structures such as fibers. Thus, it is applicable for evaluation and modification of mathematical models of white matter. Nevertheless, a realistic relation between a fiber model and imaging data does not exist. This work opens a promising avenue for relating DTMRI data to microstructural parameters of white matter. First, we propose a strategy for relating DTMRI and fiber model parameters to evaluate mathematical models in light of real data. The proposed strategy is then applied to evaluate and extend an existing model of white matter based on clinically available DTMRI data. Next, the proposed strategy is used to estimate microstructural characteristics of fiber tracts. We illustrate this approach through its application to approximation of myelin sheath thickness and fraction of volume occupied by fibers. Using sufficiently small imaging voxels, the proposed approach is capable of estimating model parameters with desirable precision.     

声图像的恢复对纹理分析参数影响的研究

本文研究了声图像的恢复对声图像纹理分析参数的影响。论文阐述了一种用于Ｂ超图像恢复的方法。它利用三个声学特性已知的超声组织仿真模块作参考,在增益与ＴＧＣ设置不变的情况下,可对均匀组织的Ｂ超图像进行恢复,论文采用了几种不同的纹理分析方法对已恢复的Ｂ超图像及未经恢复且在不同设置下采集的图像进行了分析结果的对比研究,得到了一些有实用意义的结论。     

Pediatric abdominal masses: diagnostic accuracy of diffusion weighted MRI

Purpose

To retrospectively identify apparent diffusion coefficient (ADC) values of pediatric abdominal mass lesions, to determine whether measured ADC of the lesions and signal intensity on diffusion-weighted (DW) images allow discrimination between benign and malignant mass lesions.

Materials and Methods

Approval for this retrospective study was obtained from the institutional review board. Children with abdominal mass lesions, who were examined by DW magnetic resonance imaging (MRI) were included in this study. DW MR images were obtained in the axial plane by using a non breath-hold single-shot spin-echo sequence on a 1.5-T MR scanner. ADCs were calculated for each lesion. ADC values were compared with Mann–Whitney U test. Receiver operating characteristic curve analysis was performed to determine cut-off values for ADC. The results of visual assessment on b800 images and ADC map images were compared with chi-square test.

Results

Thirty-one abdominal mass lesions (16 benign, 15 malignant) in 26 patients (15 girls, 11 boys, ranging from 2 days to 17 years with 6.9 years mean) underwent MRI. Benign lesions had significantly higher ADC values than malignant ones (P<.001). The mean ADCs of malignant lesions were 0.84±1.7×10⁻³ mm²/s, while the mean ADCs of the benign ones were 2.28±1.00×10⁻³ mm²/s. With respect to cutoff values of ADC: 1.11×10⁻³ mm²/s, sensitivity and negative predictive values were 100%, specificity was 78.6% and positive predictive value was 83.3%. For b800 and ADC map images, there were statistically significant differences on visual assessment. All malignant lesions had variable degrees of high signal intensity whereas eight of the 16 benign ones had low signal intensities on b800 images (P<.001). On ADC map images, all malignant lesions were hypointense and most of the benign ones (n=11, 68.7%) were hyperintense (P<.001).

Conclusion

DW imaging can be used for reliable discrimination of benign and malignant pediatric abdominal mass lesions based on considerable differences in the ADC values and signal intensity changes.     

A framework for voxel-based morphometric analysis of the optic radiation using diffusion tensor imaging in glaucoma

Glaucoma is an optic neuropathy affecting the entire visual system. The understanding of the glaucoma mechanism and causes remains unresolved. Diffusion tensor imaging (DTI) has been used to analyze the optic nerve and optic radiation showing global fiber abnormalities associated with glaucoma. Nevertheless, the complex structure of the optic radiation and the limitations of DTI make the localization of the glaucoma effect a difficult task. The aim of this work is to establish a framework for the determination of the local changes of the optic radiation due to glaucoma using DTI. The proposed system utilizes a semiautomated algorithm to produce an efficient identification of the optic radiation. Segmented optic radiations are transformed to a unified space using shape-based nonrigid registration. Using the deformation fields that resulted from the registration, the maps of the diffusion tensor-derived parameters are transformed to the unified space. This allows for statistical voxel-wise analysis to produce significant abnormality maps. The proposed system is applied to a group of 13 glaucoma patients and a normal control group of 10 subjects. The groups are age matched to eliminate the age effect on the analysis. Diffusion-related parameters (axial, radial and mean diffusivities) and an anisotropy index (fractional anisotropy) are studied. The anisotropy analysis indicates that the majority of the significant voxels show decreased fractional anisotropy in the glaucoma patients compared with the control group. In addition, the significant regions are mainly distributed in the middle (in reference to anterior–posterior orientation) of the optic radiation. Glaucoma subjects have increased radial diffusivity and mean diffusivity significant voxels with a main concentration in the proximal part of the right optic radiation. The proposed analysis provides a framework to capture the significant local changes of the optic radiation due to glaucoma. The preliminary analysis suggests that the glaucomatous optic radiation may suffer from localized white matter degeneration. The framework facilitates further studies and understanding of the pathophysiology of glaucoma.     

In vivo structural analysis of articular cartilage using diffusion tensor magnetic resonance imaging

Purpose

The articular cartilage is a small tissue with a matrix structure of three layers between which the orientation of collagen fiber differs. A diffusion-weighted twice-refocused spin-echo echo-planar imaging (SE-EPI) sequence was optimized for the articular cartilage, and the structure of the three layers of human articular cartilage was imaged in vivo from diffusion tensor images.

Materials and Methods

The subjects imaged were five specimens of swine femur head after removal of the flesh around the knee joint, five specimens of swine articular cartilage with flesh present and the knee cartilage of five adult male volunteers. Based on diffusion-weighted images in six directions, the mean diffusivity (MD) and the fractional anisotropy (FA) values were calculated.

Results

Diffusion tensor images of the articular cartilage were obtained by sequence optimization. The MD and FA value of the specimens (each of five examples) under different conditions were estimated. Although the articular cartilage is a small tissue, the matrix structure of each layer in the articular cartilage was obtained by SE-EPI sequence with GRAPPA. The MD and FA values of swine articular cartilage are different between the synovial fluid and saline. In human articular cartilage, the load of the body weight on the knee had an effect on the FA value of the surface layer of the articular cartilage.

Conclusion

This method can be used to create images of the articular cartilage structure, not only in vitro but also in vivo. Therefore, it is suggested that this method should support the elucidation of the in vivo structure and function of the knee joint and might be applied to clinical practice.     

Hypervascular hepatocellular carcinoma in the cirrhotic liver: diffusion-weighted imaging versus superparamagnetic iron oxide-enhanced MRI

Purpose

The purpose of the study was to validate diffusion-weighted imaging (DWI) in the assessment of hypervascular hepatocellular carcinoma (HCC) compared with superparamagnetic iron oxide (SPIO)-enhanced magnetic resonance imaging (MRI) in the cirrhotic liver.

Material and Methods

Forty-six consecutive patients with 106 hypervascular focal lesions in the cirrhotic liver who underwent DWI using three b factors and gadopentetate dimeglumine-enhanced dynamic MRI followed by SPIO-enhanced MRI were enrolled. Two independent radiologists evaluated two separated image sets (SPIO set, dynamic MRI and SPIO-enhanced T2*-weighted images; DWI set, DWI and dynamic MRI) and assigned confidence levels for diagnosis of HCC using a five-point scale for each lesion. Area under the receiver operating characteristic curve (A_z) was calculated for each image set.

Results

The A_z value of the DWI set was larger than the SPIO set by both readers (reader 1, 0.936 vs. 0.900, P=.050; reader 2, 0.938 vs. 0.905, P=.110). For the sensitivity (reader 1, 93.1% vs. 86.2%, P=.146; reader 2, 95.4% vs. 88.5%, P=.070) and specificity (reader 1, 89.5% vs. 73.7%, P=.250; reader 2, 79.0% vs. 73.7%, P=1.000) of HCC diagnosis, DWI sets were superior to SPIO sets without statistically significant differences.

Conclusion

For assessment of hypervascular HCC, DWI in combination with dynamic MRI provides comparable or slightly better information compared with the combination of dynamic and SPIO-enhanced MRI.     

Glaucoma classification based on visual pathway analysis using diffusion tensor imaging

Most of the existing methods for diagnosing glaucoma analyze the eye with a main focus on the retina, despite the transsynaptic nature of the fiber degeneration caused by glaucoma. Thus, they ignore a significant part of the visual system represented by the visual pathway in the brain. The advances in neuroimaging, especially diffusion tensor imaging (DTI), enable the identification and characterization of white matter fibers. In this work, we propose a system based on DTI analysis of the visual pathway fibers in the optic radiation for detecting and discriminating different glaucoma entities. The optic radiation is identified semi-automatically. DTI provides information about the fiber orientation as well as a set of derived parameters describing the degree of diffusion anisotropy and diffusivity. Features for each DTI derived measure are extracted from a specified region of interest on the optic radiation. The features are grouped into three sets: Histogram, co-occurrence matrices, and Laws features. For feature selection, the features are ranked using a support vector machine classifier. The highest ranked features are used for classification. A support vector machine classifier is used for classification in a 10-fold cross validation setup. The system is applied to three age-matched subjects’ categories containing 27 healthy, 39 primary open angle glaucoma (POAG), and 18 normal tension glaucoma (NTG) subjects. The discrimination accuracy between healthy and glaucoma (POAG and NTG) subjects is 94.1% with an area under the ROC of 0.97. Classification accuracy of 92.4% is obtained for the normal and the POAG groups while it increased to 100% in case of healthy and NTG groups. In addition, the system could differentiate between glaucoma types (POAG and NTG) with an accuracy of 98.3%. A complementary analysis was performed to estimate the selection bias in the obtained accuracy. The bias ranged from 10% to 20% depending on the group pair under consideration. The classification results indicate the high performance of the system compared to retina-based glaucoma detection systems. The proposed approach utilizes visual pathway analysis rather than the conventional eye analysis which presents a new trend in glaucoma detection. Analyzing the entire visual system could provide significant information that can improve the glaucoma examination flow and treatment.     

Non-Gaussian water diffusion kurtosis imaging of prostate cancer

Purpose

To evaluate the non-Gaussian water diffusion properties of prostate cancer (PCa) and determine the diagnostic performance of diffusion kurtosis (DK) imaging for distinguishing PCa from benign tissues within the peripheral zone (PZ), and assessing tumor lesions with different Gleason scores.

Materials and Methods

Nineteen patients who underwent diffusion weighted (DW) magnetic resonance imaging using multiple b-values and were pathologically confirmed with PCa were enrolled in this study. Apparent diffusion coefficient (ADC) was derived using a monoexponential model, while diffusion coefficient (D) and kurtosis (K) were determined using a DK model. Differences between the ADC, D and K values of benign PZ and PCa, as well as those of tumor lesions with Gleason scores of 6, 7 and ≥ 8 were assessed. Correlations between parameters D and K in PCa were analyzed using Pearson’s correlation coefficient. ADC, D and K values were correlated with Gleason scores of 6, 7 and ≥ 8, respectively.

Results

ADC and D values were significantly (p < 0.001) lower in PCa (0.79 ± 0.14 μm²/ms and 1.56 ± 0.23 μm²/ms, respectively) compared to benign PZ (1.23 ± 0.19 μm²/ms and 2.54 ± 0.24 μm²/ms, respectively). K values were significantly (p < 0.001) greater in PCa (0.96 ± 0.20) compared to benign PZ (0.59 ± 0.08). D and K showed fewer overlapping values between benign PZ and PCa compared to ADC. There was a strong negative correlation between D and K values in PCa (Pearson correlation coefficient r = − 0.729; p < 0.001). ADC and K values differed significantly in tumor lesions with Gleason scores of 6, 7 and ≥ 8 (p < 0.001 and p = 0.001, respectively), although no significant difference was detected for D values (p = 0.325). Significant correlations were found between the ADC value and Gleason score (r = − 0.828; p < 0.001), as well as the K value and Gleason score (r = 0.729; p < 0.001).

Conclusion

DK model may add value in PCa detection and diagnosis. K potentially offers a new metric for assessment of PCa.     

Magnetic resonance imaging follow-up of liver growth of neuroendocrine tumors in an experimental mouse model

Liver metastases in patients with gastroenteropancreatic (GEP) endocrine tumors represent the main factor of adverse prognosis in this tumor type and thus have a strong effect on the therapeutic strategies. Currently, magnetic resonance imaging (MRI) is considered the modality of choice for the noninvasive, in vivo detection of liver metastases. Dedicated MRI protocols suitable for following liver lesion evolution on an experimental model of endocrine tumors could be valuable. An experimental animal model mimicking the clinical situation of intrahepatic dissemination has been designed. The goal of this study was to characterize liver lesions in this athymic nude mouse model and assess the detection sensitivity of MRI using a physiological gating strategy optimized for high magnetic fields.     

Elevations of diffusion anisotropy are associated with hyper-acute stroke: a serial imaging study

Diffusion tensor imaging (DTI) studies of human ischemic stroke within 24 h of symptom onset have reported variable findings of changes in diffusion anisotropy. Serial DTI within 24 h may clarify these heterogeneous results. We characterized longitudinal changes of diffusion anisotropy by analyzing discrete ischemic white matter (WM) and gray matter (GM) regions during the hyperacute (2.5-7 h) and acute (21.5-29 h) scanning phases of ischemic stroke onset in 13 patients. Mean diffusivity (MD), fractional anisotropy (FA) and T2-weighted signal intensity were measured for deep and subcortical WM and deep and cortical GM areas in lesions outlined by a > or =30% decrease in MD. Average reductions of approximately 40% in relative (r) MD were observed in all four brain regions during both the hyperacute and acute phases post stroke. Overall, 9 of 13 patients within 7 h post symptom onset showed elevated FA in at least one of the four tissues, and within the same cohort, 11 of 13 patients showed reduced FA in at least one of the ischemic WM and GM regions at 21.5-29 h after stroke. The fractional anisotropy in the lesion relative to the contralateral side (rFA, mean+/-S.D.) was significantly elevated in some patients in the deep WM (1.10+/-0.11, n=4), subcortical WM (1.13+/-0.14, n=4), deep GM (1.07+/-0.06, n=1) and cortical GM (1.22+/-0.13, n=5) hyperacutely (< or =7 h); however, reductions of rFA at approximately 24 h post stroke were more consistent (rFA= 0.85+/-0.12).     

Cerebral infarction associated with moyamoya disease: histogram-based quantitative analysis of diffusion tensor imaging -- a preliminary study

Moyamoya disease (MMD) is a rare disorder of unknown etiology in which terminal portions of the internal carotid arteries become steno-occlusive, with fine collateral "moyamoya vessels" formed secondarily, resulting in serial ischemic strokes throughout its clinical course. Whole-brain histogram (WBH) of diffusion tensor imaging (WBH-DTI) is an analytical tool whose feasibility has been ascertained in various pathologies. To elucidate whether WBH-DTI could detect any difference between ischemic MMD and normal controls, we examined 27 consecutive MMD patients without hemorrhage and 48 normal controls in this prospective study using a 3.0-T magnetic resonance scanner. WBHs of fractional anisotropy (FA) (WBH-FA) and mean diffusivity (MD) (WBH-MD) were compared among three groups: Group 1, MMD patients with infarct (n=15); Group 2, MMD patients without infarct (n=12); and Group 3, normal controls (n=48). Group 1 showed significantly higher peak height and significantly lower mean value on WBH-FA, as well as significantly lower peak height and significantly higher mean value on WBH-MD, compared with Groups 2 and 3. No significant difference was seen in parameters at either WBH-FA or WBH-MD between Groups 2 and 3. These results might reflect the pathological severity of each group, and WBH-DTI could feasibly detect differences between ischemic MMD with infarction and MMD without infarction and normal controls.