Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Diffusion Tensor Imaging (DTI) is a magnetic resonance imaging (MRI) modality which can significantly improve our understanding of the brain structures and neural connectivity. DTI measures are thought to be representative of brain tissue microstructure and are particularly useful for examining organized brain regions, such as white matter tract areas. DTI measures the water diffusion tensor using diffusion weighted pulse sequences which are sensitive to microscopic random water motion. The resulting diffusion weighted images (DWI) display and allow quantification of how water diffuses along axes or diffusion encoding directions. This can help to measure and quantify the tissue’s orientation and structure, making it an ideal tool for examining cerebral white matter and neural fiber tracts. In this chapter the authors discuss the theoretical aspects of DTI, the information that can be extracted from DTI data, and the use of the extracted information for the reconstruction of fiber tracts and the diagnosis of a disease. In addition, a review of known fiber tracking algorithms is presented.

Objective Astrocytic tumors in motor area often grow infihratively with worse outcome. It is significant to identify the tumor infiltrating field before the operation to improve the outcome of surgery. Diffusion tensor imaging(DTI) is an advanced quantitative form of diffusion-weighted imaging. The study is to discuss the clinical application of DTI in identifying, forecasting the grades of astrocytoma and choosing the best procedure for resecting astrocytoma. Method The clinical data of consecutive 33 patients with astrocytoma in motor function area underwent DTI examination before the operation. Results Compared with normal brain tissue, significant differences of ADC and FA were found in solid area of astrocytoma necrotic region, edema region(P<0.05). Significant differences of ADC were also found in solid tumor compared with necrotic region and edema region respectively(P<0.05). By the imaging guidance of DTI, we could show white matter fiber tracts of the motor area and evaluate the relationship between astrocytoma and white matter fiber for the operation. Conclusions ADC and FA can be used to differentiate normal brain tissue from astrocytoma. According to the change of white matter fiber tracts around the tumors in DTT, we could optimize the operational project and improve the resection of astrocytoma significantly, as well as to decrease potential disability after operation. Key words: Astrocytoma; Diffusion magnetic resonance imaging

ObjectiveTo explore the value of quantitative parameters derived from diffusion spectrum imaging (DSI) in preoperatively predicting human epidermal growth factor receptor 2 (HER2) status in patients with breast cancer.MethodsIn this prospective study, 114 and 56 female patients with invasive ductal carcinoma were consecutively included in a derivation cohort and an independent validation cohort, respectively. Each patient was categorized into HER2-positive or HER2-negative groups based on the pathologic result. All patients underwent DSI and conventional MRI including dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted imaging (DWI). The tumor size, type of the time-signal intensity curve (TIC) from DCE-MRI, apparent diffusion coefficient (ADC) from DWI, and quantitative parameters derived from DSI, including diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), mean apparent propagator (MAP), and neurite orientation dispersion and density imaging (NODDI) of primary tumors, were measured and compared between the HER2-positive and HER2-negative groups in the derivation cohort. Univariable and multivariable logistic regression analyses were used to determine the potential independent predictors of HER2 status. The discriminative ability of quantitative parameters was assessed by receiver operating characteristic (ROC) curve analyses and validated in the independent cohort.ResultsIn the derivation cohort, the tumor size, TIC type, and ADC values did not differ between the HER2-positive and HER2-negative groups (p = 0.126–0.961). DSI quantitative parameters including axial kurtosis of DKI (DKI_AK), non-Gaussianity (MAP_NG), axial non-Gaussianity (MAP_NGAx), radial non-Gaussianity (MAP_NGRad), return-to-origin probability (MAP_RTOP), return-to-axis probability of MAP (MAP_RTAP), and intracellular volume fraction of NODDI (NODDI_ICVF) were lower in the HER2-positive group than in the HER2-negative group (p ≤ 0.001–0.035). DSI quantitative parameters including radial diffusivity (DTI_RD), mean diffusivity of DTI (DTI_MD), mean squared diffusion (MAP_MSD), and q-space inverse variance of MAP (MAP_QIV) were higher in the HER2-positive group than in the HER2-negative group (p = 0.016–0.049). The ROC analysis showed that the area under the curve (AUC) of ADC was 0.632 and 0.568, respectively, in the derivation and validation cohorts. The AUC values of DSI quantitative parameters ranged from 0.628 to 0.700 and from 0.673 to 0.721, respectively, in the derivation and validation cohorts. Logistic regression analysis showed that only NODDI_ICVF was an independent predictor of HER2 status (p = 0.001), with an AUC of 0.700 and 0.721, respectively, in the derivation and validation cohorts.ConclusionsDSI could be helpful for preoperative prediction of HER2, but DSI alone may not be sufficient in predicting HER2 status preoperatively in patients with breast cancer.

Diffusion tensor (DT) imaging tractography is increasingly used to map fiber tracts in patients with surgical brain lesions to reduce the risk of postoperative functional deficit. There are few validation studies of DT imaging tractography in these patients. The aim of this study was to compare DT imaging tractography of language fiber tracts by using intraoperative subcortical electrical stimulations. The authors included 10 patients with low-grade gliomas or dysplasia located in language areas. The MR imaging examination included 3D T1-weighted images for anatomical coregistration, FLAIR, and DT images. Diffusion tensors and fiber tracts were calculated using in-house software. Four tracts were reconstructed in each patient including the arcuate fasciculus, the inferior occipitofrontal fasciculus, and 2 premotor fasciculi (the subcallosal medialis fiber tract and cortical fibers originating from the medial and lateral premotor areas). The authors compared fiber tracts reconstructed using DT imaging with those evidenced using intraoperative subcortical language mapping. Seventeen (81%) of 21 positive stimulations were concordant with DT imaging fiber bundles (located within 6 mm of a fiber tract). Four positive stimulations were not located in the vicinity of a DT imaging fiber tract. Stimulations of the arcuate fasciculus mostly induced articulatory and phonemic/syntactic disorders and less frequently semantic paraphasias. Stimulations of the inferior occipitofrontal fasciculus induced semantic paraphasias. Stimulations of the premotor-related fasciculi induced dysarthria and articulatory planning deficit. There was a good correspondence between positive stimulation sites and fiber tracts, suggesting that DT imaging fiber tracking is a reliable technique but not yet optimal to map language tracts in patients with brain lesions. Negative tractography does not rule out the persistence of a fiber tract, especially when invaded by the tumor. Stimulations of the different tracts induced variable language disorders that were specific to each fiber tract.

In this paper, we present a novel set of features which mainly comprises Fourier descriptors to facilitate the classification of white matter (WM) fiber tracts reconstructed from diffusion tensor imaging (DTI) tractography. Particularly, Fourier descriptors composing the feature vectors are different frequency terms of the discrete Fourier transform of the Euclidean coordinates of the step points of WM fiber tracts. This approach can effectively reduce the computing cost in WM fiber tract classification due to the decreased feature vector dimensionality. As integrals, Fourier descriptor features make the algorithm less sensitive to DTI noise. The fact that Fourier descriptors achieve spatial independent representation and normalization of WM fiber tracts makes it useful for group studies of WM fiber tracts. Specially, a new strategy for using Fourier descriptors is proposed. Experimental results with real datasets show that this technique is feasible and may be an alternative to existing approaches.

In this chapter, we present methods to analyze three types of diffusion-weighted imaging (DWI), i.e., diffusion tensor imaging (DTI), Q-ball imaging (QBI), and diffusion spectrum imaging (DSI). DWI is one of the methods to measure water diffusion in tissues. It provides unique biologically and clinically relevant information that is not available from other imaging modalities. Because of its noninvasive nature, DWI has been applied widely in many studies, including but not limited to fiber tracts in cerebral cortex. We will begin with the physical background of diffusion MRI (dMRI), and then we will present method to compute the apparent diffusion coefficient (ADC) map and the eigenvalues for DTI study. After that, we introduce the measures for the water diffusion anisotropy and give one example fiber tractography method using DTI.

Objective To explore facial emotion cognition character and the correlation to frontal lobe white matter fiber tracts in first-episode of schizophrenia patients in comparison with healthy control. Method The diffusion tensor imaging data were obtained from 56 patients with untreated first-episode schizophrenia and 30 healthy controls subjects. Fiber tracking was performed in the whole cerebral cortex of brain. The parameter of impairment white matter fiber tracts were obtained,such as fractional anisotropy, mean diffusivity, radial diffusivity, axial diffusivity. Computer-based facial emotion cognition test was used to evaluate difference of facial emotion identification. The correlation between ability of identifying ambiguous emotion and the parameter of impairment white matter fiber tracts, and the correlation between ability of identifying ambiguous emotion and PANSS scale were explored by linear correlation analysis. Result (1) Between patients and healthy control, there was no significant difference in the proportion of recognition as happy emotion to mixture of 50% happy emotion plus 50% angry emotion. In patients group, the number of regarding 100% happy emotion plus 0 angry emotion (9.96±2.42) and regarding 75% happy emotion plus 25% angry emotion (9.91±2.33) both as happy emotion were significantly lower than the healthy control (11.40±1.48, 11.30±1.44; t=-3.332, -3.325; all P<0.01).The number of regarding 25% happy emotion and 75% angry emotion as happy emotion(2.24±2.57), and the number of regarding 0 happy emotion and 100% angry emotion as happy emotion(1.78±2.66) were higher than healthy control(0.83±2.21, 0.70±2.02; t=2.537, 2.056; P<0.05 or P<0.01). The total response time for all images on screen was significantly longer than healthy control(t=6.441, P<0.01).(2)There are five relative serious fiber tracts impaired. Patients with schizophrenia were demonstrated lower activation in right dorsolateral frontal gyru, right inferior frontal operculum,right medial frontal gyrus, left precentral gyrus, left olfactory cortex (t=-2.993 0-2.830 0, P<0.01 or P<0.05), in comparison with healthy controls, except FA value of right inferior frontal operculum and AD value of left precentral gyrus were found higher in patients group. (3) There was no correlation between identifying facial emotion and PANSS. (4)The correlation between identifying ambiguous emotion and the parameter of impairment or white matter fiber tracts was explored by linear correlation analysis, which found FA value of left precentral gyrus positively correlated to the number of identifying happy emotion from 25% happy emotion plus 75% angry emotion (r=0.362, P=0.007), and from 0 happy emotion plus 100% angry emotion (r=0.476, P=0.000). Conclusion This study suggests that schizophrenia patients could not identify facial emotion accurately and their white matter fiber tracts in the frontal lobe are damaged significantly. The impairment of facial emotion recognition is correlated with the abnormality of white matter fiber tracts. Key words: Schizophrenia; Cognition; Frontal lobe; White matter fiber tracts

Based on Brownian motion, diffusion statement of proton hydro inside body is one of the most important variables affected on the diagnosis, treatment planning, and disease response to treatment. There are some different kinds of diffusion-weighted magnetic resonance imaging types such as diffusion-weighted imaging, diffusion tensor imaging, diffusion kurtosis imaging, intravoxel incoherent motion imaging, zoom diffusion imaging, and diffusion spectrum imaging. In this short communication, we aimed to introduce clinical applications of these diffusion-weighted magnetic resonance imaging types.

We applied a novel diffusion spectrum imaging (DSI) acquisition to determine associations between aging and subcortical fiber tract integrity. We studied 35 cognitively healthy subjects (17 women), spanning the adult age range between 23 and 77 years, using anatomical MRI and a novel DSI acquisition scheme at 3 Tesla. The study was approved by the local institutional review board. DSI data were analyzed using tractography and complementary voxel-based analysis of generalized fractional anisotropy (GFA) maps. We determined the effects of age on generalized fractional anisotropy in selected fiber tracts as well as in a whole brain voxel-based analysis. For comparison, we studied the effects of age on regional gray and white matter volumes. We found a significant reduction in anterior corpus callosum fiber tract integrity with age (P < 0.001), as well as significant GFA reduction throughout the subcortical white matter (P < 0.05, false discovery rate [FDR] corrected). GFA decline was accompanied by significant gray matter atrophy in frontal and temporal association cortex (P < 0.05, FDR corrected). Our data suggest that normal aging leads to a regionally specific decline in fiber tract integrity. DSI may become a useful biomarker in healthy and pathological aging.

A diffusion-weighted (DW) template in a standard coordinate system is often necessary for the analysis of white matter (WM) structures using DW images. Although several DW templates have been constructed in the ICBM-152 space, a template for diffusion spectrum imaging (DSI) is still lacking. In this study, we developed a DSI template in the ICBM-152 space from 122 healthy adults. This high quality template, NTU-DSI-122, was built through incorporating the macroscopic anatomical information using high-resolution T1 -weighted images and the microscopic structural information obtained from DSI datasets. Two evaluations were conducted to examine the quality of NTU-DSI-122. The first evaluation examined the anatomical consistency of NTU-DSI-122 in matching to the ICBM-152 coordinate system. The results showed that this template matched to the ICBM-152 templates very well across the whole brain, not only in the deep white matter regions as other DW templates but also in the superficial white matter regions. In the second evaluation, a large number of independent diffusion tensor imaging (DTI) datasets were registered to the DTI template derived from NTU-DSI-122. The examination was performed by quantifying the anatomical consistency among the registered DTI datasets. The results showed that using NTU-DSI-122 as the registration template the registered DTI datasets can achieve high anatomical alignment. Both evaluations demonstrate that NTU-DSI-122 is a useful high quality DW template. Therefore, NTU-DSI-122 can serve as a representative DSI dataset for a healthy adult population, and will be of potential value for brain research and clinical applications. The NTU-DSI-122 template is available at http://www.nitrc.org/projects/ntu-dsi-122/.

It is said that knowledge doubles every 2.5 years. In the field of diagnostic imaging the doubling time is probably shorter due to the rapid pace of technological advances. Diffusion tensor imaging (DTI) and its potential application to neurologic disease represents one such advance. DTI is a special form of diffusion-weighted imaging that allows the assessment and visualization of large white matter fibers on a millimeter-level multidimensional scale.1 Although we can visualize and differentiate white and gray matter with standard MRI pulse sequences, they do not allow us to examine the integrity or directionality of white matter tracts. DTI takes advantage of the diffusivity of water and the restrictions imposed on the diffusion of water by white matter fiber tracts. When fiber tracts are dense, for example, the restriction imposed by their density leads to directionally dependent or anisotropic diffusion. By analogy, if an ink drop is placed in a narrow or oval tube the diffusion of that ink drop will adjust to the shape of the tube. In contrast, if a drop of ink is placed in a large bowl of water the drop of ink will be more spherical …

Primary brain tumors comprise 28% of all tumors and 80% of malignant tumors. Pathophysiology of high-grade gliomas includes significant distortion of white matter architecture, necrosis, the breakdown of the blood brain barrier, and increased intracranial pressure. Diffusion tensor imaging (DTI), a diffusion weighted imaging technique, can be used to assess white matter architecture. Use of DTI as a non-invasive pathophysiological tool to analyze glioma impact on white matter microstructure has yet to be fully explored.Preliminary assessment of DTI tractography was done as a measure of intracranial tumor impact on white matter architecture. Specifically, we addressed three questions: 1) whether glioma differentially affects local white matter structure compared to metastasis, 2) whether glioma affects tract integrity of major white matter bundles, 3) whether glioma lobe localization affects tract integrity of different white matter bundles.In this study, we retrospectively investigated preoperative DTI scans from 24 patients undergoing tumor resection. Fiber tractography was estimated using a deterministic fiber tracking algorithm in DSI (diffusion spectrum imaging) Studio. The automatic anatomical labeling (AAL) atlas was used to define the left and right (L/R) hemisphere regions of interest (ROI). In addition, the John Hopkins University (JHU) White Matter Atlas was used to auto-segment major white matter bundle ROIs. For all tracts derived from ROI seed targets, we computed the following parameters: tract number, tract length, fractional anisotropy (FA), axial diffusivity (AD), mean diffusivity (MD), and radial diffusivity (RD).The DTI tractography analysis revealed that white matter integrity in the hemisphere ipsilateral to intracranial tumor was significantly compromised compared to the control contralateral hemisphere. No differences were observed between high vs low-grade gliomas, however, gliomas induced significantly greater white matter degradation than metastases. In addition, targeted analysis of major white matter bundles important for sensory/motor function (i.e., corticospinal tract and superior longitudinal fasciculus) revealed tract-parameter specific susceptibility due to the presence of the tumor. Finally, major tract bundles were differentially affected based on lobar localization of the glioma.These DTI-based tractographic analyses complement findings from gross histopathological examination of glioma impact on neural tissue. Global and focal white matter architecture, ipsilateral to glioma, shows higher rates of degradation or edema – based on DTI tractographic metrics – in comparison to normal brain or metastases. Gliomas, which arise in the parietal lobe, also have a higher negative impact (potentially due to increased edema) on white matter integrity of the superior longitudinal fasciculus(SLF) than those which arise in the frontal lobe. Future studies will focus on using preoperative and postoperative tractography to predict functional deficits following resective surgery.

Multiple ring-enhancing lesions in the brain

Introduction We present the first study in literature that documents the changes in diffusion tensor imaging (DTI) indices and tractography after surgical decompression in patients with cervical myelopathy. DTI, an established tool for tracking nerve fibers in brain, is now widely evaluated for its usefulness in spine pathologies. Although there are many studies directly comparing DTI indices of control and cervical myelopathic patients, there are no studies that have evaluated the prognostic applicability of DTI indices. The present study analyzes the pre- and postdecompression DTI indices and tractography in cervical myelopathic patients and its prognostic value. Materials and Methods Total 56 subjects including 16 cervical myelopathy patients who required surgical decompression (mean age: 53.5 ± 12.3 years, males: 15, females: (1) and forty normal controls (mean age: 38.18 ± 13.74 years, males: 20, females: 20) were included in the study. DTI of cervical spine was obtained using an axial single shot echo-planar parallel diffusion-weighted imaging sequence in a 1.5 tesla magnetic resonance imaging (MRI). Apparent diffusion coefficient (ADC), fractional anisotropy (FA), and Eigen values (E1, E2, and E3) were obtained at each region of interest (cervical disk level) from C1-C2 to C7-T1. The DTI indices of myelopathic patients were compared with normal volunteers after matching was done based on sex, cord level, and cord size. Postoperatively, the patients were followed up after 6 months and DTI scan was performed again. The clinical improvement and the DTI indices observed at the follow-up were compared with the preoperative values. Results Analysis showed significant differences between the controls and patients in all the indices (p&lt;0.05) at the site of compression. At the compressed levels, FA decreased while all the other indices increased as compared to the controls. The mean DTI indices of myelopathic patients before surgery at the sites of spinal cord compression were as follows: FA (0.49 ± 0.092), ADC (1.8 ± 0.32 µm2/ms), E1 (2.80 ± 0.44 µm2/ms), E2 (1.63 ± 0.45 µm2/ms), E3 (0.95 ± 0.23 µm2/ms). The average DTI indices of matched controls were as follows: FA (0.55 ± 0.033), ADC (1.47 ± 0.066 µm2/ms), E1 (2.49 ± 0.150 µm2/ms), E2 (1.16 ± 0.050 µm2/ms), E3 (0.77 ± 0.058 µm2/ms. The Nurick grading distribution in patients before surgery was as follows: Grade 2 = 2, Gr 3 = 8, Gr 4 = 2, Gr 5 = 4. Postoperatively, all the patients had improvement of neurology by at least one Nurick grade except for one patient who had no improvement. The Nurick grading distribution in patients during 6 months follow-up after surgery was as follows: Grade 0 = 3, Gr 1 = 6, Gr 2 = 2, Gr 3 = 3, Gr 4 = 2. Mean postoperative values of ADC, E1, and E2 showed improvement towards normal values especially in patients with preoperative Nurick grade 2 and 3 (Table 1). Patients with Nurick grade 4 and 5 did not show any significant change. The mean FA and E3 values worsened when compared to preoperative DTI indices. The postoperative DTI indices for the patients who had neurological improvement are as follows: FA (0.45 ± 0.087), ADC (1.73 ± 0.31 µm2/ms), E1 (2.59 ± 0.28 µm2/ms), E2 (1.56 ± 0.38 µm2/ms), E3 (1.07 ± 0.31 µm2/ms. Tractography also showed interruption of nerve fibre tract continuity at the level of severe compression in patients with myelopathy. At levels of moderate compression over the spinal cord, the changes in direction of nerve fibres due to bulging disc-osteophytes were evident as changes in color coding of the tracts. After surgical decompression, the restitution of fibre tract pathways was clearly demonstrated in DT tractography. Conclusion For the first time, the prognostic applicability of DTI by comparing pre- and postoperative indices of cervical myelopathy patients has been described. All preoperative DTI indices at compressed levels showed significant differences from controls indicating abnormality in neuronal integrity. All but one of the patients showed clinical improvement at 6 months. The postoperative DTI values (ADC, E1 and E2) of patients with Nurick grading 2 and 3 were observed to approach normal values indicating restoration of linear diffusion in neuronal tracts. DTI indices in patients with Nurick grade 4 and 5 remained same or worsened more. This could probably indicate persistent axonal damage. At 6 months postsurgery, DTI indices show evidence of improvement towards normal values, even though the values did not match the true extent of clinical improvement. Further DTI evaluation at 12 months and 2 years is required to analyze the extent of usefulness of DTI indices in evaluating cervical myelopathy. The results suggest that DTI indices, especially ADC and Eigen vectors can be promising indicators in the evaluation and prognostic assessment of myelopathy patients. I confirm having declared any potential conflict of interest for all authors listed on this abstract Yes Disclosure of Interest None declared

Denoising and fast diffusion imaging with physically constrained sparse dictionary learning