Estimation of Fiber Orientations Using Neighborhood Information

Data from diffusion magnetic resonance imaging (dMRI) can be used to reconstruct fiber tracts, for example, in muscle and white matter. Estimation of fiber orientations (FOs) is a crucial step in the reconstruction process and these estimates can be corrupted by noise. In this paper, a new method called Fiber Orientation Reconstruction using Neighborhood Information (FORNI) is described and shown to reduce the effects of noise and improve FO estimation performance by incorporating spatial consistency. FORNI uses a fixed tensor basis to model the diffusion weighted signals, which has the advantage of providing an explicit relationship between the basis vectors and the FOs. FO spatial coherence is encouraged using weighted l1-norm regularization terms, which contain the interaction of directional information between neighbor voxels. Data fidelity is encouraged using a squared error between the observed and reconstructed diffusion weighted signals. After appropriate weighting of these competing objectives, the resulting objective function is minimized using a block coordinate descent algorithm, and a straightforward parallelization strategy is used to speed up processing. Experiments were performed on a digital crossing phantom, ex vivo tongue dMRI data, and in vivo brain dMRI data for both qualitative and quantitative evaluation. The results demonstrate that FORNI improves the quality of FO estimation over other state of the art algorithms.Comment: Journal paper accepted in Medical Image Analysis. 35 pages and 16 figure

Real-Time Magnetic Resonance Imaging

Real‐time magnetic resonance imaging (RT‐MRI) allows for imaging dynamic processes as they occur, without relying on any repetition or synchronization. This is made possible by modern MRI technology such as fast‐switching gradients and parallel imaging. It is compatible with many (but not all) MRI sequences, including spoiled gradient echo, balanced steady‐state free precession, and single‐shot rapid acquisition with relaxation enhancement. RT‐MRI has earned an important role in both diagnostic imaging and image guidance of invasive procedures. Its unique diagnostic value is prominent in areas of the body that undergo substantial and often irregular motion, such as the heart, gastrointestinal system, upper airway vocal tract, and joints. Its value in interventional procedure guidance is prominent for procedures that require multiple forms of soft‐tissue contrast, as well as flow information. In this review, we discuss the history of RT‐MRI, fundamental tradeoffs, enabling technology, established applications, and current trends

Cardiac magnetic resonance assessment of central and peripheral vascular function in patients undergoing renal sympathetic denervation as predictor for blood pressure response

Background: Most trials regarding catheter-based renal sympathetic denervation (RDN) describe a proportion of patients without blood pressure response. Recently, we were able to show arterial stiffness, measured by invasive pulse wave velocity (IPWV), seems to be an excellent predictor for blood pressure response. However, given the invasiveness, IPWV is less suitable as a selection criterion for patients undergoing RDN. Consequently, we aimed to investigate the value of cardiac magnetic resonance (CMR) based measures of arterial stiffness in predicting the outcome of RDN compared to IPWV as reference. Methods: Patients underwent CMR prior to RDN to assess ascending aortic distensibility (AAD), total arterial compliance (TAC), and systemic vascular resistance (SVR). In a second step, central aortic blood pressure was estimated from ascending aortic area change and flow sequences and used to re-calculate total arterial compliance (cTAC). Additionally, IPWV was acquired. Results: Thirty-two patients (24 responders and 8 non-responders) were available for analysis. AAD, TAC and cTAC were higher in responders, IPWV was higher in non-responders. SVR was not different between the groups. Patients with AAD, cTAC or TAC above median and IPWV below median had significantly better BP response. Receiver operating characteristic (ROC) curves predicting blood pressure response for IPWV, AAD, cTAC and TAC revealed areas under the curve of 0.849, 0.828, 0.776 and 0.753 (p = 0.004, 0.006, 0.021 and 0.035). Conclusions: Beyond IPWV, AAD, cTAC and TAC appear as useful outcome predictors for RDN in patients with hypertension. CMR-derived markers of arterial stiffness might serve as non-invasive selection criteria for RDN

Impulsivity Relates to Relative Preservation of Mesolimbic Connectivity in Patients with Parkinson Disease.

IntroductionThe relationship between Parkinson Disease (PD) pathology, dopamine replacement therapy (DRT), and impulse control disorder (ICD) development is still incompletely understood. Given the sensorimotor-lateral substantia nigra (SN) selective degeneration associated with PD, we posit that a relative sparing of the limbic-medial SN in the context of DRT drives impulsive, reward-seeking behavior in PD patients with recent history of severe impulsivity.MethodsImpulsive and control participants were selected from a consecutive list of PD patients receiving pre-operative deep brain stimulation (DBS) planning scans including 3T structural MRI and 64 direction diffusion tensor imaging (DTI). Using previously identified substantia nigra (SN) subsegment network connectivity profiles to develop classification targets, split-hemisphere target-based SN segmentation with probabilistic tractography was performed. The relative subsegment volumes and strength of connectivity between the SN and the limbic, associative, and motor network targets were compared.ResultsOur results show that there is greater probability of connectivity between the SN and limbic network targets relative to motor and associative network targets in PD patients with recent history of severe impulsivity as compared to PD patients without impulsivity (P = 0.0075). We did not observe relative volumetric subsegment differences across groups.ConclusionFirstly, our results suggest that fine-grained, atlas-derived classification targets may be used in PD to parcellate and classify functionally distinct subsegments of the SN, with the apparent preservation of previously reported topographical limbic-medial SN, associative-ventral SN, and sensorimotor-lateral SN orientation. We suggest that relative, as opposed to absolute, degeneration amongst SN-associated dopaminergic networks relates to the impulsivity phenotype in PD

Comparison of Super Resolution Reconstruction Acquisition Geometries for Use in Mouse Phenotyping

3D isotropic imaging at high spatial resolution (30–100 microns) is important for comparing mouse phenotypes. 3D imaging at high spatial resolutions is limited by long acquisition times and is not possible in many in vivo settings. Super resolution reconstruction (SRR) is a postprocessing technique that has been proposed to improve spatial resolution in the slice-select direction using multiple 2D multislice acquisitions. Any 2D multislice acquisition can be used for SRR. In this study, the effects of using three different low-resolution acquisition geometries (orthogonal, rotational, and shifted) on SRR images were evaluated and compared to a known standard. Iterative back projection was used for the reconstruction of all three acquisition geometries. The results of the study indicate that super resolution reconstructed images based on orthogonally acquired low-resolution images resulted in reconstructed images with higher SNR and CNR in less acquisition time than those based on rotational and shifted acquisition geometries. However, interpolation artifacts were observed in SRR images based on orthogonal acquisition geometry, particularly when the slice thickness was greater than six times the inplane voxel size. Reconstructions based on rotational geometry appeared smoother than those based on orthogonal geometry, but they required two times longer to acquire than the orthogonal LR images

High-resolution three-dimensional hybrid MRI + low dose CT vocal tract modeling:A cadaveric pilot study

SummaryObjectivesMRI based vocal tract models have many applications in voice research and education. These models do not adequately capture bony structures (e.g. teeth, mandible), and spatial resolution is often relatively low in order to minimize scanning time. Most MRI sequences achieve 3D vocal tract coverage at gross resolutions of 2 mm3 within a scan time of <20 seconds. Computed tomography (CT) is well suited for vocal tract imaging, but is infrequently used due to the risk of ionizing radiation. In this cadaveric study, a single, extremely low-dose CT scan of the bony structures is blended with accelerated high-resolution (1 mm3) MRI scans of the soft tissues, creating a high-resolution hybrid CT-MRI vocal tract model.MethodsMinimum CT dosages were determined and a custom 16-channel airway receiver coil for accelerated high (1 mm3) resolution MRI was evaluated. A rigid body landmark based partial volume registration scheme was then applied to the images, creating a hybrid CT-MRI model that was segmented in Slicer.ResultsUltra-low dose CT produced images with sufficient quality to clearly visualize the bone, and exposed the cadaver to 0.06 mSv. This is comparable to atmospheric exposures during a round trip transatlantic flight. The custom 16-channel vocal tract coil produced acceptable image quality at 1 mm3 resolution when reconstructed from ∼6 fold undersampled data. High (1 mm3) resolution MR imaging of short (<10 seconds) sustained sounds was achieved. The feasibility of hybrid CT-MRI vocal tract modeling was successfully demonstrated using the rigid body landmark based partial volume registration scheme. Segmentations of CT and hybrid CT-MRI images provided more detailed 3D representations of the vocal tract than 2 mm3 MRI based segmentations.ConclusionsThe method described in this study indicates that high-resolution CT and MR image sets can be combined so that structures such as teeth and bone are accurately represented in vocal tract reconstructions. Such scans will aid learning and deepen understanding of anatomical features that relate to voice production, as well as furthering knowledge of the static and dynamic functioning of individual structures relating to voice production