Yoshitaka Masutani

Evaluation of glymphatic system activity with the diffusion MR technique: diffusion tensor image analysis along the perivascular space (DTI-ALPS) in Alzheimer's disease cases

PurposeThe activity of the glymphatic system is impaired in animal models of Alzheimer’s disease (AD). We evaluated the activity of the human glymphatic system in cases of AD with a diffusion-based technique called diffusion tensor image analysis along the perivascular space (DTI-ALPS).Materials and methodsDiffusion tensor images were acquired to calculate diffusivities in the x, y, and z axes of the plane of the lateral ventricle body in 31 patients. We evaluated the diffusivity along the perivascular spaces as well as projection fibers and association fibers separately, to acquire an index for diffusivity along the perivascular space (ALPS-index) and correlated them with the mini mental state examinations (MMSE) score.ResultsWe found a significant negative correlation between diffusivity along the projection fibers and association fibers. We also observed a significant positive correlation between diffusivity along perivascular spaces shown as ALPS-index and the MMSE score, indicating lower water diffusivity along the perivascular space in relation to AD severity.ConclusionActivity of the glymphatic system may be evaluated with diffusion images. Lower diffusivity along the perivascular space on DTI-APLS seems to reflect impairment of the glymphatic system. This method may be useful for evaluating the activity of the glymphatic system.

Automatic detection of over 100 anatomical landmarks in medical CT images: A framework with independent detectors and combinatorial optimization

&NA; An automatic detection method for 197 anatomically defined landmarks in computed tomography (CT) volumes is presented. The proposed method can handle missed landmarks caused by detection failure, a limited imaging range and other problems using a novel combinatorial optimization framework with a two‐stage sampling algorithm. After a list of candidates is generated by each landmark detector, the best combination of candidates is searched for by a combinatorial optimization algorithm using a landmark point distribution model (L‐PDM) to provide prior knowledge. Optimization is performed by simulated annealing and iterative Gibbs sampling. Prior to each cycle of Gibbs sampling, another sampling algorithm is processed to estimate the spatial distribution of each target landmark, so that landmark positions without any correct detector‐derived candidates can be estimated. The proposed method was evaluated using 104 CT volumes with various imaging ranges. The overall average detection distance error was 6.6 mm, and 83.8, 93.2 and 96.5% of landmarks were detected within 10, 15 and 20 mm from the ground truth, respectively. The proposed method worked even when most of the landmarks were outside of the imaging range. The identification accuracy of the vertebral centroid was also evaluated using public datasets and the proposed method could identify 70% of vertebrae including severely diseased ones. From these results, the feasibility of our framework in detecting multiple landmarks in various CT datasets was validated. HighlightsNovel landmark detection framework for over 100 anatomical landmarks.Handling missing landmarks caused by detection failure or a limited imaging range.Estimation of the positions of missing landmarks.A stochastic model of a general landmark detector.Validation with various CT datasets, e.g. different imaging ranges. Graphical abstract Figure. Image, graphical abstract

Computer-Assisted Detection of Cerebral Aneurysms in MR Angiography in a Routine Image-Reading Environment: Effects on Diagnosis by Radiologists

BACKGROUND AND PURPOSE: Experiences with computer-assisted detection of cerebral aneurysms in diagnosis by radiologists in real-life clinical environments have not been reported. The purpose of this study was to evaluate the usefulness of computer-assisted detection in a routine reading environment. MATERIALS AND METHODS: During 39 months in a routine clinical practice environment, 2701 MR angiograms were each read by 2 radiologists by using a computer-assisted detection system. Initial interpretation was independently made without using the detection system, followed by a possible alteration of diagnosis after referring to the lesion candidate output from the system. We used the final consensus of the 2 radiologists as the reference standard. The sensitivity and specificity of radiologists before and after seeing the lesion candidates were evaluated by aneurysm- and patient-based analyses. RESULTS: The use of the computer-assisted detection system increased the number of detected aneurysms by 9.3% (from 258 to 282). Aneurysm-based analysis revealed that the apparent sensitivity of the radiologists diagnoses made without and with the detection system was 64% and 69%, respectively. The detection system presented 82% of the aneurysms. The detection system more frequently benefited radiologists than being detrimental. CONCLUSIONS: Routine integration of computer-assisted detection with MR angiography for cerebral aneurysms is feasible, and radiologists can detect a number of additional cerebral aneurysms by using the detection system without a substantial decrease in their specificity. The low confidence of radiologists in the system may limit its usefulness.

Alterations of the optic pathway between unilateral and bilateral optic nerve damage in multiple sclerosis as revealed by the combined use of advanced diffusion kurtosis imaging and visual evoked potentials

OBJECTIVESnWe investigated changes in the optic tract and optic radiation in patients with multiple sclerosis (MS) by comparing unilateral and bilateral optic nerve damage assessed based on visual evoked potentials (VEPs) using advanced diffusion MR metrics.nnnMETHODSnIn 21 MS patients, diffusion MRI was performed. Maps of fractional anisotropy, apparent diffusion coefficient (ADC), and mean kurtosis (MK) were computed. On the basis of the P100 latency in VEPs, the MS patients were divided into three groups: bilateral (n=7), unilateral (n=7), and no abnormality (n=7). Their optic tracts and optic radiations were analyzed with diffusion MRI-based fiber tracking. We also investigated the correlations between diffusion parameters and VEPs (n=21).nnnRESULTSnIn the optic tract, the diffusion changes in each of the three groups showed step-like changes. The diffusion changes in the optic radiations of the unilateral group were similar to those in the normal VEP group. Only the bilateral group showed significantly higher ADC and lower MK relative to the other two groups (P<0.05, Steel-Dwass multiple-comparison test). A significant positive correlation between VEP latency and ADC and a significant negative correlation between VEP latency and MK were observed (P<0.01, Spearmans correction).nnnCONCLUSIONSnWe first evaluated the relationship between VEPs and DKI and concluded that the lateral geniculate nucleus may compensate for unilateral damage in the pre-geniculate optic pathway via neural plasticity.

Time Course of Diffusion Kurtosis in Cerebral Infarctions of Transient Middle Cerebral Artery Occlusion Rat Model.

OBJECTIVEnTo evaluate the relationship between fiber bundle direction and changes in diffusion kurtosis, we evaluated the apparent diffusion kurtosis coefficients (AKCs) that were perpendicular to and parallel to the principal diffusion tensor eigenvector.nnnMATERIALS AND METHODSnAdult male Wistar rats were subjected to 30 or 60 minutes of middle cerebral artery occlusion and imaged with a 7T Magnetic Resonance Imager System (Varian MRI System 7T/210: Agilent Technologies, CA). Diffusion kurtosis images were obtained before middle cerebral artery (MCA) reperfusion and 3, 6, and 24 hours after reperfusion to generate the apparent diffusion coefficient (ADC), fractional anisotropy (FA), mean apparent diffusion kurtosis coefficient (mAKC), AKC axial to the eigenvector (axAKC), and AKC radial to the eigenvector (radAKC) images. The time course of the region/normal ratio was evaluated for the above parameters in the caudoputamen and white matter.nnnRESULTSnRelative FA and relative ADC values decreased 3 hours after MCA reperfusion and remained decreased until 24 hours. Relative mAKC, axAKC, and radAKC values were increased 3 hours after MCA reperfusion, peaked after 6 hours, and slightly decreased after 24 hours. In the white matter, axAKC showed larger changes than radAKC.nnnCONCLUSIONnThe time course of the diffusion kurtosis value showed earlier pseudonormalization than the ADC value of the lesions. For white matter lesions, the increase in axAKC was larger than that in radAKC, suggesting that the tissue changes after infarction mainly produce reduced diffusivity along the fibers and lead to increased inhomogeneity of the diffusion.

Landmark-guided diffeomorphic demons algorithm and its application to automatic segmentation of the whole spine and pelvis in CT images

PurposeA fully automatic multiatlas-based method for segmentation of the spine and pelvis in a torso CT volume is proposed. A novel landmark-guided diffeomorphic demons algorithm is used to register a given CT image to multiple atlas volumes. This algorithm can utilize both grayscale image information and given landmark coordinate information optimally.MethodsThe segmentation has four steps. Firstly, 170 bony landmarks are detected in the given volume. Using these landmark positions, an atlas selection procedure is performed to reduce the computational cost of the following registration. Then the chosen atlas volumes are registered to the given CT image. Finally, voxelwise label voting is performed to determine the final segmentation result.ResultsThe proposed method was evaluated using 50 torso CT datasets as well as the public SpineWeb dataset. As a result, a mean distance error of

Managing Computer-Assisted Detection System Based on Transfer Learning with Negative Transfer Inhibition

0.59pm 0.14hbox { mm}

Cone-beam CT reconstruction for non-periodic organ motion using time-ordered chain graph model

0.59±0.14mm and a mean Dice coefficient of