Analysis of synthetic magnetic resonance images by multi-channel segmentation increases accuracy of volumetry in the putamen and decreases mis-segmentation in the dural sinuses.

BACKGROUND: Voxel-based morphometry (VBM) using magnetic resonance imaging (MR) has been used to estimate cortical atrophy associated with various diseases. However, there are mis-segmentations of segmented gray matter image in VBM. PURPOSE: To study a twofold evaluation of single- and multi-channel segmentation using synthetic MR images: (1) mis-segmentation of segmented gray matter images in transverse and cavernous sinuses; and (2) accuracy and repeatability of segmented gray matter images. MATERIAL AND METHODS: A total of 13 healthy individuals were scanned with 3D quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS) sequence on a 1.5-T scanner. Three of the 13 healthy participants were scanned five consecutive times for evaluation of repeatability. We used SyMRI software to create images with three contrasts: T1-weighted (T1W), T2-weighted (T2W), and proton density-weighted (PDW) images. Manual regions of interest (ROI) on T1W imaging were individually set as the gold standard in the transverse sinus, cavernous sinus, and putamen. Single-channel (T1W) and multi-channel (T1W + T2W, T1W + PDW, and T1W + T2W + PDW imaging) segmentations were performed with statistical parametric mapping 12 software. RESULTS: We found that mis-segmentations in both the transverse and cavernous sinuses were large in single-channel segmentation compared with multi-channel segmentations. Furthermore, the accuracy of segmented gray matter images in the putamen was high in both multi-channel T1W + PDW and T1W + T2W + PDW segmentations compared with other segmentations. Finally, the highest repeatability of left putamen volumetry was found with multi-channel segmentation T1WI + PDWI. CONCLUSION: Multi-channel segmentation with T1WI + PDWI provides good results for VBM compared with single-channel and other multi-channel segmentations.

Using modulated and smoothed data improves detectability of volume difference in group comparison, but reduces accuracy with atlas-based volumetry using Statistical Parametric Mapping 12 software.

BACKGROUND: Atlas-based volumetry using three-dimensional T1-weighted (3D-T1W) magnetic resonance imaging (MRI) has been used previously to evaluate the volumes of intracranial tissues. PURPOSE: To evaluate the detectability of volume difference and accuracy for volumetry using smoothed data with an atlas-based method. MATERIAL AND METHODS: Twenty healthy individuals and 24 patients with idiopathic normal-pressure hydrocephalus (iNPH) underwent 3-T MRI, and sagittal 3D-T1W images were obtained in all participants. Signal values (as tissue probability) of voxels in five segmented data types (gray matter, white matter, cerebrospinal fluid [CSF], skull, soft tissue) derived from the 3D-T1W images with SPM 12 software were assigned simulated 3D-T1W signal intensities to each tissue image. The assigned data were termed "reference data." We created a reference 3D-T1W image that included the reference data of all five tissue types. Standard volumes were measured for the reference CSF data with region of interest of lateral ventricle in native space, and measured volumes were obtained for non-smoothed and smoothed-modulated data. Detectability was evaluated between measured volumes in the healthy control and iNPH groups. Accuracy was evaluated as the difference between the mean measured and standard volumes. RESULTS: In group comparison of measured volumes between the healthy control and iNPH groups, the lowest P value was for smoothed-modulated CSF data. In both groups, the largest difference from the standard volume was found for the mean of the measured volumes for smoothed-modulated CSF data. CONCLUSION: Our study shows that using smoothed data can improve detectability in group comparison. However, using smoothed data reduces the accuracy of volumetry.

3D quantitative synthetic MRI-derived cortical thickness and subcortical brain volumes: Scan-rescan repeatability and comparison with conventional T1 -weighted images.

BACKGROUND: Previous quantitative synthetic MRI of the brain has been solely performed in 2D. PURPOSE: To evaluate the feasibility of the recently developed sequence 3D-QALAS for brain cortical thickness and volumetric analysis. STUDY TYPE: Reproducibility/repeatability study. SUBJECTS: Twenty-one healthy volunteers (35.6 ± 13.8 years). FIELD STRENGTH/SEQUENCE: 3D T1 -weighted fast spoiled gradient recalled echo (FSPGR) sequence was performed once, and 3D-QALAS sequence was performed twice with a 3T scanner. ASSESSMENT: FreeSurfer and FIRST were used to measure cortical thickness and volume of subcortical structures, respectively. Agreement with FSPGR and scan-rescan repeatability were evaluated for 3D-QALAS. STATISTICAL TESTS: Percent relative difference and intraclass correlation coefficient (ICC) were used to assess reproducibility and scan-rescan repeatability of the 3D-QALAS sequence-derived measurements. RESULTS: Percent relative difference compared with FSPGR in cortical thickness of the whole cortex was 3.1%, and 89% of the regional areas showed less than 10% relative difference in cortical thickness. The mean ICC across all regions was 0.65, and 74% of the structures showed substantial to almost perfect agreement. For volumes of subcortical structures, the median percent relative differences were lower than 10% across all subcortical structures, except for the accumbens area, and all structures showed ICCs of substantial to almost perfect agreement. For the scan-rescan test, percent relative difference in cortical thickness of the whole cortex was 2.3%, and 97% of the regional areas showed less than 10% relative difference in cortical thickness. The mean ICC across all regions was 0.73, and 80% showed substantial to almost perfect agreement. For volumes of subcortical structures, relative differences were less than 10% across all subcortical structures except for the accumbens area, and all structures showed ICCs of substantial to almost perfect agreement. DATA CONCLUSION: 3D-QALAS could be reliably used for measuring cortical thickness and subcortical volumes in most brain regions. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:1834-1842.

The Effect of Single-Scan and Scan-Pair Intensity Inhomogeneity Correction Methods on Repeatability of Voxel-Based Morphometry With Multiple Magnetic Resonance Scanners.

OBJECTIVE: The aim of this study was to investigate the effects of single-scan and scan-pair intensity inhomogeneity correction methods on the repeatability of voxel-based morphometry (VBM) using images acquired with multiple magnetic resonance (MR) scanners. METHODS: Three-dimensional T1-weighed MR images of the brain were obtained from 22 healthy participants using each of 5 MR scanners, yielding 110 images (5 scanners × 22 subjects) in total. Six patterns of intensity inhomogeneity corrections (no correction, single-scan corrections, and scan-pair correction, and their combinations) were applied in the VBM procedure to investigate the effect of the corrections on the repeatability of gray and white matter volume measurements. RESULTS: Single-scan and scan-pair intensity inhomogeneity corrections significantly reduced the variance in spatially normalized gray and white matter volumes. However, combining the 2 methods did not significantly improve the repeatability when evaluated as whole brain. CONCLUSIONS: Single-scan and scan-pair intensity inhomogeneity corrections improved the repeatability of gray and white matter volumes obtained by multiple MR scanners and assessed by VBM.

Depressive symptoms in Parkinson's disease are related to decreased left hippocampal volume: correlation with the 15-item shortened version of the Geriatric Depression Scale.

Background The relationship between hippocampal and amygdaloid volumes and depression in patients with Parkinson's disease (PD) is a controversial issue. Purpose To investigate the correlation between the 15-item shortened version of the Geriatric Depression Scale (GDS-15) and gray matter volume in PD. Material and Methods In the present study, 46 participants with PD were scanned with 3 T magnetic resonance imaging (MRI) to obtain three-dimensional (3D) T1-weighted (T1W) images. Neurologists specializing in movement disorders performed clinical evaluations of the participants (e.g. GDS-15, Mini-Mental State Examination, PD duration, age, sex). Statistical Parametric Mapping 8 software was used for image gray matter segmentation and for a correlation analysis between gray matter volume and GDS-15 score. Results The results showed a significant negative correlation between GDS-15 score and left hippocampal volume, and between GDS-15 score and right parahippocampal gyrus volume. No significant positive correlations were found in the whole brain. Conclusion The current results provide new evidence regarding the relationship between depression in PD and hippocampal volume.

Adverse effects of metallic artifacts on voxel-wise analysis and tract-based spatial statistics in diffusion tensor imaging.

Background Diffusion tensor imaging (DTI) is a magnetic resonance imaging (MRI) technique that reflects the Brownian motion of water molecules constrained within brain tissue. Fractional anisotropy (FA) is one of the most commonly measured DTI parameters, and can be applied to quantitative analysis of white matter as tract-based spatial statistics (TBSS) and voxel-wise analysis. Purpose To show an association between metallic implants and the results of statistical analysis (voxel-wise group comparison and TBSS) for fractional anisotropy (FA) mapping, in DTI of healthy adults. Material and Methods Sixteen healthy volunteers were scanned with 3-Tesla MRI. A magnetic keeper type of dental implant was used as the metallic implant. DTI was acquired three times in each participant: (i) without a magnetic keeper (FAnon1); (ii) with a magnetic keeper (FAimp); and (iii) without a magnetic keeper (FAnon2) as reproducibility of FAnon1. Group comparisons with paired t-test were performed as FAnon1 vs. FAnon2, and as FAnon1 vs. FAimp. Results Regions of significantly reduced and increased local FA values were revealed by voxel-wise group comparison analysis (a P value of less than 0.05, corrected with family-wise error), but not by TBSS. Conclusion Metallic implants existing outside the field of view produce artifacts that affect the statistical analysis (voxel-wise group comparisons) for FA mapping. When statistical analysis for FA mapping is conducted by researchers, it is important to pay attention to any dental implants present in the mouths of the participants.

Comparison of Reconstruction Algorithms for Decreasing the Exposure Dose During Digital Tomosynthesis for Arthroplasty: a Phantom Study.

To explore the possibility of decreasing the radiation dose during digital tomosynthesis (DT) for arthroplasty, we compared the image qualities of several reconstruction algorithms, such as filtered back projection (FBP) and two iterative reconstruction (IR), methods maximum likelihood expectation maximization (MLEM) and the simultaneous iterative reconstruction technique (SIRT) under different radiation doses. The three algorithms were implemented using a DT system and experimentally evaluated by contrast-to-noise ratio (CNR), artifact spread function (ASF), and power spectrum measurements on a prosthesis phantom. The CNR and ASF data were statistically analyzed by a one-way analysis of variance. The effectiveness of each technique for enhancing the visibility of the prosthesis phantom was quantified by the CNR (reference dose vs. 20 % reduced dose in FBP, P = 0.62; reference vs. 37 % reduced dose in FBP, P = 0.16; reference vs. 55 % reduced dose in FBP, P < 0.05; reference vs. 20 % reduced dose in IR, P = 0.92; reference vs. 37 % reduced dose in IR, P = 0.40; reference vs. 55 % reduced dose in IR, P < 0.05) and ASF (reference dose vs. 20 % reduced dose in FBP, P = 0.25; reference vs. 37 and 55 % reduced dose in FBP, P < 0.05; reference vs. 20 % reduced dose in IR, P = 0.16; reference vs. 37 and 55 % reduced dose in IR, P < 0.05). The power spectra under the reference and reduced doses are equivalent. In this phantom study, the radiation dose of the reference dose could be decreased by 20 % with FBP and IR for consideration of common factors.

Database of normal Japanese gray matter volumes in the default mode network.

PURPOSE: To show the gray matter volumes in the default mode network (DMN) using the atlas-based method and to evaluate age-related volume change in the DMN region. Estimation of gray matter volumes is interesting research because previous reports showed an association with gray matter volume (GMV) and diseases. MATERIALS AND METHODS: We focused on five nodes of the DMN (posterior cingulate, precuneus, lateral temporal cortex [LTC], medial prefrontal cortex, and inferior parietal lobule). In all, 1122 healthy adults were included in the present study. T1-weighted magnetic resonance (MR) images were obtained using a 3T-MR scanner. To investigate GMV in the DMN, segmented gray matter images were measured by the atlas-based method, using Statistical Parametric Mapping 5. Volumes were expressed using three different methods: region of interest (ROI)-volume (mL), the volume itself; ROI-TIV (%), as a percentage of total intracranial volume (individual difference of head size is corrected); and ROI-GMV (%), as a percentage of gray matter volume (individual difference of atrophy speed for aging is corrected). RESULTS: Negative correlations between measurement values on ROI and age were observed in all five ROIs of the DMN region by two measures of volume (ROI-volume (mL) and ROI-TIV (%)), in both genders. In contrast, positive correlations between measurement values on ROI and age were observed in the posterior cingulate and LTC with ROI-GMV (%), in both genders. CONCLUSION: The present study is the first report about volume change in the DMN that includes age-related effects.

[Study on cine view of relative enhancement ratio map in O2-enhanced MRI].

Magnetic resonance imaging (MRI) enables the evaluation of organ structure and function. Oxygen-enhanced MRI (O2-enhanced MRI) is a method for evaluating the pulmonary ventilation function using oxygen as a contrast agent. We created the Cine View of Relative Enhancement Ratio Map (Cine RER map) in O2-enhanced MRI to easily observe the contrast effect for clinical use. Relative enhancement ratio (RER) was determined as the pixel values of the Cine RER map. Moreover, six healthy volunteers underwent O2-enhanced MRI to determine the appropriate scale width of the Cine RER map. We calculated each RER and set 0 to 1.27 as the scale width of the Cine RER map based on the results. The Cine RER map made it possible to observe the contrast effect over time and thus is a convenient tool for evaluating the pulmonary ventilation function in O2-enhanced MRI.

Deep Learning-based Hierarchical Brain Segmentation with Preliminary Analysis of the Repeatability and Reproducibility.

PURPOSE: We developed new deep learning-based hierarchical brain segmentation (DLHBS) method that can segment T1-weighted MR images (T1WI) into 107 brain subregions and calculate the volume of each subregion. This study aimed to evaluate the repeatability and reproducibility of volume estimation using DLHBS and compare them with those of representative brain segmentation tools such as statistical parametric mapping (SPM) and FreeSurfer (FS). METHODS: Hierarchical segmentation using multiple deep learning models was employed to segment brain subregions within a clinically feasible processing time. The T1WI and brain mask pairs in 486 subjects were used as training data for training of the deep learning segmentation models. Training data were generated using a multi-atlas registration-based method. The high quality of training data was confirmed through visual evaluation and manual correction by neuroradiologists. The brain 3D-T1WI scan-rescan data of the 11 healthy subjects were obtained using three MRI scanners for evaluating the repeatability and reproducibility. The volumes of the eight ROIs-including gray matter, white matter, cerebrospinal fluid, hippocampus, orbital gyrus, cerebellum posterior lobe, putamen, and thalamus-obtained using DLHBS, SPM 12 with default settings, and FS with the "recon-all" pipeline. These volumes were then used for evaluation of repeatability and reproducibility. RESULTS: In the volume measurements, the bilateral thalamus showed higher repeatability with DLHBS compared with SPM. Furthermore, DLHBS demonstrated higher repeatability than FS in across all eight ROIs. Additionally, higher reproducibility was observed with DLHBS in both hemispheres of six ROIs when compared with SPM and in five ROIs compared with FS. The lower repeatability and reproducibility in DLHBS were not observed in any comparisons. CONCLUSION: Our results showed that the best performance in both repeatability and reproducibility was found in DLHBS compared with SPM and FS.

Association between iron content and gray matter missegmentation with voxel-based morphometry in basal ganglia.

PURPOSE: To show an association between T2-weighted signal intensity (T2-SI) variation and missegmentation in the putamen of healthy adults, using 3.0-tesla magnetic resonance scanner and voxel-based morphomery (VBM). MATERIALS AND METHODS: Contiguous sagittal T1-weighted images and axial T2-weighted images of the brain were obtained from 1380 healthy participants using a 3.0 Tesla (T) MR scanner. After image preprocessing with Statistical Parametric Mapping 5, the association between T2-SI ratio (= A/B, where A is the mean of the T2-SI in the putamen, and B is that in the thalamus) variation and gray matter missegmentation was assessed using VBM. RESULTS: A significant positive correlation was revealed between T2-SI ratio and bilateral putamen volume on the gray matter images. In addition, we found a significant negative correlation between T2-SI ratio and bilateral putamen volume on the white matter images. We consider that these results show the influence of missegmentation. CONCLUSION: To the best of our knowledge, this is the first VBM study to demonstrate an association between T2-SI variation and gray matter missegmentation. These results indicate the possibility that VBM may be more affected by individual differences in iron content levels than by individual differences in tissue volumes if detected-regions with VBM contained substantial iron deposition.

Bilateral pre- and postcentral gyrus volume positively correlates with T2-SNR of putamen in healthy adults.

INTRODUCTION: The aim of the present study was to investigate the correlation between local gray matter volume and signal-to-noise ratio on T2-weighted imaging (T2-SNR) of putamen in healthy adults using two tools: voxel-based morphometry (VBM) treating age as a confounding covariate to control for age-related gray matter volume changes and high spatial resolution T1-weighted imaging acquired with a 3.0-T magnetic resonance (3T-MR) scanner. METHODS: Contiguous sagittal T1-weighted images and axial T2-weighted images of the brain were obtained from 1,380 healthy participants. T2-SNR of putamen was defined as A/B, where A is the mean T2-weighted signal intensity (T2-SI) in the right and left sides of putamen, and B is the background noise. The software Statistical Parametric Mapping 5 was used for image segmentation. The association between T2-SNR of putamen and gray matter volume was assessed with VBM, treating age as a confounding covariate. RESULTS: A significant positive correlation was obtained between T2-SNR of putamen and bilateral pre- and postcentral gyrus volume. CONCLUSION: To the best of our knowledge, this is the first VBM study to show an age-independent relationship between T2-SNR of putamen and bilateral pre- and postcentral gyrus volumes in healthy adults.

Diffeomorphic Anatomical Registration Through Exponentiated Lie Algebra provides reduced effect of scanner for cortex volumetry with atlas-based method in healthy subjects.

INTRODUCTION: This study aimed to investigate whether the effect of scanner for cortex volumetry with atlas-based method is reduced using Diffeomorphic Anatomical Registration Through Exponentiated Lie Algebra (DARTEL) normalization compared with standard normalization. METHODS: Three-dimensional T1-weighted magnetic resonance images (3D-T1WIs) of 21 healthy subjects were obtained and evaluated for effect of scanner in cortex volumetry. 3D-T1WIs of the 21 subjects were obtained with five MRI systems. Imaging of each subject was performed on each of five different MRI scanners. We used the Voxel-Based Morphometry 8 tool implemented in Statistical Parametric Mapping 8 and WFU PickAtlas software (Talairach brain atlas theory). The following software default settings were used as bilateral region-of-interest labels: "Frontal Lobe," "Hippocampus," "Occipital Lobe," "Orbital Gyrus," "Parietal Lobe," "Putamen," and "Temporal Lobe." RESULTS: Effect of scanner for cortex volumetry using the atlas-based method was reduced with DARTEL normalization compared with standard normalization in Frontal Lobe, Occipital Lobe, Orbital Gyrus, Putamen, and Temporal Lobe; was the same in Hippocampus and Parietal Lobe; and showed no increase with DARTEL normalization for any region of interest (ROI). CONCLUSION: DARTEL normalization reduces the effect of scanner, which is a major problem in multicenter studies.

Evaluation of motion artefact reduction depending on the artefacts' directions in head MRI using conditional generative adversarial networks.

Motion artefacts caused by the patient's body movements affect magnetic resonance imaging (MRI) accuracy. This study aimed to compare and evaluate the accuracy of motion artefacts correction using a conditional generative adversarial network (CGAN) with an autoencoder and U-net models. The training dataset consisted of motion artefacts generated through simulations. Motion artefacts occur in the phase encoding direction, which is set to either the horizontal or vertical direction of the image. To create T2-weighted axial images with simulated motion artefacts, 5500 head images were used in each direction. Of these data, 90% were used for training, while the remainder were used for the evaluation of image quality. Moreover, the validation data used in the model training consisted of 10% of the training dataset. The training data were divided into horizontal and vertical directions of motion artefact appearance, and the effect of combining this data with the training dataset was verified. The resulting corrected images were evaluated using structural image similarity (SSIM) and peak signal-to-noise ratio (PSNR), and the metrics were compared with the images without motion artefacts. The best improvements in the SSIM and PSNR were observed in the consistent condition in the direction of the occurrence of motion artefacts in the training and evaluation datasets. However, SSIM > 0.9 and PSNR > 29 dB were accomplished for the learning model with both image directions. The latter model exhibited the highest robustness for actual patient motion in head MRI images. Moreover, the image quality of the corrected image with the CGAN was the closest to that of the original image, while the improvement rates for SSIM and PSNR were approximately 26% and 7.7%, respectively. The CGAN model demonstrated a high image reproducibility, and the most significant model was the consistent condition of the learning model and the direction of the appearance of motion artefacts.

Accuracy of skull stripping in a single-contrast convolutional neural network model using eight-contrast magnetic resonance images.

In automated analyses of brain morphometry, skull stripping or brain extraction is a critical first step because it provides accurate spatial registration and signal-intensity normalization. Therefore, it is imperative to develop an ideal skull-stripping method in the field of brain image analysis. Previous reports have shown that convolutional neural network (CNN) method is better at skull stripping than non-CNN methods. We aimed to evaluate the accuracy of skull stripping in a single-contrast CNN model using eight-contrast magnetic resonance (MR) images. A total of 12 healthy participants and 12 patients with a clinical diagnosis of unilateral Sturge-Weber syndrome were included in our study. A 3-T MR imaging system and QRAPMASTER were used for data acquisition. We obtained eight-contrast images produced by post-processing T1, T2, and proton density (PD) maps. To evaluate the accuracy of skull stripping in our CNN method, gold-standard intracranial volume (ICVG) masks were used to train the CNN model. The ICVG masks were defined by experts using manual tracing. The accuracy of the intracranial volume obtained from the single-contrast CNN model (ICVE) was evaluated using the Dice similarity coefficient [= 2(ICVE ⋂ ICVG)/(ICVE + ICVG)]. Our study showed significantly higher accuracy in the PD-weighted image (WI), phase-sensitive inversion recovery (PSIR), and PD-short tau inversion recovery (STIR) compared to the other three contrast images (T1-WI, T2-fluid-attenuated inversion recovery [FLAIR], and T1-FLAIR). In conclusion, PD-WI, PSIR, and PD-STIR should be used instead of T1-WI for skull stripping in the CNN models.

Repeatability of measured brain volume by atlas-based method using T1-weighted image.

The aims of this study were to (1) investigate the repeatability of measured volumes using the atlas-based method in each area of the brain, and (2) validate our hypothesis that the repeatability of the measured volumes with the atlas-based method was improved by using smoothed images. T1-weighted magnetic resonance images were obtained in five healthy subjects using the 1.5-T scanner. We used Statistical Parametric Mapping 5 and WFU PickAtlas software (theory of the Talairach brain atlas). Volumes inside region-of-interest (ROI) were measured in ten sets (five subjects × right and left) on six ROIs, respectively. One set comprises five images (one subject × five 3D-T1WIs). The percentage change was defined as [100 × (measured volume-mean volume in each set)/mean volume in each set)]. As a result, the average percentage changes using non-smoothed image on each ROI were as follows: gray matter, 0.482%; white matter, 0.375%; cerebrospinal fluid images, 0.731%; hippocampus, 0.864%; orbital gyrus, 1.692%; cerebellum posterior lobe, 0.854%. Using smoothed images with large FWHM resulted in improved repeatability on orbital gyrus. This is the first report of repeatability in each brain structure and improved repeatability with smoothed images using the atlas-based method.