Decreased diffusivity along the perivascular space and cerebral hemodynamic disturbance in adult moyamoya disease.

Moyamoya disease (MMD) causes cerebral arterial stenosis and hemodynamic disturbance, the latter of which may disrupt glymphatic system activity, the waste clearance system. We evaluated 46 adult patients with MMD and 33 age- and sex-matched controls using diffusivity along the perivascular space (ALPS) measured with diffusion tensor imaging (ALPS index), which may partly reflect glymphatic system activity, and multishell diffusion MRI to generate freewater maps. Twenty-three patients were also evaluated via 15O-gas positron emission tomography (PET), and all patients underwent cognitive tests. Compared to controls, patients (38.4 (13.2) years old, 35 females) had lower ALPS indices in the left and right hemispheres (1.94 (0.27) vs. 1.65 (0.25) and 1.94 (0.22) vs. 1.65 (0.19), P < 0.001). While the right ALPS index showed no correlation, the left ALPS index was correlated with parenchymal freewater (ρ = -0.47, P < 0.001); perfusion measured with PET (cerebral blood flow, ρ = 0.70, P < 0.001; mean transit time, ρ = -0.60, P = 0.003; and oxygen extraction fraction, ρ = -0.52, P = 0.003); and cognitive tests (trail making test part B for executive function; ρ = -0.37, P = 0.01). Adult patients with MMD may exhibit decreased glymphatic system activity, which is correlated with the degree of hemodynamic disturbance, increased interstitial freewater, and cognitive dysfunction, but further investigation is needed.

Assessing interstitial fluid dynamics in type 2 diabetes mellitus and prediabetes cases through diffusion tensor imaging analysis along the perivascular space.

Background and purpose: Glymphatic system in type 2 diabetes mellitus (T2DM) but not in the prodrome, prediabetes (Pre-DM) was investigated using diffusion tensor image analysis along the perivascular space (DTI-ALPS). Association between glymphatic system and insulin resistance of prominent characteristic in T2DM and Pre-DM between is yet elucidated. Therefore, this study delves into the interstitial fluid dynamics using the DTI-ALPS in both Pre-DM and T2DM and association with insulin resistance. Materials and methods: In our cross-sectional study, we assessed 70 elderly individuals from the Bunkyo Health Study, which included 22 with Pre-DM, 18 with T2DM, and 33 healthy controls with normal glucose metabolism (NGM). We utilized the general linear model (GLM) to evaluate the ALPS index based on DTI-ALPS across these groups, considering variables like sex, age, intracranial volume, years of education, anamnesis of hypertension and hyperlipidemia, and the total Fazekas scale. Furthermore, we have explored the relationship between the ALPS index and insulin resistance, as measured by the homeostasis model assessment of insulin resistance (HOMA-IR) using GLM and the same set of covariates. Results: In the T2DM group, the ALPS index demonstrated a reduction compared with the NGM group [family-wise error (FWE)-corrected p < 0.001; Cohen's d = -1.32]. Similarly, the Pre-DM group had a lower ALPS index than the NGM group (FWE-corrected p < 0.001; Cohen's d = -1.04). However, there was no significant disparity between the T2DM and Pre-DM groups (FWE-corrected p = 1.00; Cohen's d = -0.63). A negative correlation was observed between the ALPS index and HOMA-IR in the combined T2DM and Pre-DM groups (partial correlation coefficient r = -0.35, p < 0.005). Conclusion: The ALPS index significantly decreased in both the pre-DM and T2DM groups and showed a correlated with insulin resistance. This indicated that changes in interstitial fluid dynamics are associated with insulin resistance.

Deep Learning-Driven Transformation: A Novel Approach for Mitigating Batch Effects in Diffusion MRI Beyond Traditional Harmonization.

BACKGROUND: "Batch effect" in MR images, due to vendor-specific features, MR machine generations, and imaging parameters, challenges image quality and hinders deep learning (DL) model generalizability. PURPOSE: We aim to develop a DL model using contrast adjustment and super-resolution to reduce diffusion-weighted images (DWIs) diversity across magnetic field strengths and imaging parameters. STUDY TYPE: Retrospective. SUBJECTS: The DL model was built using an open dataset from one individual. The MR machine identification model was trained and validated on a dataset of 1134 adults (54% females, 46% males), with 1050 subjects showing no DWI abnormalities and 84 with conditions like stroke and tumors. The 21,000 images were divided into 80% for training, 20% for validation, and 3500 for testing. FIELD STRENGTH/SEQUENCE: Seven MR scanners from four manufacturers with 1.5 T and 3 T magnetic field strengths. DWIs were acquired using spin-echo sequences and high-resolution T2WIs using the T2-SPACE sequence. ASSESSMENT: An experienced, board-certified radiologist evaluated the effectiveness of restoring high-resolution T2WI and harmonizing diverse DWI with metrics such as PSNR and SSIM, and the texture and frequency attributes were further analyzed using gray-level co-occurrence matrix and 1-dimensional power spectral density. The model's impact on machine-specific characteristics was gauged through the performance metrics of a ResNet-50 model. Comprehensive statistical tests were employed for statistical robustness, including McNemar's test and the Dice index. RESULTS: Our DL protocol reduced DWI contrast and resolution variation. ResNet-50 model's accuracy decreased from 0.9443 to 0.5786, precision from 0.9442 to 0.6494, recall from 0.9443 to 0.5786, and F1 score from 0.9438 to 0.5587. The t-SNE visualization indicated more consistent image features across multiple MR devices. Autoencoder halved learning iterations; Dice coefficient >0.74 confirmed signal reproducibility in 84 lesions. CONCLUSION: This study presents a DL strategy to mitigate batch effects in diffusion MR images, improving their quality and generalizability. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 1.

Glymphatic system impairment in sleep disruption: diffusion tensor image analysis along the perivascular space (DTI-ALPS).

PURPOSE: This study aimed to evaluate the relationship between sleep quality as assessed using the Pittsburgh Sleep Quality Index (PSQI) and the index of diffusivity along the perivascular space (ALPS index), a possible indirect indicator of glymphatic system activity. MATERIALS AND METHODS: This study included the diffusion magnetic resonance imaging (MRI) data of 317 people with sleep disruption and 515 healthy controls (HCs) from the Human Connectome Project (WU-MINN HCP 1200). The ALPS index was calculated automatically based on diffusion tensor image analysis (DTI)-ALPS of diffusion MRI. The ALPS index of the sleep disruption and HC groups was compared using general linear model (GLM) analysis with covariates, such as age, sex, level of education, and intracranial volume. In addition, to confirm the relationship between sleep quality and the ALPS index in the sleep disruption group as well as evaluate the effect of each PSQI component on the ALPS index, correlation analyses between the ALPS indices and PSQI scores of all the components and between the ALPS index and each PSQI component was performed using GLM analysis with the abovementioned covariates, respectively. RESULTS: The ALPS index was significantly lower in the sleep disruption group than in the HC group (p = 0.001). Moreover, the ALPS indices showed significant negative correlations with the PSQI scores of all the components (false discovery rate [FDR]-corrected p < 0.001). Two significant negative correlations were also found between the ALPS index and PSQI component 2 (sleep latency, FDR-corrected p < 0.001) and 6 (the use of sleep medication, FDR-corrected p < 0.001). CONCLUSION: Our findings suggest that glymphatic system impairment contributes to sleep disruption in young adults.

Glymphatic system impairment in nonathlete older male adults who played contact sports in their youth associated with cognitive decline: A diffusion tensor image analysis along the perivascular space study.

Background and purpose: Exposure to contact sports in youth causes brain health problems later in life. For instance, the repetitive head impacts in contact sports might contribute to glymphatic clearance impairment and cognitive decline. This study aimed to assess the effect of contact sports participation in youth on glymphatic function in old age and the relationship between glymphatic function and cognitive status using the analysis along the perivascular space (ALPS) index. Materials and methods: A total of 52 Japanese older male subjects were included in the study, including 12 who played heavy-contact sports (mean age, 71.2 years), 15 who played semicontact sports (mean age, 73.1 years), and 25 who played noncontact sports (mean age, 71.3 years) in their youth. All brain diffusion-weighted images (DWIs) of the subjects were acquired using a 3T MRI scanner. The ALPS indices were calculated using a validated semiautomated pipeline. The ALPS indices from the left and right hemispheres were compared between groups using a general linear model, including age and years of education. Furthermore, partial Spearman's rank correlation tests were performed to assess the correlation between the ALPS indices and cognitive scores (Mini-Mental State Examination and the Japanese version of the Montreal Cognitive Assessment [MoCA-J]) after adjusting for age years of education and HbA1c. Results: The left ALPS index was significantly lower in the heavy-contact and semicontact groups than that in the noncontact group. Although no significant differences were observed in the left ALPS index between the heavy-contact and semicontact groups and in the right ALPS index among groups, a trend toward lower was found in the right ALPS index in individuals with semicontact and heavy-contact compared to the noncontact group. Both sides' ALPS indices were significantly positively correlated with the MoCA-J scores. Conclusion: The findings indicated the potential adverse effect of contact sports experience in youth on the glymphatic system function in old age associated with cognitive decline.

Feasibility of Quantitative MRI Using 3D-QALAS for Discriminating Immunohistochemical Status in Invasive Ductal Carcinoma of the Breast.

BACKGROUND: Two-dimensional synthetic MRI of the breast has limited spatial coverage. Three-dimensional (3D) synthetic MRI could provide volumetric quantitative parameters that may reflect the immunohistochemical (IHC) status in invasive ductal carcinoma (IDC) of the breast. PURPOSE: To evaluate the feasibility of 3D synthetic MRI using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (QALAS) for discriminating the IHC status, including hormone receptor (HR), human epidermal growth factor receptor 2 (HER 2), and Ki-67 expression in IDC. STUDY TYPE: Prospective observational study. POPULATION: A total of 33 females with IDC of the breast (mean, 52.3 years). FIELD STRENGTH/SEQUENCE: A 3-T, 3D-QALAS gradient-echo and fat-suppressed T1-weighted 3D fast spoiled gradient-echo sequences. ASSESSMENT: Two radiologists semiautomatically delineated 3D regions of interest (ROIs) of the whole tumors on the dynamic MRI that was registered to the synthetic T1-weighted images acquired from 3D-QALAS. The mean T1 and T2 were measured for each IDC. STATISTICAL TESTS: Intraclass correlation coefficient for assessing interobserver agreement. Mann-Whitney U test to determine the relationship between the mean T1 or T2 and the IHC status. Multivariate logistic regression analysis followed by receiver operating characteristics (ROC) analysis for discriminating IHC status. A P value <0.05 was considered statistically significant. RESULTS: The interobserver agreement was good to excellent. There was a significant difference in the mean T1 between HR-positive and HR-negative lesions, while the mean T2 value differed between HR-positive and HR-negative lesions, between the triple-negative and HR-positive or HER2-positive lesions, and between the Ki-67 level > 14% and ≤ 14%. Multivariate analysis showed that the mean T2 was higher in HR-negative IDC than in HR-positive IDC. ROC analysis revealed that the mean T2 was predictive for discriminating HR status, triple-negative status, and Ki-67 level. DATA CONCLUSION: 3D synthetic MRI using QALAS may be useful for discriminating IHC status in IDC of the breast. EVIDENCE LEVEL: 1. TECHNICAL EFFICACY: Stage 2.

Neuroimaging findings related to glymphatic system alterations in older adults with metabolic syndrome.

OBJECTIVE: The glymphatic system is a glial-based perivascular network that promotes brain metabolic waste clearance. Reduced glymphatic flow has been observed in rat models of type 2 diabetes and hypertension, indicating the role of vascular risk factors in the glymphatic system. However, little is known about how vascular risk factors affect the human glymphatic system. The present study aims to assess the relationships between metabolic syndrome (MetS), a cluster of vascular risk factors, and the glymphatic system function using diffusion magnetic resonance imaging (MRI)-based measures of water diffusivity in the glymphatic compartments, including the brain interstitial space and perivascular spaces around the deep medullary vein. We hypothesized that vascular risk factors are associated with glymphatic dysfunction, leading to cognitive impairment in older adults. METHODS: This cross-sectional study assessed 61 older adults (age range, 65-82 years) who had participated in the Bunkyo Health Study, including 15 healthy controls (mean age, 70.87 ± 4.90 years) and 46 individuals with MetS (mean age, 71.76 ± 4.61 years). Fractional volume of extracellular-free water (FW) and an index of diffusion tensor imaging along the perivascular space (DTI-ALPS) were used as indirect indicators of water diffusivity in the interstitial extracellular and perivenous spaces of white matter, respectively. RESULTS: After adjusting for age, sex, years of education, total Fazekas scale, Pittsburgh sleep quality index (PSQI) score, and intracranial volume (ICV), a significantly (P = 0.030; Cohen's d = 1.01) higher FW was observed in individuals with MetS than in the healthy controls. Furthermore, individuals with MetS had a significantly (P = 0.031; Cohen's d = 0.86) lower ALPS index than the healthy controls, with age, sex, years of education, total Fazekas scale, PSQI score, ICV, fractional anisotropy, and mean diffusivity included as confounding factors. Higher FW was significantly associated with lower ALPS index (r = -0.37; P = 0.004). Multiple linear regression (MLR) with backward elimination analyses showed that higher diastolic blood pressure (BP; standardized ß = 0.33, P = 0.005) was independently associated with higher FW, whereas higher fasting plasma glucose levels (standardized ß = -0.63, P = 0.002) or higher Brinkman index of cigarette consumption cumulative amount (standardized ß = -0.27, P = 0.022) were associated with lower ALPS index. The lower ALPS index (standardized ß, 0.28; P = 0.040) was associated with poorer global cognitive performance, which was determined using the Japanese version of the Montreal Cognitive Assessment (MOCA-J) scores. Finally, partial correlation analyses showed a significant correlation between higher FW and lower MOCA-J scores (r = -0.35; P = 0.025) and between higher FW and higher diastolic BP (r = 0.32, P = 0.044). CONCLUSION: The present study shows the changes in diffusion MRI-based measures reflected by the higher FW and lower ALPS index in older adults with MetS, possibly due to the adverse effect of vascular risk factors on the glymphatic system. Our findings also indicate the associations between the diffusion MRI-based measures and elevated diastolic BP, hyperglycemia, smoking habit, and poorer cognitive performance. However, owing to the limitations of this study, the results should be cautiously interpreted.

Automation of a Rule-based Workflow to Estimate Age from Brain MR Imaging of Infants and Children Up to 2 Years Old Using Stacked Deep Learning.

PURPOSE: Myelination-related MR signal changes in white matter are helpful for assessing normal development in infants and children. A rule-based myelination evaluation workflow regarding signal changes on T1-weighted images (T1WIs) and T2-weighted images (T2WIs) has been widely used in radiology. This study aimed to simulate a rule-based workflow using a stacked deep learning model and evaluate age estimation accuracy. METHODS: The age estimation system involved two stacked neural networks: a target network-to extract five myelination-related images from the whole brain, and an age estimation network from extracted T1- and T2WIs separately. A dataset was constructed from 119 children aged below 2 years with two MRI systems. A four-fold cross-validation method was adopted. The correlation coefficient (CC), mean absolute error (MAE), and root mean squared error (RMSE) of the corrected chronological age of full-term birth, as well as the mean difference and the upper and lower limits of 95% agreement, were measured. Generalization performance was assessed using datasets acquired from different MR images. Age estimation was performed in Sturge-Weber syndrome (SWS) cases. RESULTS: There was a strong correlation between estimated age and corrected chronological age (MAE: 0.98 months; RMSE: 1.27 months; and CC: 0.99). The mean difference and standard deviation (SD) were -0.15 and 1.26, respectively, and the upper and lower limits of 95% agreement were 2.33 and -2.63 months. Regarding generalization performance, the performance values on the external dataset were MAE of 1.85 months, RMSE of 2.59 months, and CC of 0.93. Among 13 SWS cases, 7 exceeded the limits of 95% agreement, and a proportional bias of age estimation based on myelination acceleration was exhibited below 12 months of age (P = 0.03). CONCLUSION: Stacked deep learning models automated the rule-based workflow in radiology and achieved highly accurate age estimation in infants and children up to 2 years of age.

Association of MRI Indices of Glymphatic System With Amyloid Deposition and Cognition in Mild Cognitive Impairment and Alzheimer Disease.

BACKGROUND AND OBJECTIVES: The glymphatic system is a whole-brain perivascular network, which promotes CSF/interstitial fluid exchange. Alterations to this system may play a pivotal role in amyloid ß (Aß) accumulation. However, its involvement in Alzheimer's disease (AD) pathogenesis is not fully understood. Here, we investigated the changes in noninvasive MRI measurements related to the perivascular network in patients with mild cognitive impairment (MCI) and AD. Additionally, we explored the associations of MRI measures with neuropsychological score, PET standardized uptake value ratio (SUVR), and Aß deposition. METHODS: MRI measures, including perivascular space (PVS) volume fraction (PVSVF), fractional volume of free water in white matter (FW-WM), and index of diffusivity along the perivascular space (ALPS index) of patients with MCI, those with AD, and healthy controls from the Alzheimer's Disease Neuroimaging Initiative database were compared. MRI measures were also correlated with the levels of CSF biomarkers, PET SUVR, and cognitive score in the combined subcohort of patients with MCI and AD. Statistical analyses were performed with age, sex, years of education, and APOE status as confounding factors. RESULTS: In total, 36 patients with AD, 44 patients with MCI, and 31 healthy controls were analyzed. Patients with AD had significantly higher total, WM, and basal ganglia PVSVF (Cohen's d = 1.15-1.48; p < 0.001), and FW-WM (Cohen's d = 0.73; p < 0.05) and a lower ALPS index (Cohen's d = 0.63; p < 0.05) than healthy controls. Meanwhile, the MCI group only showed significantly higher total (Cohen's d = 0.99; p < 0.05) and WM (Cohen's d = 0.91; p < 0.05) PVSVF. Low ALPS index was associated with lower CSF Aß42 (r s = 0.41, p fdr = 0.026), FDG-PET uptake (r s = 0.54, p fdr < 0.001), and worse multiple cognitive domain deficits. High FW-WM was also associated with lower CSF Aß42 (r s = -0.47, p fdr = 0.021) and worse cognitive performances. CONCLUSION: Our study indicates that changes in PVS-related MRI parameters occur in MCI and AD, possibly due to impairment of the glymphatic system. We also report the associations between MRI parameters and Aß deposition, neuronal change, and cognitive impairment in AD.

Water Diffusivity Changes Along the Perivascular Space After Lumboperitoneal Shunt Surgery in Idiopathic Normal Pressure Hydrocephalus.

Background: The aim of this study was to evaluate the water diffusivity changes along the perivascular space after lumboperitoneal shunt (LPS) surgery in idiopathic normal pressure hydrocephalus. Methods: Nine patients diagnosed with idiopathic normal pressure hydrocephalus (iNPH; three men and six women, mean age ± SD = 75.22 ± 5.12 years) according to the guidelines for iNPH in Japan were included in the study. Post-LPS surgery, six patients with iNPH who exhibited improvement in symptoms were defined as responder subjects, while three patients with iNPH who did not were defined as non-responder subjects. We calculated the mean analysis along the perivascular space (ALPS) index of the left and right hemispheres and compared the differences between pre- and post-LPS surgery mean ALPS indices in iNPH patients. In the responder or non-responder subjects, the mean ALPS indices in the pre- and post-operative iNPH groups were compared using Wilcoxon signed-rank tests. Next, correlation analyses between pre- and post-operation changes in the mean ALPS index and clinical characteristics were conducted. Results: The mean ALPS index of the post-operative iNPH group was significantly higher than that of the pre-operative iNPH group (p = 0.021). In responder subjects, the mean ALPS index of the post-operative iNPH group was significantly higher than that of the pre-operative iNPH group (p = 0.046). On the other hand, in the non-responder subjects, the mean ALPS index of the post-operative iNPH group was not significantly different compared to the pre-operative iNPH group (p = 0.285). The mean ALPS index change was not significantly correlated with changes in the Mini-Mental State Examination (MMSE) score (r = -0.218, p = 0.574), Frontal Assessment Battery (FAB) score (r = 0.185, p = 0.634), Trail Making Test A (TMTA) score (r = 0.250, p = 0.516), and Evans' index (r = 0.109, p = 0.780). In responder subjects, the mean ALPS index change was significantly correlated with Evans' index in pre-operative patients with iNPH (r = 0.841, p = 0.036). Conclusion: This study demonstrates the improved water diffusivity along perivascular space in patients with iNPH after LPS surgery. This could be indicative of glymphatic function recovery following LPS surgery.

Reproducibility of diffusion tensor image analysis along the perivascular space (DTI-ALPS) for evaluating interstitial fluid diffusivity and glymphatic function: CHanges in Alps index on Multiple conditiON acquIsition eXperiment (CHAMONIX) study.

PURPOSE: The diffusion tensor image analysis along the perivascular space (DTI-ALPS) method was developed to evaluate the brain's glymphatic function or interstitial fluid dynamics. This study aimed to evaluate the reproducibility of the DTI-ALPS method and the effect of modifications in the imaging method and data evaluation. MATERIALS AND METHODS: Seven healthy volunteers were enrolled in this study. Image acquisition was performed for this test-retest study using a fixed imaging sequence and modified imaging methods which included the placement of region of interest (ROI), imaging plane, head position, averaging, number of motion-proving gradients, echo time (TE), and a different scanner. The ALPS-index values were evaluated for the change of conditions listed above. RESULTS: This test-retest study by a fixed imaging sequence showed very high reproducibility (intraclass coefficient = 0.828) for the ALPS-index value. The bilateral ROI placement showed higher reproducibility. The number of averaging and the difference of the scanner did not influence the ALPS-index values. However, modification of the imaging plane and head position impaired reproducibility, and the number of motion-proving gradients affected the ALPS-index value. The ALPS-index values from 12-axis DTI and 3-axis diffusion-weighted image (DWI) showed good correlation (r = 0.86). Also, a shorter TE resulted in a larger value of the ALPS-index. CONCLUSION: ALPS index was robust under the fixed imaging method even when different scanners were used. ALPS index was influenced by the imaging plane, the number of motion-proving gradient axes, and TE in the imaging sequence. These factors should be uniformed in the planning ALPS method studies. The possibility to develop a 3-axis DWI-ALPS method using three axes of the motion-proving gradient was also suggested.

Altered structural connectivity of pain-related brain network in burning mouth syndrome-investigation by graph analysis of probabilistic tractography.

PURPOSE: Burning mouth syndrome (BMS) is a chronic intraoral pain syndrome featuring idiopathic oral pain and burning discomfort despite clinically normal oral mucosa. The etiology of chronic pain syndrome is unclear, but preliminary neuroimaging research has suggested the alteration of volume, metabolism, blood flow, and diffusion at multiple brain regions. According to the neuromatrix theory of Melzack, pain sense is generated in the brain by the network of multiple pain-related brain regions. Therefore, the alteration of pain-related network is also assumed as an etiology of chronic pain. In this study, we investigated the brain network of BMS brain by using probabilistic tractography and graph analysis. METHODS: Fourteen BMS patients and 14 age-matched healthy controls underwent 1.5T MRI. Structural connectivity was calculated in 83 anatomically defined regions with probabilistic tractography of 60-axis diffusion tensor imaging and 3D T1-weighted imaging. Graph theory network analysis was used to evaluate the brain network at local and global connectivity. RESULTS: In BMS brain, a significant difference of local brain connectivity was recognized at the bilateral rostral anterior cingulate cortex, right medial orbitofrontal cortex, and left pars orbitalis which belong to the medial pain system; however, no significant difference was recognized at the lateral system including the somatic sensory cortex. A strengthened connection of the anterior cingulate cortex and medial prefrontal cortex with the basal ganglia, thalamus, and brain stem was revealed. CONCLUSION: Structural brain network analysis revealed the alteration of the medial system of the pain-related brain network in chronic pain syndrome.

Efficacy of distortion correction on diffusion imaging: comparison of FSL eddy and eddy_correct using 30 and 60 directions diffusion encoding.

Diffusion imaging is a unique noninvasive tool to detect brain white matter trajectory and integrity in vivo. However, this technique suffers from spatial distortion and signal pileup or dropout originating from local susceptibility gradients and eddy currents. Although there are several methods to mitigate these problems, most techniques can be applicable either to susceptibility or eddy-current induced distortion alone with a few exceptions. The present study compared the correction efficiency of FSL tools, "eddy_correct" and the combination of "eddy" and "topup" in terms of diffusion-derived fractional anisotropy (FA). The brain diffusion images were acquired from 10 healthy subjects using 30 and 60 directions encoding schemes based on the electrostatic repulsive forces. For the 30 directions encoding, 2 sets of diffusion images were acquired with the same parameters, except for the phase-encode blips which had opposing polarities along the anteroposterior direction. For the 60 directions encoding, non-diffusion-weighted and diffusion-weighted images were obtained with forward phase-encoding blips and non-diffusion-weighted images with the same parameter, except for the phase-encode blips, which had opposing polarities. FA images without and with distortion correction were compared in a voxel-wise manner with tract-based spatial statistics. We showed that images corrected with eddy and topup possessed higher FA values than images uncorrected and corrected with eddy_correct with trilinear (FSL default setting) or spline interpolation in most white matter skeletons, using both encoding schemes. Furthermore, the 60 directions encoding scheme was superior as measured by increased FA values to the 30 directions encoding scheme, despite comparable acquisition time. This study supports the combination of eddy and topup as a superior correction tool in diffusion imaging rather than the eddy_correct tool, especially with trilinear interpolation, using 60 directions encoding scheme.

Data management solution for large-volume computed tomography in an existing picture archiving and communication system (PACS).

Multidetector row computed tomography (MDCT) creates massive amounts of data, which can overload a picture archiving and communication system (PACS). To solve this problem, we designed a new data storage and image interpretation system in an existing PACS. Two MDCT image datasets, a thick- and a thin-section dataset, and a single-detector CT thick-section dataset were reconstructed. The thin-section dataset was archived in existing PACS disk space reserved for temporary storage, and the system overwrote the source data to preserve available disk space. The thick-section datasets were archived permanently. Multiplanar reformation (MPR) images were reconstructed from the stored thin-section datasets on the PACS workstation. In regular interpretations by eight radiologists during the same week, the volume of images and the times taken for interpretation of thick-section images with (246 CT examinations) or without (170 CT examinations) thin-section images were recorded, and the diagnostic usefulness of the thin-section images was evaluated. Thin-section datasets and MPR images were used in 79% and 18% of cases, respectively. The radiologists' assessments of this system were useful, though the volume of images and times taken to archive, retrieve, and interpret thick-section images together with thin-section images were significantly greater than the times taken without thin-section images. The limitations were compensated for by the usefulness of thin-section images. This data storage and image interpretation system improves the storage and availability of the thin-section datasets of MDCT and can prevent overloading problems in an existing PACS for the moment.