The processing of brain diffusion tensor imaging (DTI) data for large cohort studies requires fully automatic pipelines to perform quality control (QC) and artifact/outlier removal procedures on the ...raw DTI data prior to calculation of diffusion parameters. In this study, three automatic DTI processing pipelines, each complying with the general ENIGMA framework, were designed by uniquely combining multiple image processing software tools. Different QC procedures based on the RESTORE algorithm, the DTIPrep protocol, and a combination of both methods were compared using simulated ground truth and artifact containing DTI datasets modeling eddy current induced distortions, various levels of motion artifacts, and thermal noise. Variability was also examined in 20 DTI datasets acquired in subjects with vascular cognitive impairment (VCI) from the multi-site Ontario Neurodegenerative Disease Research Initiative (ONDRI). The mean fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were calculated in global brain grey matter (GM) and white matter (WM) regions. For the simulated DTI datasets, the measure used to evaluate the performance of the pipelines was the normalized difference between the mean DTI metrics measured in GM and WM regions and the corresponding ground truth DTI value. The performance of the proposed pipelines was very similar, particularly in FA measurements. However, the pipeline based on the RESTORE algorithm was the most accurate when analyzing the artifact containing DTI datasets. The pipeline that combined the DTIPrep protocol and the RESTORE algorithm produced the lowest standard deviation in FA measurements in normal appearing WM across subjects. We concluded that this pipeline was the most robust and is preferred for automated analysis of multisite brain DTI data.
We propose a novel image analysis framework to automate analysis of X‐ray microtomography images of sintering ceramics and glasses, using open‐source toolkits and machine learning. Additive ...manufacturing (AM) of glasses and ceramics usually requires sintering of green bodies. Sintering causes shrinkage, which presents a challenge for controlling the metrology of the final architecture. Therefore, being able to monitor sintering in 3D over time (termed 4D) is important when developing new porous ceramics or glasses. Synchrotron X‐ray tomographic imaging allows in situ, real‐time capture of the sintering process at both micro and macro scales using a furnace rig, facilitating 4D quantitative analysis of the process. The proposed image analysis framework is capable of tracking and quantifying the densification of glass or ceramic particles within multiple volumes of interest (VOIs) along with structural changes over time using 4D image data. The framework is demonstrated by 4D quantitative analysis of bioactive glass ICIE16 within a 3D‐printed scaffold. Here, densification of glass particles within 3 VOIs were tracked and quantified along with diameter change of struts and interstrut pore size over the 3D image series, delivering new insights on the sintering mechanism of ICIE16 bioactive glass particles in both micro and macro scales.
Background Cerebral small vessel disease is associated with higher ratios of soluble-epoxide hydrolase derived linoleic acid diols (12,13-dihydroxyoctadecenoic acid DiHOME and 9,10-DiHOME) to their ...parent epoxides (12(13)-epoxyoctadecenoic acid EpOME and 9(10)-EpOME); however, the relationship has not yet been examined in stroke. Methods and Results Participants with mild to moderate small vessel stroke or large vessel stroke were selected based on clinical and imaging criteria. Metabolites were quantified by ultra-high-performance liquid chromatography-mass spectrometry. Volumes of stroke, lacunes, white matter hyperintensities, magnetic resonance imaging visible perivascular spaces, and free water diffusion were quantified from structural and diffusion magnetic resonance imaging (3 Tesla). Adjusted linear regression models were used for analysis. Compared with participants with large vessel stroke (n=30), participants with small vessel stroke (n=50) had a higher 12,13-DiHOME/12(13)-EpOME ratio (β=0.251,
=0.023). The 12,13-DiHOME/12(13)-EpOME ratio was associated with more lacunes (β=0.266,
=0.028) but not with large vessel stroke volumes. Ratios of 12,13-DiHOME/12(13)-EpOME and 9,10-DiHOME/9(10)-EpOME were associated with greater volumes of white matter hyperintensities (β=0.364,
<0.001; β=0.362,
<0.001) and white matter MRI-visible perivascular spaces (β=0.302,
=0.011; β=0.314,
=0.006). In small vessel stroke, the 12,13-DiHOME/12(13)-EpOME ratio was associated with higher white matter free water diffusion (β=0.439,
=0.016), which was specific to the temporal lobe in exploratory regional analyses. The 9,10-DiHOME/9(10)-EpOME ratio was associated with temporal lobe atrophy (β=-0.277,
=0.031). Conclusions Linoleic acid markers of cytochrome P450/soluble-epoxide hydrolase activity were associated with small versus large vessel stroke, with small vessel disease markers consistent with blood brain barrier and neurovascular-glial disruption, and temporal lobe atrophy. The findings may indicate a novel modifiable risk factor for small vessel disease and related neurodegeneration.
PURPOSEMagnetic resonance imaging (MRI) scanner-specific geometric distortions may contribute to scanner induced variability and decrease volumetric measurement precision for multi-site studies. The ...purpose of this study was to determine whether geometric distortion correction increases the precision of brain volumetric measurements in a multi-site multi-scanner study. METHODSGeometric distortion variation was quantified over a one-year period at 10 sites using the distortion fields estimated from monthly 3D T1-weighted MRI geometrical phantom scans. The variability of volume and distance measurements were quantified using synthetic volumes and a standard quantitative MRI (qMRI) phantom. The effects of geometric distortion corrections on MRI derived volumetric measurements of the human brain were assessed in two subjects scanned on each of the 10 MRI scanners and in 150 subjects with cerebrovascaular disease (CVD) acquired across imaging sites. RESULTSGeometric distortions were found to vary substantially between different MRI scanners but were relatively stable on each scanner over a one-year interval. Geometric distortions varied spatially, increasing in severity with distance from the magnet isocenter. In measurements made with the qMRI phantom, the geometric distortion correction decreased the standard deviation of volumetric assessments by 35% and distance measurements by 42%. The average coefficient of variance decreased by 16% in gray matter and white matter volume estimates in the two subjects scanned on the 10 MRI scanners. CONCLUSIONGeometric distortion correction using an up-to-date correction field is recommended to increase precision in volumetric measurements made from MRI images.
Estimation of prostate location and volume is essential in determining a dose plan for ultrasound-guided brachytherapy, a common prostate cancer treatment. However, manual segmentation is difficult, ...time consuming and prone to variability. In this paper, we present a semi-automatic discrete dynamic contour (DDC) model based image segmentation algorithm, which effectively combines a multi-resolution model refinement procedure together with the domain knowledge of the image class. The segmentation begins on a low-resolution image by defining a closed DDC model by the user. This contour model is then deformed progressively towards higher resolution images. We use a combination of a domain knowledge based fuzzy inference system (FIS) and a set of adaptive region based operators to enhance the edges of interest and to govern the model refinement using a DDC model. The automatic vertex relocation process, embedded into the algorithm, relocates deviated contour points back onto the actual prostate boundary, eliminating the need of user interaction after initialization. The accuracy of the prostate boundary produced by the proposed algorithm was evaluated by comparing it with a manually outlined contour by an expert observer. We used this algorithm to segment the prostate boundary in 114 2D transrectal ultrasound (TRUS) images of six patients scheduled for brachytherapy. The mean distance between the contours produced by the proposed algorithm and the manual outlines was 2.70 +/- 0.51 pixels (0.54 +/- 0.10 mm). We also showed that the algorithm is insensitive to variations of the initial model and parameter values, thus increasing the accuracy and reproducibility of the resulting boundaries in the presence of noise and artefacts.
Atherosclerosis at the carotid bifurcation can result in cerebral emboli, which in turn can block the blood supply to the brain causing ischemic strokes. Noninvasive imaging tools that better ...characterize arterial wall, and atherosclerotic plaque structure and composition may help to determine the factors which lead to the development of unstable lesions, and identify patients at risk of plaque disruption and stroke. Carotid magnetic resonance (MR) imaging allows for the characterization of carotid vessel wall and plaque composition, the characterization of normal and pathological arterial wall, the quantification of plaque size, and the detection of plaque integrity. On the other hand, various ultrasound (US) measurements have also been used to quantify atherosclerosis, carotid stenosis, intima-media thickness, total plaque volume, total plaque area, and vessel wall volume. Combining the complementary information provided by 3D MR and US carotid images may lead to a better understanding of the underlying compositional and textural factors that define plaque and wall vulnerability, which may lead to better and more effective stroke prevention strategies and patient management. Combining these images requires nonrigid registration to correct the nonlinear misalignments caused by relative twisting and bending in the neck due to different head positions during the two image acquisition sessions. The high degree of freedom and large number of parameters associated with existing nonrigid image registration methods causes several problems including unnatural plaque morphology alteration, high computational complexity, and low reliability. Thus, a “twisting and bending” model was used with only six parameters to model the normal movement of the neck for nonrigid registration. The registration technique was evaluated using 3D US and MR carotid images at two field strengths, 1.5 and
3.0
T
, of the same subject acquired on the same day. The mean registration error between the segmented carotid artery wall boundaries in the target US image and the registered MR images was calculated using a distance-based error metric after applying a “twisting and bending” model based nonrigid registration algorithm. An average registration error of
1.4
±
0.3
mm
was obtained for
1.5
T
MR and
1.5
±
0.4
mm
for
3.0
T
MR, when registered with 3D US images using the nonrigid registration technique presented in this paper. Visual inspection of segmented vessel surfaces also showed a substantial improvement of alignment with this nonrigid registration technique compared to rigid registration.
Atherosclerosis at the carotid bifurcation resulting in cerebral emboli is a major cause of ischemic stroke. Most strokes associated with carotid atherosclerosis can be prevented by lifestyle/dietary ...changes and pharmacological treatments if identified early by monitoring carotid plaque changes. Registration of 3-D ultrasound (US) images of carotid plaque obtained at different time points is essential for sensitive monitoring of plaque changes in volume and surface morphology. This registration technique should be nonrigid, since different head positions during image acquisition sessions cause relative bending and torsion in the neck, producing nonlinear deformations between the images. We modeled the movement of the neck using a ldquotwisting and bendingrdquo model with only six parameters for nonrigid registration. We evaluated the algorithm using 3-D US carotid images acquired at two different head positions to simulate images acquired at different times. We calculated the mean registration error (MRE) between the segmented vessel surfaces in the target image and the registered image using a distance-based error metric after applying our ldquotwisting and bendingrdquo model-based nonrigid registration algorithm. We achieved an average registration error of 0.80 plusmn 0.26 mm using our nonrigid registration technique, which was a significant improvement in registration accuracy over rigid registration, even with reduced degrees-of-freedom compared to the other nonrigid registration algorithms.
Background
Homocysteine (Hcy) is an amino acid generated as a byproduct of methionine metabolism. It is a risk factor for vascular and neurodegenerative diseases. This study investigated ...relationships between plasma Hcy concentrations and neurodegenerative biomarkers in people clinically diagnosed with Alzheimer’s disease (AD) or mild cognitive impairment (MCI) due to AD.
Method
Participants were identified from the Ontario Neurodegenerative Disease Research Initiative. Brain parenchymal fraction (BPF) was quantified using T1‐ and T2‐weighted structural magnetic resonance imaging with an in‐house Semi‐Automated Brain Region Extraction and Lesion Explorer package. Plasma amyloid beta (Aβ) 42, Aβ40, phosphorylated tau 181 (p‐tau181), and neurofilament light chain (NfL) were measured with Single molecule array (Simoa) assays. Linear regression analyses were used to test associations between Hcy and neuroimaging or plasma biomarkers, controlling for age, sex, hypertension, hyperlipidemia, diabetes, cholesterol, and vitamin B12. Analyses were stratified by apolipoprotein E (APOE) ε4 carrier status (non‐carriers: n = 64, mean age = 70.9 years, 41% female; carriers: n = 62, mean age = 71.2 years, 50% female).
Result
In APOE ε4 non‐carriers, Hcy was associated negatively with BPF (β = ‐0.233, p = 0.047, 95% CI ‐0.460, ‐0.003), notably in temporal lobe regions in exploratory regional analyses. Hcy was also associated positively with plasma concentrations of NfL (β = 0.403, p = 0.007, 95% CI 0.117, 0.688) and p‐tau181 (β = 0.357, p = 0.023, 95% CI 0.051, 0.663) in APOE ε4 non‐carriers. Also, in APOE ε4 non‐carriers, Hcy was associated positively with Aβ40 (β = 0.367, p = 0.015, 95% CI 0.074, 0.660) and Aβ42 (β = 0.305, p = 0.041, 95% CI 0.012, 0.598), but not with the Aβ42/40 ratio (β = 0.155, p = 0.339, 95% CI ‐0.166, 0.476). None of these associations were seen in APOE ε4 carriers.
Conclusion
In non‐carriers of the APOE ε4 allele clinically diagnosed with AD or MCI, homocysteine was associated with Amyloid, tau and neurodegeneration. The specificity of these relationships to ε4 non‐carriers identifies a unique risk factor profile for AD that is independent of APOE ε4 status.
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