Reducing Susceptibility Distortion Related Image Blurring in Diffusion MRI EPI Data

Diffusion magnetic resonance imaging (MRI) is an increasingly popular technique in basic and clinical neuroscience. One promising application is to combine diffusion MRI with myelin maps from complementary MRI techniques such as multi-parameter mapping (MPM) to produce g-ratio maps that represent the relative myelination of axons and predict their conduction velocity. Statistical Parametric Mapping (SPM) can process both diffusion data and MPMs, making SPM the only widely accessible software that contains all the processing steps required to perform group analyses of g-ratio data in a common space. However, limitations have been identified in its method for reducing susceptibility-related distortion in diffusion data. More generally, susceptibility-related image distortion is often corrected by combining reverse phase-encoded images (blip-up and blip-down) using the arithmetic mean (AM), however, this can lead to blurred images. In this study we sought to (1) improve the susceptibility-related distortion correction for diffusion MRI data in SPM; (2) deploy an alternative approach to the AM to reduce image blurring in diffusion MRI data when combining blip-up and blip-down EPI data after susceptibility-related distortion correction; and (3) assess the benefits of these changes for g-ratio mapping. We found that the new processing pipeline, called consecutive Hyperelastic Susceptibility Artefact Correction (HySCO) improved distortion correction when compared to the standard approach in the ACID toolbox for SPM. Moreover, using a weighted average (WA) method to combine the distortion corrected data from each phase-encoding polarity achieved greater overlap of diffusion and more anatomically faithful structural white matter probability maps derived from minimally distorted multi-parameter maps as compared to the AM. Third, we showed that the consecutive HySCO WA performed better than the AM method when combined with multi-parameter maps to perform g-ratio mapping. These improvements mean that researchers can conveniently access a wide range of diffusion-related analysis methods within one framework because they are now available within the open-source ACID toolbox as part of SPM, which can be easily combined with other SPM toolboxes, such as the hMRI toolbox, to facilitate computation of myelin biomarkers that are necessary for g-ratio mapping.

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Reducing susceptibility distortion related image blurring in diffusion MRI EPI data

10.1101/2021.06.07.447406 ◽

2021 ◽

Author(s):

Ian A Clark ◽

Martina F Callaghan ◽

Nikolaus Weiskopf ◽

Eleanor A Maguire ◽

Siawoosh Mohammadi

Keyword(s):

Diffusion Mri ◽

Statistical Parametric Mapping ◽

Weighted Average ◽

Distortion Correction ◽

Diffusion Data ◽

Wide Range ◽

Image Blurring ◽

Magnetic Resonance Imaging Mri ◽

New Processing ◽

G Ratio

Diffusion magnetic resonance imaging (MRI) is an increasingly popular technique in basic and clinical neuroscience. One promising application is to combine diffusion MRI with myelin maps from complementary MRI techniques such as multi-parameter mapping (MPM) to produce g-ratio maps that represent the relative myelination of axons and predict their conduction velocity. Statistical Parametric Mapping (SPM) can process both diffusion data and MPMs, making SPM the only widely accessible software that contains all the processing steps required to perform group analyses of g-ratio data in a common space. However, limitations have been identified in its method for reducing susceptibility-related distortion in diffusion data. More generally, susceptibility-related image distortion is often corrected by combining oppositely phase-encoded images (blip-up and blip-down) using the arithmetic mean (AM), however, this can lead to blurred images. In this study we sought to (1) improve the susceptibility-related distortion correction for diffusion MRI data in SPM; (2) deploy an alternative approach to the AM to reduce image blurring in diffusion MRI data when combining blip-up and blip-down EPI data after susceptibility-related distortion correction; and (3) assess the benefits of these changes for g-ratio mapping. We found that the new processing pipeline, called consecutive HySCO, improved distortion correction when compared to the standard approach in the ACID toolbox for SPM. Moreover, using a weighted average (WA) method to combine the distortion corrected data from each phase-encoding polarity achieved greater overlap of diffusion and more anatomically faithful structural white matter probability maps derived from minimally distorted multi-parameter maps as compared to the AM. Third, we showed that the consecutive HySCO WA performed better than the AM method when combined with multi-parameter maps to perform g-ratio mapping. These improvements mean that researchers can conveniently access a wide range of diffusion-related analysis methods within one framework because they are now available within the open-source ACID toolbox as part of SPM, which can be easily combined with other SPM toolboxes, such as the hMRI toolbox, to facilitate computation of myelin biomarkers that are necessary for g-ratio mapping.

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Role of Cardiac MRI in Detecting Familial Hypertrophic Cardiomyopathy: Review

Journal of Clinical and Health Sciences ◽

10.24191/jchs.v1i1.5846 ◽

2016 ◽

Vol 1 (1) ◽

pp. 4

Author(s):

Marymol Koshy ◽

Bushra Johari ◽

Mohd Farhan Hamdan ◽

Mohammad Hanafiah

Keyword(s):

Hypertrophic Cardiomyopathy ◽

Magnetic Resonance ◽

Genetic Disorder ◽

Familial Hypertrophic Cardiomyopathy ◽

Non Invasive ◽

Wide Range ◽

Proper Diagnosis ◽

Magnetic Resonance Imaging Mri ◽

Potential Use

Hypertrophic cardiomyopathy (HCM) is a global disease affecting people of various ethnic origins and both genders. HCM is a genetic disorder with a wide range of symptoms, including the catastrophic presentation of sudden cardiac death. Proper diagnosis and treatment of this disorder can relieve symptoms and prolong life. Non-invasive imaging is essential in diagnosing HCM. We present a review to deliberate the potential use of cardiac magnetic resonance (CMR) imaging in HCM assessment and also identify the risk factors entailed with risk stratification of HCM based on Magnetic Resonance Imaging (MRI).

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Multiparametric MRI Texture Analysis in Prediction of Glioma Biomarker Status: Added Value of MR Diffusion

Neuro-Oncology Advances ◽

10.1093/noajnl/vdab051 ◽

2021 ◽

Author(s):

Shingo Kihira ◽

Nadejda Tsankova ◽

Adam Bauer ◽

Yu Sakai ◽

Keon Mahmoudi ◽

...

Keyword(s):

Texture Analysis ◽

Diffusion Mri ◽

Test Group ◽

Multiparametric Mri ◽

Added Value ◽

Conventional Mri ◽

Mri Features ◽

Wide Range ◽

Mr Diffusion ◽

And Diffusion

Abstract Background Early identification of glioma molecular phenotypes can lead to understanding of patient prognosis and treatment guidance. We aimed to develop a multiparametric MRI texture analysis model using a combination of conventional and diffusion MRI to predict a wide range of biomarkers in patients with glioma. Methods In this retrospective study, patients were included if they 1) had diagnosis of gliomas with known IDH1, EGFR, MGMT, ATRX, TP53 and PTEN status from surgical pathology and 2) had preoperative MRI including FLAIR, T1c+ and diffusion for radiomic texture analysis. Statistical analysis included logistic regression and receiver-operating characteristic (ROC) curve analysis to determine the optimal model for predicting glioma biomarkers. A comparative analysis between ROCs (conventional only vs. conventional + diffusion) was performed. Results From a total of 111 patients included, 91 (82%) were categorized to training and 20 (18%) to test datasets. Constructed cross-validated model using a combination of texture features from conventional and diffusion MRI resulted in overall AUC/accuracy of 1/79% for IDH1, 0.99/80% for ATRX, 0.79/67% for MGMT, and 0.77/66% for EGFR. The addition of diffusion data to conventional MRI features significantly (p<0.05) increased predictive performance for IDH1, MGMT and ATRX. The overall accuracy of the final model in predicting biomarkers in the test group was 80% (IDH1), 70% (ATRX), 70% (MGMT) and 75% (EGFR). Conclusion Addition of MR diffusion to conventional MRI features provides added diagnostic value in preoperative determination of IDH1, MGMT, and ATRX in patients with glioma.

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Considerations of the Scale of Radiocarbon Offsets in the East Mediterranean, and Considering a Case for the Latest (Most Recent) Likely Date for the Santorini Eruption

Radiocarbon ◽

10.1017/s0033822200047202 ◽

2012 ◽

Vol 54 (3-4) ◽

pp. 449-474 ◽

Cited By ~ 13

Author(s):

Sturt W Manning ◽

Bernd Kromer

Keyword(s):

Time Horizon ◽

Weighted Average ◽

17Th Century ◽

Data Sets ◽

East Mediterranean ◽

Average Value ◽

Accuracy And Precision ◽

Wide Range ◽

The Impact ◽

East Mediterranean Region

The debate over the dating of the Santorini (Thera) volcanic eruption has seen sustained efforts to criticize or challenge the radiocarbon dating of this time horizon. We consider some of the relevant areas of possible movement in the14C dating—and, in particular, any plausible mechanisms to support as late (most recent) a date as possible. First, we report and analyze data investigating the scale of apparent possible14C offsets (growing season related) in the Aegean-Anatolia-east Mediterranean region (excluding the southern Levant and especially pre-modern, pre-dam Egypt, which is a distinct case), and find no evidence for more than very small possible offsets from several cases. This topic is thus not an explanation for current differences in dating in the Aegean and at best provides only a few years of latitude. Second, we consider some aspects of the accuracy and precision of14C dating with respect to the Santorini case. While the existing data appear robust, we nonetheless speculate that examination of the frequency distribution of the14C data on short-lived samples from the volcanic destruction level at Akrotiri on Santorini (Thera) may indicate that the average value of the overall data sets is not necessarily the most appropriate14C age to use for dating this time horizon. We note the recent paper of Soter (2011), which suggests that in such a volcanic context some (small) age increment may be possible from diffuse CO2emissions (the effect is hypothetical at this stage and hasnotbeen observed in the field), and that "if short-lived samples from the same stratigraphic horizon yield a wide range of14C ages, the lower values may be the least altered by old CO2." In this context, it might be argued that a substantive “low” grouping of14C ages observable within the overall14C data sets on short-lived samples from the Thera volcanic destruction level centered about 3326–3328 BP is perhaps more representative of the contemporary atmospheric14C age (without any volcanic CO2contamination). This is a subjective argument (since, in statistical terms, the existing studies using the weighted average remain valid) that looks to support as late a date as reasonable from the14C data. The impact of employing this revised14C age is discussed. In general, a late 17th century BC date range is found (to remain) to be most likelyeven ifsuch a late-dating strategy is followed—a late 17th century BC date range is thus a robust finding from the14C evidence even allowing for various possible variation factors. However, the possibility of a mid-16th century BC date (within ∼1593–1530 cal BC) is increased when compared against previous analyses if the Santorini data are considered in isolation.

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Automated quality control for within and between studies diffusion MRI data using a non-parametric framework for movement and distortion correction

NeuroImage ◽

10.1016/j.neuroimage.2018.09.073 ◽

2019 ◽

Vol 184 ◽

pp. 801-812 ◽

Cited By ~ 37

Author(s):

Matteo Bastiani ◽

Michiel Cottaar ◽

Sean P. Fitzgibbon ◽

Sana Suri ◽

Fidel Alfaro-Almagro ◽

...

Keyword(s):

Quality Control ◽

Diffusion Mri ◽

Distortion Correction ◽

Automated Quality Control ◽

Non Parametric

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Intratendinous ganglion cyst of peroneus brevis tendon and its reconstruction with semitendinosus graft

Vojnosanitetski pregled ◽

10.2298/vsp150521275f ◽

2017 ◽

Vol 74 (9) ◽

pp. 896-899

Author(s):

Igor Frangez ◽

Tea Nizic-Kos ◽

Matej Cimerman

Keyword(s):

Ganglion Cyst ◽

Peroneal Tendons ◽

Common Benign Tumor ◽

Wide Range ◽

Life Functioning ◽

Peroneus Brevis ◽

Magnetic Resonance Imaging Mri ◽

Semitendinosus Graft ◽

Sports Activities

Introduction. A ganglion cyst is a common benign tumor, mainly found in the wrist and ankle. The ones originating from a tendon, such as in our case, are the most rare. The ganglion cyst presents with a variety of symptoms, offering a wide range of possible differential diagnoses. Physical examination is crucial to make an accurate diagnosis, but magnetic resonance imaging (MRI) can help in identifying the ganglion cyst. The treatment is mostly conservative, but in cases when the ganglion cyst disables the patient?s ability for normal life functioning, due to pain and decreased mobility, surgery is necessary. Case report. A 38-year-old female with persistent ankle pain and edema was clinically diagnosed with luxation of peroneal tendons. Further investigation with MRI showed tenosynovitis of peroneal ten-dons and rupture of the superior peroneal retinaculum with an intratendinous ganglion cyst of peroneus brevis tendon. Surgical treatment with the reconstruction of peroneus brevis and peroneal retinaculum was performed with semitendinosus graft and anchor sutures. Histology confirmed the diagnosis of the intratendinous ganglion. After four months of rehabilitation, the patient returned to normal daily and sports activities and was pain-free on the follow-up. No recurrence of the ganglion cyst was acknowledged. Conclusion. Surgery is crucial for patients with intratendinous ganglion cyst and symptomatic instability of the peroneal tendons with chronic subluxation.

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Fixel-based Analysis of Diffusion MRI: Methods, Applications, Challenges and Opportunities

10.31219/osf.io/zu8fv ◽

2020 ◽

Author(s):

Thijs Dhollander ◽

Adam Clemente ◽

Mervyn Singh ◽

Frederique Boonstra ◽

Oren Civier ◽

...

Keyword(s):

Diffusion Mri ◽

State Of The Art ◽

Specific Information ◽

Analysis Framework ◽

Wide Range ◽

Challenges And Opportunities ◽

P Diffusion ◽

Modelling Techniques ◽

The Rich

Diffusion MRI has provided the neuroimaging community with a powerful tool to acquire in-vivo data sensitive to microstructural features of white matter, up to 3 orders of magnitude smaller than typical voxel sizes. The key to extracting such valuable information lies in complex modelling techniques, which form the link between the rich diffusion MRI data and various metrics related to the microstructural organisation. Over time, increasingly advanced techniques have been developed, up to the point where some diffusion MRI models can now provide access to properties specific to individual fibre populations in each voxel in the presence of multiple "crossing" fibre pathways. While highly valuable, such fibre-specific information poses unique challenges for typical image processing pipelines and statistical analysis. In this work, we review the "fixel-based analysis" (FBA) framework that implements bespoke solutions to this end, and has recently seen a stark increase in adoption for studies of both typical (healthy) populations as well as a wide range of clinical populations. We describe the main concepts related to fixel-based analyses, as well as the methods and specific steps involved in a state-of-the-art FBA pipeline, with a focus on providing researchers with practical advice on how to interpret results. We also include an overview of the scope of current fixel-based analysis studies (until August 2020), categorised across a broad range of neuroscientific domains, listing key design choices and summarising their main results and conclusions. Finally, we critically discuss several aspects and challenges involved with the fixel-based analysis framework, and outline some directions and future opportunities.

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Virtual Prototyping: Computational Device Placements within Detailed Human Heart Models

Applied Sciences ◽

10.3390/app10010175 ◽

2019 ◽

Vol 10 (1) ◽

pp. 175

Author(s):

Alex J. Deakyne ◽

Tinen L. Iles ◽

Alexander R. Mattson ◽

Paul A. Iaizzo

Keyword(s):

Anatomical Study ◽

3D Models ◽

Anatomical Models ◽

Cardiac Tissues ◽

Patient Demographics ◽

Wide Range ◽

Specific Device ◽

Mri Scans ◽

3D Printed ◽

Magnetic Resonance Imaging Mri

Data relative to anatomical measurements, spatial relationships, and device–tissue interaction are invaluable to medical device designers. However, obtaining these datasets from a wide range of anatomical specimens can be difficult and time consuming, forcing designers to make decisions on the requisite shapes and sizes of a device from a restricted number of specimens. The Visible Heart® Laboratories have a unique library of over 500 perfusion-fixed human cardiac specimens from organ donors whose hearts (and or lungs) were not deemed viable for transplantation. These hearts encompass a wide variety of pathologies, patient demographics, surgical repairs, and/or interventional procedures. Further, these specimens are an important resource for anatomical study, and their utility may be augmented via generation of 3D computational anatomical models, i.e., from obtained post-fixation magnetic resonance imaging (MRI) scans. In order to optimize device designs and procedural developments, computer generated models of medical devices and delivery tools can be computationally positioned within any of the generated anatomical models. The resulting co-registered 3D models can be 3D printed and analyzed to better understand relative interfaces between a specific device and cardiac tissues within a large number of diverse cardiac specimens that would be otherwise unattainable.

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