The bottom line: fiber tracking through edema with ODF-fingerprinting is improved by adding an anisotropy boosting term, even in clinically feasible single-shell #dMRI.
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#DMRI
Latest posts tagged with #DMRI on Bluesky
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Posts tagged #DMRI
We demonstrate the anisotropy boost in 19 glioma cases w/ substantial peritumoral edema. The method increases overlap between key tracts & edema. E.g., the arcuate fasciculus, crucial for language, shows improved tracking in both research (left) & clinical #dMRI (right).
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This example shows lateral corticospinal & corticobulbar projections traversing edematous white matter more clearly, improving fiber identification & tractography in both long multi-b-shell research #dMRI (left) & shorter single b-shell clinical acquisitions (right).
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On #dMRI, viable white matter tracts at tumor margins are often masked by vasogenic edema’s excess fluid. Protecting such tracts while optimizing resection volume helps minimize likelihood of post-operative deficits while maximizing chances of progression-free survival.
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Proud to share new work led by my lab’s Patryk Filipiak: tackling the hard problem of fiber #tractography for #neurosurgery through cerebral vasogenic edema—on real clinical #dMRI datasets. Now in MRM doi.org/10.1002/mrm.70314
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Non-invasive, millimetre-scale diffusion #MRI can be used to detect morphological changes in axons – a common hallmark of a wide range of neurological disorders, new research from 🇫🇮 @uniuef.bsky.social and the 🇺🇸 New York University (NYU) Grossman School of Medicine shows. #neurology #dMRI
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Neurological reference standards can solve non-obvious and costly problems in neuroimaging data quality.
A short thread…
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#MRI #dMRI #diffusionMRI #neurosky #neuro #neurorad #neuroradiology #neuroscience #imagingstudies #radiologyAI
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⏰ Quick reminder:
Registration for the IST Winter School Verona 2026 is still open! Join us in February for a hands-on tractography workshop.
Sign up: event.fourwaves.com/istwintersch...
#Tractography #DMRI #Neuroscience
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Diffusion MRI of the human heart provides unique insight into myocardial microstructure but has been hampered by cardiac and respiratory motion, short T2 of the heart muscle, and limited gradient strength. Recent advances in ultra-strong gradient technology not only help to overcome these technical challenges but also allow higher diffusion weighting (i.e., b-values) with clinically compatible echo times. The authors demonstrate how this enabled in vivo diffusion kurtosis imaging (DKI) and q-space trajectory imaging (QTI) in the beating human heart, therefore moving beyond the Gaussian assumptions of diffusion tensor imaging (DTI). These advances may pave the way for more sensitive biomarkers of pathological changes of the myocardium and bring microstructural imaging closer to clinical application. Key points • Ultra-strong gradients (300 mT/m) make cardiac diffusion MRI feasible at higher b-values. • In vivo cardiac diffusion kurtosis imaging and q-space trajectory imaging (QTI) were demonstrated with clinically compatible echo times. • Kurtosis and QTI metrics reveal non-Gaussian diffusion, offering access to new imaging biomarkers of myocardial microstructure. • Translation to clinical systems is within reach with new 200 mT/m gradient scanners. Shoutout and thank you to the co-authors: Lars Mueller, Ph.D.; Jürgen E Schneider, Ph.D. (Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK) Derek K Jones, Ph.D. (Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK) Filip Szczepankiewicz, Ph.D. (Department of Medical Radiation Physics, Lund University, Lund, Sweden) Fabrizio Fasano, Ph.D. (Siemens Healthineers)
Unlocking the Heart’s #Microstructure: Cardiac #Diffusion #MRI with Ultra-Strong Gradients by Maryam Afzali, PhD; et al. (@universityofleeds.bsky.social).
marketing.webassets.siemens-healthineers.com/0267aa50bc95...
@deekayjay.bsky.social
#dMRI #RadSky #CardioSky #MagnetomWorld
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DM us or email for more information. Details in bio!
#dMRI #neurosky #neurorad #MRI #neuroscience
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Designed for PhD students, postdocs, clinical scientists & researchers in neuroscience, psychology, radiology, & related fields.
#Tractography #DMRI #Neuroscience #MedicalImaging #ISTWinterSchool #Verona2026
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The choice of preprocessing pipeline for #diffusion-weighted #MRI introduces clinically important variability in parameter estimates from peripheral nerves
doi.org/10.1002/mrm....
#dMRI #DWI #nerve
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The tracts were thresholded to the required values to get connectivity along the length of the bundle, between the termini positions indicated by yellow spheres and used as termination masks for the tractography.
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#MRI #dMRI #DTI #neurorad #medicalimaging
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A short thread on partial voxel effects in MR imaging:
This figure shows the effects of partial volume on FA on 2 white matter simulating modules with diameter 5.9 mm (along S-I, in green) and 4.3 mm (along R-L, in red).
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#mri #dmri #neurorad
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Cientistas desenvolveram uma droga capaz de reverter danos na retina e restaurar a visão, ativando mecanismos naturais de reparo. Testada em animais
Matéria completa - regisandrade.com.br/nova-droga-p...
#retina #visao #cegueira #medicinaregenerativa #dmri #tecnologiademedica #descobertacientifica
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Extending conventional DWI to include advanced diffusion encoding and image readouts brings the field closer to realizing the promise of a “virtual microscope.” These advancements rely on high-performance MRI systems, with particular emphasis on the gradient system. Importantly, a vast majority of advanced DWI methods gain marked improvement in data quality from ultra- strong gradients and more efficient readout strategies, and the exploration of biomarkers can be extended to include experimental designs that were previously either too slow or yielded insufficient SNR. Such developments are particularly promising for prostate imaging, offering high-fidelity high-resolution images that reflect ever more subtle features of tissue microstructure—enhancing detection, diagnostics, and treatment monitoring. The authors present early insights into the novel information made accessible by new hardware, and how this drives further development in the context of prostate cancer imaging. As powerful MRI systems become commercially available worldwide, strong-gradient technology will facilitate new imaging biomarkers, likely playing a fundamental role in everyday clinical diagnosis and advancement of individualized precision medicine.
#MRI of the #Prostate: The Promise of Ultra-Strong Gradients and Advanced Microstructural Imaging by Dr Molendowska, @deekayjay.bsky.social, et al (Lund University & CUBRIC)
Learn more marketing.webassets.siemens-healthineers.com/f0c8b5c08fab...
#dMRI #DWI #Microstructure
@tomhilbertmri.bsky.social
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Ever wondered how neuroscientists “see” inside your brain using MRI?
MRI is like using magnets to take high-tech selfies of your #brain!
• sMRI = snapshot of brain anatomy.
• fMRI = movie of brain activity.
• dMRI = Google Maps for brain connections.
#Neuroscience #OHBM #MRI #dMRI #fMRI #ISMRM
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#NewNProt: Structural connectome atlases using #MRtrix3 software to process #dMRI data bit.ly/4hdlMuZ
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Photo: A view of Kyoto from Kiyomizudera.
This week, nearly a dozen of our center's scientists taught, moderated sessions, & shared latest research at a #diffusion #MRI workshop held by the @ismrm.bsky.social in Kyoto, celebrating a remarkable 40 years of #dMRI.
Big thanks to all the organizers & participants for a great meeting!
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Day 4 ISMRM Diffusion #MRI Workshop! Today is the most relevant for me, we are hearing about how we can translate research into the clinic to improve diagnostics and treatment, and use AI and big data. There is also a secret session 🤫 on MRI and brain development! 🧠🩻🧑🔬⚛️🧪 #dMRI #science #research
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We are on the 3rd day of the ISMRM Diffusion MRI workshop! Today we are hearing about (1) brain microstructure and validation and (2) diffusion in the body and oncology. 🧠🩻⚛️🧑🔬🧪 #MRI #DiffusionMRI #dMRI #trainees #academia #science #health #medicine #physics
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Fresh from the press!
Head Motion in Diffusion Magnetic Resonance Imaging: Quantification, Mitigation, and Structural Associations in Large, Cross-Sectional Datasets Across the Lifespan
Thanks to Kurt Schilling et al. for including me!
dx.doi.org/10.1002/hbm....
#dMRI
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Starting soon!
Meet us at the Canadian Pavilion, booth 8326 in the North Hall and get introduced to our #neuroimaging ground truth & reference standard solutions.
🧠 anisotropic diffusion phantom technology
#dMRI #neurorad
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Only a few days until #RSNA2024!
Connect with us for an intro to our anisotropic diffusion phantom technology, with modules that emulate the structure & in-vivo response of WM to human safe protocols
🧠 Ontario Pavilion, booth 8326 in the North Hall
#neuroimaging #dMRI #neurorad
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We're excited to release new versions of our BIDS-Apps for processing and analyzing #dmri data, QSIPrep and QSIRecon! Our team has been working hard to prepare these pipelines to process infant data and bring them in line with the @nipreps.bsky.social ecosystem. #neuroimaging #nipreps #bids 1/10
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Now that this platform seems to be (blue)skyrocketing, it is probably good time to share my research topic: cracking the brain with #dMRI
#MRI #minätutkin
youtu.be/8lw-wkL3vXY?...
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Here is an example in Python how to combine functional and structural #brain connectivity (fc&sc) matrices:
github.com/vilsaira/FSC
Surprisingly simple to apply:
> from fsc import fsc
> fscm = fsc(V=fc, R=sc).get_I()
biorxiv.org/content/10.1...
#dipymri #Connectivity #fMRI #dMRI
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Three years from idea to preprint but here it is: a macro-scale model combining functional and structural connectivity matrices of the human brain networks.
This is a technical report so not applied to any clinical data yet.
www.biorxiv.org/content/10.1...
#neuroimaging #fMRI #dMRI #connectivity
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Difference in the model variance between replacing and downweighting outliers. Lines indicate the average and shaded areas indicate the standard deviation calculated over the ten simulated brains. Due to only one 0% frequency simulation, there is only one data point and no variance to show. With replacement approaches, the estimated precision of the model parameters is inflated which is seen as a downward trend for both GP repol and SH repol. In contrast, with the downweighting approach, the estimated precision decreases as the outlier frequency increases which is seen as an upward trend for both GP weighted and SH weighted. The latter is the expected behaviour, as clearly the precision will go down with the increasing frequency of missing data. Regardless of the approach, when the point of too many outliers is reached (approximately 12% here), problems arising from image registration start to take effect and the linear trends disappear.
For #dMRI folks: what to do if your data contains motion outliers? Should you: Ignore them (definitely not!), replace them, or use weighted modelling?
Replacement can lead into inflation of model precision as shown in figure. More details here: www.sciencedirect.com/science/arti...
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