Evidence map›Paper›PMID 30229564›Full record

ArticleMagnetic resonance in medicine2019

Relevance of time-dependence for clinically viable diffusion imaging of the spinal cord.

Francesco Grussu, Andrada Ianuş, Carmen Tur, Ferran Prados, Torben Schneider, Enrico Kaden, Sébastien Ourselin, Ivana Drobnjak, Hui Zhang, Daniel C Alexander and 1 more

Open access · hybridAbstract read
In one paragraph

Article in Magnetic resonance in medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
3.2field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 30 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 5 institutions in 4 countries.

Francesco GrussuQueen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.
Andrada IanuşCentre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom.
Carmen TurQueen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.
Ferran PradosQueen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.
Torben SchneiderPhilips United Kingdom, Guildford, Surrey, United Kingdom.
Enrico KadenCentre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom.
Sébastien OurselinCentre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom.
Ivana DrobnjakCentre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom.
Hui ZhangCentre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom.
Daniel C AlexanderCentre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom.
Claudia A M Gandini Wheeler-KingshottQueen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.
University College London · GBQueen Mary University of London · GBChampalimaud Foundation · PTNational University of Singapore · SGPhilips (United Kingdom) · GB

Funding

Craig H. Neilsen Foundation (USA) H2020-EU.3.1 (634541)Department of Health's National Institute for Health Research Biomedical Research Centres BRC R&D 03/10/RAG0449Engineering and Physical Sciences Research Council (EPSRC)EPSRC 634541EPSRC 666992-2EPSRC EP/I027084/1EPSRC G007748EPSRC H2020-EU.3.1EPSRC I027084EPSRC M020533EPSRC M507970EPSRC N018702European Committee for Research and Treatment in Multiple Sclerosis (ECTRIMS)Horizon 2020 (H2020) Framework Programme CDS-QuaMRI 634541International Spinal Research Trust (UK)Platform Grant for medical image computing for next-generation healthcare technology EP/M020533/1UK Multiple Sclerosis Society 892/08Wings for Life (Austria)
6 · The paper itself

Abstract

purposeTime-dependence is a key feature of the diffusion-weighted (DW) signal, knowledge of which informs biophysical modelling. Here, we study time-dependence in the human spinal cord, as its axonal structure is specific and different from the brain.

methodsWe run Monte Carlo simulations using a synthetic model of spinal cord white matter (WM) (large axons), and of brain WM (smaller axons). Furthermore, we study clinically feasible multi-shell DW scans of the cervical spinal cord (b = 0; b = 711 s mm

resultsBoth intra-/extra-axonal perpendicular diffusivities and kurtosis excess show time-dependence in our synthetic spinal cord model. This time-dependence is reflected mostly in the intra-axonal perpendicular DW signal, which also exhibits strong decay, unlike our brain model. Time-dependence of the total DW signal appears detectable in the presence of noise in our synthetic spinal cord model, but not in the brain. In WM in vivo, we observe time-dependent macroscopic and microscopic diffusivities and diffusion kurtosis, NODDI and two-compartment SMT metrics. Accounting for large axon calibers improves fitting of multi-compartment models to a minor extent.

conclusionsTime-dependence of clinically viable DW MRI metrics can be detected in vivo in spinal cord WM, thus providing new opportunities for the non-invasive estimation of microstructural properties. The time-dependence of the perpendicular DW signal may feature strong intra-axonal contributions due to large spinal axon caliber. Hence, a popular model known as "stick" (zero-radius cylinder) may be sub-optimal to describe signals from the largest spinal axons.

Indexed as

Diffusion Magnetic Resonance ImagingAdultAlgorithmsAxonsBrainComputer SimulationFemaleHealthy VolunteersHumansImage Processing, Computer-AssistedMaleMonte Carlo MethodSpinal CordTime Factorsdiffusion timemicrostructureMonte Carlo simulationsspinal cordwhite matter

Identifiers

PMID30229564
PMCPMC6586052
OpenAlexW2890639228

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.