Evidence map›Paper›PMID 27560686›Full record

ArticlePloS one2016

Comparison of Diffusion MRI Acquisition Protocols for the In Vivo Characterization of the Mouse Spinal Cord: Variability Analysis and Application to an Amyotrophic Lateral Sclerosis Model.

Matteo Figini, Alessandro Scotti, Stefania Marcuzzo, Silvia Bonanno, Francesco Padelli, Victoria Moreno-Manzano, José Manuel García-Verdugo, Pia Bernasconi, Renato Mantegazza, Maria Grazia Bruzzone and 1 more

Open access · goldAbstract readComparative Study
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 24% 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

3 citing papers in PubMed, 5 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 3 institutions in 2 countries.

Matteo FiginiScientific Direction, Fondazione IRCCS Istituto Neurologico "Carlo Besta" Milan, Italy.
Alessandro ScottiScientific Direction, Fondazione IRCCS Istituto Neurologico "Carlo Besta" Milan, Italy.
Stefania MarcuzzoNeurology IV-Neuroimmunology and Neuromuscular Diseases Unit, Fondazione IRCCS Istituto Neurologico "Carlo Besta", Milan, Italy.
Silvia BonannoNeurology IV-Neuroimmunology and Neuromuscular Diseases Unit, Fondazione IRCCS Istituto Neurologico "Carlo Besta", Milan, Italy.
Francesco PadelliScientific Direction, Fondazione IRCCS Istituto Neurologico "Carlo Besta" Milan, Italy.
Victoria Moreno-ManzanoNeuronal and Tissue Regeneration Laboratory, Centro de Investigación Príncipe Felipe, Valencia, Spain.
José Manuel García-VerdugoUnidad de Neurobiología comparada, Universidad de Valencia, Valencia, Spain.
Pia BernasconiNeurology IV-Neuroimmunology and Neuromuscular Diseases Unit, Fondazione IRCCS Istituto Neurologico "Carlo Besta", Milan, Italy.
Renato MantegazzaNeurology IV-Neuroimmunology and Neuromuscular Diseases Unit, Fondazione IRCCS Istituto Neurologico "Carlo Besta", Milan, Italy.
Maria Grazia BruzzoneNeuroradiology, Fondazione IRCCS Istituto Neurologico "Carlo Besta", Milan, Italy.
Ileana ZuccaScientific Direction, Fondazione IRCCS Istituto Neurologico "Carlo Besta" Milan, Italy.
Fondazione IRCCS Istituto Neurologico Carlo Besta · ITCentro de Investigacion Principe Felipe · ESUniversitat de València · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diffusion-weighted Magnetic Resonance Imaging (dMRI) has relevant applications in the microstructural characterization of the spinal cord, especially in neurodegenerative diseases. Animal models have a pivotal role in the study of such diseases; however, in vivo spinal dMRI of small animals entails additional challenges that require a systematical investigation of acquisition parameters. The purpose of this study is to compare three acquisition protocols and identify the scanning parameters allowing a robust estimation of the main diffusion quantities and a good sensitivity to neurodegeneration in the mouse spinal cord. For all the protocols, the signal-to-noise and contrast-to noise ratios and the mean value and variability of Diffusion Tensor metrics were evaluated in healthy controls. For the estimation of fractional anisotropy less variability was provided by protocols with more diffusion directions, for the estimation of mean, axial and radial diffusivity by protocols with fewer diffusion directions and higher diffusion weighting. Intermediate features (12 directions, b = 1200 s/mm2) provided the overall minimum inter- and intra-subject variability in most cases. In order to test the diagnostic sensitivity of the protocols, 7 G93A-SOD1 mice (model of amyotrophic lateral sclerosis) at 10 and 17 weeks of age were scanned and the derived diffusion parameters compared with those estimated in age-matched healthy animals. The protocols with an intermediate or high number of diffusion directions provided the best differentiation between the two groups at week 17, whereas only few local significant differences were highlighted at week 10. According to our results, a dMRI protocol with an intermediate number of diffusion gradient directions and a relatively high diffusion weighting is optimal for spinal cord imaging. Further work is needed to confirm these results and for a finer tuning of acquisition parameters. Nevertheless, our findings could be important for the optimization of acquisition protocols for preclinical and clinical dMRI studies on the spinal cord.

Indexed as

Diffusion Magnetic Resonance ImagingAllelesAmyotrophic Lateral SclerosisAnimalsAnisotropyDiffusionDisease Models, AnimalImage Processing, Computer-AssistedMaleMiceMice, TransgenicMutationReproducibility of ResultsSignal-To-Noise RatioSpinal CordSuperoxide Dismutase-1SOD1 protein, humanSuperoxide Dismutase-1

Identifiers

PMID27560686
PMCPMC4999133
OpenAlexW2510782649

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Registered trials

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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.