Evidence map›Paper›PMID 32289460›Full record

ArticleNeuroImage2020

SANDI: A compartment-based model for non-invasive apparent soma and neurite imaging by diffusion MRI.

Marco Palombo, Andrada Ianus, Michele Guerreri, Daniel Nunes, Daniel C Alexander, Noam Shemesh, Hui Zhang

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in NeuroImage, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 212 papers.

0numbers the graph read from it
0cells of the map it votes in
212citing papers in PubMed
16.9field-weighted citation impact, top 1% 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

212 citing papers in PubMed, 331 citations in OpenAlex.

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  6. Diffusion MRI reveals amyloid plaque-associated cellular signatures through spatial transcriptomic integration.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
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152 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 2 countries.

Marco PalomboCentre for Medical Image Computing and Dept of Computer Science, University College London, London, UK. Electronic address: marco.palombo@ucl.ac.uk.
Andrada IanusCentre for Medical Image Computing and Dept of Computer Science, University College London, London, UK; Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal.
Michele GuerreriCentre for Medical Image Computing and Dept of Computer Science, University College London, London, UK.
Daniel NunesChampalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal.
Daniel C AlexanderCentre for Medical Image Computing and Dept of Computer Science, University College London, London, UK.
Noam ShemeshChampalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal.
Hui ZhangCentre for Medical Image Computing and Dept of Computer Science, University College London, London, UK.
University College London · GBChampalimaud Foundation · PT

Funding

Medical Research Council MR/T020296/1
6 · The paper itself

Abstract

This work introduces a compartment-based model for apparent cell body (namely soma) and neurite density imaging (SANDI) using non-invasive diffusion-weighted MRI (DW-MRI). The existing conjecture in brain microstructure imaging through DW-MRI presents water diffusion in white (WM) and gray (GM) matter as restricted diffusion in neurites, modelled by infinite cylinders of null radius embedded in the hindered extra-neurite water. The extra-neurite pool in WM corresponds to water in the extra-axonal space, but in GM it combines water in the extra-cellular space with water in soma. While several studies showed that this microstructure model successfully describe DW-MRI data in WM and GM at b ​≤ ​3,000 ​s/mm

Indexed as

Models, NeurologicalAdultAnimalsBrainCell BodyDiffusion Magnetic Resonance ImagingFemaleHumansMaleMiceMice, Inbred C57BLNeurites

Identifiers

PMID32289460
PMCPMC8543044
OpenAlexW3015618497

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.