Evidence map›Paper›PMID 28928705›Full record

ReviewFrontiers in neurology2017

The Role of T1-Weighted Derived Measures of Neurodegeneration for Assessing Disability Progression in Multiple Sclerosis.

Maria A Rocca, Giancarlo Comi, Massimo Filippi

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in neurology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed, 2 pooled it
5.7field-weighted citation impact, top 3% 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

40 citing papers in PubMed, 2 syntheses or guidelines pooled it, 73 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Article
  5. Observational
  6. Article
  7. Current Clinical Applications of Structural MRI in Neurological Disorders.Journal of clinical neurology (Seoul, Korea) · 2025
    Review
  8. Observational
  9. Observational
  10. Article
  11. Article
  12. Article
  13. Review
  14. Observational
  15. Article
  16. Automatic deep learning multicontrast corpus callosum segmentation in multiple sclerosis.Journal of neuroimaging : official journal of the American Society of Neuroimaging · 2022
    Article
  17. Predictive MRI Biomarkers in MS-A Critical Review.Medicina (Kaunas, Lithuania) · 2022
    Review
  18. Observational
  19. Review
  20. Article
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

3 authors at 1 institution in 1 country.

Maria A RoccaNeuroimaging Research Unit, Institute of Experimental Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.
Giancarlo ComiDepartment of Neurology, Institute of Experimental Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.
Massimo FilippiNeuroimaging Research Unit, Institute of Experimental Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.
Vita-Salute San Raffaele University · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionMultiple sclerosis (MS) is characterised by the accumulation of permanent neurological disability secondary to irreversible tissue loss (neurodegeneration) in the brain and spinal cord. MRI measures derived from T1-weighted image analysis (i.e., black holes and atrophy) are correlated with pathological measures of irreversible tissue loss. Quantifying the degree of neurodegeneration

methodsA systematic PubMed search was conducted in January 2017 to identify MRI studies in MS patients investigating the relationship between "black holes" and/or atrophy in the brain and spinal cord, and disability. Results were limited to human studies published in English in the previous 10 years.

resultsA large number of studies have evaluated the association between the previous MRI measures and disability. These vary considerably in terms of study design, duration of follow-up, size, and phenotype of the patient population. Most, although not all, have shown that there is a significant correlation between disability and black holes in the brain, as well as atrophy of the whole brain and grey matter. The results for brain white matter atrophy are less consistently positive, whereas studies evaluating spinal cord atrophy consistently showed a significant correlation with disability. Newer ways of measuring atrophy, thanks to the development of segmentation and voxel-wise methods, have allowed us to assess the involvement of strategic regions of the CNS (e.g., thalamus) and to map the regional distribution of damage. This has resulted in better correlations between MRI measures and disability and in the identification of the critical role played by some CNS structures for MS clinical manifestations.

conclusionThe evaluation of MRI measures of atrophy as predictive markers of disability in MS is a highly active area of research. At present, measurement of atrophy remains within the realm of clinical studies, but its utility in clinical practice has been recognized and barriers to its implementation are starting to be addressed.

Indexed as

atrophyblack holesdisabilitymagnetic resonance imagingmultiple sclerosisneurodegeneration

Identifiers

PMID28928705
PMCPMC5591328
OpenAlexW2751996357

What OpenQuestion holds

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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.