Evidence map›Paper›PMID 32676365›Full record

ArticleQuantitative imaging in medicine and surgery2020

Serial assessment of iron in the motor cortex in limb-onset amyotrophic lateral sclerosis using quantitative susceptibility mapping.

Anjan Bhattarai, Zhaolin Chen, Phillip G D Ward, Paul Talman, Susan Mathers, Thanh G Phan, Caron Chapman, James Howe, Sarah Lee, Yennie Lie and 2 more

Open access · diamondAbstract read
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 14% 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, 1 synthesis or guideline pooled it, 26 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

12 authors at 4 institutions in 1 country.

Anjan BhattaraiDepartment of Psychiatry, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.
Zhaolin ChenMonash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.
Phillip G D WardMonash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.
Paul TalmanDepartment of Neuroscience, Barwon Health, Geelong, Victoria, Australia.
Susan MathersStatewide Progressive Neurological Services, Calvary Health Care Bethlehem, South Caulfield, Victoria, Australia.
Thanh G PhanDepartment of Neurology, Monash Health, and School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.
Caron ChapmanStatewide Progressive Neurological Services, Calvary Health Care Bethlehem, South Caulfield, Victoria, Australia.
James HoweStatewide Progressive Neurological Services, Calvary Health Care Bethlehem, South Caulfield, Victoria, Australia.
Sarah LeeStatewide Progressive Neurological Services, Calvary Health Care Bethlehem, South Caulfield, Victoria, Australia.
Yennie LieStatewide Progressive Neurological Services, Calvary Health Care Bethlehem, South Caulfield, Victoria, Australia.
Gary F EganMonash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.
Phyllis ChuaDepartment of Psychiatry, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.
Calvary Health Care Bethlehem · AUMonash University · AUBarwon Health · AUMonash Health · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDysregulation of iron in the cerebral motor areas has been hypothesized to occur in individuals with amyotrophic lateral sclerosis (ALS). There is still limited knowledge regarding iron dysregulation in the progression of ALS pathology. Our objectives were to use magnetic resonance based quantitative susceptibility mapping (QSM) to investigate the association between iron dysregulation in the motor cortex and clinical manifestations in patients with limb-onset ALS, and to examine changes in the iron concentration in the motor cortex in these patients over a 6-month period.

methodsIron concentration was investigated using magnetic resonance based QSM in the primary motor cortex and the pre-motor area in 13 limb-onset ALS patients (including five lumbar onset, six cervical onset and two flail arm patients), and 11 age- and sex-matched control subjects. Nine ALS patients underwent follow-up scans at 6 months.

resultsSignificantly increased QSM values were observed in the left posterior primary motor area (P=0.02, Cohen's d =0.9) and right anterior primary motor area (P=0.02, Cohen's d =0.92) in the group of limb-onset ALS patients compared to that of control subjects. Increased QSM was observed in the primary motor and pre-motor area at baseline in patients with lumbar onset ALS patients, but not cervical limb-onset ALS patients, compared to control subjects. No significant change in QSM was observed at the 6-month follow-up scans in the ALS patients.

conclusionsThe findings suggest that iron dysregulation can be detected in the motor cortex in limb-onset ALS, which does not appreciably change over a further 6 months. Individuals with lumbar onset ALS appear to be more susceptible to motor cortex iron dysregulation compared to the individuals with cervical onset ALS. Importantly, this study highlights the potential use of QSM as a quantitative radiological indicator in early disease diagnosis in limb-onset ALS and its subtypes. Our serial scans results suggest a longer period than 6 months is needed to detect significant quantitative changes in the motor cortex.

Indexed as

Amyotrophic lateral sclerosis (ALS)ironmagnetic resonance imaging (MRI)motor cortexquantitative susceptibility mapping (QSM)

Identifiers

PMID32676365
PMCPMC7358415
OpenAlexW3033598918

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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.