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An MRI Investigating of the Lower Limb Musculature in Patients with Chronic Inflammatory Demyelinating Polyneuropathy

2019· article· en· W3176982744 on OpenAlexafffund
Jacob Fanous, Kevin J. Gilmore, Kurt Kimpinski, Charles L. Rice

Bibliographic record

VenueThe FASEB Journal · 2019
Typearticle
Languageen
FieldMedicine
TopicPeripheral Neuropathies and Disorders
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMedicineChronic inflammatory demyelinating polyneuropathyThighVastus medialisMagnetic resonance imagingAnatomyWeaknessFemoral nerveSciatic nerveMuscle weaknessElectromyographyRadiologyPhysical medicine and rehabilitation

Abstract

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Introduction Chronic inflammatory demyelinating polyneuropathy (CIDP) is an autoimmune disease characterized by peripheral nerve demyelination. Patients present with sensory and motor deficits, including symmetrical diffused muscle weakness especially in distal muscles. Studies have focused mainly on the neuropathic aspects of CIDP and its involvement in paresis, showing lesions in various nerve plexes including the lumbar nerve roots. Weakness in patients with CIDP has been reported predominantly in the distal musculature. However, changes in muscle quality and quantity have not been explored systematically throughout the lower limb. Thus, the purpose of this study was to use magnetic resonance imaging (MRI) to compare anatomical differences in the quadriceps femoris and triceps surae muscle complexes in a group of patients with CIDP and control subjects. Methods To date, five patients with CIDP (3 males, 2 females) and six healthy controls (4 males, 2 females) and matched on age (45 to 68 years) have been investigated. On separate days, MRI (T1) of the lower limb musculature was acquired via serial axial plane scans in a 3.0‐Tesla magnet with a 3D FLASH sequence: (0.9mm slice thickness with slice separation of 1mm ranging from 280 to 400 slices). All MRI scans were analyzed using OsiriX imaging processing software. On a single thigh slice (two‐thirds distance proximal to distal) and leg slice (one‐third distance proximal to distal) total muscle area was computed for the quadriceps femoris (rectus femoris, vastus lateralis, vastus intermedius, vastus medialis), and the triceps surae (soleus, lateral and medial gastrocnemii) groups, respectively. Contractile muscle area (fat and connective tissue removed) for each muscle group was determined using a pixel threshold intensity algorithm. Percentage of fat infiltration was computed by subtracting contractile muscle area from total muscle area. Results Patients with CIDP had ~24% less total anatomical cross‐sectional area (ACSA) in both quadriceps femoris and the triceps surae compared to controls. Patients with CIDP, however had ~35% less contractile muscle tissue in the quadriceps femoris whereas the triceps surae were ~51% lower in contractile tissue, compared with controls. The ACSA of the triceps surae of CIDP patients consisted of ~40% fat whereas the quadriceps femoris ACSA had ~16% fat infiltration. Furthermore, the control group's ACSA consisted of ~9% and 5% fat, respectively in the triceps surae and quadriceps. Conclusion Patients with CIDP have less total thigh ACSA with increased intramuscular fat infiltration compared with controls indicative of lower muscle quality in CIDP. Fatty infiltration in the CIDP group are greater in the anterior thigh compared to posterior leg. This indicates that in addition to lower muscle quantity and quality in CIDP, distal musculature seems to be affected to a greater degree by the nerve impairments noted in CIDP. Support or Funding Information Supported by NSERC This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.346

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.207
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2019
Admission routes2
Has abstractyes

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