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Record W2990184020 · doi:10.1016/j.nicl.2019.102103

Imaging the Nigrosome 1 in the substantia nigra using susceptibility weighted imaging and quantitative susceptibility mapping: An application to Parkinson's disease

2019· article· en· W2990184020 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueNeuroImage Clinical · 2019
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsnot available
FundersScience and Technology Commission of Shanghai MunicipalityNational Natural Science Foundation of ChinaM.S.I. Foundation
KeywordsSubstantia nigraQuantitative susceptibility mappingPars compactaParkinson's diseaseSusceptibility weighted imagingBasal gangliaParkinsonismNeurosciencePrecuneusMedicineMagnetic resonance imagingPathologyPsychologyDiseaseRadiologyCentral nervous systemFunctional magnetic resonance imaging

Abstract

fetched live from OpenAlex

Parkinson's disease (PD) is a clinically heterogeneous chronic progressive neuro-degenerative disease with loss of dopaminergic neurons in the nigrosome 1 (N1) territory of the substantia nigra pars compacta (SNpc). To date, there has been a major effort to identify changes in the N1 territory by monitoring increases of iron in the SNpc. However, there is no standard protocol being used to visualize or characterize the N1 territory. Therefore, the purpose of this study was to create a robust high quality, rapid imaging protocol, determine a slice by slice characterization of the appearance of N1 (the "N1 sign") and evaluate the loss of the N1 sign in order to differentiate healthy controls (HCs) from patients with PD. Firstly, one group of 10 HCs was used to determine the choice of imaging parameters. Secondly, another group of 80 HCs was used to characterize the appearance of the N1 sign and train the raters. In this step, the magnitude, susceptibility weighted images (SWI), quantitative susceptibility maps (QSM) and true SWI (tSWI) images were all reviewed using data from a 3D gradient recalled echo sequence. A resolution of 0.67 mm × 0.67 mm × 1.34 mm was chosen based on the ability to cover all the basal ganglia, midbrain and dentate nucleus with good signal-to-noise with echo times of 11 ms and 20 ms. Thirdly, 80 Parkinsonism and related disorders patients [idiopathic Parkinson's disease (IPD): 57; atypical parkinsonian syndromes (APs): 14; essential tremor (ET): 9] and one additional group of 80 age-matched HCs were blindly analyzed for the presence or absence of the N1 sign for a differential diagnosis. From the first group of 80 HCs, all of the 76 (100%) cases (4 were excluded due to motion artifacts) showed the N1 sign in one form or another after reviewing the first 5 caudal slices of the SN. For the second group of 80 HCs, 78 (97.5%) showed the N1 sign in at least 2 slices. Of the 80 Parkinsonism and related disorders patients, 32 (56.1%, 32/57) IPD and 6 (42.9%, 6/14) APs showed a bilateral loss of the N1 sign, 12 (21.1%, 12/57) IPD and 6 (42.9%, 6/14) APs showed the N1 sign unilaterally and 13 (22.8%, 13/57) IPD and 2 (14.2%, 2/14) APs showed the N1 sign bilaterally. Also, all 9 (100%, 9/9) ET patients showed the N1 sign bilaterally. The mean total structure and mean high susceptibility region for the SN for both IPD and APs patients with bilateral loss of N1 were higher than those of the HCs (p < 0.002). In conclusion, the N1 sign can be consistently visualized using tSWI with a resolution of at least 0.67 mm × 0.67 mm × 1.34 mm and can be seen in 95% of HCs.

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.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.036
Threshold uncertainty score0.881

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.059
GPT teacher head0.370
Teacher spread0.311 · 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