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Record W4367300254 · doi:10.3389/fphys.2023.1133334

Comparison of ventilation defects quantified by Technegas SPECT and hyperpolarized 129Xe MRI

2023· article· en· W4367300254 on OpenAlexaff
Nisarg Radadia, Yonni Friedlander, Eldar Priel, Norman B. Konyer, Chynna Huang, Mobin Jamal, Troy Farncombe, Christopher Marriott, Christian Finley, John Agzarian, Myrna Dolovich, Michael D. Noseworthy, Parameswaran Nair, Yaron Shargall, Sarah Svenningsen

Bibliographic record

VenueFrontiers in Physiology · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAtomic and Subatomic Physics Research
Canadian institutionsSt. Joseph’s Healthcare HamiltonMcMaster University
Fundersnot available
KeywordsNuclear medicineMedicineDLCOVentilation (architecture)Diffusing capacityIntravoxel incoherent motionSpect imagingSingle-photon emission computed tomographyMagnetic resonance imagingDiffusion MRILungRadiologyInternal medicineLung functionPhysics

Abstract

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Introduction: The ideal contrast agents for ventilation SPECT and MRI are Technegas and 129 Xe gas, respectively. Despite increasing interest in the clinical utility of ventilation imaging, these modalities have not been directly compared. Therefore, our objective was to compare the ventilation defect percent (VDP) assessed by Technegas SPECT and hyperpolarized 129 Xe MRI in patients scheduled to undergo lung cancer resection with and without pre-existing obstructive lung disease. Methods: Forty-one adults scheduled to undergo lung cancer resection performed same-day Technegas SPECT, hyperpolarized 129 Xe MRI, spirometry, and diffusing capacity of the lung for carbon monoxide (DL CO ). Ventilation abnormalities were quantified as the VDP using two different methods: adaptive thresholding (VDP T ) and k-means clustering (VDP K ). Correlation and agreement between VDP quantified by Technegas SPECT and 129 Xe MRI were determined by Spearman correlation and Bland-Altman analysis, respectively. Results: VDP measured by Technegas SPECT and 129 Xe MRI were correlated (VDP T : r = 0.48, p = 0.001; VDP K : r = 0.63, p < 0.0001). A 2.0% and 1.6% bias towards higher Technegas SPECT VDP was measured using the adaptive threshold method (VDP T : 23.0% ± 14.0% vs. 21.0% ± 5.2%, p = 0.81) and k-means method (VDP K : 9.4% ± 9.4% vs. 7.8% ± 10.0%, p = 0.02), respectively. For both modalities, higher VDP was correlated with lower FEV 1 /FVC (SPECT VDP T : r = −0.38, p = 0.01; MRI VDP K : r = −0.46, p = 0.002) and DL CO (SPECT VDP T : r = −0.61, p < 0.0001; MRI VDP K : r = −0.68, p < 0.0001). Subgroup analysis revealed that VDP measured by both modalities was significantly higher for participants with COPD (n = 13) than those with asthma (n = 6; SPECT VDP T : p = 0.007, MRI VDP K : p = 0.006) and those with no history of obstructive lung disease (n = 21; SPECT VDP T : p = 0.0003, MRI VDP K : p = 0.0003). Discussion: The burden of ventilation defects quantified by Technegas SPECT and 129 Xe MRI VDP was correlated and greater in participants with COPD when compared to those without. Our observations indicate that, despite substantial differences between the imaging modalities, quantitative assessment of ventilation defects by Technegas SPECT and 129 Xe MRI is comparable.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.345
Threshold uncertainty score0.514

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 integrity0.0000.000
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 head0.021
GPT teacher head0.318
Teacher spread0.297 · 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".

Quick stats

Citations12
Published2023
Admission routes1
Has abstractyes

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