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Record W2159187061 · doi:10.2967/jnumed.112.117515

Clinical Interpretation Standards and Quality Assurance for the Multicenter PET/CT Trial Rubidium-ARMI

2013· article· en· W2159187061 on OpenAlexaffabout
Jennifer M. Renaud, Ilias Mylonas, Brian McArdle, Taylor F. Dowsley, Kathy Yip, Éric Turcotte, Jean Guimond, Mikaël Trottier, Philipe Pibarot, Conor Maguire, Lucille D. Lalonde, Karen Y. Gulenchyn, Gerald Wisenberg, R. Glenn Wells, Terrence D. Ruddy, Benjamin J.W. Chow, Rob Beanlands, Robert A. deKemp

Bibliographic record

VenueJournal of Nuclear Medicine · 2013
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsSt Joseph's Health CareSt. Joseph’s Healthcare HamiltonUniversity of Alberta HospitalInstitut universitaire de cardiologie et de pneumologie de QuébecAlberta Hospital EdmontonCentre Hospitalier Universitaire de SherbrookeShared HealthUniversity of Ottawa
Fundersnot available
KeywordsSSS*Nuclear medicineIntraclass correlationConcordanceMedicineQuality assuranceConcordance correlation coefficientMyocardial perfusion imagingRadiologyPerfusionMathematicsExternal quality assessmentInternal medicineStatistics

Abstract

fetched live from OpenAlex

UNLABELLED: Rubidium-ARMI ((82)Rb as an Alternative Radiopharmaceutical for Myocardial Imaging) is a multicenter trial to evaluate the accuracy, outcomes, and cost-effectiveness of low-dose (82)Rb perfusion imaging using 3-dimensional (3D) PET/CT technology. Standardized imaging protocols are essential to ensure consistent interpretation. METHODS: Cardiac phantom qualifying scans were obtained at 7 recruiting centers. Low-dose (10 MBq/kg) rest and pharmacologic stress (82)Rb PET scans were obtained in 25 patients at each site. Summed stress scores, summed rest scores, and summed difference scores (SSS, SRS, and SDS [respectively] = SSS-SRS) were evaluated using 17-segment visual interpretation with a discretized color map. All scans were coread at the core lab (University of Ottawa Heart Institute) to assess agreement of scoring, clinical diagnosis, and image quality. Scoring differences greater than 3 underwent a third review to improve consensus. Scoring agreement was evaluated with intraclass correlation coefficient (ICC-r), concordance of clinical interpretation, and image quality using κ coefficient and percentage agreement. Patient (99m)Tc and (201)Tl SPECT scans (n = 25) from 2 centers were analyzed similarly for comparison to (82)Rb. RESULTS: Qualifying scores of SSS = 2, SDS = 2, were achieved uniformly at all imaging sites on 9 different 3D PET/CT scanners. Patient scores showed good agreement between core and recruiting sites: ICC-r = 0.92, 0.77 for SSS, SDS. Eighty-five and eighty-seven percent of SSS and SDS scores, respectively, had site-core differences of 3 or less. After consensus review, scoring agreement improved to ICC-r = 0.97, 0.96 for SSS, SDS (P < 0.05). The agreement of normal versus abnormal (SSS ≥ 4) and nonischemic versus ischemic (SDS ≥ 2) studies was excellent: ICC-r = 0.90 and 0.88. Overall interpretation showed excellent agreement, with a κ = 0.94. Image quality was perceived differently by the site versus core reviewers (90% vs. 76% good or better; P < 0.05). By comparison, scoring agreement of the SPECT scans was ICC-r = 0.82, 0.72 for SSS, SDS. Seventy-six and eighty-eight percent of SSS and SDS scores, respectively, had site-core differences of 3 or less. Consensus review again improved scoring agreement to ICC-r = 0.97, 0.90 for SSS, SDS (P < 0.05). CONCLUSION: (82)Rb myocardial perfusion imaging protocols were implemented with highly repeatable interpretation in centers using 3D PET/CT technology, through an effective standardization and quality assurance program. Site scoring of (82)Rb PET myocardial perfusion imaging scans was found to be in good agreement with core lab standards, suggesting that the data from these centers may be combined for analysis of the rubidium-ARMI endpoints.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.278
metaresearch head score (Gemma)0.203
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.278
Threshold uncertainty score0.891

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2780.203
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0040.001
Open science0.0040.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.044
GPT teacher head0.416
Teacher spread0.372 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreMethods

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

Citations44
Published2013
Admission routes2
Has abstractyes

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