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Record W2165039536 · doi:10.1259/bjr/23046051

Influence of post-treatment delay on the evaluation of the response to focused ultrasound surgery of breast cancer by dynamic contrast enhanced MRI

2006· article· en· W2165039536 on OpenAlexaff
Abdesslem Khiat, David Gianfelice, Mourad Amara, Yvan Boulanger

Bibliographic record

VenueBritish Journal of Radiology · 2006
Typearticle
Languageen
FieldMedicine
TopicMRI in cancer diagnosis
Canadian institutionsHôpital Saint-Luc
Fundersnot available
KeywordsMedicineMagnetic resonance imagingDynamic contrastUltrasoundNuclear medicineRadiologyBreast cancerBreast MRICancerMammographyInternal medicine

Abstract

fetched live from OpenAlex

The assessment of the effectiveness of MRI-guided focused ultrasound surgery (MRIgFUS) of breast carcinomas can be performed by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters which monitor the presence of residual tumour. The aim of this study was to evaluate the effect of the post-treatment delay on this assessment. DCE-MRI data were acquired immediately and 3-14 days after MRIgFUS treatment of 26 tumours (<7 days, n = 6; = or > ge;7 days, n = 20). The percentage of residual tumour was determined histologically on the resected mass and correlated with two DCE-MRI parameters: increase in signal intensity (ISI) and positive enhancement integral (PEI). No correlation could be found between DCE-MRI data acquired immediately after treatment and the percentage of residual tumour. Good correlation coefficients were found for data acquired several days after treatment (ISI, r = 0.749; PEI, r = 0.778). However, they were higher when the post-treatment time interval was 7 days or more (ISI, r = 0.962; PEI, r = 0.934). These results suggest that a post-treatment delay of 7 days is necessary for the accurate assessment of the presence of residual tumour by DCE-MRI parameters.

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)0.002
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.858
Threshold uncertainty score0.374

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.011
GPT teacher head0.285
Teacher spread0.273 · 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 designBench or experimental
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

Citations68
Published2006
Admission routes1
Has abstractyes

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