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Record W2120520892 · doi:10.1148/radiol.12111263

MR Volumetric Measurement of Low Rectal Cancer Helps Predict Tumor Response and Outcome after Combined Chemotherapy and Radiation Therapy

2012· article· en· W2120520892 on OpenAlexaff
Stéphanie Nougaret, Philippe Rouanet, Nicolas Molinari, Marie Ange Pierredon, Frédéric Bibeau, D. Azria, C. Lemanski, Eric Assénat, Jacqueline Duffour, Marc Ychou, Caroline Reinhold, B. Gallix

Bibliographic record

VenueRadiology · 2012
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Surgical Treatments
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineConfidence intervalColorectal cancerRadiation therapyNuclear medicineReceiver operating characteristicRetrospective cohort studyMagnetic resonance imagingStage (stratigraphy)Total mesorectal excisionT-stageCancerRadiologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE: To retrospectively determine whether magnetic resonance (MR) volumetry of rectal cancer is a reproducible method for predicting disease-free survival (DFS) in patients with locally advanced low or midrectal tumors who undergo combined chemotherapy and radiation therapy (CRT) before total mesorectal excision. MATERIALS AND METHODS: The institutional review board does not require approval for the use of patient data obtained for an observational retrospective study. Fifty-eight patients were included in the study; 42 patients had low-lying tumors. Two radiologists independently measured tumor volumes before and after CRT with use of semiautomated software. The radiologists were blinded to the clinical information for each patient. The tumor volume reduction ratio, circumferential resection margin, T stage, and occurrence of downstaging were compared with the histopathologic response and DFS. The threshold of tumor volume reduction for predicting DFS was assessed with receiver operating characteristic curve analysis. DFS was estimated with the Kaplan-Meier method and compared between groups with the log-rank test. RESULTS: The interobserver correlation coefficient between the two radiologists was 0.87 (95% confidence interval [CI]: 0.76, 0.93) for pre-CRT volumetry and 0.81 (95% CI: 0.74, 0.90) for post-CRT volumetry. A tumor volume reduction of at least 70% was significantly associated with good histologic regression (tumor regression grade [TRG], 3 or 4) (P <.0001) compared with a volume reduction rate of less than 70%. DFS was studied in 51 patients. The mean follow-up of survivors at the time of analysis was 52 months ± 20 (standard deviation). Patients with a volume reduction ratio of at least 70% had a higher DFS (P <.0001). Tumor volume reduction was an independent prognostic parameter in multivariate analysis for DFS (P = .003; 95% CI: 0.01, 0.4). CONCLUSION: The results demonstrate that volumetric measurements are reliable markers of rectal cancer prognosis, enabling the prediction of DFS and TRG. The cutoff of 70% is an easy parameter to use as a surrogate for clinical response to predict both TRG and outcome.

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)0.001
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 score0.498

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.026
GPT teacher head0.293
Teacher spread0.267 · 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

Citations108
Published2012
Admission routes1
Has abstractyes

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