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Record W2900465221 · doi:10.1002/jmri.26336

Characterization of clinical human prostate cancer lesions using 3.0‐T sodium MRI registered to Gleason‐graded whole‐mount histopathology

2018· article· en· W2900465221 on OpenAlexafffund
Nolan Christopher Broeke, Justin Peterson, Joseph Lee, Peter R. Martin, Adam Farag, José A. Gómez, Madeleine Moussa, Mena Gaed, Joseph L. Chin, Stephen E. Pautler, Aaron D. Ward, Glenn Bauman, Robert Bartha, Timothy J. Scholl

Bibliographic record

VenueJournal of Magnetic Resonance Imaging · 2018
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsOntario Institute for Cancer ResearchRobarts Clinical TrialsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsProstate cancerMedicineHistopathologyEffective diffusion coefficientSpearman's rank correlation coefficientProstateNuclear medicineMagnetic resonance imagingRank correlationCorrelationRadiologyBiopsyCancerPathologyMathematicsInternal medicineStatistics

Abstract

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Background Overtreatment of prostate cancer (PCa) is a healthcare issue. Development of noninvasive imaging tools for improved characterization of prostate lesions might reduce overtreatment. Purpose To measure the distribution of tissue sodium concentration (TSC), proton T2‐weighted signal, and apparent diffusion coefficient (ADC) values in human PCa and to test the presence of a correlation between regional differences in imaging metrics and the Gleason grade of lesions determined from histopathology. Study Type Cross‐sectional. Subjects Ten men with biopsy‐proven PCa. Sequences/Field Strength Sodium, proton T2‐weighted, and diffusion‐weighted MRI data were acquired using Broad‐Band 3D‐Fast‐Gradient‐Recalled, 3D Cube (Isotropic 3D‐Fast‐Turbo‐Spin‐Echo acquisition) and 2D Spin‐Echo sequences, respectively, with a 3.0T MR scanner. Assessment All imaging data were coregistered to Gleason‐graded postprostatectomy histology, as the standard for prostate cancer lesion characterization. Regional TSC and T2 data were assessed using percent changes from healthy tissue of the same patient (denoted ΔTSC, ΔT2). Statistics Differences in ΔTSC, ADC, and ΔT2 as a function of Gleason score were analyzed for each imaging contrast using a one‐way analysis of variance or a nonparametric t‐test. Correlations between imaging data measures and Gleason score were assessed using a Spearman's ranked correlation. Results Evaluation of the correlation of ΔTSC, ADC, and ΔT2 datasets with Gleason scoring revealed that only the correlation between ΔTSC and Gleason score was statistically significant (rs = 0.791, p < 0.01), whereas the correlations of ADC and ΔT2 with Gleason score were not (rs = –0.306, p = 0.079 and r s = –0.069, p = 0.699, respectively). In addition, all individual patients showed monotonically increasing ΔTSC with Gleason score. Data Conclusion The results of this preliminary study suggest that changes in TSC, assessed by sodium MRI, has utility as a noninvasive imaging assay to accurately characterize PCa lesions. Sodium MRI may provide useful complementary information on mpMRI, which may assist the decision‐making of men choosing either active surveillance or treatment. Level of Evidence: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1409–1419.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.061
GPT teacher head0.384
Teacher spread0.323 · 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.

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".

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Citations15
Published2018
Admission routes2
Has abstractyes

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