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Record W2021839708 · doi:10.1118/1.3182294

MO‐FF‐A3‐06: Preliminary Feasibility Study: Modeling 3D Deformations of the Prostate From Whole‐Mount Histology to in Vivo MRI

2009· article· en· W2021839708 on OpenAlex
Andrea McNiven, Joanne Moseley, DL Langer, MA Haider, K. Brock

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMedical Physics · 2009
Typearticle
Languageen
FieldEngineering
TopicMedical Imaging and Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIn vivoProstateMagnetic resonance imagingEx vivoHistologyProstatectomyContouringImage registrationFixation (population genetics)Biomedical engineeringNuclear medicineMedicineComputer sciencePathologyRadiologyArtificial intelligenceBiologyCancerImage (mathematics)

Abstract

fetched live from OpenAlex

Purpose : To investigate the accuracy of a 3D biomechanical model‐based deformation algorithm (MORFEUS) in modeling the prostate deformation that occurs between in vivo magnetic resonance imaging (MRI) and identification of the tumor on whole‐mount histology. Method and Materials : Three image sets were acquired for 10 patients: 1) in vivo T2‐weighted MR images acquired prior to prostatectomy, 2) ex vivo T2‐weighted MR images, and 3) digital images of the histological slices, rigidly registered to construct a 3D volumetric image. All three images sets were imported into the radiation treatment planning system for contouring. The entire prostate gland, the peripheral zone and central gland were contoured. The prostate was converted into a finite element model, where each zone was assigned the appropriate material property. Naturally occurring structural and morphological features ( e.g. urethra) were identified as verification points in the in vivo, ex vivo , and histological images, for quantification of the accuracy of the deformable registration. MORFEUS was used to model the deformations that occur due to excision and fixation either directly, deforming histology to in vivo MRI, or using a two‐step process, histology to in vivo MRI via an intermediate step, using ex vivo MRI. Results : Initial analysis has been completed for a subset of the patients. Uncertainties following rigid registration alone exceeded 8.0mm. No significant improvements were observed when including the intermediate deformation step. The average absolute error following deformable registration, based on the verification points, was 1.3, 1.2, and 1.9mm in the left/right, anterior/posterior, and superior/inferior directions, respectively. This error is smaller than the 3 mm image slice thickness. Conclusions : Substantial deformation confounds the ability to compare histology with in vivo imaging. Deformable registration using MORFEUS can be used to resolve the deformation, enabling quantitative evaluation of in vivo imaging based on histology as a gold standard for tumor definition.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score0.395

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 head0.015
GPT teacher head0.258
Teacher spread0.243 · 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