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Record W2950887882

Intracavitary Magnetic Resonance Elastography for Prostate Cancer Imaging

2014· dissertation· en· W2950887882 on OpenAlexaboutno aff
Arvin Forghanian-Arani

Bibliographic record

VenueTSpace (University of Toronto) · 2014
Typedissertation
Languageen
FieldMedicine
TopicUltrasound Imaging and Elastography
Canadian institutionsnot available
Fundersnot available
KeywordsElastographyProstate cancerMagnetic resonance elastographyProstateMagnetic resonance imagingMedicineCancerRadiologyMedical imagingBiomedical engineeringUltrasoundInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Prostate cancer is currently the most prevalent cancer and third leading cause of cancer related deaths amongst Canadian men. Highly sensitive, but non-specific, diagnostic techniques have made it challenging for clinicians to balance treatment efficacy with associated side-effects. Prostate imaging techniques are being investigated to assist in diagnosis, staging, monitoring, and localizing prostate cancer within the gland itself. Measuring changes in tissue biomechanics could provide important functional and morphological information about prostate cancer. Magnetic resonance elastography (MRE) is a potential candidate for imaging tissue mechanical properties, in vivo. MRE gives quantitative stiffness measurements by transmitting micrometer amplitude shear waves into tissues. Previous reports of performing MRE in prostate cancer patients have used an external source to generate shear waves inside the prostate, which has imposes limitations on the spatial resolution of the stiffness maps (elastograms). An alternative approach is to use an internal or intra-cavitary actuator to generate shear waves in closer proximity to the prostate in order to produce higher resolution elastograms. Since clinically significant prostate cancers can have diameters on the order of 1 cm, high resolution elastograms are essential in order to evaluate MRE as a potential tool for assisting in disease prognosis. This thesis demonstrates the technical feasibility of intra-cavitary (transurethral, endorectal) MRE for the purposes of evaluating localized regions of stiffness within the prostate gland. First, a combination of gel and canine experiments were performed to help outline the imaging characteristics of intra-cavitary MRE. Secondly, the feasibility of performing endorectal MRE by connecting a piezoceramic actuator to an endorectal radiofrequency receive coil while simultaneously preserving the signal to noise ratio of the acquired images wave demonstrated. Thirdly, the feasibility and tolerability of endorectal MRE in conjunction with current clinical endorectal RF coil designs was successfully demonstrated in human volunteers. This represented the first evaluation of endorectal MRE in humans. Lastly, a compliant mechanical amplifier was designed in order to develop a reliable high amplitude piezoceramic actuator for performing intracavitary MRE. Taken together, this work demonstrates the feasibility of intracavitary MRE and provides a method for locally probing the biomechanical properties of the prostate gland.

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)0.001
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.019
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0190.007

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 head0.005
GPT teacher head0.239
Teacher spread0.234 · 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".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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