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Record W7047062406

Evaluation of Patient Effective Dose of Neurovascular Imaging Protocols of a C-arm Cone-beam CT & Estimation of Current Source Radioactivity of a Cs-137 Irradiator

2012· dissertation· en· W7047062406 on OpenAlexaboutno aff

Bibliographic record

VenueDukeSpace (Duke University) · 2012
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicSuperconducting and THz Device Technology
Canadian institutionsnot available
Fundersnot available
KeywordsImaging phantomDosimetryIonization chamberNeurovascular bundleEffective dose (radiation)Dose profileCollimated lightMedical imagingIonizing radiation
DOInot available

Abstract

fetched live from OpenAlex

<p><bold>Purpose: </bold></p><p>(Project 1) The purpose of this study was three-fold: 1) to estimate the organ doses and effective dose (ED) for patients undergoing neurovascular imaging protocols, 2) to study the effect of beam collimation on ED for 3-D imaging protocols, and 3) to derive protocol-specific DAP-to-ED conversion factors.</p><p>(Project 2) The Cs-137 irradiator is one of the most commonly used irradiation device in radiobiological research. The purpose of this study is to develop a simple method to estimate the current source radioactivity of a Cs-137 irradiator (Mark I-68A, JL Shepherd). </p><p><bold>Material and Methods: </bold></p><p>(Project 1) A cone-beam CT system (Philips Allura Xper FD20/20) was used to measure the organ doses for seven 3-D (cone-beam CT and 3-D Rotational Angiography protocols) and eight 2-D (fluoroscopy and digital subtraction angiography) imaging protocols. Organ dose measurements were performed on an adult male anthropomorphic phantom (CIRS, Norfolk, VA) with 20 MOSFET detectors (Best Medical Canada, Ottawa, Canada) placed in selected organs. The dose area product (DAP) values were recorded from console. The ED values were computed by multiplying measured organ doses to corresponding ICRP 103 tissue weighting factors. The ED of four 3-D imaging protocols were also measured with standardized beam collimation to compare with the ED associated with the same protocols without beam collimation. </p><p>(Project 2) Three positions along the peak-dose irradiation direction within the irradiation chamber were picked as the reference dosimetry positions. Individual dose rate at each of these positions was measured by an ion chamber in "Gy/sec", as well as estimated by Monte Carlo simulation in "Gy/primary event". The source activity, "disintegration/sec", was then derived from these two sets of values and corrected by the branching ratio of the main 662 keV emission. </p><p><bold>Results: </bold></p><p>(Project 1) For the seven 3-D imaging protocols with uncollimated setting, the EDs ranged from 0.16 mSv to 1.6 mSv, and the DAP-to-ED conversion factors range from 0.037 to 0.17 mSv/Gy∙cm<super>2</super>. For four protocols with beam collimation, ED was reduced approximately by a factor of 2, and the DAP-to-ED conversion factors by approximately 30%. For the eight 2-D imaging protocols, the ED rates ranged from 0.02 mSv/sec to 0.04 mSv/sec (for DSA) and from 0.0011 mSv/sec to 0.0027 mSv/sec (for fluoroscopy), and the DAP-to-ED conversion factors range from 0.045 to 0.068 mSv/Gy∙cm<super>2</super> (for DSA) and factors range from 0.0029 to 0.059 mSv/Gy∙cm<super>2</super> (for fluoroscopy).</p><p>(Project 2) For the irradiator in question, the source activity, as of Nov. 17, 2011, was estimated to be 2770 Curies. The current activity from the manufacturer was calculated to be 5900 Curies.</p><p><bold>Conclusion: </bold></p><p>(Project 1) We have measured ED for standard adult neuro imaging protocols in a C-arm cone-beam CT system. Our results provide a simple means of ED estimation using DAP values from console in the C-arm cone-beam CT system.</p><p>(Project 2) Our method offers a convenient means to estimate the source activity. The result was compared to the value computed from the manufacturer. We have found discrepancies between the two: 41%, 86%, and 97%, assessed at location 1, 2, and 3, respectively.</p>

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 categoriesMeta-epidemiology (narrow)
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 score0.698
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.019
GPT teacher head0.285
Teacher spread0.266 · 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.

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

Citations0
Published2012
Admission routes1
Has abstractyes

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