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Record W1632938191 · doi:10.2214/ajr.14.12547

Metal Artifact Reduction: Added Value of Rapid-Kilovoltage-Switching Dual-Energy CT in Relation to Single-Energy CT in a Piglet Animal Model

2015· article· en· W1632938191 on OpenAlex

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

VenueAmerican Journal of Roentgenology · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvanced X-ray and CT Imaging
Canadian institutionsUniversity of TorontoSaskatoon Medical ImagingMcMaster Children's HospitalSaskatchewan Health AuthorityHospital for Sick Children
Fundersnot available
KeywordsMedicineDual energyNuclear medicineReduction (mathematics)Animal modelValue (mathematics)Energy (signal processing)RadiologyPathologyInternal medicineStatisticsMathematics

Abstract

fetched live from OpenAlex

OBJECTIVE: The purpose of this article is to evaluate virtual monochromatic spectral imaging and metal artifact reduction software for reducing metal artifact and to compare it with conventional single-energy CT (SECT) in an animal model. MATERIALS AND METHODS: Postmortem juvenile (n = 5) and adult (n = 1) swine specimens were scanned with SECT followed by a dual-energy CT (DECT) pediatric protocol after the insertion of two rods into their paraspinal thoracolumbar regions. Virtual monochromatic spectral images were extrapolated from DECT images at five monoenergetic levels (64, 69, 75, 88, and 105 keV) with and without the use of metal artifact reduction software. Images were evaluated by a 5-point scoring system for the extent of metallic artifacts and image interpretability in soft-tissue and bone windows. The density in the most pronounced artifact was measured. CT dose index was recorded. RESULTS: In studies without metal artifact reduction software, higher energy reconstructions resulted in fewer artifacts and better image interpretability in both soft-tissue and bone windows (p < 0.0001). Artifact density decreased from -792 HU at 64 keV to -128 HU at 105 keV without the use of metal artifact reduction software. No difference was noted in attributes' scores or in artifact density in studies using metal artifact reduction software (p > 0.05). DECT studies showed lower scores compared with SECT with regard to all attributes. A new faint perimetallic hypodense halo was seen in all studies with metal artifact reduction software. The CT dose index of DECT was 1.18-3.56 times higher than that of SECT techniques. CONCLUSION: DECT at all energy levels with metal artifact reduction software and higher energy extrapolations without metal artifact reduction software reduced metallic artifact and enhanced image interpretability compared with SECT. Radiation dose with DECT could be significantly higher than SECT.

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 score0.136
Threshold uncertainty score0.933

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.017
GPT teacher head0.237
Teacher spread0.220 · 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