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Absorbed Radiation Doses During Tomographic Examinations in Dental Implant Planning: A Study in Humans

2010· article· en· W1504367201 on OpenAlexvenueno aff
Élton Gonçalves Zenóbio, Madelon Aparecida Fernandes Zenóbio, Maria S. Nogueira, Teógenes A. Silva, Jamil Awad Shibli

Bibliographic record

VenueClinical Implant Dentistry and Related Research · 2010
Typearticle
Languageen
FieldDentistry
TopicDental Radiography and Imaging
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineTomographyThyroidNuclear medicineDentistryRadiologyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of this human study was to evaluate the radiation doses in the buccal cavity and face, during panoramic, spiral conventional tomography, and helicoidal computerized tomography exams. MATERIAL AND METHODS: Lithium fluoride TL detectors (TLD-100) were placed on the skin at anatomic points such as parotid glands, submandibular glands, thyroid glands, and crystalline to assess the skin entrance dose in 19 patients who were to undergo dental implant surgery. RESULTS: In the panoramic exam, maximum doses were observed near the parotid glands at 1.57 (±18%) mGy on the right and 1.89 (±18%) mGy on the left. In the spiral conventional tomography exam, the maximum dose was 4.41 (±21%) mGy near the right and left parotid glands, whereas near the right or left submandibular glands, the maximum doses reached 40.7 (±18%) mGy. In the helicoidal computerized tomography for mandibular and maxilla exams, the maximum dose was 40.9 (±15%) mGy near the parotid glands and 41.0 (±18%) mGy near the submandibular glands. Near the thyroid and eye lens, doses were lower than 0.23 (±21%) in all exams. CONCLUSION: Regardless of the exam target area, the submandibular and parotid glands represented the most irradiated organs. This data suggests that efforts should be made by professionals to improve and optimize methods in order to reduce doses without losing the information necessary for treatment planning.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.004
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 head0.079
GPT teacher head0.452
Teacher spread0.373 · 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 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

Citations7
Published2010
Admission routes1
Has abstractyes

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