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Reliability of CBCT and Periapical Radiography Methods to Evaluate External Apical Root Resorption during Early Phase of Orthodontic Treatment

2018· article· pt· W2886604870 on OpenAlexaboutno aff
Giovani V Lago, Thaís Maria Freire Fernandes, Paula Vanessa Pedron Oltramari-Navarro, Márcio Rodrigues de Almeida, Victor de Miranda Ladewig, Ana Cláudia de Castro Ferreira Conti

Bibliographic record

VenueJournal of Health Sciences · 2018
Typearticle
Languagept
FieldDentistry
TopicDental Radiography and Imaging
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRoot resorptionOrthodonticsNuclear medicinePhysicsResorption

Abstract

fetched live from OpenAlex

A reabsorção radicular apical externa - RRAE é um efeito indesejável associado ao movimento dentário induzido. O objetivo deste estudo foi avaliar a confiabilidade de dois métodos radiográficos, a tomográfica computadorizada de feixe cônico - TCFC e a radiografia periapical (RP), para mensurar a RRAE. A amostra foi composta por 25 pacientes (média de idade de 18,02 ± 6,06 anos) com presença de apinhamento de moderado a severo. A RRAE foi verificada em RP e TCFC de incisivos superiores e inferiores em dois tempos (T1 – início do tratamento ortodôntico e T2 – seis meses após início do tratamento). As RRAE foi avaliada através de mensurações da diferença no comprimento dentário (T2-T1) de cada incisivo. Foram realizadas por dois examinadores previamente calibrados. Nas imagens obtidas pela TCFC, as medidas foram realizadas por meio do programa Dolphin (Chatsworth, Calif), já nas imagens das radiografias periapicais, no programa CorelDraw X5 (Ottawa, Candá). Os erros de medição intra e interexaminadores foram avaliados pelo Coeficiente de Correlação Intraclasse - CCI. Os valores obtidos foram comparados utilizando o teste t de student com nível de significância de 5%. Os resultados da comparação entre T1 e T2, tanto para a RP (0.92mm) quanto para a TCFC (0.25mm), evidenciaram a presença de RRAE para todos os dentes mensurados, com diferença estatisticamente significante. Ambos os métodos são confiáveis para avaliar a RRAE aos 6 meses após início do tratamento ortodôntico, contudo a diferença de magnitude entre as medidas obtidas entre os métodos não justifica a solicitação de TCFC somente para este fim.Palavras-chave: Dente. Ortodontia. Tomografia Computadorizada de Feixe Cônico. AbstractExternal apical root resorption (EARR) is an undesirable therapeutic effect associated with induced tooth movement. The aim of this studywas to evaluate the reliability of two methods, cone beam computed tomography (CBCT) and periapical radiography (PR), for measuringEARR during early phases of orthodontic treatment. The study included 25 patients (mean age, 18.02 ± 6.06 years) with moderate to severetooth crowding. Maxillary and mandibular incisors were evaluated in CBCT scans and PR at two different times: T1, at the beginning oforthodontic treatment; T2, 6 months after the treatment initiation. The difference in incisor length T2-T1, as measured by two independentcalibrated examiners, represented EARR. Measurements made on the images obtained by I-cat scanner (Hatfield,PA) were performed using theDolphin program (Chatsworth, Calif.). The PR images were imported to the CorelDraw X5 program (Ottawa, Canada). Intraclass correlationcoefficient (ICC) was used to measure intra- and inter-examiner errors. A Student’s t-test was used for comparing the results between CBCTand PR, with a significance level of 5%. All teeth showed EARR, using both periapical radiographs (0.92mm) and CBCT (0.25mm). Althoughthe difference between the results of the two techniques was statistically significant, its value was lower than 1mm for all teeth measured. Bothradiographic methods are suitable and reliable for assessing EARR after 6 months of initial orthodontic treatment. However, the differencein magnitude between the measurements obtained by the two methods does not justify requesting CBCT merely to assess EARR duringorthodontic treatment.Keywords: Tooth. Orthodontics. Cone-Beam Computed Tomography.

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)0.011
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.107
Threshold uncertainty score0.820

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
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 head0.069
GPT teacher head0.456
Teacher spread0.386 · 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.

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".

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Citations5
Published2018
Admission routes1
Has abstractyes

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