Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

Aim: The objective of this study was to compare the accuracy of working length (WL) determination by X-Smart Dual, ENDOAce, and Gold Reciproc motor, in manual mode and mechanical preparation set to auto apical reverse (AAR) mode.

Materials And Methods: Forty-five anterior teeth were included in the study. The canal length was determined by introducing #10 file into the canal until it emerged at the apical foramen. The incisal edges were adjusted to obtain 18 mm standard length. The teeth were embedded in Plexiglas tubes, filled with alginate, and measured in manual and AAR modes.

Results: Within and between the groups, there was no significant difference in WL measurements, both in manual and AAR modes. In the X-Smart Dual group, all manual measurements were within root canal limits, while 13 % of AAR mode measurements were recorded when the file tip passed the apical foramen. In the ENDOAce group, 13 and 7 % of the measurements, in manual and AAR modes respectively, were recorded when the file tip passed the foramen. In the Gold Reciproc motor group, 27 and 33 % of the measurements, in manual and AAR modes respectively, were recorded when the file tip passed the foramen.

Conclusion: With the limitation of this ex vivo study, the tested devices presented no significant differences in length measurements and were within the clinical accepted margin of error.

Clinical Relevance: Mechanical preparation must be confined to the root canal system. The adverse results of overinstrumentation emphasize the need to reconsider the ±0.50 mm margin of error that is clinically acceptable for WL measurements.

Download full-text PDF

Source
http://dx.doi.org/10.1007/s00784-016-1903-3DOI Listing

Publication Analysis

Top Keywords

manual aar
16
root canal
12
measurements manual
12
aar modes
12
recorded file
12
file passed
12
working length
8
length determination
8
canal length
8
x-smart dual
8

Similar Publications

Wrist-worn photoplethysmography (PPG) enables scalable, long-term unobtrusive sleep monitoring through the expression of sympathetic and parasympathetic activity in heart rate variability. However, interindividual differences in the sympatho-vagal balance may inherently limited general PPG-based sleep staging models. This study investigates whether learning individual autonomic representations through model personalization can improve PPG based automated sleep staging performance.

View Article and Find Full Text PDF

Purpose: The purpose of this study is to evaluate the effectiveness of an artificial intelligence (AI)-assisted review (AAR) system in improving diagnostic accuracy, efficiency, and concordance with expert assessments during the evaluation of donor kidney viability.

Methods: Sixty H&E-stained frozen-section kidney biopsy slides from explant kidneys obtained for organ donation were evaluated. A board-certified renal pathologist established ground truth (GT) through manual digital evaluation on the Techcyte Fusion Platform.

View Article and Find Full Text PDF

Background: Endometrial and endocervical biopsy sampling provides critical information for diagnosing and planning treatment in cases of abnormal uterine bleeding or suspected gynecological conditions. However, documented failure rates of up to one-third due to difficulties accessing the uterine cavity or insufficient histological sampling might have considerable clinical consequences.

Aim: To assess the impact of female sexual dysfunction (FSD), depression, and anxiety on additional analgesic requirements (AAR), procedure failure (PF) due to endometrial inaccessibility, and biopsy failure (BF) among women undergoing pipelle endometrial biopsy and endocervical curettage (PEB- ECC).

View Article and Find Full Text PDF

A Deep Learning Approach for Automatic Segmentation during Daily MRI-Linac Radiotherapy of Glioblastoma.

Cancers (Basel)

October 2023

Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL 33136, USA.

Glioblastoma changes during chemoradiotherapy are inferred from high-field MRI before and after treatment but are rarely investigated during radiotherapy. The purpose of this study was to develop a deep learning network to automatically segment glioblastoma tumors on daily treatment set-up scans from the first glioblastoma patients treated on MRI-linac. Glioblastoma patients were prospectively imaged daily during chemoradiotherapy on 0.

View Article and Find Full Text PDF

This study assessed the snow/ice surface area changes over the Zemu Glacier in the Eastern Himalayas. Zemu is considered to be the largest glacier in the Eastern Himalayas located in the Sikkim State of India. Change detection in the snow/ice surface areal extent of the Zemu Glacier was delineated from the year 1945 using US Army Map Service-Topographical Sheets and Landsat imageries available from 1987 to 2020.

View Article and Find Full Text PDF