The impact of X-ray scatter correction software on abdomen radiography in terms of image quality and radiation dose.

INTRODUCTION: The conventional anti-scatter grid is widely used in X-ray radiography to reduce scattered X-rays, but it increases patient dose. Scatter-correction software offers a dose-reducing alternative by correcting for scattered X-rays without a physical grid. Grids and software correction are necessary to reduce scatter radiation and improve image quality especially for the large body parts. The scatter correction can be beneficial in situations where the use of grid is challenging. The implementation of grids and advanced software correction techniques is imperative to ensure that radiographic images maintain high levels of clarity, contrast, and resolution, and ultimately facilitating more accurate diagnoses. This study compares image quality and radiation dose for abdomen exams using scatter correction software and physical grids. METHODS: An anthropomorphic phantom (abdomen) underwent imaging with varying fat and lean tissue layers and body mass index (BMI) configurations. Imaging parameters included 70 kVp tube voltage, 110 cm SID, and Automatic Exposure Control (AEC) both lateral and central chambers. AP abdomen X-ray projections were acquired with and without an anti-scatter grid, and scatter correction software was applied. Image quality was assessed using contrast to noise ratio (CNR) and signal to noise ratio (SNR) metrics. The tube current mAs was considered an exposure factor that affected radiation dose and was used to compare the VG software and physical grid. Radiation dose was measured using Dose Area Products (DAP). The effective dose was estimated using Monte Carlo simulation-PCXMC software. Paired t-tests were used to investigate the image quality difference between the Gridless and VG software, Gridless and PG, and VG software and PG approaches. For the DAP and effective dose, paired t-test was used to investigate the difference between VG software and PG. RESULTS: Images acquired with a grid had the highest mean CNR (71.3 ± 32) compared to Gridless (50 ± 33.8) and scatter correction software (59.3 ± 37.9). The mean SNR of the grid images was (82.7.3 ± 38.9), which is 18% higher than the scatter correction software images (70.4 ± 36.7) and 29% higher than in the Gridless images (62.9.3 ± 34). The mean DAP value was reduced by 81% when the scatter correction software was used compared to the grid (mean: 65.4 µGy.m2 and 338.2 µGy.m2, respectively) with a significant difference (p = 0.001). Scatter correction software resulted in a lower effective dose compared to physical grid use, (mean difference± SD = -0.3 ± 0.18 mSv) with a significant difference (P = 0.02). CONCLUSION: Scatter correction software reduced the radiation dose required but images employing a grid yielded higher CNR and SNR. However, the radiation dose reduction might affect the image quality to a level that impacts the diagnostic information available. Thus, further research needs to be conducted to optimise the use of the scatter correction software. IMPLICATION FOR PRACTICE: Objectively, X-ray scatter correction software might be promising in conditions where a grid cannot be applied.

Performance of different dental age estimation methods on Saudi children.

AIM: To evaluate and compare the performance of six dental age estimation methods (Moorrees, Fanning and Hunt, Demirjian, Gleiser and Hunt, Nolla, Chaillet et al., and Nicodemo et al.) on a sample of Saudi children. METHOD: This cross-sectional study was based on the evaluation of a sample of 400 archived digital panoramic radiographs of healthy Saudi children (200 each from boys and girls) aged 6 to 15.99 years. Panoramic radiographs acquired during 2018-2021 were obtained from the information technology department of the dental clinics at King Saud University, Riyadh, Saudi Arabia. Dental age was evaluated using the six dental age estimation methods on the developing permanent dentition in both jaws of the left side. The accuracy of each method was assessed in relation to chronological age, and a comparison between these methods was made. RESULT: For all the tested methods, significant differences were found between chronological and dental age (P<0.001). The mean difference between dental and chronological age was (-2.19 years) for Chaillet et al. method, (0.15 years) for the Demirjian method, (-1.01 years) for the Moorrees, Fanning and Hunt method, (-1.72 years) for Nicodemo et al. method, (-1.29 years) for Nolla method, and (-1.00 years) for Gleiser and Hunt method. CONCLUSION: Among the tested methods, the accuracy in Saudi subjects was the highest for Demirjian's method, followed by the Moorrees, Fanning and Hunt method. The methods proposed by Nicodemo et al., and Chaillet et al., were the least accurate.

Accuracy of dental age estimations based on individual teeth and staging system comparisons.

AIM: To investigate whether a specific tooth or teeth provide the most accurate estimation of chronological age (CA), and determine which of the three staging systems studied represents dental development for an individual tooth. METHOD: Data were collected from 400 digital panoramic radiographs of healthy Saudi children aged 6.00-15.99 years. Each permanent tooth on the left side was evaluated to determine its developmental stage and dental age using the methods by Moorrees, Fanning, and Hunt (MFH) (1963), as adapted by Smith (1991), Gleiser and Hunt (1955), and Nicodemo et al. (1974). The accuracy (bias) of each tooth type and stage was assessed in relation to the CA, the teeth and the methods were compared, and the accuracy of age estimation using all teeth and the most accurate tooth in each method were compared. RESULTS: Regarding staging systems, comparatively, Gleiser and Hunt's method had the lowest bias for the lower first molar (-0.50 ± 1.05 years). Nicodemo et al.'s method had a lower bias for all other mandibular teeth compared to the MFH method. For individual teeth using the MFH method, the most and least accurate teeth for the combined sexes were the lower central incisor (-0.59 ± 0.77 years) and the lower first molar (-1.54 ± 0.93 years), respectively. No significant difference was found between the biases when using the lower central incisor alone and when using all teeth for the combined sexes. For individual teeth using Nicodemo et al.'s method, the most and least accurate teeth for combined sexes were the upper central incisor (-0.03 ± 1.01 years) and the lower first molar (-1.08 ± 1.59 years), respectively. A significant difference was found between the biases using the upper central incisor alone and all teeth for the combined sexes, with the upper central incisor exhibiting the lowest bias (P=0.028). CONCLUSIONS: Comparatively, Nicodemo et al.'s method had the lowest bias for all teeth except for the lower first molar, where Gleiser and Hunt's method had the lowest bias. This, however, should not be confused with precision. MFH's staging system was more representative of dental development for an individual tooth. For combined sexes, the lower central and lateral incisors were the most accurate teeth using the MFH method. The upper central incisor and lower first premolar were the most accurate teeth using Nicodemo et al.'s method. The lower first molar was the least accurate tooth using both methods.

Accuracy of dental age estimation charts: Schour and Massler, Ubelaker and the London Atlas.

Dental age estimation charts are frequently used to assess maturity and estimate age. The aim of this study was to assess the accuracy of estimating age of three dental development charts (Schour and Massler, Ubelaker, and the London Atlas). The test sample was skeletal remains and dental radiographs of known-age individuals (N = 1,506, prenatal to 23.94 years). Dental age was estimated using charts of Schour and Massler, Ubelaker, and The London Atlas. Dental and chronological ages were compared using a paired t-test for the three methods. The absolute mean difference between dental and chronological age was calculated. Results show that all three methods under-estimated age but the London Atlas performed better than Schour and Massler and Ubelaker in all measures. The mean difference for Schour and Massler and Ubelaker was -0.76 and -0.80 years (SD 1.27 year, N = 1,227) respectively and for the London Atlas was -0.10 year (SD 0.97 year, N = 1,429). Further analysis by age category showed similar accuracy for all three methods for individuals younger than 1 year. For ages 1-18, the mean difference between dental and chronological ages was significant (P < 0.05) for Schour and Massler and Ubelaker and not significant (P > 0.05) for the London Atlas for most age categories. These findings show that the London Atlas performs better than Schour and Massler and Ubelaker and represents a substantial improvement in accuracy of dental age estimation from developing teeth.

Brief communication: The London atlas of human tooth development and eruption.

The aim of this study was to develop a comprehensive evidence-based atlas to estimate age using both tooth development and alveolar eruption for human individuals between 28 weeks in utero and 23 years. This was a cross-sectional, retrospective study of archived material with the sample aged 2 years and older having a uniform age and sex distribution. Developing teeth from 72 prenatal and 104 postnatal skeletal remains of known age-at-death were examined from collections held at the Royal College of Surgeons of England and the Natural History Museum, London, UK (M 91, F 72, unknown sex 13). Data were also collected from dental radiographs of living individuals (M 264, F 264). Median stage for tooth development and eruption for all age categories was used to construct the atlas. Tooth development was determined according to Moorrees et al. (J Dent Res 42 (1963a) 490-502; Am J Phys Anthropol 21 (1963b) 205-213) and eruption was assessed relative to the alveolar bone level. Intraexaminer reproducibility calculated using Kappa on 150 teeth was 0.90 for 15 skeletal remains of age <2 years, and 0.81 from 605 teeth (50 radiographs). Age categories were monthly in the last trimester, 2 weeks perinatally, 3-month intervals during the first year, and at every year thereafter. Results show that tooth formation is least variable in infancy and most variable after the age of 16 years for the development of the third molar.