Structural Complexity of the Bone Trabecular in Children Exposed to Different Sunlight Conditions: A Cross-Sectional Study with Panoramic Radiographs

Structural Complexity of the Bone Trabecular in Children Exposed to Different Sunlight Conditions: A Cross-Sectional Study with Panoramic Radiographs | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Structural Complexity of the Bone Trabecular in Children Exposed to Different Sunlight Conditions: A Cross-Sectional Study with Panoramic Radiographs André Ramos Losso, Carla Barros de Oliveira, Andréa Fonseca-Gonçalves, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4086569/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objectives: This study aimed to assess the trabecular bone structural complexity in children with varying sunlight exposure using panoramic radiographs (PR) and investigate potential implications for bone metabolism. Fractal dimension (FD) and pixel intensity (PI) were employed for comparison. Materials and Methods: Panoramic radiographs (n=120) of 6 to 9-year-old children, divided into more (n=60) and less (n=60) sunlight exposure groups, were assessed. ImageJ ® software was used to analyze three regions of interest (ROI) in each radiograph. FD, determined by the box-counting method, and PI values were compared across ROIs and between exposure groups and genders using Kruskal-Wallis and t-tests (p<0.05). Results: Children with less sunlight exposure exhibited higher FD values (3.60 ± 0.29) compared to those with more exposure (3.31 ± 0.29) (p=0.000), particularly in ROI2 and ROI3. No gender-based differences were observed (p=0.607). PI values were similar between exposure groups (p=0.735) and genders (p=0.553), except for a significant difference in ROI2 of less exposed children (62.76 ± 20.48) compared to more exposed ones (78.30 ± 65.20). Conclusion: Reduced sunlight exposure in children was associated with higher FD values, impacting trabecular bone structural complexity. However, total PI values remained unaffected by sunlight exposure. This suggests that dentists, utilizing FD and PI analysis on routinely requested PR, can contribute to the early detection of potential bone variations in children. Clinical Relevance: Understanding FD and PI applications in PR can empower dentists for the early identification of bone variations in pediatric patients during routine clinical assessments. Fractals imaging diagnosis panoramic radiography child bone Figures Figure 1 Figure 2 Introduction Over the years, scientific evidence has shown positive associations between regular exposure to the sun and health benefits [ 1 , 2 ], considering that low exposure to sunlight can be a triggering factor for damage to bone growth in children. As the bones of the human skeleton undergo growth, modeling, and remodeling, and these events occur mainly during childhood and adolescence [ 3 , 4 ], regulating sun exposure at this stage of life can contribute to maintaining vitamin D3 (“sunshine vitamin”) and indirectly acts on the mineralization process, preventing possible bone changes [ 5 ]. Bone quality is related to the microarchitecture of the trabecular bone [ 6 , 7 ] and changes in the bone matrix modify the density and texture of the structures, which can be diagnosed through imaging exams [ 8 – 10 ]. The most used to evaluate bone trabeculation are computed tomography (CT), bone densitometry, and dual-energy X-ray absorptiometry (DXA) [ 11 , 12 ]. However, when compared to routine two-dimensional exams in clinical dental practice, these emit a higher dose of radiation to the patient, being an eminent concern, especially in children and adolescents, where the biological effects of ionizing radiation can be more harmful [ 13 , 14 ]. As panoramic radiography is the most used two-dimensional technique in Dentistry and, in many situations, sufficient to establish the diagnosis of bone changes [ 15 , 16 ], it is the best option for initial assessment of any patient [ 17 ]. Therefore, observing the characteristics of the trabecular bone, through structural complexity through panoramic radiographs, is of great importance [ 7 , 18 ] as it can assist in the diagnosis of various systemic and metabolic conditions in an individual [ 19 ]. Such an assessment can be based on the calculation of the fractal dimension (FD) [ 18 ], which is characterized by a numerical result obtained by a mathematical method called fractal analysis (FA) [ 10 , 20 ]. The fractal method determines similar shapes, regardless of the size scale [ 9 , 21 ], and allows diagnosing potential bone abnormalities and measuring the severity of existing disorders [ 22 ]. Studies have been developed in the health area to evaluate trabecular bone complexity using FD in imaging exams [ 18 , 23 ]. Pixel intensity (PI), in turn, is a measure of “darkness” or “whiteness” and is also used in healthcare to estimate bone mass [ 24 ]. Osteoporosis, for example, is one of the conditions that can be observed by calculating FD and PI values ​​on panoramic radiographs [ 24 ]. Both methods are easy to apply and reproducible and can provide valuable information about the maxillomandibular bones. However, no studies were found that evaluated such conditions in panoramic radiographic images of children, especially when considering greater or lesser exposure to sunlight. Since children's bone metabolism can be influenced by the condition of exposure to sunlight, and the structural complexity of the bone trabeculae and bone mass can be evaluated by FD and PI, respectively, the objective was to compare such aspects in children living in places with different sunlight conditions. Materials and Methods Study Design The study adhered to the guidelines for observational studies outlined in the STROBE (STrengthening the Reporting of OBservational studies in Epidemiology) Statement guide - A checklist of items that should be included in reports of cross-sectional studies [ 25 ]. Sample and Eligibility Criteria The study sample comprised digital panoramic radiographs of children aged between 6 and 9 years, sourced from databases in two cities with distinct sunlight exposure conditions. One city is in the coastal region of Rio de Janeiro – RJ (high sunlight exposure), while the other is in the Zona da Mata Mineira – MG region (low sunlight exposure). The aim was to compare, through FD and PI values, whether different sunlight exposure conditions influence the structural complexity of trabecular bone. All images were acquired using the Orthophos 3D device (Dentsply, Sirona, Erlangen, Germany) under identical acquisition parameters (64 kVp and 10 mA). Panoramic radiographs with optimal visibility and minimal degrees of magnification and distortion were included. Those with motion artifacts, positioning and technique errors, intraosseous retained teeth in ectopic positions, bone fractures, and osteolytic lesions in the mandible were excluded. Examiner training and calibration A radiologist, with experience in radiographic image analysis (M.A.V.), demonstrated to two examiners in training (A.R.L and C.B.O), through a video, the parameters necessary to obtain FD in regions of interest (ROI) selected from the public domain program ImageJ® [ 26 ]. After watching the video, all doubts were resolved, in person. Then, 20 panoramic radiographs of children, with the age of interest in the study, were used for calibration by the examiners, who independently determined the FD and PI of the ROIs selected in the images. Inter-examiner agreement ranged from 0.84 to 0.98 (ICC = 0.984), these values ​​being considered highly reproducible [ 27 ]. After this stage, the images were excluded and were not part of the main study. Pilot study and sample calculation Due to the lack of previous studies to estimate the sample calculation parameters, a pilot study was carried out with 60 digital panoramic radiographs of children living in places more (G1; n = 30) and less (G2; n = 30) exposed to sunlight. comparing them regarding FD and PI values ​​in three regions of interest (ROI1, ROI2, and ROI3). ROI1 was located halfway between the neck of the mandibular condyle and the angle of the mandible, always in the posterior region close to the outermost cortex of the ramus; ROI2 in the most central region of the mandible angle; and ROI3 close to the base of the mandible, always between the mesial and distal roots of the first permanent molar (Fig. 1 ). Thus, using the Bioestat® program, version 5.3, the sample size was calculated, considering as parameters: total values ​​(ROI1 + ROI2 + ROI3) of DF (G1: 3.36 ± 0.31; G2: 3.55 ± 0.29) and IP (G1: 244.9 ± 33.1; G2: 267 ± 54.3), a study power estimated at 80%, standard error of 5%, and a two-sided test. Therefore, it was determined that 39 panoramic radiographs would be necessary to compare IP values ​​and 60 for FD values, in each group (more and less exposed to sunlight). Therefore, the largest number calculated (n = 120; 60 for each group) was adopted to compose the sample for the present study. Image analysis After training and calibration, a single examiner (A.R.L) analyzed, blindly (hiding the region of origin of the radiographs) and randomly, all the images included (n = 120). A 21-inch high-resolution liquid crystal display (LCD) under soft lighting was used. The examiner analyzed, using the ImageJ® software, a maximum of five images per day to prevent visual fatigue from compromising the evaluations [ 28 ]. The three ROIs, with dimensions of 30x30 pixels, were selected in cortical bone, always on the right side of the panoramic radiograph, chosen randomly. The selection criteria for quantity, size, and specific location of ROIs were determined after training and calibration, and the analyses followed methodological standards previously described [ 18 , 23 , 29 ]. Fractal dimension analysis The structural complexity of the bone trabeculae was obtained by calculating the FD in the 3 selected ROIs, for each group of radiographs (G1; n = 60 and G2; n = 60). A Gaussian filter was applied to the original image (sigma = 35 pixels, kernel size = 33x33), enabling the correction of large variations in density (low-pass filtering) and removing discrepancies between pixels of similar intensity. Then, the resulting image, highly blurred, was subtracted from another duplicate of the original ROI and generated a third image, in which gray values ​​(128) were added to each pixel, thus preventing some structures from standing out concerning others. Next, the third image was binarized and subsequently segmented into components that visually approximate the trabeculae. Then, noise reduction was performed, and the image was transformed into a line of a single pixel, highlighting the texture and patterns that were subjected to FD analysis [ 18 , 23 ]. Superimposing the trabecular image on the original image of the bone demonstrates that the skeletal structure studied corresponds to the trabeculae in the original image. The FD was calculated using the boxcounting method, respecting the widths of square boxes previously established in the literature, with dimensions of 2, 3, 4, 6, 8, 12, 16, 32, and 64 pixels [ 23 , 29 ]. (Fig. 1 ). Pixel intensity analysis The PI values ​​were also calculated for each of the established ROIs, using the program's own “Histogram” tool. When calculating the PI, average, minimum, and maximum values ​​were obtained, in addition to the specific histogram for each region, highlighting the threshold (interval between grayscale values) selected (Fig. 2 ). Statistical analysis The results were analyzed using the Statistical Package for the Social Sciences (SPSS for Windows, version 21.0; SPSS Inc., Chicago, IL, USA). Descriptive and inferential analyses were performed. The Shapiro-Wilk test was used to verify the normality distribution of the data, considering the total PI and FD (sum of ROI1, ROI2, and ROI3) and individual means. To verify the difference in these total and individual values ​​of images from children less and more exposed to the sun, as well as between genders, the Kruskal-Wallis and Student's t-tests were used. A significance level of 5% was considered (p < 0.05). Results Sample description The images included in the study belonged to children with an average age of 7.39 ± 1.11 years. Of the sample (n = 120), 62 x-rays were from girls (51.7%), while 58 were from boys (48.3%). Furthermore, the following total DF and IP values ​​were observed: 3.45 ± 0.32 and 258.30 ± 58.38, respectively. Comparison of fractal dimension between groups, considering sun exposure and sex When analyzing the sum of the average FD values ​​of the three ROIs, there was a significant difference between the children most exposed (G1 = 3.31 ± 0.29) and those least exposed to the sun (G2 = 3.60 ± 0.29) (p = 0.000). When analyzing each ROI separately, a significant difference was found concerning the sum of the mean values ​​of ROI2 (p = 0.000) and ROI3 (p = 0.000) regarding sun exposure, as shown in Table 1 . Table 1 Total fractal dimension (DF) values ​​of regions of interest (ROI), presented in panoramic radiographs of children most exposed (G1) and least exposed (G2) to sunlight. ROI G1 (n = 60) Mean (SD) G2 (n = 60) Mean (SD) p value Fractal Dimension (FD) ROI 1 1,16 (0,17) 1,19 (0,19) 0,136 ROI 2 1,19 (0,19) 1,28 (0,14) 0,000* ROI 3 0,96 (0,18) 1,13 (0,21) 0,000* Total Value 3,31 (0,29) 3,60 (0,29) 0,000* Note: * Values ​​with statistical significance; SD – standard deviation. Regarding gender, considering the total sample, no significant difference was observed between FD values ​​between girls (3.48 ± 0.28) and boys (3.43 ± 0.36) (p = 0.607), and adjusting for sun exposure, there was also no difference between girls (n = 32; 3.33 ± 0.25) and more exposed boys (n = 28; 3.28 ± 0.34) (p = 0.491); as well as girls (n = 30; 3.63 ± 0.24) and less exposed boys (n = 30; 3.77 ± 0.33) (p = 0.408). Comparison of pixel intensity between groups, considering sun exposure and sex There was no difference between the total PI values ​​between children (G1 = 261.26 ± 69.54) and less exposure to sunlight (255.33 ± 44.95) (p = 0.735). However, when analyzing each ROI separately, there was a significant difference in ROI2 between those most exposed (G1 = 78.30 ± 65.20) and those least exposed (G2 = 62.76 ± 20.48) (p = 0.013), as seen in Table 2 . Table 2 Total pixel intensity (IP) values ​​of regions of interest (ROI), analyzed in panoramic radiographs of children most exposed (G1) and least exposed (G2) to sunlight. ROI G1 (n = 60) Mean (SD) G2 (n = 60) Mean (SD) p value Pixel Intensity (PI) ROI 1 90,81 (18,56) 97,00 (26,69) 0,143 ROI 2 78,30 (65,20) 62,76 (20,47) 0,013* ROI 3 92,15 (10,33) 95,57 (18,64) 0,321 Total Value 261,26 (69,54) 255,33 (44,95) 0,553 Note: * Values ​​with statistical significance; SD – standard deviation. As with FD, the total PI values ​​(p = 0.553) of the total sample were not influenced by gender, with no difference being observed between girls (257.88 ± 70.12) and boys (258.74 ± 43. 05). When sun exposure was considered, there was also no difference between girls (n = 32; 269.82 ± 88.83) and more exposed boys (n = 28; 251.48 ± 36.33) (p = 0.291) or girls (n = 30; 245.15 ± 39.76) and less exposed boys (n = 30; 265.51 ± 48.12) (p = 0.079). Discussion This study compared the structural complexity of the bone trabeculae in children residing in areas with different sunlight exposure conditions, using DF (fractal dimension) and IP (irregularity parameter) values derived from digital panoramic radiographs. The calculation of DF and IP in imaging exams has been previously employed in dentistry to assess bone trabeculae, primarily in adults, cadavers, and animals [ 23 , 24 , 30 , 31 ]. To the best of our knowledge, only one study [ 18 ] has utilized these methods to evaluate bone architecture in children. Given that sunlight exposure has the benefit of promoting the production of vitamin D3 (the "sunshine vitamin"), a crucial micronutrient for bone metabolism, especially in growing children, assessing trabecular bone alterations through DF and IP in children with varying levels of sun exposure becomes relevant and justified. In the reviewed literature, no study has examined variations in trabecular bone complexity based on sunlight conditions using panoramic radiographs. Existing studies have predominantly employed more complex imaging methods such as computed tomography (CT), densitometry, and dual-energy X-ray absorptiometry (DXA), focusing on bones like the radius and vertebrae [ 12 , 32 ]. However, digital panoramic radiographs are cost-effective, easily executed by professionals, and well-accepted by children [ 33 , 34 ]. Importantly, they pose lower risks, as radiation exposure is significantly reduced compared to the methods, making them ideal for use in children [ 16 ]. A recent systematic review indicated that childhood exposure to CT scans may be associated with an increased risk of cancer, while no significant association was observed with two-dimensional radiographic exams [ 14 ]. This current study stands as the first to evaluate trabecular bone complexity, utilizing FD and PI calculations in digital panoramic radiographs of children exposed to different sunlight conditions. A significant difference in trabecular bone density has been reported between female and male adults, being greater in men [ 35 ]. Therefore, in the present study, the influence of sex on FD and PI results was investigated. However, no differences were observed between boys and girls, as in the study by Arrepia et al., (2023). This result can be explained by the metabolic similarity of the bone growth phase between boys and girls in the age range studied (6 to 9 years), as more significant changes occur after this age [ 36 ]. This was also the reason for choosing the age group researched; since possible confounding factors in the detection of bone trabecular variations, inherent to the different metabolism between the sexes with advancing age, especially in the growth spurt phase, could influence the results. FD is widely used in the analysis of bone trabecular structure and several studies have demonstrated its ability to verify [ 37 , 38 ]. The boxcounting method is the most used and recommended for calculating FD as it is easily reproducible [ 10 ]. This method requires a pre-established tool [ 23 , 29 ] and is present in the ImageJ® program. As it is free and easily accessible software, it was chosen to be used in this work. In addition to FD, PI can also be calculated in ImageJ®, using the Histogram tool, and adds important information about the density of the analyzed region. The sum of FD values, considering the selected ROIs, showed a significant difference between children more and less exposed to the sun, rejecting the null hypothesis of the study. In children less exposed to sunlight, the total FD value was higher than in more exposed children. This result seems controversial when analyzing data from other studies that showed that an increase in the FD value may be associated with greater structural complexity [ 39 , 40 ]. However, other studies have shown that ROIs marked in areas of pathological bone formation, such as osteosarcoma, areas of implant osseointegration, and post-orthognathic recovery, present higher FD values ​​compared to a region of normal bone [ 41 – 43 ]. Thus, higher FD values ​​are not always related to increased bone density, nor can they be correlated with increased PI [ 18 ]. It is suggested, with this result, that low exposure to sunlight may be a predisposing factor to changes in the complexity of bone trabeculation, as it causes changes in bone metabolism, mainly due to the lack of vitamin D3. Sunlight is the greatest source of vitamin D, which is responsible for regulating calcium absorption and bone mineralization [ 44 , 45 ]. Maintaining controlled and regular exposure to sunlight is of great importance, especially during childhood and adolescence, as it is a critical period of bone development, thus avoiding changes such as rickets and fractures [ 46 , 47 ]. However, measuring an individual's real exposure to sunlight involves many variables, such as investigating bone mineral density (BMD), a method considered invasive and high risk due to the ionizing radiation of the tests required for this purpose. Therefore, choosing only the place where the children live may be a limitation of the study, but it is a method that does not pose any risk to the participants and provides examinations from an image bank of panoramic X-rays that are constantly requested in dental practice. Issues such as latitude, seasons, and even clothing can influence exposure to sunlight [ 48 ]. Children living in less sun-exposed areas may have different clothing habits, for instance, due to colder weather. Consequently, the use of coats and clothing covering a large part of the body may inhibit optimal absorption of sunlight through the skin, providing a possible explanation for the study's significant results. However, despite being an invasive examination and not always recommended in children without a diagnosis of bone diseases, it would be ideal to measure the serum levels of vitamin D in the researched children through blood tests, representing a limitation of the present study. It is suggested that further investigations into variations in children's trabecular bone, with measurement of serum vitamin D levels, be conducted. In the regions of the mandibular angle (ROI2) and body (ROI3), FD values were significantly higher in children less exposed to the sun, highlighting the impact of exposure on trabecular complexity. The mandibular angle region is explored in various studies due to its susceptibility to changes from childhood onwards [ 49 , 50 ]. The position of the gonion, a point located in this region, changes life phases, leading to dimensional movements of the jaw with individual growth. Several studies have shown that gonial angle values are higher at ages 5–10 and decrease over time until the age range of 15–20 [ 50 , 51 ]. The gonial angle is commonly assessed to determine jaw rotation and is a significant indicator for diagnosing patients' growth patterns [ 52 , 53 ]. Considering that low sun exposure can interfere with children's growth, it is suggested that the structural complexity of trabeculae in regions with higher metabolic activity may have been more influenced. There are studies with growing animals [ 54 , 55 ], in which the authors assessed the insertion of the masseter in the gonial region and its influence on the rotational pattern of the mandible. The results demonstrated the influence of muscular action on bone growth, meaning that depending on the location of the muscular insertion, mandibular growth can be altered either negatively or positively. However, it is not clear whether these changes affect the rotational growth pattern of the mandible [ 55 ], and it cannot be stated whether there is an association between muscular insertion and alterations in bone architecture in the mandibular angle regions (ROI2); thus, further studies in this field are necessary. Regarding the difference found in the mandibular body (ROI3) concerning the FD results, it is believed that the stages of dental development in the permanent first molar region may have influenced the findings, as this area is constantly undergoing remodeling in the age group studied. This action occurs in conjunction with muscular maturation and craniofacial growth, meaning that biological maturation has not yet been completed at this stage [ 56 ]. Therefore, it is suggested that in children with less sun exposure, higher FD values were found and may be associated with lesser development in this region. However, new studies that clinically examine children in the long term, including eruption chronology and Nolla's dental development stages, are recommended. Although the total PI value did not differ between the images of children more and less exposed to the sun, the mandibular angle region was different, even though it was always measured in cortical bone. Radiographs of less exposed children showed a lower PI value than those of children more exposed to the sun. The average PI value in ROI2 was the lowest found to the others. It is suggested that the constant modeling and bone remodeling that exists in the gonion region [ 52 , 53 ] may result in less dense images in these areas. Thus, it can be suggested that children less exposed to the sun, with lower PI values, have lower bone density in this region when compared to more exposed children, despite BMD not being assessed in the present research. Technical interferences related to the choice of imaging exam, such as the possibility of overlapping structures, and formation of ghost images, in addition to image magnification and distortion when using panoramic radiographs, could be listed as limitations. However, panoramic radiography is the most viable choice for this study, as it is a suitable method for children, due to its lower cost and lower risk, due to the low dose of radiation emitted. Possible inaccuracies in obtaining the FD could also be considered limitations since a small deviation when creating the ROI would significantly influence the morphology of tissue structures. Furthermore, the FD calculation may vary depending on the methods applied, such as boxcounting, pixel dilation, and modified pixel dilation. However, to meet these conditions, in the present study, pre-determined and anatomically demarcated ROIs were chosen, as well as the simple, public domain program, ImageJ®, in which the boxcounting method is already included. Bone fragility and fractures due to pathological conditions in children, such as rickets, are of great concern in the medical and dental fields. Therefore, the development of methods capable of assisting in the early diagnosis of these conditions becomes very important. Therefore, we can state that considering this pioneering study, a promising line of research using panoramic radiographs to observe possible variations in the complexity of bone trabeculation in children living in different sunlight conditions should be strengthened. It was seen that the use of FD and PI are good indicators for detecting bone variations in this population; Furthermore, they are easily accessible and low-cost methods, investigated in two-dimensional examinations, with low radiation doses and frequently requested by dentists in daily clinical practice. Conclusion Children less exposed to sunlight had higher FD values ​​when compared to those more exposed, showing differences in the structural complexity of the bone trabeculae, but without differences between the sexes and between the total PI values. Declarations Credit Author Statement André Ramos Losso: Conceptualization, Methodology, Writing-Original draft preparation ; Carla Barros de Oliveira: Investigation, Data curation ; Andrea Fonseca-Gonçalves: Writing - Review & Editing ; Maria Augusta Visconti: Project administration . Ethics Approval and Consent to Participate This is a cross-sectional study that received prior approval from the local Ethics Committee under protocol #6.180.196. The informed consent was “Not Applicable”. Funding: Not Applicable Conflict of Interests: The authors declare that there is no conflict of interest with the study presented. References - Albert MR, Ostheimer KG (2003) The evolution of current medical and popular attitudes toward ultraviolet light exposure: Part 2, Journal of the American Academy of Dermatology. 48(6):909–918. https://doi.org/10.1067/mjd.2003.272 - H, Van der Rhee E, de Vries C, Coomans P, van de Velde, Coebergh JW (2016) Sunlight: for better or for worse? a review of positive and negative effects of sun exposure. Cancer Res Front 2:156–183. 10.17980/2016.156 - Elsori DH, Hammoud MS (2018) Vitamin D deficiency in mothers, neonates and children. J Steroid Biochem Mol Biol 175:195–199. 10.1016/j.jsbmb.2017.01.023 - Taylor SN (2020) Vitamin D in Toddlers, Preschool Children, and Adolescents. Ann Nutr Metab 76(Suppl 2):30–41. 10.1159/000505635 - Holick MF (2006) Resurrection of vitamin D deficiency and rickets. J Clin Invest 116(8):2062–2072. 10.1172/JCI29449 - de Souza Santos D, Dos Santos LC, de Albuquerque Tavares Carvalho A et al (2016) Multifractal spectrum and lacunarity as measures of complexity of osseointegration. Clin Oral Investig 20(6):1271–1278. 10.1007/s00784-015-1606-1 - Vadiati Saberi B, Khosravifard N, Nooshmand K, Dalili Kajan Z, Ghaffari ME (2021) Fractal analysis of the trabecular bone pattern in the presence/absence of metal artifact-producing objects: Comparison of cone-beam computed tomography with panoramic and periapical radiography. Dentomaxillofac Radiol 50(6):20200559. 10.1259/dmfr.20200559 - Shore RM, Chesney RW, Rickets (2013) Part I. Pediatr Radiol 43(2):140–151. 10.1007/s00247-012-2532-x - Arsan B, Köse TE, Çene E, Özcan İ (2016) Assessment of the Trabecular Structure of Mandibular Condyles in Patients with Temporomandibular Disorders Using Fractal Analysis, Oral Surgery, Oral Medicine. Oral Pathol Oral Radiol. 10.1016/j.oooo.2016.11.005 - Kato CN, Barra SG, Tavares NP et al (2020) Use of fractal analysis in dental images: a systematic review. Dentomaxillofac Radiol 49(2):20180457. 10.1259/dmfr.20180457 - Gordon CM, Bachrach LK, Carpenter TO et al (2008) Dual energy X-ray absorptiometry interpretation and reporting in children and adolescents: the 2007 ISCD Pediatric Official Positions. J Clin Densitom 11(1):43–58. 10.1016/j.jocd.2007.12.005 - Cheung TF, Cheuk KY, Yu FW et al (2016) Prevalence of vitamin D insufficiency among adolescents and its correlation with bone parameters using high-resolution peripheral quantitative computed tomography. Osteoporos Int 27(8):2477–2488. 10.1007/s00198-016-3552-4 - Tomà P, Bartoloni A, Salerno S et al (2019) Protecting sensitive patient groups from imaging using ionizing radiation: effects during pregnancy, in fetal life and childhood. Radiol Med 124(8):736–744. 10.1007/s11547-019-01034-8 - Abalo KD, Rage E, Leuraud K et al (2020) Early life ionizing radiation exposure and cancer risks: systematic review and meta-analysis [published correction appears in Pediatr Radiol. ;:]. Pediatr Radiol. 2021;51(1):45–56. 10.1007/s00247-020-04803-0 - The 2007 Recommendations of the International Commission on Radiological Protection (2007) Ann ICRP 37:1–332. https://doi.org/10.1016/j.icrp.2007.10.003 . ICRP publication 103 - Sams CM, Dietsche EW, Swenson DW, DuPont GJ, Ayyala RS (2021) Pediatric Panoramic Radiography: Techniques, Artifacts, and Interpretation. Radiographics 41(2):595–608. 10.1148/rg.2021200112 - Mupparapu M, Akintoye SO (2023) Application of Panoramic Radiography in the Detection of Osteopenia and Osteoporosis-Current State of the Art. Curr Osteoporos Rep 21(4):354–359. 10.1007/s11914-023-00807-5 - Arrepia BF, Rocha TG, Medeiros AS, Ferreira MD, Fonseca-Gonçalves A, Visconti MA (2023) The mandibular bone structure in children by fractal dimension and its correlation with pixel intensity values: a pilot study [published online ahead of print, 2023 Jun 27]. Oral Radiol. 10.1007/s11282-023-00693-8 - Lee D-H, Ku Y, Rhyu I-C, Hong J-U, Lee C-W, Heo M-S et al (2010) A clinical study of alveolar bone quality using the fractal dimension and the implant stability quotient. J Periodontal Implant Sci 40:19–24. https://doi.org/10.5051/jpis.2010.40.1.19 - Sener E, Cinarcik S, Baksi BG (2015) Use of fractal analysis for the discrimination of trabecular changes between individuals with healthy gingiva or moderate periodontitis. J Periodontol 86:1364–1369. https://doi.org/10.1902/jop.2015.150004 - Sánchez I, Uzcátegui G (2011) Fractals in dentistry. J Dent 39:273–292. https://doi.org/10.1016/j.jdent.2011.01.010 - Lopes R, Betrouni N (2009) Fractal and multifractal analysis: a review. Med Image Anal 13(4):634–649. 10.1016/j.media.2009.05.003 - Apolinário AC, Sindeaux R, de Souza Figueiredo PT, Guimarães AT, Acevedo AC, Castro LC, de Paula AP, de Paula LM, de Melo NS, Leite AF (2016) Dental panoramic indices and fractal dimension measurements in osteogenesis imperfecta children under pamidronate treatment. Dentomaxillofac Radiol 45:20150400. https://doi.org/10.1259/dmfr.20150400 - Tosoni GM, Lurie AG, Cowan AE, Burleson JA (2006) Pixel intensity and fractal analyses: detecting osteoporosis in perimenopausal and postmenopausal women by using digital panoramic images. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 102(2):235–241. 10.1016/j.tripleo.2005.08.020 - Cuschieri S (2019) The STROBE guidelines. Saudi J Anaesth 13(Suppl 1):S31–S34. 10.4103/sja.SJA_543_18 - Schneider CA, Rasband WS, Eliceiri KW (2012) NIH Image to ImageJ: 25 years of image analysis. Nat Methods 9(7):671–675. 10.1038/nmeth.2089 - Landis JR, Koch GG (1977) The Measurement of Observer Agreement for Categorical Data. Biometrics 33:159–174. https://doi.org/10.2307/2529310 - Rosado LPL, Barbosa IS, Junqueira RB, Martins A, Verner FS (2021) Morphometric analysis of the mandibular fossa in dentate and edentulous patients: A cone beam computed tomography study. J Prosthet Dent 125:758. https://doi.org/10.1016/j.prosdent.2021.01.014 . .e1-758.e7 - White SC, Rudolph DJ (1999) Alterations of the trabecular pattern of the jaws in patients with osteoporosis. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 88(99):628–635. https://doi.org/10.1016/S1079- - Pornprasertsuk S, Ludlow JB, Webber RL, Tyndall DA, Yamauchi M (2001) Analysis of fractal dimensions of rat bones from film and digital images. Dentomaxillofac Radiol 30(3):179–183. 10.1038/sj/dmfr/4600597 - Soğur E, Baksı BG, Gröndahl HG, Sen BH (2013) Pixel intensity and fractal dimension of periapical lesions visually indiscernible in radiographs. J Endod 39(1):16–19. 10.1016/j.joen.2012.10.016 - Alghadir AH, Gabr SA, Rizk AA (2018) Physical Fitness, Adiposity, and Diets as Surrogate Measures of Bone Health in Schoolchildren: A Biochemical and Cross-Sectional Survey Analysis. J Clin Densitom 21(3):406–419. 10.1016/j.jocd.2017.12.006 - Cheung AM, Adachi JD, Hanley DA, Kendler DL, Davison KS, Josse R et al (2013) High-resolution -peripheral quantitative computed tomography for the assessment of bone strength and structure: a review by the Canadian bone strength working group. Curr Osteoporos Rep 11:136–146. https://doi.org/10.1007/s11914-013-0140-9 - Choi YJ (2016) Dual-energy x-ray absorptiometry: beyond Bone mineral density determination. Endocrinol Metab 31:25–30. https://doi.org/10.3803/EnM.2016.31.1.25 Di Stefano DA, Arosio P, Pagnutti S, Vinci R, Gherlone EF (2019) Distribution of Trabecular Bone Density in the Maxilla and Mandible. Implant Dent 28:340–348. https://doi.org/10.1097/ID.0000000000000893 - Fan Y, Penington A, Kilpatrick N, Hardiman R, Schneider P, Clement J et al (2019) Quantifcation of mandibular sexual dimorphism during adolescence. J Anat 234:709–717. https://doi.org/10.1111/joa.12949 - Ergün S, Saraçoglu A, Güneri P, Ozpinar B (2009) Application of fractal analysis in hyperparathyroidism. Dentomaxillofac Radiol 38(5):281–288. 10.1259/dmfr/24986192 - Demirbaş AK, Ergün S, Güneri P, Aktener BO, Boyacioğlu H (2008) Mandibular bone changes in sickle cell anemia: fractal analysis. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 106(1):e41–e48. 10.1016/j.tripleo.2008.03.007 - Roschger P, Paschalis EP, Fratzl P, Klaushofer K (2008) Bone mineralization density distribution in health and disease. Bone 42:456–466. https://doi.org/10.1016/j.bone.2007.10.021 - Hichijo N, Tanaka E, Kawai N, van Ruijven LJ, Langenbach GEJ (2015) Efects of decreased occlusal loading during growth on the Mandibular bone characteristics. PLoS ONE 10:e0129290. https://doi.org/10.1371/journal.pone.0129290 - Jung JH, Huh KH, Yong TH et al (2022) Differentiation of osteosarcoma from osteomyelitis using microarchitectural analysis on panoramic radiographs. Sci Rep. ;12(1):12339. Published 2022 Jul 19. 10.1038/s41598-022-16504-9 - Kış HC, Güleryüz Gürbulak A (2020) Evaluation of the peri-implant bone trabecular microstructure changes in short implants with fractal analysis. Int J Implant Dent. https://doi.org/10.1186/s40729-020-00209-7 - Heo MS et al (2002) Fractal analysis of mandibular bony healing afer orthognathic surgery. Oral Surg. Oral Med. Oral Pathol Oral Rad Endod 94:763–767. https://doi.org/10.1067/moe.2002.128972 - Cashman KD, Hill TR, Cotter AA et al (2008) Low vitamin D status adversely affects bone health parameters in adolescents. Am J Clin Nutr 87(4):1039–1044. 10.1093/ajcn/87.4.1039 - Webb AR, Kift R, Durkin MT et al (2010) The role of sunlight exposure in determining the vitamin D status of the U.K. white adult population. Br J Dermatol 163(5):1050–1055. 10.1111/j.1365-2133.2010.09975.x - Lehtonen-Veromaa MK, Möttönen TT, Nuotio IO, Irjala KM, Leino AE, Viikari JS (2002) Vitamin D and attainment of peak bone mass among peripubertal Finnish girls: a 3-y prospective study. Am J Clin Nutr 76(6):1446–1453. 10.1093/ajcn/76.6.1446 - Farrar MD, Mughal MZ, Adams JE et al (2016) Sun Exposure Behavior, Seasonal Vitamin D Deficiency, and Relationship to Bone Health in Adolescents. J Clin Endocrinol Metab 101(8):3105–3113. 10.1210/jc.2016-1559 - Webb AR, Engelsen O (2006) Calculated ultraviolet exposure levels for a healthy vitamin D status. Photochem Photobiol 82(6):1697–1703. 10.1562/2005-09-01-RA-670 - Tarazona B, Paredes V, Llamas JM, Cibrian R, Gandía JL (2010) Influence of first and second premolar extraction or non-extraction treatments on mandibular third molar angulation and position. A comparative study. Med Oral Patol Oral Cir Bucal. ;15(5):e760-e766. Published 2010 Sep 1. 10.4317/medoral.15.e760 - Upadhyay RB, Upadhyay J, Agrawal P, Rao NN (2012) Analysis of gonial angle in relation to age, gender, and dentition status by radiological and anthropometric methods. J Forensic Dent Sci 4(1):29–33. 10.4103/0975-1475.99160 Larrazabal-Moron C, Sanchis-Gimeno JA (2018) Gonial angle growth 51- patterns according to age and gender. Ann Anat 215:93–96. 10.1016/j.aanat.2017.09.004 - Okşayan R, Aktan AM, Sökücü O, Haştar E, Ciftci ME (2012) Does the panoramic radiography have the power to identify the gonial angle in orthodontics? ScientificWorldJournal 2012:219708. 10.1100/2012/219708 - Xiao D, Gao H, Ren Y (2011) Craniofacial morphological characteristics of Chinese adults with normal occlusion and different skeletal divergence. Eur J Orthod 33(2):198–204. 10.1093/ejo/cjq064 - Navarro M, Delgado E, Monje F (1995) Changes in mandibular rotation after muscular resection. Experimental study in rats. Am J Orthod Dentofac Orthop 108(4):367–379. 10.1016/s0889-5406(95)70034-x - Bayram B, Uckan S, Cetinsahin A, Arman Ozcirpici A, Ozdemir H, Yazici C (2010) Repositioning of the masseter muscle and its effect on skeletal growth. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 109(5):e1–e5. 10.1016/j.tripleo.2009.12.041 - Dean JA (2021) McDonald and Avery’s Dentistry for the Child and Adolescent, 11th edn. Elsevier, Unites States Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4086569","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":281628778,"identity":"b266627a-81ce-443b-bf7e-7564137f3eb9","order_by":0,"name":"André Ramos Losso","email":"","orcid":"","institution":"Federal University of Rio de Janeiro","correspondingAuthor":false,"prefix":"","firstName":"André","middleName":"Ramos","lastName":"Losso","suffix":""},{"id":281628779,"identity":"9864ebfa-14ff-4104-bad6-9a57247a153e","order_by":1,"name":"Carla Barros de Oliveira","email":"","orcid":"","institution":"Federal University of Rio de Janeiro","correspondingAuthor":false,"prefix":"","firstName":"Carla","middleName":"Barros","lastName":"de Oliveira","suffix":""},{"id":281628780,"identity":"3b284314-b232-4945-b2e1-d85d6aec2591","order_by":2,"name":"Andréa Fonseca-Gonçalves","email":"","orcid":"","institution":"Federal University of Rio de Janeiro","correspondingAuthor":false,"prefix":"","firstName":"Andréa","middleName":"","lastName":"Fonseca-Gonçalves","suffix":""},{"id":281628781,"identity":"9932af7b-0ebb-4619-8b3e-5bfbeea68073","order_by":3,"name":"Maria Augusta Visconti","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEElEQVRIiWNgGAWjYNACAwh14AMDM1TEBsiSwKWcGaaFmeHgDBCPDcRJI6QFymDmQdLCgEuLfET+wc88BXXy/NL9Bw/bVFjLmcs3H2DmSbjHziDd+wCbFsMbyczSPAaHDWfOOcxwOOdMurFlG1sCUEsxM4PMcQOsWmYkM0jOMDiQYHAjmeFwbtvhxA3HeAyYeX8kAP2ShtVhQC3MP2cY1EG0WMK08CTg1iIvkcwm8cGAGaKFkRgtBjyPzSw+gPwyI9ngYA/QLwbH0hIOzgFqYZM5ht2W9sTHNxL+AENMIvHxhx/AEDM4fPjggzcJCcn80m3YbTmATRQkmMyGVQPQlgYcEgx2uCRGwSgYBaNgxAEAnM1Ykc0KZRUAAAAASUVORK5CYII=","orcid":"","institution":"Federal University of Rio de Janeiro","correspondingAuthor":true,"prefix":"","firstName":"Maria","middleName":"Augusta","lastName":"Visconti","suffix":""}],"badges":[],"createdAt":"2024-03-12 17:05:49","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4086569/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4086569/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53254527,"identity":"f4422a1d-3e63-4463-bb54-139071f1da92","added_by":"auto","created_at":"2024-03-22 13:23:34","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":420187,"visible":true,"origin":"","legend":"\u003cp\u003eDigital analysis of the structural complexity of bone trabeculae, through the processing of regions of interest (ROI), located in the mandible, using the boxcounting method, to calculate the fractal dimension (DF). \u003cstrong\u003e1)\u003c/strong\u003e ROI1 selection area \u003cstrong\u003e2)\u003c/strong\u003eROI2 selection area \u003cstrong\u003e3)\u003c/strong\u003e ROI3 selection area. \u003cstrong\u003eA)\u003c/strong\u003e Selected original ROI1 \u003cstrong\u003eB)\u003c/strong\u003e Result after applying a 35 Gaussian filter to the duplicate of ROI1, generating a blurred image \u003cstrong\u003eC)\u003c/strong\u003e Result of subtracting the original ROI1 from the duplicate \u003cstrong\u003eD)\u003c/strong\u003e Addition of gray values ​​(128) in the subtracted image \u003cstrong\u003eE)\u003c/strong\u003e Image binarization \u003cstrong\u003eF)\u003c/strong\u003e Skeletonized trabecular pattern \u003cstrong\u003eG)\u003c/strong\u003e Overlay of Image F and A to visually demonstrate that the skeletonized image corresponds to the original \u003cstrong\u003eH)\u003c/strong\u003e Result of the DF calculation by boxcounting from the skeletonized image.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4086569/v1/43c2b02facac908d7d20a135.jpeg"},{"id":53254526,"identity":"548ecb05-2128-423a-970c-59bbc31500b1","added_by":"auto","created_at":"2024-03-22 13:23:34","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":383977,"visible":true,"origin":"","legend":"\u003cp\u003eDigital analysis of pixel intensity (IP), through the processing of regions of interest (ROI), located in the mandible, using the Histogram tool.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4086569/v1/2a665ed9b9e1e2edcfbb59bc.jpeg"},{"id":54533318,"identity":"a729b097-b817-4203-8a03-8ae33be9bc7a","added_by":"auto","created_at":"2024-04-12 01:36:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":480880,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4086569/v1/fbd4c968-1ef1-43e8-81a8-4ab3bdab04f9.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Structural Complexity of the Bone Trabecular in Children Exposed to Different Sunlight Conditions: A Cross-Sectional Study with Panoramic Radiographs","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOver the years, scientific evidence has shown positive associations between regular exposure to the sun and health benefits [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], considering that low exposure to sunlight can be a triggering factor for damage to bone growth in children. As the bones of the human skeleton undergo growth, modeling, and remodeling, and these events occur mainly during childhood and adolescence [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], regulating sun exposure at this stage of life can contribute to maintaining vitamin D3 (\u0026ldquo;sunshine vitamin\u0026rdquo;) and indirectly acts on the mineralization process, preventing possible bone changes [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBone quality is related to the microarchitecture of the trabecular bone [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] and changes in the bone matrix modify the density and texture of the structures, which can be diagnosed through imaging exams [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The most used to evaluate bone trabeculation are computed tomography (CT), bone densitometry, and dual-energy X-ray absorptiometry (DXA) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. However, when compared to routine two-dimensional exams in clinical dental practice, these emit a higher dose of radiation to the patient, being an eminent concern, especially in children and adolescents, where the biological effects of ionizing radiation can be more harmful [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAs panoramic radiography is the most used two-dimensional technique in Dentistry and, in many situations, sufficient to establish the diagnosis of bone changes [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], it is the best option for initial assessment of any patient [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Therefore, observing the characteristics of the trabecular bone, through structural complexity through panoramic radiographs, is of great importance [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] as it can assist in the diagnosis of various systemic and metabolic conditions in an individual [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSuch an assessment can be based on the calculation of the fractal dimension (FD) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], which is characterized by a numerical result obtained by a mathematical method called fractal analysis (FA) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The fractal method determines similar shapes, regardless of the size scale [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], and allows diagnosing potential bone abnormalities and measuring the severity of existing disorders [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Studies have been developed in the health area to evaluate trabecular bone complexity using FD in imaging exams [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Pixel intensity (PI), in turn, is a measure of \u0026ldquo;darkness\u0026rdquo; or \u0026ldquo;whiteness\u0026rdquo; and is also used in healthcare to estimate bone mass [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Osteoporosis, for example, is one of the conditions that can be observed by calculating FD and PI values ​​on panoramic radiographs [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Both methods are easy to apply and reproducible and can provide valuable information about the maxillomandibular bones.\u003c/p\u003e \u003cp\u003eHowever, no studies were found that evaluated such conditions in panoramic radiographic images of children, especially when considering greater or lesser exposure to sunlight. Since children's bone metabolism can be influenced by the condition of exposure to sunlight, and the structural complexity of the bone trabeculae and bone mass can be evaluated by FD and PI, respectively, the objective was to compare such aspects in children living in places with different sunlight conditions.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eStudy Design\u003c/p\u003e \u003cp\u003eThe study adhered to the guidelines for observational studies outlined in the STROBE (STrengthening the Reporting of OBservational studies in Epidemiology) Statement guide - A checklist of items that should be included in reports of cross-sectional studies [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSample and Eligibility Criteria\u003c/p\u003e \u003cp\u003eThe study sample comprised digital panoramic radiographs of children aged between 6 and 9 years, sourced from databases in two cities with distinct sunlight exposure conditions. One city is in the coastal region of Rio de Janeiro \u0026ndash; RJ (high sunlight exposure), while the other is in the Zona da Mata Mineira \u0026ndash; MG region (low sunlight exposure). The aim was to compare, through FD and PI values, whether different sunlight exposure conditions influence the structural complexity of trabecular bone.\u003c/p\u003e \u003cp\u003eAll images were acquired using the Orthophos 3D device (Dentsply, Sirona, Erlangen, Germany) under identical acquisition parameters (64 kVp and 10 mA). Panoramic radiographs with optimal visibility and minimal degrees of magnification and distortion were included. Those with motion artifacts, positioning and technique errors, intraosseous retained teeth in ectopic positions, bone fractures, and osteolytic lesions in the mandible were excluded.\u003c/p\u003e \u003cp\u003eExaminer training and calibration\u003c/p\u003e \u003cp\u003eA radiologist, with experience in radiographic image analysis (M.A.V.), demonstrated to two examiners in training (A.R.L and C.B.O), through a video, the parameters necessary to obtain FD in regions of interest (ROI) selected from the public domain program ImageJ\u0026reg; [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. After watching the video, all doubts were resolved, in person. Then, 20 panoramic radiographs of children, with the age of interest in the study, were used for calibration by the examiners, who independently determined the FD and PI of the ROIs selected in the images. Inter-examiner agreement ranged from 0.84 to 0.98 (ICC\u0026thinsp;=\u0026thinsp;0.984), these values ​​being considered highly reproducible [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. After this stage, the images were excluded and were not part of the main study.\u003c/p\u003e \u003cp\u003ePilot study and sample calculation\u003c/p\u003e \u003cp\u003eDue to the lack of previous studies to estimate the sample calculation parameters, a pilot study was carried out with 60 digital panoramic radiographs of children living in places more (G1; n\u0026thinsp;=\u0026thinsp;30) and less (G2; n\u0026thinsp;=\u0026thinsp;30) exposed to sunlight. comparing them regarding FD and PI values ​​in three regions of interest (ROI1, ROI2, and ROI3). ROI1 was located halfway between the neck of the mandibular condyle and the angle of the mandible, always in the posterior region close to the outermost cortex of the ramus; ROI2 in the most central region of the mandible angle; and ROI3 close to the base of the mandible, always between the mesial and distal roots of the first permanent molar (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Thus, using the Bioestat\u0026reg; program, version 5.3, the sample size was calculated, considering as parameters: total values ​​(ROI1\u0026thinsp;+\u0026thinsp;ROI2\u0026thinsp;+\u0026thinsp;ROI3) of DF (G1: 3.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31; G2: 3.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29) and IP (G1: 244.9\u0026thinsp;\u0026plusmn;\u0026thinsp;33.1; G2: 267\u0026thinsp;\u0026plusmn;\u0026thinsp;54.3), a study power estimated at 80%, standard error of 5%, and a two-sided test. Therefore, it was determined that 39 panoramic radiographs would be necessary to compare IP values ​​and 60 for FD values, in each group (more and less exposed to sunlight). Therefore, the largest number calculated (n\u0026thinsp;=\u0026thinsp;120; 60 for each group) was adopted to compose the sample for the present study.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eImage analysis\u003c/p\u003e \u003cp\u003eAfter training and calibration, a single examiner (A.R.L) analyzed, blindly (hiding the region of origin of the radiographs) and randomly, all the images included (n\u0026thinsp;=\u0026thinsp;120). A 21-inch high-resolution liquid crystal display (LCD) under soft lighting was used. The examiner analyzed, using the ImageJ\u0026reg; software, a maximum of five images per day to prevent visual fatigue from compromising the evaluations [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe three ROIs, with dimensions of 30x30 pixels, were selected in cortical bone, always on the right side of the panoramic radiograph, chosen randomly. The selection criteria for quantity, size, and specific location of ROIs were determined after training and calibration, and the analyses followed methodological standards previously described [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFractal dimension analysis\u003c/p\u003e \u003cp\u003eThe structural complexity of the bone trabeculae was obtained by calculating the FD in the 3 selected ROIs, for each group of radiographs (G1; n\u0026thinsp;=\u0026thinsp;60 and G2; n\u0026thinsp;=\u0026thinsp;60). A Gaussian filter was applied to the original image (sigma\u0026thinsp;=\u0026thinsp;35 pixels, kernel size\u0026thinsp;=\u0026thinsp;33x33), enabling the correction of large variations in density (low-pass filtering) and removing discrepancies between pixels of similar intensity. Then, the resulting image, highly blurred, was subtracted from another duplicate of the original ROI and generated a third image, in which gray values ​​(128) were added to each pixel, thus preventing some structures from standing out concerning others. Next, the third image was binarized and subsequently segmented into components that visually approximate the trabeculae. Then, noise reduction was performed, and the image was transformed into a line of a single pixel, highlighting the texture and patterns that were subjected to FD analysis [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSuperimposing the trabecular image on the original image of the bone demonstrates that the skeletal structure studied corresponds to the trabeculae in the original image. The FD was calculated using the boxcounting method, respecting the widths of square boxes previously established in the literature, with dimensions of 2, 3, 4, 6, 8, 12, 16, 32, and 64 pixels [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePixel intensity analysis\u003c/p\u003e \u003cp\u003eThe PI values ​​were also calculated for each of the established ROIs, using the program's own \u0026ldquo;Histogram\u0026rdquo; tool. When calculating the PI, average, minimum, and maximum values ​​were obtained, in addition to the specific histogram for each region, highlighting the threshold (interval between grayscale values) selected (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe results were analyzed using the Statistical Package for the Social Sciences (SPSS for Windows, version 21.0; SPSS Inc., Chicago, IL, USA). Descriptive and inferential analyses were performed. The Shapiro-Wilk test was used to verify the normality distribution of the data, considering the total PI and FD (sum of ROI1, ROI2, and ROI3) and individual means. To verify the difference in these total and individual values ​​of images from children less and more exposed to the sun, as well as between genders, the Kruskal-Wallis and Student's t-tests were used. A significance level of 5% was considered (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eSample description\u003c/p\u003e \u003cp\u003eThe images included in the study belonged to children with an average age of 7.39\u0026thinsp;\u0026plusmn;\u0026thinsp;1.11 years. Of the sample (n\u0026thinsp;=\u0026thinsp;120), 62 x-rays were from girls (51.7%), while 58 were from boys (48.3%). Furthermore, the following total DF and IP values ​​were observed: 3.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32 and 258.30\u0026thinsp;\u0026plusmn;\u0026thinsp;58.38, respectively.\u003c/p\u003e \u003cp\u003eComparison of fractal dimension between groups, considering sun exposure and sex\u003c/p\u003e \u003cp\u003eWhen analyzing the sum of the average FD values ​​of the three ROIs, there was a significant difference between the children most exposed (G1\u0026thinsp;=\u0026thinsp;3.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29) and those least exposed to the sun (G2\u0026thinsp;=\u0026thinsp;3.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29) (p\u0026thinsp;=\u0026thinsp;0.000). When analyzing each ROI separately, a significant difference was found concerning the sum of the mean values ​​of ROI2 (p\u0026thinsp;=\u0026thinsp;0.000) and ROI3 (p\u0026thinsp;=\u0026thinsp;0.000) regarding sun exposure, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTotal fractal dimension (DF) values ​​of regions of interest (ROI), presented in panoramic radiographs of children most exposed (G1) and least exposed (G2) to sunlight.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eROI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eG1 (n\u0026thinsp;=\u0026thinsp;60)\u003c/p\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eG2 (n\u0026thinsp;=\u0026thinsp;60)\u003c/p\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eFractal Dimension (FD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eROI 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,16 (0,17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,19 (0,19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0,136\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eROI 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,19 (0,19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,28 (0,14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0,000*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eROI 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,96 (0,18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,13 (0,21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0,000*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,31 (0,29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,60 (0,29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0,000*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: * Values ​​with statistical significance; SD \u0026ndash; standard deviation.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRegarding gender, considering the total sample, no significant difference was observed between FD values ​​between girls (3.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28) and boys (3.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36) (p\u0026thinsp;=\u0026thinsp;0.607), and adjusting for sun exposure, there was also no difference between girls (n\u0026thinsp;=\u0026thinsp;32; 3.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25) and more exposed boys (n\u0026thinsp;=\u0026thinsp;28; 3.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34) (p\u0026thinsp;=\u0026thinsp;0.491); as well as girls (n\u0026thinsp;=\u0026thinsp;30; 3.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24) and less exposed boys (n\u0026thinsp;=\u0026thinsp;30; 3.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33) (p\u0026thinsp;=\u0026thinsp;0.408).\u003c/p\u003e \u003cp\u003eComparison of pixel intensity between groups, considering sun exposure and sex\u003c/p\u003e \u003cp\u003eThere was no difference between the total PI values ​​between children (G1\u0026thinsp;=\u0026thinsp;261.26\u0026thinsp;\u0026plusmn;\u0026thinsp;69.54) and less exposure to sunlight (255.33\u0026thinsp;\u0026plusmn;\u0026thinsp;44.95) (p\u0026thinsp;=\u0026thinsp;0.735). However, when analyzing each ROI separately, there was a significant difference in ROI2 between those most exposed (G1\u0026thinsp;=\u0026thinsp;78.30\u0026thinsp;\u0026plusmn;\u0026thinsp;65.20) and those least exposed (G2\u0026thinsp;=\u0026thinsp;62.76\u0026thinsp;\u0026plusmn;\u0026thinsp;20.48) (p\u0026thinsp;=\u0026thinsp;0.013), as seen in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTotal pixel intensity (IP) values ​​of regions of interest (ROI), analyzed in panoramic radiographs of children most exposed (G1) and least exposed (G2) to sunlight.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eROI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eG1 (n\u0026thinsp;=\u0026thinsp;60)\u003c/p\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eG2 (n\u0026thinsp;=\u0026thinsp;60)\u003c/p\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003ePixel Intensity (PI)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eROI 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90,81 (18,56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97,00 (26,69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,143\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eROI 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78,30 (65,20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62,76 (20,47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,013*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eROI 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92,15 (10,33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95,57 (18,64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,321\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e261,26 (69,54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e255,33 (44,95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,553\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNote: * Values ​​with statistical significance; SD \u0026ndash; standard deviation.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs with FD, the total PI values ​​(p\u0026thinsp;=\u0026thinsp;0.553) of the total sample were not influenced by gender, with no difference being observed between girls (257.88\u0026thinsp;\u0026plusmn;\u0026thinsp;70.12) and boys (258.74\u0026thinsp;\u0026plusmn;\u0026thinsp;43. 05). When sun exposure was considered, there was also no difference between girls (n\u0026thinsp;=\u0026thinsp;32; 269.82\u0026thinsp;\u0026plusmn;\u0026thinsp;88.83) and more exposed boys (n\u0026thinsp;=\u0026thinsp;28; 251.48\u0026thinsp;\u0026plusmn;\u0026thinsp;36.33) (p\u0026thinsp;=\u0026thinsp;0.291) or girls (n\u0026thinsp;=\u0026thinsp;30; 245.15\u0026thinsp;\u0026plusmn;\u0026thinsp;39.76) and less exposed boys (n\u0026thinsp;=\u0026thinsp;30; 265.51\u0026thinsp;\u0026plusmn;\u0026thinsp;48.12) (p\u0026thinsp;=\u0026thinsp;0.079).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study compared the structural complexity of the bone trabeculae in children residing in areas with different sunlight exposure conditions, using DF (fractal dimension) and IP (irregularity parameter) values derived from digital panoramic radiographs. The calculation of DF and IP in imaging exams has been previously employed in dentistry to assess bone trabeculae, primarily in adults, cadavers, and animals [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. To the best of our knowledge, only one study [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] has utilized these methods to evaluate bone architecture in children. Given that sunlight exposure has the benefit of promoting the production of vitamin D3 (the \"sunshine vitamin\"), a crucial micronutrient for bone metabolism, especially in growing children, assessing trabecular bone alterations through DF and IP in children with varying levels of sun exposure becomes relevant and justified.\u003c/p\u003e \u003cp\u003eIn the reviewed literature, no study has examined variations in trabecular bone complexity based on sunlight conditions using panoramic radiographs. Existing studies have predominantly employed more complex imaging methods such as computed tomography (CT), densitometry, and dual-energy X-ray absorptiometry (DXA), focusing on bones like the radius and vertebrae [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. However, digital panoramic radiographs are cost-effective, easily executed by professionals, and well-accepted by children [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Importantly, they pose lower risks, as radiation exposure is significantly reduced compared to the methods, making them ideal for use in children [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. A recent systematic review indicated that childhood exposure to CT scans may be associated with an increased risk of cancer, while no significant association was observed with two-dimensional radiographic exams [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. This current study stands as the first to evaluate trabecular bone complexity, utilizing FD and PI calculations in digital panoramic radiographs of children exposed to different sunlight conditions.\u003c/p\u003e \u003cp\u003eA significant difference in trabecular bone density has been reported between female and male adults, being greater in men [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Therefore, in the present study, the influence of sex on FD and PI results was investigated. However, no differences were observed between boys and girls, as in the study by Arrepia et al., (2023). This result can be explained by the metabolic similarity of the bone growth phase between boys and girls in the age range studied (6 to 9 years), as more significant changes occur after this age [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. This was also the reason for choosing the age group researched; since possible confounding factors in the detection of bone trabecular variations, inherent to the different metabolism between the sexes with advancing age, especially in the growth spurt phase, could influence the results.\u003c/p\u003e \u003cp\u003eFD is widely used in the analysis of bone trabecular structure and several studies have demonstrated its ability to verify [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. The boxcounting method is the most used and recommended for calculating FD as it is easily reproducible [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. This method requires a pre-established tool [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] and is present in the ImageJ\u0026reg; program. As it is free and easily accessible software, it was chosen to be used in this work. In addition to FD, PI can also be calculated in ImageJ\u0026reg;, using the Histogram tool, and adds important information about the density of the analyzed region.\u003c/p\u003e \u003cp\u003eThe sum of FD values, considering the selected ROIs, showed a significant difference between children more and less exposed to the sun, rejecting the null hypothesis of the study. In children less exposed to sunlight, the total FD value was higher than in more exposed children. This result seems controversial when analyzing data from other studies that showed that an increase in the FD value may be associated with greater structural complexity [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. However, other studies have shown that ROIs marked in areas of pathological bone formation, such as osteosarcoma, areas of implant osseointegration, and post-orthognathic recovery, present higher FD values ​​compared to a region of normal bone [\u003cspan additionalcitationids=\"CR42\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Thus, higher FD values ​​are not always related to increased bone density, nor can they be correlated with increased PI [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. It is suggested, with this result, that low exposure to sunlight may be a predisposing factor to changes in the complexity of bone trabeculation, as it causes changes in bone metabolism, mainly due to the lack of vitamin D3.\u003c/p\u003e \u003cp\u003eSunlight is the greatest source of vitamin D, which is responsible for regulating calcium absorption and bone mineralization [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Maintaining controlled and regular exposure to sunlight is of great importance, especially during childhood and adolescence, as it is a critical period of bone development, thus avoiding changes such as rickets and fractures [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. However, measuring an individual's real exposure to sunlight involves many variables, such as investigating bone mineral density (BMD), a method considered invasive and high risk due to the ionizing radiation of the tests required for this purpose. Therefore, choosing only the place where the children live may be a limitation of the study, but it is a method that does not pose any risk to the participants and provides examinations from an image bank of panoramic X-rays that are constantly requested in dental practice.\u003c/p\u003e \u003cp\u003eIssues such as latitude, seasons, and even clothing can influence exposure to sunlight [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Children living in less sun-exposed areas may have different clothing habits, for instance, due to colder weather. Consequently, the use of coats and clothing covering a large part of the body may inhibit optimal absorption of sunlight through the skin, providing a possible explanation for the study's significant results. However, despite being an invasive examination and not always recommended in children without a diagnosis of bone diseases, it would be ideal to measure the serum levels of vitamin D in the researched children through blood tests, representing a limitation of the present study. It is suggested that further investigations into variations in children's trabecular bone, with measurement of serum vitamin D levels, be conducted.\u003c/p\u003e \u003cp\u003eIn the regions of the mandibular angle (ROI2) and body (ROI3), FD values were significantly higher in children less exposed to the sun, highlighting the impact of exposure on trabecular complexity. The mandibular angle region is explored in various studies due to its susceptibility to changes from childhood onwards [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. The position of the gonion, a point located in this region, changes life phases, leading to dimensional movements of the jaw with individual growth. Several studies have shown that gonial angle values are higher at ages 5\u0026ndash;10 and decrease over time until the age range of 15\u0026ndash;20 [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. The gonial angle is commonly assessed to determine jaw rotation and is a significant indicator for diagnosing patients' growth patterns [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Considering that low sun exposure can interfere with children's growth, it is suggested that the structural complexity of trabeculae in regions with higher metabolic activity may have been more influenced.\u003c/p\u003e \u003cp\u003eThere are studies with growing animals [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e], in which the authors assessed the insertion of the masseter in the gonial region and its influence on the rotational pattern of the mandible. The results demonstrated the influence of muscular action on bone growth, meaning that depending on the location of the muscular insertion, mandibular growth can be altered either negatively or positively. However, it is not clear whether these changes affect the rotational growth pattern of the mandible [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e], and it cannot be stated whether there is an association between muscular insertion and alterations in bone architecture in the mandibular angle regions (ROI2); thus, further studies in this field are necessary.\u003c/p\u003e \u003cp\u003eRegarding the difference found in the mandibular body (ROI3) concerning the FD results, it is believed that the stages of dental development in the permanent first molar region may have influenced the findings, as this area is constantly undergoing remodeling in the age group studied. This action occurs in conjunction with muscular maturation and craniofacial growth, meaning that biological maturation has not yet been completed at this stage [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Therefore, it is suggested that in children with less sun exposure, higher FD values were found and may be associated with lesser development in this region. However, new studies that clinically examine children in the long term, including eruption chronology and Nolla's dental development stages, are recommended.\u003c/p\u003e \u003cp\u003eAlthough the total PI value did not differ between the images of children more and less exposed to the sun, the mandibular angle region was different, even though it was always measured in cortical bone. Radiographs of less exposed children showed a lower PI value than those of children more exposed to the sun. The average PI value in ROI2 was the lowest found to the others. It is suggested that the constant modeling and bone remodeling that exists in the gonion region [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] may result in less dense images in these areas. Thus, it can be suggested that children less exposed to the sun, with lower PI values, have lower bone density in this region when compared to more exposed children, despite BMD not being assessed in the present research.\u003c/p\u003e \u003cp\u003eTechnical interferences related to the choice of imaging exam, such as the possibility of overlapping structures, and formation of ghost images, in addition to image magnification and distortion when using panoramic radiographs, could be listed as limitations. However, panoramic radiography is the most viable choice for this study, as it is a suitable method for children, due to its lower cost and lower risk, due to the low dose of radiation emitted. Possible inaccuracies in obtaining the FD could also be considered limitations since a small deviation when creating the ROI would significantly influence the morphology of tissue structures. Furthermore, the FD calculation may vary depending on the methods applied, such as boxcounting, pixel dilation, and modified pixel dilation. However, to meet these conditions, in the present study, pre-determined and anatomically demarcated ROIs were chosen, as well as the simple, public domain program, ImageJ\u0026reg;, in which the boxcounting method is already included.\u003c/p\u003e \u003cp\u003eBone fragility and fractures due to pathological conditions in children, such as rickets, are of great concern in the medical and dental fields. Therefore, the development of methods capable of assisting in the early diagnosis of these conditions becomes very important. Therefore, we can state that considering this pioneering study, a promising line of research using panoramic radiographs to observe possible variations in the complexity of bone trabeculation in children living in different sunlight conditions should be strengthened. It was seen that the use of FD and PI are good indicators for detecting bone variations in this population; Furthermore, they are easily accessible and low-cost methods, investigated in two-dimensional examinations, with low radiation doses and frequently requested by dentists in daily clinical practice.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eChildren less exposed to sunlight had higher FD values ​​when compared to those more exposed, showing differences in the structural complexity of the bone trabeculae, but without differences between the sexes and between the total PI values.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCredit Author Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAndr\u0026eacute; Ramos Losso:\u0026nbsp;\u003c/strong\u003eConceptualization, Methodology, Writing-Original draft preparation\u003cstrong\u003e; Carla Barros de Oliveira:\u0026nbsp;\u003c/strong\u003eInvestigation, Data curation\u003cstrong\u003e; Andrea Fonseca-Gon\u0026ccedil;alves:\u0026nbsp;\u003c/strong\u003eWriting - Review \u0026amp; Editing\u003cstrong\u003e; Maria Augusta Visconti:\u0026nbsp;\u003c/strong\u003eProject administration\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis is a cross-sectional study that received prior approval from the local Ethics Committee under protocol #6.180.196. The informed consent was \u0026ldquo;Not Applicable\u0026rdquo;.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interests:\u0026nbsp;\u003c/strong\u003eThe authors declare that there is no conflict of interest with the study presented.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e- Albert MR, Ostheimer KG (2003) The evolution of current medical and popular attitudes toward ultraviolet light exposure: Part 2, Journal of the American Academy of Dermatology. 48(6):909\u0026ndash;918. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1067/mjd.2003.272\u003c/span\u003e\u003cspan address=\"10.1067/mjd.2003.272\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- H, Van der Rhee E, de Vries C, Coomans P, van de Velde, Coebergh JW (2016) Sunlight: for better or for worse? a review of positive and negative effects of sun exposure. Cancer Res Front 2:156\u0026ndash;183. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.17980/2016.156\u003c/span\u003e\u003cspan address=\"10.17980/2016.156\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Elsori DH, Hammoud MS (2018) Vitamin D deficiency in mothers, neonates and children. J Steroid Biochem Mol Biol 175:195\u0026ndash;199. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jsbmb.2017.01.023\u003c/span\u003e\u003cspan address=\"10.1016/j.jsbmb.2017.01.023\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Taylor SN (2020) Vitamin D in Toddlers, Preschool Children, and Adolescents. Ann Nutr Metab 76(Suppl 2):30\u0026ndash;41. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1159/000505635\u003c/span\u003e\u003cspan address=\"10.1159/000505635\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Holick MF (2006) Resurrection of vitamin D deficiency and rickets. J Clin Invest 116(8):2062\u0026ndash;2072. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1172/JCI29449\u003c/span\u003e\u003cspan address=\"10.1172/JCI29449\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- de Souza Santos D, Dos Santos LC, de Albuquerque Tavares Carvalho A et al (2016) Multifractal spectrum and lacunarity as measures of complexity of osseointegration. Clin Oral Investig 20(6):1271\u0026ndash;1278. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00784-015-1606-1\u003c/span\u003e\u003cspan address=\"10.1007/s00784-015-1606-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Vadiati Saberi B, Khosravifard N, Nooshmand K, Dalili Kajan Z, Ghaffari ME (2021) Fractal analysis of the trabecular bone pattern in the presence/absence of metal artifact-producing objects: Comparison of cone-beam computed tomography with panoramic and periapical radiography. Dentomaxillofac Radiol 50(6):20200559. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1259/dmfr.20200559\u003c/span\u003e\u003cspan address=\"10.1259/dmfr.20200559\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Shore RM, Chesney RW, Rickets (2013) Part I. Pediatr Radiol 43(2):140\u0026ndash;151. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00247-012-2532-x\u003c/span\u003e\u003cspan address=\"10.1007/s00247-012-2532-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Arsan B, K\u0026ouml;se TE, \u0026Ccedil;ene E, \u0026Ouml;zcan İ (2016) Assessment of the Trabecular Structure of Mandibular Condyles in Patients with Temporomandibular Disorders Using Fractal Analysis, Oral Surgery, Oral Medicine. Oral Pathol Oral Radiol. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.oooo.2016.11.005\u003c/span\u003e\u003cspan address=\"10.1016/j.oooo.2016.11.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Kato CN, Barra SG, Tavares NP et al (2020) Use of fractal analysis in dental images: a systematic review. Dentomaxillofac Radiol 49(2):20180457. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1259/dmfr.20180457\u003c/span\u003e\u003cspan address=\"10.1259/dmfr.20180457\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Gordon CM, Bachrach LK, Carpenter TO et al (2008) Dual energy X-ray absorptiometry interpretation and reporting in children and adolescents: the 2007 ISCD Pediatric Official Positions. J Clin Densitom 11(1):43\u0026ndash;58. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jocd.2007.12.005\u003c/span\u003e\u003cspan address=\"10.1016/j.jocd.2007.12.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Cheung TF, Cheuk KY, Yu FW et al (2016) Prevalence of vitamin D insufficiency among adolescents and its correlation with bone parameters using high-resolution peripheral quantitative computed tomography. Osteoporos Int 27(8):2477\u0026ndash;2488. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00198-016-3552-4\u003c/span\u003e\u003cspan address=\"10.1007/s00198-016-3552-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Tom\u0026agrave; P, Bartoloni A, Salerno S et al (2019) Protecting sensitive patient groups from imaging using ionizing radiation: effects during pregnancy, in fetal life and childhood. Radiol Med 124(8):736\u0026ndash;744. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11547-019-01034-8\u003c/span\u003e\u003cspan address=\"10.1007/s11547-019-01034-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Abalo KD, Rage E, Leuraud K et al (2020) Early life ionizing radiation exposure and cancer risks: systematic review and meta-analysis [published correction appears in Pediatr Radiol. ;:]. Pediatr Radiol. 2021;51(1):45\u0026ndash;56. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00247-020-04803-0\u003c/span\u003e\u003cspan address=\"10.1007/s00247-020-04803-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- The 2007 Recommendations of the International Commission on Radiological Protection (2007) Ann ICRP 37:1\u0026ndash;332. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.icrp.2007.10.003\u003c/span\u003e\u003cspan address=\"10.1016/j.icrp.2007.10.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. ICRP publication 103\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Sams CM, Dietsche EW, Swenson DW, DuPont GJ, Ayyala RS (2021) Pediatric Panoramic Radiography: Techniques, Artifacts, and Interpretation. Radiographics 41(2):595\u0026ndash;608. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1148/rg.2021200112\u003c/span\u003e\u003cspan address=\"10.1148/rg.2021200112\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Mupparapu M, Akintoye SO (2023) Application of Panoramic Radiography in the Detection of Osteopenia and Osteoporosis-Current State of the Art. Curr Osteoporos Rep 21(4):354\u0026ndash;359. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11914-023-00807-5\u003c/span\u003e\u003cspan address=\"10.1007/s11914-023-00807-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Arrepia BF, Rocha TG, Medeiros AS, Ferreira MD, Fonseca-Gon\u0026ccedil;alves A, Visconti MA (2023) The mandibular bone structure in children by fractal dimension and its correlation with pixel intensity values: a pilot study [published online ahead of print, 2023 Jun 27]. Oral Radiol. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11282-023-00693-8\u003c/span\u003e\u003cspan address=\"10.1007/s11282-023-00693-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Lee D-H, Ku Y, Rhyu I-C, Hong J-U, Lee C-W, Heo M-S et al (2010) A clinical study of alveolar bone quality using the fractal dimension and the implant stability quotient. J Periodontal Implant Sci 40:19\u0026ndash;24. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5051/jpis.2010.40.1.19\u003c/span\u003e\u003cspan address=\"10.5051/jpis.2010.40.1.19\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Sener E, Cinarcik S, Baksi BG (2015) Use of fractal analysis for the discrimination of trabecular changes between individuals with healthy gingiva or moderate periodontitis. J Periodontol 86:1364\u0026ndash;1369. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1902/jop.2015.150004\u003c/span\u003e\u003cspan address=\"10.1902/jop.2015.150004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- S\u0026aacute;nchez I, Uzc\u0026aacute;tegui G (2011) Fractals in dentistry. J Dent 39:273\u0026ndash;292. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jdent.2011.01.010\u003c/span\u003e\u003cspan address=\"10.1016/j.jdent.2011.01.010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Lopes R, Betrouni N (2009) Fractal and multifractal analysis: a review. Med Image Anal 13(4):634\u0026ndash;649. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.media.2009.05.003\u003c/span\u003e\u003cspan address=\"10.1016/j.media.2009.05.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Apolin\u0026aacute;rio AC, Sindeaux R, de Souza Figueiredo PT, Guimar\u0026atilde;es AT, Acevedo AC, Castro LC, de Paula AP, de Paula LM, de Melo NS, Leite AF (2016) Dental panoramic indices and fractal dimension measurements in osteogenesis imperfecta children under pamidronate treatment. Dentomaxillofac Radiol 45:20150400. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1259/dmfr.20150400\u003c/span\u003e\u003cspan address=\"10.1259/dmfr.20150400\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Tosoni GM, Lurie AG, Cowan AE, Burleson JA (2006) Pixel intensity and fractal analyses: detecting osteoporosis in perimenopausal and postmenopausal women by using digital panoramic images. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 102(2):235\u0026ndash;241. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.tripleo.2005.08.020\u003c/span\u003e\u003cspan address=\"10.1016/j.tripleo.2005.08.020\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Cuschieri S (2019) The STROBE guidelines. Saudi J Anaesth 13(Suppl 1):S31\u0026ndash;S34. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4103/sja.SJA_543_18\u003c/span\u003e\u003cspan address=\"10.4103/sja.SJA_543_18\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Schneider CA, Rasband WS, Eliceiri KW (2012) NIH Image to ImageJ: 25 years of image analysis. Nat Methods 9(7):671\u0026ndash;675. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/nmeth.2089\u003c/span\u003e\u003cspan address=\"10.1038/nmeth.2089\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Landis JR, Koch GG (1977) The Measurement of Observer Agreement for Categorical Data. Biometrics 33:159\u0026ndash;174. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2307/2529310\u003c/span\u003e\u003cspan address=\"10.2307/2529310\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Rosado LPL, Barbosa IS, Junqueira RB, Martins A, Verner FS (2021) Morphometric analysis of the mandibular fossa in dentate and edentulous patients: A cone beam computed tomography study. J Prosthet Dent 125:758. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.prosdent.2021.01.014\u003c/span\u003e\u003cspan address=\"10.1016/j.prosdent.2021.01.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. .e1-758.e7\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- White SC, Rudolph DJ (1999) Alterations of the trabecular pattern of the jaws in patients with osteoporosis. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 88(99):628\u0026ndash;635. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S1079-\u003c/span\u003e\u003cspan address=\"10.1016/S1079-\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Pornprasertsuk S, Ludlow JB, Webber RL, Tyndall DA, Yamauchi M (2001) Analysis of fractal dimensions of rat bones from film and digital images. Dentomaxillofac Radiol 30(3):179\u0026ndash;183. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/sj/dmfr/4600597\u003c/span\u003e\u003cspan address=\"10.1038/sj/dmfr/4600597\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Soğur E, Baksı BG, Gr\u0026ouml;ndahl HG, Sen BH (2013) Pixel intensity and fractal dimension of periapical lesions visually indiscernible in radiographs. J Endod 39(1):16\u0026ndash;19. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.joen.2012.10.016\u003c/span\u003e\u003cspan address=\"10.1016/j.joen.2012.10.016\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Alghadir AH, Gabr SA, Rizk AA (2018) Physical Fitness, Adiposity, and Diets as Surrogate Measures of Bone Health in Schoolchildren: A Biochemical and Cross-Sectional Survey Analysis. J Clin Densitom 21(3):406\u0026ndash;419. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jocd.2017.12.006\u003c/span\u003e\u003cspan address=\"10.1016/j.jocd.2017.12.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Cheung AM, Adachi JD, Hanley DA, Kendler DL, Davison KS, Josse R et al (2013) High-resolution -peripheral quantitative computed tomography for the assessment of bone strength and structure: a review by the Canadian bone strength working group. Curr Osteoporos Rep 11:136\u0026ndash;146. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11914-013-0140-9\u003c/span\u003e\u003cspan address=\"10.1007/s11914-013-0140-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Choi YJ (2016) Dual-energy x-ray absorptiometry: beyond Bone mineral density determination. Endocrinol Metab 31:25\u0026ndash;30. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3803/EnM.2016.31.1.25\u003c/span\u003e\u003cspan address=\"10.3803/EnM.2016.31.1.25\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDi Stefano DA, Arosio P, Pagnutti S, Vinci R, Gherlone EF (2019) Distribution of Trabecular Bone Density in the Maxilla and Mandible. Implant Dent 28:340\u0026ndash;348. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/ID.0000000000000893\u003c/span\u003e\u003cspan address=\"10.1097/ID.0000000000000893\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Fan Y, Penington A, Kilpatrick N, Hardiman R, Schneider P, Clement J et al (2019) Quantifcation of mandibular sexual dimorphism during adolescence. J Anat 234:709\u0026ndash;717. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/joa.12949\u003c/span\u003e\u003cspan address=\"10.1111/joa.12949\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Erg\u0026uuml;n S, Sara\u0026ccedil;oglu A, G\u0026uuml;neri P, Ozpinar B (2009) Application of fractal analysis in hyperparathyroidism. Dentomaxillofac Radiol 38(5):281\u0026ndash;288. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1259/dmfr/24986192\u003c/span\u003e\u003cspan address=\"10.1259/dmfr/24986192\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Demirbaş AK, Erg\u0026uuml;n S, G\u0026uuml;neri P, Aktener BO, Boyacioğlu H (2008) Mandibular bone changes in sickle cell anemia: fractal analysis. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 106(1):e41\u0026ndash;e48. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.tripleo.2008.03.007\u003c/span\u003e\u003cspan address=\"10.1016/j.tripleo.2008.03.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Roschger P, Paschalis EP, Fratzl P, Klaushofer K (2008) Bone mineralization density distribution in health and disease. Bone 42:456\u0026ndash;466. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.bone.2007.10.021\u003c/span\u003e\u003cspan address=\"10.1016/j.bone.2007.10.021\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Hichijo N, Tanaka E, Kawai N, van Ruijven LJ, Langenbach GEJ (2015) Efects of decreased occlusal loading during growth on the Mandibular bone characteristics. PLoS ONE 10:e0129290. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0129290\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0129290\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Jung JH, Huh KH, Yong TH et al (2022) Differentiation of osteosarcoma from osteomyelitis using microarchitectural analysis on panoramic radiographs. Sci Rep. ;12(1):12339. Published 2022 Jul 19. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41598-022-16504-9\u003c/span\u003e\u003cspan address=\"10.1038/s41598-022-16504-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Kış HC, G\u0026uuml;lery\u0026uuml;z G\u0026uuml;rbulak A (2020) Evaluation of the peri-implant bone trabecular microstructure changes in short implants with fractal analysis. Int J Implant Dent. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s40729-020-00209-7\u003c/span\u003e\u003cspan address=\"10.1186/s40729-020-00209-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Heo MS et al (2002) Fractal analysis of mandibular bony healing afer orthognathic surgery. Oral Surg. Oral Med. Oral Pathol Oral Rad Endod 94:763\u0026ndash;767. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1067/moe.2002.128972\u003c/span\u003e\u003cspan address=\"10.1067/moe.2002.128972\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Cashman KD, Hill TR, Cotter AA et al (2008) Low vitamin D status adversely affects bone health parameters in adolescents. Am J Clin Nutr 87(4):1039\u0026ndash;1044. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/ajcn/87.4.1039\u003c/span\u003e\u003cspan address=\"10.1093/ajcn/87.4.1039\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Webb AR, Kift R, Durkin MT et al (2010) The role of sunlight exposure in determining the vitamin D status of the U.K. white adult population. Br J Dermatol 163(5):1050\u0026ndash;1055. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1365-2133.2010.09975.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1365-2133.2010.09975.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Lehtonen-Veromaa MK, M\u0026ouml;tt\u0026ouml;nen TT, Nuotio IO, Irjala KM, Leino AE, Viikari JS (2002) Vitamin D and attainment of peak bone mass among peripubertal Finnish girls: a 3-y prospective study. Am J Clin Nutr 76(6):1446\u0026ndash;1453. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/ajcn/76.6.1446\u003c/span\u003e\u003cspan address=\"10.1093/ajcn/76.6.1446\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Farrar MD, Mughal MZ, Adams JE et al (2016) Sun Exposure Behavior, Seasonal Vitamin D Deficiency, and Relationship to Bone Health in Adolescents. J Clin Endocrinol Metab 101(8):3105\u0026ndash;3113. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1210/jc.2016-1559\u003c/span\u003e\u003cspan address=\"10.1210/jc.2016-1559\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Webb AR, Engelsen O (2006) Calculated ultraviolet exposure levels for a healthy vitamin D status. Photochem Photobiol 82(6):1697\u0026ndash;1703. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1562/2005-09-01-RA-670\u003c/span\u003e\u003cspan address=\"10.1562/2005-09-01-RA-670\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Tarazona B, Paredes V, Llamas JM, Cibrian R, Gand\u0026iacute;a JL (2010) Influence of first and second premolar extraction or non-extraction treatments on mandibular third molar angulation and position. A comparative study. Med Oral Patol Oral Cir Bucal. ;15(5):e760-e766. Published 2010 Sep 1. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4317/medoral.15.e760\u003c/span\u003e\u003cspan address=\"10.4317/medoral.15.e760\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Upadhyay RB, Upadhyay J, Agrawal P, Rao NN (2012) Analysis of gonial angle in relation to age, gender, and dentition status by radiological and anthropometric methods. J Forensic Dent Sci 4(1):29\u0026ndash;33. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4103/0975-1475.99160\u003c/span\u003e\u003cspan address=\"10.4103/0975-1475.99160\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLarrazabal-Moron C, Sanchis-Gimeno JA (2018) Gonial angle growth 51- patterns according to age and gender. Ann Anat 215:93\u0026ndash;96. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.aanat.2017.09.004\u003c/span\u003e\u003cspan address=\"10.1016/j.aanat.2017.09.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Okşayan R, Aktan AM, S\u0026ouml;k\u0026uuml;c\u0026uuml; O, Haştar E, Ciftci ME (2012) Does the panoramic radiography have the power to identify the gonial angle in orthodontics? ScientificWorldJournal 2012:219708. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1100/2012/219708\u003c/span\u003e\u003cspan address=\"10.1100/2012/219708\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Xiao D, Gao H, Ren Y (2011) Craniofacial morphological characteristics of Chinese adults with normal occlusion and different skeletal divergence. Eur J Orthod 33(2):198\u0026ndash;204. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/ejo/cjq064\u003c/span\u003e\u003cspan address=\"10.1093/ejo/cjq064\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Navarro M, Delgado E, Monje F (1995) Changes in mandibular rotation after muscular resection. Experimental study in rats. Am J Orthod Dentofac Orthop 108(4):367\u0026ndash;379. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/s0889-5406(95)70034-x\u003c/span\u003e\u003cspan address=\"10.1016/s0889-5406(95)70034-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Bayram B, Uckan S, Cetinsahin A, Arman Ozcirpici A, Ozdemir H, Yazici C (2010) Repositioning of the masseter muscle and its effect on skeletal growth. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 109(5):e1\u0026ndash;e5. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.tripleo.2009.12.041\u003c/span\u003e\u003cspan address=\"10.1016/j.tripleo.2009.12.041\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Dean JA (2021) McDonald and Avery\u0026rsquo;s Dentistry for the Child and Adolescent, 11th edn. Elsevier, Unites States\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Fractals, imaging diagnosis, panoramic radiography, child, bone","lastPublishedDoi":"10.21203/rs.3.rs-4086569/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4086569/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjectives: \u003c/strong\u003eThis study aimed to assess the trabecular bone structural complexity in children with varying sunlight exposure using panoramic radiographs (PR) and investigate potential implications for bone metabolism. Fractal dimension (FD) and pixel intensity (PI) were employed for comparison.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterials and Methods: \u003c/strong\u003ePanoramic radiographs (n=120) of 6 to 9-year-old children, divided into more (n=60) and less (n=60) sunlight exposure groups, were assessed. ImageJ\u003csup\u003e®\u003c/sup\u003e software was used to analyze three regions of interest (ROI) in each radiograph. FD, determined by the box-counting method, and PI values were compared across ROIs and between exposure groups and genders using Kruskal-Wallis and t-tests (p\u0026lt;0.05).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eChildren with less sunlight exposure exhibited higher FD values (3.60 ± 0.29) compared to those with more exposure (3.31 ± 0.29) (p=0.000), particularly in ROI2 and ROI3. No gender-based differences were observed (p=0.607). PI values were similar between exposure groups (p=0.735) and genders (p=0.553), except for a significant difference in ROI2 of less exposed children (62.76 ± 20.48) compared to more exposed ones (78.30 ± 65.20).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eReduced sunlight exposure in children was associated with higher FD values, impacting trabecular bone structural complexity. However, total PI values remained unaffected by sunlight exposure. This suggests that dentists, utilizing FD and PI analysis on routinely requested PR, can contribute to the early detection of potential bone variations in children.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Relevance: \u003c/strong\u003eUnderstanding FD and PI applications in PR can empower dentists for the early identification of bone variations in pediatric patients during routine clinical assessments.\u003c/p\u003e","manuscriptTitle":"Structural Complexity of the Bone Trabecular in Children Exposed to Different Sunlight Conditions: A Cross-Sectional Study with Panoramic Radiographs","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-22 13:23:29","doi":"10.21203/rs.3.rs-4086569/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f6208100-0977-48e1-b1bd-71e590b97d58","owner":[],"postedDate":"March 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-04-12T01:28:27+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-22 13:23:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4086569","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4086569","identity":"rs-4086569","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}