Quantitative evaluation of artifact expression of mesoporous calcium silicate nanoparticles as a new promising root canal sealer in cone-beam computed tomography

Quantitative evaluation of artifact expression of mesoporous calcium silicate nanoparticles as a new promising root canal sealer in cone-beam computed tomography | 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 Quantitative evaluation of artifact expression of mesoporous calcium silicate nanoparticles as a new promising root canal sealer in cone-beam computed tomography Tingting Zhu, Cheng Chen, Huili Wu, Xiao Zhao, Diya Leng, Daming Wu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1749437/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: To quantitatively evaluate the artifact area of the image of mesoporous calcium silicate nanoparticles (MCSNs) using cone-beam computed tomography (CBCT). Methods: Forty single-rooted mandibular premolars were selected and prepared with NiTi rotary instruments to 35/0.04, and divided into four groups (n=10): (I) AH Plus sealer; (II) MCSNs sealer; (III) iRoot SP sealer and (IV) no sealer. There were filled with a single cone (35/0.04 taper) method. The roots were scanned using a CBCT with the same parameters before and after filling. The images were evaluated using ImageJ’s threshold tool to quantitatively determine the hyperdense and hypodense artifacts, and non-affected teeth areas within 8-bit images extracted from the scans. Results: MCSNs showed fewer hyperdense artifacts than AH plus and iRoot SP ( P 0.05). Conclusion: MSCNs can effectively reduce the generation of hyperdense artifacts in CBCT images and show better image qualities, indicating that they have a minor adverse effect on evaluating the quality of root canal filling and diagnosing root canal diseases in CBCT images. Clinical Relevance: As a novel type of root canal filling nanomaterials, MSCNs have less artifact expression and higher quality in CBCT images. Therefore, this new root filling material is expected to play a positive role in improving the correct clinical evaluation of root canal filling teeth and the visualization of root canal cracks and fractures. artifacts cone-beam computed tomography mesoporous calcium-silicate nanoparticles root canal sealer Figures Figure 1 Figure 2 1. Introduction In recent years, cone-beam computed tomography (CBCT) has been widely used in stomatology due to its low cost, low radiation dose, small size, high spatial resolution, easy operation and maintenance [ 1 – 3 ] . Its high resolution and multi-plane images are beneficial to diagnosing, treating and prognostic evaluation of endodontic diseases and often positively influence the final diagnosis and treatment plan. During the endodontic treatment or retreatment, CBCT scanning is considered necessary for evaluating inflammatory resorptive defects and making surgical treatment plans [ 3 , 4 ] . However, CBCT also has limitations, such as artifacts, which will reduce the contrast between adjacent objects, significantly affect the quality of CBCT images and eventually lead to inaccurate or false diagnoses. Image artifacts are visual structures in reconstructed data that do not exist in the subjects under investigation and occur due to the patient's movement, image capture, and reconstruction processes [ 5 ] . Among all kinds of artifacts (such as noise, beam hardening, scattering, pseudo-enhancement, motion, cone beam, spiral, ring artifacts, and others), beam hardening artifacts are considered the most common artifacts caused by dental implants and metal restorations [ 6 ] . As the beam passes through a highly absorbing material (such as metal), lower energy photons absorb faster than higher energy photons, causing the beam to harden, i.e., its average energy increases, which may affect the gray level non-uniformity on the CBCT [ 5 ] . Gutta-percha point (GP) and sealers are the most commonly used root canal filling materials with a high atomic number and high density. Streaks, hypodense halos, or cupping artifacts around the root filling on CBCT images [ 7 ] . These artifacts can alter the dentin visibility and accuracy around the root filling, interfere with the diagnostic process and lead to incorrect diagnosis and treatment plans. For example, the artifacts caused by root filling materials reduce the ability to detect vertical root fractures [ 8 , 9 ] and distort the area's volume around the materials [ 10 , 11 ] , affecting the evaluation of filling quality and the exploration of missing root canals. What is more serious is that these inaccurate image interpretations may lead to unnecessary extraction of teeth. Computer hardware and software development and scanning parameter setting of CBCT is the leading solutions for eliminating image artifacts. Most studies observed artifacts in reconstructed images according to different CBCT units [ 12 ] , exposure parameters [ 13 ] , field of view size [ 14 ] , and filling materials [ 15 ] . Based on these quantitative or qualitative analyses, there are significant differences among the studied filling materials compared to the weak interaction among the exposure parameters [ 13 ] . When studying the role of artifact reduction software in overcoming the light or dark components of beam hardening artifacts, the results suggested that the images generated by artifact reduction programs should be cautious [ 16 , 17 ] . An important objective in radiology is to use a radiation dose as low as diagnostically acceptable according to the as low as reasonably achievable (ALARA) principle, however, many abnormalities in image quality may occur because of the reduction of the radiation dose to the patient to a minimum. Therefore, it is important to balance radiation dose reduction and maintain high image quality. Mesoporous calcium-silicate nanoparticles (MCSNs) are new advanced biomaterials with multi-functional root canal filling [ 18 ] . MCSNs can promote the osteogenic differentiation of stem cells in vitro and hard tissue regeneration in vivo and realize bone generation and defect repair. They are also considered an excellent platform for effective drug delivery and osteogenesis [ 19 ] . In our previous study, MCSNs have an internal mesoporous microstructure and high specific surface area and pore volume, can be used as an injection paste for sealing tooth apical root canal [ 18 ] . MCSNs can induce mineralization and have good drug delivery and antibacterial properties, making them possible to become a new type of root canal sealer. The components of MCSNs are similar to mineral trioxide aggregate (MTA) and iRoot SP sealer, of which produce obvious artifacts in CBCT images [ 15 ] . However, it is unclear whether MCSNs produce artifacts in CBCT images. Therefore, the aim of this study is to quantitatively evaluate the artifacts expression of MCSNs in CBCT images and compare it with the expression of commonly used root canal filling materials in the clinic. 2. Materials And Methods 2.1. Sample selection This study was approved by the Ethics Committee of our university (PJ2021-123-001) and follows the Helsinki Declaration. Written informed consent has been obtained from the participants. Mature single-rooted mandibular premolars recently extracted for orthodontic treatment were collected. All teeth were inspected by clinical inspection and pre-operative periapical radiography to confirm the presence of only one straight root canal, without caries lesions, pulp calcification, internal and/or external root resorption, previous endodontic treatment, posts or crowns restoration, root fractures or any other anomaly. A total of 40 premolars were collected. 2.2. Sample Preparation The crowns of the teeth were removed, and the roots were standardized to 12 mm long from the root apex. The working length was established at 0.5mm short of the apical foramen. Root canals were prepared with M3 nickel titanium rotary instruments (United Dental, Shanghai, China) to 35#/0.04. During preparation, the root canals were irrigated with 2 mL of 5.25% sodium hypochlorite (NaOCl) between files. After preparation, root canals were irrigated with 5 mL of 17% EDTA, followed by 3 mL of 5.25% NaOCl and 3 mL of distilled water. Root canals were dried with paper points. 2.3. CBCT Scanning A dry edentulous human mandible was used as a phantom for this study. To simulate soft tissue attenuation, a 5-mm-thick layer of wax was placed on the periphery of the mandible. The CBCT images were acquired using a scanner (NewTom 5G, QR s.r.l., Italy) according to the manufacturer's recommended protocol by an experienced radiologist with the following parameter: 110KV, 5 mA, voxel size of 0.15mm, 12cm×8cm field of view, exposure time of 5.4 seconds, high resolution scanning protocols. The data was exported as Digital Imaging and Communication in Medicine (DICOM) files. 2.4. Sample Obturation and CBCT Scanning The sample was randomly divided into four groups (n = 10): Group 1 was filled with a gutta-percha point (Maillefer, Ballaiges, Switzerland) and AH Plus sealer (Dentsply DeGrey, Konstanz, Germany), Group 2 was filled with a gutta-percha point and MCSNs sealer, Group 3 was filled with a gutta-percha point and iRoot SP sealer (FKG Dentaire SA, Switzerland) and Group 4 was filled with a gutta-percha point (blank control). MCSNs were synthesized and characterized in our previous studies (10,19). MCSNs sealer was prepared by mixing MCSNs with sterile ddH 2 O in a ratio of 1:3. AH Plus and iRoot SP sealers were prepared according to the manufacturer's recommendations. All canals were filled with a single cone (35/0.04 taper) method. Coronal access was sealed with a temporary sealer and the roots were stored at 37°C in 100% humidity for 7 days to allow complete setting of the sealer. An experienced operator completed all operations following the manufacturers’ instructions. Then, the teeth were scanned using the CBCT again as described above. 2.5. Imaging preparation As the first image processing step, all DICOM files were imported into the 3D Slicer software ( http://www.slicer.org , Surgical Planning Laboratory, Harvard University, Boston, MA, USA, version 4.11) for image registration purposes. To select the corresponding slices on the images of the different states of the sample, we registered the images using the Elastix software packages ( http://elastix.isi.uu.nl/ , University Medical Centre Utrecht and collaborators), which is a collection of parametric intensity-based registration methods. The most basic command to run registration is the no fill group as the ‘fixed’ image and the filling group as the ‘moving’ image. This application is used rigid transformations (global translations and rotations). Aligned CBCT images were saved in DICOM format. Then, the DICOM files were imported into the Mimics software (version 21.0, Materialise NV, Leuven, Belgium), and each sample was first separated from the others using the crop tool. The most representative axial slice of the root was selected at 4 mm from the cementoenamel junction (CEJ). Axial slices were transferred to the ImageJ software (National Institutes of Health, Bethesda, MD) in JPEG format for analysis (8-bit). For image processing, copy each unfilled dental axis image and convert it into a binary image (0-root canal and background, 255 dentine) by using the threshold tool of ImageJ software. The binarized unfilled and filled tooth images overlapped with the GNU Image processing program (GIMP), then ImageJ software removed the area where the image corresponded to the root canal material, finally obtaining axial images for artifacts quantitative analysis. All CBCT image processing programs are shown in Fig. 1 . 2.6. Artifact analysis In 8-bit images with 256 gray levels, the hypodense and hyperdense artifact areas were determined using the ImageJ thresholding tool. As shown in Fig. 2 , hypodense artifacts ranged from 105 to 179, hyperdense artifacts ranged from 238 to 255, and non-affected teeth were between low - and high-density artifacts ranging from 180 to 237. Behind the macro tool selects all slices for the corresponding region, the “measure” option obtains the result for the ROI (the region of interest). After 30 days, the intra-examiner agreement followed for a repeat assessment. 2.7. Statistics Analysis Statistical analysis used the SPSS Statistics software package (Version 23; IBM Corp., Armonk, NY, USA). Considering data were normally distributed, differences between groups test by analysis of variance (ANOVA) and differences within groups by paired t-test. In addition, intra- examiner agreement calculates using the intraclass correlation coefficient. Significance level set at α = 5%. 3. Results The Intraclass correlation coefficient showed excellent reproducibility with an ICC value of 0.974, 0.842 and 0.975, respectively. Table 1 and Table 2 showed the hyperdense area, hypodense area and non-affected tooth area of the experimental groups. The hyperdense areas of MCSNs were not significantly different from the GP but lower than the other two groups( P < 0.01), while the hyperdense area of AH Plus was higher than the other groups ( P < 0.01). Table 1 Mean area and standard deviation (SD), minimum and maximum artifacts of the root filling materials measured in CBCT images (µm 2 ). Artifacts Sealers Minimum Maximum Mean ± SD P values hyperdense Area AH plus 1624.0 12463.0 6295.4 ± 2832 a 0.000 MCSNs 1976.0 6661.0 2060.2 ± 1816.43 c iRootSP 244.0 6238.0 4022.3 ± 1465.85 b GP 58.0 4342.0 1665.8 ± 1402.14 c hypodense Area AH plus 2490.0 10873.0 5307.5 ± 2559.84 a 0.841 MCSNs 2757.0 10692.0 5649.4 ± 3197.96 a iRootSP 2579.0 9238.0 4644.7 ± 1902.65 a GP 2433.0 8418.0 5307.9 ± 2249.97 a non-affected Area AH plus 3591.0 16077.0 7667.2 ± 4028.88 b 0.025 MCSNs 3106.0 26463.0 12547 ± 6705.02 ab iRootSP 4067.0 17340.0 9512.4 ± 4367.85 b GP 6488.0 28400.0 15156.3 ± 6718.82 a * Different letters in the same column represent statistically significant results ( P < .05). Table 2 Comparison of beam hardening artifact area between hyperdense artifact and hypodense artifact. Sealers Artifact Mean ± SD P-value AH plus + GP Hyperdense Area 6295.4 ± 2832.00 0.333 Hypodense Area 5307.5 ± 2559.84 MCNSs + GP Hyperdense Area 2060.2 ± 1816.43 0.004 Hypodense Area 5649.4 ± 3197.96 iRoot SP + GP Hyperdense Area 4022.3 ± 1465.85 0.326 Hypodense Area 4644.7 ± 1902.65 GP Hyperdense Area 1665.8 ± 1402.14 0.002 Hypodense Area 5307.9 ± 2249.97 There was no significant difference in the area of the hypodense area between the experimental groups ( P > 0.05). Moreover, there was no significant difference between the non-affected area of MCSNs and GP ( P > 0.05), but the non-affected area of AH Plus and iRoot SP decreased significantly compared with GP ( P > 0.05) Paired sample t-test showed that the average value of the hyperdense area of MCSNs and GP was significantly lower than that of the hypodense area ( P < 0.05). 4. Discussion CBCT has excellent help in diagnosing, treating and evaluating pulp diseases, but its image quality is often affected by many factors such as artifacts. Studies have shown that differences between the actual physical conditions of the measurement equipment and the simplified mathematical assumptions used for 3D reconstruction lead to artifacts [ 20 ] . Other factors, such as initial reconstruction, artifact reduction algorithm, projection polychromatic, patient movement, FOV and photon diffraction, all affect the generation of artifacts [ 2 ] . Clinical artifacts have a stripy appearance due to the substantial absorption of low-energy (lower wavelength) rays in the polychromatic spectrum emitted by X-ray sources as they pass through an object. For example, its internal absorption wavelength acts as a filter with a high density and high atomic number of metal materials. Nanomaterials have unique structures and properties different from other materials and have been increasingly widely used in oral materials, among which nanoparticles are the most prominent [ 21 ] .For example, nanoparticles in clinical dental prosthesis composites can promote dentin remineralization and tubule occlusion [ 22 , 23 ] . In addition, they can be used in combination with sealants, obturating material [ 24 ] , intracanal medicament and irrigating solutions [ 25 ] for therapeutic use, providing new strategies for treating dental pulp diseases. Previous studies have confirmed that MCSNs have low cytotoxicity and strong antibacterial activity and can induce calcified tissue formation around the apical pore. Meanwhile, the high surface area and porous interior of MCSNs can serve as a reservoir for drug molecules. It can further destroy bacterial biofilm and prevent adhesion to dentin [ 19 ] . In this study, the artifacts of MCSNs in CBCT images were quantitatively compared with AH, iRoot SP and gutta-percha. The results show that the hypodense artifacts of MCSNs are not significantly different from those of other materials ( P ༞0.05), suggesting that MCSNs showed the same properties as existing materials in terms of hypodense artifacts, which met the requirements of radiopaque materials for root canal filling. However, When X-rays pass through, low-energy X-ray photons are absorbed, and the remaining high-energy photons are not easy to attenuate, leading to the beam hardening effect. After all, the generation of artifacts is related to the radiopacifiers and other chemicals in the formulations of these sealants, which may lead to different densities. The density of these materials can explain no significant difference between the hypodense artifacts of AH plus and iRoot SP in the experiment, which is different from the previous experimental results [ 15 ] . Clinically, hypodense artifacts may mimic diseases such as root fissures, or fractures in root fillings, negatively affecting diagnostic accuracy [ 8 ] . In addition, the study showed that the hyperdense artifact area of MCSNs was significantly lower than that of AH plus and iRoot SP ( P < 0.01). While the radiation impermeability of bioceramic sealer is markedly lower than that of AH plus, which is consistent with previous studies [ 10 , 15 , 26 ] . Since this is the first time that artifacts produced by MCSNs have been evaluated, the atomic number of the nanoparticle materials is lower, considering that these filling materials have different atomic compositions. Compared with AH plus (oxygen Z = 8, silicon Z = 14, calcium Z = 20, iron Z = 26, zirconium Z = 40, tungsten Z = 74) and iRoot SP(hydrogen Z = 1, oxygen Z = 8, silicon Z = 14, calcium Z = 20, phosphorus Z = 15, zirconium Z = 40), MSCNs had the lowest atomic numbers (oxygen Z = 8, silicon Z = 14, calcium Z = 20) [ 27 ] . Studies have confirmed that hyperdense artifacts have a partial volume effect [ 28 ] , which will blur the anatomical morphology of the root canal, hinder the detection of the region of interest, and seriously impair the evaluation of root filling teeth and the visualization of root canals, cracks and tooth fractures. These hyperdense artifacts may negatively affect the accuracy of diagnosis, especially in the clinical diagnosis of vertical root fractures (VRF) and perforation [ 29 ] , which have a poor prognosis. Therefore, we tested the artifact expression of MCSNs and confirmed its obvious advantage in reducing the image density artifact area, which can effectively avoid misdiagnosis. We believe that MCSNs will become an attractive material in root canal therapy in the future. There were no significant differences between the AH plus and the iRoot SP groups ( P > 0.05). However, there were substantial differences in hyperdense and hypodense artifacts area between the MCSNs group and the GP group ( P < 0.05), which were similar to previous studies [ 13 , 30 , 31 ] . Interestingly, the mean area and standard deviation results showed that MSCNs produced significantly fewer artifacts and were the root canal sealant material with the smallest artifact area. Studies have shown that the different CBCT units [ 12 , 32 , 33 ] and exposure parameters (such as tube voltage, tube current, FOV and reconstructed voxel) lead to significant differences in the appearance of artifacts [ 14 , 34 , 35 ] . In this study, we used the same CBCT units and exposure parameters to eliminate the possible influence of these different structures on gray value and area assessment. In addition, although MCSNs are not yet clinically available, given the increasing use of CBCT in current dental practice, we believe that our results on the artifacts properties of this material will contribute to significant improvements in dental nanomaterials. 5. Conclusions MSCNs have the same performance as AH plus and iRoot SP in displaying hypodense artifacts but significantly reducing the generation of hyperdense artifacts, indicating that they can be used as a new and promising root canal sealer and have a minor adverse effect on evaluating the quality of root canal filling and diagnosing root canal diseases in CBCT images. Declarations Acknowledgments The work was supported by A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (2018-87) and the Scientific Research Project of Health Care for Cadres of Jiangsu Province (BJ21034). The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Author Contributions Tingting Zhu: Conceptualization, Methodology, Software, Writing - Original Draft. Cheng Chen: Software, Validation. Huili Wu: Data Curation. Xiao Zhao: Resources. Diya Leng: Supervision. Daming Wu: Writing - Review & Editing, Funding acquisition. Funding The work was supported by A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (2018-87) and the Scientific Research Project of Health Care for Cadres of Jiangsu Province (BJ21034). 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Influence of voxel size and scan field of view on fracture-like artifacts from gutta-percha obturated endodontically treated teeth on cone-beam computed tomography images.Oral Surg Oral Med Oral Pathol Oral Radiol 122: 631-637.10.1016/j.oooo.2016.07.014 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-1749437","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":115229047,"identity":"14ee8556-3ba3-4a99-91b0-96a9e1554791","order_by":0,"name":"Tingting Zhu","email":"","orcid":"","institution":"The Affiliated Stomatological Hospital of Nanjing Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Tingting","middleName":"","lastName":"Zhu","suffix":""},{"id":115229048,"identity":"20177f9d-3b95-4eb9-8b01-8b302f2a7b85","order_by":1,"name":"Cheng Chen","email":"","orcid":"","institution":"The Affiliated Stomatological Hospital of Nanjing Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Cheng","middleName":"","lastName":"Chen","suffix":""},{"id":115229049,"identity":"1c116efd-d1f8-44d9-8430-2cd3f1d0791b","order_by":2,"name":"Huili Wu","email":"","orcid":"","institution":"The Affiliated Stomatological Hospital of Nanjing Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Huili","middleName":"","lastName":"Wu","suffix":""},{"id":115229050,"identity":"3ccf7ec9-a85e-4743-b04e-261712d701fb","order_by":3,"name":"Xiao Zhao","email":"","orcid":"","institution":"The Affiliated Stomatological Hospital of Nanjing Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiao","middleName":"","lastName":"Zhao","suffix":""},{"id":115229051,"identity":"40ea3edb-8b4b-4574-ad18-f77e5b647a91","order_by":4,"name":"Diya Leng","email":"","orcid":"","institution":"The Affiliated Stomatological Hospital of Nanjing Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Diya","middleName":"","lastName":"Leng","suffix":""},{"id":115229052,"identity":"a8e73f58-6cee-45f6-93cc-6c1974a347ae","order_by":5,"name":"Daming Wu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyUlEQVRIiWNgGAWjYFCCBIYDDAw2DIwNIA4b8VrSSNQCBIehHGK0GBzPTjxc8Ot8HvO0MwYMH8oOM/DPbiCg5czbDYdn9t0uZpydY8A449xhBok7B/BrMbuRu+Ewb8/txEagFmbetsMMBhIJRGk5B9Hyl2gtPD8OQLQwEqPFHuQX3oZkoJa0goM959J5JG4Q0CLZnrv5M88fu8SNs5M3PvhRZi3HP4OAFjBgbGNgMGxgAMUpAw8R6kHgDwODPJFKR8EoGAWjYAQCAF9/TMSDnQURAAAAAElFTkSuQmCC","orcid":"","institution":"The Affiliated Stomatological Hospital of Nanjing Medical University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Daming","middleName":"","lastName":"Wu","suffix":""}],"badges":[],"createdAt":"2022-06-12 03:29:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1749437/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1749437/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":23147083,"identity":"87652a49-f8d1-440b-961c-941ad5c5c498","added_by":"auto","created_at":"2022-06-27 20:59:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1686717,"visible":true,"origin":"","legend":"\u003cp\u003eMethodology Flowchart.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-1749437/v1/835ac4c342fa26197bc51ef5.png"},{"id":23147086,"identity":"42c445f8-5db5-4cb7-9235-88c6328ae827","added_by":"auto","created_at":"2022-06-27 20:59:15","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":891498,"visible":true,"origin":"","legend":"\u003cp\u003eSelection of the areas corresponding to the studied artifacts with the Threshold tool: (A) Hyperdense area, (B) Hypodense area (C) Non-affected tooth area (a)Hyperdense artifact binary image(b) Hypodense artifact binary image(c) the remaining tooth binary image.\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-1749437/v1/4191fa06ab514b1afc40aa1d.png"},{"id":29693121,"identity":"e8f6fff8-fc1a-4b6c-80a2-90bb74fb6efb","added_by":"auto","created_at":"2022-11-30 01:14:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":620455,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1749437/v1/9f433d3b-59d1-4fe8-8ea8-f51f6f848727.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Quantitative evaluation of artifact expression of mesoporous calcium silicate nanoparticles as a new promising root canal sealer in cone-beam computed tomography","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eIn recent years, cone-beam computed tomography (CBCT) has been widely used in stomatology due to its low cost, low radiation dose, small size, high spatial resolution, easy operation and maintenance\u003csup\u003e[\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. Its high resolution and multi-plane images are beneficial to diagnosing, treating and prognostic evaluation of endodontic diseases and often positively influence the final diagnosis and treatment plan. During the endodontic treatment or retreatment, CBCT scanning is considered necessary for evaluating inflammatory resorptive defects and making surgical treatment plans\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. However, CBCT also has limitations, such as artifacts, which will reduce the contrast between adjacent objects, significantly affect the quality of CBCT images and eventually lead to inaccurate or false diagnoses.\u003c/p\u003e \u003cp\u003eImage artifacts are visual structures in reconstructed data that do not exist in the subjects under investigation and occur due to the patient's movement, image capture, and reconstruction processes\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. Among all kinds of artifacts (such as noise, beam hardening, scattering, pseudo-enhancement, motion, cone beam, spiral, ring artifacts, and others), beam hardening artifacts are considered the most common artifacts caused by dental implants and metal restorations\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. As the beam passes through a highly absorbing material (such as metal), lower energy photons absorb faster than higher energy photons, causing the beam to harden, i.e., its average energy increases, which may affect the gray level non-uniformity on the CBCT\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eGutta-percha point (GP) and sealers are the most commonly used root canal filling materials with a high atomic number and high density. Streaks, hypodense halos, or cupping artifacts around the root filling on CBCT images\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. These artifacts can alter the dentin visibility and accuracy around the root filling, interfere with the diagnostic process and lead to incorrect diagnosis and treatment plans. For example, the artifacts caused by root filling materials reduce the ability to detect vertical root fractures\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e and distort the area's volume around the materials\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e, affecting the evaluation of filling quality and the exploration of missing root canals. What is more serious is that these inaccurate image interpretations may lead to unnecessary extraction of teeth.\u003c/p\u003e \u003cp\u003eComputer hardware and software development and scanning parameter setting of CBCT is the leading solutions for eliminating image artifacts. Most studies observed artifacts in reconstructed images according to different CBCT units \u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e, exposure parameters\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e, field of view size\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e, and filling materials\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. Based on these quantitative or qualitative analyses, there are significant differences among the studied filling materials compared to the weak interaction among the exposure parameters\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. When studying the role of artifact reduction software in overcoming the light or dark components of beam hardening artifacts, the results suggested that the images generated by artifact reduction programs should be cautious\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. An important objective in radiology is to use a radiation dose as low as diagnostically acceptable according to the as low as reasonably achievable (ALARA) principle, however, many abnormalities in image quality may occur because of the reduction of the radiation dose to the patient to a minimum. Therefore, it is important to balance radiation dose reduction and maintain high image quality.\u003c/p\u003e \u003cp\u003eMesoporous calcium-silicate nanoparticles (MCSNs) are new advanced biomaterials with multi-functional root canal filling\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. MCSNs can promote the osteogenic differentiation of stem cells in vitro and hard tissue regeneration in vivo and realize bone generation and defect repair. They are also considered an excellent platform for effective drug delivery and osteogenesis \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. In our previous study, MCSNs have an internal mesoporous microstructure and high specific surface area and pore volume, can be used as an injection paste for sealing tooth apical root canal\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. MCSNs can induce mineralization and have good drug delivery and antibacterial properties, making them possible to become a new type of root canal sealer. The components of MCSNs are similar to mineral trioxide aggregate (MTA) and iRoot SP sealer, of which produce obvious artifacts in CBCT images\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. However, it is unclear whether MCSNs produce artifacts in CBCT images.\u003c/p\u003e \u003cp\u003eTherefore, the aim of this study is to quantitatively evaluate the artifacts expression of MCSNs in CBCT images and compare it with the expression of commonly used root canal filling materials in the clinic.\u003c/p\u003e"},{"header":"2. Materials And Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Sample selection\u003c/h2\u003e \u003cp\u003eThis study was approved by the Ethics Committee of our university (PJ2021-123-001) and follows the Helsinki Declaration. Written informed consent has been obtained from the participants.\u003c/p\u003e \u003cp\u003eMature single-rooted mandibular premolars recently extracted for orthodontic treatment were collected. All teeth were inspected by clinical inspection and pre-operative periapical radiography to confirm the presence of only one straight root canal, without caries lesions, pulp calcification, internal and/or external root resorption, previous endodontic treatment, posts or crowns restoration, root fractures or any other anomaly. A total of 40 premolars were collected.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Sample Preparation\u003c/h2\u003e \u003cp\u003eThe crowns of the teeth were removed, and the roots were standardized to 12 mm long from the root apex. The working length was established at 0.5mm short of the apical foramen. Root canals were prepared with M3 nickel titanium rotary instruments (United Dental, Shanghai, China) to 35#/0.04. During preparation, the root canals were irrigated with 2 mL of 5.25% sodium hypochlorite (NaOCl) between files. After preparation, root canals were irrigated with 5 mL of 17% EDTA, followed by 3 mL of 5.25% NaOCl and 3 mL of distilled water. Root canals were dried with paper points.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. CBCT Scanning\u003c/h2\u003e \u003cp\u003eA dry edentulous human mandible was used as a phantom for this study. To simulate soft tissue attenuation, a 5-mm-thick layer of wax was placed on the periphery of the mandible.\u003c/p\u003e \u003cp\u003eThe CBCT images were acquired using a scanner (NewTom 5G, QR s.r.l., Italy) according to the manufacturer's recommended protocol by an experienced radiologist with the following parameter: 110KV, 5 mA, voxel size of 0.15mm, 12cm\u0026times;8cm field of view, exposure time of 5.4 seconds, high resolution scanning protocols. The data was exported as Digital Imaging and Communication in Medicine (DICOM) files.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Sample Obturation and CBCT Scanning\u003c/h2\u003e \u003cp\u003eThe sample was randomly divided into four groups (n\u0026thinsp;=\u0026thinsp;10): Group 1 was filled with a gutta-percha point (Maillefer, Ballaiges, Switzerland) and AH Plus sealer (Dentsply DeGrey, Konstanz, Germany), Group 2 was filled with a gutta-percha point and MCSNs sealer, Group 3 was filled with a gutta-percha point and iRoot SP sealer (FKG Dentaire SA, Switzerland) and Group 4 was filled with a gutta-percha point (blank control). MCSNs were synthesized and characterized in our previous studies (10,19). MCSNs sealer was prepared by mixing MCSNs with sterile ddH\u003csub\u003e2\u003c/sub\u003eO in a ratio of 1:3. AH Plus and iRoot SP sealers were prepared according to the manufacturer's recommendations. All canals were filled with a single cone (35/0.04 taper) method. Coronal access was sealed with a temporary sealer and the roots were stored at 37\u0026deg;C in 100% humidity for 7 days to allow complete setting of the sealer. An experienced operator completed all operations following the manufacturers\u0026rsquo; instructions.\u003c/p\u003e \u003cp\u003eThen, the teeth were scanned using the CBCT again as described above.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Imaging preparation\u003c/h2\u003e \u003cp\u003eAs the first image processing step, all DICOM files were imported into the 3D Slicer software (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.slicer.org\u003c/span\u003e\u003cspan address=\"http://www.slicer.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, Surgical Planning Laboratory, Harvard University, Boston, MA, USA, version 4.11) for image registration purposes. To select the corresponding slices on the images of the different states of the sample, we registered the images using the Elastix software packages (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://elastix.isi.uu.nl/\u003c/span\u003e\u003cspan address=\"http://elastix.isi.uu.nl/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, University Medical Centre Utrecht and collaborators), which is a collection of parametric intensity-based registration methods. The most basic command to run registration is the no fill group as the \u0026lsquo;fixed\u0026rsquo; image and the filling group as the \u0026lsquo;moving\u0026rsquo; image. This application is used rigid transformations (global translations and rotations). Aligned CBCT images were saved in DICOM format. Then, the DICOM files were imported into the Mimics software (version 21.0, Materialise NV, Leuven, Belgium), and each sample was first separated from the others using the crop tool. The most representative axial slice of the root was selected at 4 mm from the cementoenamel junction (CEJ). Axial slices were transferred to the ImageJ software (National Institutes of Health, Bethesda, MD) in JPEG format for analysis (8-bit).\u003c/p\u003e \u003cp\u003eFor image processing, copy each unfilled dental axis image and convert it into a binary image (0-root canal and background, 255 dentine) by using the threshold tool of ImageJ software. The binarized unfilled and filled tooth images overlapped with the GNU Image processing program (GIMP), then ImageJ software removed the area where the image corresponded to the root canal material, finally obtaining axial images for artifacts quantitative analysis. All CBCT image processing programs are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Artifact analysis\u003c/h2\u003e \u003cp\u003eIn 8-bit images with 256 gray levels, the hypodense and hyperdense artifact areas were determined using the ImageJ thresholding tool. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, hypodense artifacts ranged from 105 to 179, hyperdense artifacts ranged from 238 to 255, and non-affected teeth were between low - and high-density artifacts ranging from 180 to 237. Behind the macro tool selects all slices for the corresponding region, the \u0026ldquo;measure\u0026rdquo; option obtains the result for the ROI (the region of interest). After 30 days, the intra-examiner agreement followed for a repeat assessment.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7. Statistics Analysis\u003c/h2\u003e \u003cp\u003eStatistical analysis used the SPSS Statistics software package (Version 23; IBM Corp., Armonk, NY, USA). Considering data were normally distributed, differences between groups test by analysis of variance (ANOVA) and differences within groups by paired t-test. In addition, intra- examiner agreement calculates using the intraclass correlation coefficient. Significance level set at α\u0026thinsp;=\u0026thinsp;5%.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eThe Intraclass correlation coefficient showed excellent reproducibility with an ICC value of 0.974, 0.842 and 0.975, respectively.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e showed the hyperdense area, hypodense area and non-affected tooth area of the experimental groups. The hyperdense areas of MCSNs were not significantly different from the GP but lower than the other two groups(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), while the hyperdense area of AH Plus was higher than the other groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\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\u003eMean area and standard deviation (SD), minimum and maximum artifacts of the root filling materials measured in CBCT images (\u0026micro;m\u003csup\u003e2\u003c/sup\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArtifacts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSealers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMinimum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e values\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003ehyperdense Area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAH plus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1624.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12463.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6295.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2832\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMCSNs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1976.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6661.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2060.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1816.43\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eiRootSP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e244.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6238.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4022.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1465.85\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4342.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1665.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1402.14\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003ehypodense Area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAH plus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2490.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10873.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5307.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2559.84\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.841\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMCSNs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2757.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10692.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5649.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3197.96\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eiRootSP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2579.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9238.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4644.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1902.65\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2433.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8418.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5307.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2249.97\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003enon-affected Area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAH plus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3591.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16077.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7667.2\u0026thinsp;\u0026plusmn;\u0026thinsp;4028.88\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMCSNs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3106.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26463.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12547\u0026thinsp;\u0026plusmn;\u0026thinsp;6705.02\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eiRootSP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4067.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17340.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9512.4\u0026thinsp;\u0026plusmn;\u0026thinsp;4367.85\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6488.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28400.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15156.3\u0026thinsp;\u0026plusmn;\u0026thinsp;6718.82\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e* Different letters in the same column represent statistically significant results (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\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\u003eComparison of beam hardening artifact area between hyperdense artifact and hypodense artifact.\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=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSealers\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eArtifact\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAH plus\u0026thinsp;+\u0026thinsp;GP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHyperdense Area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e6295.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2832.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.333\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHypodense Area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e5307.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2559.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMCNSs\u0026thinsp;+\u0026thinsp;GP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHyperdense Area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2060.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1816.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHypodense Area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e5649.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3197.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eiRoot SP\u0026thinsp;+\u0026thinsp;GP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHyperdense Area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e4022.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1465.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.326\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHypodense Area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e4644.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1902.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHyperdense Area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1665.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1402.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHypodense Area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e5307.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2249.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThere was no significant difference in the area of the hypodense area between the experimental groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Moreover, there was no significant difference between the non-affected area of MCSNs and GP (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), but the non-affected area of AH Plus and iRoot SP decreased significantly compared with GP (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05)\u003c/p\u003e \u003cp\u003ePaired sample t-test showed that the average value of the hyperdense area of MCSNs and GP was significantly lower than that of the hypodense area (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eCBCT has excellent help in diagnosing, treating and evaluating pulp diseases, but its image quality is often affected by many factors such as artifacts. Studies have shown that differences between the actual physical conditions of the measurement equipment and the simplified mathematical assumptions used for 3D reconstruction lead to artifacts\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. Other factors, such as initial reconstruction, artifact reduction algorithm, projection polychromatic, patient movement, FOV and photon diffraction, all affect the generation of artifacts\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. Clinical artifacts have a stripy appearance due to the substantial absorption of low-energy (lower wavelength) rays in the polychromatic spectrum emitted by X-ray sources as they pass through an object. For example, its internal absorption wavelength acts as a filter with a high density and high atomic number of metal materials.\u003c/p\u003e \u003cp\u003eNanomaterials have unique structures and properties different from other materials and have been increasingly widely used in oral materials, among which nanoparticles are the most prominent\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e .For example, nanoparticles in clinical dental prosthesis composites can promote dentin remineralization and tubule occlusion \u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. In addition, they can be used in combination with sealants, obturating material\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e, intracanal medicament and irrigating solutions\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e for therapeutic use, providing new strategies for treating dental pulp diseases. Previous studies have confirmed that MCSNs have low cytotoxicity and strong antibacterial activity and can induce calcified tissue formation around the apical pore. Meanwhile, the high surface area and porous interior of MCSNs can serve as a reservoir for drug molecules. It can further destroy bacterial biofilm and prevent adhesion to dentin\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn this study, the artifacts of MCSNs in CBCT images were quantitatively compared with AH, iRoot SP and gutta-percha. The results show that the hypodense artifacts of MCSNs are not significantly different from those of other materials (\u003cem\u003eP\u003c/em\u003e༞0.05), suggesting that MCSNs showed the same properties as existing materials in terms of hypodense artifacts, which met the requirements of radiopaque materials for root canal filling. However, When X-rays pass through, low-energy X-ray photons are absorbed, and the remaining high-energy photons are not easy to attenuate, leading to the beam hardening effect. After all, the generation of artifacts is related to the radiopacifiers and other chemicals in the formulations of these sealants, which may lead to different densities. The density of these materials can explain no significant difference between the hypodense artifacts of AH plus and iRoot SP in the experiment, which is different from the previous experimental results\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. Clinically, hypodense artifacts may mimic diseases such as root fissures, or fractures in root fillings, negatively affecting diagnostic accuracy \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn addition, the study showed that the hyperdense artifact area of MCSNs was significantly lower than that of AH plus and iRoot SP (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). While the radiation impermeability of bioceramic sealer is markedly lower than that of AH plus, which is consistent with previous studies \u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. Since this is the first time that artifacts produced by MCSNs have been evaluated, the atomic number of the nanoparticle materials is lower, considering that these filling materials have different atomic compositions. Compared with AH plus (oxygen Z\u0026thinsp;=\u0026thinsp;8, silicon Z\u0026thinsp;=\u0026thinsp;14, calcium Z\u0026thinsp;=\u0026thinsp;20, iron Z\u0026thinsp;=\u0026thinsp;26, zirconium Z\u0026thinsp;=\u0026thinsp;40, tungsten Z\u0026thinsp;=\u0026thinsp;74) and iRoot SP(hydrogen Z\u0026thinsp;=\u0026thinsp;1, oxygen Z\u0026thinsp;=\u0026thinsp;8, silicon Z\u0026thinsp;=\u0026thinsp;14, calcium Z\u0026thinsp;=\u0026thinsp;20, phosphorus Z\u0026thinsp;=\u0026thinsp;15, zirconium Z\u0026thinsp;=\u0026thinsp;40), MSCNs had the lowest atomic numbers (oxygen Z\u0026thinsp;=\u0026thinsp;8, silicon Z\u0026thinsp;=\u0026thinsp;14, calcium Z\u0026thinsp;=\u0026thinsp;20)\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. Studies have confirmed that hyperdense artifacts have a partial volume effect \u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e, which will blur the anatomical morphology of the root canal, hinder the detection of the region of interest, and seriously impair the evaluation of root filling teeth and the visualization of root canals, cracks and tooth fractures. These hyperdense artifacts may negatively affect the accuracy of diagnosis, especially in the clinical diagnosis of vertical root fractures (VRF) and perforation \u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e, which have a poor prognosis. Therefore, we tested the artifact expression of MCSNs and confirmed its obvious advantage in reducing the image density artifact area, which can effectively avoid misdiagnosis. We believe that MCSNs will become an attractive material in root canal therapy in the future.\u003c/p\u003e \u003cp\u003eThere were no significant differences between the AH plus and the iRoot SP groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). However, there were substantial differences in hyperdense and hypodense artifacts area between the MCSNs group and the GP group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), which were similar to previous studies \u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e. Interestingly, the mean area and standard deviation results showed that MSCNs produced significantly fewer artifacts and were the root canal sealant material with the smallest artifact area.\u003c/p\u003e \u003cp\u003eStudies have shown that the different CBCT units \u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e and exposure parameters (such as tube voltage, tube current, FOV and reconstructed voxel) lead to significant differences in the appearance of artifacts \u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e. In this study, we used the same CBCT units and exposure parameters to eliminate the possible influence of these different structures on gray value and area assessment. In addition, although MCSNs are not yet clinically available, given the increasing use of CBCT in current dental practice, we believe that our results on the artifacts properties of this material will contribute to significant improvements in dental nanomaterials.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eMSCNs have the same performance as AH plus and iRoot SP in displaying hypodense artifacts but significantly reducing the generation of hyperdense artifacts, indicating that they can be used as a new and promising root canal sealer and have a minor adverse effect on evaluating the quality of root canal filling and diagnosing root canal diseases in CBCT images.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe work was supported by A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (2018-87) and the Scientific Research Project of Health Care for Cadres of Jiangsu Province (BJ21034).\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Competing Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTingting Zhu: Conceptualization, Methodology,\u0026nbsp;Software, Writing - Original Draft.\u0026nbsp;Cheng Chen:\u0026nbsp;Software, Validation.\u0026nbsp;Huili Wu:\u0026nbsp;Data Curation.\u0026nbsp;Xiao Zhao:\u0026nbsp;Resources. Diya Leng:\u0026nbsp;Supervision. Daming Wu:\u0026nbsp;Writing - Review \u0026amp; Editing, Funding acquisition.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe work was supported by A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (2018-87) and the Scientific Research Project of Health Care for Cadres of Jiangsu Province (BJ21034).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompliance with Ethical Standards\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of our university (PJ2021-123-001)\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003e\u003cspan\u003eGinat D. T. and Gupta R. (2014). Advances in computed tomography imaging technology.Annu Rev Biomed Eng 16: 431 \u0026ndash; 53.10.1146/annurev-bioeng-121813-113601\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eMacDonald D. 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Influence of voxel size and scan field of view on fracture-like artifacts from gutta-percha obturated endodontically treated teeth on cone-beam computed tomography images.Oral Surg Oral Med Oral Pathol Oral Radiol 122: 631-637.10.1016/j.oooo.2016.07.014\u003c/span\u003e\u003c/li\u003e\n\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":"artifacts, cone-beam computed tomography, mesoporous calcium-silicate nanoparticles, root canal sealer","lastPublishedDoi":"10.21203/rs.3.rs-1749437/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1749437/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eObjectives:\u003c/em\u003e\u003c/strong\u003e To quantitatively evaluate the artifact area of the image of mesoporous calcium silicate nanoparticles (MCSNs) using cone-beam computed tomography (CBCT).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e\u003cem\u003eMethods:\u003c/em\u003e\u003c/strong\u003e Forty single-rooted mandibular premolars were selected and prepared with NiTi rotary instruments to 35/0.04, and divided into four groups (n=10): (I) AH Plus sealer; (II) MCSNs sealer; (III) iRoot SP sealer and (IV) no sealer. There were filled with a single cone (35/0.04 taper) method. The roots were scanned using a CBCT with the same parameters before and after filling. The images were evaluated using ImageJ’s threshold tool to quantitatively determine the hyperdense and hypodense artifacts, and non-affected teeth areas within 8-bit images extracted from the scans.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e\u003cem\u003eResults:\u003c/em\u003e\u003c/strong\u003e MCSNs showed fewer hyperdense artifacts than AH plus and iRoot SP (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01), while the hypodense artifacts were not statistically significant among groups (\u003cem\u003eP\u003c/em\u003e \u0026gt; 0.05).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConclusion:\u003c/em\u003e\u003c/strong\u003e MSCNs can effectively reduce the generation of hyperdense artifacts in CBCT images and show better image qualities, indicating that they have a minor adverse effect on evaluating the quality of root canal filling and diagnosing root canal diseases in CBCT images.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e\u003cem\u003eClinical Relevance:\u003c/em\u003e\u003c/strong\u003e As a novel type of root canal filling nanomaterials, MSCNs have less artifact expression and higher quality in CBCT images. Therefore, this new root filling material is expected to play a positive role in improving the correct clinical evaluation of root canal filling teeth and the visualization of root canal cracks and fractures.\u003c/p\u003e","manuscriptTitle":"Quantitative evaluation of artifact expression of mesoporous calcium silicate nanoparticles as a new promising root canal sealer in cone-beam computed tomography","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-06-27 20:59:12","doi":"10.21203/rs.3.rs-1749437/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":"c3ee660b-d310-485c-bae9-0b4eb1fd00ac","owner":[],"postedDate":"June 27th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2022-11-30T01:14:14+00:00","versionOfRecord":[],"versionCreatedAt":"2022-06-27 20:59:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1749437","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1749437","identity":"rs-1749437","version":["v1"]},"buildId":"FbvkV6FR0MCFSLy54lSbu","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}