Comparative Evaluation of Artifacts Originated by Four Different Post Materials Using Different CBCT Settings Article Swipe
Dilek Helvacıoğlu-Yiğit
,
Umut Seki
,
Sebnem Kursun-Cakmak
,
Hüsniye Demirtürk Kocasaraç
,
Maharaj Singh
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3390/tomography8060245
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3390/tomography8060245
The aim of this study was to evaluate whether cone beam computed tomography (CBCT) images in the presence of four different post materials, obtained from different kVps with varying resolutions and varying metal artifact reduction (MAR) algorithms, differed in artifact estimation, and to compare tooth regions in terms of artifact value. Materials and Methods: Forty premolar teeth were used in this study. Root canals were treated, and teeth were randomly distributed into four subgroups (n = 10) for the preparation of post materials: titanium, gold (Nordin), quartz fiber (Bisco DT Light), and glass fiber (Rely X). The CBCT images were taken with two different kVps, three different metal artifact reduction (MAR) algorithm options, and two different resolutions. For each protocol, the effective dose was calculated according to the dose area production (DAP) value. The standard analysis of variance technique and the Tukey multiple comparison adjustment method were used to assess interactions among material types, kVp, MAR, and voxel settings. Results: More artifacts were found in the middle third than in the cervical third (p < 0.05). The mean value of artifacts was highest for gold (Nordin), 90 kVp, no MAR, and 100 voxel size. Glass or quartz fiber posts at low resolution, with high MAR and 96 kVp, originated fewer artifacts. Moreover, the use of 90 and 96 kVp with 200 voxel size and high MAR provided the least amount of radiation. Conclusion: The best setting for radiographic follow-up of post materials on the Planmeca ProMax is 96 kVp with low resolution and high MAR; this setting produced one of the lowest effective doses. Clinical Significance: This study estimated the best scanning protocol by lowering the effective dose to a minimum level according to the “as low as reasonably achievable” principle, as well as assessing the tooth region and the post material generating the fewest artifacts, in order to prevent image interpretation challenges such as false-positive and false-negative results stemming from the deterioration of the visibility of the root canal due to perforation, fractures, and voids in the root canal region.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/tomography8060245
- https://www.mdpi.com/2379-139X/8/6/245/pdf?version=1670920449
- OA Status
- gold
- Cited By
- 4
- References
- 27
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4311236639
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4311236639Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/tomography8060245Digital Object Identifier
- Title
-
Comparative Evaluation of Artifacts Originated by Four Different Post Materials Using Different CBCT SettingsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-12-13Full publication date if available
- Authors
-
Dilek Helvacıoğlu-Yiğit, Umut Seki, Sebnem Kursun-Cakmak, Hüsniye Demirtürk Kocasaraç, Maharaj SinghList of authors in order
- Landing page
-
https://doi.org/10.3390/tomography8060245Publisher landing page
- PDF URL
-
https://www.mdpi.com/2379-139X/8/6/245/pdf?version=1670920449Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2379-139X/8/6/245/pdf?version=1670920449Direct OA link when available
- Concepts
-
Artifact (error), Voxel, Cone beam computed tomography, Premolar, Nuclear medicine, Materials science, Medicine, Dentistry, Biomedical engineering, Computed tomography, Molar, Computer science, Radiology, Artificial intelligenceTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
4Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 2, 2024: 1, 2023: 1Per-year citation counts (last 5 years)
- References (count)
-
27Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4311236639 |
|---|---|
| doi | https://doi.org/10.3390/tomography8060245 |
| ids.doi | https://doi.org/10.3390/tomography8060245 |
| ids.pmid | https://pubmed.ncbi.nlm.nih.gov/36548537 |
| ids.openalex | https://openalex.org/W4311236639 |
| fwci | 1.11056173 |
| mesh[0].qualifier_ui | |
| mesh[0].descriptor_ui | D016477 |
| mesh[0].is_major_topic | True |
| mesh[0].qualifier_name | |
| mesh[0].descriptor_name | Artifacts |
| mesh[1].qualifier_ui | |
| mesh[1].descriptor_ui | D011791 |
| mesh[1].is_major_topic | False |
| mesh[1].qualifier_name | |
| mesh[1].descriptor_name | Quartz |
| mesh[2].qualifier_ui | |
| mesh[2].descriptor_ui | D054894 |
| mesh[2].is_major_topic | True |
| mesh[2].qualifier_name | |
| mesh[2].descriptor_name | Spiral Cone-Beam Computed Tomography |
| mesh[3].qualifier_ui | Q000379 |
| mesh[3].descriptor_ui | D054893 |
| mesh[3].is_major_topic | False |
| mesh[3].qualifier_name | methods |
| mesh[3].descriptor_name | Cone-Beam Computed Tomography |
| mesh[4].qualifier_ui | |
| mesh[4].descriptor_ui | D006046 |
| mesh[4].is_major_topic | False |
| mesh[4].qualifier_name | |
| mesh[4].descriptor_name | Gold |
| mesh[5].qualifier_ui | |
| mesh[5].descriptor_ui | D016477 |
| mesh[5].is_major_topic | True |
| mesh[5].qualifier_name | |
| mesh[5].descriptor_name | Artifacts |
| mesh[6].qualifier_ui | |
| mesh[6].descriptor_ui | D011791 |
| mesh[6].is_major_topic | False |
| mesh[6].qualifier_name | |
| mesh[6].descriptor_name | Quartz |
| mesh[7].qualifier_ui | |
| mesh[7].descriptor_ui | D054894 |
| mesh[7].is_major_topic | True |
| mesh[7].qualifier_name | |
| mesh[7].descriptor_name | Spiral Cone-Beam Computed Tomography |
| mesh[8].qualifier_ui | Q000379 |
| mesh[8].descriptor_ui | D054893 |
| mesh[8].is_major_topic | False |
| mesh[8].qualifier_name | methods |
| mesh[8].descriptor_name | Cone-Beam Computed Tomography |
| mesh[9].qualifier_ui | |
| mesh[9].descriptor_ui | D006046 |
| mesh[9].is_major_topic | False |
| mesh[9].qualifier_name | |
| mesh[9].descriptor_name | Gold |
| type | article |
| title | Comparative Evaluation of Artifacts Originated by Four Different Post Materials Using Different CBCT Settings |
| biblio.issue | 6 |
| biblio.volume | 8 |
| biblio.last_page | 2928 |
| biblio.first_page | 2919 |
| topics[0].id | https://openalex.org/T11363 |
| topics[0].field.id | https://openalex.org/fields/35 |
| topics[0].field.display_name | Dentistry |
| topics[0].score | 0.9998999834060669 |
| topics[0].domain.id | https://openalex.org/domains/4 |
| topics[0].domain.display_name | Health Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/3504 |
| topics[0].subfield.display_name | Oral Surgery |
| topics[0].display_name | Dental Radiography and Imaging |
| topics[1].id | https://openalex.org/T12386 |
| topics[1].field.id | https://openalex.org/fields/22 |
| topics[1].field.display_name | Engineering |
| topics[1].score | 0.9973999857902527 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2204 |
| topics[1].subfield.display_name | Biomedical Engineering |
| topics[1].display_name | Advanced X-ray and CT Imaging |
| topics[2].id | https://openalex.org/T10536 |
| topics[2].field.id | https://openalex.org/fields/35 |
| topics[2].field.display_name | Dentistry |
| topics[2].score | 0.9890000224113464 |
| topics[2].domain.id | https://openalex.org/domains/4 |
| topics[2].domain.display_name | Health Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/3504 |
| topics[2].subfield.display_name | Oral Surgery |
| topics[2].display_name | Endodontics and Root Canal Treatments |
| is_xpac | False |
| apc_list.value | 1800 |
| apc_list.currency | CHF |
| apc_list.value_usd | 1949 |
| apc_paid.value | 1800 |
| apc_paid.currency | CHF |
| apc_paid.value_usd | 1949 |
| concepts[0].id | https://openalex.org/C2779010991 |
| concepts[0].level | 2 |
| concepts[0].score | 0.6370863318443298 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q2720909 |
| concepts[0].display_name | Artifact (error) |
| concepts[1].id | https://openalex.org/C54170458 |
| concepts[1].level | 2 |
| concepts[1].score | 0.5722211599349976 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q663554 |
| concepts[1].display_name | Voxel |
| concepts[2].id | https://openalex.org/C2779813781 |
| concepts[2].level | 3 |
| concepts[2].score | 0.5208892822265625 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q1224951 |
| concepts[2].display_name | Cone beam computed tomography |
| concepts[3].id | https://openalex.org/C2780641865 |
| concepts[3].level | 3 |
| concepts[3].score | 0.4798238277435303 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q839483 |
| concepts[3].display_name | Premolar |
| concepts[4].id | https://openalex.org/C2989005 |
| concepts[4].level | 1 |
| concepts[4].score | 0.4572477340698242 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q214963 |
| concepts[4].display_name | Nuclear medicine |
| concepts[5].id | https://openalex.org/C192562407 |
| concepts[5].level | 0 |
| concepts[5].score | 0.45258980989456177 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q228736 |
| concepts[5].display_name | Materials science |
| concepts[6].id | https://openalex.org/C71924100 |
| concepts[6].level | 0 |
| concepts[6].score | 0.3684017062187195 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q11190 |
| concepts[6].display_name | Medicine |
| concepts[7].id | https://openalex.org/C199343813 |
| concepts[7].level | 1 |
| concepts[7].score | 0.34804072976112366 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q12128 |
| concepts[7].display_name | Dentistry |
| concepts[8].id | https://openalex.org/C136229726 |
| concepts[8].level | 1 |
| concepts[8].score | 0.32460182905197144 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q327092 |
| concepts[8].display_name | Biomedical engineering |
| concepts[9].id | https://openalex.org/C544519230 |
| concepts[9].level | 2 |
| concepts[9].score | 0.21292787790298462 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q32566 |
| concepts[9].display_name | Computed tomography |
| concepts[10].id | https://openalex.org/C202271784 |
| concepts[10].level | 2 |
| concepts[10].score | 0.19697564840316772 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q189218 |
| concepts[10].display_name | Molar |
| concepts[11].id | https://openalex.org/C41008148 |
| concepts[11].level | 0 |
| concepts[11].score | 0.1880190670490265 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[11].display_name | Computer science |
| concepts[12].id | https://openalex.org/C126838900 |
| concepts[12].level | 1 |
| concepts[12].score | 0.17864879965782166 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q77604 |
| concepts[12].display_name | Radiology |
| concepts[13].id | https://openalex.org/C154945302 |
| concepts[13].level | 1 |
| concepts[13].score | 0.17168375849723816 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[13].display_name | Artificial intelligence |
| keywords[0].id | https://openalex.org/keywords/artifact |
| keywords[0].score | 0.6370863318443298 |
| keywords[0].display_name | Artifact (error) |
| keywords[1].id | https://openalex.org/keywords/voxel |
| keywords[1].score | 0.5722211599349976 |
| keywords[1].display_name | Voxel |
| keywords[2].id | https://openalex.org/keywords/cone-beam-computed-tomography |
| keywords[2].score | 0.5208892822265625 |
| keywords[2].display_name | Cone beam computed tomography |
| keywords[3].id | https://openalex.org/keywords/premolar |
| keywords[3].score | 0.4798238277435303 |
| keywords[3].display_name | Premolar |
| keywords[4].id | https://openalex.org/keywords/nuclear-medicine |
| keywords[4].score | 0.4572477340698242 |
| keywords[4].display_name | Nuclear medicine |
| keywords[5].id | https://openalex.org/keywords/materials-science |
| keywords[5].score | 0.45258980989456177 |
| keywords[5].display_name | Materials science |
| keywords[6].id | https://openalex.org/keywords/medicine |
| keywords[6].score | 0.3684017062187195 |
| keywords[6].display_name | Medicine |
| keywords[7].id | https://openalex.org/keywords/dentistry |
| keywords[7].score | 0.34804072976112366 |
| keywords[7].display_name | Dentistry |
| keywords[8].id | https://openalex.org/keywords/biomedical-engineering |
| keywords[8].score | 0.32460182905197144 |
| keywords[8].display_name | Biomedical engineering |
| keywords[9].id | https://openalex.org/keywords/computed-tomography |
| keywords[9].score | 0.21292787790298462 |
| keywords[9].display_name | Computed tomography |
| keywords[10].id | https://openalex.org/keywords/molar |
| keywords[10].score | 0.19697564840316772 |
| keywords[10].display_name | Molar |
| keywords[11].id | https://openalex.org/keywords/computer-science |
| keywords[11].score | 0.1880190670490265 |
| keywords[11].display_name | Computer science |
| keywords[12].id | https://openalex.org/keywords/radiology |
| keywords[12].score | 0.17864879965782166 |
| keywords[12].display_name | Radiology |
| keywords[13].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[13].score | 0.17168375849723816 |
| keywords[13].display_name | Artificial intelligence |
| language | en |
| locations[0].id | doi:10.3390/tomography8060245 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4210172093 |
| locations[0].source.issn | 2379-1381, 2379-139X |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 2379-1381 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Tomography |
| locations[0].source.host_organization | |
| locations[0].source.host_organization_name | |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://www.mdpi.com/2379-139X/8/6/245/pdf?version=1670920449 |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Tomography |
| locations[0].landing_page_url | https://doi.org/10.3390/tomography8060245 |
| locations[1].id | pmid:36548537 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306525036 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | PubMed |
| locations[1].source.host_organization | https://openalex.org/I1299303238 |
| locations[1].source.host_organization_name | National Institutes of Health |
| locations[1].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | publishedVersion |
| locations[1].raw_type | |
| locations[1].license_id | |
| locations[1].is_accepted | True |
| locations[1].is_published | True |
| locations[1].raw_source_name | Tomography (Ann Arbor, Mich.) |
| locations[1].landing_page_url | https://pubmed.ncbi.nlm.nih.gov/36548537 |
| locations[2].id | pmh:oai:doaj.org/article:5bea585a61444adeb2c62d775564e5a0 |
| locations[2].is_oa | True |
| locations[2].source.id | https://openalex.org/S4306401280 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | False |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[2].source.host_organization | |
| locations[2].source.host_organization_name | |
| locations[2].license | cc-by-sa |
| locations[2].pdf_url | |
| locations[2].version | submittedVersion |
| locations[2].raw_type | article |
| locations[2].license_id | https://openalex.org/licenses/cc-by-sa |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | Tomography, Vol 8, Iss 6, Pp 2919-2928 (2022) |
| locations[2].landing_page_url | https://doaj.org/article/5bea585a61444adeb2c62d775564e5a0 |
| locations[3].id | pmh:oai:pubmedcentral.nih.gov:9781935 |
| locations[3].is_oa | True |
| locations[3].source.id | https://openalex.org/S2764455111 |
| locations[3].source.issn | |
| locations[3].source.type | repository |
| locations[3].source.is_oa | False |
| locations[3].source.issn_l | |
| locations[3].source.is_core | False |
| locations[3].source.is_in_doaj | False |
| locations[3].source.display_name | PubMed Central |
| locations[3].source.host_organization | https://openalex.org/I1299303238 |
| locations[3].source.host_organization_name | National Institutes of Health |
| locations[3].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[3].license | other-oa |
| locations[3].pdf_url | |
| locations[3].version | submittedVersion |
| locations[3].raw_type | Text |
| locations[3].license_id | https://openalex.org/licenses/other-oa |
| locations[3].is_accepted | False |
| locations[3].is_published | False |
| locations[3].raw_source_name | Tomography |
| locations[3].landing_page_url | https://www.ncbi.nlm.nih.gov/pmc/articles/9781935 |
| locations[4].id | pmh:oai:qspace.qu.edu.qa:10576/37567 |
| locations[4].is_oa | False |
| locations[4].source.id | https://openalex.org/S4306400014 |
| locations[4].source.issn | |
| locations[4].source.type | repository |
| locations[4].source.is_oa | False |
| locations[4].source.issn_l | |
| locations[4].source.is_core | False |
| locations[4].source.is_in_doaj | False |
| locations[4].source.display_name | Qatar University QSpace (Qatar University) |
| locations[4].source.host_organization | https://openalex.org/I60342839 |
| locations[4].source.host_organization_name | Qatar University |
| locations[4].source.host_organization_lineage | https://openalex.org/I60342839 |
| locations[4].license | |
| locations[4].pdf_url | |
| locations[4].version | submittedVersion |
| locations[4].raw_type | Article |
| locations[4].license_id | |
| locations[4].is_accepted | False |
| locations[4].is_published | False |
| locations[4].raw_source_name | |
| locations[4].landing_page_url | http://hdl.handle.net/10576/37567 |
| indexed_in | crossref, doaj, pubmed |
| authorships[0].author.id | https://openalex.org/A5000944427 |
| authorships[0].author.orcid | https://orcid.org/0000-0001-5999-9726 |
| authorships[0].author.display_name | Dilek Helvacıoğlu-Yiğit |
| authorships[0].countries | QA |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I60342839 |
| authorships[0].affiliations[0].raw_affiliation_string | College of Dental Medicine, QU Health, Qatar University, Doha 2713, Qatar |
| authorships[0].institutions[0].id | https://openalex.org/I60342839 |
| authorships[0].institutions[0].ror | https://ror.org/00yhnba62 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I60342839 |
| authorships[0].institutions[0].country_code | QA |
| authorships[0].institutions[0].display_name | Qatar University |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Dilek Helvacioglu-Yigit |
| authorships[0].is_corresponding | True |
| authorships[0].raw_affiliation_strings | College of Dental Medicine, QU Health, Qatar University, Doha 2713, Qatar |
| authorships[1].author.id | https://openalex.org/A5085988748 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-0286-9792 |
| authorships[1].author.display_name | Umut Seki |
| authorships[1].countries | TR |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I51826884 |
| authorships[1].affiliations[0].raw_affiliation_string | Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Kocaeli University, Kocaeli 41190, Turkey |
| authorships[1].institutions[0].id | https://openalex.org/I51826884 |
| authorships[1].institutions[0].ror | https://ror.org/0411seq30 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I51826884 |
| authorships[1].institutions[0].country_code | TR |
| authorships[1].institutions[0].display_name | Kocaeli Üniversitesi |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Umut Seki |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Kocaeli University, Kocaeli 41190, Turkey |
| authorships[2].author.id | https://openalex.org/A5062576960 |
| authorships[2].author.orcid | |
| authorships[2].author.display_name | Sebnem Kursun-Cakmak |
| authorships[2].countries | TR |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I4210150808 |
| authorships[2].affiliations[0].raw_affiliation_string | Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Ankara Yıldırım Beyazıt University, Ankara 1487, Turkey |
| authorships[2].institutions[0].id | https://openalex.org/I4210150808 |
| authorships[2].institutions[0].ror | https://ror.org/05ryemn72 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I4210150808 |
| authorships[2].institutions[0].country_code | TR |
| authorships[2].institutions[0].display_name | Ankara Yıldırım Beyazıt University |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Sebnem Kursun-Cakmak |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Ankara Yıldırım Beyazıt University, Ankara 1487, Turkey |
| authorships[3].author.id | https://openalex.org/A5009812818 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-4808-0949 |
| authorships[3].author.display_name | Hüsniye Demirtürk Kocasaraç |
| authorships[3].countries | TR |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I4387155008, https://openalex.org/I51826884 |
| authorships[3].affiliations[0].raw_affiliation_string | Department of Dentomaxillofacial Radiology, Kocaeli Health and Technology University, Kocaeli 41000, Turkey |
| authorships[3].affiliations[1].raw_affiliation_string | BeamReaders Inc., Kennewick, WA 99336, USA |
| authorships[3].institutions[0].id | https://openalex.org/I4387155008 |
| authorships[3].institutions[0].ror | https://ror.org/016dcc221 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I4387155008 |
| authorships[3].institutions[0].country_code | |
| authorships[3].institutions[0].display_name | Kocaeli Sağlık ve Teknoloji Üniversitesi |
| authorships[3].institutions[1].id | https://openalex.org/I51826884 |
| authorships[3].institutions[1].ror | https://ror.org/0411seq30 |
| authorships[3].institutions[1].type | education |
| authorships[3].institutions[1].lineage | https://openalex.org/I51826884 |
| authorships[3].institutions[1].country_code | TR |
| authorships[3].institutions[1].display_name | Kocaeli Üniversitesi |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Husniye Demirturk Kocasarac |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | BeamReaders Inc., Kennewick, WA 99336, USA, Department of Dentomaxillofacial Radiology, Kocaeli Health and Technology University, Kocaeli 41000, Turkey |
| authorships[4].author.id | https://openalex.org/A5047199449 |
| authorships[4].author.orcid | https://orcid.org/0000-0001-7736-1291 |
| authorships[4].author.display_name | Maharaj Singh |
| authorships[4].countries | US |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I102461120 |
| authorships[4].affiliations[0].raw_affiliation_string | College of Nursing, Marquette University, Milwaukee, WI 53233, USA |
| authorships[4].institutions[0].id | https://openalex.org/I102461120 |
| authorships[4].institutions[0].ror | https://ror.org/04gr4te78 |
| authorships[4].institutions[0].type | education |
| authorships[4].institutions[0].lineage | https://openalex.org/I102461120 |
| authorships[4].institutions[0].country_code | US |
| authorships[4].institutions[0].display_name | Marquette University |
| authorships[4].author_position | last |
| authorships[4].raw_author_name | Maharaj Singh |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | College of Nursing, Marquette University, Milwaukee, WI 53233, USA |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://www.mdpi.com/2379-139X/8/6/245/pdf?version=1670920449 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Comparative Evaluation of Artifacts Originated by Four Different Post Materials Using Different CBCT Settings |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T11363 |
| primary_topic.field.id | https://openalex.org/fields/35 |
| primary_topic.field.display_name | Dentistry |
| primary_topic.score | 0.9998999834060669 |
| primary_topic.domain.id | https://openalex.org/domains/4 |
| primary_topic.domain.display_name | Health Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/3504 |
| primary_topic.subfield.display_name | Oral Surgery |
| primary_topic.display_name | Dental Radiography and Imaging |
| related_works | https://openalex.org/W52840052, https://openalex.org/W3027020613, https://openalex.org/W2016533837, https://openalex.org/W1741504538, https://openalex.org/W1687852313, https://openalex.org/W3167885074, https://openalex.org/W3029243869, https://openalex.org/W2019696434, https://openalex.org/W2502336004, https://openalex.org/W3162837891 |
| cited_by_count | 4 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 2 |
| counts_by_year[1].year | 2024 |
| counts_by_year[1].cited_by_count | 1 |
| counts_by_year[2].year | 2023 |
| counts_by_year[2].cited_by_count | 1 |
| locations_count | 5 |
| best_oa_location.id | doi:10.3390/tomography8060245 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4210172093 |
| best_oa_location.source.issn | 2379-1381, 2379-139X |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 2379-1381 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Tomography |
| best_oa_location.source.host_organization | |
| best_oa_location.source.host_organization_name | |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://www.mdpi.com/2379-139X/8/6/245/pdf?version=1670920449 |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Tomography |
| best_oa_location.landing_page_url | https://doi.org/10.3390/tomography8060245 |
| primary_location.id | doi:10.3390/tomography8060245 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4210172093 |
| primary_location.source.issn | 2379-1381, 2379-139X |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 2379-1381 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Tomography |
| primary_location.source.host_organization | |
| primary_location.source.host_organization_name | |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://www.mdpi.com/2379-139X/8/6/245/pdf?version=1670920449 |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Tomography |
| primary_location.landing_page_url | https://doi.org/10.3390/tomography8060245 |
| publication_date | 2022-12-13 |
| publication_year | 2022 |
| referenced_works | https://openalex.org/W2166018620, https://openalex.org/W1998361352, https://openalex.org/W2178094143, https://openalex.org/W2198254608, https://openalex.org/W2064128230, https://openalex.org/W2136883723, https://openalex.org/W2483568104, https://openalex.org/W2998474419, https://openalex.org/W3009405065, https://openalex.org/W2004502579, https://openalex.org/W2108647886, https://openalex.org/W2150517181, https://openalex.org/W2079661986, https://openalex.org/W3025013394, https://openalex.org/W2218314993, https://openalex.org/W2886938176, https://openalex.org/W1971769932, https://openalex.org/W2333608617, https://openalex.org/W3136397203, https://openalex.org/W3080406221, https://openalex.org/W2946590320, https://openalex.org/W2194599627, https://openalex.org/W1811751235, https://openalex.org/W2082304659, https://openalex.org/W2770015277, https://openalex.org/W3048010858, https://openalex.org/W2343353927 |
| referenced_works_count | 27 |
| abstract_inverted_index.= | 75 |
| abstract_inverted_index.a | 279 |
| abstract_inverted_index.(n | 74 |
| abstract_inverted_index.(p | 173 |
| abstract_inverted_index.90 | 186, 215 |
| abstract_inverted_index.96 | 206, 217, 247 |
| abstract_inverted_index.DT | 89 |
| abstract_inverted_index.as | 287, 291, 293, 314 |
| abstract_inverted_index.at | 199 |
| abstract_inverted_index.by | 273 |
| abstract_inverted_index.in | 15, 38, 46, 59, 164, 169, 306, 336 |
| abstract_inverted_index.is | 246 |
| abstract_inverted_index.no | 188 |
| abstract_inverted_index.of | 2, 18, 48, 80, 136, 179, 214, 230, 239, 259, 323, 326 |
| abstract_inverted_index.on | 242 |
| abstract_inverted_index.or | 195 |
| abstract_inverted_index.to | 6, 42, 126, 148, 278, 283, 308, 331 |
| abstract_inverted_index.10) | 76 |
| abstract_inverted_index.100 | 191 |
| abstract_inverted_index.200 | 220 |
| abstract_inverted_index.For | 117 |
| abstract_inverted_index.MAR | 204, 225 |
| abstract_inverted_index.The | 0, 96, 133, 176, 233 |
| abstract_inverted_index.X). | 95 |
| abstract_inverted_index.aim | 1 |
| abstract_inverted_index.and | 30, 41, 52, 66, 91, 113, 139, 156, 190, 205, 216, 223, 252, 298, 316, 334 |
| abstract_inverted_index.due | 330 |
| abstract_inverted_index.for | 77, 183, 236 |
| abstract_inverted_index.kVp | 218, 248 |
| abstract_inverted_index.low | 200, 250, 286 |
| abstract_inverted_index.one | 258 |
| abstract_inverted_index.the | 16, 78, 120, 127, 140, 165, 170, 212, 227, 243, 260, 269, 275, 284, 295, 299, 303, 321, 324, 327, 337 |
| abstract_inverted_index.two | 102, 114 |
| abstract_inverted_index.use | 213 |
| abstract_inverted_index.was | 5, 123, 181 |
| abstract_inverted_index.< | 174 |
| abstract_inverted_index.CBCT | 97 |
| abstract_inverted_index.MAR, | 155, 189 |
| abstract_inverted_index.MAR; | 254 |
| abstract_inverted_index.More | 160 |
| abstract_inverted_index.Root | 62 |
| abstract_inverted_index.This | 266 |
| abstract_inverted_index.area | 129 |
| abstract_inverted_index.beam | 10 |
| abstract_inverted_index.best | 234, 270 |
| abstract_inverted_index.cone | 9 |
| abstract_inverted_index.dose | 122, 128, 277 |
| abstract_inverted_index.each | 118 |
| abstract_inverted_index.four | 19, 72 |
| abstract_inverted_index.from | 24, 320 |
| abstract_inverted_index.gold | 84, 184 |
| abstract_inverted_index.high | 203, 224, 253 |
| abstract_inverted_index.into | 71 |
| abstract_inverted_index.kVp, | 154, 187, 207 |
| abstract_inverted_index.kVps | 26 |
| abstract_inverted_index.mean | 177 |
| abstract_inverted_index.post | 21, 81, 240, 300 |
| abstract_inverted_index.root | 328, 338 |
| abstract_inverted_index.size | 222 |
| abstract_inverted_index.such | 313 |
| abstract_inverted_index.than | 168 |
| abstract_inverted_index.this | 3, 60, 255 |
| abstract_inverted_index.used | 58, 147 |
| abstract_inverted_index.well | 292 |
| abstract_inverted_index.were | 57, 64, 68, 99, 146, 162 |
| abstract_inverted_index.with | 27, 101, 202, 219, 249 |
| abstract_inverted_index.(DAP) | 131 |
| abstract_inverted_index.(MAR) | 35, 110 |
| abstract_inverted_index.(Rely | 94 |
| abstract_inverted_index.Forty | 54 |
| abstract_inverted_index.Glass | 194 |
| abstract_inverted_index.Tukey | 141 |
| abstract_inverted_index.among | 151 |
| abstract_inverted_index.canal | 329, 339 |
| abstract_inverted_index.fewer | 209 |
| abstract_inverted_index.fiber | 87, 93, 197 |
| abstract_inverted_index.found | 163 |
| abstract_inverted_index.glass | 92 |
| abstract_inverted_index.image | 310 |
| abstract_inverted_index.kVps, | 104 |
| abstract_inverted_index.least | 228 |
| abstract_inverted_index.level | 281 |
| abstract_inverted_index.metal | 32, 107 |
| abstract_inverted_index.order | 307 |
| abstract_inverted_index.posts | 198 |
| abstract_inverted_index.size. | 193 |
| abstract_inverted_index.study | 4, 267 |
| abstract_inverted_index.taken | 100 |
| abstract_inverted_index.teeth | 56, 67 |
| abstract_inverted_index.terms | 47 |
| abstract_inverted_index.third | 167, 172 |
| abstract_inverted_index.three | 105 |
| abstract_inverted_index.tooth | 44, 296 |
| abstract_inverted_index.value | 178 |
| abstract_inverted_index.voids | 335 |
| abstract_inverted_index.voxel | 157, 192, 221 |
| abstract_inverted_index.“as | 285 |
| abstract_inverted_index.(Bisco | 88 |
| abstract_inverted_index.(CBCT) | 13 |
| abstract_inverted_index.0.05). | 175 |
| abstract_inverted_index.ProMax | 245 |
| abstract_inverted_index.amount | 229 |
| abstract_inverted_index.assess | 149 |
| abstract_inverted_index.canals | 63 |
| abstract_inverted_index.doses. | 263 |
| abstract_inverted_index.fewest | 304 |
| abstract_inverted_index.images | 14, 98 |
| abstract_inverted_index.lowest | 261 |
| abstract_inverted_index.method | 145 |
| abstract_inverted_index.middle | 166 |
| abstract_inverted_index.quartz | 86, 196 |
| abstract_inverted_index.region | 297 |
| abstract_inverted_index.study. | 61 |
| abstract_inverted_index.types, | 153 |
| abstract_inverted_index.value. | 50, 132 |
| abstract_inverted_index.Light), | 90 |
| abstract_inverted_index.compare | 43 |
| abstract_inverted_index.highest | 182 |
| abstract_inverted_index.minimum | 280 |
| abstract_inverted_index.prevent | 309 |
| abstract_inverted_index.region. | 340 |
| abstract_inverted_index.regions | 45 |
| abstract_inverted_index.results | 318 |
| abstract_inverted_index.setting | 235, 256 |
| abstract_inverted_index.varying | 28, 31 |
| abstract_inverted_index.whether | 8 |
| abstract_inverted_index.Clinical | 264 |
| abstract_inverted_index.Methods: | 53 |
| abstract_inverted_index.Planmeca | 244 |
| abstract_inverted_index.Results: | 159 |
| abstract_inverted_index.analysis | 135 |
| abstract_inverted_index.artifact | 33, 39, 49, 108 |
| abstract_inverted_index.cervical | 171 |
| abstract_inverted_index.computed | 11 |
| abstract_inverted_index.differed | 37 |
| abstract_inverted_index.evaluate | 7 |
| abstract_inverted_index.lowering | 274 |
| abstract_inverted_index.material | 152, 301 |
| abstract_inverted_index.multiple | 142 |
| abstract_inverted_index.obtained | 23 |
| abstract_inverted_index.options, | 112 |
| abstract_inverted_index.premolar | 55 |
| abstract_inverted_index.presence | 17 |
| abstract_inverted_index.produced | 257 |
| abstract_inverted_index.protocol | 272 |
| abstract_inverted_index.provided | 226 |
| abstract_inverted_index.randomly | 69 |
| abstract_inverted_index.scanning | 271 |
| abstract_inverted_index.standard | 134 |
| abstract_inverted_index.stemming | 319 |
| abstract_inverted_index.treated, | 65 |
| abstract_inverted_index.variance | 137 |
| abstract_inverted_index.(Nordin), | 85, 185 |
| abstract_inverted_index.Materials | 51 |
| abstract_inverted_index.Moreover, | 211 |
| abstract_inverted_index.according | 125, 282 |
| abstract_inverted_index.algorithm | 111 |
| abstract_inverted_index.artifacts | 161, 180 |
| abstract_inverted_index.assessing | 294 |
| abstract_inverted_index.different | 20, 25, 103, 106, 115 |
| abstract_inverted_index.effective | 121, 262, 276 |
| abstract_inverted_index.estimated | 268 |
| abstract_inverted_index.follow-up | 238 |
| abstract_inverted_index.materials | 241 |
| abstract_inverted_index.protocol, | 119 |
| abstract_inverted_index.reduction | 34, 109 |
| abstract_inverted_index.settings. | 158 |
| abstract_inverted_index.subgroups | 73 |
| abstract_inverted_index.technique | 138 |
| abstract_inverted_index.titanium, | 83 |
| abstract_inverted_index.adjustment | 144 |
| abstract_inverted_index.artifacts, | 305 |
| abstract_inverted_index.artifacts. | 210 |
| abstract_inverted_index.calculated | 124 |
| abstract_inverted_index.challenges | 312 |
| abstract_inverted_index.comparison | 143 |
| abstract_inverted_index.fractures, | 333 |
| abstract_inverted_index.generating | 302 |
| abstract_inverted_index.materials, | 22 |
| abstract_inverted_index.materials: | 82 |
| abstract_inverted_index.originated | 208 |
| abstract_inverted_index.principle, | 290 |
| abstract_inverted_index.production | 130 |
| abstract_inverted_index.radiation. | 231 |
| abstract_inverted_index.reasonably | 288 |
| abstract_inverted_index.resolution | 251 |
| abstract_inverted_index.tomography | 12 |
| abstract_inverted_index.visibility | 325 |
| abstract_inverted_index.Conclusion: | 232 |
| abstract_inverted_index.algorithms, | 36 |
| abstract_inverted_index.distributed | 70 |
| abstract_inverted_index.estimation, | 40 |
| abstract_inverted_index.preparation | 79 |
| abstract_inverted_index.resolution, | 201 |
| abstract_inverted_index.resolutions | 29 |
| abstract_inverted_index.interactions | 150 |
| abstract_inverted_index.perforation, | 332 |
| abstract_inverted_index.radiographic | 237 |
| abstract_inverted_index.resolutions. | 116 |
| abstract_inverted_index.Significance: | 265 |
| abstract_inverted_index.achievable” | 289 |
| abstract_inverted_index.deterioration | 322 |
| abstract_inverted_index.false-negative | 317 |
| abstract_inverted_index.false-positive | 315 |
| abstract_inverted_index.interpretation | 311 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5000944427 |
| countries_distinct_count | 3 |
| institutions_distinct_count | 5 |
| corresponding_institution_ids | https://openalex.org/I60342839 |
| citation_normalized_percentile.value | 0.72134782 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |