Automatic computation of mandibular indices in dental panoramic radiographs for early osteoporosis detection

Aliaga, Ignacio; Vera, Vicente; Vera, María Isabel Paredes; García, Enrique; Pedrera, María; Pajares, Gonzalo

doi:10.1016/j.artmed.2020.101816

Cited by 21 publications

(31 citation statements)

References 52 publications

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“…The included studies were ranged from the year 2000 to 2020. The studies were from four categories: cohort study [ 5 , 16 , 27 ], case control [ 28 , 29 ], clinical trials [ 6 – 12 , 17 , 30 – 43 ], and experimental trials [ 13 – 15 , 44 , 45 ]. The follow-up period was mentioned in one study [ 43 ].…”

Section: Resultsmentioning

confidence: 99%

“…The follow-up period was mentioned in one study [ 43 ]. The various techniques of artificial intelligence was applied in the field oral and maxillofacial surgery [ 27 – 29 , 38 , 45 ], oral medicine [ 28 ], oral radiology [ 42 ], esthetic dentistry [ 17 , 44 ], restorative dentistry [ 11 – 13 , 34 , 36 , 40 ], endodontics [ 6 , 9 , 10 , 41 ], oral diagnosis [ 5 – 9 , 15 , 33 , 34 , 36 , 37 , 42 , 43 , 45 ], orthodontics and orthognathic surgery [ 16 , 35 ], forensic dentistry [ 8 ], gerodontology [ 39 ], implantology [ 43 ], periodontics [ 31 , 32 ], and prosthodontics [ 14 , 15 , 30 ].…”

Section: Resultsmentioning

confidence: 99%

“…In 5 studies, randomizations [ 5 , 7 , 34 , 37 , 39 ] were performed. The dropout rate was mentioned in 31 studies [ 5 – 11 , 13 – 17 , 27 – 45 ]. The study variables were analyzed for accuracy in 30 studies [ 5 – 13 , 15 – 17 , 27 – 29 , 37 , 39 – 45 ].…”

Section: Resultsmentioning

confidence: 99%

“…According to the standards described in the Cochrane Handbook for Systematic Reviews of Interventions (v5.1.0) [19], the following findings were recorded. Out of the 32 studies [5][6][7][8][9][10][11][12][13][14][15][16][17][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44][45] assessed, 1 study employed blinding [6]. In 5 studies, randomizations [5,7,34,37,39] were performed.…”

Section: Author and Year Reason Of Exclusionmentioning

confidence: 99%

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Artificial Intelligence Techniques: Analysis, Application, and Outcome in Dentistry—A Systematic Review

Ahmed

Abbasi

Zuberi

et al. 2021

BioMed Research International

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Objective. The objective of this systematic review was to investigate the quality and outcome of studies into artificial intelligence techniques, analysis, and effect in dentistry. Materials and Methods. Using the MeSH keywords: artificial intelligence (AI), dentistry, AI in dentistry, neural networks and dentistry, machine learning, AI dental imaging, and AI treatment recommendations and dentistry. Two investigators performed an electronic search in 5 databases: PubMed/MEDLINE (National Library of Medicine), Scopus (Elsevier), ScienceDirect databases (Elsevier), Web of Science (Clarivate Analytics), and the Cochrane Collaboration (Wiley). The English language articles reporting on AI in different dental specialties were screened for eligibility. Thirty-two full-text articles were selected and systematically analyzed according to a predefined inclusion criterion. These articles were analyzed as per a specific research question, and the relevant data based on article general characteristics, study and control groups, assessment methods, outcomes, and quality assessment were extracted. Results. The initial search identified 175 articles related to AI in dentistry based on the title and abstracts. The full text of 38 articles was assessed for eligibility to exclude studies not fulfilling the inclusion criteria. Six articles not related to AI in dentistry were excluded. Thirty-two articles were included in the systematic review. It was revealed that AI provides accurate patient management, dental diagnosis, prediction, and decision making. Artificial intelligence appeared as a reliable modality to enhance future implications in the various fields of dentistry, i.e., diagnostic dentistry, patient management, head and neck cancer, restorative dentistry, prosthetic dental sciences, orthodontics, radiology, and periodontics. Conclusion. The included studies describe that AI is a reliable tool to make dental care smooth, better, time-saving, and economical for practitioners. AI benefits them in fulfilling patient demand and expectations. The dentists can use AI to ensure quality treatment, better oral health care outcome, and achieve precision. AI can help to predict failures in clinical scenarios and depict reliable solutions. However, AI is increasing the scope of state-of-the-art models in dentistry but is still under development. Further studies are required to assess the clinical performance of AI techniques in dentistry.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Author and Year Reason Of Exclusionmentioning

confidence: 99%

See 2 more Smart Citations

Artificial Intelligence Techniques: Analysis, Application, and Outcome in Dentistry—A Systematic Review

Ahmed

Abbasi

Zuberi

et al. 2021

BioMed Research International

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show abstract

“…The AUROC of this AI system for identifying subjects with osteoporosis was 0.90 [98]. Apart from this study, another four studies have applied AI-like deep convolutional neural networks [99][100][101][102]. Panoramic radiography is rapidly shifting to a digital system; approximately 85% of panoramic radiography machines in Japan were digital in 2017 [103].…”

Section: Recommendations and Perspectives About Osteoporosis Screeninmentioning

confidence: 99%

Clinical guidelines for the application of panoramic radiographs in screening for osteoporosis

et al. 2021

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Osteoporotic fractures are associated with an increased risk of subsequent fractures, a higher rate of mortality, and incremental medical costs. Incidental findings, which include some measurements related to the mandibular inferior cortex and the alveolar trabecular bone pattern of the mandible determined on panoramic radiographs, are considered to be a useful tool for identifying asymptomatic individuals at risk of having osteoporosis and/or fragility fractures. We undertook a worldwide literature survey and present the following clinical recommendations. Postmenopausal female dental patients with a mandibular inferior cortical width of less than 3 mm on panoramic radiographs may be at risk of having low skeletal bone mineral density (BMD) or osteoporosis, but not fragility fractures. In addition, those with a severely eroded mandibular inferior cortex may have an increased risk of having low skeletal BMD, osteoporosis, and fragility fractures. The alveolar trabecular bone pattern of the mandible might be useful for identifying female dental patients at risk of having fragility fractures, although further investigation is necessary to confirm this possibility. These incidental findings on panoramic radiographs, when used for identifying asymptomatic postmenopausal female patients at risk of having osteoporosis in general dental practice, may be helpful in reducing the incidence of first fractures, with a consequent reduction in the secondary fractures, medical costs, and mortality associated with osteoporotic fragility fractures, without incurring any additional cost.

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Brief Introduction to Artificial Intelligence and Machine Learning

Motamedian¹,

Hassanzadeh-Samani²,

Nadimi³

et al. 2023

Emerging Technologies in Oral and Maxillofacial Surgery

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Automatic computation of mandibular indices in dental panoramic radiographs for early osteoporosis detection

Cited by 21 publications

References 52 publications

Artificial Intelligence Techniques: Analysis, Application, and Outcome in Dentistry—A Systematic Review

Artificial Intelligence Techniques: Analysis, Application, and Outcome in Dentistry—A Systematic Review

Clinical guidelines for the application of panoramic radiographs in screening for osteoporosis

Brief Introduction to Artificial Intelligence and Machine Learning

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