APPLICATION OF NOLLA'S METHOD FOR AGE ESTIMATION: A CBCT STUDY ON MAXILLARY SECOND MOLARS AND CANINES IN THE RAJASTHAN POPULATION

The study aimed to assess the correlation between dental age and chronological age using Nolla's radiographic method, specifically evaluating mineralization stages of maxillary canine and second molar for sub-adult tooth age estimation. This retrospective single-centre study, conducted at the Department of Oral Medicine and Radiology, RUHS College of Dental Sciences in Jaipur, Rajasthan, aimed to assess age using Cone Beam Computed Tomography (CBCT) scans. CBCT scans of thirty patients (15 males, 15 females), aged 8 to 14 years were randomly selected and evaluated, focusing on developmental stages of maxillary canine and second molar for dental age estimation. Inclusion criteria ensured participants' oral health and normal growth, while exclusion criteria ruled out systemic diseases, congenital anomalies, and dental pathologies. Statistical analysis employed SPSS Version 29, utilizing one-way ANOVAfor intergroup comparisons. Results, presented as P values and F-static values, highlighted the study's precision in dental age estimation. Dental age was estimated using CBCTwhile categorizing subjects aged 8-14 into six subgroups (1-6). Group-wise analysis revealed non-significant differences between chronological and dental age. Molar and canine dental age showed overall underestimation, with subgroup variations. The reliability of dental age, evaluated particularly through Nolla's method, underscores its efficacy as a trustworthy indicator for assessing dental maturity. The demonstrated validity of Nolla's dental age estimation further solidifies its utility as a robust dental maturity indicator.

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Journal
INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH
Published
2025-02-01
DOI
https://doi.org/10.36106/ijsr/5406394
Primary Topic
Human Pose and Action Recognition
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article
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article

APPLICATION OF NOLLA'S METHOD FOR AGE ESTIMATION: A CBCT STUDY ON MAXILLARY SECOND MOLARS AND CANINES IN THE RAJASTHAN POPULATION

Krishna Sireesha Sundaragiri, Jaishree Thanvi, Geetika Sobti, P. K. Chaudhary et al.
INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH
Human Pose and Action Recognition
article

APPLICATION OF NOLLA'S METHOD FOR AGE ESTIMATION: A CBCT STUDY ON MAXILLARY SECOND MOLARS AND CANINES IN THE RAJASTHAN POPULATION

Krishna Sireesha Sundaragiri, Jaishree Thanvi, Geetika Sobti, P. K. Chaudhary, Prajjawal Gahlot
article en

Abstract

The study aimed to assess the correlation between dental age and chronological age using Nolla's radiographic method, specifically evaluating mineralization stages of maxillary canine and second molar for sub-adult tooth age estimation. This retrospective single-centre study, conducted at the Department of Oral Medicine and Radiology, RUHS College of Dental Sciences in Jaipur, Rajasthan, aimed to assess age using Cone Beam Computed Tomography (CBCT) scans. CBCT scans of thirty patients (15 males, 15 females), aged 8 to 14 years were randomly selected and evaluated, focusing on developmental stages of maxillary canine and second molar for dental age estimation. Inclusion criteria ensured participants' oral health and normal growth, while exclusion criteria ruled out systemic diseases, congenital anomalies, and dental pathologies. Statistical analysis employed SPSS Version 29, utilizing one-way ANOVAfor intergroup comparisons. Results, presented as P values and F-static values, highlighted the study's precision in dental age estimation. Dental age was estimated using CBCTwhile categorizing subjects aged 8-14 into six subgroups (1-6). Group-wise analysis revealed non-significant differences between chronological and dental age. Molar and canine dental age showed overall underestimation, with subgroup variations. The reliability of dental age, evaluated particularly through Nolla's method, underscores its efficacy as a trustworthy indicator for assessing dental maturity. The demonstrated validity of Nolla's dental age estimation further solidifies its utility as a robust dental maturity indicator.

INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH
Rajasthan University of Health Sciences (IN)
Openalex Percentile: Top 98%
Human Pose and Action Recognition
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