Dataset Information

Cross-Sectional Imaging of Third Molar-Related Abnormalities.

ABSTRACT: Third molars may be associated with a wide range of pathologic conditions, including mechanical, inflammatory, infectious, cystic, neoplastic, and iatrogenic. Diagnosis of third molar-related conditions can be challenging for radiologists who lack experience in dental imaging. Appropriate imaging evaluation can help practicing radiologists arrive at correct diagnoses, thus improving patient care. This review discusses the imaging findings of various conditions related to third molars, highlighting relevant anatomy and cross-sectional imaging techniques. In addition, key imaging findings of complications of third molar extraction are presented.

SUBMITTER: Loureiro RM

PROVIDER: S-EPMC7658851 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Cross-Sectional Imaging of Third Molar-Related Abnormalities.

Loureiro R M RM Sumi D V DV Tames H L V C HLVC Ribeiro S P P SPP Soares C R CR Gomes R L E RLE Daniel M M MM

AJNR. American journal of neuroradiology 20200910 11

Third molars may be associated with a wide range of pathologic conditions, including mechanical, inflammatory, infectious, cystic, neoplastic, and iatrogenic. Diagnosis of third molar-related conditions can be challenging for radiologists who lack experience in dental imaging. Appropriate imaging evaluation can help practicing radiologists arrive at correct diagnoses, thus improving patient care. This review discusses the imaging findings of various conditions related to third molars, highlighti ...[more]

PMID: 32912872

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Project description:BackgroundAlzheimer's disease (AD) is a prevalent neurodegenerative disorder that poses a worldwide public health challenge. A neuroimaging biomarker would significantly improve early diagnosis and intervention, ultimately enhancing the quality of life for affected individuals and reducing the burden on healthcare systems.MethodsCross-sectional and longitudinal data (10,099 participants with 13,380 scans) from 12 independent datasets were used in the present study (this study was performed between September 1, 2021 and February 15, 2023). The Individual Brain-Related Abnormalities In Neurodegeneration (IBRAIN) score was developed via integrated regional- and network-based measures under an ensemble machine learning model based on structural MRI data. We systematically assessed whether IBRAIN could be a neuroimaging biomarker for AD.FindingsIBRAIN accurately differentiated individuals with AD from NCs (AUC = 0.92) and other neurodegenerative diseases, including Frontotemporal dementia (FTD), Parkinson's disease (PD), Vascular dementia (VaD) and Amyotrophic Lateral Sclerosis (ALS) (AUC = 0.92). IBRAIN was significantly correlated to clinical measures and gene expression, enriched in immune process and protein metabolism. The IBRAIN score exhibited a significant ability to reveal the distinct progression of prodromal AD (i.e., Mild cognitive impairment, MCI) (Hazard Ratio (HR) = 6.52 [95% CI: 4.42∼9.62], p < 1 × 10-16), which offers similar powerful performance with Cerebrospinal Fluid (CSF) Aβ (HR = 3.78 [95% CI: 2.63∼5.43], p = 2.13 × 10-14) and CSF Tau (HR = 3.77 [95% CI: 2.64∼5.39], p = 9.53 × 10-15) based on the COX and Log-rank test. Notably, the IBRAIN shows comparable sensitivity (beta = -0.70, p < 1 × 10-16) in capturing longitudinal changes in individuals with conversion to AD than CSF Aβ (beta = -0.26, p = 4.40 × 10-9) and CSF Tau (beta = 0.12, p = 1.02 × 10-5).InterpretationOur findings suggested that IBRAIN is a biologically relevant, specific, and sensitive neuroimaging biomarker that can serve as a clinical measure to uncover prodromal AD progression. It has strong potential for application in future clinical practice and treatment trials.FundingScience and Technology Innovation 2030 Major Projects, the National Natural Science Foundation of China, Beijing Natural Science Funds, the Fundamental Research Funds for the CentralUniversity, and the Startup Funds for Talents at Beijing Normal University.

Dataset Information

Cross-Sectional Imaging of Third Molar-Related Abnormalities.

Publications

Cross-Sectional Imaging of Third Molar-Related Abnormalities.

Similar Datasets

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