Detection of vertical root fractures by using cone-beam computed tomography: a clinical study. 2011

Mitchell Edlund, and Madhu K Nair, and Umadevi P Nair
Department of Endodontics, College of Dentistry, University of Florida, Gainesville, Florida 32610-0436, USA. unair@dental.ufl.edu

BACKGROUND Vertical root fractures of teeth (VRFs) often pose a diagnostic dilemma because of the difficulty in detection of these in intraoral radiographs except in certain cases with very distinct clinical findings. This often leads to unwarranted extraction of the tooth. Cone-beam computed tomography (CBCT) produces three-dimensional images and allows precise visualization and evaluation of VRFs or cracks in extracted teeth, as reported previously. This clinical pilot study was designed to determine the diagnostic accuracy of noninvasive CBCT for detection of suspected VRFs in endodontically treated teeth by using exploratory surgery to confirm the presence or absence of a fracture. METHODS Thirty-two teeth in 29 patients with clinical signs and symptoms suggestive of VRF were included in the study after informed consent was obtained. They underwent a limited area CBCT evaluation. All CBCT studies were blinded, and 2 board-certified oral and maxillofacial radiologists assessed the presence or absence of VRF through sequential evaluation of the three-dimensional volume. Subjects underwent surgical exploration as part of treatment, which helped establish the presence or absence of VRF. RESULTS Pearson correlation coefficient by using surgical finding to confirm presence/absence of fracture was 0.602, positive predictive value was 91%, and negative predictive value was 67%. The sensitivity was 88%, and specificity was 75%. CONCLUSIONS This study revealed the superior diagnostic accuracy of CBCT for detection of VRF.

UI MeSH Term Description Entries
D007091 Image Processing, Computer-Assisted A technique of inputting two-dimensional or three-dimensional images into a computer and then enhancing or analyzing the imagery into a form that is more useful to the human observer. Biomedical Image Processing,Computer-Assisted Image Processing,Digital Image Processing,Image Analysis, Computer-Assisted,Image Reconstruction,Medical Image Processing,Analysis, Computer-Assisted Image,Computer-Assisted Image Analysis,Computer Assisted Image Analysis,Computer Assisted Image Processing,Computer-Assisted Image Analyses,Image Analyses, Computer-Assisted,Image Analysis, Computer Assisted,Image Processing, Biomedical,Image Processing, Computer Assisted,Image Processing, Digital,Image Processing, Medical,Image Processings, Medical,Image Reconstructions,Medical Image Processings,Processing, Biomedical Image,Processing, Digital Image,Processing, Medical Image,Processings, Digital Image,Processings, Medical Image,Reconstruction, Image,Reconstructions, Image
D008866 Microsurgery The performance of surgical procedures with the aid of a microscope.
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D010514 Periodontal Pocket An abnormal extension of a gingival sulcus accompanied by the apical migration of the epithelial attachment and bone resorption. Pocket, Periodontal,Periodontal Pockets,Pockets, Periodontal
D010865 Pilot Projects Small-scale tests of methods and procedures to be used on a larger scale if the pilot study demonstrates that these methods and procedures can work. Pilot Studies,Pilot Study,Pilot Project,Project, Pilot,Projects, Pilot,Studies, Pilot,Study, Pilot
D011237 Predictive Value of Tests In screening and diagnostic tests, the probability that a person with a positive test is a true positive (i.e., has the disease), is referred to as the predictive value of a positive test; whereas, the predictive value of a negative test is the probability that the person with a negative test does not have the disease. Predictive value is related to the sensitivity and specificity of the test. Negative Predictive Value,Positive Predictive Value,Predictive Value Of Test,Predictive Values Of Tests,Negative Predictive Values,Positive Predictive Values,Predictive Value, Negative,Predictive Value, Positive
D003937 Diagnosis, Differential Determination of which one of two or more diseases or conditions a patient is suffering from by systematically comparing and contrasting results of diagnostic measures. Diagnoses, Differential,Differential Diagnoses,Differential Diagnosis
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000328 Adult A person having attained full growth or maturity. Adults are of 19 through 44 years of age. For a person between 19 and 24 years of age, YOUNG ADULT is available. Adults
D000368 Aged A person 65 years of age or older. For a person older than 79 years, AGED, 80 AND OVER is available. Elderly

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