Apical root resorption due to orthodontic treatment detected by cone beam computed tomography

Abstract

Objective: To determine the frequency of apical root resorption (ARR) due to orthodontic treatment using cone beam computed tomography (CBCT) in a sample of 1256 roots from 30 patients.

Materials and methods: All patients had Class I malocclusion with crowding. Of the 30 patients evaluated, 11 were boys and 19 were girls; their mean age was 13 years (11 to 16 years). Orthodontic treatment followed the nonextraction treatment. CBCT images were obtained before and after orthodontic treatment, and ARR was determined using Axial Guided Navigation of CBCT images.

Results: All patients had ARR. No statistically significant association was found between resorption frequency, gender, and age. ARR was detected using CBCT in 46% of all roots that underwent orthodontic treatment.

Conclusions: CBCT was effective for detecting in vivo even minimal degrees of ARR due to orthodontic treatment and allowed three-dimensional evaluation of dental roots and visualization of palatine roots of maxillary molars. The highest frequencies and the most significant ARR occurred in incisors and distal roots of first maxillary and mandibular molars.

Figures

Figure 1.

Reference points to measure maximum linear length.

Figure 2.

Axial multiplanar reconstruction with identification of root apex (A) as a reference point. Coronal (B) and sagittal (C) multiplanar reconstruction identifies root apex on intersection of axial cursor with coronal and sagittal cursors. Identification of incisal edge and cusp (D) as reference points after axial cursor movement on coronal (E) and sagittal (F) multiplanar reconstruction. Tracing with CT software measuring tool on sagittal (G and I) or coronal (H and J) cursor line based on landmarks identified in axial multiplanar reconstruction (A and D).

Figure 3.

Box plots of the apical root resorption values in the roots in which resorption was statistically significant, including minimum/maximum values and outliers.