Baiba Springe, DDS/Anda Slaidina, DDS, PhD/Una Soboleva, DDS, MSc, PhD/Aivars Lejnieks, MD, PhD: Purpose: This prospective, cross-sectional study evaluated the relationship between bone mineral density (BMD) and the width and height parameters of the mandibular residual ridge. Materials and Methods: BMD was determined in the lumbar spine and femoral necks by dual energy x-ray absorptiometry (DXA) in 45 edentulous, postmenopausal women (mean age, 72.08 ? 8.53 years) who had used conventional complete dentures for at least 3 years. Measurements of the mandibular residual ridge were performed using cone beam computed tomography (CBCT). Height and width measurements were performed in the midline and adjacent to the mental foramina. Data were analyzed with descriptive and analytic statistics. The relationship between BMD and mandibular height and width measurements was assessed using analysis of variance as well as linear and multivariate regression analyses. Eight patients were excluded from the study because they did not complete both of the required imaging analyses (DXA and/or CBCT). Results: There was no statistically significant relationship between BMD and mandibular bone height measurements in the midline and both regions of the mental foramina, and no statistically significant relationship existed between BMD and mandibular bone width measurements in the midline and both of the mental foramina regions. Conclusions: Postmenopausal women with reduced general BMD do not appear to have a reduction in the size of the mandibular residual ridge. Int J Prosthodont 2014;27:270?276. doi: 10.11607/ijp.3283

In this technical note, we examine the capabilities of deep convolutional neural networks (DCNNs) for diagnosing osteoporosis through cone-beam computed tomography (CBCT) scans of the mandible. The evaluation was conducted using 188 patients’ mandibular CBCT images utilizing DCNN models built on the ResNet-101 framework. We adopted a segmented three-phase method to assess osteoporosis. Stage 1 focused on mandibular bone slice identification, Stage 2 pinpointed the coordinates for mandibular bone cross-sectional views, and Stage 3 computed the mandibular bone’s thickness, highlighting osteoporotic variances. The procedure, built using ResNet-101 networks, showcased efficacy in osteoporosis detection using CBCT scans: Stage 1 achieved a remarkable 98.85% training accuracy, Stage 2 minimized L1 loss to a mere 1.02 pixels, and the last stage’s bone thickness computation algorithm reported a mean squared error of 0.8377. These findings underline the significant potential of AI in osteoporosis identification and its promise for enhanced medical care. The compartmentalized method endorses a sturdier DCNN training and heightened model transparency. Moreover, the outcomes illustrate the efficacy of a modular transfer learning method for osteoporosis detection, even when relying on limited mandibular CBCT datasets. The methodology given is accompanied by the source code available on GitLab.

Introduction: Periapical lesions of teeth are typically evaluated using periapical X-rays (PA) or cone-beam computer tomography (CBCT); however, ultrasound imaging (US) can also be used to detect bone defects. A comparative analysis is necessary to establish the diagnostic accuracy of US for the detection of periapical lesions in comparison with PA and CBCT. Objectives: This study aimed to evaluate and compare the measurement precision of US against PA and CBCT in detecting periapical lesions. Methods: This study included 43 maxillary and mandibular teeth with periapical lesions. All teeth were examined clinically, radiographically, and ultrasonographically. Observers evaluated and measured the periapical lesions on CBCT, PA, and US images. Results: The comparison of lesion size showed that it differs significantly between the different methods of examination. A statistically significant difference was found between CBCT and US (mean difference = 0.99 mm, 95% CI [0.43–1.55]), as well as between CBCT and PA (mean difference = 0.61 mm, 95% CI [0.17–1.05]). No difference was found between the US and PA methods (p = 0.193). Conclusion: US cannot replace PA radiography in detecting pathologies but it can accurately measure and characterize periapical lesions with minimal radiation exposure. CBCT is the most precise and radiation-intensive method so it should only be used for complex cases.

Background: Osteoporosis is a disease which is characterized by a decrease in general bone mineral density (BMD), resulting in decreased bone strength and an increased risk of bone fractures. The effect of reduced BMD on the jawbones is still not fully understood. The purpose of the study was to evaluate the impact of BMD on the quality and quantity of the edentulous mandible. Methods: The present study included 127 edentulous postmenopausal women who underwent cone beam computed tomography (CBCT) examinations. BMD measurements of the lumbar spine and femoral necks were performed by dual-energy X-ray absorptiometry. In the cross-sectional CBCT images, three different areas of the mandible (lateral incisor, first premolar, and first molar) were selected. The complete mandibular, trabecular, and cortical bone volumes were measured. All measurements were performed on the total mandibular area, and the basal and alveolar parts of the mandible. Results: The volume of the cortical bone was reduced for females with reduced BMD in the lateral incisor and first premolar regions, both in the total mandibular area and in the basal part of the mandible. The trabecular bone volume statistically significantly increased when the BMD decreased in the complete mandibular area and the basal part of the mandible (linear regression). The total bone volume significantly decreased with a decrease in BMD in the basal part of the mandible. Conclusions: Reduced BMD has a negative effect on the quantity and quality of bone in the basal part of the edentulous mandible.