Gray values of the cervical vertebrae detected by cone beam computed tomography for the identification of osteoporosis and osteopenia in postmenopausal women

Ankle Joint Bone Density Distribution Correlates with Overall 3-Dimensional Foot and Ankle Alignment

BACKGROUND

Altered stress distribution in the lower limb may impact bone mineral density (BMD) in the ankle bones. The purpose of the present study was to evaluate the spatial distribution of BMD with use of weight-bearing cone-beam computed tomography (WBCT). Our hypothesis was that BMD distribution would be even in normal hindfeet, increased medially in varus hindfeet, and increased laterally in valgus hindfeet.

METHODS

In this study, 27 normally aligned hindfeet were retrospectively compared with 27 valgus and 27 varus-aligned hindfeet. Age (p = 0.967), body mass index (p = 0.669), sex (p = 0.820), and side (p = 0.708) were similar in the 3 groups. Hindfoot alignment was quantified on the basis of WBCT data sets with use of multiple measurements. BMD was calculated with use of the mean Hounsfield unit (HU) value as a surrogate. The HU medial-to-lateral ratio (HUR), calculated from tibial and talar medial and lateral half-volumes, was the primary outcome of the study.

RESULTS

The 3 groups significantly differed (p < 0.001) in terms of tibial HUR (median, 0.91 [interquartile range (IQR), 0.75 to 0.98] in valgus hindfeet, 1 [IQR, 0.94 to 1.05] in normal hindfeet, and 1.04 [IQR, 0.99 to 1.1] in varus hindfeet) and talar HUR (0.74 [IQR, 0.50 to 0.80] in valgus hindfeet, 0.82 [IQR, 0.76 to 0.87] in normal hindfeet, and 0.92 [IQR, 0.86 to 1.05] in varus hindfeet). Linear regression showed that all hindfoot measurements significantly correlated with tibial and talar HUR (p < 0.001 for all). The mean HU values for normally-aligned hindfeet were 495.2 ± 110 (medial tibia), 495.6 ± 108.1 (lateral tibia), 368.9 ± 80.3 (medial talus), 448.2 ± 90.6 (lateral talus), and 686.7 ± 120.4 (fibula). The mean HU value for each compartment was not significantly different across groups.

CONCLUSIONS

Hindfoot alignment and medial-to-lateral BMD distribution were correlated. In varus hindfeet, an increased HU medial-to-lateral ratio was consistent with a greater medial bone density in the tibia and talus as compared with the lateral parts of these bones. In valgus hindfeet, a decreased ratio suggested greater bone density in the lateral as compared with the medial parts of both the tibia and the talus.

LEVEL OF EVIDENCE

Prognostic Level III . See Instructions for Authors for a complete description of levels of evidence.

Modular Neural Networks for Osteoporosis Detection in Mandibular Cone-Beam Computed Tomography Scans

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.

Aging Alters Cervical Vertebral Bone Density Distribution: A Cross-Sectional Study

Osteoporosis reduces bone mineral density (BMD) with aging. The incidence of cervical vertebral injuries for the elderly has increased in the last decade. Thus, the objective of the current study was to examine whether dental cone beam computed tomography (CBCT) can identify age and sex effects on volumetric BMD and morphology of human cervical vertebrae. A total of 136 clinical CBCT images were obtained from 63 male and 73 female patients (20 to 69 years of age). Three-dimensional images of cervical vertebral bodies (C2 and C3) were digitally isolated. A gray level, which is proportional to BMD, was obtained and its distribution was analyzed in each image. Morphology, including volume, heights, widths, and concavities, was also measured. Most of the gray level parameters had significantly higher values of C2 and C3 in females than in males for all age groups (p < 0.039). The female 60-age group had significant lower values of Mean and Low5 of C2 and C3 than both female 40- and 50-age groups (p < 0.03). The reduced BMD of the female 60-age group likely resulted from postmenopausal demineralization of bone. Current findings suggest that dental CBCT can detect age-dependent changes of cervical vertebral BMD, providing baseline information to develop an alternative tool to diagnose osteoporosis.