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Background: Dental cone beam computed tomography (CBCT) is commonly used to evaluate cancellous bone density before dental implant surgery. However, to our knowledge, no measurement approach has been standardized yet. This study aimed to evaluate the relationship between three different regions of interest (ROI) methods on cancellous bone density at the dental implant site using dental CBCT images., Methods: Patients' dental CBCT images (n = 300) obtained before dental implant surgery were processed using Mimics (Materialise, Leuven, Belgium). At the potential implant sites, the rectangle, cylinder, and surrounding cylinder ROI methods were used to measure bone density. Repeated measures one-way analysis of variance was performed to compare the three ROI methods in terms of measurement results. Pearson correlation analysis was performed to identify the likely pair-wise correlations between the three ROI methods., Results: The density value obtained using the surrounding cylinder approach (grayscale value [GV],523.56 ± 228.03) was significantly higher than the values obtained using the rectangle (GV, 497.04 ± 236.69) and cylinder (GV,493 ± 231.19) ROI methods in terms of results. Furthermore, significant correlations were noted between the ROI methods (r > 0.965; p < 0.001)., Conclusions: The density measured using the surrounding cylinder method was the highest. The choice of method may not influence the trends of measurement results., Trial Registration: This study was approved by the Institutional Review Board of China Medical University Hospital, No. CMUH111-REC3-205. Informed consent was waived by the Institutional Review Board of China Medical University Hospital, CMUH111-REC3-205, owing to the retrospective nature of the study., (© 2024. The Author(s).)

Osteoporosis is a disease characterized by a degradation of bone structures. Various methods have been developed to diagnose osteoporosis by measuring bone mineral density (BMD) of patients. However, BMDs from these methods were not equivalent and were incomparable. In addition, partial volume effect introduces errors in estimating bone volume from computed tomography (CT) images using image segmentation. In this study, a two-compartment model (TCM) was proposed to calculate bone volume fraction (BV/TV) and BMD from CT images. The TCM considers bones to be composed of two sub-materials. Various equivalent BV/TV and BMD can be calculated by applying corresponding sub-material pairs in the TCM. In contrast to image segmentation, the TCM prevented the influence of the partial volume effect by calculating the volume percentage of sub-material in each image voxel. Validations of the TCM were performed using bone-equivalent uniform phantoms, a 3D-printed trabecular-structural phantom, a temporal bone flap, and abdominal CT images. By using the TCM, the calculated BV/TVs of the uniform phantoms were within percent errors of ±2%; the percent errors of the structural volumes with various CT slice thickness were below 9%; the volume of the temporal bone flap was close to that from micro-CT images with a percent error of 4.1%. No significant difference (p >0.01) was found between the areal BMD of lumbar vertebrae calculated using the TCM and measured using dual-energy X-ray absorptiometry. In conclusion, the proposed TCM could be applied to diagnose osteoporosis, while providing a basis for comparing various measurement methods.

Objective: This study proposed a new classification method of bone quantity and quality at the dental implant site using cone-beam computed tomography (CBCT) image analysis, classifying cortical and cancellous bones separately and using CBCT for quantitative analysis. Methods: Preoperative CBCT images were obtained from 128 implant patients (315 sites). First, measure the crestal cortical bone thickness (in mm) and the cancellous bone density [in grayscale values (GV) and bone mineral density (g/cm3)] at the implant sites. The new classification for bone quality at the implant site proposed in this study is a "nine-square division" bone classification system, where the cortical bone thickness is classified into A: > 1.1 mm, B:0.7–1.1 mm, and C: < 0.7 mm, and the cancellous bone density is classified into 1: > 600 GV (= 420 g/cm3), 2:300–600 GV (= 160 g/cm3–420 g/cm3), and 3: < 300 GV (= 160 g/cm3). Results: The results of the nine bone type proportions based on the new jawbone classification were as follows: A1 (8.57%,27/315), A2 (13.02%), A3 (4.13%), B1 (17.78%), B2 (20.63%), B3 (8.57%) C1 (4.44%), C2 (14.29%), and C3 (8.57%). Conclusions: The proposed classification can complement the parts overlooked in previous bone classification methods (bone types A3 and C1). Trial registration: The retrospective registration of this study was approved by the Institutional Review Board of China Medical University Hospital, No. CMUH 108-REC2-181. [ABSTRACT FROM AUTHOR]

Bone quality parameters (BQPs) calculated from computed tomography (CT) and micro-computed tomography (μCT) images have been applied in clinical to diagnose and prevent osteoporotic fractures. However, the BQPs calculated from CT and μCT images are at different scales and incomparable due to the differences in image resolutions and accounted bone compositions. In this study, we proposed a novel method to convert HU values of CT images into the BQPs that were originally calculated using different tools. By using the standard bone composition of human bones, the BQPs of bone volume fractions (BV/TV) and volumetric bone mineral densities (vBMD) of the bones were calculated using different accounted compositions of bones and mathematical relationships defined in this study. In addition, the HU values of the bones were estimated using a parametric physical model and spectrum characteristic parameters. Relationships for converting HU values into BQPs were determined by linear fitting the calculated BQPs and estimated HU values. Cadaveric and patient studies show that the micro-scale bone volumes and macro-scale vBMDs of vertebrae calculated from CT images using the conversion relationships determined by the proposed method were close to those calculated from the μCT images and quantitative CT, respectively, with mean percent errors lower than 5%. The proposed method could be applied in clinical to accurately compute micro- and macro-scale BQPs from CT images for assessing the bone quality of patients. • Calculating bone quality parameters of varying accounted compositions at different scales. • Defining conversion relationships between bone quality parameters. • Estimating photon attenuation properties of human bones. • Accurately calculating micro-scale BV/TVs and macro-scale vBMDs of vertebrae. • Assisting accurate calculations of various bone quality parameters in clinical. [ABSTRACT FROM AUTHOR]

Dental implant surgery is a common treatment for missing teeth. Its survival rate is considerably affected by host bone quality and quantity, which is often assessed prior to surgery through dental cone-beam computed tomography (CBCT). Dental CBCT was used in this study to evaluate dental implant sites for (1) differences in and (2) correlations between cancellous bone density and cortical bone thickness among four regions of the jawbone. In total, 315 dental implant sites (39 in the anterior mandible, 42 in the anterior maxilla, 107 in the posterior mandible, and 127 in the posterior maxilla) were identified in dental CBCT images from 128 patients. All CBCT images were loaded into Mimics 15.0 to measure cancellous bone density (unit: grayscale value (GV) and cortical bone thickness (unit: mm)). Differences among the four regions of the jawbone were evaluated using one-way analysis of variance and Scheffe's posttest. Pearson coefficients for correlations between cancellous bone density and cortical bone thickness were also calculated for the four jawbone regions. The results revealed that the mean cancellous bone density was highest in the anterior mandible (722 ± 227 GV), followed by the anterior maxilla (542 ± 208 GV), posterior mandible (535 ± 206 GV), and posterior maxilla (388 ± 206 GV). Cortical bone thickness was highest in the posterior mandible (1.15 ± 0.42 mm), followed by the anterior mandible (1.01 ± 0.32 mm), anterior maxilla (0.89 ± 0.26 mm), and posterior maxilla (0.72 ± 0.19 mm). In the whole jawbone, a weak correlation (r = 0.133, p = 0.041) was detected between cancellous bone density and cortical bone thickness. Furthermore, except for the anterior maxilla (r = 0.306, p = 0.048), no correlation between the two bone parameters was observed (all p > 0.05). Cancellous bone density and cortical bone thickness varies by implant site in the four regions of the jawbone. The cortical and cancellous bone of a jawbone dental implant site should be evaluated individually before surgery. [ABSTRACT FROM AUTHOR]