A Comparative Study on the Voxel Values in Alveolar Bones Acquired by MDCT and Newly Developed Dental Dual-Energy CBCT

Low-cost dual-energy CBCT by spectral filtration of a dual focal spot X-ray source

Dual-energy cone beam computed tomography (DE-CBCT) has been shown to provide more information and improve performance compared to a conventional single energy spectrum CBCT. Here we report a low-cost DE-CBCT by spectral filtration of a carbon nanotube x-ray source array. The x-ray photons from two focal spots were filtered respectively by a low and a high energy filter. Projection images were collected by alternatively activating the two beams while the source array and detector rotated around the object, and were processed by a one-step materials decomposition and reconstruction method. The performance of the DE-CBCT scanner was evaluated by imaging a water-equivalent plastic phantom with inserts containing known densities of calcium or iodine and an anthropomorphic head phantom with dental implants. A mean energy separation of 15.5 keV was achieved at acceptable dose rates and imaging time. Accurate materials quantification was obtained by materials decomposition. Metal artifacts were reduced in the virtual monoenergetic images synthesized at high energies. The results demonstrated the feasibility of high quality DE-CBCT imaging by spectral filtration without using either an energy sensitive detector or rapid high voltage switching.

Improving the accuracy of bone mineral density using a multisource CBCT

Multisource cone beam computed tomography CBCT (ms-CBCT) has been shown to overcome some of the inherent limitations of a conventional CBCT. The purpose of this study was to evaluate the accuracy of ms-CBCT for measuring the bone mineral density (BMD) of mandible and maxilla compared to the conventional CBCT. The values measured from a multi-detector CT (MDCT) were used as substitutes for the ground truth. An anthropomorphic adult skull and tissue equivalent head phantom and a homemade calibration phantom containing inserts with varying densities of calcium hydroxyapatite were imaged using the ms-CBCT, the ms-CBCT operating in the conventional single source CBCT mode, and two clinical CBCT scanners at similar imaging doses; and a clinical MDCT. The images of the anthropomorphic head phantom were reconstructed and registered, and the cortical and cancellous bones of the mandible and the maxilla were segmented. The measured CT Hounsfield Unit (HU) and Greyscale Value (GV) at multiple region-of-interests were converted to the BMD using scanner-specific calibration functions. The results from the various CBCT scanners were compared to that from the MDCT. Statistical analysis showed a significant improvement in the agreement between the ms-CBCT and MDCT compared to that between the CBCT and MDCT.

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.

TIME-Net: Transformer-Integrated Multi-Encoder Network for limited-angle artifact removal in dual-energy CBCT

Dual-energy cone-beam computed tomography (DE-CBCT) is a promising imaging technique with foreseeable clinical applications. DE-CBCT images acquired with two different spectra can provide material-specific information. Meanwhile, the anatomical consistency and energy-domain correlation result in significant information redundancy, which could be exploited to improve image quality. In this context, this paper develops the Transformer-Integrated Multi-Encoder Network (TIME-Net) for DE-CBCT to remove the limited-angle artifacts. TIME-Net comprises three encoders (image encoder, prior encoder, and transformer encoder), two decoders (low- and high-energy decoders), and one feature fusion module. Three encoders extract various features for image restoration. The feature fusion module compresses these features into more compact shared features and feeds them to the decoders. Two decoders perform differential learning for DE-CBCT images. By design, TIME-Net could obtain high-quality DE-CBCT images using two complementary quarter-scans, holding great potential to reduce radiation dose and shorten the acquisition time. Qualitative and quantitative analyses based on simulated data and real rat data have demonstrated the promising performance of TIME-Net in artifact removal, subtle structure restoration, and reconstruction accuracy preservation. Two clinical applications, virtual non-contrast (VNC) imaging and iodine quantification, have proved the potential utility of the DE-CBCT images provided by TIME-Net.