Search

This study investigated the feasibility of a highly specific multiplexed image-guided small animal radiation therapy (SART) platform based on triple imaging from on-board single-photon emission computed tomography (SPECT), spectral-CT, and cone-beam CT (CBCT) guidance in radiotherapy treatment. As a proof-of-concept, the SART system was built with the capability of triple on-board image guidance by utilizing an x-ray tube and a single cadmium zinc telluride (CZT) semiconductor photon-counting imager via a Monte Carlo simulation study. The x-ray tube can be set at a low tube current for imaging mode and a high tube current for radiation therapy mode, respectively. In the imaging mode, both x-ray and gamma-ray projection data were collected by the imager to reconstruct CBCT, SPECT and spectral CT images of small animals being treated. The modulation transfer function (MTF) of the pixelated CZT imager measured was 8.6 lp/mm. The overall performances of the CBCT and SPECT imaging of the system were evaluated with sufficient spatial resolution and imaging quality to be fitted into the SART platform. The material differentiation and decomposition capacities of spectral CT within the system were verified using K-edge imaging, image-based optimal energy weighted imaging, and image-based linear material decomposition methods. The triple imaging capability of the system was demonstrated using a PMMA phantom containing gadolinium, iodine and radioisotope 99mTc inserts. All the probes were clearly identified in the registered image. The results demonstrated that a novel SART platform with high-quality on-board CBCT, spectral-CT, SPECT image guidance is technically feasible by using a single semiconductor imager, thus affording comprehensive image guidance from anatomical, functional, and molecular levels for radiation treatment beam delivery. [ABSTRACT FROM AUTHOR]

Identification and treatment of obstructive airway disorders (OADs) are greatly aided by imaging of the geometry of the airway lumen. Anatomical optical coherence tomography (aOCT) is a promising high-speed and minimally invasive endoscopic imaging modality for providing micrometer-resolution scans of the upper airway. Resistance to airflow in OADs is directly caused by the reduction in luminal cross-sectional area (CSA). It is hypothesized that aOCT can produce airway CSA measurements as accurate as that from computed tomography (CT). Scans of machine hollowed cylindrical tubes were used to develop methods for segmentation and measurement of airway lumen in CT and aOCT. Simulated scans of virtual cones were used to validate 3-D resampling and reconstruction methods in aOCT. Then, measurements of two segments of a 3-D printed pediatric airway phantom from aOCT and CT independently were compared to ground truth CSA. In continuous unobstructed regions, the mean CSA difference for each phantom segment was 2.2 ± 3.5 and 1.5 ± 5.3 mm2 for aOCT, and −3.4 ± 4.3 and −1.9 ± 1.2 mm2 for CT. Because of the similar magnitude of these differences, these results support the hypotheses and underscore the potential for aOCT as a viable alternative to CT in airway imaging, while offering greater potential to capture respiratory dynamics. [ABSTRACT FROM AUTHOR]

A single-scan dual-energy low-dose cone-beam CT (CBCT) imaging technique that exploits a multi-slit filter is proposed in this paper. The multi-slit filter installed between the x-ray source and the scanned object is reciprocated during a scan. The x-ray beams through the slits would generate relatively low-energy x-ray projection data, while the filtered beams would make high-energy projection data. An iterative image reconstruction algorithm that uses an adaptive-steepest-descent method to minimize image total-variation under the constraint of data fidelity was applied to reconstructing the image from the low-energy projection data. Since the high-energy projection data suffer from a substantially high noise level due to the beam filtration, we have developed a new algorithm that exploits the joint sparsity between the low- and high-energy CT images for image reconstruction of the high-energy CT image. The proposed image reconstruction algorithm uses a gradient magnitude image (GMI) of the low-energy CT image by regularizing the difference of GMIs of the low- and high-energy CT images to be minimized. The feasibility of the proposed technique has been demonstrated by the use of various phantoms in the experimental CBCT setup. Furthermore, based on the proposed dual-energy imaging, a material differentiation was performed and its potential utility has been shown. The proposed imaging technique produced promising results for its potential application to a low-dose single-scan dual-energy CBCT. [ABSTRACT FROM PUBLISHER]