A respiratory-guided 4D digital tomosynthesis

Dose Reduction and Low-Contrast Detectability Using Iterative CBCT Reconstruction Algorithm for Radiotherapy

Introduction: Several studies have reported the relation between the imaging dose and secondary cancer risk and have emphasized the need to minimize the additional imaging dose as low as reasonably achievable. The iterative cone-beam computed tomography (iCBCT) algorithm can improve the image quality by utilizing scatter correction and statistical reconstruction. We investigate the use of a novel iCBCT reconstruction algorithm to reduce the patient dose while maintaining low-contrast detectability and registration accuracy. Methods: Catphan and anthropomorphic phantoms were analyzed. All CBCT images were acquired with varying dose levels and reconstructed with a Feldkamp-Davis-Kress algorithm-based CBCT (FDK-CBCT) and iCBCT. The low-contrast detectability was subjectively assessed using a 9-point scale by 4 reviewers and objectively assessed using structure similarity index (SSIM). The soft tissue-based registration error was analyzed for each dose level and reconstruction technique. Results: The results of subjective low-contrast detectability found that the iCBCT acquired at two-thirds of a dose was superior to the FDK-CBCT acquired at a full dose (6.4 vs 5.4). Relative to FDK-CBCT acquired at full dose, SSIM was higher for iCBCT acquired at one-sixth dose in head and head and neck region while equivalent with iCBCT acquired at two-thirds dose in pelvis region. The soft tissue-based registration was 2.2 and 0.6 mm for FDK-CBCT and iCBCT, respectively. Conclusion: Use of iCBCT reconstruction algorithm can generally reduce the patient dose by approximately two-thirds compared to conventional reconstruction methods while maintaining low-contrast detectability and accuracy of registration.

Four-dimensional inverse-geometry computed tomography: a preliminary study

This study introduces and evaluates respiratory-correlated four-dimensional (4D) inverse geometry computed tomography (IGCT). The projection data of the IGCT were acquired in a single gantry rotation over 120 s. Three virtual phantoms-static Defrise, 4D Shepp-Logan, and 4D extended cardiac-torso (XCAT)-were used to obtain projection data for the IGCT and cone-beam computed tomography (CBCT). The projection acquisition parameters were determined to eliminate vacancies in the Radon space for an accurate rebinning process. Phase-based sorting was conducted within 10 phase bins, and the sorted projection data were binned into a cone beam geometry. Finally, Feldkamp-Davis-Kress reconstruction was conducted independently at each phase. The reconstructed images were compared using the structural similarity index measure (SSIM) and root mean square error (RMSE). The vertical profile of the Defrise reconstruction image was uniform, and the cone beam artefact was reduced in the IGCT image. Under an ideal projection acquisition condition, the mean coronal plane SSIMs of the Shepp-Logan and 4D XCAT phantoms were 0.899 and 0.706, respectively, which were higher than those of the CBCT (0.784 and 0.623, respectively). Similarly, the mean RMSEs of the coronal plane IGCT (0.036 and 0.158) exhibited an improvement over those of the CBCT (0.165 and 0.261, respectively). The mean standard deviations of the SSIM and RMSE were lower for IGCT than for CBCT. In particular, the SSIM and RMSE of the sagittal and coronal planes of the Shepp-Logan IGCT images were stable in all phase bins; however, those of the CBCT changed depending on the phase bins. Poor image quality was observed for IGCT under inappropriate conditions. This was caused by a vacancy in the Radon space, owing to an inappropriate scan setting. Overall, the proposed 4D IGCT exhibited better image quality than conventional CBCT.

Real-time control of respiratory motion: Beyond radiation therapy

Motion management in radiation oncology is an important aspect of modern treatment planning and delivery. Special attention has been paid to control respiratory motion in recent years. However, other medical procedures related to both diagnosis and treatment are likely to benefit from the explicit control of breathing motion. Quantitative imaging - including increasingly important tools in radiology and nuclear medicine - is among the fields where a rapid development of motion control is most likely, due to the need for quantification accuracy. Emerging treatment modalities like focussed-ultrasound tumor ablation are also likely to benefit from a significant evolution of motion control in the near future. In the present article an overview of available respiratory motion systems along with ongoing research in this area is provided. Furthermore, an attempt is made to envision some of the most expected developments in this field in the near future.