Abstract
BackgroundTo develop a low-dose cone beam CT (LD-CBCT) reconstruction method named simultaneous algebraic reconstruction technique and dual-dictionary learning (SART-DDL) joint algorithm for image guided radiation therapy (IGRT) and evaluate its imaging quality and clinical application ability.MethodsIn this retrospective study, 62 CBCT image sets from February 2018 to July 2018 at west china hospital were randomly collected from 42 head and neck patients (mean [standard deviation] age, 49.7 [11.4] years, 12 females and 30 males). All image sets were retrospectively reconstructed by SART-DDL (resultant D-CBCT image sets) with 18% less clinical raw projections. Reconstruction quality was evaluated by quantitative parameters compared with SART and Total Variation minimization (SART-TV) joint reconstruction algorithm with paired t test. Five-grade subjective grading evaluations were done by two oncologists in a blind manner compared with clinically used Feldkamp-Davis-Kress algorithm CBCT images (resultant F-CBCT image sets) and the grading results were compared by paired Wilcoxon rank test. Registration results between D-CBCT and F-CBCT were compared. D-CBCT image geometry fidelity was tested.ResultsThe mean peak signal to noise ratio of D-CBCT was 1.7 dB higher than SART-TV reconstructions (P < .001, SART-DDL vs SART-TV, 36.36 ± 0.55 dB vs 34.68 ± 0.28 dB). All D-CBCT images were recognized as clinically acceptable without significant difference with F-CBCT in subjective grading (P > .05). In clinical registration, the maximum translational and rotational difference was 1.8 mm and 1.7 degree respectively. The horizontal, vertical and sagittal geometry fidelity of D-CBCT were acceptable.ConclusionsThe image quality, geometry fidelity and clinical application ability of D-CBCT are comparable to that of the F-CBCT for head-and-neck patients with 18% less projections by SART-DDL.
Highlights
To develop a low-dose cone beam CT (LD-CBCT) reconstruction method named simultaneous algebraic reconstruction technique and dual-dictionary learning (SART-dual dictionary learning (DDL)) joint algorithm for image guided radiation therapy (IGRT) and evaluate its imaging quality and clinical application ability
The image quality, geometry fidelity and clinical application ability of SART-DDL CBCT (D-CBCT) are comparable to that of the Feldkamp-Davis-Kress algorithm CBCT (F-CBCT) for head-and-neck patients with 18% less projections by SART-DDL
We considered to employ the dual dictionary learning (DDL) strategy, which takes advantages of a paired atom that consists of anatomical structures from both F-CBCT and LDCBCT images
Summary
To develop a low-dose cone beam CT (LD-CBCT) reconstruction method named simultaneous algebraic reconstruction technique and dual-dictionary learning (SART-DDL) joint algorithm for image guided radiation therapy (IGRT) and evaluate its imaging quality and clinical application ability. On-board CBCT which provides volumetric information of a patient at treatment position is valuable for accurate patient setup before the treatment. CBCT imaging would be repeatedly applied to a patient during the IGRT treatment course for over 25 times in common. It raises a great concern that repeated CBCT scans deliver too much dose to the patient at 3 ∼ 5 cGy per scan and 90 ∼ 150 cGy if scanned daily for Varian on-board imager [4] and the isocenter doses ranged between 0.1 and 2.2 cGy per scan for the Elekta X-ray volumetric imager [5]. Previous study pointed out that daily CBCT scan for IGRT could increase the secondary cancer risk by 2% up to 4% [7]. There is great significance to reduce the CBCT delivery dose while remaining the reconstruction quality
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
