Low-dose cone-beam CT (LD-CBCT) reconstruction for image-guided radiation therapy (IGRT) by three-dimensional dual-dictionary learning.

ABSTRACT: BACKGROUND: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. METHODS:In 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. RESULTS:The mean peak signal to noise ratio of D-CBCT was 1.7?dB higher than SART-TV reconstructions (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. CONCLUSIONS:The 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.

SUBMITTER: Song Y 

PROVIDER: S-EPMC7425566 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature