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

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. Met...

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Veröffentlicht in:Radiation oncology (London, England) Jg. 15; H. 1; S. 1 - 9
Hauptverfasser: Song, Ying, Zhang, Weikang, Zhang, Hong, Wang, Qiang, Xiao, Qing, Li, Zhibing, Wei, Xing, Lai, Jialu, Wang, Xuetao, Li, Wan, Zhong, Quan, Gong, Pan, Zhong, Renming, Zhao, Jun
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London BioMed Central 12.08.2020
Springer Nature B.V
BMC
Schlagworte:
Acceptable noise levels
Accuracy
Algorithms
Biomedical and Life Sciences
Biomedicine
Cancer Research
CBCT reconstruction
Clinical Radiation Oncology
Computed tomography
Dictionaries
Dictionary learning
Evaluation
Geometry
Head & neck cancer
Head and neck
Image processing
Image quality
Image reconstruction
Imaging
Low dose
Machine learning
Mathematical analysis
Medical imaging
Neck
Noise levels
Object recognition
Oncology
Patients
Quality
Radiation
Radiation therapy
Radiology
Radiotherapy
Rank tests
Registration
Signal to noise ratio
United States > US
Radiation therapy
CBCT reconstruction
Low dose
Dictionary learning
ISSN:1748-717X, 1748-717X
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Zusammenfassung: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  < .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. 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.
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ISSN:1748-717X
1748-717X
DOI:10.1186/s13014-020-01630-3