Literature DB >> 28338470

Reducing scan angle using adaptive prior knowledge for a limited-angle intrafraction verification (LIVE) system for conformal arc radiotherapy.

Yawei Zhang1, Fang-Fang Yin, You Zhang, Lei Ren.   

Abstract

The purpose of this study is to develop an adaptive prior knowledge guided image estimation technique to reduce the scan angle needed in the limited-angle intrafraction verification (LIVE) system for 4D-CBCT reconstruction. The LIVE system has been previously developed to reconstruct 4D volumetric images on-the-fly during arc treatment for intrafraction target verification and dose calculation. In this study, we developed an adaptive constrained free-form deformation reconstruction technique in LIVE to further reduce the scanning angle needed to reconstruct the 4D-CBCT images for faster intrafraction verification. This technique uses free form deformation with energy minimization to deform prior images to estimate 4D-CBCT based on kV-MV projections acquired in extremely limited angle (orthogonal 3°) during the treatment. Note that the prior images are adaptively updated using the latest CBCT images reconstructed by LIVE during treatment to utilize the continuity of the respiratory motion. The 4D digital extended-cardiac-torso (XCAT) phantom and a CIRS 008A dynamic thoracic phantom were used to evaluate the effectiveness of this technique. The reconstruction accuracy of the technique was evaluated by calculating both the center-of-mass-shift (COMS) and 3D volume-percentage-difference (VPD) of the tumor in reconstructed images and the true on-board images. The performance of the technique was also assessed with varied breathing signals against scanning angle, lesion size, lesion location, projection sampling interval, and scanning direction. In the XCAT study, using orthogonal-view of 3° kV and portal MV projections, this technique achieved an average tumor COMS/VPD of 0.4  ±  0.1 mm/5.5  ±  2.2%, 0.6  ±  0.3 mm/7.2  ±  2.8%, 0.5  ±  0.2 mm/7.1  ±  2.6%, 0.6  ±  0.2 mm/8.3  ±  2.4%, for baseline drift, amplitude variation, phase shift, and patient breathing signal variation, respectively. In the CIRS phantom study, this technique achieved an average tumor COMS/VPD of 0.7  ±  0.1 mm/7.5  ±  1.3% for a 3 cm lesion and 0.6  ±  0.2 mm/11.4  ±  1.5% for a 2 cm lesion in the baseline drift case. The average tumor COMS/VPD were 0.5  ±  0.2 mm/10.8  ±  1.4%, 0.4  ±  0.3 mm/7.3  ±  2.9%, 0.4  ±  0.2 mm/7.4  ±  2.5%, 0.4  ±  0.2 mm/7.3  ±  2.8% for the four real patient breathing signals, respectively. Results demonstrated that the adaptive prior knowledge guided image estimation technique with LIVE system is robust against scanning angle, lesion size, location and scanning direction. It can estimate on-board images accurately with as little as 6 projections in orthogonal-view 3° angle. In conclusion, adaptive prior knowledge guided image reconstruction technique accurately estimates 4D-CBCT images using extremely-limited angle and projections. This technique greatly improves the efficiency and accuracy of LIVE system for ultrafast 4D intrafraction verification of lung SBRT treatments.

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Year:  2017        PMID: 28338470      PMCID: PMC5543931          DOI: 10.1088/1361-6560/aa6913

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  34 in total

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Review 2.  Digital x-ray tomosynthesis: current state of the art and clinical potential.

Authors:  James T Dobbins; Devon J Godfrey
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3.  Respiratory correlated cone beam CT.

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4.  Linac-integrated 4D cone beam CT: first experimental results.

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Review 5.  Adaptive radiotherapy for lung cancer.

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6.  Stereotactic ablative radiotherapy versus lobectomy for operable stage I non-small-cell lung cancer: a pooled analysis of two randomised trials.

Authors:  Joe Y Chang; Suresh Senan; Marinus A Paul; Reza J Mehran; Alexander V Louie; Peter Balter; Harry J M Groen; Stephen E McRae; Joachim Widder; Lei Feng; Ben E E M van den Borne; Mark F Munsell; Coen Hurkmans; Donald A Berry; Erik van Werkhoven; John J Kresl; Anne-Marie Dingemans; Omar Dawood; Cornelis J A Haasbeek; Larry S Carpenter; Katrien De Jaeger; Ritsuko Komaki; Ben J Slotman; Egbert F Smit; Jack A Roth
Journal:  Lancet Oncol       Date:  2015-05-13       Impact factor: 41.316

7.  Stereotactic radiotherapy for primary lung cancer and pulmonary metastases: a noninvasive treatment approach in medically inoperable patients.

Authors:  Joern Wulf; Ulrich Haedinger; Ulrich Oppitz; Wibke Thiele; Gerd Mueller; Michael Flentje
Journal:  Int J Radiat Oncol Biol Phys       Date:  2004-09-01       Impact factor: 7.038

8.  Automatic registration between reference and on-board digital tomosynthesis images for positioning verification.

Authors:  Lei Ren; Devon J Godfrey; Hui Yan; Q Jackie Wu; Fang-Fang Yin
Journal:  Med Phys       Date:  2008-02       Impact factor: 4.071

9.  Dosimetric verification of lung cancer treatment using the CBCTs estimated from limited-angle on-board projections.

Authors:  You Zhang; Fang-Fang Yin; Lei Ren
Journal:  Med Phys       Date:  2015-08       Impact factor: 4.071

Review 10.  Megavoltage cone-beam CT: system description and clinical applications.

Authors:  Olivier Morin; Amy Gillis; Josephine Chen; Michèle Aubin; M Kara Bucci; Mack Roach; Jean Pouliot
Journal:  Med Dosim       Date:  2006       Impact factor: 1.482

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  15 in total

1.  Technical Note: Imaging dose resulting from optimized procedures with limited-angle intrafractional verification system during stereotactic body radiation therapy lung treatment.

Authors:  George X Ding; Yawei Zhang; Lei Ren
Journal:  Med Phys       Date:  2019-04-29       Impact factor: 4.071

2.  Development of realistic multi-contrast textured XCAT (MT-XCAT) phantoms using a dual-discriminator conditional-generative adversarial network (D-CGAN).

Authors:  Yushi Chang; Kyle Lafata; William Paul Segars; Fang-Fang Yin; Lei Ren
Journal:  Phys Med Biol       Date:  2020-03-19       Impact factor: 3.609

3.  Augmentation of CBCT Reconstructed From Under-Sampled Projections Using Deep Learning.

Authors:  Zhuoran Jiang; Yingxuan Chen; Yawei Zhang; Yun Ge; Fang-Fang Yin; Lei Ren
Journal:  IEEE Trans Med Imaging       Date:  2019-04-23       Impact factor: 10.048

4.  Predicting real-time 3D deformation field maps (DFM) based on volumetric cine MRI (VC-MRI) and artificial neural networks for on-board 4D target tracking: a feasibility study.

Authors:  Jonathan Pham; Wendy Harris; Wenzheng Sun; Zi Yang; Fang-Fang Yin; Lei Ren
Journal:  Phys Med Biol       Date:  2019-08-21       Impact factor: 3.609

5.  Low dose CBCT reconstruction via prior contour based total variation (PCTV) regularization: a feasibility study.

Authors:  Yingxuan Chen; Fang-Fang Yin; Yawei Zhang; You Zhang; Lei Ren
Journal:  Phys Med Biol       Date:  2018-04-19       Impact factor: 3.609

6.  Image acquisition optimization of a limited-angle intrafraction verification (LIVE) system for lung radiotherapy.

Authors:  Yawei Zhang; Xinchen Deng; Fang-Fang Yin; Lei Ren
Journal:  Med Phys       Date:  2017-11-30       Impact factor: 4.071

7.  First clinical retrospective investigation of limited projection CBCT for lung tumor localization in patients receiving SBRT treatment.

Authors:  Yawei Zhang; Fang-Fang Yin; Lei Ren
Journal:  Phys Med Biol       Date:  2019-05-08       Impact factor: 3.609

8.  Low dose cone-beam computed tomography reconstruction via hybrid prior contour based total variation regularization (hybrid-PCTV).

Authors:  Yingxuan Chen; Fang-Fang Yin; Yawei Zhang; You Zhang; Lei Ren
Journal:  Quant Imaging Med Surg       Date:  2019-07

9.  Enhancing digital tomosynthesis (DTS) for lung radiotherapy guidance using patient-specific deep learning model.

Authors:  Zhuoran Jiang; Fang-Fang Yin; Yun Ge; Lei Ren
Journal:  Phys Med Biol       Date:  2021-01-26       Impact factor: 3.609

10.  Daily edge deformation prediction using an unsupervised convolutional neural network model for low dose prior contour based total variation CBCT reconstruction (PCTV-CNN).

Authors:  Yingxuan Chen; Fang-Fang Yin; Zhuoran Jiang; Lei Ren
Journal:  Biomed Phys Eng Express       Date:  2019-10-07
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