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Vergalasova I, Cai J. A modern review of the uncertainties in volumetric imaging of respiratory-induced target motion in lung radiotherapy. Med Phys 2020; 47:e988-e1008. [PMID: 32506452 DOI: 10.1002/mp.14312] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Revised: 05/15/2020] [Accepted: 05/26/2020] [Indexed: 12/25/2022] Open
Abstract
Radiotherapy has become a critical component for the treatment of all stages and types of lung cancer, often times being the primary gateway to a cure. However, given that radiation can cause harmful side effects depending on how much surrounding healthy tissue is exposed, treatment of the lung can be particularly challenging due to the presence of moving targets. Careful implementation of every step in the radiotherapy process is absolutely integral for attaining optimal clinical outcomes. With the advent and now widespread use of stereotactic body radiation therapy (SBRT), where extremely large doses are delivered, accurate, and precise dose targeting is especially vital to achieve an optimal risk to benefit ratio. This has largely become possible due to the rapid development of image-guided technology. Although imaging is critical to the success of radiotherapy, it can often be plagued with uncertainties due to respiratory-induced target motion. There has and continues to be an immense research effort aimed at acknowledging and addressing these uncertainties to further our abilities to more precisely target radiation treatment. Thus, the goal of this article is to provide a detailed review of the prevailing uncertainties that remain to be investigated across the different imaging modalities, as well as to highlight the more modern solutions to imaging motion and their role in addressing the current challenges.
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Affiliation(s)
- Irina Vergalasova
- Department of Radiation Oncology, Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ, USA
| | - Jing Cai
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong
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Choi S, Lee S, Kang YN, Hsieh SS, Kim HJ. 4D digital tomosynthesis image reconstruction using brute force-based adaptive total variation (BF-ATV) in a prototype LINAC system. Phys Med Biol 2019; 64:095029. [PMID: 30840940 DOI: 10.1088/1361-6560/ab0d50] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Respiratory-correlated cone-beam CT (CBCT) not only inhibits rapid scanning due to the slow speed of the LINAC head gantry rotation, but its implementation for routine patient imaging is impractical because of the high radiation dose delivered during the process. Digital tomosynthesis (DTS) is a potentially faster technique that delivers a much lower radiation dose by reducing the number of projections in a limited angular range. Unfortunately, 4D-DTS introduces strong aliasing artifacts in the reconstructed images due to the sparsely sampled projections in each respiratory phase bin. The authors hereby suggest a novel low-dose 4D-DTS image reconstruction method that achieves a compromise between the occurrence of aliasing artifacts and image smoothing using a brute force-based adaptive weighting parameter searching technique. We used a prototype LINAC system mounted with a flat-panel detector to acquire tomosynthesis projections of respiratory motion in a phantom in the anterior-posterior (AP) and lateral views. Three different 4D-DTS image reconstruction schemes that included conventional filtered back-projection (FBP), adaptive steepest descent projection onto convex sets (ASD-POCS), and the proposed brute force-based adaptive total variation (BF-ATV) were implemented in four different respiratory phase bins for both AP and lateral views. All reconstructions were accelerated using a single GPU card to reduce the computation time. To study the performance of the algorithm under various sparse conditions, we operated the prototype system in three different gantry sweep modes. The results indicate that the proposed BF-ATV method yields the largest structural similarities in the differenced image between the ground-truth dataset acquired using the slow gantry sweep mode and the sparse dataset from both moderate and fast sweep modes. In addition, the proposed method maintained the object sharpness with less streaking lines and small loss of sharpness compared to the conventional FBP and ASD-POCS methods. In conclusion, the proposed low-dose 4D-DTS reconstruction scheme may provide better performance due in part to its rapid scanning. Therefore, it is potentially applicable to practical 4D imaging for radiotherapy.
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Affiliation(s)
- Sunghoon Choi
- Department of Radiological Science, College of Health Science, Yonsei University, 1 Yonseidae-gil, Wonju 26493, Republic of Korea
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Kim DS, Lee S, Kim TH, Kang SH, Kim KH, Shin DS, Kim S, Suh TS. A respiratory-guided 4D digital tomosynthesis. ACTA ACUST UNITED AC 2018; 63:245007. [DOI: 10.1088/1361-6560/aaeddb] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
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Shimizu Y, Takamatsu S, Yamamoto K, Maeda Y, Sasaki M, Tamamura H, Bou S, Kumano T, Gabata T. Segmental analysis of respiratory liver motion in patients with and without a history of abdominal surgery. Jpn J Radiol 2018; 36:511-518. [DOI: 10.1007/s11604-018-0750-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2018] [Accepted: 06/04/2018] [Indexed: 10/28/2022]
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Hazelaar C, Dahele M, Mostafavi H, van der Weide L, Slotman B, Verbakel W. Markerless positional verification using template matching and triangulation of kV images acquired during irradiation for lung tumors treated in breath-hold. ACTA ACUST UNITED AC 2018; 63:115005. [DOI: 10.1088/1361-6560/aac1a9] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
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Zhang Y, Ren L, Vergalasova I, Yin FF. Clinical Study of Orthogonal-View Phase-Matched Digital Tomosynthesis for Lung Tumor Localization. Technol Cancer Res Treat 2017; 16:866-878. [PMID: 28449625 PMCID: PMC5547009 DOI: 10.1177/1533034617705716] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Background and Purpose: Compared to cone-beam computed tomography, digital tomosynthesis imaging has the benefits of shorter scanning time, less imaging dose, and better mechanical clearance for tumor localization in radiation therapy. However, for lung tumors, the localization accuracy of the conventional digital tomosynthesis technique is affected by the lack of depth information and the existence of lung tumor motion. This study investigates the clinical feasibility of using an orthogonal-view phase-matched digital tomosynthesis technique to improve the accuracy of lung tumor localization. Materials and Methods: The proposed orthogonal-view phase-matched digital tomosynthesis technique benefits from 2 major features: (1) it acquires orthogonal-view projections to improve the depth information in reconstructed digital tomosynthesis images and (2) it applies respiratory phase-matching to incorporate patient motion information into the synthesized reference digital tomosynthesis sets, which helps to improve the localization accuracy of moving lung tumors. A retrospective study enrolling 14 patients was performed to evaluate the accuracy of the orthogonal-view phase-matched digital tomosynthesis technique. Phantom studies were also performed using an anthropomorphic phantom to investigate the feasibility of using intratreatment aggregated kV and beams’ eye view cine MV projections for orthogonal-view phase-matched digital tomosynthesis imaging. The localization accuracy of the orthogonal-view phase-matched digital tomosynthesis technique was compared to that of the single-view digital tomosynthesis techniques and the digital tomosynthesis techniques without phase-matching. Results: The orthogonal-view phase-matched digital tomosynthesis technique outperforms the other digital tomosynthesis techniques in tumor localization accuracy for both the patient study and the phantom study. For the patient study, the orthogonal-view phase-matched digital tomosynthesis technique localizes the tumor to an average (± standard deviation) error of 1.8 (0.7) mm for a 30° total scan angle. For the phantom study using aggregated kV–MV projections, the orthogonal-view phase-matched digital tomosynthesis localizes the tumor to an average error within 1 mm for varying magnitudes of scan angles. Conclusion: The pilot clinical study shows that the orthogonal-view phase-matched digital tomosynthesis technique enables fast and accurate localization of moving lung tumors.
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Affiliation(s)
- You Zhang
- Medical Physics Graduate Program, Duke University, Durham, NC, USA
| | - Lei Ren
- Medical Physics Graduate Program, Duke University, Durham, NC, USA.,Department of Radiation Oncology, Duke University Medical Center, Durham, NC, USA
| | - Irina Vergalasova
- Department of Radiation Oncology, Duke University Medical Center, Durham, NC, USA
| | - Fang-Fang Yin
- Medical Physics Graduate Program, Duke University, Durham, NC, USA.,Department of Radiation Oncology, Duke University Medical Center, Durham, NC, USA
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Chao M, Wei J, Li T, Yuan Y, Rosenzweig KE, Lo YC. Robust breathing signal extraction from cone beam CT projections based on adaptive and global optimization techniques. Phys Med Biol 2016; 61:3109-26. [PMID: 27008349 DOI: 10.1088/0031-9155/61/8/3109] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
We present a study of extracting respiratory signals from cone beam computed tomography (CBCT) projections within the framework of the Amsterdam Shroud (AS) technique. Acquired prior to the radiotherapy treatment, CBCT projections were preprocessed for contrast enhancement by converting the original intensity images to attenuation images with which the AS image was created. An adaptive robust z-normalization filtering was applied to further augment the weak oscillating structures locally. From the enhanced AS image, the respiratory signal was extracted using a two-step optimization approach to effectively reveal the large-scale regularity of the breathing signals. CBCT projection images from five patients acquired with the Varian Onboard Imager on the Clinac iX System Linear Accelerator (Varian Medical Systems, Palo Alto, CA) were employed to assess the proposed technique. Stable breathing signals can be reliably extracted using the proposed algorithm. Reference waveforms obtained using an air bellows belt (Philips Medical Systems, Cleveland, OH) were exported and compared to those with the AS based signals. The average errors for the enrolled patients between the estimated breath per minute (bpm) and the reference waveform bpm can be as low as -0.07 with the standard deviation 1.58. The new algorithm outperformed the original AS technique for all patients by 8.5% to 30%. The impact of gantry rotation on the breathing signal was assessed with data acquired with a Quasar phantom (Modus Medical Devices Inc., London, Canada) and found to be minimal on the signal frequency. The new technique developed in this work will provide a practical solution to rendering markerless breathing signal using the CBCT projections for thoracic and abdominal patients.
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Affiliation(s)
- Ming Chao
- Department of Radiation Oncology, Mount Sinai Medical Center, New York, NY 10029, USA
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Yan H, Dai JR. A software tool of digital tomosynthesis application for patient positioning in radiotherapy. J Appl Clin Med Phys 2016; 17:174-193. [PMID: 27074482 PMCID: PMC5874927 DOI: 10.1120/jacmp.v17i2.5999] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2015] [Revised: 11/09/2015] [Accepted: 11/04/2015] [Indexed: 11/29/2022] Open
Abstract
Digital Tomosynthesis (DTS) is an image modality in reconstructing tomographic images from two‐dimensional kV projections covering a narrow scan angles. Comparing with conventional cone‐beam CT (CBCT), it requires less time and radiation dose in data acquisition. It is feasible to apply this technique in patient positioning in radiotherapy. To facilitate its clinical application, a software tool was developed and the reconstruction processes were accelerated by graphic processing unit (GPU). Two reconstruction and two registration processes are required for DTS application which is different from conventional CBCT application which requires one image reconstruction process and one image registration process. The reconstruction stage consists of productions of two types of DTS. One type of DTS is reconstructed from cone‐beam (CB) projections covering a narrow scan angle and is named onboard DTS (ODTS), which represents the real patient position in treatment room. Another type of DTS is reconstructed from digitally reconstructed radiography (DRR) and is named reference DTS (RDTS), which represents the ideal patient position in treatment room. Prior to the reconstruction of RDTS, The DRRs are reconstructed from planning CT using the same acquisition setting of CB projections. The registration stage consists of two matching processes between ODTS and RDTS. The target shift in lateral and longitudinal axes are obtained from the matching between ODTS and RDTS in coronal view, while the target shift in longitudinal and vertical axes are obtained from the matching between ODTS and RDTS in sagittal view. In this software, both DRR and DTS reconstruction algorithms were implemented on GPU environments for acceleration purpose. The comprehensive evaluation of this software tool was performed including geometric accuracy, image quality, registration accuracy, and reconstruction efficiency. The average correlation coefficient between DRR/DTS generated by GPU‐based algorithm and CPU‐based algorithm is 0.99. Based on the measurements of cube phantom on DTS, the geometric errors are within 0.5 mm in three axes. For both cube phantom and pelvic phantom, the registration errors are within 0.5 mm in three axes. Compared with reconstruction performance of CPU‐based algorithms, the performances of DRR and DTS reconstructions are improved by a factor of 15 to 20. A GPU‐based software tool was developed for DTS application for patient positioning of radiotherapy. The geometric and registration accuracy met the clinical requirement in patient setup of radiotherapy. The high performance of DRR and DTS reconstruction algorithms was achieved by the GPU‐based computation environments. It is a useful software tool for researcher and clinician in evaluating DTS application in patient positioning of radiotherapy. PACS number(s): 87.57.nf
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Affiliation(s)
- Hui Yan
- Cancer Hospital Chinese Academy of Medical Sciences.
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Hess CB, Thompson HM, Benedict SH, Seibert JA, Wong K, Vaughan AT, Chen AM. Exposure Risks Among Children Undergoing Radiation Therapy: Considerations in the Era of Image Guided Radiation Therapy. Int J Radiat Oncol Biol Phys 2016; 94:978-92. [PMID: 27026304 DOI: 10.1016/j.ijrobp.2015.12.372] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2015] [Revised: 11/30/2015] [Accepted: 12/22/2015] [Indexed: 12/14/2022]
Abstract
Recent improvements in toxicity profiles of pediatric oncology patients are attributable, in part, to advances in the field of radiation oncology such as intensity modulated radiation (IMRT) and proton therapy (IMPT). While IMRT and IMPT deliver highly conformal dose to targeted volumes, they commonly demand the addition of 2- or 3-dimensional imaging for precise positioning--a technique known as image guided radiation therapy (IGRT). In this manuscript we address strategies to further minimize exposure risk in children by reducing effective IGRT dose. Portal X rays and cone beam computed tomography (CBCT) are commonly used to verify patient position during IGRT and, because their relative radiation exposure is far less than the radiation absorbed from therapeutic treatment beams, their sometimes significant contribution to cumulative risk can be easily overlooked. Optimizing the conformality of IMRT/IMPT while simultaneously ignoring IGRT dose may result in organs at risk being exposed to a greater proportion of radiation from IGRT than from therapeutic beams. Over a treatment course, cumulative central-axis CBCT effective dose can approach or supersede the amount of radiation absorbed from a single treatment fraction, a theoretical increase of 3% to 5% in mutagenic risk. In select scenarios, this may result in the underprediction of acute and late toxicity risk (such as azoospermia, ovarian dysfunction, or increased lifetime mutagenic risk) in radiation-sensitive organs and patients. Although dependent on variables such as patient age, gender, weight, body habitus, anatomic location, and dose-toxicity thresholds, modifying IGRT use and acquisition parameters such as frequency, imaging modality, beam energy, current, voltage, rotational degree, collimation, field size, reconstruction algorithm, and documentation can reduce exposure, avoid unnecessary toxicity, and achieve doses as low as reasonably achievable, promoting a culture and practice of "gentle IGRT."
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Affiliation(s)
- Clayton B Hess
- Department of Radiation Oncology, University California Davis Comprehensive Cancer Center, Sacramento, California
| | - Holly M Thompson
- Department of Diagnostic Radiology, University of California Davis Medical Center, Sacramento, California
| | - Stanley H Benedict
- Department of Radiation Oncology, University California Davis Comprehensive Cancer Center, Sacramento, California
| | - J Anthony Seibert
- Department of Diagnostic Radiology, University of California Davis Medical Center, Sacramento, California
| | - Kenneth Wong
- Department of Radiation Oncology, University of California Los Angeles Jonsson Comprehensive Cancer Center, University of California David Geffen School of Medicine, Los Angeles, California
| | - Andrew T Vaughan
- Department of Radiation Oncology, University California Davis Comprehensive Cancer Center, Sacramento, California
| | - Allen M Chen
- Department of Radiation Oncology, University of California Los Angeles Jonsson Comprehensive Cancer Center, University of California David Geffen School of Medicine, Los Angeles, California.
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