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

PURPOSE Lung cancer treatment is susceptible to treatment errors caused by interfractional anatomical and respirational variations of the patient. On-board treatment dose verification is especially critical for the lung stereotactic body radiation therapy due to its high fractional dose. This study investigates the feasibility of using cone-beam (CB)CT images estimated by a motion modeling and free-form deformation (MM-FD) technique for on-board dose verification. METHODS Both digital and physical phantom studies were performed. Various interfractional variations featuring patient motion pattern change, tumor size change, and tumor average position change were simulated from planning CT to on-board images. The doses calculated on the planning CT (planned doses), the on-board CBCT estimated by MM-FD (MM-FD doses), and the on-board CBCT reconstructed by the conventional Feldkamp-Davis-Kress (FDK) algorithm (FDK doses) were compared to the on-board dose calculated on the "gold-standard" on-board images (gold-standard doses). The absolute deviations of minimum dose (ΔDmin), maximum dose (ΔDmax), and mean dose (ΔDmean), and the absolute deviations of prescription dose coverage (ΔV100%) were evaluated for the planning target volume (PTV). In addition, 4D on-board treatment dose accumulations were performed using 4D-CBCT images estimated by MM-FD in the physical phantom study. The accumulated doses were compared to those measured using optically stimulated luminescence (OSL) detectors and radiochromic films. RESULTS Compared with the planned doses and the FDK doses, the MM-FD doses matched much better with the gold-standard doses. For the digital phantom study, the average (± standard deviation) ΔDmin, ΔDmax, ΔDmean, and ΔV100% (values normalized by the prescription dose or the total PTV) between the planned and the gold-standard PTV doses were 32.9% (±28.6%), 3.0% (±2.9%), 3.8% (±4.0%), and 15.4% (±12.4%), respectively. The corresponding values of FDK PTV doses were 1.6% (±1.9%), 1.2% (±0.6%), 2.2% (±0.8%), and 17.4% (±15.3%), respectively. In contrast, the corresponding values of MM-FD PTV doses were 0.3% (±0.2%), 0.9% (±0.6%), 0.6% (±0.4%), and 1.0% (±0.8%), respectively. Similarly, for the physical phantom study, the average ΔDmin, ΔDmax, ΔDmean, and ΔV100% of planned PTV doses were 38.1% (±30.8%), 3.5% (±5.1%), 3.0% (±2.6%), and 8.8% (±8.0%), respectively. The corresponding values of FDK PTV doses were 5.8% (±4.5%), 1.6% (±1.6%), 2.0% (±0.9%), and 9.3% (±10.5%), respectively. In contrast, the corresponding values of MM-FD PTV doses were 0.4% (±0.8%), 0.8% (±1.0%), 0.5% (±0.4%), and 0.8% (±0.8%), respectively. For the 4D dose accumulation study, the average (± standard deviation) absolute dose deviation (normalized by local doses) between the accumulated doses and the OSL measured doses was 3.3% (±2.7%). The average gamma index (3%/3 mm) between the accumulated doses and the radiochromic film measured doses was 94.5% (±2.5%). CONCLUSIONS MM-FD estimated 4D-CBCT enables accurate on-board dose calculation and accumulation for lung radiation therapy. It can potentially be valuable for treatment quality assessment and adaptive radiation therapy.

[1]  Myonggeun Yoon,et al.  Imaging Doses and Secondary Cancer Risk From Kilovoltage Cone-beam CT in Radiation Therapy , 2013, Health physics.

[2]  Fang-Fang Yin,et al.  Adaptive Radiation Therapy: Technical Components and Clinical Applications , 2011, Cancer journal.

[3]  Frank Bergner,et al.  An investigation of 4D cone-beam CT algorithms for slowly rotating scanners. , 2010, Medical physics.

[4]  F. Yin,et al.  Adaptive stereotactic body radiation therapy planning for lung cancer. , 2013, International Journal of Radiation Oncology, Biology, Physics.

[5]  Jian Zhu,et al.  Radiotherapy dose calculation on KV cone‐beam CT image for lung tumor using the CIRS calibration , 2014, Thoracic cancer.

[6]  Lei Xing,et al.  Evaluation of the deformation and corresponding dosimetric implications in prostate cancer treatment , 2012, Physics in medicine and biology.

[7]  Xuejun Gu,et al.  Simultaneous motion estimation and image reconstruction (SMEIR) for 4D cone-beam CT , 2013, 2013 IEEE Nuclear Science Symposium and Medical Imaging Conference (2013 NSS/MIC).

[8]  M. Gillin,et al.  Energy dependence and dose response of Gafchromic EBT2 film over a wide range of photon, electron, and proton beam energies. , 2010, Medical physics.

[9]  W P Segars,et al.  Realistic CT simulation using the 4D XCAT phantom. , 2008, Medical physics.

[10]  Patrick A Kupelian,et al.  A technique for adaptive image-guided helical tomotherapy for lung cancer. , 2006, International journal of radiation oncology, biology, physics.

[11]  Y. Shibamoto,et al.  Clinical outcomes of 3D conformal hypofractionated single high-dose radiotherapy for one or two lung tumors using a stereotactic body frame. , 2001, International journal of radiation oncology, biology, physics.

[12]  L. Feldkamp,et al.  Practical cone-beam algorithm , 1984 .

[13]  M. Murphy,et al.  4D Cone-beam CT reconstruction using a motion model based on principal component analysis. , 2011, Medical physics.

[14]  Fang-Fang Yin,et al.  On-Line Adaptive Radiation Therapy: Feasibility and Clinical Study , 2010, Journal of oncology.

[15]  Michael Velec,et al.  Accumulated dose in liver stereotactic body radiotherapy: positioning, breathing, and deformation effects. , 2012, International journal of radiation oncology, biology, physics.

[16]  Cedric X. Yu,et al.  Guidance document on delivery, treatment planning, and clinical implementation of IMRT: report of the IMRT Subcommittee of the AAPM Radiation Therapy Committee. , 2003, Medical physics.

[17]  Steve B. Jiang,et al.  Synchronized moving aperture radiation therapy (SMART): improvement of breathing pattern reproducibility using respiratory coaching , 2006, Physics in medicine and biology.

[18]  Guang-Hong Chen,et al.  Prior image constrained compressed sensing (PICCS) , 2008, SPIE BiOS.

[19]  Fang-Fang Yin,et al.  Potential underestimation of the internal target volume (ITV) from free-breathing CBCT. , 2011, Medical physics.

[20]  Lech Papiez,et al.  Stereotactic body radiation therapy for early-stage non-small-cell lung carcinoma: four-year results of a prospective phase II study. , 2009, International journal of radiation oncology, biology, physics.

[21]  Matthias Guckenberger,et al.  Investigation of the usability of conebeam CT data sets for dose calculation , 2008, Radiation oncology.

[22]  D. Low,et al.  A technique for the quantitative evaluation of dose distributions. , 1998, Medical physics.

[23]  W. Tomé,et al.  Dose calculation on kV cone beam CT images: an investigation of the Hu-density conversion stability and dose accuracy using the site-specific calibration. , 2010, Medical dosimetry : official journal of the American Association of Medical Dosimetrists.

[24]  Fang-Fang Yin,et al.  Preliminary clinical evaluation of a 4D-CBCT estimation technique using prior information and limited-angle projections. , 2015, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[25]  E G Yukihara,et al.  Optically stimulated luminescence (OSL) dosimetry in medicine , 2008, Physics in medicine and biology.

[26]  Fang-Fang Yin,et al.  A novel digital tomosynthesis (DTS) reconstruction method using a deformation field map. , 2008, Medical physics.

[27]  Mauro Iori,et al.  Testing of the analytical anisotropic algorithm for photon dose calculation. , 2006, Medical physics.

[28]  Fang-Fang Yin,et al.  A technique for estimating 4D-CBCT using prior knowledge and limited-angle projections. , 2013, Medical physics.

[29]  Fang-Fang Yin,et al.  Comparing digital tomosynthesis to cone-beam CT for position verification in patients undergoing partial breast irradiation. , 2009, International journal of radiation oncology, biology, physics.

[30]  Boyd McCurdy,et al.  Cone beam computerized tomography: the effect of calibration of the Hounsfield unit number to electron density on dose calculation accuracy for adaptive radiation therapy , 2009, Physics in medicine and biology.

[31]  Hui Yan,et al.  Development and clinical evaluation of a three-dimensional cone-beam computed tomography estimation method using a deformation field map. , 2012, International journal of radiation oncology, biology, physics.

[32]  Jing Wang,et al.  High-quality four-dimensional cone-beam CT by deforming prior images. , 2013, Physics in medicine and biology.

[33]  Xun Jia,et al.  Four-dimensional cone beam CT reconstruction and enhancement using a temporal nonlocal means method. , 2012, Medical physics.

[34]  D. Hallahan,et al.  A study on adaptive IMRT treatment planning using kV cone-beam CT. , 2007, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[35]  Steve B. Jiang,et al.  The management of respiratory motion in radiation oncology report of AAPM Task Group 76. , 2006, Medical physics.

[36]  Steve B. Jiang,et al.  The management of respiratory motion in radiation oncology report of AAPM Task Group 76. , 2006, Medical physics.

[37]  R. Emery,et al.  Clinical experience using respiratory gated radiation therapy: comparison of free-breathing and breath-hold techniques. , 2004, International journal of radiation oncology, biology, physics.

[38]  Fang-Fang Yin,et al.  Dosimetric feasibility of cone-beam CT-based treatment planning compared to CT-based treatment planning. , 2006, International journal of radiation oncology, biology, physics.

[39]  Huaiqun Guan,et al.  Dose calculation accuracy using cone-beam CT (CBCT) for pelvic adaptive radiotherapy , 2009, Physics in medicine and biology.

[40]  Fang-Fang Yin,et al.  A limited-angle intrafraction verification (LIVE) system for radiation therapy. , 2014, Medical physics.

[41]  Lei Xing,et al.  Evaluation of on-board kV cone beam CT (CBCT)-based dose calculation , 2007, Physics in medicine and biology.

[42]  Steve B. Jiang,et al.  Real-time volumetric image reconstruction and 3D tumor localization based on a single x-ray projection image for lung cancer radiotherapy. , 2010, Medical physics.

[43]  G S Bauman,et al.  Tracking the dose distribution in radiation therapy by accounting for variable anatomy , 2004, Physics in medicine and biology.

[44]  G. Christensen,et al.  A method for the reconstruction of four-dimensional synchronized CT scans acquired during free breathing. , 2003, Medical physics.

[45]  D. Jaffray,et al.  Advances in image-guided radiation therapy. , 2007, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[46]  Radhe Mohan,et al.  Audio-visual biofeedback for respiratory-gated radiotherapy: impact of audio instruction and audio-visual biofeedback on respiratory-gated radiotherapy. , 2006, International journal of radiation oncology, biology, physics.

[47]  Jing Cai,et al.  Establishing a framework to implement 4D XCAT phantom for 4D radiotherapy research. , 2012, Journal of cancer research and therapeutics.

[48]  Steve B. Jiang,et al.  Measurement of the interplay effect in lung IMRT treatment using EDR2 films , 2006, Journal of applied clinical medical physics.

[49]  Lei Xing,et al.  Formulating adaptive radiation therapy (ART) treatment planning into a closed-loop control framework , 2007, Physics in medicine and biology.

[50]  Andrea Bezjak,et al.  Cone-beam computed tomographic image guidance for lung cancer radiation therapy. , 2009, International journal of radiation oncology, biology, physics.

[51]  W. Paul Segars,et al.  An Integrated Simulation System Based on Digital Human Phantom for 4D Radiation Therapy of Lung Cancer , 2014 .