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

Abstract

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 (∆D min ), maximum dose (∆D max ), and mean dose (∆D mean ), and the absolute deviations of prescription dose coverage (∆V 100% ) 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) ∆D min , ∆D max , ∆D mean , and ∆V 100% (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 ∆D min , ∆D max , ∆D mean , and ∆V 100% 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 do...

Dosimetric evaluation of 4D‐CBCT reconstructed by Simultaneous Motion Estimation and Image Reconstruction (SMEIR) for carbon ion therapy of lung cancer

“…Lung cancer is one of the leading causes of cancer‐related deaths in both men and women worldwide with respiration‐related motion providing the biggest challenge to an efficient treatment . Radiation dose to the heart is one of the main factors affecting survival and patient‐reported quality of life .…”

“…11 Lung cancer is one of the leading causes of cancer-related deaths in both men and women worldwide 12 with respirationrelated motion providing the biggest challenge to an efficient treatment. 13,14 Radiation dose to the heart is one of the main factors affecting survival and patient-reported quality of life. 1 Motion-induced anatomical changes may result in significant errors in imaging, treatment planning, which, in turn, affect radiation delivery.…”

Advanced 4-dimensional cone-beam computed tomography reconstruction by combining motion estimation, motion-compensated reconstruction, biomechanical modeling and deep learning

“…The 2D-3D deformation algorithm iteratively optimizes the DVF, such that it deforms the prior image until the digitally-reconstructed-radiographs (DRRs) of the deformed image match the acquired cone-beam projections. The 2D-3D deformation technique can not only generate 4D-CBCT images, but provide DVFs to potentially allow automatic tumor localization, target tracking, dose accumulation and adaptive radiation therapy [29][30][31][32]. The incorporation of highquality prior information also introduces more accurate Hounsfield units [30], and allows further imaging dose reduction by acquiring fewer projections for reconstruction.…”

A Biomechanical Modeling Guided CBCT Estimation Technique

“…With the high-quality image as prior information, the CBCT imaging dose can be substantially reduced by acquiring fewer projections for image estimation. The deformation approach can also pass along the accurate Hounsfield units (HU) from high-quality prior CT images to estimated CBCT images, enabling more accurate dose calculations for radiation therapy [12]. The solved deformation field can also be utilized for tumor tracking [13], dose accumulation [14], adaptive radiation therapy [15], and functional imaging [16].…”