[en] Lung tumors treated in breath-hold are subject to inter- and intra-breath-hold variations, which makes tumor position monitoring during each breath-hold important. A markerless technique is desirable, but limited tumor visibility on kV images makes this challenging. We evaluated if template matching  +  triangulation of kV projection images acquired during breath-hold stereotactic treatments could determine 3D tumor position. Band-pass filtering and/or digital tomosynthesis (DTS) were used as image pre-filtering/enhancement techniques. On-board kV images continuously acquired during volumetric modulated arc irradiation of (i) a 3D-printed anthropomorphic thorax phantom with three lung tumors (n  =  6 stationary datasets, n  =  2 gradually moving), and (ii) four patients (13 datasets) were analyzed. 2D reference templates (filtered DRRs) were created from planning CT data. Normalized cross-correlation was used for 2D matching between templates and pre-filtered/enhanced kV images. For 3D verification, each registration was triangulated with multiple previous registrations. Generally applicable image processing/algorithm settings for lung tumors in breath-hold were identified. For the stationary phantom, the interquartile range of the 3D position vector was on average 0.25 mm for 12° DTS  +  band-pass filtering (average detected positions in 2D  =  99.7%, 3D  =  96.1%, and 3D excluding first 12° due to triangulation angle  =  99.9%) compared to 0.81 mm for band-pass filtering only (55.8/52.9/55.0%). For the moving phantom, RMS errors for the lateral/longitudinal/vertical direction after 12° DTS  +  band-pass filtering were 1.5/0.4/1.1 mm and 2.2/0.3/3.2 mm. For the clinical data, 2D position was determined for at least 93% of each dataset and 3D position excluding first 12° for at least 82% of each dataset using 12° DTS  +  band-pass filtering. Template matching  +  triangulation using DTS  +  band-pass filtered images could accurately determine the position of stationary lung tumors. However, triangulation was less accurate/reliable for targets with continuous, gradual displacement in the lateral and vertical directions. This technique is therefore currently most suited to detect/monitor offsets occurring between initial setup and the start of treatment, inter-breath-hold variations, and tumors with predominantly longitudinal motion. (paper)

[en] Dual-energy (DE) imaging using planar imaging with an on-board imager (OBI) is being considered in radiotherapy. We describe here a custom phantom designed to optimize DE imaging parameters using the OBI of a commercial linear accelerator. The phantom was constructed of lung-, tissue- and bone-equivalent material slabs. Five simulated tumors located at two different depths were encased in the lung-equivalent materials. Two slabs with bone-equivalent material inserts were constructed to simulate ribs, which overlap the simulated tumors. DE bone suppression was performed using a weighted logarithmic subtraction based on an iterative method that minimized the contrast between simulated bone- and lung-equivalent materials. The phantom was subsequently used to evaluate different combinations of high-low kV x-ray pairs of images based on the signal-difference-to-noise ratio (SDNR) metric. The results show a strong correlation between tumor visibility and selected energy pairs, where higher energy separation leads to larger SDNR values. To evaluate the effect of image post-processing methods on tumor visibility, an anti-correlated noise reduction (ACNR) technique and adaptive kernel scatter correction method were applied to subsequent DE images. Application of the ACNR technique approximately doubled the SDNR values, hence increasing tumor visibility, while scatter correction had little effect on SDNR values. This phantom allows for quick image acquisition and optimization of imaging parameters and weighting factors. Optimized DE imaging increases soft tissue visibility and may allow for markerless motion tracking of lung tumors. (note)

[en] Monitoring the stability of patient position is essential during high-precision radiotherapy such as spine stereotactic body radiotherapy (SBRT). We evaluated the combination of digital tomosynthesis (DTS) and triangulation for spine position detection, using non-clinical DTS software and an anthropomorphic pelvic phantom that includes a bone-like spine structure. Kilovoltage cone beam CT projection images over 2–16° gantry rotation were used to generate single slice DTS images. Each DTS slice was registered to a digitally reconstructed DTS derived from the planning CT scan to determine 2D shifts between actual phantom and treatment plan position. Two or more DTS registrations, central axes 4–22° apart, were triangulated to determine the 3D phantom position. Using sequentially generated DTS images, the phantom position can be updated every degree with a small latency of DTS and triangulation angle. The precision of position determination was investigated as function of DTS and triangulation angle. To mimic the scenario of spine SBRT, the effect on the standard deviation of megavoltage radiation delivery during kV image acquisition was tested. In addition, the ability of the system to detect different types of movement was investigated for a variety of small sudden and gradual movements during kV image acquisition. (paper)

[en] Purpose: The ability to verify intrafraction tumor position is clinically useful for hypofractionated treatments. Short arc kV digital tomosynthesis (DTS) could facilitate more frequent target verification. The authors used DTS combined with triangulation to determine the mean temporal position of small-volume lung tumor targets treated with stereotactic radiotherapy. DTS registration results were benchmarked against online clinical localization using registration between free-breathing cone-beam computed tomography (CBCT) and the average intensity projection (AvIP) of the planning 4DCT.Methods: In this retrospective study, 76 sets of kV-projection images from online CBCT scans of 13 patients were used to generate DTS image slices (CB-DTS) with nonclinical research software (DTS Toolkit, Varian Medical Systems). Three-dimensional tumor motion was 1.3–4 mm in six patients and 6.1–25.4 mm in seven patients on 4DCT (significant difference in the mean of the groups, P < 0.01). The 4DCT AvIP was used to digitally reconstruct the Reference-DTS. DTS registration and DTS registration combined with triangulation were investigated. Progressive shortening of total DTS arc lengths from 95° to 35° around 0° gantry position was evaluated for different scenarios: DTS registration using the entire arc; DTS registration plus triangulation using two nonoverlapping arcs; and for 55° and 45° total gantry rotation, DTS registration plus triangulation using two overlapping arcs. Finally, DTS registration plus triangulation performed at eight gantry angles, each separated by 45° was evaluated using full fan kV projection data for one patient with an immobile tumor and five patients with mobile tumors.Results: For DTS registration alone, shortening arc length did not influence accuracy in X- and Y-directions, but in Z-direction, mean deviations from online CBCT localization systematically increased for shorter arc length (P < 0.05). For example, using a 95° arc mean DTS-CBCT difference was 0.8 mm (1 SD = 0.6 mm) and for a 35° arc the mean was 2.4 mm (1 SD = 1.7 mm). DTS plus triangulation using nonoverlapping-arcs increased accuracy in Z-direction for tested arc lengths ≤55° (P < 0.01). Overlapping arcs increased accuracy in Y-direction for tumors with motion >4 mm (P < 0.02) but increased Z-direction accuracy was only observed with 55° total gantry rotation. The 95th percentile deviations with this overlapping technique in X-, Y-, and Z-directions were 1.3, 2.0, and 2.5 mm, respectively. For the five patients with mobile tumors where DTS + triangulation was performed with 45° intervals, the pooled deviation from online CBCT correction showed, for X-, Y-, and Z-directions, mean of 1.1 mm, standard deviations (SD) of 0.9, 1.0, and 0.9 mm, respectively. The mean + 2 SD was <3 mm for each direction.Conclusions: Short-arc DTS verification of time averaged lung tumor position is feasible using free-breathing kV projection data and the AvIP of the 4DCT as a reference. Observed differences between DTS and online CBCT registration with AvIP were ≤3 mm (mean + 2 SD), however, the increased temporal resolution of DTS + triangulation also identified short period deviations from the average target position on the CBCT. Short-arc DTS appears promising for intrafraction tumor position monitoring during stereotactic lung radiotherapy delivered with a rotational technique

[en] Highlights: • Continuous fluoroscopy during MV delivery allows for markerless real time tumor tracking. • 3D lung tumor position monitoring was based on template matching and triangulation. • Lung tumor tracking was possible for >70% of the time during single fraction 34Gy lung SBRT. • Longitudinal, lateral and vertical position of the tumor was within 3 mm PTV margin 85.3% of the time. • The total time from first set-up imaging to end of the last arc was 18.3–31.4 min (mean = 23.4, SD = 4.1). Positional verification during single fraction lung SBRT could increase confidence and reduce the chance of geographic miss. As planar 2DkV imaging during VMAT irradiation is already available on current linear accelerators, markerless tracking based on these images could offer widely available and low-cost verification. We evaluated treatment delivery data and template matching and triangulation for 3D-positional verification during free-breathing, single fraction (34 Gy), 10 MV flattening-filter-free VMAT lung SBRT.

[en] Purpose: (1) To validate retrospective markerless tracking software for small lung tumors by comparing tracked motion in 4-dimensional planning computed tomography (4DCT) derived kV projection images and known tumor motion in the same 4DCT. (2) To evaluate variability of tumor motion using kV projection images from cone-beam computed tomography (CBCT) scans acquired on different days. Methods: Nonclinical tumor tracking software (TTS) used a normalized cross correlation algorithm to track the tumor on enhanced kV projection images (e.g., from a CBCT scan). The reference dataset consisted of digitally reconstructed radiographs (DRRs) from one phase of a planning 4DCT. TTS matches two in-plane coordinates and obtains the out-of-plane coordinate by triangulating with match results from other projections. (1) To validate TTS, tracking results were compared with known 4DCT tumor motion for two patients (A and B). Projection images (1 image/1°) were digitally reconstructed for each 4DCT phase. From these, kV projection series were composed simulating full breathing cycles every 20° of gantry rotation [breathing period = 20°/(6°/s) = 3.33 s]. Reference templates were 360 “tumor enhanced” DRRs from the 4DCT expiration phase. TTS-derived tumor motion was compared to known tumor motion on 4DCT. (2) For five patients, TTS-assessed motion during clinical CBCT acquisition was compared with motion on the planning 4DCT, and the motion component in the Y (cranio–caudal)-direction was compared with the motion of an external marker box (RPM, real-time position management). Results: (1) Validation results: TTS for case A (tumor 6.2 cm³, 32 mm axial diameter) over 360° showed mean motion X (medial–lateral) = 3.4, Y = 11.5, and Z (ventral–dorsal) = 4.9 mm (1 SD < 1.0 mm). Corresponding 4DCT motion was X = 3.1, Y = 11.3, and Z = 5.1 mm. Correlation coefficients between TTS tumor motion and displacement of the tumor’s center of mass (CoM) on 4DCT were 0.64, 0.96, and 0.82 (X, Y, and Z, respectively). For case B (4.1 cm³, 20 mm diameter), due to temporarily decreased tumor visibility preventing TTS from resolving the tumor, robust tracking data were only available between angles 300°–40° and 120°–220°. Mean motion according to TTS was X = 2.0, Y = 7.7, and Z = 8.2 mm (1 SD < 0.9 mm). Tumor motion on 4DCT was X = 1.8, Y = 7.6, and Z = 9.5 mm and correlation coefficients between TTS motion and CoM displacement were 0.59, 0.95, and 0.93 (X, Y, and Z, respectively). (2) Clinical results: TTS revealed a mean intrafraction variation in tumor motion in Y-direction of >2.0 mm (1 SD) in four of five patients. In addition, clinical tumor motion amplitude differed from that seen on planning 4DCT. Internal and external structures that create abrupt density change (e.g., table-top edge, interface between lung/mediastinum and lung/heart) were observed to prevent 360° tracking of the tumor. Correlation coefficients between TTS motion in the Y-direction and the RPM signal (22 observations) ranged from 0.78 to 0.96. In 2D, 241 TTS matches at end-inspiration and end-expiration were visually validated: mean difference was 0.8 mm (SD = 0.7) for both. Conclusions: TTS can track small lung tumors if these are visible in kV projections. A 4DCT dataset can be used to validate kV tracking of moving targets. TTS and 4DCT displacement agreed to within 2 mm. TTS and RPM motion were closely associated but tumor motion during CBCT can vary from the planning 4DCT

[en] Purpose: Spine stereotactic body radiation therapy (SBRT) requires highly accurate positioning. We report our experience with markerless template matching and triangulation of kilovoltage images routinely acquired during spine SBRT, to determine spine position. Methods and Materials: Kilovoltage images, continuously acquired at 7, 11 or 15 frames/s during volumetric modulated spine SBRT of 18 patients, consisting of 93 fluoroscopy datasets (1 dataset/arc), were analyzed off-line. Four patients were immobilized in a head/neck mask, 14 had no immobilization. Two-dimensional (2D) templates were created for each gantry angle from planning computed tomography data and registered to prefiltered kilovoltage images to determine 2D shifts between actual and planned spine position. Registrations were considered valid if the normalized cross correlation score was ≥0.15. Multiple registrations were triangulated to determine 3D position. For each spine position dataset, average positional offset and standard deviation were calculated. To verify the accuracy and precision of the technique, mean positional offset and standard deviation for twenty stationary phantom datasets with different baseline shifts were measured. Results: For the phantom, average standard deviations were 0.18 mm for left-right (LR), 0.17 mm for superior-inferior (SI), and 0.23 mm for the anterior-posterior (AP) direction. Maximum difference in average detected and applied shift was 0.09 mm. For the 93 clinical datasets, the percentage of valid matched frames was, on average, 90.7% (range: 49.9-96.1%) per dataset. Average standard deviations for all datasets were 0.28, 0.19, and 0.28 mm for LR, SI, and AP, respectively. Spine position offsets were, on average, −0.05 (range: −1.58 to 2.18), −0.04 (range: −3.56 to 0.82), and −0.03 mm (range: −1.16 to 1.51), respectively. Average positional deviation was <1 mm in all directions in 92% of the arcs. Conclusions: Template matching and triangulation using kilovoltage images acquired during irradiation allows spine position detection with submillimeter accuracy at subsecond intervals. Although the majority of patients were not immobilized, most vertebrae were stable at the sub-mm level during spine SBRT delivery.

[en] To evaluate fast-kV switching (FS) dual energy (DE) cone beam computed tomography (CBCT) using the on-board imager (OBI) of a commercial linear accelerator to produce virtual monoenergetic (VM) and relative electron density (RED) images.

Using an polynomial attenuation mapping model, CBCT phantom projections obtained at 80 and 140 kVp with FS imaging, were decomposed into equivalent thicknesses of aluminum (Al) and polymethyl methacrylate (PMMA). All projections were obtained with the titanium foil and bowtie filter in place. Basis material projections were then recombined to create VM images by using the linear attenuation coefficients at the specified energy for each material. Similarly, RED images were produced by replacing the linear attenuation values of Al and PMMA by their respective RED values in the projection space. VM and RED images were reconstructed using Feldkamp–Davis–Kress (FDK) and an iterative algorithm (iCBCT, Varian Medical Systems). Hounsfield units (HU), contrast-to-noise ratio (CNR) and RED values were compared against known values.

The results after VM-CBCT production showed good material decomposition and consistent HU_VM values, with measured root mean square errors (RMSE) from theoretical values, after FDK reconstruction, of 20.5, 5.7, 12.8 and 21.7 HU for 50, 80, 100 and 150 keV, respectively. The largest CNR improvements, when compared to polychromatic images, were observed for the 50 keV VM images. Image noise was reduced up to 28% in the VM-CBCT images after iterative image reconstruction. RED values measured for our method resulted in a mean percentage error of 0.0%  ±  1.8%.

This study describes a method to generate VM-CBCT and RED images using FS-DE scans obtained using the OBI of a linac, including the effects of the bowtie filter. The creation of VM and RED images increases the dynamic range of CBCT images, and provides additional data that may be used for adaptive radiotherapy, and on table verification for radiotherapy treatments. (paper)

[en] Purpose: Real-time tracking of respiratory target motion during radiation therapy is technically challenging, owing to rapid and possibly irregular breathing variations. The authors report on a method to predict and correct respiration-averaged drift in target position by means of couch adjustments on an accelerator equipped with such capability. Methods: Dose delivery is broken up into a sequence of 10 s field segments, each followed by a couch adjustment based on analysis of breathing motion from an external monitor as a surrogate of internal target motion. Signal averaging over three respiratory cycles yields a baseline representing target drift. A Kalman filter predicts the baseline position 5 s in advance, for determination of the couch correction. The method's feasibility is tested with a motion phantom programmed according to previously recorded patient signals. Computed couch corrections are preprogrammed into a research mode of an accelerator capable of computer-controlled couch translations synchronized with the motion phantom. The method's performance is evaluated with five cases recorded during hypofractionated treatment and five from respiration-correlated CT simulation, using a root-mean-squared deviation (RMSD) of the baseline from the treatment planned position. Results: RMSD is reduced in all 10 cases, from a mean of 4.9 mm (range 2.7–9.4 mm) before correction to 1.7 mm (range 0.7–2.3 mm) after correction. Treatment time is increased ∼5% relative to that for no corrections. Conclusions: This work illustrates the potential for reduction in baseline respiratory drift with periodic adjustments in couch position during treatment. Future treatment machine capabilities will enable the use of “on-the-fly” couch adjustments during treatment.

[en] Due to the risk of pneumothorax, many clinicians are reluctant to implant radiopaque markers within patients' lungs for the purpose of radiographic or fluoroscopic tumour localization. We propose a method of gated therapy using fluoroscopic information without the implantation of radiopaque markers. The method presented here does not rely on any external motion signal either. Breathing phase information is found by analysing the fluoroscopic intensity fluctuations in the lung. As the lungs fill/empty, the radiological pathlength through them shortens/lengthens, giving brighter/darker fluoroscopic intensities. The phase information is combined with motion-enhanced template matching to turn the beam on when the tumour is in the desired location. A study based on patient data is presented to demonstrate the feasibility of this procedure. The resulting beam-on pattern is similar to that produced by an external gating system. The only discrepancies occur briefly and at the gate edges