This work indicates the potential for markerless tumor tracking utilizing DE fluoroscopy. With DE imaging, the algorithm showed improved detectability vs SE fluoroscopy and was able to accurately track the tumor in nearly all cases.

Objective: To investigate the effects of adaptive radiotherapy on dosimetric, clinical, and toxicity outcomes for patients with head and neck cancer undergoing chemoradiotherapy with intensity-modulated radiotherapy. Methods: Fifty-one patients with advanced head and neck cancer underwent definitive chemoradiotherapy with the original plan optimized to deliver 70.2 Gy. All patients were resimulated at a median dose of 37.8 Gy (range, 27.0-48.6 Gy) due to changes in tumor volume and/or patient weight loss (>15% from baseline). Thirty-four patients underwent adaptive replanning for their boost planning (21.6 Gy). The dosimetric effects of the adaptive plan were compared to the original plan and the original plan copied on rescan computed tomography. Acute and late toxicities and tumor local control were assessed. Gross tumor volume reduction rate was calculated. Results: With adaptive replanning, the maximum dose to the spinal cord, brain stem, mean ipsilateral, and contralateral parotid had a median reduction of À4.5%, À3.0%, À6.2%, and À2.5%, respectively (median of 34 patients). Median gross tumor volume and boost planning target volume coverage improved by 0.8% and 0.5%, respectively. With a median follow-up time of 17.6 months, median disease-free survival and overall survival was 14.8 and 21.1 months, respectively. Median tumor volume reduction rate was 35.2%. For patients with tumor volume reduction rate 35.2%, median disease-free survival was 8.7 months, whereas it was 16.9 months for tumor volume reduction rate >35.2%. Four patients had residual disease after chemoradiotherapy, whereas 64.7% (20 of 34) of patients achieved locoregional control. Conclusion: Implementation of adaptive radiotherapy in head and neck cancer offers benefits including improvement in tumor coverage and decrease in dose to organs at risk. The tumor volume reduction rate during treatment was significantly correlated with disease-free survival and overall survival.

Purpose: To evaluate markerless tumor tracking (MTT) using fast-kV switching dual-energy (DE) fluoroscopy on a bench top system. Methods: Fast-kV switching DE fluoroscopy was implemented on a bench top which includes a turntable stand, flat panel detector, and x-ray tube. The customized generator firmware enables consecutive x-ray pulses that alternate between programmed high and low energies (e.g., 60 and 120 kVp) with a maximum frame rate of 15 Hz. In-house software was implemented to perform weighted DE subtraction of consecutive images to create an image sequence that removes bone and enhances soft tissues. The weighting factor was optimized based on gantry angle. To characterize this system, a phantom was used that simulates the chest anatomy and tumor motion in the lung. Five clinically relevant tumor sizes (5-25 mm diameter) were considered. The targets were programmed to move in the inferior-superior direction of the phantom, perpendicular to the x-ray beam, using a cos 4 waveform to mimic respiratory motion. Target inserts were then tracked with MTT software using a template matching method. The optimal computed tomography (CT) slice thickness for template generation was also evaluated. Tracking success rate and accuracy were calculated in regions of the phantom where the target overlapped ribs vs spine, to compare the performance of single energy (SE) and DE imaging methods. Results: For the 5 mm target, a CT slice thickness of 0.75 mm resulted in the lowest tracking error. For the larger targets (≥10 mm) a CT slice thickness ≤2 mm resulted in comparable tracking errors for SE and DE images. Overall DE imaging improved MTT accuracy, relative to SE imaging, for all tumor targets in a rotational acquisition. Compared to SE, DE imaging increased tracking success rate of small target inserts (5 and 10 mm). For fast motion tracking, success rates improved from 23% to 64% and 74% to 90% for 5 and 10 mm targets inserts overlapping ribs, respectively. For slow moving targets success rates improved from 19% to 59% and 59% to 91% in 5 and 10 mm targets overlapping the ribs, respectively. Similar results were observed when the targets overlapped the spine. For larger targets (≥15 mm) tracking success rates were comparable using SE and DE imaging. Conclusion: This work presents the first results of MTT using fast-kV switching DE fluoroscopy. Using DE imaging has improved the tracking accuracy of MTT, especially for small targets. The results of this study will guide the future implementation of fast-kV switching DE imaging using the on-board imager of a linear accelerator.

Objective: To develop decision trees predicting for tumor volume reduction in patients with head and neck (H&N) cancer using pretreatment clinical and pathological parameters. Methods: Forty-eight patients treated with definitive concurrent chemoradiotherapy for squamous cell carcinoma of the nasopharynx, oropharynx, oral cavity, or hypopharynx were retrospectively analyzed. These patients were rescanned at a median dose of 37.8 Gy and replanned to account for anatomical changes. The percentages of gross tumor volume (GTV) change from initial to rescan computed tomography (CT; %GTVD) were calculated. Two decision trees were generated to correlate %GTVD in primary and nodal volumes with 14 characteristics including age, gender, Karnofsky performance status (KPS), site, human papilloma virus (HPV) status, tumor grade, primary tumor growth pattern (endophytic/exophytic), tumor/nodal/group stages, chemotherapy regimen, and primary, nodal, and total GTV volumes in the initial CT scan. The C4.5 Decision Tree induction algorithm was implemented. Results: The median %GTVD for primary, nodal, and total GTVs was 26.8%, 43.0%, and 31.2%, respectively. Type of chemotherapy, age, primary tumor growth pattern, site, KPS, and HPV status were the most predictive parameters for primary %GTVD decision tree, whereas for nodal %GTVD, KPS, site, age, primary tumor growth pattern, initial primary GTV, and total GTV volumes were predictive. Both decision trees had an accuracy of 88%. Conclusions: There can be significant changes in primary and nodal tumor volumes during the course of H&N chemoradiotherapy. Considering the proposed decision trees, radiation oncologists can select patients predicted to have high %GTVD, who would theoretically gain the most benefit from adaptive radiotherapy, in order to better use limited clinical resources.

Purpose: 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. Methods: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 relative electron density (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. Results: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. Relative electron density values measured for our method resulted in a mean percentage error of 0.0 ± 1.8%. Conclusions: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