A survey on table tolerances and couch overrides in radiotherapy.

The purpose of this study was to survey current departmental policies on treatment couch overrides and the values of table tolerances used clinically. A 25-question electronic survey on couch overrides and tolerances was sent to full members of the American Association of Physicists in Medicine (AAPM). The first part of the survey asked participants if table overrides were allowed at their institution, who was allowed to perform these overrides, and if imaging was required with overrides. The second part of the survey asked individuals to provide table tolerance data for the following treatment sites: brain/head and neck (H&N), lung, breast, abdo-men/pelvis and prostate. Each site was further divided into IMRT/VMAT and 3D conformal techniques. Spaces for free-text were provided, allowing respondents to enter any table tolerance data they were unable to specify under the treatment sites listed. A total of 361 individuals responded, of which approximately half partici-pated in the couch tolerances portion of the survey. Overall, 86% of respondents' institutions allow couch tolerance overrides at treatment. Therapists were the most common staff members permitted to perform overrides, followed by physicists, dosimetrists, and physicians, respectively. Of the institutions allowing overrides, 34% reported overriding daily. More than half of the centers document the over-ride and/or require a setup image to radiographically verify the treatment site. With respect to table tolerances, SRS/SBRT table tolerances were the tightest, while clinical setup table tolerances were the largest. There were minimal statistically significant differences between IMRT/VMAT and 3D conformal table tolerances. Our results demonstrated that table overrides are relatively common in radiotherapy despite being a potential safety concern. Institutions should review their override policy and table tolerance values in light of the practices of other institutions. Careful attention to these matters is crucial in ensuring the safe and accurate delivery of radiotherapy.

Technical Note: Estimation of lung tumor thickness from planar dual-energy kV images.

PURPOSE: Dual-energy (DE) imaging is a method that suppresses bony anatomy on planar kV images while enhancing soft tissue contrast. This technique has been used specifically in the chest to improve the visualization of small lung tumors. However, DE imaging may also provide quantitative information that has not been previously investigated. In this study, the aim was to establish a theoretical relationship between DE image contrast and tumor thickness and to observe this trend in phantom experiments. METHODS: A phantom consisting cork (used to simulate lung), tissue-equivalent material, and pork ribs was constructed to test for a relationship between DE image contrast and simulated tumor thickness. Fifteen phantom setups were used with various thicknesses of cork and tissue-equivalent material. For each setup, high (120 kVp) and low (60 kVp) energy planar images were acquired and DE images were produced. The image contrast between the simulated tumor and surrounding tissue was then plotted against the known thicknesses and a linear regression was performed. RESULTS: A linear regression of the contrast data vs simulated tumor thickness resulted in a slope of -0.0454 with an R(2) = 0.9904. The expected uncertainty in the thickness measurements using the regression parameters and DE contrast standard deviation was 0.13 cm. CONCLUSIONS: Phantom data exhibited a linear relationship between DE image contrast and simulated tumor thickness. Future studies will investigate patient-specific parameters so that this method can be used clinically to evaluate tumor thickness from planar kV images. Such an approach may have benefits for both adaptive and heavy ion therapies.

Markerless motion tracking of lung tumors using dual-energy fluoroscopy.

PURPOSE: To evaluate the efficacy of dual-energy (DE) vs single-energy (SE) fluoroscopic imaging of lung tumors using a markerless template-based tracking algorithm. METHODS: Ten representative patient breathing patterns were programmed into a Quasar™ motion phantom. The phantom was modified by affixing pork ribs to the surface, and a cedar insert with a small spherical volume was used to simulate lung and tumor, respectively. Sequential 60 kVp (6 mA) and 120 kVp (1.5 mA) fluoroscopic sequences were acquired. Frame-by-frame weighted logarithmic subtraction was performed resulting in a DE fluoroscopic sequence. A template-based algorithm was then used to track tumor motion throughout the DE and SE fluoroscopy sequences. Tracking coordinates were evaluated against ground-truth tumor locations. Fluoroscopic images were also acquired for two lung cancer patients, neither of which had implanted fiducials. RESULTS: For phantom imaging, a total of 1925 frames were analyzed. The algorithm successfully tracked the target on 99.9% (1923/1925) of DE frames vs 90.7% (1745/1925) SE images (p < 0.01). The displacement between tracking coordinates and ground truth for the phantom was 1.4 mm ± 1.1 mm for DE vs 2.0 mm ± 1.3 mm for SE (p < 0.01). Images from two patients, one with a larger tumor and one with a smaller tumor, were also analyzed. For the patient with the larger tumor, the average displacement from physician defined ground truth was 1.2 mm ± 0.6 mm for DE vs 1.4 mm ± 0.7 mm for SE (p = 0.016). For the patient that presented with a smaller tumor, the average displacement from physician defined ground truth was 2.2 mm ± 1.0 mm for DE vs 3.2 mm ± 1.4 mm for SE (p < 0.01). Importantly, for this single patient with the smaller tumor, 15.6% of the SE frames had >5 mm displacements from the ground truth vs 0% for DE fluoroscopy. CONCLUSIONS: 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.