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Purpose To investigate the effect of tumor site, measurement precision, tumor–surrogate correlation, training data selection, model design, and interpatient and interfraction variations on the accuracy of external marker-based models of tumor position. Methods and Materials Cyberknife Synchrony system log files comprising synchronously acquired positions of external markers and the tumor from 167 treatment fractions were analyzed. The accuracy of Synchrony, ordinary-least-squares regression, and partial-least-squares regression models for predicting the tumor position from the external markers was evaluated. The quantity and timing of the data used to build the predictive model were varied. The effects of tumor–surrogate correlation and the precision in both the tumor and the external surrogate position measurements were explored by adding noise to the data. Results The tumor position prediction errors increased during the duration of a fraction. Increasing the training data quantities did not always lead to more accurate models. Adding uncorrelated noise to the external marker-based inputs degraded the tumor–surrogate correlation models by 16% for partial-least-squares and 57% for ordinary-least-squares. External marker and tumor position measurement errors led to tumor position prediction changes 0.3–3.6 times the magnitude of the measurement errors, varying widely with model algorithm. The tumor position prediction errors were significantly associated with the patient index but not with the fraction index or tumor site. Partial-least-squares was as accurate as Synchrony and more accurate than ordinary-least-squares. Conclusions The accuracy of surrogate-based inferential models of tumor position was affected by all the investigated factors, except for the tumor site and fraction index.

To compare the retention rates of two types of implanted fiducial markers for stereotactic ablative radiotherapy (SABR) of pulmonary tumors, smooth cylindrical gold "seed" markers ("seeds") and platinum endovascular embolization coils ("coils"), and to compare the complication rates associated with the respective implantation procedures.We retrospectively analyzed the retention of percutaneously implanted markers in 54 consecutive patients between January 2004 and June 2009. A total of 270 markers (129 seeds, 141 coils) were implanted in or around 60 pulmonary tumors over 59 procedures. Markers were implanted using a percutaneous approach under computed tomography (CT) guidance. Postimplantation and follow-up imaging studies were analyzed to score marker retention relative to the number of markers implanted. Markers remaining near the tumor were scored as retained. Markers in a distant location (e.g., pleural space) were scored as lost. CT imaging artifacts near markers were quantified on radiation therapy planning scans.Immediately after implantation, 140 of 141 coils (99.3%) were retained, compared to 110 of 129 seeds (85.3%); the difference was highly significant (p0.0001). Of the total number of lost markers, 45% were reported lost during implantation, but 55% were lost immediately afterwards. No additional markers were lost on longer-term follow-up. Implanted lesions were peripherally located for both seeds (mean distance, 0.33 cm from pleural surface) and coils (0.34 cm) (p=0.96). Incidences of all pneumothorax (including asymptomatic) and pneumothorax requiring chest tube placement were lower in implantation of coils (23% and 3%, respectively) vs. seeds (54% and 29%, respectively; p=0.02 and 0.01). The degree of CT artifact was similar between marker types.Retention of CT-guided percutaneously implanted coils is significantly better than that of seed markers. Furthermore, implanting coils is at least as safe as implanting seeds. Using coils should permit implantation of fewer markers and require fewer repeat implantation procedures owing to lost markers.

Dose escalation for pancreas cancer is limited by the tolerance of adjacent normal tissues, especially with stereotactic body radiotherapy (SBRT). The duodenum is generally considered to be the organ at greatest risk. This study reports on the dosimetric determinants of duodenal toxicity with single-fraction SBRT.Seventy-three patients with locally advanced unresectable pancreatic adenocarcinoma received 25 Gy in a single fraction. Dose-volume histogram (DVH) endpoints evaluated include V(5) (volume of duodenum that received 5 Gy), V(10), V(15), V(20), V(25), and D(max) (maximum dose to 1 cm(3)). Normal tissue complication probability (NTCP) was evaluated with a Lyman model. Univariate and multivariate analyses were conducted with Kaplan-Meier and Cox regression models.The median time to Grade 2-4 duodenal toxicity was 6.3 months (range, 1.6-11.8 months). The 6- and 12-month actuarial rates of toxicity were 11% and 29%, respectively. V(10)-V(25) and D(max) all correlated significantly with duodenal toxicity (p0.05). In particular, V(15)≥9.1 cm(3) and V(15)9.1 cm(3) yielded duodenal toxicity rates of 52% and 11%, respectively (p=0.002); V(20)≥3.3 cm(3) and V(20)3.3 cm(3) gave toxicity rates of 52% and 11%, respectively (p=0.002); and D(max)≥23 Gy and D(max)23 Gy gave toxicity rates of 49% and 12%, respectively (p=0.004). Lyman NTCP model optimization generated the coefficients m=0.23, n=0.12, and TD(50)=24.6 Gy. Only the Lyman NTCP model remained significant in multivariate analysis (p=0.001).Multiple DVH endpoints and a Lyman NTCP model are strongly predictive of duodenal toxicity after SBRT for pancreatic cancer. These dose constraints will be valuable in future abdominal SBRT studies.

Purpose: Dynamically compensating for target motion during radiotherapy will increase treatment accuracy. A laboratory system for real-time target tracking with a dynamic MLC has been developed. In this study, the geometric accuracy limits of this DMLC target tracking system were evaluated. Methods and Materials: A motion simulator was programmed to follow patient-derived tumor motion paths, parallel to the leaf motion direction. A target attached to the simulator was optically tracked, and the leaf positions adjusted to continually align the DMLC beam aperture to the target. Analysis of the tracking accuracy was based on video images of the target and beam alignment. The system response time was determined and the tracking error measured. Response time–corrected tracking accuracy was also calculated to investigate the accuracy limits of an improved system. Results: The response time of the system is 160 ± 2 ms. The geometric precision for tracking patient motion is 0.6 to 1.1 mm (1σ) for the 3 patient datasets tested, with tracking errors relative to the original patient motion of 35, 40, and 100%. Conclusions: A DMLC target tracking system has been developed that can account for detected motion parallel to the leaf motion direction. The tracking error has a negligible systematic component. Reducing the response time will further increase the overall system accuracy.

The CyberKnife is a complex, emerging technology that is a significant departure from current stereotactic radiosurgery and external beam radiotherapy technologies. In its clinical application and quality assurance (QA) approach, the CyberKnife is currently situated somewhere in between stereotactic radiosurgery and radiotherapy. The clinical QA for this image-guided treatment delivery system typically follows the vendor's guidance, mainly because of the current lack of vendor-independent QA recommendations. The problem has been exacerbated because very little published data are available for QA for the CyberKnife system, especially for QA of the interaction between individual system components. The tools and techniques for QA of the CyberKnife are under development and will continue to improve with longer clinical experience of the users. The technology itself continues to evolve, forcing continuous changes and adaptation of QA. To aid in the process of developing comprehensive guidance on CyberKnife QA, a database of errors based on users reporting incidents and corrective actions would be desirable. The goal of this work was to discuss the status of QA guidelines in the clinical implementation of the CyberKnife system. This investigation was done from the perspective of an active clinical and research site using the CyberKnife.