No abstract

The medical linear accelerator ͑linac͒ integrated with a kilovoltage ͑kV͒ flat-panel imager has been emerging as an important piece of equipment for image-guided radiation therapy. Due to the sagging of the linac head and the flexing of the robotic arms that mount the x-ray tube and flat-panel detector, geometric nonidealities generally exist in the imaging geometry no matter whether it is for the two-dimensional projection image or three-dimensional cone-beam computed tomography. Normally, the geometric parameters are established during the commissioning and incorporated in correction software in respective image formation or reconstruction. A prudent use of an on-board imaging system necessitates a routine surveillance of the geometric accuracy of the system like the position of the x-ray source, imager position and orientation, isocenter, rotation trajectory, and source-to-imager distance. Here we describe a purposely built phantom and a data analysis software for monitoring these important parameters of the system in an efficient and automated way. The developed tool works equally well for the megavoltage ͑MV͒ electronic portal imaging device and hence allows us to measure the coincidence of the isocenters of the MV and kV beams of the linac. This QA tool can detect an angular uncertainty of 0.1°of the x-ray source. For spatial uncertainties, such as the source position, the imager position, or the kV/MV isocenter misalignment, the demonstrated accuracy of this tool was better than 1.6 mm. The developed tool provides us with a simple, robust, and objective way to probe and monitor the geometric status of an imaging system in a fully automatic process and facilitate routine QA workflow in a clinic.

Currently, there are two types of treatment planning algorithms for intensity modulated radiation therapy (IMRT). The beamlet-based algorithm generates beamlet intensity maps with high complexity, resulting in large numbers of segments in the delivery after a leaf-sequencing algorithm is applied. The segment-based direct aperture optimization (DAO) algorithm includes the physical constraints of the deliverable apertures in the calculation, and achieves a conformal dose distribution using a small number of segments. However, the number of segments is pre-fixed in most of the DAO approaches, and the typical random search scheme in the optimization is computationally intensive. A regularization-based algorithm is proposed to overcome the drawbacks of the DAO method. Instead of smoothing the beamlet intensity maps as in many existing methods, we include a total-variation term in the optimization objective function to reduce the number of signal levels of the beam intensity maps. An aperture rectification algorithm is then applied to generate a significantly reduced number of deliverable apertures. As compared to the DAO algorithm, our method has an efficient form of quadratic optimization, with an additional advantage of optimizing field-specific numbers of segments based on the modulation complexity. The proposed approach is evaluated using two clinical cases. Under the condition that the clinical acceptance criteria of the treatment plan are satisfied, for the prostate patient, the total number of segments for five fields is reduced from 61 using the Eclipse planning system to 35 using the proposed algorithm; for the head and neck patient, the total number of segments for seven fields is reduced from 107 to 28. The head and neck result is also compared to that using an equal number of four segments for each field. The comparison shows that using field-specific numbers of segments achieves a much improved dose distribution.

Volumetric modulated arc therapy (VMAT) has recently emerged as a new clinical modality for conformal radiation therapy. The aim of this work is to establish a methodology and procedure for retrospectively reconstructing the actual dose delivered in VMAT based on the pre-treatment cone-beam computed tomography (CBCT) and dynamic log files. CBCT was performed before the dose delivery and the system's log files were retrieved after the delivery. Actual delivery at a control point including MLC leaf positions, gantry angles and cumulative monitor units (MUs) was recorded in the log files and the information was extracted using in-house developed software. The extracted information was then embedded into the original treatment DICOM-radiation therapy (RT) file to replace the original control point parameters. This reconstituted DICOM-RT file was imported into the Eclipse treatment planning system (TPS) and dose was computed on the corresponding CBCT. A series of phantom experiments was performed to show the feasibility of dose reconstruction, validate the procedure and demonstrate the efficacy of this methodology. The resultant dose distributions and dose-volume histograms (DVHs) were compared with those of the original treatment plan. The studies indicated that CBCT-based VMAT dose reconstruction is readily achievable and provides a valuable tool for monitoring the dose actually delivered to the tumor target as well as the sensitive structures. In the absence of setup errors, the reconstructed dose shows no significant difference from the original pCT-based plan. It is also elucidated that the proposed method is capable of revealing the dosimetric changes in the presence of setup errors. The method reported here affords an objective means for dosimetric evaluation of VMAT delivery and is useful for adaptive VMAT in future.

The advantage of highly conformal dose techniques such as 3DCRT and IMRT is limited by intrafraction organ motion. A new approach to gain near real-time 3D positions of internally implanted fiducial markers is to analyze simultaneous onboard kV beam and treatment MV beam images (from fluoroscopic or electronic portal image devices). Before we can use this real-time image guidance for clinical 3DCRT and IMRT treatments, four outstanding issues need to be addressed. (1) How will fiducial motion blur the image and hinder tracking fiducials? kV and MV images are acquired while the tumor is moving at various speeds. We find that a fiducial can be successfully detected at a maximum linear speed of 1.6 cm/s. (2) How does MV beam scattering affect kV imaging? We investigate this by varying MV field size and kV source to imager distance, and find that common treatment MV beams do not hinder fiducial detection in simultaneous kV images. (3) How can one detect fiducials on images from 3DCRT and IMRT treatment beams when the MV fields are modified by a multileaf collimator (MLC)? The presented analysis is capable of segmenting a MV field from the blocking MLC and detecting visible fiducials. This enables the calculation of nearly real-time 3D positions of markers during a real treatment. (4) Is the analysis fast enough to track fiducials in nearly real time? Multiple methods are adopted to predict marker positions and reduce search regions. The average detection time per frame for three markers in a 1024 x 768 image was reduced to 0.1 s or less. Solving these four issues paves the way to tracking moving fiducial markers throughout a 3DCRT or IMRT treatment. Altogether, these four studies demonstrate that our algorithm can track fiducials in real time, on degraded kV images (MV scatter), in rapidly moving tumors (fiducial blurring), and even provide useful information in the case when some fiducials are blocked from view by the MLC. This technique can provide a gating signal or be used for intra-fractional tumor tracking on a Linac equipped with a kV imaging system. Any motion exceeding a preset threshold can warn the therapist to suspend a treatment session and reposition the patient.