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Delivery verification is the process in which the energy fluence delivered during a treatment is verified. This verified energy fluence can be used in conjunction with an image in the treatment position to reconstruct the full three-dimensional dose deposited. A method for delivery verification that utilizes a measured database of detector signal is described in this work. This database is a function of two parameters, radiological path-length and detector-to-phantom distance, both of which are computed from a CT image taken at the time of delivery. Such a database was generated and used to perform delivery verification and dose reconstruction. Two experiments were conducted: a simulated prostate delivery on an inhomogeneous abdominal phantom, and a nasopharyngeal delivery on a dog cadaver. For both cases, it was found that the verified fluence and dose results using the database approach agreed very well with those using previously developed and proven techniques. Delivery verification with a measured database and CT image at the time of treatment is an accurate procedure for tomotherapy. The database eliminates the need for any patient-specific, pre- or post-treatment measurements. Moreover, such an approach creates an opportunity for accurate, real-time delivery verification and dose reconstruction given fast image reconstruction and dose computation tools.

An integrated tomotherapy system allows for improved radiotherapy verification by enabling the collection of megavoltage computed tomography (MVCT) images before or after treatment delivery. In this investigation, the possibility of collecting MV tomographic data and reconstructing images during a tomotherapy treatment is examined. By overcoming difficulties with the normalization of modulated treatment data and with the incompleteness of treatment data, it is possible to use data collected during tomotherapeutic treatments for MVCT reconstruction. The benefits of these techniques include potential increases in patient throughput, reductions in imaging dose, visualization of the patient in the treatment position and improvements in image contrast.

Convolution/superposition software has been used to produce a library of photon pencil beam dose matrices. This library of pencil beams is designed to serve as a tool for both education and investigation in the field of radiotherapy optimization. The elegance of this pencil beam model stems from its cylindrical symmetry. Because of the symmetry, the dose distribution for a pencil beam from any arbitrary angle can be determined through a simple rotation of a pre-computed dose matrix. Rapid dose calculations can thus be performed while maintaining the accuracy of a convolution/superposition based dose computation. The pencil beam data sets have been made publicly available. It is hoped that the data sets will facilitate a comparison of a variety of optimization and delivery approaches. This paper will present a number of studies designed to demonstrate the usefulness of the pencil beam data sets. These studies include an examination of the extent to which a treatment plan can be improved through either an increase in the number of beam angles and/or a decrease in the collimator size. A few insights into the significance of heterogeneity corrections for treatment planning for intensity modulated radiotherapy will also be presented.

Post-treatment dose verification refers to the process of reconstructing delivered dose distributions internal to a patient from information obtained during the treatment. The exit dose is commonly used to describe the dose beyond the exit surface of the patient from a megavoltage photon beam. Portal imaging provides a method of determining the dose in a plane distal to a patient from a megavoltage therapeutic beam. This exit dose enables reconstruction of the dose distribution from external beam radiation throughout the patient utilizing the convolution/superposition method and an extended phantom. An iterative convolution/superposition algorithm has been created to reconstruct dose distributions in patients from exit dose measurements during a radiotherapy treatment. The method is based on an extended phantom that includes the patient CT representation and an electronic portal imaging device (EPID). The convolution/superposition method computes the dose throughout the extended phantom, which allows the portal dose image to be predicted in the EPID. The process is then reversed to take the portal dose measurement and infer what the dose distribution must have been to produce the measured portal dose. The dose distribution is modeled without knowledge of the incident intensity distribution, and includes the effects of scatter in the computation. The iterative method begins by assuming that the primary energy fluence (PEF) at the portal image plane is equal to the portal dose image, the PEF is then back-projected through the extended phantom and convolved with the dose deposition kernel to determine a new prediction of the portal dose image. The image of the ratio of the computed PEF to the computed portal dose is then multiplied by the measured portal dose image to produce a better representation of the PEF. Successive iterations of this process then converge to the exiting PEF image that would produce the measured portal dose image. Once convergence is established, the dose distribution is determined by back-projecting the PEF and convolving with the dose deposition kernel. The method is accurate, provided the patient representation during treatment is known. The method was used on three phantoms with a photon energy of 6 MV to verify convergence and accuracy of the algorithm. The reconstructed dose volumes agree to within 3% of the forward computation dose volumes. Furthermore, this technique assumes no prior knowledge of the incident fluence and therefore may better represent the dose actually delivered.

The convolution/superposition method was used to predict the dose throughout an extended volume, which includes a phantom and a portal imaging device. From the calculated dose volume, the dose delivered in the portal image plane was extracted and compared to a portal dose image. This comparison aids in verifying the beam configuration or patient setup after delivery of the radiation. The phantoms used to test the accuracy of this method include a solid water cube, a Nuclear Associates CT phantom, and an Alderson Rando thorax phantom. The dose distribution in the image plane was measured with film and an electronic portal imaging device in each case. The calculated portal dose images were within 4% of the measured images for most voxels in the central portion of the field for all of the extended volumes. The convolution/superposition method also enables the determination of the scatter and primary dose contributions using the particular dose deposition kernels for each contribution. The ratio of primary dose to total dose was used to extract the primary dose from the detected portal image, which enhances the megavoltage portal images by removing scatter blurring. By also predicting the primary energy fluence, we can find the ratio of computed primary energy fluence to total dose. Multiplying this ratio by the measured dose image estimates the relative primary energy fluence at the portal imager. The image of primary energy fluence possesses higher contrast and may be used for further quantitative image processing and dose modeling.

In contemporary radiotherapy dose optimization, radiation beams and beam modifiers are iteratively selected until the dose distribution is acceptable. Another approach, referred to as the “inverse problem,” is: Given the dose prescription, compute the optimal set of photon beams while preventing unphysical solutions such as negative beam weights, and iterate to achieve the prescription as closely as possible. This solution to this inverse problem, which uses image reconstruction mathematics, entails the delivery of large numbers of nonuniform beam intensities to produce uniform dose distributions. These dose distributions can be arranged to conform very closely to even complex target volumes, yet spare surrounding sensitive tissue. Alternatively, the dose distributions can be arranged to generously treat a regional field and “conformally avoid” overtreating sensitive volumes within the field. Multiple dose prescriptions can be delivered without additional effort. We propose that a practical way of delivering optimized dose distributions would be to intensity modulate a photon beam, using collimator leaves intersecting a slit field of radiation. Modulation is achieved by varying the time that the leaves are blocking the field. A practical geometry to deliver such a beam is a computed tomography-like gantry configuration, which also lends itself to tomographic setup verification of dose delivered to the patient. We refer to such a delivery method as “tomotherapy.” Several types of tomotherapy simulations have been conducted. A fully three dimensional optimized treatment planning system using iterative filtered back-projection have been developed. We will present examples of conformal plans for breast and prostate radiotherapy. We have constructed an experimental apparatus for simulating helical tomotherapy delivery by simultaneously rotating and longitudinally translating a phantom past an intensity-modulated fan beam. A comparison between a computation and and experimentally realized plan is presented. A Monte Carlo simulation of the angular distribution and energy fluence spectrum of 10-MV photons produced by a tungsten target have been used to estimate the optimized shape and mass of a primary shielding required to meet regulatory standards.

Tomotherapy, literally "slice therapy," is a proposal for the delivery of radiation therapy with intensity-modulated strips of radiation. The proposed method employs a linear accelerator, or another radiation-emitting device, which would be mounted on a ring gantry like a CT scanner. The patient would move through the bore of the gantry simultaneously with gantry rotation. The intensity modulation would be performed by temporally modulated multiple independent leaves that open and close across the slit opening. At any given time, any leaf would be (1) closed, covering a portion of the slit, (2) open, allowing radiation through, or (3) changing between these states. This method would result in the delivery of highly conformal radiation. Overall treatment times should be comparable with contemporary treatment delivery times. The ring gantry would make it convenient to mount a narrow multisegmented megavoltage detector system for beam verification and a CT scanner on the treatment unit. Such a treatment unit could become a powerful tool for treatment planning, conformal treatment, and verification using tomographic images. The physical properties of this treatment delivery are evaluated and the fundamental design specifications are justified.

The distribution of absolute dose per unit fluence from polyenergetic photon beams impinging upon a water phantom was calculated using two convolution approaches that properly account for beam hardening effects. Dose deposition kernels calculated previously using the EGS4 Monte Carlo code are convolved with the primary terma to give the dose for monoenergetic photon beams of energies ranging from 100 kev to 50 MeV. A polyenergetic dose distribution is composed of separately calculated monoenergetic components, which are appropriately weighted with the fluence spectrum to yield the polyenergetic dose distribution. Alternatively, a single convolution for the polyenergetic beam is considered, where a composite polyenergetic kernel is convolved with the respective polyenergetic terma. The effects of the polyenergetic kernel variance due to beam hardening as well as the effect of tilting the kernels for a diverging beam geometry were also examined. The depth dose data produced using the two proposed methods were compared with measured data and Monte Carlo simulations and showed good agreement.

There are many benefits to having an online CT imaging system for radiotherapy, as it helps identify changes in the patient's position and anatomy between the time of planning and treatment. However, many current online CT systems suffer from a limited field-of-view (LFOV) in that collected data do not encompass the patient's complete cross section. Reconstruction of these data sets can quantitatively distort the image values and introduce artifacts. This work explores the use of planning CT data as a priori information for improving these reconstructions. Methods are presented to incorporate this data by aligning the LFOV with the planning images and then merging the data sets in sinogram space. One alignment option is explicit fusion, producing fusion-aligned reprojection (FAR) images. For cases where explicit fusion is not viable, FAR can be implemented using the implicit fusion of normal setup error, referred to as normal-error-aligned reprojection (NEAR). These methods are evaluated for multiday patient images showing both internal and skin-surface anatomical variation. The iterative use of NEAR and FAR is also investigated, as are applications of NEAR and FAR to dose calculations and the compensation of LFOV online MVCT images with kVCT planning images. Results indicate that NEAR and FAR can utilize planning CT data as imperfect a priori information to reduce artifacts and quantitatively improve images. These benefits can also increase the accuracy of dose calculations and be used for augmenting CT images (e.g., MVCT) acquired at different energies than the planning CT.