Owen Clancey

CyberKnife boost for patients with cervical cancer unable to undergo brachytherapy

Standard radiation therapy for patients undergoing primary chemosensitized radiation for carcinomas of the cervix usually consists of external beam radiation followed by an intracavitary brachytherapy boost. On occasion, the brachytherapy boost cannot be performed due to unfavorable anatomy or because of coexisting medical conditions. We examined the safety and efficacy of using CyberKnife stereotactic body radiotherapy (SBRT) as a boost to the cervix after external beam radiation in those patients unable to have brachytherapy to give a more effective dose to the cervix than with conventional external beam radiation alone. Six consecutive patients with anatomic or medical conditions precluding a tandem and ovoid boost were treated with combined external beam radiation and CyberKnife boost to the cervix. Five patients received 45 Gy to the pelvis with serial intensity-modulated radiation therapy boost to the uterus and cervix to a dose of 61.2 Gy. These five patients received an SBRT boost to the cervix to a dose of 20 Gy in five fractions of 4 Gy each. One patient was treated to the pelvis to a dose of 45 Gy with an external beam boost to the uterus and cervix to a dose of 50.4 Gy. This patient received an SBRT boost to the cervix to a dose of 19.5 Gy in three fractions of 6.5 Gy. Five percent volumes of the bladder and rectum were kept to ≤75 Gy in all patients (i.e., V75 Gy ≤ 5%). All of the patients remain locally controlled with no evidence of disease following treatment. Grade 1 diarrhea occurred in 4/6 patients during the conventional external beam radiation. There has been no grade 3 or 4 rectal or bladder toxicity. There were no toxicities observed following SBRT boost. At a median follow-up of 14 months, CyberKnife radiosurgical boost is well tolerated and efficacious in providing a boost to patients with cervix cancer who are unable to undergo brachytherapy boost. Further follow-up is required to see if these results remain durable.

A memetic algorithm for dosimetric optimization in CyberKnife robotic radiosurgical treatment planning

A memetic algorithm is proposed for optimizing beam weights for robotic radiosurgical treatments delivered via the CyberKnife (Accuray, Inc., Sunnyvale, CA) system. The fitness function includes terms representing the tumor as well as terms representing organs-at-risk, and is of a quadratic form. Optimization involves inverse treatment planning, during which a set of beam weights is sought such that the user-specified radiation dose distribution is produced by the optimized ensemble of beam weights; the dose to the tumor is maximized, while the doses to the critical structures are minimized. In the present study, four distinct CT data sets for patients with carcinoma of the prostate were used to generate eight treatment plans, so that for each data set, a hypofractionated treatment plan (5 fractions) was created, as well as a treatment plan for a standard protracted dose fractionation schedule (38 fractions). In all cases, the memetic algorithm produced a treatment plan satisfying all clinical criteria in optimization times of 22–46 minutes.

An evolutionary algorithm for optimization of affine transformation parameters for dose matrix warping in patient-specific quality assurance of radiotherapy dose distributions

Patient-specific quality assurance for sophisticated treatment delivery modalities in radiation oncology, such as intensity-modulated radiation therapy (IMRT), necessitates the measurement of the delivered dose distribution, and the subsequent comparison of the measured dose distribution with that calculated by the treatment planning software. The degree to which the calculated dose distribution is reproduced upon delivery is an indication that the treatment received by the patient is acceptable. A new method for the comparison between the planned and delivered dose distributions is introduced; it assesses the agreement between planar two-dimensional dose distributions. The method uses an evolutionary algorithm to optimize the parameters of the affine transformation, consisting of translation, rotation, and dilation (or erosion), that will warp the measured dose distribution to the planned dose distribution. The deviation of the composite transformation matrix from the identity matrix is an indication of an average geometrical error in the delivered dose distribution, and represents a systematic error in dose delivery. The residual errors in radiation dose at specific points are local errors in dose delivery. The method was applied to IMRT fields consisting of horizontal intensity bands. Analysis shows the method to be a promising tool for patient-specific quality assurance.

A mimetic algorithm for simultaneous multileaf collimator aperture shape and dosimetric optimization in CyberKnife robotic radiosurgery

A mimetic algorithm for the optimization of multileaf collimator aperture shape and beam weighting is proposed for the CyberKnife M6 delivery platform (Accuray Inc., Sunnyvale, CA). The problem of optimizing a patient-specific treatment plan necessarily requires the determination of the beam geometry, beam-defining aperture shape, and beam weighting. The robotic arm of the CyberKnife moves the linear accelerator through approximately half the solid angle, the multileaf collimator in the head of the accelerator provides for conformal aperture shaping of the radiation, and the linear accelerator generates megavoltage x-rays to irradiate the target. The multileaf collimator leaf positions are optimized, as well as beam weights, by an algorithm consisting of an EA combined with a CMA-ES intense local search. The generation of apertures uses a rule-based approach, based upon dosimetric feedback regarding the radiation dose distribution acquired during each iteration. The purpose of the optimization is to find a Pareto-optimal solution which takes into account the clinical decision-making calculus of the radiation oncologist. The algorithm was tested on CT data set for a patient with carcinoma of the prostate. Twenty algorithm runs were performed; the mean fitness value was 2.48 × 105, and the standard deviation was 9.40 × 104. In all instances, the algorithm produced clinically acceptable treatment plans, meeting the user-specified dose-volume objectives for the target and critical structures. Note that there is no commercial algorithm currently available for generating these types of treatment plans, so the present work demonstrates feasibility of a novel treatment planning approach.

Young age to predict for transient elevation in PSA after definitive stereotactic body radiation therapy for prostate cancer.

118 Background: Stereotactic Body Radiation Therapy (SBRT) is a standard therapeutic option for men with prostate adenocarcinoma. There is a small body of literature characterizing a PSA bump after treatment with SBRT. Despite this, there is a paucity of data addressing rates of transient PSA increase immediately after SBRT treatment and what factors portend for this rare occurrence. This study reports outcomes on initial PSA after SBRT therapy for men who have received definitive SBRT for prostate cancer. Methods: Between May 2006 and February 2014, 921 patients with prostate cancer were treated with SBRT delivered via Cyberknife therapy. The mean age was 67 years old. 68.5% of patients were Caucasian, 17.4% African American, and 14.1% were another ethnicity. Patients were divided into prognostic risk groups with 44.7%, 43.5%, and 11.1% of patients falling in the low, intermediate, and high risk stratifications. Gleason scores were < 6 in 44.4%, 7 in 41.3%, and 8-10 in 14.2%. 37 patients also received su...

Feasibility of an ant colony optimization algorithm for multi-leaf collimator (MLC) aperture definition and beam weighting in volumetric modulated arc therapy (VMAT) radiotherapy treatment planning

Volumetric Modulated Arc Therapy (VMAT) is a sophisticated radiotherapy treatment delivery modality in which a medical linear accelerator arcs around a patient, with concurrent dynamic variation of multi-leaf collimator aperture, dose rate, and gantry speed, to produce a radiation dose distribution which delivers a highly conformal dose to the target while minimizing the incidental irradiation of normal tissue. Treatment planning for VMAT is an inverse problem, requiring optimization of the linear accelerator parameters to produce the desired radiation dose distribution, which is specified by dose-volume objectives. In this study, the feasibility of an ant colony algorithm for VMAT treatment planning is demonstrated by the ability of the algorithm to produce a treatment plan, which satisfies given dose-volume objectives, for a phantom target/critical structure geometry. Three experiments were conducted: one in which the optimization included only heuristic information, one in which there was exclusively a pheromone trail update, and one where there was both a pheromone trail update and an applied heuristic. The results indicate that the use of both a pheromone trail update and heuristic information during the optimization yields solutions of the highest quality.