"Primer shot" fractionation with an early treatment break is theoretically superior to consecutive weekday fractionation schemes for early-stage non-small cell lung cancer.

PURPOSE: Radiotherapy is traditionally given in equally spaced weekday fractions. We hypothesize that heterogeneous interfraction intervals can increase radiosensitivity via reoxygenation. Through modeling, we investigate whether this minimizes local failures and toxicity for early-stage non-small cell lung cancer (NSCLC). METHODS: Previously, a tumor dose-response model based on resource competition and cell-cycle-dependent radiosensitivity accurately predicted local failure rates for early-stage NSCLC cohorts. Here, the model mathematically determined non-uniform inter-fraction intervals minimizing local failures at similar normal tissue toxicity risk, i.e., iso-BED3 (iso-NTCP) for fractionation schemes 18Gyx3, 12Gyx4, 10Gyx5, 7.5Gyx8, 5Gyx12, 4Gyx15. Next, we used these optimized schedules to reduce toxicity risk (BED3) while maintaining stable local failures (TCP). RESULTS: Optimal schedules consistently favored a "primer shot" fraction followed by a 2-week break, allowing tumor reoxygenation. Increasing or decreasing the assumed baseline hypoxia extended or shortened this optimal break by up to one week. Fraction sizes of 7.5 Gy and up required a single primer shot, while smaller fractions needed one or two extra fractions for full reoxygenation. The optimized schedules, versus consecutive weekday fractionation, predicted absolute LF reductions of 4.6%-7.4%, except for the already optimal LF rate seen for 18Gyx3. Primer shot schedules could also reduce BED3 at iso-TCP with the biggest improvements for the shortest schedules (94.6Gy reduction for 18Gyx3). CONCLUSION: A validated simulation model clearly supports non-standard "primer shot" fractionation, reducing the impact of hypoxia-induced radioresistance. A limitation of this study is that primer-shot fractionation is outside prior clinical experience and therefore will require clinical studies for definitive testing.

Temporal patterns of patient-reported trismus and associated mouth-opening distances in radiotherapy for head and neck cancer: A prospective cohort study.

OBJECTIVES: To identify temporal patterns of patient-reported trismus during the first year post-radiotherapy, and to study their associations with maximal interincisal opening distances (MIOs). DESIGN: Single institution case series. SETTING: University hospital ENT clinic. PARTICIPANTS: One hundred and ninety-six subjects who received radiotherapy (RT) for head and neck cancer (HNC) with or without chemotherapy in 2007-2012 to a total dose of 64.6/68 Gy in 38/34 fractions, respectively. All subjects were prospectively assessed for mouth-opening ability (Gothenburg Trismus Questionnaire (GTQ), European Organization for Research and Treatment of Cancer quality of life Questionnaire (EORTC QLQ-H&N35), and MIO) pre-RT and at 3, 6 and 12 months after RT. MAIN OUTCOME MEASURES: Correlations between temporally robust GTQ symptoms and MIO as given by Pearson's correlation coefficients (Pr ); temporally robust GTQ-symptom domains as given by factor analysis; rates of trismus with respect to baseline by risk ratios (RRs). RESULTS: Four temporally robust domains were identified: Eating (3-7 symptoms), Jaw (3-7), Pain (2-5) and Quality of Life (QoL, 2-5), and included 2-3 persistent symptoms across all post-RT assessments. The median RR for a moderate/severe (>2/>3) cut-off was the highest for Jaw (3.7/3.6) and QoL (3.2/2.9). The median Pr between temporally robust symptoms and MIO post-radiotherapy was 0.25-0.35/0.34-0.43/0.24-0.31/0.34-0.50 for Eating/Jaw/Pain/QoL, respectively. CONCLUSIONS: Mouth-opening distances in patients with HNC post-RT can be understood in terms of associated patient-reported outcomes on trismus-related difficulties. Our data suggest that a reduction in MIO can be expected as patients communicate their mouth-opening status to interfere with private/social life, a clinical warning signal for emerging or worsening trismus as patients are being followed after RT.

Influence of image slice thickness on rectal dose-response relationships following radiotherapy of prostate cancer.

When pooling retrospective data from different cohorts, slice thicknesses of acquired computed tomography (CT) images used for treatment planning may vary between cohorts. It is, however, not known if varying slice thickness influences derived dose-response relationships. We investigated this for rectal bleeding using dose-volume histograms (DVHs) of the rectum and rectal wall for dose distributions superimposed on images with varying CT slice thicknesses. We used dose and endpoint data from two prostate cancer cohorts treated with three-dimensional conformal radiotherapy to either 74 Gy (N = 159) or 78 Gy (N = 159) at 2 Gy per fraction. The rectum was defined as the whole organ with content, and the morbidity cut-off was Grade ≥2 late rectal bleeding. Rectal walls were defined as 3 mm inner margins added to the rectum. DVHs for simulated slice thicknesses from 3 to 13 mm were compared to DVHs for the originally acquired slice thicknesses at 3 and 5 mm. Volumes, mean, and maximum doses were assessed from the DVHs, and generalized equivalent uniform dose (gEUD) values were calculated. For each organ and each of the simulated slice thicknesses, we performed predictive modeling of late rectal bleeding using the Lyman-Kutcher-Burman (LKB) model. For the most coarse slice thickness, rectal volumes increased (≤18%), whereas maximum and mean doses decreased (≤0.8 and ≤4.2 Gy, respectively). For all a values, the gEUD for the simulated DVHs were ≤1.9 Gy different than the gEUD for the original DVHs. The best-fitting LKB model parameter values with 95% CIs were consistent between all DVHs. In conclusion, we found that the investigated slice thickness variations had minimal impact on rectal dose-response estimations. From the perspective of predictive modeling, our results suggest that variations within 10 mm in slice thickness between cohorts are unlikely to be a limiting factor when pooling multi-institutional rectal dose data that include slice thickness variations within this range.

Modelling the interplay between hypoxia and proliferation in radiotherapy tumour response.

A tumour control probability computational model for fractionated radiotherapy was developed, with the goal of incorporating the fundamental interplay between hypoxia and proliferation, including reoxygenation over a course of radiotherapy. The fundamental idea is that the local delivery of oxygen and glucose limits the amount of proliferation and metabolically-supported cell survival a tumour sub-volume can support. The model has three compartments: a proliferating compartment of cells receiving oxygen and glucose; an intermediate, metabolically-active compartment receiving glucose; and a highly hypoxic compartment of starving cells. Following the post-mitotic cell death of proliferating cells, intermediate cells move into the proliferative compartment and hypoxic cells move into the intermediate compartment. A key advantage of the proposed model is that the initial compartmental cell distribution is uniquely determined from the assumed local growth fraction (GF) and volume doubling time (TD) values. Varying initial cell state distributions, based on the local (voxel) GF and TD, were simulated. Tumour response was simulated for head and neck squamous cell carcinoma using relevant parameter values based on published sources. The tumour dose required to achieve a 50% local control rate (TCD50) was found for various GFs and TD's, and the effect of fraction size on TCD50 was also evaluated. Due to the advantage of reoxygenation over a course of radiotherapy, conventional fraction sizes (2-2.4 Gy fx(-1)) were predicted to result in smaller TCD50's than larger fraction sizes (4-5 Gy fx(-1)) for a 10 cc tumour with GFs of around 0.15. The time to eliminate hypoxic cells (the reoxygenation time) was estimated for a given GF and decreased as GF increased. The extra dose required to overcome accelerated stem cell accumulation in longer treatment schedules was estimated to be 0.68 Gy/day (in EQD26.6), similar to published values derived from clinical data. The model predicts, for a 2 Gy/weekday fractionation, that increased initial proliferation (high GF) should, surprisingly, lead to moderately higher local control values. Tumour hypoxia is predicted to increase the required dose for local control by approximately 30%. Predicted tumour regression patterns are consistent with clinical observations. This simple yet flexible model shows how the local competition for chemical resources might impact local control rates under varying fractionation conditions.

Exploring feature-based approaches in PET images for predicting cancer treatment outcomes.

Accumulating evidence suggests that characteristics of pre-treatment FDG-PET could be used as prognostic factors to predict outcomes in different cancer sites. Current risk analyses are limited to visual assessment or direct uptake value measurements. We are investigating intensity-volume histogram metrics and shape and texture features extracted from PET images to predict patient's response to treatment. These approaches were demonstrated using datasets from cervix and head and neck cancers, where AUC of 0.76 and 1.0 were achieved, respectively. The preliminary results suggest that the proposed approaches could potentially provide better tools and discriminant power for utilizing functional imaging in clinical prognosis.

IMRT treatment planning for prostate cancer using prioritized prescription optimization and mean-tail-dose functions.

Treatment planning for intensity modulated radiation therapy (IMRT) is challenging due to both the size of the computational problems (thousands of variables and constraints) and the multi-objective, imprecise nature of the goals. We apply hierarchical programming to IMRT treatment planning. In this formulation, treatment planning goals/objectives are ordered in an absolute hierarchy, and the problem is solved from the top-down such that more important goals are optimized in turn. After each objective is optimized, that objective function is converted into a constraint when optimizing lower-priority objectives. We also demonstrate the usefulness of a linear/quadratic formulation, including the use of mean-tail-dose (mean dose to the hottest fraction of a given structure), to facilitate computational efficiency. In contrast to the conventional use of dose-volume constraints (no more than x% volume of a structure should receive more than y dose), the mean-tail-dose formulation ensures convex feasibility spaces and convex objective functions. To widen the search space without seriously degrading higher priority goals, we allowed higher priority constraints to relax or 'slip' a clinically negligible amount during lower priority iterations. This method was developed and tuned for external beam prostate planning and subsequently tested using a suite of 10 patient datasets. In all cases, good dose distributions were generated without individual plan parameter adjustments. It was found that allowance for a small amount of 'slip,' especially in target dose homogeneity, often resulted in improved normal tissue dose burdens. Compared to the conventional IMRT treatment planning objective function formulation using a weighted linear sum of terms representing very different dosimetric goals, this method: (1) is completely automatic, requiring no user intervention, (2) ensures high-priority planning goals are not seriously degraded by lower-priority goals, and (3) ensures that lower priority, yet still important, normal tissue goals are separately pushed as far as possible without seriously impacting higher priority goals.

The denoising of Monte Carlo dose distributions using convolution superposition calculations.

Monte Carlo (MC) dose calculations can be accurate but are also computationally intensive. In contrast, convolution superposition (CS) offers faster and smoother results but by making approximations. We investigated MC denoising techniques, which use available convolution superposition results and new noise filtering methods to guide and accelerate MC calculations. Two main approaches were developed to combine CS information with MC denoising. In the first approach, the denoising result is iteratively updated by adding the denoised residual difference between the result and the MC image. Multi-scale methods were used (wavelets or contourlets) for denoising the residual. The iterations are initialized by the CS data. In the second approach, we used a frequency splitting technique by quadrature filtering to combine low frequency components derived from MC simulations with high frequency components derived from CS components. The rationale is to take the scattering tails as well as dose levels in the high-dose region from the MC calculations, which presumably more accurately incorporates scatter; high-frequency details are taken from CS calculations. 3D Butterworth filters were used to design the quadrature filters. The methods were demonstrated using anonymized clinical lung and head and neck cases. The MC dose distributions were calculated by the open-source dose planning method MC code with varying noise levels. Our results indicate that the frequency-splitting technique for incorporating CS-guided MC denoising is promising in terms of computational efficiency and noise reduction.

MicroRT-small animal conformal irradiator.

A novel small animal conformal radiation therapy system has been designed and prototyped: MicroRT. The microRT system integrates multimodality imaging, radiation treatment planning, and conformal radiation therapy that utilizes a clinical 192Ir isotope high dose rate source as the radiation source (teletherapy). A multiparameter dose calculation algorithm based on Monte Carlo dose distribution simulations is used to efficiently and accurately calculate doses for treatment planning purposes. A series of precisely machined tungsten collimators mounted onto a cylindrical collimator assembly is used to provide the radiation beam portals. The current design allows a source-to-target distance range of 1-8 cm at four beam angles: 0 degrees (beam oriented down), 90 degrees, 180 degrees, and 270 degrees. The animal is anesthetized and placed in an immobilization device with built-in fiducial markers and scanned using a computed tomography, magnetic resonance, or positron emission tomography scanner prior to irradiation. Treatment plans using up to four beam orientations are created utilizing a custom treatment planning system-microRTP. A three-axis computer-controlled stage that supports and accurately positions the animals is programmed to place the animal relative to the radiation beams according to the microRTP plan. The microRT system positioning accuracy was found to be submillimeter. The radiation source is guided through one of four catheter channels and placed in line with the tungsten collimators to deliver the conformal radiation treatment. The microRT hardware specifications, the accuracy of the treatment planning and positioning systems, and some typical procedures for radiobiological experiments that can be performed with the microRT device are presented.

Dose response explorer: an integrated open-source tool for exploring and modelling radiotherapy dose-volume outcome relationships.

Radiotherapy treatment outcome models are a complicated function of treatment, clinical and biological factors. Our objective is to provide clinicians and scientists with an accurate, flexible and user-friendly software tool to explore radiotherapy outcomes data and build statistical tumour control or normal tissue complications models. The software tool, called the dose response explorer system (DREES), is based on Matlab, and uses a named-field structure array data type. DREES/Matlab in combination with another open-source tool (CERR) provides an environment for analysing treatment outcomes. DREES provides many radiotherapy outcome modelling features, including (1) fitting of analytical normal tissue complication probability (NTCP) and tumour control probability (TCP) models, (2) combined modelling of multiple dose-volume variables (e.g., mean dose, max dose, etc) and clinical factors (age, gender, stage, etc) using multi-term regression modelling, (3) manual or automated selection of logistic or actuarial model variables using bootstrap statistical resampling, (4) estimation of uncertainty in model parameters, (5) performance assessment of univariate and multivariate analyses using Spearman's rank correlation and chi-square statistics, boxplots, nomograms, Kaplan-Meier survival plots, and receiver operating characteristics curves, and (6) graphical capabilities to visualize NTCP or TCP prediction versus selected variable models using various plots. DREES provides clinical researchers with a tool customized for radiotherapy outcome modelling. DREES is freely distributed. We expect to continue developing DREES based on user feedback.

A comparison of Monte Carlo dose calculation denoising techniques.

Recent studies have demonstrated that Monte Carlo (MC) denoising techniques can reduce MC radiotherapy dose computation time significantly by preferentially eliminating statistical fluctuations ('noise') through smoothing. In this study, we compare new and previously published approaches to MC denoising, including 3D wavelet threshold denoising with sub-band adaptive thresholding, content adaptive mean-median-hybrid (CAMH) filtering, locally adaptive Savitzky-Golay curve-fitting (LASG), anisotropic diffusion (AD) and an iterative reduction of noise (IRON) method formulated as an optimization problem. Several challenging phantom and computed-tomography-based MC dose distributions with varying levels of noise formed the test set. Denoising effectiveness was measured in three ways: by improvements in the mean-square-error (MSE) with respect to a reference (low noise) dose distribution; by the maximum difference from the reference distribution and by the 'Van Dyk' pass/fail criteria of either adequate agreement with the reference image in low-gradient regions (within 2% in our case) or, in high-gradient regions, a distance-to-agreement-within-2% of less than 2 mm. Results varied significantly based on the dose test case: greater reductions in MSE were observed for the relatively smoother phantom-based dose distribution (up to a factor of 16 for the LASG algorithm); smaller reductions were seen for an intensity modulated radiation therapy (IMRT) head and neck case (typically, factors of 2-4). Although several algorithms reduced statistical noise for all test geometries, the LASG method had the best MSE reduction for three of the four test geometries, and performed the best for the Van Dyk criteria. However, the wavelet thresholding method performed better for the head and neck IMRT geometry and also decreased the maximum error more effectively than LASG. In almost all cases, the evaluated methods provided acceleration of MC results towards statistically more accurate results.

Uncertainties in model-based outcome predictions for treatment planning.

PURPOSE: Model-based treatment-plan-specific outcome predictions (such as normal tissue complication probability [NTCP] or the relative reduction in salivary function) are typically presented without reference to underlying uncertainties. We provide a method to assess the reliability of treatment-plan-specific dose-volume outcome model predictions. METHODS AND MATERIALS: A practical method is proposed for evaluating model prediction based on the original input data together with bootstrap-based estimates of parameter uncertainties. The general framework is applicable to continuous variable predictions (e.g., prediction of long-term salivary function) and dichotomous variable predictions (e.g., tumor control probability [TCP] or NTCP). Using bootstrap resampling, a histogram of the likelihood of alternative parameter values is generated. For a given patient and treatment plan we generate a histogram of alternative model results by computing the model predicted outcome for each parameter set in the bootstrap list. Residual uncertainty ("noise") is accounted for by adding a random component to the computed outcome values. The residual noise distribution is estimated from the original fit between model predictions and patient data. RESULTS: The method is demonstrated using a continuous-endpoint model to predict long-term salivary function for head-and-neck cancer patients. Histograms represent the probabilities for the level of posttreatment salivary function based on the input clinical data, the salivary function model, and the three-dimensional dose distribution. For some patients there is significant uncertainty in the prediction of xerostomia, whereas for other patients the predictions are expected to be more reliable. In contrast, TCP and NTCP endpoints are dichotomous, and parameter uncertainties should be folded directly into the estimated probabilities, thereby improving the accuracy of the estimates. Using bootstrap parameter estimates, competing treatment plans can be ranked based on the probability that one plan is superior to another. Thus, reliability of plan ranking could also be assessed. CONCLUSIONS: A comprehensive framework for incorporating uncertainties into treatment-plan-specific outcome predictions is described. Uncertainty histograms for continuous variable endpoint models provide a straightforward method for visual review of the reliability of outcome predictions for each treatment plan.

A prospective study of salivary function sparing in patients with head-and-neck cancers receiving intensity-modulated or three-dimensional radiation therapy: initial results.

OBJECTIVES: In a prospective clinical study, we tested the hypothesis that sparing the parotid glands may result in significant objective and subjective improvement of xerostomia in patients with head-and-neck cancers. The functional outcome 6 months after the completion of radiation therapy is presented. METHODS AND MATERIALS: From February 1997 to February 1999, 41 patients with head-and-neck cancers were enrolled in a prospective salivary function study. Inverse-planning intensity-modulated radiation therapy (IMRT) was used to treat 27 patients, and forward-planning three-dimensional radiation therapy in 14. To avoid potential bias in data interpretation, only patients whose submandibular glands received greater than 50 Gy were eligible. Attempts were made to spare the superficial lobe of the parotid glands to avoid underdosing tumor targets in the parapharyngeal space; however, the entire parotid volume was used to compute dose-volume histograms (DVHs) for this analysis. DVHs were computed for each gland separately. Parotid function was assessed objectively by measuring stimulated and unstimulated saliva flow before and 6 months after the completion of radiation therapy. Measurements were converted to flow rate (mL/min) and normalized relative to that before treatment. The corresponding quality-of-life (QOL) outcome was assessed by five questions regarding the patient's oral discomfort and eating/speaking problems. RESULTS: We observed a correlation between parotid mean dose and the fractional reduction of stimulated saliva output at 6 months after the completion of radiation therapy. We further examined whether the functional outcome could be modeled as a function of dose. Two models were found to describe the dose-response data well. The first model assumed that each parotid gland is comprised of multiple independent parallel functional subunits (corresponding to computed tomography voxels) and that each gland contributes equally to overall flow, and that saliva output decreases exponentially as a quadratic function of irradiation dose to each voxel. The second approach uses the equivalent uniform dose (EUD) metrics, which assumes loss of salivary function with increase in EUD for each parotid gland independently. The analysis suggested that the mean dose to each parotid gland is a reasonable indicator for the functional outcome of each gland. The corresponding exponential coefficient was 0.0428/Gy (95% confidence interval: 0.01, 0.09). The QOL questions on eating/speaking function were significantly correlated with stimulated and unstimulated saliva flow at 6 months. In a multivariate analysis, a toxicity score derived from the model based on radiation dose to the parotid gland was found to be the sole significant predictive factor for xerostomia. Neither radiation technique (IMRT vs. non-IMRT) nor chemotherapy (yes or no) independently influenced the functional outcome of the salivary glands. CONCLUSION: Sparing of the parotid glands translates into objective and subjective improvement of both xerostomia and QOL scores in patients with head-and-neck cancers receiving radiation therapy. Modeling results suggest an exponential relationship between saliva flow reduction and mean parotid dose for each gland. We found that the stimulated saliva flow at 6 months after treatment is reduced exponentially, for each gland independently, at a rate of approximately 4% per Gy of mean parotid dose.

Denoising of electron beam Monte Carlo dose distributions using digital filtering techniques.

The Monte Carlo (MC) method has long been viewed as the ultimate dose distribution computational technique. The inherent stochastic dose fluctuations (i.e. noise), however, have several important disadvantages: noise will affect estimates of all the relevant dosimetric and radiobiological indices, and noise will degrade the resulting dose contour visualizations. We suggest the use of a post-processing denoising step to reduce statistical fluctuations and also improve dose contour visualization. We report the results of applying four different two-dimensional digital smoothing filters to two-dimensional dose images. The Integrated Tiger Series MC code was used to generate 10 MeV electron beam dose distributions at various depths in two different phantoms. The observed qualitative effects of filtering include: (a) the suppression of voxel-to voxel (high-frequency) noise and (b) the resulting contour plots are visually more comprehensible. Drawbacks include, in some cases, slight blurring of penumbra near the surface and slight blurring of other very sharp real dosimetric features. Of the four digital filters considered here, one, a filter based on a local least-squares principle, appears to suppress noise with negligible degradation of real dosimetric features. We conclude that denoising of electron beam MC dose distributions is feasible and will yield improved dosimetric reliability and improved visualization of dose distributions.

A proton dose calculation algorithm for conformal therapy simulations based on Molière's theory of lateral deflections.

An algorithm is developed for computing proton dose distributions in the therapeutic energy range (100-250 MeV). The goal is to provide accurate pencil beam dose distributions for two-dimensional or three-dimensional simulations of possible intensity-modulated proton therapy delivery schemes. The algorithm is based on Molière's theory of lateral deflections, which accurately describes the distribution of lateral deflections suffered by incident charged particles. The theory is applied to nonuniform targets through the usual pencil beam approximation which assumes that all protons from a given pencil beam pass through the same material at each depth. Fluence-to-dose conversion is made via Monte Carlo calculated broad-field central-axis depth-dose curves, which accounts for attenuation due to nuclear collisions and range straggling. Calculation speed is enhanced by using a best-fit Gaussian approximation of the radial distribution function at depth. Representative pencil beam and spread-out Bragg-peak computations are presented at 250 MeV and 160 MeV in water. Computed lateral full-widths-at-half-maximum's in water, at the Bragg peak, agree with the expected theoretical lateral values to within 1% at 160 MeV and to within 3% at 250 MeV. This algorithm differs from convolution methods in that the effect of the depth of any inhomogeneities in density or atomic composition are accounted for in a rigorous fashion. The algorithm differs from Fermi-Eyges based methods by accounting in a rigorous way for the effect of nonsmall-angle scattering and screening due to atomic electrons. The computational burden is only slightly greater than that expected using the less-rigorous Fermi-Eyges theory.

Multiple local minima in radiotherapy optimization problems with dose-volume constraints.

The cause of multiple local minima in beam weight optimization problems subject to dose-volume constraints is analyzed. Three objective functions were considered: (a) maximization of tumor control probability (TCP), (b) maximization of the minimum target dose, and (c) minimization of the mean-squared-deviation of the target dose from the prescription dose. It is shown that: (a) TCP models generally result in strongly quasiconvex objective functions; (b) maximization of the minimum target dose results in a strongly quasiconvex objective function; and (c) minimizing the root-mean-square dose deviation results in a convex objective function. Dose-volume constraints are considered such that, for each region at risk (RAR), the volume of tissue whose dose exceeds a certain tolerance dose (DTol) is kept equal to or below a given fractional level (VTol). If all RARs lack a "volume effect" (i.e., VTol = 0 for all RARs) then there is a single local minimum. But if volume effects are present, then the feasible space is possibly nonconvex and therefore possibly leads to multiple local minima. These conclusions hold for all three objective functions. Hence, possible local minima come not from the nonlinear nature of the objective functions considered, but from the "either this volume or that volume but not both" nature of the volume effect. These observations imply that optimization algorithms for dose-volume constraint types of problems should have effective strategies for dealing with multiple local minima.

An investigation of tomotherapy beam delivery.

Experimental simulations for tomotherapy beam delivery were performed using a computer-controlled phantom positioner, a cylindrical phantom, and a 6 MV x-ray slit beam. Both continuous helical beam and sequential segmented tomotherapy (SST) beam deliveries were evaluated. Beam junctioning problem due to couch indexing error or field width errors presented severe dose uniformity perturbations for SST, while the problem was minimized for helical beam delivery. Longitudinal breathing motions were experimentally simulated for helical and SST beam delivery. While motions reduced the dose uniformity perturbations for SST, small artifacts in dose uniformity can be introduced for helical beam delivery. With typical breath frequency and magnitude, for a slit beam of 2.0 cm width at 4 rpm, the dose uniformity perturbation was not significant. A running start/stop technique was implemented with helical beam delivery to sharpen the 20%-80% longitudinal dose fall-off from 1.5 to 0.5 cm. The latter was comparable to the corresponding dose penumbra of a conventional 6 MV 10 x 10 cm2 field. All together, helical beam delivery showed advantages over SST for tomotherapy beam delivery under similar delivery conditions.

The dose distribution produced by a 32P source for endovascular irradiation.

PURPOSE: Percutaneous transluminal coronary angioplasty (PTCA) is one of the most common therapies for obstructive coronary artery disease. Unfortunately, subsequent restenosis after percutaneous balloon angioplasty occurs in 30-50% of patients and remains one of the major unsolved problems of contemporary cardiology. The study of endovascular irradiation has been greatly stimulated by the discovery that the process of restenosis may be impaired by irradiation. The objective of this study was to examine a custom-made commercial 32P wire and to determine whether the present source presentation is suitable for this application. METHODS AND MATERIALS: Measurements of the dose distribution around a 3 mm long 32P source with an activity of 0.414 GBq (11.2 mCi) were made by using LiF thermoluminescent dosimeters and a scintillation detector. The source had the dimensions of 0.3 mm in diameter and 3 mm in length, and was first encapsulated by a plastic tube and then encapsulated in a specially manufactured Ni-Ti wire with a diameter of 0.4 mm and a length of 2.6 m. The detector size effect is removed from the measurements calculation. Loevinger's equation for the dose distribution around a 32P source was used for the calculations. RESULTS: The dose rate at a radial distance of 1.5 mm was 53 cGy/s per GBq (1.96 cGy/s per mCi) and fell off rapidly perpendicularly to the axis of the source in an approximately exponential manner, from 53-5.3 cGy/s per GBq (approximately 2 to 0.2 cGy/s per mCi) as radial distances increased from 0.2 to 0.4 g/cm2 (1.5 to 3.5 mm away from the center of the source). The treatment length parallel along the wire could be as long as 24 mm for eight source dwell positions with the average dose rate of 59 cGy/s per GBq (2.2 cGy/s per mCi) and a variation of +/- 2.3% at a radial distance of 1.5 mm. CONCLUSIONS: Our experiments show that the dose distribution is ideal for endovascular irradiation. The source was incorporated in the end of a flexible cable and with a half-life of 14.3 days is suitable for endovascular irradiation.

Measured electron energy and angular distributions from clinical accelerators.

Electron energy spectra and angular distributions, including angular spreads, were measured using magnetic spectrometer techniques, at isocenter, for two clinical linear accelerators: one scanning beam machine, which achieves field flatness by scanning a pencil beam over the desired field at the patient plane, and one scattering foil machine, which disperses the electrons through a graded-thickness scattering foil. All measurements were made at isocenter (in the patient plane), in air, 1 m from the nominal accelerator source. The energy measurements were confined to electrons traveling along the central axis; any widely scattered electrons were effectively neglected. The energy spectra of the scanning beam machine are all of nearly Gaussian shape and energy full-width-at-half-maximum intensity (FWHM) of about 5% of the peak mean energy (denoted (E0)*). The energy spectra of the scattering foil machine have a variety of forms as a function of energy, including even spectra with double peaks, and spectra which changed with time. The FWHM values ranged from 9%-22% of (E0)*. The angular spread measurements, at isocenter, yielded sigma theta (x) x (E0)* approximately 295 mrad-MeV for the scanning beam machine, and 346 mrad-MeV for the scattering foil machine, where sigma theta x denotes the standard deviation of the plane-projected angular distribution. These angular spreads are 30%-40% smaller than angular spreads reported by others on a very similar machine using the penumbra method. Possible causes of this discrepancy are discussed.