Correlation between lung fibrosis and radiation therapy dose after concurrent radiation therapy and chemotherapy for limited small cell lung cancer.

PURPOSE: To evaluate the relationship between physician-identified radiographic fibrosis, lung tissue physical density change, and radiation dose after concurrent radiation therapy and chemotherapy for limited small cell lung cancer. MATERIALS AND METHODS: Fibrosis volumes of different severity levels were delineated on computed tomography (CT) images obtained at 1-year follow-up of 21 patients with complete response to concurrent radiation therapy and chemotherapy for limited small cell lung carcinoma. Delivered treatments were reconstructed with a three-dimensional treatment planning system and geometrically registered to the follow-up CT images. Tissue physical density change and radiation dose were computed for each voxel within each fibrosis volume and within normal lung. Patient responses were grouped per radiation and chemotherapy protocol. RESULTS: A significant correlation was noted between fibrosis grade and tissue physical density change and fibrosis grade. For doses less than 30 Gy, the probability of observing fibrosis was less than 2% with conventional fractionation and less than 4% with accelerated fractionation. Physical lung density change also showed a threshold of 30-35 Gy. For doses of 30-55 Gy and cisplatin and etoposide (PE) chemotherapy, fibrosis probability was 2.0 times greater for accelerated fractionation compared with conventional fractionation (P < .005) and was correlated to increasing dose for both fractionation schedules. CONCLUSION: Lung tissue physical density changes correlated well with fibrosis incidence, and both increased with increasing dose greater than a threshold of 30-35 Gy. With concurrent PE chemotherapy, fibrosis probability was twice as great with accelerated fractionation as with once-daily fractionation.

Phase I study of concomitant gemcitabine and IMRT for patients with unresectable adenocarcinoma of the pancreatic head.

PURPOSE: We hypothesized that dynamic intensity-modulated radiotherapy (IMRT) would protect normal tissues enough to allow the escalation of either the gemcitabine or radiotherapy dose in unresectable pancreatic cancer patients. METHODS AND MATERIALS: The trial was designed to build on a previous phase I trial that determined the maximum tolerated dose (MTD) of gemcitabine (350 mg/m2) with concurrent radiotherapy (30 Gy/10 fractions). Only patients with unresectable disease based on established criteria were eligible. The plan was to alternate escalating the radiation dose by 3 Gy and the gemcitabine dose by 50 mg/m2. The starting dose of gemcitabine was 350 mg/m2 and 33 Gy/11 fractions of IMRT to the regional lymphatics and primary disease. The NCI Common Toxicity Criteria were used for dose-limiting toxicity (DLT). RESULTS: All three patients in the first cohort treated suffered DLT. Therefore, a second cohort of patients received a lower gemcitabine dose (250 mg/m2). Both patients treated at this dose level experienced DLT. The DLTs were all due to myelosuppression and upper gastrointestinal toxicity. All patients required a gemcitabine dose reduction. Also, four patients required hospital admission for supportive care, while the fifth died of an unrelated cause shortly after completing therapy. The trial was then closed due to excessive toxicity. CONCLUSION: Hypofractionated dynamic IMRT to the primary site and regional lymphatics did not permit escalation of either the radiation or gemcitabine dose. Dynamic IMRT requires further investigation before it can be applied to toxic combinations of chemotherapy and radiation in the upper abdomen.

Beam-commissioning methodology for a three-dimensional convolution/superposition photon dose algorithm.

Commissioning beam data for the convolution/superposition dose-calculation algorithm used in a commercial three-dimensional radiation treatment planning (3D RTP) system (PINNACLE(3), ADAC Laboratories, Milpitas, CA) can be difficult and time consuming. Sixteen adjustable parameters, as well as spectral weights representing a discrete energy spectrum, must be fit to sets of central-axis depth doses and off-axis profiles for a large number of field sizes. This paper presents the beam-commissioning methodology that we used to generate accurate beam models. The methodology is relatively rapid and provides physically reasonable values for beam parameters. The methodology was initiated by using vendor-provided automodeling software to generate a single set of beam parameters that gives an approximate fit to relative dose distributions for all beams, open and wedged, in a data set. A limited number of beam parameters were adjusted by small amounts to give accurate beam models for four open-beam field sizes and three wedged-beam field sizes. Beam parameters for other field sizes were interpolated and validated against measured beam data. Using this methodology, a complete set of beam parameters for a single energy can be generated and validated in approximately 40 h. The resulting parameter values yielded calculated relative doses that matched measured relative doses in a water phantom to within 0.5-1.0% along the central axis and 2% along off-axis beam profiles for field sizes from 4 cmx4 cm to the largest field size available. While the methodology presented is specific to the ADAC PINNACLE(3) treatment planning system, the approach should apply to other implementations of the dose model in other treatment planning system.

On the need for monitor unit calculations as part of a beam commissioning methodology for a radiation treatment planning system.

This paper illustrates the need for validating the calculation of monitor units as part of the process of commissioning a photon beam model in a radiation treatment planning system. Examples are provided in which this validation identified subtle errors, either in the dose model or in the implementation of the dose algorithm. These errors would not have been detected if the commissioning process only compared relative dose distributions. A set of beam configurations, with varying field sizes, source-to-skin distances, wedges, and blocking, were established to validate monitor unit calculations for two different beam models in two different radiation treatment planning systems. Monitor units calculated using the treatment planning systems were compared with monitor units calculated from point dose calculations from tissue-maximum ratio (TMR) tables. When discrepancies occurred, the dose models and the code were analyzed to identify the causes of the discrepancies. Discrepancies in monitor unit calculations were both significant (up to 5%) and systematic. Analysis of the dose computation software found: (1) a coordinate system transformation error, (2) mishandling of dose-spread arrays, (3) differences between dose calculations in the commissioning software and the planning software, and (4) shortcomings in modeling of head scatter. Corrections were made in the beam calculation software or in the data sets to overcome these discrepancies. Consequently, we recommend incorporating validation of monitor unit calculations as part of a photon beam commissioning process.

Prostate cancer treatment with radiotherapy: maturing methods that minimize morbidity.

Technological advances in treatment delivery and planning have provided the backdrop for an unprecedented number of options in the treatment of prostate cancer with radiotherapy. The more common choices include classical external-beam radiotherapy, external-beam radiotherapy using three-dimensional treatment planning and conformal radiotherapy (3DCRT), ultrasound-guided transperineal implant monotherapy alone or in combination with external-beam radiotherapy, and intensity-modulated radiotherapy (IMRT) techniques. This chapter reviews the data from these methods with an emphasis on dose escalation, provides comparisons with prostate-specific antigen (PSA)-era radical prostatectomy series where appropriate, and highlights future initiatives designed to further improve outcome.

Planning target volumes for radiotherapy: how much margin is needed?

PURPOSE: The radiotherapy planning target volume (PTV) encloses the clinical target volume (CTV) with anisotropic margins to account for possible uncertainties in beam alignment, patient positioning, organ motion, and organ deformation. Ideally, the CTV-PTV margin should be determined solely by the magnitudes of the uncertainties involved. In practice, the clinician usually also considers doses to abutting healthy tissues when deciding on the size of the CTV-PTV margin. This study calculates the ideal size of the CTV-PTV margin when only physical position uncertainties are considered. METHODS AND MATERIALS: The position of the CTV for any treatment is assumed to be described by independent Gaussian distributions in each of the three Cartesian directions. Three strategies for choosing a CTV-PTV margin are analyzed. The CTV-PTV margin can be based on: 1. the probability that the CTV is completely enclosed by the PTV; 2. the probability that the projection of the CTV in the beam's eye view (BEV) is completely enclosed by the projection of the PTV in the BEV; and 3. the probability that a point on the edge of the CTV is within the PTV. Cumulative probability distributions are derived for each of the above strategies. RESULTS: Expansion of the CTV by 1 standard deviation (SD) in each direction results in the CTV being entirely enclosed within the PTV 24% of the time; the BEV projection of the CTV is enclosed within the BEV projection of the PTV 39% of the time; and a point on the edge of the CTV is within the PTV 84% of the time. To have the CTV enclosed entirely within the PTV 95% of the time requires a margin of 2.8 SD. For the BEV projection of the CTV to be within the BEV projection of the PTV 95% of the time requires a margin of 2.45 SD. To have any point on the surface of the CTV be within the PTV 95% of the time requires a margin of 1.65 SD. CONCLUSION: In the first two strategies for selecting a margin, the probability of finding the CTV within the PTV is unrelated to dose variations in the CTV. In the third strategy, the specified confidence limit is correlated with the minimum target dose. We recommend that the PTV be calculated from the CTV using a margin of 1.65 SD in each direction. This gives a minimum CTV dose that is greater than 95% of the minimum PTV dose. Additional sparing of adjoining healthy structures should be accomplished by modifying beam portals, rather than adjusting the PTV. Then, the dose distributions more accurately reflect the clinical compromise between treating the tumor and sparing the patient.

Optimization of beam orientations and weights for coplanar conformal beams in treating pancreatic cancer.

In treating pancreatic cancer with external-beam radiotherapy, radiation dose given to the tumor volume is largely limited by the tolerance of the normal structures near the disease site, including the kidneys, liver, stomach, small bowel, and spinal cord. The purpose of this work was to investigate whether a coplanar conformal therapy technique with beam optimization could reduce dose to the normal tissues compared to the conventional 4-field technique; and if this was true, whether other beam arrangements were more effective than the 4-field technique in treating pancreatic cancer. In this study, 9 patients who were treated previously for T3N0 or T3N1 pancreatic cancer with external-beam therapy of 30 Gy in 10 fractions were selected. Beam orientations and weights were optimized for 4 to 6 coplanar conformal beams using a simulated annealing algorithm to minimize the kidney volume receiving more than 20 Gy. Optimized plans were compared with standard plans using a 4-field technique with respect to the isodose distributions and dose volume histograms. For the standard 4-field plans giving 30 Gy to the tumor volume, the total kidney volume above 20 Gy ranged from 10% to 35%, with a mean of 22% and a standard deviation of 7%. Optimization of the beam orientations and weights reduced this volume by approximately 2 times without a significant increase of dose to the liver, stomach, and small bowel. This indicated that the radiation toxicity to the kidneys could be reduced substantially by a careful selection of oblique beam angles and weights. Analysis of the optimized plans showed that beam arrangements which involved left and right anterior oblique beams were superior to the conventional 4-field technique for reducing the kidney dose in treating pancreatic cancer.

Effect of using an initial polyenergetic spectrum with the pencil-beam redefinition algorithm for electron-dose calculations in water.

This work compares the accuracy of dose distributions computed using an incident polyenergetic (PE) spectrum and a monoenergetic (ME) spectrum in the electron pencil-beam redefinition algorithm (PBRA). It also compares the times required to compute PE and ME dose distributions. This has been accomplished by comparing PBRA calculated dose distributions with measured dose distributions in water from the National Cancer Institute electron collaborative working group (ECWG) data set. Comparisons are made at 9 and 20 MeV for the 15 x 15 cm2 and 6 x 6 cm2 fields at 100- and 110-cm SSD. The incident PE spectrum is determined by a process that best matches the weighted sum of monoenergetic PBRA calculated central-axis depth doses, each calculated with the energy correction factor, C(E), equal to unity, to the ECWG measured depth dose for the 15 x 15 cm2 field at 100-cm SSD. C(E) is determined by a least square fit to central-axis depth dose for the PE PBRA. Results show that both the PE and ME PBRA accurately calculate central-axis depth dose at 100-cm SSD for the 6 x 6 cm2 and 15 x 15 cm2 field sizes and also at 110-cm SSD for the 15 x 15 cm2 field size. In the penumbral region, the PE PBRA calculation is significantly more accurate than the ME PBRA for all measurement conditions. Both the PE and ME PBRA exhibit significant dose errors (> 4%) outside the penumbra at shallow depths for the 6 x 6 cm2 and 15 x 15 cm2 fields at 100-cm SSD and inside the penumbra at shallow depths for the 6 x 6 cm2 field size at 110-cm SSD. These errors are attributed to the fact that the PBRA does not model collimator scatter in the incident beam. Calculation times for the PE PBRA are approximately 70%-140% greater than those for the ME PBRA. We conclude that the PE PBRA is significantly more accurate than the ME PBRA, and we believe that the increase in time for the PE PBRA will not significantly impact the clinical utility of the PBRA.

Prostate target volume variations during a course of radiotherapy.

PURPOSE: The purpose of this study was to measure the mobility of the clinical target volume (CTV) in prostate radiotherapy with respect to the pelvic anatomy during a course of therapy. These data are needed to properly design the planning target volume (PTV). METHODS AND MATERIALS: Seventeen patients were studied. Each patient underwent computed tomography (CT) scanning for treatment planning purposes. Subsequently, three CT scans were obtained at approximately 2-week intervals during treatment. The prostate, seminal vesicles, bladder, and rectum were outlined on each CT study. The second through the fourth CT studies were aligned with the first study using a rigid body transformation based on the bony anatomy. The transformation was used to compute the center of mass position and bounding box of each organ in the subsequent studies relative to the first study. Differences in the bounding box limits and center of mass positions between the first and subsequent studies were tabulated and correlated with bladder and rectal volume and positional parameters. RESULTS: The mobility of the CTV was characterized by standard deviations of 0.09 cm (left-right), 0.36 cm (cranial-caudal), and 0.41cm (anterior-posterior). Prostate mobility was not significantly correlated with bladder volume. However, the mobility of both the prostate and seminal vesicles was very significantly correlated with rectal volume. Bladder and rectal volumes decreased between the pretreatment CT scan and the first on-treatment CT scan, but were constant for all on-treatment CT scans. CONCLUSION: Margins between the CTV and PTV based on the simple geometric requirement that a point on the edge of the CTV is enclosed by the PTV 95% of the time are 0.7 cm in the lateral and cranial-caudal directions, and 1.1 cm in the anterior-posterior direction. However, minimum dose to the CTV and avoidance of organs at risk are more important considerations when drawing beam apertures. More consistent methods for reproducing prostate position (e.g., empty rectum) and more sophisticated beam aperture optimization are needed to guarantee consistent coverage of the CTV while avoiding organs at risk.

Writing software for the clinic.

Medical physicists often write computer programs to support scientific, educational, and clinical endeavors. Errors in scientific and educational software can waste time and effort by producing meaningless results, but errors in clinical software can contribute to patient injuries. Although the ultimate goal of error-free software is impossible to achieve except in very small programs, there are many good design, implementation, and testing practices that can be used by small development groups to significantly reduce errors, improve quality, and reduce maintenance. The software development process should include four basic steps: specifications, design, implementation, and testing. A specifications document defining what the software is intended to do is valuable for clearly delimiting the scope of the project and providing a benchmark for evaluating the final product. Keep the software design simple and straightforward. Document assumptions, and check them. Emphasize maintainability, portability, and reliability rather than speed. Use layers to isolate the application from hardware and the operating system. Plan for upgrades. Expect the software to be used in unplanned ways. Whenever possible, be generous with RAM and disk storage; hardware is cheaper than development and maintenance. During implementation, use well-known algorithms whenever possible. Use prototypes to try out ideas. Use generic modules, version numbering, unique file names, defensive programming, and operating system and language/compiler defaults. Avoid binary data files and clever tricks. Remember that real numbers are not exact in a computer. Get it right before making it faster. Document the software extensively. Test continuously during development; the later a problem is found, the more it costs to fix. Use a written procedure to test the final product exactly as a typical user would run it. Allow no changes after clinical release. Expect to spend at least an additional 50% of the initial development effort on testing, fixing errors, and getting the software into routine operation.

Evaluation and scoring of radiotherapy treatment plans using an artificial neural network.

PURPOSE: The objective of this work was to demonstrate the feasibility of using an artificial neural network to predict the clinical evaluation of radiotherapy treatment plans. METHODS AND MATERIALS: Approximately 150 treatment plans were developed for 16 patients who received external-beam radiotherapy for soft-tissue sarcomas of the lower extremity. Plans were assigned a figure of merit by a radiation oncologist using a five-point rating scale. Plan scoring was performed by a single physician to ensure consistency in rating. Dose-volume information extracted from a training set of 511 treatment plans on 14 patients was correlated to the physician-generated figure of merit using an artificial neural network. The neural network was tested with a test set of 19 treatment plans on two patients whose plans were not used in the training of the neural net. RESULTS: Physician scoring of treatment plans was consistent to within one point on the rating scale 88% of the time. The neural net reproduced the physician scores in the training set to within one point approximately 90% of the time. It reproduced the physician scores in the test set to within one point approximately 83% of the time. CONCLUSIONS: An artificial neural network can be trained to generate a score for a treatment plan that can be correlated to a clinically-based figure of merit. The accuracy of the neural net in scoring plans compares well with the reproducibility of the clinical scoring. The system of radiotherapy treatment plan evaluation using an artificial neural network demonstrates promise as a method for generating a clinically relevant figure of merit.

Conventional vs. conformal radiotherapy for prostate cancer: preliminary results of dosimetry and acute toxicity.

PURPOSE: To compare conformal radiotherapy using three dimensional treatment planning (3D-CRT) to conventional radiotherapy (Conven-RT) for patients with Stages T2-T4 adenocarcinoma of the prostate. METHODS AND MATERIALS: A Phase III randomized study was activated in May 1993, to compare treatment toxicity and patient outcome after 78 Gy in 39 fractions using 3D-CRT to that after 70 Gy in 35 fractions using Conven-RT. The first 46 Gy were administered using the same nonconformal field arrangement (four field) in both arms. The boost was given nonconformally using four fields in the Conven-RT arm and conformally using six fields in the 3D-CRT arm. The dose was specific to the isocenter. The first 60 patients, 29 in the 3D-CRT arm and 31 in the Conven-RT arm, are the subject of this preliminary analysis. RESULTS: The two treatment arms were first compared in terms of dosimetry by dose-volume histogram analysis. Using a subgroup of patients in the 3D-CRT arm (n=15), both Conven-RT and 3D-CRT plans were generated and the dose-volume histogram data compared. The mean volumes treated to doses above 60 Gy for the bladder and rectum were 28 and 36% for the 3D-CRT plans, and 43 and 38% for the Conven-RT plans, respectively (p < 0.05 for the bladder volumes). The mean clinical target volume (prostate and seminal vesicles) treated to 95% of the prescribed dose was 97.5% for the 3D-CRT arm, and 95.6% for the Conven-RT arm (p < 0.05). There were no significant differences in the acute reactions between the two arms, with the majority experiencing Grade 2 or less toxicity (92%). Moreover, no relationship was seen between acute toxicity and the volume of bladder and rectum receiving in excess of 60 Gy for those in the 3D-CRT arm. There was also no difference between the groups in terms of early biochemical response. Prostate-specific antigen levels at 3 and 6 months after completion of radiotherapy were similar in the two treatment arms. There was only one biochemical failure in the study population at the time of the analysis. CONCLUSIONS: Comparison of the Conven-RT and 3D-RT treatment plans revealed that significantly less bladder was in the high dose volume in the 3D-CRT plans, while the volume of rectum receiving doses over 60 Gy was equivalent. There were no differences between the two treatment arms in terms of acute toxicity or early biochemical response. Longer follow-up is needed to determine the impact of 3D-CRT on long-term patient outcome and late reactions.

Comparison of simulated annealing algorithms for conformal therapy treatment planning.

PURPOSE: The efficiency of four fast simulated annealing algorithms for optimizing conformal radiation therapy treatment plans was studied and the resulting plans were compared with each other and to optimized conventional plans. METHODS AND MATERIALS: Four algorithms were selected on the basis of their reported successes in solving other minimization problems: fast simulated annealing with a Cauchy generating function, fast simulated annealing with a Lorentzian generating function, variable step size generalized simulated annealing (VSGSA), and very fast simulated reannealing (VFSR). They were tested on six clinical cases using a multiple beam coplanar conformal treatment technique. Relative beam weights were computed that maximized the minimum tumor dose subject to dose-volume constraints on normal organ doses. Following some initial tuning of the annealing parameters, each algorithm was applied identically to each test case. Optimization tests were run using different random number sequences and different numbers of iterations. RESULTS: The VSGSA algorithm consistently produced the best results. Using long run times, it generated plans with the highest minimum tumor dose in five of the six cases. For the short run times, the VSGSA solutions averaged larger minimum tumor doses than those of the other algorithms for all six patients, with increases ranging from 0.4 to 5.9 Gy. For three of the patients, the conformal plan gave a clinically significant increase in the minimum tumor dose over the conventional plan, ranging from 8.2 to 13.0 Gy. In two other cases, there was little difference between the two treatment approaches. For one case, the optimized conventional plan was much better than the conformal plan because the conventional beam arrangement included wedges, which offset the multiple beam advantage of the conformal plans. CONCLUSIONS: For equal computing times of both long and short duration, the VSGSA algorithm consistently produced conformal plans that were superior to those produced by the other algorithms. The simple conformal technique used in this study showed a significant potential advantage in the treatment of abdominal tumors. In three of the cases, the conformal plans showed clinically important increases in tumor dose over optimized conventional plans.

Very fast simulated reannealing in radiation therapy treatment plan optimization.

PURPOSE: Very Fast Simulated Reannealing is a relatively new (1989) and sophisticated algorithm for simulated annealing applications. It offers the advantages of annealing methods while requiring shorter execution times. The purpose of this investigation was to adapt Very Fast Simulated Reannealing to conformal treatment planning optimization. METHODS AND MATERIALS: We used Very Fast Simulated Reannealing to optimize treatments for three clinical cases with two different cost functions. The first cost function was linear (minimum target dose) with nonlinear dose-volume normal tissue constraints. The second cost function (probability of uncomplicated local control) was a weighted product of normal tissue complication probabilities and the tumor control probability. RESULTS: For the cost functions used in this study, the Very Fast Simulated Reannealing algorithm achieved results within 5-10% of the final solution (100,000 iterations) after 1000 iterations and within 3-5% of the final solution after 5000-10000 iterations. These solutions were superior to those produced by a conventional treatment plan based on an analysis of the resulting dose-volume histograms. However, this technique is a stochastic method and results vary in a statistical manner. Successive solutions may differ by up to 10%. CONCLUSION: Very Fast Simulated Reannealing, with modifications, is suitable for radiation therapy treatment planning optimization. It produced results within 3-10% of the optimal solution, produced using another optimization algorithm (Mixed Integer Programming), in clinically useful execution times.

Tissue heterogeneity effects in treatment plan optimization.

PURPOSE: There is general agreement that tissue density correction factors improve the accuracy of dose calculations. However, there is disagreement over the proper heterogeneity correction algorithm and a lack of clinical experience in using them. Therefore, there has not been widespread implementation of density correction factors into clinical practice. Furthermore, the introduction of optimized conformal therapy leads to new and radically different treatment techniques outside the clinical experience of the physician. It is essential that the effects of tissue density corrections are understood so that these types of treatments can be safely delivered. METHODS AND MATERIALS: In this paper, we investigate the effect of tissue density corrections on optimized conformal type treatment planning in the thorax region. Specifically, we study the effects on treatment plans optimized without type treatment planning in the thorax region. Specifically, we study the effects on treatment plans optimized without tissue density corrections, when those corrections are applied to the resulting dose distributions. These effects are compared for two different conformal techniques. RESULTS: This study indicates that failure to include tissue density correction factors results in an increased dose of approximately 5-15%. This is consistent with published studies using conventional treatment techniques. Additionally, the high-dose region of the dose distribution expands laterally into the uninvolved lung and other normal structures. The use of dose-volume histograms to compare these distributions demonstrates that treatment plans optimized without tissue density corrections lead to an increased dose to uninvolved normal structures. This increase in dose often violates the constraints used to determine the optimal solution. CONCLUSIONS: The neglect of tissue density correction factors can result in a 5-15% increase in the delivered dose. In addition, suboptimal dose distributions are produced. To benefit from the advantages of optimized conformal therapy in the thorax, tissue density correction factors should be used.

Assessment of a linear accelerator for segmented conformal radiation therapy.

Segmented conformal radiation therapy is a new computer-controlled treatment technique under investigation in which the target volume is subdivided into thick transverse segments each of which is then treated individually by rectangular transverse abutting fields. In order to obtain uniform dose at abutments, the machine isocenter remains fixed in the patient and field edges are defined by independently moving focused collimator jaws to give matching geometric divergence. Mechanical variation in jaw and gantry positioning will create some dose variation at field abutments. Film dosimetry was used to study the radiation field positioning accuracy and precision of a commercial linear accelerator. A method of field position calibration was developed using multiple nonabutting fields exposed on the same radiograph. Verification of collimator jaw calibration measurements was performed using multiple abutting fields exposed on a single radiograph. Measurements taken over 5 months of clinical accelerator operation studied the effects of simple jaw motion, simple gantry motion, and combined jaw/gantry motion on jaw position precision and accuracy. The inherent precision and accuracy of radiation field positioning was found to be better than +/- 0.3 mm for both jaws with all types of motions except for the Y2 jaw under combined jaw/gantry motion. When the ability to deliver abutting beams was verified in clinical mode, the average dose variation at abutments was less than 6% at all gantry angles except for one. However, due to accelerator software limitations in clinical mode, the settings for collimator positions could not take advantage of the maximum accuracy of which the hardware is capable.(ABSTRACT TRUNCATED AT 250 WORDS)

Optimized dynamic rotation with wedges.

Dynamic rotation is a computer-controlled therapy technique utilizing an automated multileaf collimator in which the radiation beam shape changes dynamically as the treatment machine rotates about the patient so that at each instant the beam shape matches the projected shape of the target volume. In simple dynamic rotation, the dose rate remains constant during rotation. For optimized dynamic rotation, the dose rate is varied as a function of gantry angle. Optimum dose rate at each gantry angle is computed by linear programming. Wedges can be included in the optimized dynamic rotation therapy by using additional rotations. Simple and optimized dynamic rotation treatment plans, with and without wedges, for a pancreatic tumor have been compared using optimization cost function values, normal tissue complication probabilities, and positive difference statistic values. For planning purposes, a continuous rotation is approximated by static beams at a number of gantry angles equally spaced about the patient. In theory, the quality of optimized treatment planning solutions should improve as the number of static beams increases. The addition of wedges should further improve dose distributions. For the case studied, no significant improvements were seen for more than 36 beam angles. Open and wedged optimized dynamic rotations were better than simple dynamic rotation, but wedged optimized dynamic rotation showed no definitive improvement over open beam optimized dynamic rotation.

Custom beam profiles in computer-controlled radiation therapy.

A computer-controlled radiation therapy technique is demonstrated which uses multiple concurrent boost fields to modify the beam profile of a conventional treatment beam. A principal field, identical to that of a corresponding conventional treatment plan, delivers the major component of the prescribed dose. Dose increments given from boost fields placed within this principal field compensate for variations in patient anatomy, for variations in target volume shape, and/or for imperfect beam characteristics, such as excessive off-axis dose or inadequate beam wedge angle. This concurrent boost field technique is demonstrated for several treatment sites. It produces significant improvement in uniformity of dose delivered to the target compared to conventional treatment. Implementation of these treatments requires a computer-controlled linear accelerator with independently-movable collimator jaws, an automatic beam set-up procedure, and a patient prescription database. Since all fields are delivered under computer control, concurrent boost technique treatment times are not much longer than those of conventional treatments.

Dose-volume considerations with linear programming optimization.

A method of incorporating dose-volume considerations within the framework of conventional linear programming is presented. This method is suitable for the optimization of beam weights and angles using a conformal treatment philosophy (i.e., tailoring the high-dose region to the target volume only). Dose-volume constraints are introduced using the concept that volumes of normal tissue nearer the target volume will be allowed higher dose constraints than volumes of normal tissue distal to the target volume. Each involved normal structure is divided into high-dose and low-dose volumes. These two volume partitions are represented by constraint points with either high-dose or low-dose constraints, respectively. Optimized treatment plans for three clinical sites demonstrate that this technique meets or surpasses the original dose-volume constraints for a conformal-type treatment plan using straightforward linear programming in a time frame that is comparable to other linear programming problems.

Treatment planning optimization using constrained simulated annealing.

A variation of simulated annealing optimization called 'constrained simulated annealing' is used with a simple annealing schedule to optimize beam weights and angles in radiation therapy treatment planning. Constrained simulated annealing is demonstrated using two contrasting objective functions which incorporate both biological response and dose-volume considerations. The first objective function maximizes the probability of a complication-free treatment (PCFT) by minimizing the normal tissue complications subject to the constraint that the entire target volume receives a prescribed minimum turmourcidal dose with a specified dose homogeneity. Probabilities of normal tissue complication are based on published normal tissue complication probability functions and computed from dose-volume histograms. The second objective function maximizes the isocentre dose subject to a set of customized normal tissue dose-volume and target volume dose homogeneity constraints (MVDL). Although the PCFT objective function gives consistently lower estimates of normal tissue complication probabilities, the ability to specify individualized dose-volume limits, and therefore the individualized probability of complication, for an individual organ makes the MDVL objective function more useful for treatment planning.