Evaluation of concave dose distributions created using an inverse planning system

A novel knowledge-based prediction model for estimating an initial equivalent uniform dose in semi-auto-planning for cervical cancer

Background

We developed a novel concept, equivalent uniform length (EUL), to describe the relationship between the generalized equivalent uniform dose (EUD) and the geometric anatomy around a tumor target. By correlating EUL with EUD, we established two EUD–EUL knowledge-based (EEKB) prediction models for the bladder and rectum that predict initial EUD values for generating quality treatment plans.

Methods

EUL metrics for the rectum and bladder were extracted and collected from the intensity-modulated radiotherapy therapy (IMRT) plans of 60 patients with cervical cancer. The two EEKB prediction models were built using linear regression to establish the relationships between EUL_r and EUD_r (EUL and EUD of rectum) and EUL_b, and EUD_b (EUL and EUD of bladder), respectively. The EE plans were optimized by incorporating the predicted initial EUD parameters for the rectum and bladder with the conventional pinnacle auto-planning (PAP) initial dose parameters for other organs. The efficiency of the predicted initial EUD values were then evaluated by comparing the consistency and quality of the EE plans, PAP plans (based on default PAP initial parameters), and manual plans (designed manually by different dosimetrists) for a sample of 20 patients.

Results

Linear regression analyses showed a significant correlation between EUL and EUD (R² = 0.79 and 0.69 for EUD_b and EUD_r, respectively). In a sample of 20 patients, the average bladder V40 and V50 derived from the EE plans were significantly lower (V40: 30.00 ± 5.76, V50: 14.36 ± 4.00) than the V40 and V50 values derived from manual plans (V40: 36.03 ± 8.02, V50: 19.02 ± 5.42). Compared with the PAP plans, the EE plans produced significantly lower average V30 and Dmean values for the bladder (V30: 50.55 ± 6.33, Dmean: 31.48 ± 1.97 Gy).

Conclusions

Our EEKB prediction models predicted reasonable initial EUD values for the rectum and bladder based on patient-specific geometric EUL values, thereby improving optimization and planning efficiency.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13014-022-02120-4.

Projections onto the Pareto surface in multicriteria radiation therapy optimization

PURPOSE

To eliminate or reduce the error to Pareto optimality that arises in Pareto surface navigation when the Pareto surface is approximated by a small number of plans.

METHODS

The authors propose to project the navigated plan onto the Pareto surface as a postprocessing step to the navigation. The projection attempts to find a Pareto optimal plan that is at least as good as or better than the initial navigated plan with respect to all objective functions. An augmented form of projection is also suggested where dose-volume histogram constraints are used to prevent that the projection causes a violation of some clinical goal. The projections were evaluated with respect to planning for intensity modulated radiation therapy delivered by step-and-shoot and sliding window and spot-scanned intensity modulated proton therapy. Retrospective plans were generated for a prostate and a head and neck case.

RESULTS

The projections led to improved dose conformity and better sparing of organs at risk (OARs) for all three delivery techniques and both patient cases. The mean dose to OARs decreased by 3.1 Gy on average for the unconstrained form of the projection and by 2.0 Gy on average when dose-volume histogram constraints were used. No consistent improvements in target homogeneity were observed.

CONCLUSIONS

There are situations when Pareto navigation leaves room for improvement in OAR sparing and dose conformity, for example, if the approximation of the Pareto surface is coarse or the problem formulation has too permissive constraints. A projection onto the Pareto surface can identify an inaccurate Pareto surface representation and, if necessary, improve the quality of the navigated plan.

Atlas-guided prostate intensity modulated radiation therapy (IMRT) planning

An atlas-based IMRT planning technique for prostate cancer was developed and evaluated. A multi-dose atlas was built based on the anatomy patterns of the patients, more specifically, the percent distance to the prostate and the concaveness angle formed by the seminal vesicles relative to the anterior-posterior axis. A 70-case dataset was classified using a k-medoids clustering analysis to recognize anatomy pattern variations in the dataset. The best classification, defined by the number of classes or medoids, was determined by the largest value of the average silhouette width. Reference plans from each class formed a multi-dose atlas. The atlas-guided planning (AGP) technique started with matching the new case anatomy pattern to one of the reference cases in the atlas; then a deformable registration between the atlas and new case anatomies transferred the dose from the atlas to the new case to guide inverse planning with full automation. 20 additional clinical cases were re-planned to evaluate the AGP technique. Dosimetric properties between AGP and clinical plans were evaluated. The classification analysis determined that the 5-case atlas would best represent anatomy patterns for the patient cohort. AGP took approximately 1 min on average (corresponding to 70 iterations of optimization) for all cases. When dosimetric parameters were compared, the differences between AGP and clinical plans were less than 3.5%, albeit some statistical significances observed: homogeneity index (p  >  0.05), conformity index (p  <  0.01), bladder gEUD (p  <  0.01), and rectum gEUD (p  =  0.02). Atlas-guided treatment planning is feasible and efficient. Atlas predicted dose can effectively guide the optimizer to achieve plan quality comparable to that of clinical plans.

Volumetric-modulated arc therapy planning using multicriteria optimization for localized prostate cancer

The purpose of this work is to evaluate the volumetric‐modulated arc therapy (VMAT) multicriteria optimization (MCO) algorithm clinically available in the RayStation treatment planning system (TPS) and its ability to reduce treatment planning time while providing high dosimetric plan quality. Nine patients with localized prostate cancer who were previously treated with 78 Gy in 39 fractions using VMAT plans and rayArc system based on the direct machine parameter optimization (DMPO) algorithm were selected and replanned using the VMAT‐MCO system. First, the dosimetric quality of the plans was evaluated using multiple conformity metrics that account for target coverage and sparing of healthy tissue, used in our departmental clinical protocols. The conformity and homogeneity index, number of monitor units, and treatment planning time for both modalities were assessed. Next, the effects of the technical plan parameters, such as constraint leaf motion CLM (cm/°) and maximum arc delivery time T (s), on the accuracy of delivered dose were evaluated using quality assurance passing rates (QAs) measured using the Delta⁴ phantom from ScandiDos. For the dosimetric plan's quality analysis, the results show that the VMAT‐MCO system provides plans comparable to the rayArc system with no statistical difference for V95% (p<0.01), D1% (p<0.01), CI (p<0.01), and HI (p<0.01) of the PTV, bladder (p<0.01), and rectum (p<0.01) constraints, except for the femoral heads and healthy tissues, for which a dose reduction was observed using MCO compared with rayArc (p<0.01). The technical parameter study showed that a combination of CLM equal to 0.5 cm/degree and a maximum delivery time of 72 s allowed the accurate delivery of the VMAT‐MCO plan on the Elekta Versa HD linear accelerator. Planning evaluation and dosimetric measurements showed that VMAT‐MCO can be used clinically with the advantage of enhanced planning process efficiency by reducing the treatment planning time without impairing dosimetric quality.

PACS numbers: 87.55.D, 87.55.de, 87.55.Qr

Incorporating single-side sparing in models for predicting parotid dose sparing in head and neck IMRT

PURPOSE

Sparing of single-side parotid gland is a common practice in head-and-neck (HN) intensity modulated radiation therapy (IMRT) planning. It is a special case of dose sparing tradeoff between different organs-at-risk. The authors describe an improved mathematical model for predicting achievable dose sparing in parotid glands in HN IMRT planning that incorporates single-side sparing considerations based on patient anatomy and learning from prior plan data.

METHODS

Among 68 HN cases analyzed retrospectively, 35 cases had physician prescribed single-side parotid sparing preferences. The single-side sparing model was trained with cases which had single-side sparing preferences, while the standard model was trained with the remainder of cases. A receiver operating characteristics (ROC) analysis was performed to determine the best criterion that separates the two case groups using the physician's single-side sparing prescription as ground truth. The final predictive model (combined model) takes into account the single-side sparing by switching between the standard and single-side sparing models according to the single-side sparing criterion. The models were tested with 20 additional cases. The significance of the improvement of prediction accuracy by the combined model over the standard model was evaluated using the Wilcoxon rank-sum test.

RESULTS

Using the ROC analysis, the best single-side sparing criterion is (1) the predicted median dose of one parotid is higher than 24 Gy; and (2) that of the other is higher than 7 Gy. This criterion gives a true positive rate of 0.82 and a false positive rate of 0.19, respectively. For the bilateral sparing cases, the combined and the standard models performed equally well, with the median of the prediction errors for parotid median dose being 0.34 Gy by both models (p = 0.81). For the single-side sparing cases, the standard model overestimates the median dose by 7.8 Gy on average, while the predictions by the combined model differ from actual values by only 2.2 Gy (p = 0.005). Similarly, the sum of residues between the modeled and the actual plan DVHs is the same for the bilateral sparing cases by both models (p = 0.67), while the standard model predicts significantly higher DVHs than the combined model for the single-side sparing cases (p = 0.01).

CONCLUSIONS

The combined model for predicting parotid sparing that takes into account single-side sparing improves the prediction accuracy over the previous model.

Apparatus-dependent dosimetric differences in spine stereotactic body radiotherapy

The purpose of this investigation was to study apparatus-dependent dose distribution differences specific to spine stereotactic body radiotherapy (SBRT) treatment planning. This multi-institutional study was performed evaluating an image-guided robotic radiosurgery system (CK), intensity modulated protons (IMP), multileaf collimator (MLC) fixed-field IMRT with 5 mm (11 field), 4 mm (9 field), and 2.5 mm (8- and 9-field) leaf widths and intensity modulated volumetric arc therapy (IMVAT) with a 2.5 mm MLC. Treatment plans were systematically developed for targets consisting of one, two and three consecutive thoracic vertebral bodies (VBs) with the esophagus and spinal cord contoured as the organs at risk. It was found that all modalities achieved acceptable treatment planning constraints. However, following normalization fixed field IMRT with a 2.5 mm MLC, IMVAT and IMP systems yielded the smallest ratio of maximum dose divided by the prescription dose (MD/PD) for one-, two- and three-VB PTVs (ranging from 1.1-1.16). The 2.5 mm MLC 9-field IMRT, IMVAT and CK plans resulted in the least dose to 0.1 cc volumes of spinal cord and esophagus. CK plans had the greatest degree of target dose inhomogeneity. As the level of complexity increased with an increasing number of vertebral bodies, distinct apparatus features such as the use of a high number of beams and a finer leaf size MLC were favored. Our study quantified apparatus-dependent dose-distribution differences specific to spine SBRT given strict, but realistic, constraints and highlights the need to benchmark physical dose distributions for multi-institutional clinical trials.

Improved planning time and plan quality through multicriteria optimization for intensity-modulated radiotherapy

PURPOSE

To test whether multicriteria optimization (MCO) can reduce treatment planning time and improve plan quality in intensity-modulated radiotherapy (IMRT).

METHODS AND MATERIALS

Ten IMRT patients (5 with glioblastoma and 5 with locally advanced pancreatic cancers) were logged during the standard treatment planning procedure currently in use at Massachusetts General Hospital (MGH). Planning durations and other relevant planning information were recorded. In parallel, the patients were planned using an MCO planning system, and similar planning time data were collected. The patients were treated with the standard plan, but each MCO plan was also approved by the physicians. Plans were then blindly reviewed 3 weeks after planning by the treating physician.

RESULTS

In all cases, the treatment planning time was vastly shorter for the MCO planning (average MCO treatment planning time was 12 min; average standard planning time was 135 min). The physician involvement time in the planning process increased from an average of 4.8 min for the standard process to 8.6 min for the MCO process. In all cases, the MCO plan was blindly identified as the superior plan.

CONCLUSIONS

This provides the first concrete evidence that MCO-based planning is superior in terms of both planning efficiency and dose distribution quality compared with the current trial and error-based IMRT planning approach.

A practical approach to assess clinical planning tradeoffs in the design of individualized IMRT treatment plans

BACKGROUND AND PURPOSE

To investigate the tradeoffs between organ at risk sparing and tumour coverage for IMRT treatment of lung tumours, and to develop a tool for clinical use to graphically represent these tradeoffs.

MATERIAL AND METHODS

For 5 patients with inoperable non-small cell lung cancer (NSCLC) different IMRT plans were generated using a standard TPS. The plans were automatically generated for a range of IMRT settings (weights and dose levels of the objective functions) and were systematically evaluated, focusing on the tradeoffs between organ at risk (OAR) dose and target coverage. A method to analyze and visualize planning tradeoffs was developed and evaluated.

RESULTS

Lung and oesophagus were identified as the critical organs at risk for NSCLC, the sparing of which strongly influences PTV coverage. Systematically analyzing the tradeoffs between these organs revealed that the sparing of these organs was approximately linearly related to PTV coverage parameters. Using this property, a tool was developed to graphically present the tradeoffs between the sparing of these organs at risk and the PTV coverage. The tool is an effective method to visualize the tradeoffs.

CONCLUSIONS

A tool was developed to assist IMRT plan design and selection. The clear presentation of the tradeoffs between OAR dose and coverage facilitates the optimization process and offers additional information to the clinician for a patient specific choice of the optimal IMRT plan.

The feasibility of using Pareto fronts for comparison of treatment planning systems and delivery techniques

Pareto optimality is a concept that formalises the trade-off between a given set of mutually contradicting objectives. A solution is said to be Pareto optimal when it is not possible to improve one objective without deteriorating at least one of the other. A set of Pareto optimal solutions constitute the Pareto front. The Pareto concept applies well to the inverse planning process, which involves inherently contradictory objectives, high and uniform target dose on one hand, and sparing of surrounding tissue and nearby organs at risk (OAR) on the other. Due to the specific characteristics of a treatment planning system (TPS), treatment strategy or delivery technique, Pareto fronts for a given case are likely to differ. The aim of this study was to investigate the feasibility of using Pareto fronts as a comparative tool for TPSs, treatment strategies and delivery techniques. In order to sample Pareto fronts, multiple treatment plans with varying target conformity and dose sparing of OAR were created for a number of prostate and head & neck IMRT cases. The DVHs of each plan were evaluated with respect to target coverage and dose to relevant OAR. Pareto fronts were successfully created for all studied cases. The results did indeed follow the definition of the Pareto concept, i.e. dose sparing of the OAR could not be improved without target coverage being impaired or vice versa. Furthermore, various treatment techniques resulted in distinguished and well separated Pareto fronts. Pareto fronts may be used to evaluate a number of parameters within radiotherapy. Examples are TPS optimization algorithms, the variation between accelerators or delivery techniques and the degradation of a plan during the treatment planning process. The issue of designing a model for unbiased comparison of parameters with such large inherent discrepancies, e.g. different TPSs, is problematic and should be carefully considered.

On the role of modeling parameters in IMRT plan optimization

The formulation of optimization problems in intensity-modulated radiotherapy (IMRT) planning comprises the choice of various values such as function-specific parameters or constraint bounds. In current inverse planning programs that yield a single treatment plan for each optimization, it is often unclear how strongly these modeling parameters affect the resulting plan. This work investigates the mathematical concepts of elasticity and sensitivity to deal with this problem. An artificial planning case with a horse-shoe formed target with different opening angles surrounding a circular risk structure is studied. As evaluation functions the generalized equivalent uniform dose (EUD) and the average underdosage below and average overdosage beyond certain dose thresholds are used. A single IMRT plan is calculated for an exemplary parameter configuration. The elasticity and sensitivity of each parameter are then calculated without re-optimization, and the results are numerically verified. The results show the following. (1) elasticity can quantify the influence of a modeling parameter on the optimization result in terms of how strongly the objective function value varies under modifications of the parameter value. It also can describe how strongly the geometry of the involved planning structures affects the optimization result. (2) Based on the current parameter settings and corresponding treatment plan, sensitivity analysis can predict the optimization result for modified parameter values without re-optimization, and it can estimate the value intervals in which such predictions are valid. In conclusion, elasticity and sensitivity can provide helpful tools in inverse IMRT planning to identify the most critical parameters of an individual planning problem and to modify their values in an appropriate way.

Dosimetric effect of translational and rotational errors for patients undergoing image-guided stereotactic body radiotherapy for spinal metastases

PURPOSE

To investigate the dosimetric effects of translational and rotational patient positioning errors on the treatment of spinal and paraspinal metastases using computed tomography image-guided stereotactic body radiotherapy. The results of this study provide guidance for the treatment planning process and recognition of the dosimetric consequences of daily patient treatment setup errors.

METHODS AND MATERIALS

The data from 20 patients treated for metastatic spinal cancer using image-guided stereotactic body radiotherapy were investigated in this study. To simulate the dosimetric effects of residual setup uncertainties, 36 additional plans (total, 756 plans) were generated for each isocenter (total, 21 isocenters) on the planning computed tomography images, which included isocenter lateral, anteroposterior, superoinferior shifts, and patient roll, yaw, and pitch rotations. Tumor volume coverage and the maximal dose to the organs at risk were compared with those of the original plan. Six daily treatments were also investigated to determine the dosimetric effect with or without the translational and rotational corrections.

RESULTS

A 2-mm error in translational patient positioning error in any direction can result in >5% tumor coverage loss and >25% maximal dose increase to the organs at risk. Rotational correction is very important for patients with multiple targets and for the setup of paraspinal patients when the isocenter is away from bony structures. Compared with the original plans, the daily treatment data indicated that translational adjustments could correct most of the setup errors to mean divergences of -1.4% for tumor volume coverage and -0.3% for the maximal dose to the organs at risk.

CONCLUSION

For the best dosimetric results, spinal stereotactic treatments should have setup translational errors of < or =1 mm and rotational errors of < or =2 degrees .

Intensity-modulated radiation therapy for head and neck carcinoma

Intensity-modulated radiation therapy (IMRT) for head and neck tumors refers to a new approach that aims at increasing the radiation dose gradient between the target tissues and the surrounding normal tissues at risk, thus offering the prospect of increasing the locoregional control probability while decreasing the complication rate. As a prerequisite, IMRT requires a proper selection and delineation of target volumes. For the latter, recent data indicate the potential of functional imaging to complement anatomic imaging modalities. Nonrandomized clinical series in paranasal sinuses and pharyngolaryngeal carcinoma have shown that IMRT was able to achieve a very high rate of locoregional control with less morbidity, such as dry-eye syndrome, xerostomia, and swallowing dysfunction. The promising results of IMRT are likely to be achieved when many treatment conditions are met, for example, optimal selection and delineation of the target volumes and organs at risk, appropriate physical quality control of the irradiation, and accurate patient setup with the use of onboard imaging. Because of the complexity of the various tasks, it is thus likely that these conditions will only be met in institutions having large patient throughput and experience with IMRT. Therefore, patient referral to those institutions is recommended.

A new concept for interactive radiotherapy planning with multicriteria optimization: first clinical evaluation

BACKGROUND AND PURPOSE

Currently, inverse planning for intensity-modulated radiotherapy (IMRT) can be a time-consuming trial and error process. This is because many planning objectives are inherently contradictory and cannot reach their individual optimum all at the same time. Therefore in clinical practice the potential of IMRT cannot be fully exploited for all patients. Multicriteria (multiobjective) optimization combined with interactive plan navigation is a promising approach to overcome these problems.

PATIENTS AND METHODS

We developed a new inverse planning system called "Multicriteria Interactive Radiotherapy Assistant (MIRA)". The optimization result is a database of patient specific, Pareto-optimal plan proposals. The database is explored with an intuitive user interface that utilizes both a new interactive element for plan navigation and familiar dose visualizations in form of DVH and isodose projections. Two clinical test cases, one paraspinal meningioma case and one prostate case, were optimized using MIRA and compared with the clinically approved planning program KonRad.

RESULTS

Generating the databases required no user interaction and took approx. 2-3h per case. The interactive exploration required only a few minutes until the best plan was identified, resulting in a significant reduction of human planning time. The achievable plan quality was comparable to KonRad with the additional benefit of having plan alternatives at hand to perform a sensitivity analysis or to decide for a different clinical compromise.

CONCLUSIONS

The MIRA system provides a complete database and interactive exploration of the solution space in real time. Hence, it is ideally suited for the inherently multicriterial problem of inverse IMRT treatment planning.

Intensity-modulated radiation therapy in head and neck cancers: an update

Intensity-modulated radiation therapy (IMRT), an advent of three-dimensional conformal radiotherapy (3D CRT), has excited the profession of radiation oncology more than any other new invention since the introduction of the linear accelerator. Approximately 1000 articles have been published on this topic to date, more than 200 of which focus on head and neck cancer. IMRT is based on computer-optimized treatment planning and a computer-controlled treatment delivery system. The computer-driven technology generates dose distributions that sharply conform to the tumor target while minimizing the dose delivered to the surrounding normal tissues. The high dose volume that tailors to the 3D configuration of the tumor along with the ability to spare the nearby normal tissues allows the option of tumor dose escalation. The head and neck region is an ideal target for this new technology for several reasons. First, IMRT offers the potential for improved tumor control through delivery of high doses to the target volume. Second, because of sharp dose gradients, IMRT results in the relative sparing of normal structures, such as the parotid glands, in the head and neck region. Third, organ motion is virtually absent in the head and neck region so, with proper immobilization, treatment can be accurately delivered. Although this is a relatively new technology, single-institution retrospective studies show better dosimetric profiles compared with conventional radiation techniques, as well as excellent clinical results. Salivary gland sparing using IMRT has also resulted in reduced incidence and severity of xerostomia, and this has been tested in a randomized trial against conventional radiotherapy for early-stage nasopharyngeal cancer. The results do confirm that IMRT does decrease xerostomia compared with conventional radiotherapy.

Reduced-order parameter optimization for simplifying prostate IMRT planning

Intensity-modulated radiotherapy (IMRT) has become an effective tool for cancer treatment with radiation. However, even expert radiation planners still need to spend a substantial amount of time manually adjusting IMRT optimization parameters such as dose limits and costlet weights in order to obtain a clinically acceptable plan. In this paper, we describe two main advances that simplify the parameter adjustment process for five-field prostate IMRT planning. First, we report the results of a sensitivity analysis that quantifies the effect of each hand-tunable parameter of the IMRT cost function on each clinical objective and the overall quality of the resulting plan. Second, we show that a recursive random search over the six most sensitive parameters as an outer loop in IMRT planning can quickly and automatically determine parameters for the cost function that lead to a plan meeting the clinical requirements. Our experiments on a ten-patient dataset show that for 70% of the cases, we can automatically determine a plan in 10 min (on the average) that is either clinically acceptable or requires only minor adjustment by the planner. The outer-loop optimization can be easily integrated into a traditional IMRT planning system.

Derivative-free generation and interpolation of convex Pareto optimal IMRT plans

In inverse treatment planning for intensity-modulated radiation therapy (IMRT), beamlet intensity levels in fluence maps of high-energy photon beams are optimized. Treatment plan evaluation criteria are used as objective functions to steer the optimization process. Fluence map optimization can be considered a multi-objective optimization problem, for which a set of Pareto optimal solutions exists: the Pareto efficient frontier (PEF). In this paper, a constrained optimization method is pursued to iteratively estimate the PEF up to some predefined error. We use the property that the PEF is convex for a convex optimization problem to construct piecewise-linear upper and lower bounds to approximate the PEF from a small initial set of Pareto optimal plans. A derivative-free Sandwich algorithm is presented in which these bounds are used with three strategies to determine the location of the next Pareto optimal solution such that the uncertainty in the estimated PEF is maximally reduced. We show that an intelligent initial solution for a new Pareto optimal plan can be obtained by interpolation of fluence maps from neighbouring Pareto optimal plans. The method has been applied to a simplified clinical test case using two convex objective functions to map the trade-off between tumour dose heterogeneity and critical organ sparing. All three strategies produce representative estimates of the PEF. The new algorithm is particularly suitable for dynamic generation of Pareto optimal plans in interactive treatment planning.

Approximating convex pareto surfaces in multiobjective radiotherapy planning

Radiotherapy planning involves inherent tradeoffs: the primary mission, to treat the tumor with a high, uniform dose, is in conflict with normal tissue sparing. We seek to understand these tradeoffs on a case-to-case basis, by computing for each patient a database of Pareto optimal plans. A treatment plan is Pareto optimal if there does not exist another plan which is better in every measurable dimension. The set of all such plans is called the Pareto optimal surface. This article presents an algorithm for computing well distributed points on the (convex) Pareto optimal surface of a multiobjective programming problem. The algorithm is applied to intensity-modulated radiation therapy inverse planning problems, and results of a prostate case and a skull base case are presented, in three and four dimensions, investigating tradeoffs between tumor coverage and critical organ sparing.

Learning the relationship between patient geometry and beam intensity in breast intensity-modulated radiotherapy

Intensity modulated radiotherapy (IMRT) has become an effective tool for cancer treatment with radiation. However, even expert radiation planners still need to spend a substantial amount of time adjusting IMRT optimization parameters in order to get a clinically acceptable plan. We demonstrate that the relationship between patient geometry and radiation intensity distributions can be automatically inferred using a variety of machine learning techniques in the case of two-field breast IMRT. Our experiments show that given a small number of human-expert-generated clinically acceptable plans, the machine learning predictions produce equally acceptable plans in a matter of seconds. The machine learning approach has the potential for greater benefits in sites where the IMRT planning process is more challenging or tedious.

Exploration of tradeoffs in intensity-modulated radiotherapy

The purpose of this study is to calculate Pareto surfaces in multi-criteria radiation treatment planning and to analyse the dependency of the Pareto surfaces on the objective functions used for the volumes of interest. We develop a linear approach that allows us to calculate truly Pareto optimal treatment plans, and we apply it to explore the tradeoff between tumour dose homogeneity and critical structure sparing. We show that for two phantom and two clinical cases, a smooth (as opposed to kinked) Pareto tradeoff curve exists. We find that in the paraspinal cases the Pareto surface is invariant to the response function used on the spinal cord: whether the mean cord dose or the maximum cord dose is used, the Pareto plan database is similar. This is not true for the lung studies, where the choice of objective function on the healthy lung tissue influences the resulting Pareto surface greatly. We conclude that in the special case when the tumour wraps around the organ at risk, e.g. prostate cases and paraspinal cases, the Pareto surface will be largely invariant to the objective function used to model the organ at risk.

Evaluation of image-guided helical tomotherapy for the retreatment of spinal metastasis

INTRODUCTION

Patients with vertebral metastasis that receive radiation therapy are typically treated to the spinal cord tolerance dose. As such, it is difficult to successfully deliver a second course of radiation therapy for patients with overlapping treatment volumes. In this study, an image-guided helical tomotherapy system was evaluated for the retreatment of previously irradiated vertebral metastasis.

METHODS AND MATERIALS

Helical tomotherapy dose gradients and maximum cord doses were measured in a cylindrical phantom for geometric test cases with separations between the planning target volume (PTV) and the spinal cord organ at risk (OAR) of 2 mm, 4 mm, 6 mm, 8 mm, and 10 mm. Megavoltage computed tomography (CT) images were examined for their ability to localize spinal anatomy for positioning purposes by repeat imaging of the cervical spine in an anthropomorphic phantom. In addition to the phantom studies, 8 patients with cord compressions that had received previous radiation therapy were retreated to a mean dose of 28 Gy using conventional fractionation.

RESULTS AND DISCUSSION

Megavoltage CT images were capable of positioning an anthropomorphic phantom to within +/-1.2 mm (2sigma) superior-inferiorly and within +/-0.6 mm (2sigma) anterior-posteriorly and laterally. Dose gradients of 10% per mm were measured in phantom while PTV uniformity indices of less than 11% were maintained. The calculated maximum cord dose was 25% of the prescribed dose for a 10-mm PTV-to-OAR separation and 71% of the prescribed dose for a PTV-to-OAR separation of 2 mm. Eight patients total have been treated without radiation-induced myelopathy or any other adverse effects from treatment.

CONCLUSIONS

A technique has been evaluated for the retreatment of vertebral metastasis using image-guided helical tomotherapy. Phantom and patient studies indicated that a tomotherapy system is capable of delivering dose gradients of 10% per mm and positioning the patient within 1.2 mm without the use of special stereotactic immobilization.

An examination of the number of required apertures for step-and-shoot IMRT

We have examined the degree to which step-and-shoot IMRT treatment plans can be simplified (using a small number of apertures) without sacrificing the dosimetric quality of the plans. A key element of this study was the use of direct aperture optimization (DAO), an inverse planning technique where all of the multi-leaf collimator constraints are incorporated into the optimization. For seven cases (1 phantom, 1 prostate, 3 head-and-neck and 2 lung), DAO was used to perform a series of optimizations where the number of apertures per beam direction varied from 1 to 15. In this work, we attempt to provide general guidelines for how many apertures per beam direction are sufficient for various clinical cases using DAO. Analysis of the optimized treatment plans reveals that for most cases, only modest improvements in the objective function and the corresponding DVHs are seen beyond 5 apertures per beam direction. However, for more complex cases, some dosimetric gain can be achieved by increasing the number of apertures per beam direction beyond 5. Even in these cases, however, only modest improvements are observed beyond 9 apertures per beam direction. In our clinical experience, 38 out of the first 40 patients treated using IMRT plans produced using DAO were treated with 9 or fewer apertures per beam direction. The results indicate that many step-and-shoot IMRT treatment plans delivered today are more complex than necessary and can be simplified without sacrificing plan quality.

Intensity-modulated radiotherapy as the boost or salvage treatment of nasopharyngeal carcinoma: The appropriate parameters in the inverse planning and the effect of patient's anatomic factors on the planning results

The current study demonstrates that the large increase in normal tissue penalty often degrades target dose uniformity without a concomitant large improvement in normal tissue dose, especially in anatomically unfavorable patients. The excessively large normal tissue penalties do not improve treatment plans for patients having unfavorable geometry.

IMRT planning on adaptive volume structures—a decisive reduction in computational complexity

The objective of radiotherapy planning is to find a compromise between the contradictive goals of delivering a sufficiently high dose to the target volume while widely sparing critical structures. The search for such a compromise requires the computation of several plans, which mathematically means solving several optimization problems. In the case of intensity modulated radiotherapy (IMRT) these problems are large-scale, hence the accumulated computational expense is very high. The adaptive clustering method presented in this paper overcomes this difficulty. The main idea is to use a preprocessed hierarchy of aggregated dose-volume information as a basis for individually adapted approximations of the original optimization problems. This leads to a decisively reduced computational expense: numerical experiments on several sets of real clinical data typically show computation times decreased by a factor of about 10. In contrast to earlier work in this field, this reduction in computational complexity will not lead to a loss in accuracy: the adaptive clustering method produces the optimum of the original optimization problem.

Choix des contraintes et amélioration dosimétrique d’une radiothérapie conformationnelle du cancer de la prostate modulée en intensité pendant une partie du traitement

PURPOSE

Intensity modulated radiation therapy (IMRT) is based on a methodology called inverse planning. Starting from dosimetric objectives, constraints of optimization are fixed and given to the inverse planning system, which in turn calculates the modulated intensity to apply to each beam. Since the algorithms allow the constraints to be violated, the results of optimization may differ from the initial dosimetric objectives. Consequently, the user is compelled to adapt the choice of the constraints according to the type of modulation and until satisfactory results are found. The purpose of this work is to present our experience in the choice of these constraints for prostate cancer treatments, as we moved from conformal radiotherapy to IMRT. Treatments were performed with a Varian 23EX linac and calculations were realized with the Varian CadPlan-Helios planning system.

PATIENTS AND METHODS

The approach used for the first 12 patients treated at institut Curie with IMRT from June 2002 was analysed. The treatment always consisted of a combination of conformal radiotherapy with and without intensity modulation.

RESULTS AND CONCLUSION

Results showed that, a larger fraction of the treatment performed with IMRT induced a better sparing of the organs at risk for the same homogeneous dose distribution to the target volume. Apart from the dose-volume constraint for the rectum, a fixed set of constraints, slightly more restrictive than the dosimetric objectives, could be used for all patients. Compared with conformal radiotherapy, the conformation factor for IMRT increased up to 16%. A specific study was undertaken in view of treatments completely performed with IMRT. The optimal technique consisted in performing separated IMRT plans for the two target volumes, the prostate volume and the prostate plus seminal vesicles volume respectively. Another satisfactory possibility was to define new constraints on two separated planning target volumes, prostate and seminal vesicles. This last approach is now routinely implemented for our IMRT patients.

The physical basis of IMRT and inverse planning

Intensity-modulated radiation therapy (IMRT) can sculpt the high-dose volume around the site of disease with hitherto unachievable precision. Conformal avoidance of normal tissues goes hand in hand with this. Inhomogeneous dose painting is possible. The technique has become a clinical reality and is likely to be the dominant approach this decade for improving the clinical practice of photon therapy. This Series will explore all aspects of the "IMRT chain". Only 15 years ago just a handful of physicists were working on this subject. IMRT has developed so rapidly that its recent past is also its ancient history. This article will review the history of IMRT with just a glance at precursors. The physical basis of IMRT is then described including an attempt to introduce the concepts of convex and concave dose distributions, ill-conditioning, inverse-problem degeneracy, cost functions and complex solutions all with a minimum of technical jargon or mathematics. The many techniques for inverse planning are described and the review concludes with a look forward to the future of image-guided IMRT (IG-IMRT).

Use of a quantitative index of beam modulation to characterize dose conformality: illustration by a comparison of full beamlet IMRT, few-segment IMRT (fsIMRT) and conformal unmodulated radiotherapy

A technique is presented for characterizing the degree of modulation in an intensity-modulated beam. It is shown that the modulation increases as dose conformality increases. Full intensity-modulated radiation therapy (IMRT) is compared with a two-weight-per-field technique and with simple geometrically conformal beams. It is suggested that each individual planning problem requires some comparative planning of this type because there is no simple answer to the question of the degree to which IMRT improves dose conformality. This depends on the problem geometry, the dose prescription, the cost function, the number of beams and other planning conditions. A methodology is presented for such comparative planning studies and this is illustrated with the solution of two planning problems.