Morphology-guided radiosurgery treatment planning and optimization for multiple isocenters

Automated isocenter optimization approach for treatment planning for gyroscopic radiosurgery

BACKGROUND

Radiosurgery is a well-established treatment for various intracranial tumors. In contrast to other established radiosurgery platforms, the new ZAP-X® allows for self-shielding gyroscopic radiosurgery. Here, treatment beams with variable beam-on times are targeted towards a small number of isocenters. The existing planning framework relies on a heuristic based on random selection or manual selection of isocenters, which often leads to a higher plan quality in clinical practice.

PURPOSE

The purpose of this work is to study an improved approach for radiosurgery treatment planning, which automatically selects the isocenter locations for the treatment of brain tumors and diseases in the head and neck area using the new system ZAP-X® .

METHODS

We propose a new method to automatically obtain the locations of the isocenters, which are essential in gyroscopic radiosurgery treatment planning. First, an optimal treatment plan is created based on a randomly selected nonisocentric candidate beam set. The intersections of the resulting subset of weighted beams are then clustered to find isocenters. This approach is compared to sphere-packing, random selection, and selection by an expert planner for generating isocenters. We retrospectively evaluate plan quality on 10 acoustic neuroma cases.

RESULTS

Isocenters acquired by the method of clustering result in clinically viable plans for all 10 test cases. When using the same number of isocenters, the clustering approach improves coverage on average by 31 percentage points compared to random selection, 15 percentage points compared to sphere packing and 2 percentage points compared to the coverage achieved with the expert selected isocenters. The automatic determination of location and number of isocenters leads, on average, to a coverage of 97 ± 3% with a conformity index of 1.22 ± 0.22, while using 2.46 ± 3.60 fewer isocenters than manually selected. In terms of algorithm performance, all plans were calculated in less than 2 min with an average runtime of 75 ± 25 s.

CONCLUSIONS

This study demonstrates the feasibility of an automatic isocenter selection by clustering in the treatment planning process with the ZAP-X® system. Even in complex cases where the existing approaches fail to produce feasible plans, the clustering method generates plans that are comparable to those produced by expert selected isocenters. Therefore, our approach can help reduce the effort and time required for treatment planning in gyroscopic radiosurgery.

The effect of tumor shape irregularity on Gamma Knife treatment plan quality and treatment outcome: an analysis of 234 vestibular schwannomas

The primary aim of Gamma Knife (GK) radiosurgery is to deliver high-dose radiation precisely to a target while conforming to the target shape. In this study, the effects of tumor shape irregularity (TSI) on GK dose-plan quality and treatment outcomes were analyzed in 234 vestibular schwannomas. TSI was quantified using seven different metrics including volumetric index of sphericity (VioS). GK treatment plans were created on a single GK-Perfexion/ICON platform. The plan quality was measured using selectivity index (SI), gradient index (GI), Paddick's conformity index (PCI), and efficiency index (EI). Correlation and linear regression analyses were conducted between shape irregularity features and dose plan indices. Machine learning was employed to identify the shape feature that predicted dose plan quality most effectively. The treatment outcome analysis including tumor growth control and serviceable hearing preservation at 2 years, were conducted using Cox regression analyses. All TSI features correlated significantly with the dose plan indices (P < 0.0012). With increasing tumor volume, vestibular schwannomas became more spherical (P < 0.05) and the dose plan indices varied significantly between tumor volume subgroups (P < 0.001 and P < 0.01). VioS was the most effective predictor of GK indices (P < 0.001) and we obtained 89.36% accuracy (79.17% sensitivity and 100% specificity) for predicting PCI. Our results indicated that TSI had significant effects on the plan quality however did not adversely affect treatment outcomes.

Knowledge-based isocenter selection in radiosurgery planning

PURPOSE

We present a new method for knowledge-based isocenter selection for treatment planning in radiosurgery. Our objective is to develop a prediction model that can learn from past manually designed treatment plans. We leverage recent advances in deep learning to predict isocenter locations in treatment plans in order to provide a decision support tool.

METHODS

The proposed method adapts a geometric approach using orthogonal moment expansions as a feature vector for describing the shape of the tumor. Our approach accounts primarily for tumor shape and OAR proximity, the two factors that are known to greatly affect the isocenter placement. We solve the prediction problem by training a residual neural network with skip connections on the formed shape descriptors. Our network was trained on 533 patient cases and was validated on a set of out-of-sample cases.

RESULTS

Our method generates heatmap predictions for isocenter locations that are in most cases comparable to the experienced human planners, which shows that the method can be used in treatment planning to guide the users for determining the isocenters.

CONCLUSIONS

Our numerical experiments indicate a positive predictive value on an independent validation set when compared against a test dataset that was not seen by the model during training.

A fully automatic approach for multimodal PET and MR image segmentation in gamma knife treatment planning

BACKGROUND AND OBJECTIVES

Nowadays, clinical practice in Gamma Knife treatments is generally based on MRI anatomical information alone. However, the joint use of MRI and PET images can be useful for considering both anatomical and metabolic information about the lesion to be treated. In this paper we present a co-segmentation method to integrate the segmented Biological Target Volume (BTV), using [¹¹C]-Methionine-PET (MET-PET) images, and the segmented Gross Target Volume (GTV), on the respective co-registered MR images. The resulting volume gives enhanced brain tumor information to be used in stereotactic neuro-radiosurgery treatment planning. GTV often does not match entirely with BTV, which provides metabolic information about brain lesions. For this reason, PET imaging is valuable and it could be used to provide complementary information useful for treatment planning. In this way, BTV can be used to modify GTV, enhancing Clinical Target Volume (CTV) delineation.

METHODS

A novel fully automatic multimodal PET/MRI segmentation method for Leksell Gamma Knife^® treatments is proposed. This approach improves and combines two computer-assisted and operator-independent single modality methods, previously developed and validated, to segment BTV and GTV from PET and MR images, respectively. In addition, the GTV is utilized to combine the superior contrast of PET images with the higher spatial resolution of MRI, obtaining a new BTV, called BTV_MRI. A total of 19 brain metastatic tumors, undergone stereotactic neuro-radiosurgery, were retrospectively analyzed. A framework for the evaluation of multimodal PET/MRI segmentation is also presented. Overlap-based and spatial distance-based metrics were considered to quantify similarity concerning PET and MRI segmentation approaches. Statistics was also included to measure correlation among the different segmentation processes. Since it is not possible to define a gold-standard CTV according to both MRI and PET images without treatment response assessment, the feasibility and the clinical value of BTV integration in Gamma Knife treatment planning were considered. Therefore, a qualitative evaluation was carried out by three experienced clinicians.

RESULTS

The achieved experimental results showed that GTV and BTV segmentations are statistically correlated (Spearman's rank correlation coefficient: 0.898) but they have low similarity degree (average Dice Similarity Coefficient: 61.87 ± 14.64). Therefore, volume measurements as well as evaluation metrics values demonstrated that MRI and PET convey different but complementary imaging information. GTV and BTV could be combined to enhance treatment planning. In more than 50% of cases the CTV was strongly or moderately conditioned by metabolic imaging. Especially, BTV_MRI enhanced the CTV more accurately than BTV in 25% of cases.

CONCLUSIONS

The proposed fully automatic multimodal PET/MRI segmentation method is a valid operator-independent methodology helping the clinicians to define a CTV that includes both metabolic and morphologic information. BTV_MRI and GTV should be considered for a comprehensive treatment planning.

Automated treatment planning for a dedicated multi-source intracranial radiosurgery treatment unit using projected gradient and grassfire algorithms

PURPOSE

The purpose of this work is to develop a framework to the inverse problem for radiosurgery treatment planning on the Gamma Knife(®) Perfexion™ (PFX) for intracranial targets.

METHODS

The approach taken in the present study consists of two parts. First, a hybrid grassfire and sphere-packing algorithm is used to obtain shot positions (isocenters) based on the geometry of the target to be treated. For the selected isocenters, a sector duration optimization (SDO) model is used to optimize the duration of radiation delivery from each collimator size from each individual source bank. The SDO model is solved using a projected gradient algorithm. This approach has been retrospectively tested on seven manually planned clinical cases (comprising 11 lesions) including acoustic neuromas and brain metastases.

RESULTS

In terms of conformity and organ-at-risk (OAR) sparing, the quality of plans achieved with the inverse planning approach were, on average, improved compared to the manually generated plans. The mean difference in conformity index between inverse and forward plans was -0.12 (range: -0.27 to +0.03) and +0.08 (range: 0.00-0.17) for classic and Paddick definitions, respectively, favoring the inverse plans. The mean difference in volume receiving the prescribed dose (V(100)) between forward and inverse plans was 0.2% (range: -2.4% to +2.0%). After plan renormalization for equivalent coverage (i.e., V(100)), the mean difference in dose to 1 mm(3) of brainstem between forward and inverse plans was -0.24 Gy (range: -2.40 to +2.02 Gy) favoring the inverse plans. Beam-on time varied with the number of isocenters but for the most optimal plans was on average 33 min longer than manual plans (range: -17 to +91 min) when normalized to a calibration dose rate of 3.5 Gy/min. In terms of algorithm performance, the isocenter selection for all the presented plans was performed in less than 3 s, while the SDO was performed in an average of 215 min.

CONCLUSIONS

PFX inverse planning can be performed using geometric isocenter selection and mathematical modeling and optimization techniques. The obtained treatment plans all meet or exceed clinical guidelines while displaying high conformity.

Feasibility of identification of gamma knife planning strategies by identification of pareto optimal gamma knife plans

The use of conformity indices to optimize Gamma Knife planning is common, but does not address important tradeoffs between dose to tumor and normal tissue. Pareto analysis has been used for this purpose in other applications, but not for Gamma Knife (GK) planning. The goal of this work is to use computer models to show that Pareto analysis may be feasible for GK planning to identify dosimetric tradeoffs. We define a GK plan A to be Pareto dominant to B if the prescription isodose volume of A covers more tumor but not more normal tissue than B, or if A covers less normal tissue but not less tumor than B. A plan is Pareto optimal if it is not dominated by any other plan. Two different Pareto optimal plans represent different tradeoffs between dose to tumor and normal tissue, because neither plan dominates the other. ‘GK simulator’ software calculated dose distributions for GK plans, and was called repetitively by a genetic algorithm to calculate Pareto dominant plans. Three irregular tumor shapes were tested in 17 trials using various combinations of shots. The mean number of Pareto dominant plans/trial was 59 ± 17 (sd). Different planning strategies were identified by large differences in shot positions, and 70 of the 153 coordinate plots (46%) showed differences of 5mm or more. The Pareto dominant plans dominated other nearby plans. Pareto dominant plans represent different dosimetric tradeoffs and can be systematically calculated using genetic algorithms. Automatic identification of non-intuitive planning strategies may be feasible with these methods.

Registration methodology for histological sections and in vivo imaging of human prostate

RATIONALE AND OBJECTIVES

Registration enables quantitative spatial correlation of features from different imaging modalities. Our objective is to register in vivo imaging with histologic sections of the human prostate so that histologic truth can be correlated with in vivo imaging features.

MATERIALS AND METHODS

In vivo imaging of the prostate included T2-weighted anatomic and diffusion weighted 3-T magnetic resonance imaging (MRI) as well as 11C-choline positron emission tomography (PET). In addition, ex vivo 3-T MRI of the prostate specimen, histology, and associated block face photos of the prostate specimen were obtained. A standard registration method based on mutual information (MI) and thin-plate spline (TPS) was applied. Registration among in vivo imaging modalities is well established; however, accurate registration involving histology is difficult. Our approach breaks up the difficult direct registration of histology and in vivo imaging into achievable subregistration tasks involving intermediate ex vivo modalities like block face photography and specimen MRI. Results of subregistration tasks are combined to compute the intended, final registration between in vivo imaging and histology.

RESULTS

The methodology was applied to two patients and found to be clinically feasible. Overall registered anatomic MRI, diffusion MRI, and 11C-choline PET aligned well with histology qualitatively for both patients. There is no ground truth of registration accuracy as the scans are real patient scans. An indirect validation of the registration accuracy has been proposed comparing tumor boundary markings found in diffusion MRI and histologic sections. Registration errors for two patients between diffusion MRI and histology were 3.74 and 2.26 mm.

CONCLUSION

This proof of concept paper demonstrates a method based on intrinsic image information content for successfully registering in vivo imaging of the human prostate with its post-resection histology, which does not require the use of extrinsic fiducial markers. The methodology successfully mapped histology onto the in vivo imaging space, allowing the observation of how well different in vivo imaging features correspond to histologic truth. The methodology is therefore the basis for a systematic comparison of in vivo imaging for staging of human prostate cancer.

A new Gamma Knife radiosurgery paradigm: tomosurgery

This study proposes and simulates an inverse treatment planning and a continuous dose delivery approach for the Leksell Gamma Knife (LGK, Elekta, Stockholm, Sweden) which we refer to as "Tomosurgery." Tomosurgery uses an isocenter that moves within the irradiation field to continuously deliver the prescribed radiation dose in a raster-scanning format, slice by slice, within an intracranial lesion. Our Tomosurgery automated (inverse) treatment planning algorithm utilizes a two-stage optimization strategy. The first stage reduces the current three-dimensional (3D) treatment planning problem to a series of more easily solved 2D treatment planning subproblems. In the second stage, those 2D treatment plans are assembled to obtain a final 3D treatment plan for the entire lesion. We created Tomosurgery treatment plans for 11 patients who had already received manually-generated LGK treatment plans to treat brain tumors. For the seven cases without critical structures (CS), the Tomosurgery treatment plans showed borderline to significant improvement in within-tumor dose standard deviation (STD) (p <0.058, or p <0.011 excluding case 2) and conformality (p < 0.042), respectively. In three of the four cases that presented CS, the Tomosurgery treatment plans showed no statistically significant improvements in dose conformality (p <0.184), and borderline significance in improving within-tumor dose homogeneity (p <0.054); CS damage measured by V20 or V30 (i.e., irradiated CS volume that receives > or =20% or > or =30% of the maximum dose) showed no significant improvement in the Tomosurgery treatment plans (p<0.345 and p <0.423, respectively). However, the overall CS dose volume histograms were improved in the Tomosurgery treatment plans. In addition, the LGK Tomosurgery inverse treatment planning required less time than standard of care, forward (manual) LGK treatment planning (i.e., 5-35 min vs 1-3 h) for all 11 cases. We expect that LGK Tomosurgery will speed treatment planning and improve treatment quality, especially for large and/or geometrically complex lesions. However, using only 4 mm collimators could greatly increase treatment plan delivery time for a large brain lesion. This issue is subject to further investigation.

Shielding strategies for Gamma Knife surgery of pituitary adenomas

OBJECT

The relative performances of two plugging strategies commonly used for pituitary adenoma dose plans were evaluated in terms of factors that influence dose plan quality.

METHODS

Dose plans and clinical treatment data were obtained in 108 patients treated with the Model C Gamma Knife at the University of Virginia. These data were analyzed to determine factors (including plugging strategy) influencing the quality of the dose plans in terms of beam time, conformity, dose to the optic apparatus, and plugging burden. For both secretory and nonsecretory adenomas, beam time (p(secretory) < 0.001, p(nonsecretory) = 0.015) and plugging burden (p(secretory) = 0.007, p(nonsecretory) = 0.038) were reduced when using the customized plugging strategy. The choice of plugging strategy was found to play no significant role in conformity or dose to the optic apparatus. Other factors found to play a significant role in adenoma dose plan quality included tumor volume, prescription dose, and distance from the target to the optic pathways.

CONCLUSIONS

While both plugging strategies were effective at providing the required protection to the optic pathways, the authors found that the customized plugging strategy provided more efficient performance in pituitary adenoma treatments.

Automated gamma knife radiosurgery treatment planning with image registration, data-mining, and Nelder-Mead simplex optimization

Gamma knife treatments are usually planned manually, requiring much expertise and time. We describe a new, fully automatic method of treatment planning. The treatment volume to be planned is first compared with a database of past treatments to find volumes closely matching in size and shape. The treatment parameters of the closest matches are used as starting points for the new treatment plan. Further optimization is performed with the Nelder-Mead simplex method: the coordinates and weight of the isocenters are allowed to vary until a maximally conformal plan specific to the new treatment volume is found. The method was tested on a randomly selected set of 10 acoustic neuromas and 10 meningiomas. Typically, matching a new volume took under 30 seconds. The time for simplex optimization, on a 3 GHz Xeon processor, ranged from under a minute for small volumes (<1000 cubic mm, 2-3 isocenters), to several tens of hours for large volumes (>30,000 cubic mm, >20 isocenters). In 8/10 acoustic neuromas and 8/10 meningiomas, the automatic method found plans with conformation number equal or better than that of the manual plan. In 4/10 acoustic neuromas and 5/10 meningiomas, both overtreatment and undertreatment ratios were equal or better in automated plans. In conclusion, data-mining of past treatments can be used to derive starting parameters for treatment planning. These parameters can then be computer optimized to give good plans automatically.

A constrained tracking algorithm to optimize plug patterns in multiple isocenter gamma knife radiosurgery planning

We developed a source blocking optimization algorithm for Gamma Knife radiosurgery, which is based on tracking individual source contributions to arbitrarily shaped target and critical structure volumes. A scalar objective function and a direct search algorithm were used to produce near real-time calculation results. The algorithm allows the user to set and vary the total number of plugs for each shot to limit the total beam-on time. We implemented and tested the algorithm for several multiple-isocenter Gamma Knife cases. It was found that the use of limited number of plugs significantly lowered the integral dose to the critical structures such as an optical chiasm in pituitary adenoma cases. The main effect of the source blocking is the faster dose falloff in the junction area between the target and the critical structure. In summary, we demonstrated a useful source-plugging algorithm for improving complex multi-isocenter Gamma Knife treatment planning cases.

A geometrically based method of step and shoot stereotactic radiosurgery with a miniature multileaf collimator

Conventional methods of inverse planning for intensity-modulated radiotherapy (IMRT) and intensity-modulated radiosurgery (IMRS) are generally based upon optimizing a set of beam fluence profiles according to a set of dose-volume constraints specified by a human planner. This optimization is generally carried out through an iterative approach that relies upon the optimization of a score, driving the plan's ability to satisfy the user-provided constraints. Following optimization of the fluence distribution, the non-trivial problem of converting the fluence distribution into a set of deliverable, intensity-modulated beams must be solved. A novel approach to solving this IMRS total inverse problem is presented in this paper. The proposed method uses a class solution that provides an optimized dose gradient and a method of designing a conformal plan based on an existing geometrically based optimization algorithm. After developing an optimal fluence distribution, the process then arranges the fluence into a set of simple and efficient MLC beam delivery sequences. The algorithm presented here offers several potential advantages for the application of intensity modulation to radiosurgery treatment planning. The geometrically based optimization process' simplicity requires far less human user input and decision making in the specification of dose and dose-volume constraints than do conventional inverse planning algorithms. This simplicity allows the optimization process to be completed much faster than conventional inverse-planning algorithms, literally seconds compared with at least several minutes. Likewise, the fluence conversion step is a simplified process (compared to conventional IMRT planning), which takes advantage of some simplifications uniquely appropriate to the problem at hand (IMRS). The converted, deliverable IMRS beams allow superior conformity and dose gradient relative to conventional IMRS planning or 3DCRT radiosurgery planning. Another benefit is that the number of beam intensity levels is greatly reduced, from hundreds to as few as a half-dozen intensity levels. Finally, since the treatment plan optimization process is based upon proven principles applicable to optimizing radiosurgery (rather than the general problem of optimizing fractionated radiotherapy plans), the plans generated and deliverable with this method of IMRS are potentially superior to those produced by conventional inverse-planning methods of IMRT/IMRS.

Selective source blocking for Gamma Knife radiosurgery of trigeminal neuralgia based on analytical dose modelling

We have developed an automatic critical region shielding (ACRS) algorithm for Gamma Knife radiosurgery of trigeminal neuralgia. The algorithm selectively blocks 201 Gamma Knife sources to minimize the dose to the brainstem while irradiating the root entry area of the trigeminal nerve with 70-90 Gy. An independent dose model was developed to implement the algorithm. The accuracy of the dose model was tested and validated via comparison with the Leksell GammaPlan (LGP) calculations. Agreements of 3% or 3 mm in isodose distributions were found for both single-shot and multiple-shot treatment plans. After the optimized blocking patterns are obtained via the independent dose model, they are imported into the LGP for final dose calculations and treatment planning analyses. We found that the use of a moderate number of source plugs (30-50 plugs) significantly lowered (approximately 40%) the dose to the brainstem for trigeminal neuralgia treatments. Considering the small effort involved in using these plugs, we recommend source blocking for all trigeminal neuralgia treatments with Gamma Knife radiosurgery.

Real-time inverse planning for Gamma Knife radiosurgery

The challenges of real-time Gamma Knife inverse planning are the large number of variables involved and the unknown search space a priori. With limited collimator sizes, shots have to be heavily overlapped to form a smooth prescription isodose line that conforms to the irregular target shape. Such overlaps greatly influence the total number of shots per plan, making pre-determination of the total number of shots impractical. However, this total number of shots usually defines the search space, a pre-requisite for most of the optimization methods. Since each shot only covers part of the target, a collection of shots in different locations and various collimator sizes selected makes up the global dose distribution that conforms to the target. Hence, planning or placing these shots is a combinatorial optimization process that is computationally expensive by nature. We have previously developed a theory of shot placement and optimization based on skeletonization. The real-time inverse planning process, reported in this paper, is an expansion and the clinical implementation of this theory. The complete planning process consists of two steps. The first step is to determine an optimal number of shots including locations and sizes and to assign initial collimator size to each of the shots. The second step is to fine-tune the weights using a linear-programming technique. The objective function is to minimize the total dose to the target boundary (i.e., maximize the dose conformity). Results of an ellipsoid test target and ten clinical cases are presented. The clinical cases are also compared with physician's manual plans. The target coverage is more than 99% for manual plans and 97% for all the inverse plans. The RTOG PITV conformity indices for the manual plans are between 1.16 and 3.46, compared to 1.36 to 2.4 for the inverse plans. All the inverse plans are generated in less than 2 min, making real-time inverse planning a reality.

Development of a rapid planning technique based on heuristic target shaping for stereotactic radiosurgery

Stereotactic radiosurgery (SRS) is a technique to delivering a high dose to a target region and a low dose to a critical organ by using only one or a few irradiations. Traditionally, SRS is performed using a Gamma knife with using 201 cobalt 60 sources or a linear accelerator with equally spaced noncoplanar arcs. Finding a specific condition that includes the target in the prescription dose while sparing the critical organ is tedious, because there are many combinations of positions and collimator sizes for each isocenter. Many methods of identifying suitable planning condition automatically have been proposed. However, there are some limitations using these methods. These include a long calculation time to obtain the final plan, and difficulties finding a unique solution due to different tumor shapes. This study uses three steps to solve these problems. (1) The dose distribution of one isocenter is modeled as a sphere. This makes it possible to reduce the time needed to obtain the result due to the absence of a dose calculation. (2) The target was constructed by piling up cylinders along a virtual axis, which was the longest line in a given target. (3) Spheres were then packed in each cylinder according to the position and diameter of each cylinder in order to cover each target divided by the height of the cylinder. The results of applying three imaginary targets were found to be satisfactory in terms of: target coverage-more than 50%, the reproducibility of the result and the calculation time-several tens of seconds. The PITV ratio was less than 2.0. However, the dose applied to normal tissue around the target must be reduced slightly. Planner or conventional optimization algorithms might easily solve this limitation.

Quality of coverage: conformity measures for stereotactic radiosurgery

In radiosurgery, conformity indices are often used to compare competing plans, evaluate treatment techniques, and assess clinical complications. Several different indices have been reported to measure the conformity of the prescription isodose to the target volume. The PITV recommended in the Radiation Therapy Oncology Group (RTOG) radiosurgery guidelines, defined as the ratio of the prescription isodose volume (PI) over the target volume (TV), is probably the most frequently quoted. However, these currently used conformity indices depend on target size and shape complexity. The objectives of this study are to systematically investigate the influence of target size and shape complexity on existing conformity indices, and to propose a different conformity index–the conformity distance index (CDI). The CDI is defined as the average distance between the target and the prescription isodose line. This study examines five case groups with volumes of 0.3, 1.0, 3.0, 10.0, and 30.0 cm³. Each case group includes four simulated shapes: a sphere, a moderate ellipsoid, an extreme ellipsoid, and a concave “C” shape. Prescription dose coverages are generated for three simplified clinical scenarios, i.e., the PI completely covers the TV with 1 and 2 mm margins, and the PI over‐covers one half of the TV with a 1 mm margin and under‐covers the other half with a 1 mm margin. Existing conformity indices and the CDI are calculated for these five case groups as well as seven clinical cases. When these values are compared, the RTOG PITV conformity index and other similar conformity measures have much higher values than the CDI for smaller and more complex shapes. With the same quality of prescription dose coverage, the CDI yields a consistent conformity measure. For the seven clinical cases, we also find that the same PITV values can be associated with very different conformity qualities while the CDI predicts the conformity quality accurately. In summary, the proposed CDI provides more consistent and accurate conformity measurements for all target sizes and shapes studied, and therefore will be a more useful conformity index for irregularly shaped targets.

PACS number(s): 87.90.+y, 87.53.Ly

Clinical implementation of an automated planning system for gamma knife radiosurgery

PURPOSE

To evaluate an automated treatment planning system for gamma knife radiosurgery. This planning system was developed in our clinic and is now in routine clinical use. The system simultaneously optimizes the shot sizes, locations, and weights. It also guides the user in selecting the total number of radiation shots.

METHODS AND MATERIALS

We assessed the clinical significance of the automated system by comparing an optimized plan with a manual plan for 10 consecutive patients treated at our gamma knife facility. Each treatment plan was analyzed using dose-volume histograms in conjunction with the conformity index, the minimum target dose, and the integral normal tissue dose.

RESULTS

On average, the treatment plan produced by the inverse planning tool provided an improved conformity index, a higher minimum target dose, and a reduced volume of the 30% isodose line as compared to the corresponding plan developed by an experienced physician. An optimized treatment plan can typically be produced in 10 min or less.

CONCLUSIONS

The automated planning system consistently provides a high-quality treatment plan while reducing the time required for gamma knife treatment planning.

Sequential annealing-gradient Gamma-Knife radiosurgery optimization

Simulated annealing and gradient methods are commonly employed for inverse planning of radiotherapy delivery schemes. Annealing is effective in finding an approximation of the global solution, suffering from slow late convergence and in some cases poor dose homogeneity. Gradient methods converge well but not necessarily to the global minimum. We explored simulated annealing followed by gradient optimization to improve on either method alone, using radiosurgery as the model system. Simulated annealing and gradient inverse planning programs using the same objective function were adapted for radiosurgical optimization. The objective function chosen is a least-squares dose-matching function, with differential weighting of tissues. A simple test target allowing local minima in the objective function was evaluated. Two hundred trials using the gradient method were done. The gradient method approximated the global solution only 12% of the time, commonly finding a local minimum. The annealing-gradient technique converged to the global minimum in 78 out of 80 trials, more efficiently than annealing alone. Dose homogeneity was improved. In conclusion, sequential annealing-gradient optimization can improve on either method alone. The technique may be extensible to radiotherapy inverse planning in general, with benefit expected for problems characterized by slow gradient method convergence and local minima.

Safety of multiple stereotactic radiosurgery treatments for multiple brain lesions

BACKGROUND

Stereotactic radiosurgery (SRS) is a widely used therapy for multiple brain lesions, and studies have clearly established the safety and efficacy of single-dose SRS. However, as patient survival has increased, the recurrence of tumors and the development of metastases to new sites within the brain have made it desirable to repeat treatments over time. The cumulative toxicity of multi-isocenter, multiple treatments has not been well defined. We have retrospectively studied 10 patients who received multiple SRS treatments for multiple brain lesions to assess the cumulative toxicity of these treatments.

METHODS

In a retrospective review of all patients treated with SRS using the X-knife (Radionics, Burlington, MA) at Westchester Medical Center/New York Medical College between December 1995 and December 2000, 10 patients were identified who received at least two treatments to at least 3 isocenters and had a minimum follow-up period of 6 months. Image fusion technique was used to determine cumulative doses to targeted lesions, whole brain and critical brain structures. Toxicities and complications were identified by chart and radiological review.

RESULTS

The average of the maximum doses (cGy) to a point within the whole brain was 2402 (range 1617-3953); to the brainstem, 1059 (range 48-4126); to the right optic nerve, 223 (range 14-1012); to the left optic nerve, 159 (range 17-475); and to the optic chiasm, 219 (range 15-909). There were no focal neurological toxicities, including visual disturbances, cranial nerve palsies, or ataxia in any of the 10 patients. There were also no global toxicities, including cognitive decline or secondary tumors. Only one patient developed seizures that were difficult to control in association with radiation necrosis.

CONCLUSIONS

Multiple SRS treatments at the cumulative doses used in our study are a safe therapy for patients with multiple brain lesions.

Treatment planning for stereotactic radiosurgery with photon beams

Stereotactic Radiosurgery (SRS) has evolved as a unique discipline that combines aspects of both surgery and radiation oncology. Technological developments in the past few decades have provided a wide array of treatment techniques, including (i) the Gamma Knife; (ii) Linac-based stereotactic techniques using circular collimators or using micro multileaf collimators (mMLCs); (iii) the Cyber Knife, using an x-band linac mounted on a robotic arm; and (iv) serial and spiral tomotherapy. This paper provides a review of the treatment planning methods for stereotactic radiosurgery. Because of the differences in planning strategies used for each SRS technique, this paper will provide both a general review of the pre-requisites and common features of SRS treatment planning and the planning techniques specific to each of the SRS techniques.

Plug pattern optimization for gamma knife radiosurgery treatment planning

PURPOSE

To develop a novel dose optimization algorithm for improving the sparing of critical structures during gamma knife radiosurgery by shaping the plug pattern of each individual shot.

METHOD AND MATERIALS

We first use a geometric information (medial axis) aided guided evolutionary simulated annealing (GESA) optimization algorithm to determine the number of shots and isocenter location, size, and weight of each shot. Then we create a plug quality score system that checks the dose contribution to the volume of interest by each plug in the treatment plan. A positive score implies that the corresponding source could be open to improve tumor coverage, whereas a negative score means the source could be blocked for the purpose of sparing normal and critical structures. The plug pattern is then optimized via the GESA algorithm that is integrated with this score system. Weight and position of each shot are also tuned in this procedure.

RESULTS

An acoustic tumor case is used to evaluate our algorithm. Compared to the treatment plan generated without plug patterns, adding an optimized plug pattern into the treatment planning process boosts tumor coverage index from 95.1% to 97.2%, reduces RTOG conformity index from 1.279 to 1.167, lowers Paddick's index from 1.34 to 1.20, and trims the critical structure receiving more than 30% maximum dose from 16 mm(3) to 6 mm(3).

CONCLUSIONS

Automated GESA-based plug pattern optimization of gamma knife radiosurgery frees the treatment planning team from the manual forward planning procedure and provides an optimal treatment plan.

Optimization of Gamma knife treatment planning via guided evolutionary simulated annealing

We present a method for generating optimized Gamma Knife (Elekta, Stockholm, Sweden) radiosurgery treatment plans. This semiautomatic method produces a highly conformal shot packing plan for the irradiation of an intracranial tumor. We simulate optimal treatment planning criteria with a probability function that is linked to every voxel in a volumetric (MR or CT) region of interest. This sigmoidal P+ parameter models the requirement of conformality (i.e., tumor ablation and normal tissue sparing). After determination of initial radiosurgery treatment parameters, a guided evolutionary simulated annealing (GESA) algorithm is used to find the optimal size, position, and weight for each shot. The three-dimensional GESA algorithm searches the shot parameter space more thoroughly than is possible during manual shot packing and provides one plan that is suitable to the treatment criteria of the attending neurosurgeon and radiation oncologist. The result is a more conformal plan, which also reduces redundancy, and saves treatment administration time.

A variable fluence step clustering and segmentation algorithm for step and shoot IMRT

A step and shoot sequencer was developed that can be integrated into an IMRT optimization algorithm. The method uses non-uniform fluence steps and is adopted to the constraints of an MLC. It consists of a clustering, a smoothing and a segmentation routine. The performance of the algorithm is demonstrated for eight mathematical profiles of differing complexity and two optimized profiles of a clinical prostate case. The results in terms of stability, flexibility, speed and conformity fulfil the criteria for the integration into the optimization concept. The performance of the clustering routine is compared with another previously published one (Bortfeld et al 1994 Int. J. Radiat. Oncol. Biol. Ph.vs. 28 723-30) and yields slightly better results in terms of mean and maximum deviation between the optimized and the clustered protile. We discuss the specific attributes of the algorithm concerning its integration into the optimization concept.

Inverse treatment planning for Gamma Knife radiosurgery

An inverse treatment planning system for Gamma Knife radiosurgery has been developed using nonlinear programming techniques. The system optimizes the shot sizes, locations, and weights for Gamma Knife treatments. In the patient's prescription, the user can specify both the maximum number of shots of radiation and a minimum isodose line that must surround the entire treatment volume. After satisfying all of the constraints included in the prescription, the system maximizes the conformity of the dose distribution. This automated approach to treatment planning has been applied retrospectively to a series of patient cases, and each optimized plan has been compared to the corresponding manual plan produced by an experienced user. The results demonstrate that this tool can often improve the tumor dose homogeneity while using fewer shots than were included in the original plan. Therefore, inverse treatment planning should improve both the quality and the efficiency of Gamma Knife treatments.

A geometrically based method for automated radiosurgery planning

PURPOSE

A geometrically based method of multiple isocenter linear accelerator radiosurgery treatment planning optimization was developed, based on a target's solid shape.

METHODS AND MATERIALS

Our method uses an edge detection process to determine the optimal sphere packing arrangement with which to cover the planning target. The sphere packing arrangement is converted into a radiosurgery treatment plan by substituting the isocenter locations and collimator sizes for the spheres.

RESULTS

This method is demonstrated on a set of 5 irregularly shaped phantom targets, as well as a set of 10 clinical example cases ranging from simple to very complex in planning difficulty. Using a prototype implementation of the method and standard dosimetric radiosurgery treatment planning tools, feasible treatment plans were developed for each target. The treatment plans generated for the phantom targets showed excellent dose conformity and acceptable dose homogeneity within the target volume. The algorithm was able to generate a radiosurgery plan conforming to the Radiation Therapy Oncology Group (RTOG) guidelines on radiosurgery for every clinical and phantom target examined.

CONCLUSIONS

This automated planning method can serve as a valuable tool to assist treatment planners in rapidly and consistently designing conformal multiple isocenter radiosurgery treatment plans.