Helen Liu

Report of the AAPM Task Group No. 105: Issues associated with clinical implementation of Monte Carlo‐based photon and electron external beam treatment planning

The Monte Carlo (MC) method has been shown through many research studies to calculate accurate dose distributions for clinical radiotherapy, particularly in heterogeneous patient tissues where the effects of electron transport cannot be accurately handled with conventional, deterministic dose algorithms. Despite its proven accuracy and the potential for improved dose distributions to influence treatment outcomes, the long calculation times previously associated with MC simulation rendered this method impractical for routine clinical treatment planning. However, the development of faster codes optimized for radiotherapy calculations and improvements in computer processor technology have substantially reduced calculation times to, in some instances, within minutes on a single processor. These advances have motivated several major treatment planning system vendors to embark upon the path of MC techniques. Several commercial vendors have already released or are currently in the process of releasing MC algorithms for photon and/or electron beam treatment planning. Consequently, the accessibility and use of MC treatment planning algorithms may well become widespread in the radiotherapy community. With MC simulation, dose is computed stochastically using first principles; this method is therefore quite different from conventional dose algorithms. Issues such as statistical uncertainties, the use of variance reduction techniques, theability to account for geometric details in the accelerator treatment head simulation, and other features, are all unique components of a MC treatment planning algorithm. Successful implementation by the clinical physicist of such a system will require an understanding of the basic principles of MC techniques. The purpose of this report, while providing education and review on the use of MC simulation in radiotherapy planning, is to set out, for both users and developers, the salient issues associated with clinical implementation and experimental verification of MC dose algorithms. As the MC method is an emerging technology, this report is not meant to be prescriptive. Rather, it is intended as a preliminary report to review the tenets of the MC method and to provide the framework upon which to build a comprehensive program for commissioning and routine quality assurance of MC-based treatment planning systems.

Influence of technologic advances on outcomes in patients with unresectable, locally advanced non-small-cell lung cancer receiving concomitant chemoradiotherapy.

PURPOSE In 2004, our institution began using four-dimensional computed tomography (4DCT) simulation and then intensity-modulated radiotherapy (IMRT) (4DCT/IMRT) instead of three-dimensional conformal radiotherapy (3DCRT) for the standard treatment of non-small-cell lung cancer (NSCLC). This retrospective study compares disease outcomes and toxicity in patients treated with concomitant chemotherapy and either 4DCT/IMRT or 3DCRT. METHODS AND MATERIALS A total of 496 NSCLC patients have been treated at M. D. Anderson Cancer Center between 1999 and 2006 with concomitant chemoradiotherapy. Among these, 318 were treated with CT/3DCRT and 91 with 4DCT/IMRT. Both groups received a median dose of 63 Gy. Disease end points were locoregional progression (LRP), distant metastasis (DM), and overall survival (OS). Disease covariates were gross tumor volume (GTV), nodal status, and histology. The toxicity end point was Grade >or=3 radiation pneumonitis; toxicity covariates were GTV, smoking status, and dosimetric factors. Data were analyzed using Cox proportional hazards models. RESULTS Mean follow-up times in the 4DCT/IMRT and CT/3DCRT groups were 1.3 (range, 0.1-3.2) and 2.1 (range, 0.1-7.9) years, respectively. The hazard ratios for 4DCT/IMRT were <1 for all disease end points; the difference was significant only for OS. The toxicity rate was significantly lower in the IMRT/4DCT group than in the CT/3DCRT group. V20 was significantly higher in the 3DCRT group and was a significant factor in determining toxicity. Freedom from DM was nearly identical in both groups. CONCLUSIONS Treatment with 4DCT/IMRT was at least as good as that with 3DCRT in terms of the rates of freedom from LRP and DM. There was a significant reduction in toxicity and a significant improvement in OS.

Image–Guided Radiation Therapy for Non–small Cell Lung Cancer

Recent developments in image-guided radiotherapy are ushering in a new era of radiotherapy for lung cancer. Positron emission tomography/computed tomography (PET/CT) has been shown to improve targeting accuracy in 25 to 50% of cases, and four-dimensional CT scanning helps to individualize radiotherapy by accounting for tumor motion. Daily on-board imaging reduces treatment set-up uncertainty and provides information about daily organ motion and variations in anatomy. Image-guided intensity-modulated radiotherapy may allow for the escalation of radiotherapy dose with no increase in toxicity. More importantly, treatment adaptations based on anatomic changes during the course of radiotherapy and dose painting within involved lesions using functional imaging such as PET may further improve clinical outcomes of lung cancer patients and potentially lead to new clinical trials. Image-guided stereotactic radiotherapy can achieve local control rates exceeding 90% through the use of focused, hypofractionated, highly biologically effective doses. These novel approaches were considered experimental just a few years ago, but accumulating evidence of their potential for significantly improving clinical outcomes is leading to their inclusion in standard treatments for lung cancer at major cancer centers. In this review article, we focus on novel image-guided radiotherapy approaches, particularly PET/CT and four-dimensional CT-based radiotherapy planning and on-board image-guided delivery, stereotactic radiotherapy, and intensity-modulated radiotherapy for mobile nonsmall cell lung cancer.

Intensity-modulated radiotherapy optimization with gEUD-guided dose–volume objectives

Currently, most intensity-modulated radiation therapy systems use dose-volume (DV)-based objectives. Although acceptable plans can be generated using these objectives, much trial and error is necessary to plan complex cases with many structures because numerous parameters need to be adjusted. An objective function that makes use of a generalized equivalent uniform dose (gEUD) was developed recently that has the advantage of involving simple formulae and fewer parameters. In addition, not only does the gEUD-based optimization provide the same coverage of the target, it provides significantly better protection of critical structures. However, gEUD-based optimization may not be superior once dose distributions and dose-volume histograms (DVHs) are used to evaluate the plan. Moreover, it is difficult to fine-tune the DVH with gEUD-based optimization. In this paper, we propose a method for combining the gEUD-based and DV-based optimization approaches to overcome these limitations. In this method, the gEUD optimization is performed initially to search for a solution that meets or exceeds most of the treatment objectives. Depending on the requirements, DV-based optimization with a gradient technique is then used to fine-tune the DVHs. The DV constraints are specified according to the gEUD plan, and the initial intensities are obtained from the gEUD plan as well. We demonstrated this technique in two clinical cases: aprostate cancer and ahead and neck cancer case. Compared with the DV-optimized plan, the gEUD plan provided better protection of critical structures and the target coverage was similar. However, homogeneities were slightly poorer. The gEUD plan was then fine-tuned with DV constraints, and the resulting plan was superior to the other plans in terms of the dose distributions. The planning time was significantly reduced as well. This technique is an effective means of optimizing individualized treatment plans.

CONSEQUENCES OF ANATOMIC CHANGES AND RESPIRATORY MOTION ON RADIATION DOSE DISTRIBUTIONS IN CONFORMAL RADIOTHERAPY FOR LOCALLY ADVANCED NON-SMALL-CELL LUNG CANCER

PURPOSE To determine the effect of interfractional changes in anatomy on the target and normal tissue dose distributions during course of radiotherapy in non-small-cell lung cancer patients. METHODS AND MATERIALS Weekly respiration-correlated four-dimensional computed tomography scans were acquired for 10 patients. Original beam arrangements from conventional and inverse treatment plans were transferred into each of the weekly four-dimensional computed tomography data sets, and the dose distributions were recalculated. Dosimetric changes to the target volumes and relevant normal structures relative to the baseline treatment plans were analyzed by dose-volume histograms. RESULTS The overall difference in the mean +/- standard deviation of the doses to 95% of the planning target volume and internal target volume between the initial and weekly treatment plans was -11.9% +/- 12.1% and -2.5% +/- 3.9%, respectively. The mean +/- standard deviation change in the internal target volume receiving 95% of the prescribed dose was -2.3% +/- 4.1%. The overall differences in the mean +/- standard deviation between the initial and weekly treatment plans was 3.1% +/- 6.8% for the total lung volume exceeding 20 Gy, 2.2% +/- 4.8% for mean total lung dose, and 34.3% +/- 43.0% for the spinal cord maximal dose. CONCLUSION Serial four-dimensional computed tomography scans provided useful anatomic information and dosimetric changes during radiotherapy. Although the observed dosimetric variations were small, on average, the interfractional changes in tumor volume, mobility, and patient setup was sometimes associated with dramatic dosimetric consequences. Therefore, for locally advanced lung cancer patients, efforts to include image-guided treatment and to perform repeated imaging during the treatment course are recommended.

Dose sculpting with generalized equivalent uniform dose

With intensity-modulated radiotherapy (IMRT), a variety of user-defined dose distribution can be produced using inverse planning. The generalized equivalent uniform dose (gEUD) has been used in IMRT optimization as an alternative objective function to the conventional dose-volume-based criteria. The purpose of this study was to investigate the effectiveness of gEUD optimization to fine tune the dose distributions of IMRT plans. We analyzed the effect of gEUD-based optimization parameters on plan quality. The objective was to determine whether dose distribution to selected structures could be improved using gEUD optimization without adversely altering the doses delivered to other structures, as in sculpting. We hypothesized that by carefully defining gEUD parameters (EUD0 and n) based on the current dose distributions, the optimization system could be instructed to search for alternative solutions in the neighborhood, and we could maintain the dose distributions for structures already satisfactory and improve dose for structures that need enhancement. We started with an already acceptable IMRT plan optimized with any objective function. The dose distribution was analyzed first. For structures that dose should not be changed, a higher value of n was used and EUD0 was set slightly higher/lower than the EUD value at the current dose distribution for critical structures/targets. For structures that needed improvement in dose, a higher to medium value of n was used, and EUD0 was set to the EUD value or slightly lower/higher for the critical structure/target at the current dose distribution. We evaluated this method in one clinical case each of head and neck, lung and prostate cancer. Dose volume histograms, isodose distributions, and relevant tolerance doses for critical structures were used for the assessment. We found that by adjusting gEUD optimization parameters, the dose distribution could be improved with only a few iterations. A larger value of n could lead to faster convergence and a medium value of n could result in a search in a broader area. Such improvement could also be achieved by optimization based on other criteria, but the gEUD-based method has the advantage of efficiency and flexibility. Therefore, gEUD-based optimization can be used as a tool to improve IMRT plans by adjusting the planning parameters, thereby making dose sculpting feasible.

A sensitivity-guided algorithm for automated determination of IMRT objective function parameters

Optimizing intensity-modulated radiotherapy (IMRT) plans involves tradeoffs that balance normal-tissue objectives against each other and against tumor objectives. Adjusting the parameters that determine the appropriate contributions of individual anatomic structures to the objective functions through trial and error is time consuming and may not produce the best achievable plans. We have developed a sensitivity-guided parameter optimization (SGPO) method to assist in the automatic determination of parameters to drive the IMRT optimization to better achieve, or even exceed, specified planning goals. The method is based on the trade-off relationships among multiple objectives: In a globally optimal plan (or within a convex subspace of the plan objectives), any attempt to improve the achievement of goals for a structure will result in sacrificing the goals for at least one other structure. However, different objectives may have different sensitivities to the overall goal of an IMRT plan. For instance, changes in dose distribution, hence the subscore corresponding to an objective for a given normal structure, may minimally impact the target dose distribution. Stated differently, the target coverage is insensitive to the changes in dose distribution of the specific normal structure. A lung cancer treatment plan designed with the SGPO method was used to demonstrate that IMRT plans could be designed to favor a structure with the highest target sensitivity and spare the structures with the least target sensitivity without compromising the target coverage. Using one case each of prostate and paranasal sinus cancers, we also demonstrated that several alternative optimal solutions could be designed with the SGPO algorithm favoring different structures. Finally, we applied the method to eight oropharyngeal cancer cases to obtain objective function parameters that satisfied the Radiation Therapy Oncology Group RTOG-H-0022 protocol. The eight plans optimized using the computer-generated objective function parameters met the protocols scoring criteria with no or only minor protocol violations. Our preliminary study indicates that the SGPO method may be an effective and practical way to improve IMRT planning.

Target delineation for esophageal cancer

AbstractAlthough esophagectomy remains the treatment of choice for resectable tumors, the combination of chemoradiotherapy and surgery has become a common treatment of esophageal carcinoma. The most common combination is preoperative concurrent chemoradiation therapy followed by esophagectomy. For p