Biomedical subjects

Qiuwen Wu

Publications and source records attributed to Qiuwen Wu.

8 recordsLinked to original sources

PubMed2003

A fast dose calculation method based on table lookup for IMRT optimization.

This note describes a fast dose calculation method that can be used to speed up the optimization process in intensity-modulated radiotherapy (IMRT). Most iterative optimization algorithms in IMRT require a large number of dose calculations to achieve convergence and therefore the total amount of time needed for the IMRT planning can be substantially reduced by using a faster dose calculation method. The method that is described in this note relies on an accurate dose calculation engine that is used to calculate an approximate dose kernel for each beam used in the treatment plan. Once the kernel is computed and saved, subsequent dose calculations can be done rapidly by looking up this kernel. Inaccuracies due to the approximate nature of the kernel in this method can be reduced by performing scheduled kernel updates. This fast dose calculation method can be performed more than two orders of magnitude faster than the typical superposition/convolution methods and therefore is suitable for applications in which speed is critical, e.g., in an IMRT optimization that requires a simulated annealing optimization algorithm or in a practical IMRT beam-angle optimization system.

Algorithms↗

PubMed2003

Simultaneous integrated boost intensity-modulated radiotherapy for locally advanced head-and-neck squamous cell carcinomas. I: dosimetric results.

PURPOSE: This report describes the dosimetric analyses of a Phase I/II protocol, designed to examine the capabilities of an institutionally developed intensity-modulated radiotherapy (IMRT) system with respect to dose escalation. The protocol employed stringent dosimetric guidelines in the treatment of locally advanced head-and-neck squamous cell carcinomas (HNSCC) with radiotherapy alone using IMRT and the simultaneous integrated boost (SIB) technique. METHODS AND MATERIALS: The first 14 patients enrolled on the protocol were included in this analysis. Escalating doses of 68.1 Gy (6 patients), 70.8 Gy (6 patients), and 73.8 Gy (2 patients) were delivered to the gross tumor volume (GTV) in 30 fractions. Simultaneously, constant dose coverage was given to the subclinical disease and the electively treated nodal regions, which received 60 Gy and 54 Gy, respectively, in all three cohorts. Parotid glands were spared to the degree possible without compromising target coverage. The following indices are reported for the GTV: (1) dose to specified percent volumes (e.g., D(98) and D(2)); (2) homogeneity index defined as the ratio (D(2) - D(98))/D(prescription); (3) biologically equivalent uniform dose (EUD); and (4) an index of conformality, PITV, defined as the ratio of volume enclosed within the prescribed isodose surface to the target volume. Treatments were planned and delivered with nine 6-MV photon beams using the multileaf collimator (MLC) "sliding window" technique. RESULTS: Mean doses to 98% of GTV were 68.4 Gy, 70.5 Gy, and 70.8 Gy, and average GTV dose homogeneity was 6.7%, 7.6%, and 8.8% for the three cohorts. The average doses to the parotid gland proximal to and distant from GTV were 41.3 Gy and 25.7 Gy, respectively. Dose distributions measured in phantom showed good agreement with calculations. CONCLUSIONS: Treatment of locally advanced HNSCC using SIB-IMRT as described is feasible. Treatment planning and delivery are safer and more efficient than with conventional three-dimensional processes. Predicted dose distributions can be accurately delivered with excellent conformality using dynamic MLC. At least one of the parotid glands can be adequately spared. Patient follow-up continues and will allow eventual quantitative correlation of delivered dose distributions with clinical outcomes.

Carcinoma, Squamous Cell↗

PubMed2003

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.

Adenocarcinoma↗

PubMed2002

Optimization of intensity-modulated radiotherapy plans based on the equivalent uniform dose.

PURPOSE: The equivalent uniform dose (EUD) for tumors is defined as the biologically equivalent dose that, if given uniformly, will lead to the same cell kill in the tumor volume as the actual nonuniform dose distribution. Recently, a new formulation of EUD was introduced that applies to normal tissues as well. EUD can be a useful end point in evaluating treatment plans with nonuniform dose distributions for three-dimensional conformal radiotherapy and intensity-modulated radiotherapy. In this study, we introduce an objective function based on the EUD and investigate the feasibility and usefulness of using it for intensity-modulated radiotherapy optimization. METHODS AND MATERIALS: We applied the EUD-based optimization to obtain intensity-modulated radiotherapy plans for prostate and head-and-neck cancer patients and compared them with the corresponding plans optimized with dose-volume-based criteria. RESULTS: We found that, for the same or better target coverage, EUD-based optimization is capable of improving the sparing of critical structures beyond the specified requirements. We also found that, in the absence of constraints on the maximal target dose, the target dose distributions are more inhomogeneous, with significant hot spots within the target volume. This is an obvious consequence of unrestricted maximization target cell kill and, although this may be considered beneficial for some cases, it is generally not desirable. To minimize the magnitude of hot spots, we applied dose inhomogeneity constraints to the target by treating it as a "virtual" normal structure as well. This led to much-improved target dose homogeneity, with a small, but expected, degradation in normal structure sparing. We also found that, in principle, the dose-volume objective function may be able to arrive at similar optimum dose distributions by using multiple dose-volume constraints for each anatomic structure and with considerably greater trial-and-error to adjust a large number of objective function parameters. CONCLUSION: The general inference drawn from our investigation is that the EUD-based objective function has the advantages that it needs only a small number of parameters and allows exploration of a much larger universe of solutions, making it easier for the optimization system to balance competing requirements in search of a better solution.

Algorithms↗

PubMed2002

Technical considerations in the application of intensity-modulated radiotherapy as a concomitant integrated boost for locally-advanced cervix cancer.

The technical aspects of IMRT applied to cervix cancer are discussed in this paper, as well as issues related to tumor delineation, target volume definitions, inverse planning, and IMRT delivery. A theoretical example illustrating how IMRT can accurately mimic dose distributions obtained using conventional planning plus HDR brachytherapy is also shown. The notion of clinical optimization parameters is introduced to account for the radiation delivery variables, which affect the overall treatment time. This is especially relevant to the possible introduction of intrafractional movement and resulting inaccuracy, as well as facility efficiency.

Brachytherapy↗

PubMed2002

Clinical application of intensity-modulated radiotherapy for locally advanced cervical cancer.

Intensity-modulated radiotherapy (IMRT) offers technical advantages over conventional external beam radiotherapy (CXRT) that might prove clinically advantageous in the management of gynecologic malignancies. Especially in the case of locally advanced cervical cancer, IMRT provides an opportunity to improve the therapeutic ratio by allowing a selective combination of normal tissue dose reduction and/or concomitant integrated boost dose to the tumor. The clinical and biologic rationale for IMRT in this setting is presented here, and pertinent technical considerations such as the delineation of relevant clinical and planning target volumes are discussed. The capacity for IMRT-mediated normal tissue sparing is illustrated by example and review of the literature. Furthermore, for a small cohort of patients with locally advanced or recurrent cervical cancer treated with concomitant integrated boost IMRT and concurrent chemotherapy, preliminary clinical observations of toxicity and tumor response are presented. Concomitant integrated boost IMRT appears clinically tolerable and efficacious in this setting, and formal clinical investigation is warranted as a means of exploiting the fraction-size dependence of radiosensitizers in common clinical use.

Female↗

PubMed2002

Reducing dose calculation time for accurate iterative IMRT planning.

A time-consuming component of IMRT optimization is the dose computation required in each iteration for the evaluation of the objective function. Accurate superposition/convolution (SC) and Monte Carlo (MC) dose calculations are currently considered too time-consuming for iterative IMRT dose calculation. Thus, fast, but less accurate algorithms such as pencil beam (PB) algorithms are typically used in most current IMRT systems. This paper describes two hybrid methods that utilize the speed of fast PB algorithms yet achieve the accuracy of optimizing based upon SC algorithms via the application of dose correction matrices. In one method, the ratio method, an infrequently computed voxel-by-voxel dose ratio matrix (R = D(SC)/D(PB)) is applied for each beam to the dose distributions calculated with the PB method during the optimization. That is, D(PB) x R is used for the dose calculation during the optimization. The optimization proceeds until both the IMRT beam intensities and the dose correction ratio matrix converge. In the second method, the correction method, a periodically computed voxel-by-voxel correction matrix for each beam, defined to be the difference between the SC and PB dose computations, is used to correct PB dose distributions. To validate the methods, IMRT treatment plans developed with the hybrid methods are compared with those obtained when the SC algorithm is used for all optimization iterations and with those obtained when PB-based optimization is followed by SC-based optimization. In the 12 patient cases studied, no clinically significant differences exist in the final treatment plans developed with each of the dose computation methodologies. However, the number of time-consuming SC iterations is reduced from 6-32 for pure SC optimization to four or less for the ratio matrix method and five or less for the correction method. Because the PB algorithm is faster at computing dose, this reduces the inverse planning optimization time for our implementation by a factor of 2 to 8 compared with pure SC optimization, without compromising the quality or accuracy of the final treatment plan.

Algorithms↗

PubMed2002

Multiple local minima in IMRT optimization based on dose-volume criteria.

Multiple local minima traps are known to exist in dose-volume and dose-response objective functions. Nevertheless, their presence and consequences are not considered impediments in finding satisfactory solutions in routine optimization of IMRT plans using gradient methods. However, there is often a concern that a significantly superior solution may exist unbeknownst to the planner and that the optimization process may not be able to reach it. We have investigated the soundness of the assumption that the presence of multiple minima traps can be ignored. To find local minima, we start the optimization process a large number of times with random initial intensities. We investigated whether the occurrence of local minima depends upon the choice of the objective function parameters and the number of variables and whether their existence is an impediment in finding a satisfactory solution. To learn about the behavior of multiple minima, we first used a symmetric cubic phantom containing a cubic target and an organ-at-risk surrounding it to optimize the beam weights of two pairs of parallel-opposed beams using a gradient technique. The phantom studies also served to test our software. Objective function parameters were chosen to ensure that multiple minima would exist. Data for 500 plans, optimized with random initial beam weights, were analyzed. The search process did succeed in finding the local minima and showed that the number of minima depends on the parameters of the objective functions. It was also found that the consequences of local minima depended on the number of beams. We further searched for the multiple minima in intensity-modulated treatment plans for a head-and-neck case and a lung case. In addition to the treatment plan scores and the dose-volume histograms, we examined the dose distributions and intensity patterns. We did not find any evidence that multiple local minima affect the outcome of optimization using gradient techniques in any clinically significant way. Our study supports the notion that multiple minima should not be an impediment to finding a good solution when gradient-based optimization techniques are employed. Changing the parameters for the objective function had no observable effect on our findings.

Dose-Response Relationship, Radiation↗