Biomedical subjects

Radhe Mohan

Publications and source records attributed to Radhe Mohan.

11 recordsLinked to original sources

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↗

PubMed2003

Patient training in respiratory-gated radiotherapy.

Respiratory gating is used to counter the effects of organ motion during radiotherapy for chest tumors. The effects of variations in patient breathing patterns during a single treatment and from day to day are unknown. We evaluated the feasibility of using patient training tools and their effect on the breathing cycle regularity and reproducibility during respiratory-gated radiotherapy. To monitor respiratory patterns, we used a component of a commercially available respiratory-gated radiotherapy system (Real Time Position Management (RPM) System, Varian Oncology Systems, Palo Alto, CA 94304). This passive marker video tracking system consists of reflective markers placed on the patient's chest or abdomen, which are detected by a wall-mounted video camera. Software installed on a PC interfaced to this camera detects the marker motion digitally and records it. The marker position as a function of time serves as the motion signal that may be used to trigger imaging or treatment. The training tools used were audio prompting and visual feedback, with free breathing as a control. The audio prompting method used instructions to "breathe in" or "breathe out" at periodic intervals deduced from patients' own breathing patterns. In the visual feedback method, patients were shown a real-time trace of their abdominal wall motion due to breathing. Using this, they were asked to maintain a constant amplitude of motion. Motion traces of the abdominal wall were recorded for each patient for various maneuvers. Free breathing showed a variable amplitude and frequency. Audio prompting resulted in a reproducible frequency; however, the variability and the magnitude of amplitude increased. Visual feedback gave a better control over the amplitude but showed minor variations in frequency. We concluded that training improves the reproducibility of amplitude and frequency of patient breathing cycles. This may increase the accuracy of respiratory-gated radiation therapy.

Acoustic Stimulation↗

PubMed2003

Determining the incident electron fluence for Monte Carlo-based photon treatment planning using a standard measured data set.

An accurate dose calculation in phantom and patient geometries requires an accurate description of the radiation source. Errors in the radiation source description are propagated through the dose calculation. With the emergence of linear accelerators whose dosimetric characteristics are similar to within measurement uncertainty, the same radiation source description can be used as the input to dose calculation for treatment planning at many institutions with the same linear accelerator model. Our goal in the current research was to determine the initial electron fluence above the linear accelerator target for such an accelerator to allow a dose calculation in water to within 1% or 1 mm of the measured data supplied by the manufacturer. The method used for both the radiation source description and the patient transport was Monte Carlo. The linac geometry was input into the Monte Carlo code using the accelerator's manufacturer's specifications. Assumptions about the initial electron source above the target were made based on previous studies. The free parameters derived for the calculations were the mean energy and radial Gaussian width of the initial electron fluence and the target density. A combination of the free parameters yielded an initial electron fluence that, when transported through the linear accelerator and into the phantom, allowed a dose-calculation agreement to the experimental ion chamber data to within the specified criteria at both 6 and 18 MV nominal beam energies, except near the surface, particularly for the 18 MV beam. To save time during Monte Carlo treatment planning, the initial electron fluence was transported through part of the treatment head to a plane between the monitor chambers and the jaws and saved as phase-space files. These files are used for clinical Monte Carlo-based treatment planning and are freely available from the authors.

Algorithms↗

PubMed2002

A method for photon beam Monte Carlo multileaf collimator particle transport.

Monte Carlo (MC) algorithms are recognized as the most accurate methodology for patient dose assessment. For intensity-modulated radiation therapy (IMRT) delivered with dynamic multileaf collimators (DMLCs), accurate dose calculation, even with MC, is challenging. Accurate IMRT MC dose calculations require inclusion of the moving MLC in the MC simulation. Due to its complex geometry, full transport through the MLC can be time consuming. The aim of this work was to develop an MLC model for photon beam MC IMRT dose computations. The basis of the MC MLC model is that the complex MLC geometry can be separated into simple geometric regions, each of which readily lends itself to simplified radiation transport. For photons, only attenuation and first Compton scatter interactions are considered. The amount of attenuation material an individual particle encounters while traversing the entire MLC is determined by adding the individual amounts from each of the simplified geometric regions. Compton scatter is sampled based upon the total thickness traversed. Pair production and electron interactions (scattering and bremsstrahlung) within the MLC are ignored. The MLC model was tested for 6 MV and 18 MV photon beams by comparing it with measurements and MC simulations that incorporate the full physics and geometry for fields blocked by the MLC and with measurements for fields with the maximum possible tongue-and-groove and tongue-or-groove effects, for static test cases and for sliding windows of various widths. The MLC model predicts the field size dependence of the MLC leakage radiation within 0.1% of the open-field dose. The entrance dose and beam hardening behind a closed MLC are predicted within +/- 1% or 1 mm. Dose undulations due to differences in inter- and intra-leaf leakage are also correctly predicted. The MC MLC model predicts leaf-edge tongue-and-groove dose effect within +/- 1% or 1 mm for 95% of the points compared at 6 MV and 88% of the points compared at 18 MV. The dose through a static leaf tip is also predicted generally within +/- 1% or 1 mm. Tests with sliding windows of various widths confirm the accuracy of the MLC model for dynamic delivery and indicate that accounting for a slight leaf position error (0.008 cm for our MLC) will improve the accuracy of the model. The MLC model developed is applicable to both dynamic MLC and segmental MLC IMRT beam delivery and will be useful for patient IMRT dose calculations, pre-treatment verification of IMRT delivery and IMRT portal dose transmission dosimetry.

Algorithms↗

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

Incorporating multi-leaf collimator leaf sequencing into iterative IMRT optimization.

Intensity modulated radiation therapy (IMRT) treatment planning typically considers beam optimization and beam delivery as separate tasks. Following optimization, a multi-leaf collimator (MLC) or other beam delivery device is used to generate fluence patterns for patient treatment delivery. Due to limitations and characteristics of the MLC, the deliverable intensity distributions often differ from those produced by the optimizer, leading to differences between the delivered and the optimized doses. Objective function parameters are then adjusted empirically, and the plan is reoptimized to achieve a desired deliverable dose distribution. The resulting plan, though usually acceptable, may not be the best achievable. A method has been developed to incorporate the MLC restrictions into the optimization process. Our in-house IMRT system has been modified to include the calculation of the deliverable intensity into the optimizer. In this process, prior to dose calculation, the MLC leaf sequencer is used to convert intensities to dynamic MLC sequences, from which the deliverable intensities are then determined. All other optimization steps remain the same. To evaluate the effectiveness of deliverable-based optimization, 17 patient cases have been studied. Compared with standard optimization plus conversion to deliverable beams, deliverable-based optimization results show improved isodose coverage and a reduced dose to critical structures. Deliverable-based optimization results are close to the original nondeliverable optimization results, suggesting that IMRT can overcome the MLC limitations by adjusting individual beamlets. The use of deliverable-based optimization may reduce the need for empirical adjustment of objective function parameters and reoptimization of a plan to achieve desired results.

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↗