Biomedical subjects

Shahid A Naqvi

Publications and source records attributed to Shahid A Naqvi.

11 recordsLinked to original sources

PubMed2006

A difference-matrix metaheuristic for intensity map segmentation in step-and-shoot IMRT delivery.

At an intermediate stage of radiation treatment planning for IMRT, most commercial treatment planning systems for IMRT generate intensity maps that describe the grid of beamlet intensities for each beam angle. Intensity map segmentation of the matrix of individual beamlet intensities into a set of MLC apertures and corresponding intensities is then required in order to produce an actual radiation delivery plan for clinical use. Mathematically, this is a very difficult combinatorial optimization problem, especially when mechanical limitations of the MLC lead to many constraints on aperture shape, and setup times for apertures make the number of apertures an important factor in overall treatment time. We have developed, implemented and tested on clinical cases a metaheuristic (that is, a method that provides a framework to guide the repeated application of another heuristic) that efficiently generates very high-quality (low aperture number) segmentations. Our computational results demonstrate that the number of beam apertures and monitor units in the treatment plans resulting from our approach is significantly smaller than the corresponding values for treatment plans generated by the heuristics embedded in a widely use commercial system. We also contrast the excellent results of our fast and robust metaheuristic with results from an 'exact' method, branch-and-cut, which attempts to construct optimal solutions, but, within clinically acceptable time limits, generally fails to produce good solutions, especially for intensity maps with more than five intensity levels. Finally, we show that in no instance is there a clinically significant change of quality associated with our more efficient plans.

Algorithms↗

PubMed2006

Doppler broadening effect on low-energy photon dose calculations using MCNP5 and PENELOPE.

Recent releases of the MCNP5 and PENELOPE Monte Carlo codes include the transport algorithm and momentum profiles that are necessary for accounting for Doppler broadening in Compton scattering processes. Such improvements might be particularly important in low-energy photon dose calculations. MCPLIB04 and PENDBASE (PENELOPE photon dataset) are based on the EPDL97 library with Compton momentum profiles, while MCPLIB03 and MCPLIB02 are based on the 1970's old library, with MCPLIB03 including the Compton momentum profiles. To isolate the dosimetric effects of Doppler broadening by the transport algorithm and Compton momentum profiles, we varied the choice of the above photon databases, in the same simulation geometry, using either version of MCNP5 or MCNP4 (no Doppler algorithm). We computed dose rate constants and dose distributions for r = 0.2-10 cm from a point source in a 50-cm-diameter sphere of water. Nine discrete energies for primary photon sources were chosen in the range of 10-150 keV. The results from both versions of MCNP with MCPLIB04 agreed with those of PENELOPE within statistical uncertainties (+/-1%) over the entire ranges of energies and radial distances investigated. MCNP5 with either MCPLIB03 or MCPLIB02 yielded almost identical data within statistical uncertainties (+/-1%) over the entire ranges of energies and radial distances investigated. This implies that in spite of the spectral broadening of scattered photons due to the orbital electron motion, the dosimetric effect of Doppler broadening for Compton interactions in water appears to be insignificant in the energy range investigated. The spectral dose analysis with and without the Doppler broadening supported this conclusion.

Algorithms↗

PubMed2006

Feasibility of delivering grid therapy using a multileaf collimator.

The feasibility of using a multileaf collimator (MLC) for grid therapy is demonstrated in this study. Grids with the projected field openings of 10 mm x 10 mm and 5 mm x 5 mm were created using multiple MLC-shaped fields. The deposited doses were measured with films at different depths in a solid water phantom and compared to those of Cerrobend grid collimators of similar hole sizes and hole separations. At the depth of maximum dose (dmax), the valley-to-peak dose ratios of the MLC grids were found to be about 11% and 19% for the respective 10 mm x 10 mm and 5 mm X 5 mm grid openings, and those of the corresponding grid blocks were about 15% and 20%. To quantify the dose contributed by transmission in the blocked areas due to the limited leaf thickness, Monte Carlo simulations (based on convolution/superposition method) were performed to calculate the doses in the solid water phantom using an ideal MLC with no leakage and perfect divergence in both the leaf end and side. About 7% reduction in the valley-to-peak dose ratio was found for both grid sizes at dmax. The results clearly showed that MLCs can be used to provide grid treatments with at least as good dosimetric properties as those of the Cerrobend grid blocks, though the former would in general require a longer delivery time.

Dose Fractionation, Radiation↗

PubMed2006

An improved MLC segmentation algorithm and software for step-and-shoot IMRT delivery without tongue-and-groove error.

We present an improved multileaf collimator (MLC) segmentation algorithm, denoted by SLS(NOTG) (static leaf sequencing with no tongue-and-groove error), for step-and-shoot intensity-modulated radiation therapy (IMRT) delivery. SLS(NOTG) is an improvement over the MLC segmentation algorithm called SLS that was developed by Luan et al. [Med. Phys. 31(4), 695-707 (2004)], which did not consider tongue-and-groove error corrections. The aims of SLS(NOTG) are (1) shortening the treatment times of IMRT plans by minimizing their numbers of segments and (2) minimizing the tongue-and-groove errors of the computed IMRT plans. The input to SLS(NOTG) is intensity maps (IMs) produced by current planning systems, and its output is (modified) optimized leaf sequences without tongue-and-groove error. Like the previous SLS algorithm [Luan et al., Med. Phys. 31(4), 695-707 (2004)], SLS(NOTG) is also based on graph algorithmic techniques in computer science. It models the MLC segmentation problem as a weighted minimum-cost path problem, where the weight of the path is the number of segments and the cost of the path is the amount of tongue-and-groove error. Our comparisons of SLS(NOTG) with CORVUS indicated that for the same intensity maps, the numbers of segments computed by SLS(NOTG) are up to 50% less than those by CORVUS 5.0 on the Elekta LINAC system. Our clinical verifications have shown that the dose distributions of the SLS(NOTG) plans do not have tongue-and-groove error and match those of the corresponding CORVUS plans, thus confirming the correctness of SLS(NOTG). Comparing with existing segmentation methods, SLS(NOTG) also has two additional advantages: (1) SLS(NOTG) can compute leaf sequences whose tongue-and-groove error is minimized subject to a constraint on the maximum allowed number of segments, which may be desirable in clinical situations where a treatment with the complete correction of tongue-and-groove error takes too much time, and (2) SLS(NOTG) can be used to minimize a more general type of error called the tongue-or-groove error.

Algorithms↗

PubMed2005

Using a photon phase-space source for convolution/superposition dose calculations in radiation therapy.

For a given linac design, the dosimetric characteristics of a photon beam are determined uniquely by the energy and radial distributions of the electron beam striking the x-ray target. However, in the usual commissioning of a beam from measured data, a large number of variables can be independently tuned, making it difficult to derive a unique and self-consistent beam model. For example, the measured dosimetric penumbra in water may be attributed in various proportions to the lateral secondary electron range, the focal spot size and the transmission through the tips of a non-divergent collimator; the head-scatter component in the tails of the transverse profiles may not be easy to resolve from phantom scatter and head leakage; and the head-scatter tails corresponding to a certain extra-focal source model may not agree self-consistently with in-air output factors measured on the central axis. To reduce the number of adjustable variables in beam modelling, we replace the focal and extra-focal sources with a single phase-space plane scored just above the highest adjustable collimator in a EGS/BEAM simulation of the linac. The phase-space plane is then used as photon source in a stochastic convolution/superposition dose engine. A photon sampled from the uncollimated phase-space plane is first propagated through an arbitrary collimator arrangement and then interacted in the simulation phantom. Energy deposition kernel rays are then randomly issued from the interaction points and dose is deposited along these rays. The electrons in the phase-space file are used to account for electron contamination. 6 MV and 18 MV photon beams from an Elekta SL linac are used as representative examples. Except for small corrections for monitor backscatter and collimator forward scatter for large field sizes (<0.5% with <20 x 20 cm2 field size), we found that the use of a single phase-space photon source provides accurate and self-consistent results for both relative and absolute dose calculations.

Algorithms↗

PubMed2005

Real-time intra-fraction-motion tracking using the treatment couch: a feasibility study.

Significant differences between planned and delivered treatments may occur due to respiration-induced tumour motion, leading to underdosing of parts of the tumour and overdosing of parts of the surrounding critical structures. Existing methods proposed to counter tumour motion include breath-holds, gating and MLC-based tracking. Breath-holds and gating techniques increase treatment time considerably, whereas MLC-based tracking is limited to two dimensions. We present an alternative solution in which a robotic couch moves in real time in response to organ motion. To demonstrate proof-of-principle, we constructed a miniature adaptive couch model consisting of two movable platforms that simulate tumour motion and couch motion, respectively. These platforms were connected via an electronic feedback loop so that the bottom platform responded to the motion of the top platform. We tested our model with a seven-field step-and-shoot delivery case in which we performed three film-based experiments: (1) static geometry, (2) phantom-only motion and (3) phantom motion with simulated couch motion. Our measurements demonstrate that the miniature couch was able to compensate for phantom motion to the extent that the dose distributions were practically indistinguishable from those in static geometry. Motivated by this initial success, we investigated a real-time couch compensation system consisting of a stereoscopic infra-red camera system interfaced to a robotic couch known as the Hexapod, which responds in real time to any change in position detected by the cameras. Optical reflectors placed on a solid water phantom were used as surrogates for motion. We tested the effectiveness of couch-based motion compensation for fixed fields and a dynamic arc delivery cases. Due to hardware limitations, we performed film-based experiments (1), (2) and (3), with the robotic couch at a phantom motion period and dose rate of 16 s and 100 MU min(-1), respectively. Analysis of film measurements showed near-equivalent dose distributions (<or=2 mm agreement of corresponding isodose lines) for static geometry and motion-synchronized real-time robotic couch tracking-based radiation delivery.

Computer Systems↗

PubMed2005

A stochastic convolution/superposition method with isocenter sampling to evaluate intrafraction motion effects in IMRT.

Current methods to calculate dose distributions with organ motion can be broadly classified as "dose convolution" and "fluence convolution" methods. In the former, a static dose distribution is convolved with the probability distribution function (PDF) that characterizes the motion. However, artifacts are produced near the surface and around inhomogeneities because the method assumes shift invariance. Fluence convolution avoids these artifacts by convolving the PDF with the incident fluence instead of the patient dose. In this paper we present an alternative method that improves the accuracy, generality as well as the speed of dose calculation with organ motion. The algorithm starts by sampling an isocenter point from a parametrically defined space curve corresponding to the patient-specific motion trajectory. Then a photon is sampled in the linac head and propagated through the three-dimensional (3-D) collimator structure corresponding to a particular MLC segment chosen randomly from the planned IMRT leaf sequence. The photon is then made to interact at a point in the CT-based simulation phantom. Randomly sampled monoenergetic kernel rays issued from this point are then made to deposit energy in the voxels. Our method explicitly accounts for MLC-specific effects (spectral hardening, tongue-and-groove, head scatter) as well as changes in SSD with isocentric displacement, assuming that the body moves rigidly with the isocenter. Since the positions are randomly sampled from a continuum, there is no motion discretization, and the computation takes no more time than a static calculation. To validate our method, we obtained ten separate film measurements of an IMRT plan delivered on a phantom moving sinusoidally, with each fraction starting with a random phase. For 2 cm motion amplitude, we found that a ten-fraction average of the film measurements gave an agreement with the calculated infinite fraction average to within 2 mm in the isodose curves. The results also corroborate the existing notion that the interfraction dose variability due to the interplay between the MLC motion and breathing motion averages out over typical multifraction treatments. Simulation with motion waveforms more representative of real breathing indicate that the motion can produce penumbral spreading asymmetric about the static dose distributions. Such calculations can help a clinician decide to use, for example, a larger margin in the superior direction than in the inferior direction. In the paper we demonstrate that a 15 min run on a single CPU can readily illustrate the effect of a patient-specific breathing waveform, and can guide the physician in making informed decisions about margin expansion and dose escalation.

Algorithms↗

PubMed2004

Benchmark of PENELOPE code for low-energy photon transport: dose comparisons with MCNP4 and EGS4.

The expanding clinical use of low-energy photon emitting 125I and 103Pd seeds in recent years has led to renewed interest in their dosimetric properties. Numerous papers pointed out that higher accuracy could be obtained in Monte Carlo simulations by utilizing newer libraries for the low-energy photon cross-sections, such as XCOM and EPDL97. The recently developed PENELOPE 2001 Monte Carlo code is user friendly and incorporates photon cross-section data from the EPDL97. The code has been verified for clinical dosimetry of high-energy electron and photon beams, but has not yet been tested at low energies. In the present work, we have benchmarked the PENELOPE code for 10-150 keV photons. We computed radial dose distributions from 0 to 10 cm in water at photon energies of 10-150 keV using both PENELOPE and MCNP4C with either DLC-146 or DLC-200 cross-section libraries, assuming a point source located at the centre of a 30 cm diameter and 20 cm length cylinder. Throughout the energy range of simulated photons (except for 10 keV), PENELOPE agreed within statistical uncertainties (at worst +/- 5%) with MCNP/DLC-146 in the entire region of 1-10 cm and with published EGS4 data up to 5 cm. The dose at 1 cm (or dose rate constant) of PENELOPE agreed with MCNP/DLC-146 and EGS4 data within approximately +/- 2% in the range of 20-150 keV, while MCNP/DLC-200 produced values up to 9% lower in the range of 20-100 keV than PENELOPE or the other codes. However, the differences among the four datasets became negligible above 100 keV.

Benchmarking↗

PubMed2004

A new MLC segmentation algorithm/software for step-and-shoot IMRT delivery.

We present a new MLC segmentation algorithm/software for step-and-shoot IMRT delivery. Our aim in this work is to shorten the treatment time by minimizing the number of segments. Our new segmentation algorithm, called SLS (an abbreviation for static leaf sequencing), is based on graph algorithmic techniques in computer science. It takes advantage of the geometry of intensity maps. In our SLS approach, intensity maps are viewed as three-dimensional (3-D) "mountains" made of unit-sized "cubes." Such a 3-D "mountain" is first partitioned into special-structured submountains using a new mixed partitioning scheme. Then the optimal leaf sequences for each submountain are computed by either a shortest-path algorithm or a maximum-flow algorithm based on graph models. The computations of SLS take only a few minutes. Our comparison studies of SLS with CORVUS (both the 4.0 and 5.0 versions) and with the Xia and Verhey segmentation methods on Elekta Linac systems showed substantial improvements. For instance, for a pancreatic case, SLS used only one-fifth of the number of segments required by CORVUS 4.0 to create the same intensity maps, and the SLS sequences took only 25 min to deliver on an Elekta SL 20 Linac system in contrast to the 72 min for the CORVUS 4.0 sequences (a three-fold improvement). To verify the accuracy of our new leaf sequences, we conducted film and ion-chamber measurements on phantom. The results showed that both the intensity distributions as well as dose distributions of the SLS delivery match well with those of CORVUS delivery. SLS can also be extended to other types of Linac systems.

Algorithms↗

PubMed2003

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.

Humans↗

PubMed2003

Convolution/superposition using the Monte Carlo method.

The convolution/superposition calculations for radiotherapy dose distributions are traditionally performed by convolving polyenergetic energy deposition kernels with TERMA (total energy released per unit mass) precomputed in each voxel of the irradiated phantom. We propose an alternative method in which the TERMA calculation is replaced by random sampling of photon energy, direction and interaction point. Then, a direction is randomly sampled from the angular distribution of the monoenergetic kernel corresponding to the photon energy. The kernel ray is propagated across the phantom, and energy is deposited in each voxel traversed. An important advantage of the explicit sampling of energy is that spectral changes with depth are automatically accounted for. No spectral or kernel hardening corrections are needed. Furthermore, the continuous sampling of photon direction allows us to model sharp changes in fluence, such as those due to collimator tongue-and-groove. The use of explicit photon direction also facilitates modelling of situations where a given voxel is traversed by photons from many directions. Extra-focal radiation, for instance, can therefore be modelled accurately. Our method also allows efficient calculation of a multi-segment/multi-beam IMRT plan by sampling of beam angles and field segments according to their relative weights. For instance, an IMRT plan consisting of seven 14 x 12 cm2 beams with a total of 300 field segments can be computed in 15 min on a single CPU, with 2% statistical fluctuations at the isocentre of the patient's CT phantom divided into 4 x 4 x 4 mm3 voxels. The calculation contains all aperture-specific effects, such as tongue and groove, leaf curvature and head scatter. This contrasts with deterministic methods in which each segment is given equal importance, and the time taken scales with the number of segments. Thus, the Monte Carlo superposition provides a simple, accurate and efficient method for complex radiotherapy dose calculations.

Algorithms↗