Biomedical subjects

Daniel L McShan

Publications and source records attributed to Daniel L McShan.

18 recordsLinked to original sources

PubMed2006

Reporting and analyzing statistical uncertainties in Monte Carlo-based treatment planning.

PURPOSE: To investigate methods of reporting and analyzing statistical uncertainties in doses to targets and normal tissues in Monte Carlo (MC)-based treatment planning. METHODS AND MATERIALS: Methods for quantifying statistical uncertainties in dose, such as uncertainty specification to specific dose points, or to volume-based regions, were analyzed in MC-based treatment planning for 5 lung cancer patients. The effect of statistical uncertainties on target and normal tissue dose indices was evaluated. The concept of uncertainty volume histograms for targets and organs at risk was examined, along with its utility, in conjunction with dose volume histograms, in assessing the acceptability of the statistical precision in dose distributions. The uncertainty evaluation tools were extended to four-dimensional planning for application on multiple instances of the patient geometry. All calculations were performed using the Dose Planning Method MC code. RESULTS: For targets, generalized equivalent uniform doses and mean target doses converged at 150 million simulated histories, corresponding to relative uncertainties of less than 2% in the mean target doses. For the normal lung tissue (a volume-effect organ), mean lung dose and normal tissue complication probability converged at 150 million histories despite the large range in the relative organ uncertainty volume histograms. For "serial" normal tissues such as the spinal cord, large fluctuations exist in point dose relative uncertainties. CONCLUSIONS: The tools presented here provide useful means for evaluating statistical precision in MC-based dose distributions. Tradeoffs between uncertainties in doses to targets, volume-effect organs, and "serial" normal tissues must be considered carefully in determining acceptable levels of statistical precision in MC-computed dose distributions.

Esophagus↗

PubMed2005

Monte Carlo-based lung cancer treatment planning incorporating PET-defined target volumes.

Despite the well-known benefits of positron emission tomography (PET) imaging in lung cancer diagnosis and staging, the poor spatial resolution of PET has limited its use in radiotherapy planning. Methods used for segmenting tumor from normal tissue, such as threshold boundaries using a fraction of the standardized uptake value (SUV), are subject to uncertainties. The issue of respiratory motion in the thorax confounds the problem of accurate target definition. In this work, we evaluate how changing the PET-defined target volume by varying the threshold value in the segmentation process impacts target and normal lung tissue doses. For each of eight lung cancer patients we retrospectively generated multiple PET-target volumes; each target volume corresponds to those voxels with intensities above a given threshold level, defined by a percentage of the maximum voxel intensity. PET-defined targets were compared to those from CT; CT targets comprise a composite volume generated from breath-hold inhale and exhale datasets; the CT dataset therefore also includes the extents of tumor motion. Treatment plans using Monte Carlo dose calculation were generated for all targets; the dose uniformity was approximately 100+/-5% within the internal target volume (ITV) (formed by a uniform 8-mm expansion of the composite gross target volume (GTV)). In all cases differences were observed in the generalized equivalent uniform doses (gEUDs) to the targets and in the mean lung doses (MLDs) and normal tissue complication probabilities (NTCPs) to the normal lung tissues. The magnitudes of the dose differences were found to depend on the target volume, location, and amount of irradiated normal lung tissue, and in many instances were clinically meaningful (greater than a single 2 Gy fraction). For those patients studied, results indicate that accurate dosimetry using PET volumes is highly dependent on accurate target segmentation. Further study with correlation to clinical outcome will be helpful in determining how to apply these various PET and CT volumes in treatment planning, to potentially improve local tumor control and reduce normal tissue toxicities.

Algorithms↗

PubMed2005

Evaluating the influence of setup uncertainties on treatment planning for focal liver tumors.

PURPOSE: A mechanism has been developed to evaluate the influence of random setup variations on dose during treatment planning. The information available for studying these factors shifts from population-based models toward patient-specific data as treatment progresses and setup measurements for an individual patient become available. This study evaluates the influence of population as well as patient-specific setup distributions on treatment plans for focal liver tumors. METHODS AND MATERIALS: Eight patients with focal liver tumors were treated on a protocol that involved online setup measurement and adjustment, as well as ventilatory immobilization. Summary statistics from these three-dimensional conformal treatments yielded individual and population distributions of position at initial setup for each fraction. A convolution model for evaluation of the influence of random setup variation on calculated dose distributions has been previously described and investigated for application to focal liver radiotherapy by our department. Individual patient doses based on initial setup positions were calculated by convolving the calculated dose distribution with an anisotropic probability distribution function representing the individual patient's random variations. A separate convolution using population-averaged random variations was performed. Individual beam apertures were then adjusted to provide plans that ensured proper dose to the clinical target volume following convolution with population distributions, as well as individual patient position uncertainty models. RESULTS: Individual patient setup distributions for the course of treatment had random setup variations (sigma) that ranged from 2.5 to 5.7 mm (left-right), 2.1 to 8.3 mm (anterior-posterior), and 4.1 to 10.8 mm (cranial-caudal). The population random components were 4.2 mm (left-right), 4.1 mm (anterior-posterior), and 7.0 mm (cranial-caudal) at initial setup. The initial static planned dose distribution overestimated the volume of liver irradiated to high doses, because inclusion of setup uncertainties generally blurred the resulting doses, shifting the higher-dose region of normal liver dose-volume histograms to lower doses. Furthermore, the population-based dose convolution tended to predict a higher risk of radiation damage to the liver (based on an in-house parameterization of the Lyman normal tissue complication probability model) than the individual patient calculations. For an individual plan, application of different individual random variations yielded change in effective volume differences with a 3% range. Plan adjustment to account for random setup variations generally resulted in a lower change in effective volume than initial planning using a planning target volume followed by calculation of delivered dose based on random offsets. CONCLUSION: This study hints at the factors that most strongly influence planning of liver treatments taking into account geometric variations. Given a setup verification methodology that rapidly reduces systematic offsets, the importance of realistic incorporation of geometric variations as an initial step in treatment planning, as well as possible plan refinement, is demonstrated.

Feasibility Studies↗

PubMed2005

The influence of beam model differences in the comparison of dose calculation algorithms for lung cancer treatment planning.

In this study, we show that beam model differences play an important role in the comparison of does calculated with various algorithms for lung cancer treatment planning. These differences may impact the accurate correlation of dose with clinical outcome. To accomplish this, we modified the beam model penumbral parameters in an equivalent path length (EPL) algorithm and subsequently compared the EPL doses with those generated with Monte Carlo (MC). A single AP beam was used for beam fitting. Two different beam models were generated for EPL calculations: (1) initial beam model (init_fit) and (2) optimized beam model (best_fit) , with parameters optimized to produce the best agreement with MC calculated profiles at several depths in a water phantom. For the 6 MV, AP beam, EPL(init_fit) calculations were on average within 2%/2 mm (1.4 mm max.) agreement with MC; the agreement for EPL(best_fit) was 2%/1.0 mm (1.3 mm max.) for EPL(best_fit). Treatment planning was performed using a realistic lung phantom using 6 and 15 MV photons. In all homogeneous phantom plans, EPL(best_fit) calculations were in better agreement with MC. In the heterogeneous 6 MV plan, differences between EPL(best_fit and init_fit) and MC were significant for the tumour. The EPL(init_fit), unlike the EPL(best_fit) calculation, showed large differences in the lung relative to MC. For the 15 MV heterogeneous plan, clinically important differences were found between EPL(best_fit or init_fit) and MC for tumour and lung, suggesting that the algorithmic difference in inhomogeneous cases, differences between EPL(best_fit) and MC for lung tissues were smaller compared to those between EPL(init_fit) and MC. Although the extent to which beam model differences impact the dose comparisons will be dependent upon beam parameters (orientation, field size and energy), and the size and location of the tumour, this study shows that failing to correctly account for beam model differences will lead to biased comparisons between dose algorithms. This may ultimately hinder our ability to accurately correlate dose with clinical outcome.

Algorithms↗

PubMed2005

Dose reconstruction in deforming lung anatomy: dose grid size effects and clinical implications.

In this study we investigated the accumulation of dose to a deforming anatomy (such as lung) based on voxel tracking and by using time weighting factors derived from a breathing probability distribution function (p.d.f.). A mutual information registration scheme (using thin-plate spline warping) provided a transformation that allows the tracking of points between exhale and inhale treatment planning datasets (and/or intermediate state scans). The dose distributions were computed at the same resolution on each dataset using the Dose Planning Method (DPM) Monte Carlo code. Two accumulation/interpolation approaches were assessed. The first maps exhale dose grid points onto the inhale scan, estimates the doses at the "tracked" locations by trilinear interpolation and scores the accumulated doses (via the p.d.f.) on the original exhale data set. In the second approach, the "volume" associated with each exhale dose grid point (exhale dose voxel) is first subdivided into octants, the center of each octant is mapped to locations on the inhale dose grid and doses are estimated by trilinear interpolation. The octant doses are then averaged to form the inhale voxel dose and scored at the original exhale dose grid point location. Differences between the interpolation schemes are voxel size and tissue density dependent, but in general appear primarily only in regions with steep dose gradients (e.g., penumbra). Their magnitude (small regions of few percent differences) is less than the alterations in dose due to positional and shape changes from breathing in the first place. Thus, for sufficiently small dose grid point spacing, and relative to organ motion and deformation, differences due solely to the interpolation are unlikely to result in clinically significant differences to volume-based evaluation metrics such as mean lung dose (MLD) and tumor equivalent uniform dose (gEUD). The overall effects of deformation vary among patients. They depend on the tumor location, field size, volume expansion, tissue heterogeneity, and direction of tumor displacement with respect to the beam, and are more likely to have an impact on serial organs (such as esophagus), rather than on large parallel organs (such as lung).

Body Burden↗

PubMed2004

Accounting for center-of-mass target motion using convolution methods in Monte Carlo-based dose calculations of the lung.

We have applied convolution methods to account for some of the effects of respiratory induced motion in clinical treatment planning of the lung. The 3-D displacement of the GTV center-of-mass (COM) as determined from breath-hold exhale and inhale CT scans was used to approximate the breathing induced motion. The time-course of the GTV-COM was estimated using a probability distribution function (PDF) previously derived from diaphragmatic motion [Med. Phys. 26, 715-720 (1990)] but also used by others for treatment planning in the lung [Int. J. Radiat. Oncol., Biol., Phys. 53, 822-834 (2002); Med. Phys. 30, 1086-1095 (2003)]. We have implemented fluence and dose convolution methods within a Monte Carlo based dose calculation system with the intent of comparing these approaches for planning in the lung. All treatment plans in this study have been calculated with Monte Carlo using the breath-hold exhale CT data sets. An analysis of treatment plans for 3 patients showed substantial differences (hot and cold spots consistently greater than +/- 15%) between the motion convolved and static treatment plans. As fluence convolution accounts for the spatial variance of the dose distribution in the presence of tissue inhomogeneities, the doses were approximately 5% greater than those calculated with dose convolution in the vicinity of the lung. DVH differences between the static, fluence and dose convolved distributions for the CTV were relatively small, however, larger differences were observed for the PTV. An investigation of the effect of the breathing PDF asymmetry on the motion convolved dose distributions showed that reducing the asymmetry resulted in increased hot and cold spots in the motion convolved distributions relative to the static cases. In particular, changing from an asymmetric breathing function to one that is symmetric results in an increase in the hot/cold spots of +/- 15% relative to the static plan. This increase is not unexpected considering that the target spends relatively more time at inhale as the asymmetry decreases (note that the treatment plans were generated using the exhale CT scans).

Body Burden↗

PubMed2004

Mutual information based CT registration of the lung at exhale and inhale breathing states using thin-plate splines.

The advent of dynamic radiotherapy modeling and treatment techniques requires an infrastructure to weigh the merits of various interventions (breath holding, gating, tracking). The creation of treatment planning models that account for motion and deformation can allow the relative worth of such techniques to be evaluated. In order to develop a treatment planning model of a moving and deforming organ such as the lung, registration tools that account for deformation are required. We tested the accuracy of a mutual information based image registration tool using thin-plate splines driven by the selection of control points and iterative alignment according to a simplex algorithm. Eleven patients each had sequential CT scans at breath-held normal inhale and exhale states. The exhale right lung was segmented from CT and served as the reference model. For each patient, thirty control points were used to align the inhale CT right lung to the exhale CT right lung. Alignment accuracy (the standard deviation of the difference in the actual and predicted inhale position) was determined from locations of vascular and bronchial bifurcations, and found to be 1.7, 3.1, and 3.6 mm about the RL, AP, and IS directions. The alignment accuracy was significantly different from the amount of measured movement during breathing only in the AP and IS directions. The accuracy of alignment including thin-plate splines was more accurate than using affine transformations and the same iteration and scoring methodology. This technique shows promise for the future development of dynamic models of the lung for use in four-dimensional (4-D) treatment planning.

Algorithms↗

PubMed2003

Alterations in normal liver doses due to organ motion.

PURPOSE: To assess the clinical significance of differences between treatment planning calculations based on static computed tomography (CT) and more realistic predictions of the actual delivered dose to intrahepatic lesions by a geometric convolution approach that accounts for random setup variations and breathing-induced organ motion. MATERIALS AND METHODS: We recalculated target and normal liver doses for 40 patients previously treated on a conformal therapy dose escalation protocol to include the effect of setup uncertainties and liver motion due to patient breathing. Initial three-dimensional (3D) dose calculations based on pretreatment CT scans taken with voluntary breath-hold at normal exhalation were convolved with 3D anisotropic probability distribution functions reflecting population measurements of position setup variation. The convolution also included a distribution function (one-dimensional, inferior-superior direction only) representing the asymmetric temporal pattern (biased toward exhalation, based on population measurements) of a typical breathing cycle, scaled in amplitude for each patient. RESULTS: After convolution, the minimum clinical target volume (CTV) dose met or exceeded the minimum planning target volume (PTV) dose from the static plan in all but one case, indicating adequate PTV design. However, clinically relevant and statistically significant increases (decreases) in liver normal tissue complication probability (NTCP) from values computed for the static cases occurred for tumors located toward the bottom (top) of the liver, as predicted for these patients scanned at exhalation. The change in liver NTCP (from a nominal 20%) ranged from +12.0% to -11.7% (average magnitude change 3.9% [sigma = 3.3%]). Changes in prescription dose required to restore the original 20% NTCP ranged from -3.7 Gy to +7.9 Gy (average magnitude change 1.9 Gy [sigma = 1.9 Gy]). CONCLUSIONS: Although the PTV concept can ensure adequate CTV coverage, the doses to normal liver are incorrectly modeled without including patient-related geometric uncertainties.

Algorithms↗

PubMed2003

Potential gains for irradiation of chest wall and regional nodes with intensity modulated radiotherapy.

PURPOSE: To develop an intensity modulated radiotherapy (IMRT) technique for postmastectomy RT that improves target coverage while sparing all appropriate normal tissues. MATERIALS AND METHODS: IMRT plans were generated using an in-house optimization system. Priority was given to matching the heart doses achieved with partially wide tangent fields (PWTFs) while maintaining 50 Gy +/- 5% to the chest wall, internal mammary nodes, and supraclavicular nodes. Other normal tissue doses were then minimized. Metrics for plan comparisons included minimal, maximal, and mean doses and normal tissue complication probability. RESULTS: IMRT resulted in more uniform chest wall coverage than did PWTFs. The average chest wall minimal dose was 43.7 +/- 1.1 Gy for IMRT and 31.2 +/- 16.5 Gy for PWTFs (p = 0.04). The average internal mammary node minimal dose was 42.8 +/- 2.1 Gy for IMRT and 21.8 +/- 13.2 Gy for PWTFs (p = 0.001). IMRT matched the <1% heart normal tissue complication probability achieved using PWTFs. The average contralateral breast mean dose was 2.8 +/- 1.7 Gy for IMRT, but a greater breast volume was exposed compared with PWTFs. The mean ipsilateral lung normal tissue complication probability was lower for IMRT (0.0) than for PWTFs (0.07 +/- 0.07; p = 0.02). The mean contralateral lung dose was greater for IMRT (5.8 +/- 1.8 Gy) than for PWTFs (1.6 +/- 0.1 Gy; p = <0.0001). CONCLUSION: A new IMRT technique achieves full target coverage while maintaining similar doses to heart and ipsilateral lung as conventional techniques. However, contralateral lung and breast volumes exposed to low doses were increased with IMRT and will need to be reduced in future studies.

Breast Neoplasms↗

PubMed2003

Photon beam relative dose validation of the DPM Monte Carlo code in lung-equivalent media.

Validation experiments have been conducted using 6 and 15 MV photons in inhomogeneous (water/lung/water) media to benchmark the accuracy of the DPM Monte Carlo code for photon beam dose calculations. Small field sizes (down to 2 x 2 cm2) and low-density media were chosen for this investigation because the intent was to test the DPM code under conditions where lateral electronic disequilibrium effects are emphasized. The treatment head components of a Varian 21EX linear accelerator, including the jaws (defining field sizes of 2 x 2, 3 x 3 and 10 x 10 cm2), were simulated using the BEAMnrc code. The phase space files were integrated within the DPM code system, and central axis depth dose and profile calculations were compared against diode measurements in a homogeneous water phantom in order to validate the phase space. Results of the homogeneous phantom study indicated that the relative differences between DPM calculations and measurements were within +/- 1% (based on the rms deviation) for the depth dose curves; relative profile dose differences were on average within +/- 1%/1 mm. Depth dose and profile measurements were carried out using an ion-chamber and film, within an inhomogeneous phantom consisting of a 6 cm slab of lung-equivalent material embedded within solid water. For the inhomogeneous phantom experiment, DPM depth dose calculations were within +/- 1% (based on the rms deviation) of measurements; relative profile differences at depths within and beyond the lung were, on average, within +/- 2% in the inner and outer beam regions, and within 1-2 mm distance-to-agreement within the penumbral region. Relative point differences on the order of 2-3% were within the estimated experimental uncertainties. This work demonstrates that the DPM Monte Carlo code is capable of accurate photon beam dose calculations in situations where lateral electron disequilibrium effects are pronounced.

Algorithms↗

PubMed2003

A fluence convolution method to account for respiratory motion in three-dimensional dose calculations of the liver: a Monte Carlo study.

We describe the implementation of a fluence convolution method to account for the influence of superior-inferior (SI) respiratory induced motion on a Monte Carlo-based dose calculation of a tumor located in the liver. This method involves convolving the static fluence map with a function describing the SI motion of the liver-the motion function has been previously derived from measurements of diaphragm movement observed under fluoroscopy. Significant differences are noted between fluence-convolved and static dose distributions in an example clinical treatment plan; hot and cold spots (on the order of 25%) are observed in the fluence-convolved plan at the superior and inferior borders of the liver, respectively. This study illustrates that the fluence convolution method can be incorporated into Monte Carlo dose calculation algorithms to account for some of the effects of patient breathing during radiotherapy treatment planning, thus leading to more accurate dose calculations.

Algorithms↗

PubMed2002

Experimental validation of the DPM Monte Carlo code using minimally scattered electron beams in heterogeneous media.

A comprehensive set of measurements and calculations has been conducted to investigate the accuracy of the Dose Planning Method (DPM) Monte Carlo code for electron beam dose calculations in heterogeneous media. Measurements were made using 10 MeV and 50 MeV minimally scattered, uncollimated electron beams from a racetrack microtron. Source distributions for the Monte Carlo calculations were reconstructed from in-air ion chamber scans and then benchmarked against measurements in a homogeneous water phantom. The in-air spatial distributions were found to have FWHM of 4.7 cm and 1.3 cm, at 100 cm from the source, for the 10 MeV and 50 MeV beams respectively. Energy spectra for the electron beams were determined by simulating the components of the microtron treatment head using the code MCNP4B. Profile measurements were made using an ion chamber in a water phantom with slabs of lung or bone-equivalent materials submerged at various depths. DPM calculations are, on average, within 2% agreement with measurement for all geometries except for the 50 MeV incident on a 6 cm lung-equivalent slab. Measurements using approximately monoenergetic, 50 MeV, 'pencil-beam'-type electrons in heterogeneous media provide conditions for maximum electronic disequilibrium and hence present a stringent test of the code's electron transport physics; the agreement noted between calculation and measurement illustrates that the DPM code is capable of accurate dose calculation even under such conditions.

Electrons↗

PubMed2002

Daily prostate targeting using implanted radiopaque markers.

PURPOSE: A system has been implemented for daily localization of the prostate through radiographic localization of implanted markers. This report summarizes an initial trial to establish the accuracy of patient setup via this system. METHODS AND MATERIALS: Before radiotherapy, three radiopaque markers are implanted in the prostate periphery. Reference positions are established from CT data. Before treatment, orthogonal radiographs are acquired. Projected marker positions are extracted semiautomatically from the radiographs and aligned to the reference positions. Computer-controlled couch adjustment is performed, followed by acquisition of a second pair of radiographs to verify prostate position. Ten patients (6 prone, 4 supine) participated in a trial of daily positioning. RESULTS: Three hundred seventy-four fractions were treated using this system. Treatment times were on the order of 30 minutes. Initial prostate position errors (sigma) ranged from 3.1 to 5.8 mm left-right, 4.0 to 10.1 mm anterior-posterior, and 2.6 to 9.0 mm inferior-superior in prone patients. Initial position was more reproducible in supine patients, with errors of 2.8 to 5.0 mm left-right, 1.9 to 3.0 mm anterior-posterior, and 2.6 to 5.3 mm inferior-superior. After prostate localization and adjustment, the position errors were reduced to 1.3 to 3.5 mm left-right, 1.7 to 4.2 mm anterior-posterior, and 1.6 to 4.0 mm inferior-superior in prone patients, and 1.2 to 1.8 mm left-right, 0.9 to 1.8 mm anterior-posterior, and 0.8 to 1.5 mm inferior-superior in supine patients. CONCLUSIONS: Daily targeting of the prostate has been shown to be technically feasible. The implemented system provides the ability to significantly reduce treatment margins for most patients with cancer confined to the prostate. The differences in final position accuracy between prone and supine patients suggest variations in intratreatment prostate movement related to mechanisms of patient positioning.

Dose Fractionation, Radiation↗

PubMed2002

Daily targeting of intrahepatic tumors for radiotherapy.

INTRODUCTION: A system has been developed for daily targeting of intrahepatic tumors using a combination of ventilatory immobilization, in-room diagnostic imaging, and on-line setup adjustment. By reducing geometric position uncertainty, as well as organ movement, this system permits reduction of margins and thus potentially higher treatment doses. This paper reports our initial experience treating 8 patients with focal liver tumors using this system. METHODS AND MATERIALS: The system includes diagnostic X-ray tubes mounted on the wall and ceiling of a treatment room, an active matrix flat panel imager, in-room control for image acquisition and setup adjustment, and a ventilatory immobilization system via active breathing control (ABC). Eight patients participated in the study, two using an early prototype ABC unit, and the remaining six with a commercial ABC system and improved setup measurement tools. Treatment margins were reduced, and dose consequently increased because of increased confidence in target position under this protocol. After daily setup via skin marks, orthogonal radiographs were acquired at suspended ventilation. The images were aligned to the CT model using the diaphragm for inferior-superior (IS) alignment, and the skeleton for left-right (LR) and anterior-posterior (AP) alignment. Adjustments were made for positioning errors greater than a threshold (3 or 5 mm). After treatment, retrospective analysis determined the final setup accuracy, as well as the error in initial setup measurement performed before setup adjustment. RESULTS: Two hundred sixty-two treatment fractions were delivered on eight patients, with 171 treatments requiring repositioning. Typical treatment times were 25-30 min. Patients were able to tolerate ABC throughout the course of treatment. Breath holds up to 35 s long were used for treatment. The use of on-line imaging and setup adjustment reduced setup errors (sigma) from 4.0 mm (LR), 6.7 mm (IS), and 3.8 mm (AP) to 2.1 mm (LR), 3.5 mm (IS), and 2.3 mm (AP). Prescribed doses were increased using this system by an average of 5 Gy. CONCLUSIONS: Daily targeting of intrahepatic targets has been demonstrated to be feasible. The potential for reduction in treatment margin and consequential safe dose escalation has been demonstrated, while maintaining reasonable treatment delivery times.

Dose Fractionation, Radiation↗

PubMed2002

Reduction of rectal dose by integration of the boost in the large-field treatment plan for prostate irradiation.

PURPOSE: To reduce the dose in the rectal wall from prostate irradiation at high dose levels. METHODS AND MATERIALS: Treatment plans in which the boost fields were integrated into the large fields (simultaneous integrated boost [SIB]) were compared with plans in which the large fields and boost fields were planned individually and applied in a sequential manner (sequential boost). Two target volumes were delineated: PTV1, the target volume of the large fields that is irradiated to 68 Gy, and PTV2, the target volume of the boost fields that is irradiated to 10 Gy. The sequential boost and the SIB were normalized to the mean dose in PTV2, being 78 Gy. We used a five-field intensity-modulated radiotherapy (IMRT) technique, applied in a step and shoot mode, and included beam weight optimization. A set of 5 patients with varying degree of overlap between PTV1 and the rectal wall was used for analysis. RESULTS: The SIB resulted in a reduction of the dose in the rectal wall. Rectal normal tissue complication probability (NTCP) decreased for the SIB, on average, by a factor of almost 2, compared with the sequential boost. CONCLUSION: The SIB reduced the dose in the rectal wall, compared with the sequential boost technique.

Adenocarcinoma↗

PubMed2002

Optimizing radiation treatment plans for lung cancer using lung perfusion information.

PURPOSE: To study the impact of incorporation of lung perfusion information in the optimization of radical radiotherapy (RT) treatment plans for patients with medically inoperable non-small cell lung cancer (NSCLC). MATERIALS AND METHODS: The treatment plans for a virtual phantom and for five NSCLC patients with typical defects of pre-RT lung perfusion were optimized to minimize geometrically determined parameters as the mean lung dose (MLD), the lung volume receiving more than 20 Gy (V20), and the functional equivalent of the MLD, using perfusion-weighted dose-volume histograms. For the patients the (perfusion-weighted) optimized plans were compared to the clinically applied treatment plans. RESULTS: The feasibility of perfusion-weighted optimization was demonstrated in the phantom. Using perfusion information resulted in an increase of the weights of those beams that were directed through the hypo-perfused lung regions both for the phantom and for the studied patients. The automatically optimized dose distributions were improved with respect to lung toxicity compared with the clinical treatment plans. For patients with one hypo-perfused hemi-thorax, the estimated gain in post-RT lung perfusion was 6% of the prescribed dose compared to the geometrically optimized plan. For patients with smaller perfusion defects, perfusion-weighted optimization resulted in the same plan as the geometrically optimized plan. CONCLUSION: Perfusion-weighted optimization resulted in clinically well applicable treatment plans, which cause less radiation damage to functioning lung for patients with large perfusion defects.

Carcinoma, Non-Small-Cell Lung↗

PubMed2002

Benchmarking of the dose planning method (DPM) Monte Carlo code using electron beams from a racetrack microtron.

A comprehensive set of measurements and calculations has been conducted to investigate the accuracy of the Dose Planning Method (DPM) Monte Carlo code for dose calculations from 10 and 50 MeV scanned electron beams produced from a racetrack microtron. Central axis depth dose measurements and a series of profile scans at various depths were acquired in a water phantom using a Scanditronix type RK ion chamber. Source spatial distributions for the Monte Carlo calculations were reconstructed from in-air ion chamber measurements carried out across the two-dimensional beam profile at 100 cm downstream from the source. The in-air spatial distributions were found to have full width at half maximum of 4.7 and 1.3 cm, at 100 cm from the source, for the 10 and 50 MeV beams, respectively. Energy spectra for the 10 and 50 MeV beams were determined by simulating the components of the microtron treatment head using the code MCNP4B. DPM calculations are on average within +/- 2% agreement with measurement for all depth dose and profile comparisons conducted in this study. The accuracy of the DPM code illustrated in this work suggests that DPM may be used as a valuable tool for electron beam dose calculations.

Algorithms↗

PubMed2002

A comparison of computer-controlled versus manual on-line patient setup adjustment.

A study was performed to determine the relative advantage of computer-controlled couch movement versus manual repositioning to correct patient setup error measured using an electronic portal imaging device (EPID). Twenty-eight on-line setup adjustment trials of anterior-posterior (AP) pelvic projections were evaluated, with 13 setups corrected by automated couch movement determined by direct feedback from the EPID image alignment tool and 15 setups manually corrected based on the transformation displayed from the same tool. The speed of setup adjustment and accuracy of corrected setup were determined. Computer controlled setup adjustment was determined to be faster (25.4 s versus 101.9 s) and slightly more accurate (1.8 mm versus 2.5 mm error in adjusted setup) than manual correction.

Humans↗