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Thomas R Mackie

Publications and source records attributed to Thomas R Mackie.

At least 19 recordsLinked to original sources
PubMed2005

Imaging dose management using multi-resolution in CT-guided radiation therapy.

In image-guided radiation therapy, megavoltage computerized tomography (MVCT) delivers higher dose to the patient for lower image quality than diagnostic kilovoltage CT (kVCT). One way to reduce the mean imaging dose is to reduce the imaging volume, which is often sufficient for registration and dosimetry purposes. The filtered back projection using truncated data causes artefacts that degrade the image quality. Those artefacts can be effectively reduced by wavelet-based multi-resolution analysis (WMRA), in which the detail and approximate information are reconstructed separately to bypass the non-locality of filtered back projection. In this study, WMRA was used to reconstruct local images from both very low-dose kVCT scans from a bench-top tomotherapy unit and MVCT scans from helical tomotherapy. Results show that mean imaging dose can be significantly reduced by imaging a small region of interest. In simulation, the root-mean-square error brought by the truncation is smaller than 1-2% and depends on the level of dose reduction. On the other hand, the same mean dose that would have been delivered by a low-quality global CT can be conformed to a smaller volume to improve the visibility of low-contrast organs and fine structures using WMRA. Organs at risk can be avoided during repeated daily CT imaging when irregular-shaped reconstruction areas are used. WMRA does not involve computationally expensive iterations and is suitable for image-guided radiation therapy where imaging speed is essential. Compared with extrapolation methods, errors are further reduced to improve the detection of low contrast and fine structures.

Algorithms↗
PubMed2005

Accurate convolution/superposition for multi-resolution dose calculation using cumulative tabulated kernels.

Convolution/superposition (C/S) is regarded as the standard dose calculation method in most modern radiotherapy treatment planning systems. Different implementations of C/S could result in significantly different dose distributions. This paper addresses two major implementation issues associated with collapsed cone C/S: one is how to utilize the tabulated kernels instead of analytical parametrizations and the other is how to deal with voxel size effects. Three methods that utilize the tabulated kernels are presented in this paper. These methods differ in the effective kernels used: the differential kernel (DK), the cumulative kernel (CK) or the cumulative-cumulative kernel (CCK). They result in slightly different computation times but significantly different voxel size effects. Both simulated and real multi-resolution dose calculations are presented. For simulation tests, we use arbitrary kernels and various voxel sizes with a homogeneous phantom, and assume forward energy transportation only. Simulations with voxel size up to 1 cm show that the CCK algorithm has errors within 0.1% of the maximum gold standard dose. Real dose calculations use a heterogeneous slab phantom, both the 'broad' (5 x 5 cm2) and the 'narrow' (1.2 x 1.2 cm2) tomotherapy beams. Various voxel sizes (0.5 mm, 1 mm, 2 mm, 4 mm and 8 mm) are used for dose calculations. The results show that all three algorithms have negligible difference (0.1%) for the dose calculation in the fine resolution (0.5 mm voxels). But differences become significant when the voxel size increases. As for the DK or CK algorithm in the broad (narrow) beam dose calculation, the dose differences between the 0.5 mm voxels and the voxels up to 8 mm (4 mm) are around 10% (7%) of the maximum dose. As for the broad (narrow) beam dose calculation using the CCK algorithm, the dose differences between the 0.5 mm voxels and the voxels up to 8 mm (4 mm) are around 1% of the maximum dose. Among all three methods, the CCK algorithm is demonstrated to be the most accurate one for multi-resolution dose calculations.

Algorithms↗
PubMed2005

Motion-encoded dose calculation through fluence/sinogram modification.

Conventional radiotherapy treatment planning systems rely on a static computed tomography (CT) image for planning and evaluation. Intra/inter-fraction patient motions may result in significant differences between the planned and the delivered dose. In this paper, we develop a method to incorporate the knowledge of intra/inter-fraction patient motion directly into the dose calculation. By decomposing the motion into a parallel (to beam direction) component and perpendicular (to beam direction) component, we show that the motion effects can be accounted for by simply modifying the fluence distribution (sinogram). After such modification, dose calculation is the same as those based on a static planning image. This method is superior to the "dose-convolution" method because it is not based on "shift invariant" assumption. Therefore, it deals with material heterogeneity and surface curvature very well. We test our method using extensive simulations, which include four phantoms, four motion patterns, and three plan beams. We compare our method with the "dose-convolution" and the "stochastic simulation" methods (gold standard). As for the homogeneous flat surface phantom, our method has similar accuracy as the "dose-convolution" method. As for all other phantoms, our method outperforms the "dose-convolution." The maximum motion encoded dose calculation error using our method is within 4% of the gold standard. It is shown that a treatment planning system that is based on "motion-encoded dose calculation" can incorporate random and systematic motion errors in a very simple fashion. Under this approximation, in principle, a planning target volume definition is not required, since it already accounts for the intra/inter-fraction motion variations and it automatically optimizes the cumulative dose rather than the single fraction dose.

Algorithms↗
PubMed2005

Dose calibration of nonconventional treatment systems applied to helical tomotherapy.

Current dosimetric protocols based on the absorbed dose (AAPM TG-51 and IAEA TRS-398 protocols) require calibration measurements under reference conditions. For some radiotherapy systems, this requirement cannot be met, and calibration has to be performed under nonreference experimental conditions. In order to solve this problem, both protocols can be extended by inclusion of the measured-to-reference conversion factor, k(mr). In order to determine this factor, basic dosimetric quantities, like stopping power ratios, mass attenuation coefficients and chamber correction factors have to be calculated. If measurements are not feasible, accurate Monte Carlo modeling is required. The extension of the protocols is illustrated using the case of the helical tomotherapy radiation unit, where the typical calibration measurement conditions are the 10 x 5 cm2 field size and the 85 cm surface source distance, limited by the system design. It was calculated that the k(mr) factor for this conditions is close to unity (0.997+/-0.001). In addition, the deviation of the measurement conditions from the reference conditions results in the change of the quality conversion factor (approximately 0.995-0.998, depending on the ionization chamber used). This change is the same regardless of the used calibration protocol. For smaller field sizes the corrections become more significant, resulting in the total correction factor compared to the reference conditions of up to 1.5% for the smallest considered field size of 2 x 2 cm2.

Algorithms↗
PubMed2004

Fast free-form deformable registration via calculus of variations.

In this paper, we present a fully automatic, fast and accurate deformable registration technique. This technique deals with free-form deformation. It minimizes an energy functional that combines both similarity and smoothness measures. By using calculus of variations, the minimization problem was represented as a set of nonlinear elliptic partial differential equations (PDEs). A Gauss-Seidel finite difference scheme is used to iteratively solve the PDE. The registration is refined by a multi-resolution approach. The whole process is fully automatic. It takes less than 3 min to register two three-dimensional (3D) image sets of size 256 x 256 x 61 using a single 933 MHz personal computer. Extensive experiments are presented. These experiments include simulations, phantom studies and clinical image studies. Experimental results show that our model and algorithm are suited for registration of temporal images of a deformable body. The registration of inspiration and expiration phases of the lung images shows that the method is able to deal with large deformations. When applied to the daily CT images of a prostate patient, the results show that registration based on iterative refinement of displacement field is appropriate to describe the local deformations in the prostate and the rectum. Similarity measures improved significantly after the registration. The target application of this paper is for radiotherapy treatment planning and evaluation that incorporates internal organ deformation throughout the course of radiation therapy. The registration method could also be equally applied in diagnostic radiology.

Algorithms↗
PubMed2004

Fast treatment plan modification with an over-relaxed Cimmino algorithm.

A method to quickly modify a treatment plan in adaptive radiotherapy was proposed and studied. The method is based on a Cimmino-type algorithm in linear programming. The fast convergence speed is achieved by over-relaxing the algorithm relaxation parameter from its sufficient convergence range of (0, 2) to (0, infinity). The algorithm parameters are selected so that the over-relaxed Cimmino (ORC) algorithm can effectively approximate an unconstrained re-optimization process in adaptive radiotherapy. To demonstrate the effectiveness and flexibility of the proposed method in adaptive radiotherapy, two scenarios with different organ motion/deformation of one nasopharyngeal case were presented with comparisons made between this method and the re-optimization method. In both scenarios, the ORC algorithm modified treatment plans have dose distributions that are similar to those given by the re-optimized treatment plans. It takes us using the ORC algorithm to finish a treatment plan modification at least three times faster than the re-optimization procedure compared.

Algorithms↗
PubMed2004

Radiation characteristics of helical tomotherapy.

Helical tomotherapy is a dedicated intensity modulated radiation therapy (IMRT) system with on-board imaging capability (MVCT) and therefore differs from conventional treatment units. Different design goals resulted in some distinctive radiation field characteristics. The most significant differences in the design are the lack of flattening filter, increased shielding of the collimators, treatment and imaging operation modes and narrow fan beam delivery. Radiation characteristics of the helical tomotherapy system, sensitivity studies of various incident electron beam parameters and radiation safety analyses are presented here. It was determined that the photon beam energy spectrum of helical tomotherapy is similar to that of more conventional radiation treatment units. The two operational modes of the system result in different nominal energies of the incident electron beam with approximately 6 MeV and 3.5 MeV in the treatment and imaging modes, respectively. The off-axis mean energy dependence is much lower than in conventional radiotherapy units with less than 5% variation across the field, which is the consequence of the absent flattening filter. For the same reason the transverse profile exhibits the characteristic conical shape resulting in a 2-fold increase of the beam intensity in the center. The radiation leakage outside the field was found to be negligible at less than 0.05% because of the increased shielding of the collimators. At this level the in-field scattering is a dominant source of the radiation outside the field and thus a narrow field treatment does not result in the increased leakage. The sensitivity studies showed increased sensitivity on the incident electron position because of the narrow fan beam delivery and high sensitivity on the incident electron energy, as common to other treatment systems. All in all, it was determined that helical tomotherapy is a system with some unique radiation characteristics, which have been to a large extent optimized for intensity modulated delivery.

Electrons↗
PubMed2004

Treatment plan optimization incorporating respiratory motion.

Similar to conventional conformal radiotherapy, during lung tomotherapy, a motion margin has to be set for respiratory motion. Consequently, large volume of normal tissue is irradiated by intensive radiation. To solve this problem, we have developed a new motion mitigation method by incorporating target motion into treatment optimization. In this method, the delivery-breathing correlation is determined prior to treatment plan optimization. Beamlets are calculated by using the CT images at the corresponding breathing phases from a dynamic (four-dimensional) image sequence. With the displacement vector fields at different breathing phases, a set of deformed beamlets is obtained by mapping the dose to the primary phase. Optimization incorporating motion is then performed by using the deformed beamlets obtained by dose mapping. During treatment delivery, the same breathing-delivery correlation can be reproduced by instructing the patient to breathe following a visually displayed guiding cycle. This method was tested using a computer-simulated deformable phantom and a real lung case. Results show that treatment optimization incorporating motion achieved similar high dose conformality on a mobile target compared with static delivery. The residual motion effects due to imperfect breathing tracking were also analyzed.

Biophysical Phenomena↗
PubMed2004

Helical tomotherapy as a means of delivering accelerated partial breast irradiation.

A novel treatment approach utilizing helical tomotherapy for partial breast irradiation for patients with early-stage breast cancer is described. This technique may serve as an alternative to high dose-rate (HDR) interstitial brachytherapy and standard linac-based approaches. Through helical tomotherapy, highly conformal irradiation of target volumes and avoidance of normal sensitive structures can be achieved. Unlike HDR brachytherapy, it is noninvasive. Unlike other linac-based techniques, it provides image-guided adaptive radiotherapy along with intensity modulation. A treatment planning CT scan was obtained as usual on a post-lumpectomy patient undergoing HDR interstitial breast brachytherapy. The patient underwent catheter placement for HDR treatment and was positioned prone on a specially designed position-supporting mattress during CT. The planning target volume (PTV) was defined as the lumpectomy bed plus a 20 mm margin. The prescription dose was 34 Gy (10 fx of 3.4 Gy) in both the CT based HDR and on the tomotherapy plan. Cumulative dose-volume histograms (DVHs) were generated and analyzed for the target, lung, heart, skin, pectoralis muscle, and chest wall for both HDR brachytherapy and helical tomotherapy. Dosimetric coverage of the target with helical tomotherapy was conformal and homogeneous. "Hot spots" (> or =150% isodose line) were present around implanted dwell positions in brachytherapy plan whereas no isodose lines higher than 109% were present in the helical tomotherapy plan. Similar dose coverage was achieved for lung, pectoralis muscle, heart, chest wall and breast skin with the two methods. We also compared our results to that obtained using conventional linac-based three dimensional (3D) conformal accelerated partial breast irradiation. Dose homogeneity is excellent with 3D conformal irradiation, and lung, heart and chest wall dose is less than for either HDR brachytherapy or helical tomotherapy but skin and pectoral muscle doses were higher than with the other techniques. Our results suggest that helical tomotherapy can serve as an effective means of delivering accelerated partial breast irradiation and may offer superior dose homogeneity compared to HDR brachytherapy.

Brachytherapy↗
PubMed2004

Megavoltage computed tomography imaging: a potential tool to guide and improve the delivery of thoracic radiation therapy.

Helical tomotherapy is an innovative means of delivering intensity-modulated radiation therapy (IMRT) using a device that merges features of a linear accelerator and a helical computed tomography (CT) scanner. The tomotherapy unit can generate CT images from the megavoltage radiation it uses for treatment as often as needed during a course of radiation therapy. These megavoltage CT (MVCT) images offer verification of patient position prior to and potentially during radiation therapy, and provide considerably more anatomical detail than the conventional radiation therapy port films used for patient set-up verification. Also, MVCT imaging may enable reconstruction of the radiation dose delivered, thereby providing unprecedented verification of the actual treatment. These key features of helical tomotherapy distinguish it from other IMRT approaches. We report results from a pilot feasibility trial of 10 patients with non-small-cell lung cancer (NSCLC) on whom we obtained MVCT images using a prototype helical tomotherapy system. All patients underwent conventional CT imaging for radiation therapy treatment planning. Specific aims were to subjectively compare MVCT and conventional CT images and then to objectively compare the 2 modalities by contouring tumors and performing a volumetric comparison. Seven patients had disease located primarily in the lung parenchyma, 2 primarily in the mediastinum, and 1 in both. When evaluated by location, all 7 patients with lesions primarily in the lung parenchyma had subjectively high-quality MVCT images. Objectively, the volumetric agreement between conventional and MVCT for parenchymal lesions was excellent in 5 of the 7 patients. Megavoltage CT imaging via the helical tomotherapy prototype provided adequate information for use in verification of patient position and dose reconstruction for lesions within the pulmonary parenchyma, but presently appears suboptimal for primarily mediastinal disease. Further studies are ongoing to optimize MVCT imaging and better define its utility in patients with NSCLC.

Carcinoma, Non-Small-Cell Lung↗
PubMed2003

Adaptive anisotropic diffusion filtering of Monte Carlo dose distributions.

The Monte Carlo method is the most accurate method for radiotherapy dose calculations, if used correctly. However, any Monte Carlo dose calculation is burdened with statistical noise. In this paper, denoising of Monte Carlo dose distributions with a three-dimensional adaptive anisotropic diffusion method was investigated. The standard anisotropic diffusion method was extended by changing the filtering parameters adaptively according to the local statistical noise. Smoothing of dose distributions with different noise levels in an inhomogeneous phantom, a conventional and an IMRT treatment case is shown. The resultant dose distributions were analysed using several evaluating criteria. It is shown that the adaptive anisotropic diffusion method can reduce statistical noise significantly (two to five times, corresponding to the reduction of simulation time by a factor of up to 20), while preserving important gradients of the dose distribution well. The choice of free parameters of the method was found to be fairly robust.

Anisotropy↗
PubMed2003

Optimizer convergence and local minima errors and their clinical importance.

Two of the errors common in the inverse treatment planning optimization have been investigated. The first error is the optimizer convergence error, which appears because of non-perfect convergence to the global or local solution, usually caused by a non-zero stopping criterion. The second error is the local minima error, which occurs when the objective function is not convex and/or the feasible solution space is not convex. The magnitude of the errors, their relative importance in comparison to other errors as well as their clinical significance in terms of tumour control probability (TCP) and normal tissue complication probability (NTCP) were investigated. Two inherently different optimizers, a stochastic simulated annealing and deterministic gradient method were compared on a clinical example. It was found that for typical optimization the optimizer convergence errors are rather small, especially compared to other convergence errors, e.g., convergence errors due to inaccuracy of the current dose calculation algorithms. This indicates that stopping criteria could often be relaxed leading into optimization speed-ups. The local minima errors were also found to be relatively small and typically in the range of the dose calculation convergence errors. Even for the cases where significantly higher objective function scores were obtained the local minima errors were not significantly higher. Clinical evaluation of the optimizer convergence error showed good correlation between the convergence of the clinical TCP or NTCP measures and convergence of the physical dose distribution. On the other hand, the local minima errors resulted in significantly different TCP or NTCP values (up to a factor of 2) indicating clinical importance of the local minima produced by physical optimization.

Algorithms↗
PubMed2003

Treatment plan modification using voxel-based weighting factors/dose prescription.

Under various clinical situations, it is desirable to modify the original treatment plan to better suit the clinical goals. In this work, a method to help physicians modify treatment plans based on their clinical preferences is proposed. The method uses a weighted quadratic dose objective function. The commonly used organ-/ROI-based weighting factors are expanded to a set of voxel-based weighting factors in order to obtain greater flexibility in treatment plan modification. Two different but equivalent modification schemes based on Rustem's quadratic programming algorithms--modification of a weighting matrix and modification of prescribed doses--are presented. Case studies demonstrated the effectiveness of the two methods with regard to their capability to fine-tune treatment plans.

Algorithms↗
PubMed2003

The method of intercepts in parameter space for the analysis of local minima caused by dose-volume constraints.

The local minima problem in radiotherapy optimization has been a concern for both researchers and physicians. In this work, local minima induced by dose-volume histogram (DVH) constraints are discussed. The non-convex property of the feasible set formed by DVH constraints is discussed in beam weight space. An intuitive explanation of the origin of this type of local minima is given by a two-beam model setup. Some interesting properties and insights about the DVH-induced local minima are found. Based on this, a heuristic non-random initial guess sampling method is proposed and applied to a clinical nasopharyngeal case, where some significantly different local minima are located.

Algorithms↗
PubMed2003

Application of the spirometer in respiratory gated radiotherapy.

The signal from a spirometer is directly correlated with respiratory motion and is ideal for target respiratory motion tracking. However, its susceptibility to signal drift deters its application in radiotherapy. In this work, a few approaches are investigated to control spirometer signal drift for a Bernoulli-type spirometer. A method is presented for rapid daily calibration of the spirometer to obtain a flow sensitivity function. Daily calibration assures accurate airflow measurement and also reduces signal drift. Dynamic baseline adjustment further controls the signal drift. The accuracy of these techniques was studied and it was found that the spirometer is able to provide a long-term drift-free breathing signal. The tracking error is comprised of two components: calibration error and stochastic signal baseline variation error. The calibration error is very small (1% of 3 l) and therefore negligible. The stochastic baseline variation error can be as large as 20% of the normal breathing amplitude. In view of these uncertainties, the applications of spirometers in treatment techniques that rely on breathing monitoring are discussed. Spirometer-based monitoring is noted most suitable for deep inspiration breath-hold but less important for free breathing gating techniques.

Calibration↗
PubMed2002

Re-optimization in adaptive radiotherapy.

In routine clinical practice, radiotherapy treatment planning is performed based on the patient CT images obtained during the patient setup procedure. However, the actual delivered dose to the patient might be different from the planned dose because of various reasons such as patient motion. Under such situations, it is desirable to modify the original treatment plan in order to partially remedy the dose delivery errors in the subsequent dose delivery process. Such modification can be implemented by modifying the original treatment plan using re-optimization. In this work, issues such as the re-optimization dose prescription, optimization constraints in re-optimization, re-optimization in multiple fractionation schemes and re-optimization procedure with generalized dose-based objective functions were investigated and corresponding mathematical schemes proposed. The derived results were applied to a clinical case study in which it was shown that the proposed re-optimization method is able to remedy the cold spots in tumour while delivering low dose to normal structures. Thus the potential effectiveness of the method was demonstrated.

Algorithms↗
PubMed2002

Tomographic motion detection and correction directly in sinogram space.

Patient motion, especially respiratory motion, results in various artefacts such as blurring and streaks in tomographic images. The interplay of the movement of the beam aperture and variations of organ anatomy during delivery can create 'hot' and 'cold' spots throughout the field in intensity-modulated radiation therapy (IMRT). Detection and correction of patient motion is extremely important in tomographic imaging and IMRT. Tomographic projection data (sinogram) encode not only the patient anatomy information, but also the intra-scanning motion information. In this paper, we developed an algorithm to detect and correct the in-plane respiratory motion directly in sinogram space. The respiratory motion is modelled as time-varying scaling along the x and y directions. Its effects on the sinogram are discussed. Based on the traces of some nodal points in the sinogram, the intra-scanning motion is determined. The motion correction is also implemented in sinogram space. The motion-corrected sinogram is used for reconstruction by the filtered back-projection (FBP) method. Computer simulations validate the motion detection and correction algorithm. The reconstructed images from the motion-corrected sinogram eliminate the majority of the artefacts. The method could be applied to projection data used in CT and ECT, as well as in tomotherapy delivery modification and dose reconstruction.

Computer Simulation↗