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Results for “Optimization”

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PubMed2001

Individually optimizing posterior tibial somatosensory evoked potential P37 scalp derivations for intraoperative monitoring.

This investigation sought the optimal (highest amplitude) derivation for monitoring the posterior tibial P37 for each side in each individual, and determined whether this may change intraoperatively. Fifty monitored patients were studied using a partial P37 map consisting of FPz, Fz, Cz, Cz', Pz, POz, C4', and C3' to a noncephalic reference. From this, the highest amplitude scalp derivation was determined for each side. Of 100 tibial nerves, the initial optimal input 1 was Cz' in 52%, Pz in 28%, and Cz or iC' in 10%, and optimal input 2 was cC' in 69% and FPz in 31%. The optimal derivation was the same for each side in 34% of patients and different in 66%. Of 31 patients with at least one subsequent trial later during surgery, P37 topography changed in 14 and affected optimal inputs in 12. This occurred regularly during sitting-position posterior fossa surgery because of intracranial air, but sometimes occurred during other surgeries as well. The most common change consisted of FPz replacing cC' as optimal input 2. Input 1 changes were predominantly in an anterior or posterior sagittal direction. The results demonstrate great inter- and intraindividual P37 variability, and document intraoperative topographic changes. Both phenomena can be addressed by a practical method to refine intraoperative monitoring by individually optimizing scalp derivations and identifying topographic P37 changes during surgery.

Evoked Potentials, Somatosensory↗

PubMed2001

Optimized protocols in terms of equalizing the true and accidental coincidences of each bed position in static multiple bed position carbon-11 PET studies and a target single bed position study.

Quantitative carbon-11 (11C) positron emission tomography (PET) is gaining more attention in oncological applications. In addition, it was discovered that accidental coincidences (randoms) can play an important role in studies such as partial volume effects correction without needing to use anatomical information. However, because of the short half-life of 11C, a homogeneous multiple bed position 11C image is hard to obtain. This study aimed to determine whether innovative pseudogating, optimized pseudogating and optimized double-up methods could match the true counts and randoms to each bed position and to a target single bed position study. A long cylindrical phantom filled with [11C]acetate was scanned by a dedicated PET scanner using six protocols: whole body, frame-duration-compensated whole body, double-up, optimized double-up, pseudogating, and optimized pseudogating. The differences between the protocols are in the initial activity, frame duration and frame number for each bed position. The parameters for pseudogating were determined according to the theory that true counts and randoms are proportional to the radioactivity and its square, respectively. The results show that the stated goals could only be achieved by pseudogating and optimized pseudogating. We conclude that pseudogating or optimized pseudogating must be applied for a critical quantitative study. However, optimized double-up and double-up methods are good alternatives for semi-quantitative and qualitative studies, respectively.

Algorithms↗

PubMed2004

Interbody fusion cage design using integrated global layout and local microstructure topology optimization.

STUDY DESIGN: An approach combining global layout and local microstructure topology optimization was used to create a new interbody fusion cage design that concurrently enhanced stability, biofactor delivery, and mechanical tissue stimulation for improved arthrodesis. OBJECTIVE: To develop a new interbody fusion cage design by topology optimization with porous internal architecture. To compare the performance of this new design to conventional threaded cage designs regarding early stability and long-term stress shielding effects on ingrown bone. SUMMARY OF BACKGROUND DATA: Conventional interbody cage designs mainly fall into categories of cylindrical or rectangular shell shapes. The designs contribute to rigid stability and maintain disc height for successful arthrodesis but may also suffer mechanically mediated failures of dislocation or subsidence, as well as the possibility of bone resorption. The new optimization approach created a cage having designed microstructure that achieved desired mechanical performance while providing interconnected channels for biofactor delivery. METHODS: The topology optimization algorithm determines the material layout under desirable volume fraction (50%) and displacement constraints favorable to bone formation. A local microstructural topology optimization method was used to generate periodic microstructures for porous isotropic materials. Final topology was generated by the integration of the two-scaled structures according to segmented regions and the corresponding material density. Image-base finite element analysis was used to compare the mechanical performance of the topology-optimized cage and conventional threaded cage. RESULTS: The final design can be fabricated by a variety of Solid Free-Form systems directly from the image output. The new design exhibited a narrower, more uniform displacement range than the threaded cage design and lower stress at the cage-vertebra interface, suggesting a reduced risk of subsidence. Strain energy density analysis also indicated that a higher portion of total strain energy density was transferred into the new bone region inside the new designed cage, indicating a reduced risk of stress shielding. CONCLUSION: The new design approach using integrated topology optimization demonstrated comparable or better stability by limited displacement and reduced localized deformation related to the risk of subsidence. Less shielding of newly formed bone was predicted inside the new designed cage. Using the present approach, it is also possible to tailor cage design for specific materials, either titanium or polymer, that can attain the desired balance between stability, reduced stress shielding, and porosity for biofactor delivery.

Algorithms↗

PubMed2005

How optimal life history changes with the community size-spectrum.

This paper derives optimal life histories for fishes or other animals in relation to the size spectrum of the ecological community in which they are both predators and prey. Assuming log-linear size-spectra and well known scaling laws for feeding and mortality, we first construct the energetics of the individual. From these we find, using dynamic programming, the optimal allocation of energy between growth and reproduction as well as the trade-off between offspring size and numbers. Optimal strategies were found to be strongly dependent on size spectrum slope. For steep size spectra (numbers declining rapidly with size), determinate growth was optimal and allocation to somatic growth increased rapidly with increasing slope. However, restricting reproduction to a fixed mating season changed optimal allocations to give indeterminate growth approximating a von Bertalanffy trajectory. The optimal offspring size was as small as possible given other restrictions such as newborn starvation mortality. For shallow size spectra, finite optimal maturity size required a decline in fitness for large size or age. All the results are compared with observed size spectra of fish communities to show their consistency and relevance.

Animals↗

PubMed2000

Optimal periodic orbits of continuous time chaotic systems

In previous work [B. R. Hunt and E. Ott, Phys. Rev. Lett. 76, 2254 (1996); Phys. Rev. E 54, 328, (1996)], based on numerical experiments and analysis, it was conjectured that the optimal orbit selected from all possible orbits on a chaotic attractor is "typically" a periodic orbit of low period. By an optimal orbit we mean the orbit that yields the largest value of a time average of a given smooth "performance" function of the system state. Thus optimality is defined with respect to the given performance function. (The study of optimal orbits is of interest in at least three contexts: controlling chaos, embedding of low-dimensional attractors of high-dimensional dynamical systems in low-dimensional measurement spaces, and bubbling bifurcations of synchronized chaotic systems.) Here we extend this previous work. In particular, the previous work was for discrete time dynamical systems, and here we shall consider continuous time systems (flows). An essential difference for flows is that chaotic attractors can have embedded within them, not only unstable periodic orbits, but also unstable steady states, and we find that optimality can often occur on steady states. We also shed further light on the sense in which optimality is "typically" achieved at low period. In particular, we find that, as a system parameter is tuned to be closer to a crisis of the chaotic attractor, optimality may occur at higher period.

Journal Article↗

PubMed2003

Optimal noise-aided signal transmission through populations of neurons.

Metabolic considerations and neurophysiological measurements indicate that biological neural systems prefer information transmission via many parallel low intensity channels, compared to few high intensity ones [S. B. Laughlin et al., Nature Neurosci. 1, 36 (1998)]. Furthermore, cortical neurons are exposed to a considerable amount of synaptic background activity, which increases the neurons' conductance and leads to a fluctuating membrane potential that, on average, is close to the threshold [A. Destexhe and D. Paré, J. Neurophysiol. 81, 1531 (1999)]. Recent studies have shown that noise can improve the transmission of subthreshold signals in populations of neurons, e.g., if their response is pooled. In general, the optimal noise level depends on the stimulus distribution and on the number of neurons in the population. In this contribution we show that for a large enough number of neurons the latter dependency becomes weak, such that the optimal noise level becomes almost independent of the number of neurons in the population. First we investigate a binary threshold model of neurons. We derive an analytic expression for the optimal noise level at each single neuron, which-for a large enough population size-depends only on quantities that are locally available to a single neuron. Using numerical simulations, we then verify the weak dependence of the optimal noise level on population size in a more realistic framework using leaky integrate-and-fire as well as Hodgkin-Huxley-type model neurons. Next we construct a cost function, where quality of information transmission is traded against its metabolic costs. Again we find that-for subthreshold signals-there is an optimal noise level which maximizes this cost. This noise level, however, is almost independent of the number of neurons, even for small population sizes, as numerical simulations using the Hodgkin-Huxley model show. Since the dependence of the optimal noise level on population size is weak for large enough populations, local neural adaptation is sufficient to adjust the level of noise to its optimal value.

Animals↗

PubMed1996

Optimal head related transfer functions for hearing and monaural localization in elevation: a signal processing design perspective.

Localization of sound sources by human listeners has been widely studied and theories and various models of the localization and hearing mechanism have been constructed. In the classical "duplex" theory, sound localization in azimuth is explained by interaural time or equivalently, phase differences at low frequencies, and by interaural amplitude differences at higher frequencies. Head related transfer functions (HRTF's) present a linear system approach to modeling localization by representing the direction-dependent transformation the sound undergoes at each ear. Localization in elevation is explained by directional differences in the HRTF's, which also explains monaural localization. We conjecture that the HRTF's evolved during the course of nature (due to the evolution of the shape and structure of the ear etc.) are optimal with respect to several physically realizable criteria. In this paper, we investigate the problem of defining the design constraints which when optimized yield a set of HRTF's for hearing and monaural vertical localization in an attempt to better understand, and if possible, duplicate nature's design. We pursue an engineer's design perspective and formulate a constrained optimization problem, where the desired set of HRTF's is optimized according to a cost function based on several criteria for localization, hearing and smoothness, and also by imposing physically realizable constraints on the HRTF's such as nonnegativity, energy etc. The value of the cost function for a candidate set of HRTF's is an indication of the similarity of that set of HRTF's with respect to the ideal solution (measured HRTF data). The final optimization results we present are similar to the actual HRTF's measured in human subjects, and the associated cost function values are found to be almost equal. This points to the fact that the optimization criteria defined are quite relevant. The significant outcome of this research is the identification of a relevant set of mathematical criteria that could be optimized in the human auditory system to facilitate good hearing and localization. These criteria along with the associated constraints represent the desirable characteristics of the HRTF's in an HRTF-based localization system, and could lead to a better understanding and modeling of the auditory system.

Algorithms↗

PubMed2006

Optimization of partition-based Weighted Sum filters and their application to image denoising.

Partition-based Weighted Sum (P-WS) filtering is an effective method for processing nonstationary signals, especially those with regularly occurring structures, such as images. P-WS filters were originally formulated as Hard-partition Weighted Sum (HP-WS) filters and were successfully applied to image denoising. This formulation relied on intuitive arguments to generate the filter class. Here we present a statistical analysis that justifies the use of weighted sum filters after observation space partitioning. Unfortunately, the HP-WS filters are nondifferentiable and an analytical solution for their global optimization is therefore difficult to obtain. A two-stage suboptimal training procedure has been reported in the literature, but prior to this research no evaluation on the optimality of this approach has been reported. Here, a Genetic Algorithm (GA) HP-WS optimization procedure is developed that, in simulations, shows that the simpler two-stage training procedure yields near optimal results. Also developed in this paper are Soft-partition Weighted Sum (SP-WS) filters. The SP-WS filters utilize soft, or fuzzy, partitions that yield a differentiable filtering operation, enabling the development of gradient-based optimization procedures. Image denoising simulation results are presented comparing HP-WS and SP-WS filters, their optimization procedures, and wavelet-based image denoising. These results show that P-WS filters, in general, outperform traditional and wavelet-based image filters, and SP-WS filters utilizing soft partitioning not only allow for simple optimization, but also yields improved performance.

Algorithms↗

PubMed2004

Trajectory priming with dynamic fuzzy networks in nonlinear optimal control.

Fuzzy logic systems have been recognized as a robust and attractive alternative to some classical control methods. The application of classical fuzzy logic (FL) technology to dynamic system control has been constrained by the nondynamic nature of popular FL architectures. Many difficulties include large rule bases (i.e., curse of dimensionality), long training times, etc. These problems can be overcome with a dynamic fuzzy network (DFN), a network with unconstrained connectivity and dynamic fuzzy processing units called "feurons." In this study, DFN as an optimal control trajectory priming system is considered as a nonlinear optimization with dynamic equality constraints. The overall algorithm operates as an autotrainer for DFN (a self-learning structure) and generates optimal feed-forward control trajectories in a significantly smaller number of iterations. For this, DFN encapsulates and generalizes the optimal control trajectories. By the algorithm, the time-varying optimal feedback gains are also generated along the trajectory as byproducts. This structure assists the speeding up of trajectory calculations for intelligent nonlinear optimal control. For this purpose, the direct-descent-curvature algorithm is used with some modifications [called modified-descend-controller (MDC) algorithm] for the nonlinear optimal control computations. The algorithm has numerically generated robust solutions with respect to conjugate points. The minimization of an integral quadratic cost functional subject to dynamic equality constraints (which is DFN) is considered for trajectory obtained by MDC tracking applications. The adjoint theory (whose computational complexity is significantly less than direct method) has been used in the training of DFN, which is as a quasilinear dynamic system. The updating of weights (identification of DFN parameters) are based on Broyden-Fletcher-Goldfarb-Shanno (BFGS) method. Simulation results are given for controlling a difficult nonlinear second-order system using fully connected three-feuron DFN.

Fuzzy Logic↗

PubMed2004

The hyper-cube framework for ant colony optimization.

Ant colony optimization is a metaheuristic approach belonging to the class of model-based search algorithms. In this paper, we propose a new framework for implementing ant colony optimization algorithms called the hyper-cube framework for ant colony optimization. In contrast to the usual way of implementing ant colony optimization algorithms, this framework limits the pheromone values to the interval [0,1]. This is obtained by introducing changes in the pheromone value update rule. These changes can in general be applied to any pheromone value update rule used in ant colony optimization. We discuss the benefits coming with this new framework. The benefits are twofold. On the theoretical side, the new framework allows us to prove that in Ant System, the ancestor of all ant colony optimization algorithms, the average quality of the solutions produced increases in expectation over time when applied to unconstrained problems. On the practical side, the new framework automatically handles the scaling of the objective function values. We experimentally show that this leads on average to a more robust behavior of ant colony optimization algorithms.

Algorithms↗

PubMed2000

Hemodynamically optimized temporary cardiac pacing after surgery for congenital heart defects.

Disturbance of normal AV synchrony and dyssynchronous ventricular contraction may be deleterious in patients with otherwise compromised hemodynamics. This study evaluated the effect of hemodynamically optimized temporary dual chamber pacing in patients after surgery for congenital heart disease. Pacing was performed in 23 children aged 5 days to 7.7 years (median 7.3 months) with various postoperative dysrhythmias, low cardiac output, and/or high inotropic support and optimized to achieve the highest systolic and mean arterial pressures. The following four pacing modes were used: (1) AV synchronous or AV sequential pacing with individually optimized AV delay in 11 patients with first- to third-degree AV block; (2) AV sequential pacing using transesophageal atrial pacing in combination with a temporary DDD pacemaker for atrial tracking and ventricular pacing in three patients with third-degree AV block and junctional ectopic tachycardia, respectively, who had poor signal and exit block on atrial epicardial pacing wires; (3) R wave synchronized atrial pacing in eight patients with junctional ectopic tachycardia and impaired antegrade AV conduction precluding the use of atrial overdrive pacing; (4) Atrio-biventricular sequential pacing in two patients. Pressures measured during optimized pacing were compared to baseline values at underlying rhythm (13 patients with first-degree AV block or junctional ectopic tachycardia) or during pacing modes commonly used in the given clinical situation: AAI pacing (1 patient with slow junctional rhythm and first-degree AV block during atrial pacing), VVI pacing (2 patients with third-degree AV block and exit block and poor sensing on epicardial atrial pacing wires) and dual-chamber pacing with AV delays set to 100 ms (atrial tracking) or 150 ms (AV sequential pacing) in 7 patients with second- to third-degree AV block and functional atrial pacing wires. Optimized pacing led to a significant increase in arterial systolic (mean) pressure from 71.5 +/- 12.5 (52.3 +/- 9.0) to 80.5 +/- 12.2 (59.7 +/- 9.1) mmHg (P < 0.001 for both) and a decrease in central venous (left atrial) pressure from 12.3 +/- 3.4 (10.5 +/- 3.2) to 11.0 +/- 3.0 (9.2 +/- 2.7) mmHg (P < 0.001 and < 0.005, respectively). In conclusion, several techniques of individually optimized temporary dual chamber pacing leading to optimal AV synchrony and/or synchronous ventricular contraction were successfully used to improve hemodynamics in patients with heart failure and selected dysrhythmias after congenital heart surgery.

Arrhythmias, Cardiac↗

PubMed2002

Experimental optimization of pivot point height for swing-arm type rear suspensions in off-road bicycles.

Towards the ultimate goal of designing dual suspension off-road bicycles which decouple the suspension motion from the pedaling action, this study focused on determining experimentally the optimum pivot point height for a swing-arm type rear suspension such that the suspension motion was minimized. Specific objectives were (1) to determine the effect of interaction between the front and rear suspensions on the optimal pivot point height, (2) to investigate the sensitivity of the optimal height to the pedaling mechanics of the rider in both the seated and standing postures, (3) to determine the dependence of the optimal height on the rider posture. Eleven experienced subjects rode a custom-built adjustable dual suspension off-road bicycle, [Needle, S., and Hull, M. L., 1997, "An Off-Road Bicycle With Adjustable Suspension Kinematics," Journal of Mechanical Design 119, pp. 370-375], on an inclined treadmill. The treadmill was set to a constant 6 percent grade at a constant velocity of 24.8 km/hr. With the bicycle in a fixed gear combination of 38 x 14, the corresponding cadence was 84 rpm. For each subject, the pivot point height was varied randomly while the motions across both the front and rear suspension elements were measured. Subjects rode in both the seated and standing postures and with the front suspension active and inactive. It was found that the power loss from the rear suspension at the optimal pivot point height was not significantly dependent on the interaction between the front and rear suspensions. In the seated posture, the optimal pivot point height was 9.8 cm on average and had a range of 8.0-12.3 cm. The average optimal pivot point height for the seated posture corresponded to an average power loss for the rear suspension that was within 10 percent of the minimum power loss for each subject for 8 of the 11 subjects. In the standing posture, the average height was 5.9 cm and ranged from 5.1-7.2 cm. The average heightfor the standing posture was within 10 percent of the minimum power loss for each subject for 9 of the 11 subjects. While the optimum height was relatively insensitive to pedaling mechanics in both the seated and standing postures, the choice of the optimal pivot point height in production bicycles necessitates some compromise in performance given the disparity in the averages between the seated and standing postures.

Adult↗

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↗

PubMed2005

Feasibility of a fast inverse dose optimization algorithm for IMRT via matrix inversion without negative beamlet intensities.

A fast optimization algorithm is very important for inverse planning of intensity modulated radiation therapy (IMRT), and for adaptive radiotherapy of the future. Conventional numerical search algorithms such as the conjugate gradient search, with positive beam weight constraints, generally require numerous iterations and may produce suboptimal dose results due to trapping in local minima. A direct solution of the inverse problem using conventional quadratic objective functions without positive beam constraints is more efficient but will result in unrealistic negative beam weights. We present here a direct solution of the inverse problem that does not yield unphysical negative beam weights. The objective function for the optimization of a large number of beamlets is reformulated such that the optimization problem is reduced to a linear set of equations. The optimal set of intensities is found through a matrix inversion, and negative beamlet intensities are avoided without the need for externally imposed ad-hoc constraints. The method has been demonstrated with a test phantom and a few clinical radiotherapy cases, using primary dose calculations. We achieve highly conformal primary dose distributions with very rapid optimization times. Typical optimization times for a single anatomical slice (two dimensional) (head and neck) using a LAPACK matrix inversion routine in a single processor desktop computer, are: 0.03 s for 500 beamlets; 0.28 s for 1000 beamlets; 3.1 s for 2000 beamlets; and 12 s for 3000 beamlets. Clinical implementation will require the additional time of a one-time precomputation of scattered radiation for all beamlets, but will not impact the optimization speed. In conclusion, the new method provides a fast and robust technique to find a global minimum that yields excellent results for the inverse planning of IMRT.

Algorithms↗

PubMed2006

Continuous intensity map optimization (CIMO): a novel approach to leaf sequencing in step and shoot IMRT.

A new leaf-sequencing approach has been developed that is designed to reduce the number of required beam segments for step-and-shoot intensity modulated radiation therapy (IMRT). This approach to leaf sequencing is called continuous-intensity-map-optimization (CIMO). Using a simulated annealing algorithm, CIMO seeks to minimize differences between the optimized and sequenced intensity maps. Two distinguishing features of the CIMO algorithm are (1) CIMO does not require that each optimized intensity map be clustered into discrete levels and (2) CIMO is not rule-based but rather simultaneously optimizes both the aperture shapes and weights. To test the CIMO algorithm, ten IMRT patient cases were selected (four head-and-neck, two pancreas, two prostate, one brain, and one pelvis). For each case, the optimized intensity maps were extracted from the Pinnacle3 treatment planning system. The CIMO algorithm was applied, and the optimized aperture shapes and weights were loaded back into Pinnacle. A final dose calculation was performed using Pinnacle's convolution/superposition based dose calculation. On average, the CIMO algorithm provided a 54% reduction in the number of beam segments as compared with Pinnacle's leaf sequencer. The plans sequenced using the CIMO algorithm also provided improved target dose uniformity and a reduced discrepancy between the optimized and sequenced intensity maps. For ten clinical intensity maps, comparisons were performed between the CIMO algorithm and the power-of-two reduction algorithm of Xia and Verhey [Med. Phys. 25(8), 1424-1434 (1998)]. When the constraints of a Varian Millennium multileaf collimator were applied, the CIMO algorithm resulted in a 26% reduction in the number of segments. For an Elekta multileaf collimator, the CIMO algorithm resulted in a 67% reduction in the number of segments. An average leaf sequencing time of less than one minute per beam was observed.

Algorithms↗

PubMed2006

Improving IMRT dose accuracy via deliverable Monte Carlo optimization for the treatment of head and neck cancer patients.

The purpose of this work is to investigate the effect of dose-calculation accuracy on head and neck (H&N) intensity modulated radiation therapy (IMRT) plans by determining the systematic dose-prediction and optimization-convergence errors (DPEs and OCEs), using a superposition/convolution (SC) algorithm. Ten patients with locally advanced H&N squamous cell carcinoma who were treated with simultaneous integrated boost IMRT were selected for this study. The targets consisted of gross target volume (GTV), clinical target volume (CTV), and nodal target volumes (CTV nodes). The critical structures included spinal cord, parotid glands, and brainstem. For all patients, three IMRT plans were created: A: an SC optimized plan (SCopt), B: an SCopt plan recalculated with Monte Carlo [MC(SCopt)], and C: an MC optimized plan (MCopt). For each structure, DPEs and OCEs were estimated as DPE(SC)=D(B)-D(A) and OCE(SC)=D(C)-D(B) where A, B, and C stand for the three different optimized plans as defined above. Deliverable optimization was used for all plans, that is, a leaf-sequencing step was incorporated into the optimization loop at each iteration. The range of DPE(SC) in the GTV D98 varied from -1.9% to -4.9%, while the OCE(SC) ranged from 0.9% to 7.0%. The DPE(SC) in the contralateral parotid D50 reached 8.2%, while the OCE(SC) in the contralateral parotid D50 varied from 0.91% to 6.99%. The DPE(SC) in cord D2 reached -3.0%, while the OCE(SC) reached to -7.0%. The magnitude of the DPE(SC) and OCE(SC) differences demonstrate the importance of using the most accurate available algorithm in the deliverable IMRT optimization process, especially for the estimation of normal structure doses.

Algorithms↗

PubMed1994

Optimal radiographic magnification for portal imaging.

Two approaches to estimate the optimal radiographic magnification for a TV camera-based portal imaging system and portal films have been used. The first approach optimizes signal transfer while the second optimizes signal-to-noise ratio (SNR) transfer. In order to perform these optimization calculations, the physical characteristics of the imaging system (modulation transfer function and noise power spectrum) as well as the sizes of the radiation sources of our medical linear accelerators have been measured. Using these data, the optimal magnification considering signal transfer alone (M signal) has been calculated to range between 2.0 and 2.3 for the TV camera-based imaging system and is about 1.0 for portal films. Conversely, the optimal magnification considering SNR transfer (MSNR) has been calculated to range between 1.5 and 1.7 for the TV camera-based imaging system and is about 1.0 for portal films. The results suggest that most portal imaging systems are operated close to their optimal radiographic magnification.

Humans↗

PubMed1995

The influence of scatter on the design of optimized intensity modulations.

In contrast to the traditional treatment planning process where beam parameters are adjusted in order to produce a desired dose distribution, the inverse treatment planning technique starts from the desired dose distribution and employs mathematical inversion to derive a set of optimal intensity profiles for beams with predefined directions. Crucial to the success of the inverse technique is the mathematical inversion process that yields the optimized intensity modulation. This paper systematically investigates the influence of phantom scatter in the process of designing the optimized intensity modulation and assesses its clinical consequences through the resultant treatment plans. Optimized intensity modulations and the resultant dose distributions were calculated for four prostate patients and for a simple cubic phantom under two conditions: one includes scatter and the other ignores scatter in designing the optimized intensity modulation. The effects of scatter were assessed by comparing the isodose distributions, the dose-volume histograms of the target and of the critical organs, and the tumor control probabilities and the normal tissue complication probabilities of two set prostate treatment plans. The comparison reveals that the dose homogeneity to the target is significantly improved when scatter is included in the optimization process. For prostate patients, the dose to the volume enclosed by the outer rectal contour is concomitantly reduced. Our results suggest that it is important to include the scatter in the iterative design of the optimized intensity modulations.

Biophysical Phenomena↗