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PubMed1997

Decision theoretic steering and genetic algorithm optimization: application to stereotactic radiosurgery treatment planning.

Treatment planning for stereotactic radiosurgery and fractionated radiotherapy is currently a labor intensive, operator-dependent process. Many degrees of freedom exist to make rigorous optimization intractable except by computationally intelligent techniques. The quality of a given plan is determined by an aggregate of clinical objectives, most of which are subject to competing tradeoffs. In this work, we present an autonomous scheme that couples decision theoretic guidance with a genetic algorithm for optimization. Ordinal ranking among a population of viable treatment plans is based on a generalized distance metric, which promotes a decreasing hyperfrontier of the efficient solution set. The solution set is driven toward efficiency by the genetic algorithm, which uses the tournament selection mechanism based on the ordinal ranking. Goals and satisficing conditions can be defined to signal the ultimate and the minimum achievement levels in a given objective. A conventionally challenging case in radiosurgery was used to demonstrate the practical utility and the problem-solving power of the decision theoretic genetic algorithm. Treatment plans with one isocenter and four isocenters were derived under the autonomous scheme and compared to the actual treatment plan manually optimized by the expert planner. Quality assessment based on dose-volume histograms and normal tissue complication probabilities suggested that computational optimization could be driven to offer varying degrees of dosimetric improvement over a human-guided optimization effort. Furthermore, it was possible to achieve a high degree of isodose conformity to the target volume in computational optimization by increasing the degree of freedom in the treatment parameters. The time taken to derive an efficient planning solution was comparable and usually shorter than in the manual planning process, and can be scaled down almost linearly with the number of processors. Overall, the autonomous genetic algorithm scheme was found to be powerful and versatile as a computationally intelligent counterpart to human-guided strategies in treatment optimization for stereotactic radiosurgery and radiotherapy.

Algorithms↗

PubMed1999

Estimation theory and model parameter selection for therapeutic treatment plan optimization.

Treatment optimization is usually formulated as an inverse problem, which starts with a prescribed dose distribution and obtains an optimized solution under the guidance of an objective function. The solution is a compromise between the conflicting requirements of the target and sensitive structures. In this paper, the treatment plan optimization is formulated as an estimation problem of a discrete and possibly nonconvex system. The concept of preference function is introduced. Instead of prescribing a dose to a structure (or a set of voxels), the approach prioritizes the doses with different preference levels and reduces the problem into selecting a solution with a suitable estimator. The preference function provides a foundation for statistical analysis of the system and allows us to apply various techniques developed in statistical analysis to plan optimization. It is shown that an optimization based on a quadratic objective function is a special case of the formalism. A general two-step method for using a computer to determine the values of the model parameters is proposed. The approach provides an efficient way to include prior knowledge into the optimization process. The method is illustrated using a simplified two-pixel system as well as two clinical cases. The generality of the approach, coupled with promising demonstrations, indicates that the method has broad implications for radiotherapy treatment plan optimization.

Algorithms↗

PubMed2000

Beam orientation optimization in intensity-modulated radiation treatment planning.

Beam direction optimization is an important problem in radiation therapy. In intensity modulated radiation therapy (IMRT), the difficulty for computer optimization of the beam directions arises from the fact that they are coupled with the intensity profiles of the incident beams. In order to obtain the optimal incident beam directions using iterative or stochastic methods, the beam profiles ought to be optimized after every change of beam configuration. In this paper we report an effective algorithm to optimize gantry angles for IMRT. In our calculation the gantry angles and the beam profiles (beamlet weights) were treated as two separate groups of variables. The gantry angles were sampled according to a simulated annealing algorithm. For each sampled beam configuration, beam profile calculation was done using a fast filtered backprojection (FBP) method. Simulated annealing was also used for beam profile optimization to examine the performance of the FBP for beam orientation optimization. Relative importance factors were incorporated into the objective function to control the relative importance of the target and the sensitive structures. Minimization of the objective function resulted in the best possible beam orientations and beam profiles judged by the given objective function. The algorithm was applied to several model problems and the results showed that the approach has potential for IMRT applications.

Algorithms↗

PubMed2002

Effect of noise and occupancy on optimal reverberation times for speech intelligibility in classrooms.

The question of what is the optimal reverberation time for speech intelligibility in an occupied classroom has been studied recently in two different ways, with contradictory results. Experiments have been performed under various conditions of speech-signal to background-noise level difference and reverberation time, finding an optimal reverberation time of zero. Theoretical predictions of appropriate speech-intelligibility metrics, based on diffuse-field theory, found nonzero optimal reverberation times. These two contradictory results are explained by the different ways in which the two methods account for background noise, both of which are unrealistic. To obtain more realistic and accurate predictions, noise sources inside the classroom are considered. A more realistic treatment of noise is incorporated into diffuse-field theory by considering both speech and noise sources and the effects of reverberation on their steady-state levels. The model shows that the optimal reverberation time is zero when the speech source is closer to the listener than the noise source, and nonzero when the noise source is closer than the speech source. Diffuse-field theory is used to determine optimal reverberation times in unoccupied classrooms given optimal values for the occupied classroom. Resulting times can be as high as several seconds in large classrooms; in some cases, optimal values are unachievable, because the occupants contribute too much absorption.

Acoustics↗

PubMed1999

Comparison of the OptiMAL test with PCR for diagnosis of malaria in immigrants.

The OptiMAL test (Flow Inc., Portland, Oreg.), which detects a malaria parasite lactate dehydrogenase (pLDH) antigen, has not been evaluated for its sensitivity in the diagnosis of malaria infection in various epidemiological settings. Using microscopy and a PCR as reference standards, we performed a comparison of these assays with the OptiMAL test for the detection of Plasmodium falciparum and Plasmodium vivax infection in 550 immigrants who had come from areas where malaria is endemic to reside in Kuwait, where malaria is not endemic. As determined by microscopy, 125 (23%) patients had malaria, and of these, 84 (67%) were infected with P. vivax and 36 were infected with P. falciparum; in 5 cases the parasite species could not be determined due to a paucity of the parasites. The PCR detected malaria infection in 145 (26%) patients; 102 (70%) of the patients had P. vivax infection and 43 had P. falciparum infection. Of the five cases undetermined by microscopy, the PCR detected P. falciparum infection in two cases, P. vivax infection in two cases, and mixed (P. falciparum plus P. vivax) infection in one case. Correspondingly, the OptiMAL test detected malaria infection in 95 patients (17%); of these, 70 (74%) had P. vivax infection and 25 were infected with P. falciparum. In this study, 61 (49%) of the 125 malaria cases, as confirmed by microscopy, had a degree of parasitemia of <100 parasites per microl, and 23 (18%) of the cases had a degree of <50 parasites per microl. Our results show that the sensitivity of the OptiMAL test is high (97%) at a high level of parasitemia (>100 parasites/microl) but drops to 59% when the level is <100 parasites/microl and to 39% when it is <50 parasites/microl. In addition, the OptiMAL test failed to identify four patients whose blood smears contained P. falciparum gametocytes only. We conclude that the sensitivity and specificity of the OptiMAL test are comparable to those of microscopy in detecting malaria infection at a parasitemia level of >100 parasites/microl; however, the test failed to identify more than half of the patients with a parasitemia level of <50 parasites/microl. Thus, the OptiMAL test should be used with great caution, and it should not replace conventional microscopy in the diagnosis of malaria infection.

Animals↗

PubMed1998

Changes over time in optimal duplex threshold for the identification of patients eligible for carotid endarterectomy.

BACKGROUND AND PURPOSE: Two surgical trials established that carotid endarterectomy is beneficial to symptomatic patients who have a severe internal carotid artery (ICA) stenosis on angiograms. Duplex ultrasonography-derived hemodynamic parameters show a good correlation with angiography and are often used for detecting severe ICA stenoses. However, duplex performance is ultrasound machine and operator dependent. Over time both may change, possibly affecting duplex performance. We compared duplex performance of 2 time periods in 1 specific vascular laboratory using angiography as the gold standard. METHODS: Consecutive patients who underwent both angiography and duplex examinations of the ICA were evaluated (first period, 60 patients; second period, 61 patients). Peak systolic velocity and several other hemodynamic parameters and ratios were analyzed by receiver operating characteristic curves in their ability to detect severe ICA stenoses. The optimal parameter and threshold were determined for each period. Subsequently, duplex test characteristics were compared after the optimal thresholds of both the first and the second periods were applied in the second period. RESULTS: In both periods peak systolic velocity of the ICA was the best test parameter; areas under the receiver operating characteristic curve were similar (0.957 and 0.954, respectively). However, the optimal threshold was different. The optimal threshold in the second period was 270 cm/s. When the optimal threshold of 210 cm/s of the first period was applied in the second period, test characteristics changed significantly. Sensitivity increased from 98% to 100%, and specificity decreased from 85% to 71% (P=0.004). CONCLUSIONS: The optimal threshold for detecting severe ICA stenoses with duplex ultrasonography in our laboratory changed over time. Individual laboratories should assess duplex accuracy regularly and adjust adopted criteria if necessary to keep diagnostic performance optimal.

Adult↗

PubMed1997

Optimization of road networks using evolutionary strategies

A road network usually has to fulfill two requirements: (i) it should as far as possible provide direct connections between nodes to avoid large detours; and (ii) the costs for road construction and maintenance, which are assumed proportional to the total length of the roads, should be low. The optimal solution is a compromise between these contradictory demands, which in our model can be weighted by a parameter. The road optimization problem belongs to the class of frustrated optimization problems. In this paper, a special class of evolutionary strategies, such as the Boltzmann and Darwin and mixed strategies, are applied to find differently optimized solutions (graphs of varying density) for the road network, depending on the degree of frustration. We show that the optimization process occurs on two different time scales. In the asymptotic limit, a fixed relation between the mean connection distance (detour) and the total length (costs) of the network exists that defines a range of possible compromises. Furthermore, we investigate the density of states, which describes the number of solutions with a certain fitness value in the stationary regime. We find that the network problem belongs to a class of optimization problems in which more effort in optimization certainly yields better solutions. An analytical approximation for the relation between effort and improvement is derived.

Journal Article↗

PubMed2004

Optimism and pessimism in the context of health: bipolar opposites or separate constructs?

One difficulty plaguing research on dispositional optimism and health is whether optimism and pessimism are bipolar opposites or constitute distinct constructs. The present study examined the Life Orientation Test to determine whether the two-factor structure is explained by method bias (due to measurement) or substantive differences. The authors compared three measurement models: bipolar, bivariate, and method artifact. Optimism and pessimism emerged as distinct constructs due to substantive differences. The authors also considered the validity of optimism and pessimism, examining their relations with psychological and physical health outcomes. Optimism and pessimism were more similar in relation to psychological health than to other health-related behavior or physical health outcomes. However, a strongly interpretable pattern for the relation of optimism and pessimism to the health outcomes did not emerge. Further research may benefit from considering optimism and pessimism as bivariate and also should consider the conceptual components and behavioral mechanisms specific to each variable.

Adolescent↗

PubMed2000

Automated assay optimization with integrated statistics and smart robotics.

The transition from manual to robotic high throughput screening (HTS) in the last few years has made it feasible to screen hundreds of thousands of chemical entities against a biological target in less than a month. This rate of HTS has increased the visibility of bottlenecks, one of which is assay optimization. In many organizations, experimental methods are generated by therapeutic teams associated with specific targets and passed on to the HTS group. The resulting assays frequently need to be further optimized to withstand the rigors and time frames inherent in robotic handling. Issues such as protein aggregation, ligand instability, and cellular viability are common variables in the optimization process. The availability of robotics capable of performing rapid random access tasks has made it possible to design optimization experiments that would be either very difficult or impossible for a person to carry out. Our approach to reducing the assay optimization bottleneck has been to unify the highly specific fields of statistics, biochemistry, and robotics. The product of these endeavors is a process we have named automated assay optimization (AAO). This has enabled us to determine final optimized assay conditions, which are often a composite of variables that we would not have arrived at by examining each variable independently. We have applied this approach to both radioligand binding and enzymatic assays and have realized benefits in both time and performance that we would not have predicted a priori. The fully developed AAO process encompasses the ability to download information to a robot and have liquid handling methods automatically created. This evolution in smart robotics has proven to be an invaluable tool for maintaining high-quality data in the context of increasing HTS demands.

Automation↗

PubMed2004

Optimized LOWESS normalization parameter selection for DNA microarray data.

BACKGROUND: Microarray data normalization is an important step for obtaining data that are reliable and usable for subsequent analysis. One of the most commonly utilized normalization techniques is the locally weighted scatterplot smoothing (LOWESS) algorithm. However, a much overlooked concern with the LOWESS normalization strategy deals with choosing the appropriate parameters. Parameters are usually chosen arbitrarily, which may reduce the efficiency of the normalization and result in non-optimally normalized data. Thus, there is a need to explore LOWESS parameter selection in greater detail. RESULTS AND DISCUSSION: In this work, we discuss how to choose parameters for the LOWESS method. Moreover, we present an optimization approach for obtaining the fraction of data points utilized in the local regression and analyze results for local print-tip normalization. The optimization procedure determines the bandwidth parameter for the local regression by minimizing a cost function that represents the mean-squared difference between the LOWESS estimates and the normalization reference level. We demonstrate the utility of the systematic parameter selection using two publicly available data sets. The first data set consists of three self versus self hybridizations, which allow for a quantitative study of the optimization method. The second data set contains a collection of DNA microarray data from a breast cancer study utilizing four breast cancer cell lines. Our results show that different parameter choices for the bandwidth window yield dramatically different calibration results in both studies. CONCLUSIONS: Results derived from the self versus self experiment indicate that the proposed optimization approach is a plausible solution for estimating the LOWESS parameters, while results from the breast cancer experiment show that the optimization procedure is readily applicable to real-life microarray data normalization. In summary, the systematic approach to obtain critical parameters in the LOWESS technique is likely to produce data that optimally meets assumptions made in the data preprocessing step and thereby makes studies utilizing the LOWESS method unambiguous and easier to repeat.

Algorithms↗

PubMed2006

Optimizing amino acid substitution matrices with a local alignment kernel.

BACKGROUND: Detecting remote homologies by direct comparison of protein sequences remains a challenging task. We had previously developed a similarity score between sequences, called a local alignment kernel, that exhibits good performance for this task in combination with a support vector machine. The local alignment kernel depends on an amino acid substitution matrix. Since commonly used BLOSUM or PAM matrices for scoring amino acid matches have been optimized to be used in combination with the Smith-Waterman algorithm, the matrices optimal for the local alignment kernel can be different. RESULTS: Contrary to the local alignment score computed by the Smith-Waterman algorithm, the local alignment kernel is differentiable with respect to the amino acid substitution and its derivative can be computed efficiently by dynamic programming. We optimized the substitution matrix by classical gradient descent by setting an objective function that measures how well the local alignment kernel discriminates homologs from non-homologs in the COG database. The local alignment kernel exhibits better performance when it uses the matrices and gap parameters optimized by this procedure than when it uses the matrices optimized for the Smith-Waterman algorithm. Furthermore, the matrices and gap parameters optimized for the local alignment kernel can also be used successfully by the Smith-Waterman algorithm. CONCLUSION: This optimization procedure leads to useful substitution matrices, both for the local alignment kernel and the Smith-Waterman algorithm. The best performance for homology detection is obtained by the local alignment kernel.

Algorithms↗

PubMed2004

Echocardiographic AV-interval optimization in patients with reduced left ventricular function.

BACKGROUND: Ritter's method is a tool used to optimize AV delay in DDD pacemaker patients with normal left ventricular function only. The goal of our study was to evaluate Ritter's method in AV delay-interval optimization in patients with reduced left ventricular function. METHODS: Patients with implanted DDD pacemakers and AVB III degrees were assigned to one of two groups according to ejection fraction (EF): Group 1 (EF > 35%) and Group 2 (EF < 35%). AV delay optimization was performed by means of radionuclide ventriculography (RNV) and application of Ritter's method. RESULTS: For each of the patients examined, we succeeded in defining an optimal AV interval by means of both RNV and Ritter's method. The optimal AV delay determined by RNV correlated well with the delay found by Ritter's method, especially among those patients with reduced EF. The intra-class correlation coefficient was 0.8965 in Group 1 and 0.9228 in Group 2. The optimal AV interval in Group 1 was 190 +/- 28.5 ms, and 180 +/- 35 ms in Group 2. CONCLUSION: Ritter's method is also effective for optimization of AV intervals among patients with reduced left ventricular function (EF < 35%). The results obtained by RNV correlate well with those from Ritter's method. Individual programming of the AV interval is fundamentally essential in all cases.

Aged↗

PubMed2005

Simultaneous population optimal design for pharmacokinetic-pharmacodynamic experiments.

Multiple outputs or measurement types are commonly gathered in biological experiments. Often, these experiments are expensive (such as clinical drug trials) or require careful design to achieve the desired information content. Optimal experimental design protocols could help alleviate the cost and increase the accuracy of these experiments. In general, optimal design techniques ignore between-individual variability, but even work that incorporates it (population optimal design) has treated simultaneous multiple output experiments separately by computing the optimal design sequentially, first finding the optimal design for one output (eg, a pharmacokinetic [PK] measurement) and then determining the design for the second output (eg, a pharmacodynamic [PD] measurement). Theoretically, this procedure can lead to biased and imprecise results when the second model parameters are also included in the first model (as in PK-PD models). We present methods and tools for simultaneous population D-optimal experimental designs, which simultaneously compute the design of multiple output experiments, allowing for correlation between model parameters. We then apply these methods to simulated PK-PD experiments. We compare the new simultaneous designs to sequential designs that first compute the PK design, fix the PK parameters, and then compute the PD design in an experiment. We find that both population designs yield similar results in designs for low sample number experiments, with simultaneous designs being possibly superior in situations in which the number of samples is unevenly distributed between outputs. Simultaneous population D-optimality is a potentially useful tool in the emerging field of experimental design.

Computer Simulation↗

PubMed2005

Long-term follow-up of atrioventricular delay optimization in patients with biventricular pacing.

BACKGROUND: Atrioventricular (AV) delay optimization may be important in patients with biventricular pacing and the optimal AV delay can be predicted using Doppler echocardiography and the formula: optimal AV delay = AV delay-the interval between the end of A wave and complete closure of the mitral valve when the AV delay is set at slightly prolonged AV delay. METHODS AND RESULTS: In the present study the efficacy of this method was evaluated in 5 patients (67.4+/-8.0 (SD) years old) with biventricular pacing. Cardiac output (CO) and diastolic filling time were measured by Doppler echocardiography. When the AV delay was set at the predicted optimal AV delay -25 ms, the predicted optimal AV delay (133+/-66 ms) and predicted optimal AV delay + 25 ms, the respective CO were 4.5+/-0.9, 5.3+/-1.0, 4.8+/-1.0 L/min (p<0.05, ANOVA) and the diastolic filling times were 364 +/-100, 373+/-105, 335+/-84 ms (p<0.05, ANOVA). Congestive heart failure improved from New York Heart Association class 3.6+/-0.5 to 1.4+/-0.5 (p<0.001). CONCLUSIONS: AV delay optimization is important in patients with biventricular pacing and can be easily achieved by the new method.

Aged↗

PubMed2001

Optimization technique for a Prompt Gamma-ray SPECT collimator system.

Because background radiation in an irradiation room creates a problem with the PG-SPECT (Prompt Gamma-ray Single Photon Emission Computed Tomography) system, which evaluates the absorbed dose for the Boron Neutron Capture Therapy treatment, optimization of a collimator system was performed while taking the shielding of background gamma-rays into consideration. Assuming that a parallel-beam collimator is used, three parameters--the diameter of a hole, the length of the collimator, and the number of detectors (the number of holes of the collimator)--were selected for optimization. Because the combinations of these parameters are limitless, it is difficult to determine them simultaneously. Therefore, a statistically derived Optimization Criterion has been proposed to optimize these parameters. When the spatial resolution was 1 cm-FWHM (full width at half maximum), the optimal diameter of the collimator was 5.4 mm, the optimal length was 321 mm, and the optimal number of detectors was 31 x 31.

Boron Neutron Capture Therapy↗

PubMed2005

Optimism, positive affectivity, and salivary cortisol.

OBJECTIVES: Research on stress and salivary cortisol has focused almost exclusively on the effects of negative psychological conditions or emotional states. Little attention has been drawn to the impact associated with positive psychological conditions, which have been shown recently to have significant influences on neuroendocrine regulation. The aim of this study is to examine the impact of optimism and positive affect on salivary cortisol with the effects of their negative counterparts controlled for. DESIGN: Optimism and pessimism, and positive and negative affectivity were studied in relation to the diurnal rhythm of salivary cortisol in a group of 80 Hong Kong Chinese, who provided six saliva samples over the course of a day on two consecutive days. The separate effects of optimism and positive affect on two dynamic components of cortisol secretion, awakening response, and diurnal decline were examined. METHODS: Optimism and pessimism were measured using the Chinese version of the revised Life Orientation Test while generalized affects and mood states were assessed by the Chinese Affect Scale. An enzyme-linked immunoabsorbent assay kit (EIA) developed for use in saliva was adopted for the biochemical analysis of cortisol. Testing of major group differences associated with positive psychological conditions was carried out using two-way (group by saliva collection time) ANOVAs for repeated measures with negative psychological conditions and mood states as covariates. RESULTS: Participants having higher optimism scores exhibited less cortisol secretion in the awakening period when the effect of pessimism and mood were controlled. This effect was more apparent in men than in women who had higher cortisol levels in the awakening period. Optimism did not have similar effect on cortisol levels during the underlying period of diurnal decline. On the other hand, higher generalized positive affect was associated with lower cortisol levels during the underlying period of diurnal decline after the effects of negative affect and mood states had been controlled. Generalized positive affect did not significantly influence cortisol secretion during the awakening period. CONCLUSIONS: These findings suggest that positive psychological resources including optimism and generalized positive affect had higher impact on cortisol secretion than their negative counterparts, and point to the need for increased attention to the potential contribution of positive mental states to well-being.

Adult↗

PubMed2004

Optimization of a laser satellite communication system with an optical preamplifier.

We derive a model that optimizes the performance of a laser satellite communication link with an optical preamplifier in the presence of random jitter in the transmitter-receiver line of sight. The system utilizes a transceiver containing a single telescope with a circulator. The telescope is used for both transmitting and receiving and thus reduces communication terminal dimensions and weight. The optimization model was derived under the assumption that the dominant noise source was amplifier spontaneous-emission noise. It is shown that, given the required bit-error rate (BER) and the rms random pointing jitter, an optimal transceiver gain exists that minimizes transmitted power. We investigate the effect of the amplifier spontaneous-emission noise on the optimal transmitted power and gain by performing an optimization procedure for various combinations of amplifier gain and noise figure. We demonstrate that the amplifier noise figure determines the optimal transmitted power needed to achieve the desired BER but does not affect the optimal transceiver telescope gain. Our numerical example shows that for a BER of 10(-9), doubling the amplifier noise figure results in an 80% increase in minimal transmitted power for a rms pointing jitter of 0.44 microrad.

Journal Article↗

PubMed2001

Optimization of atrioventricular delay and follow-up in a patient with congestive heart failure and with bi-ventricular pacing.

Cardiac function is improved by bi-ventricular pacing in patients with severe reduced cardiac function. Atrioventricular (AV) delay optimization is also important in this therapy. However, the AV delay required to achieve the optimal AV synchrony varied from time to time. We have reported that the critical AV delay that induces diastolic mitral regurgitation (MR) may represent the upper limit of the optimal AV delay. The optimal AV delay can be predicted by a simple method; slightly prolonged AV delay-interval between the end of atrial kick and complete closure of the mitral valve (duration of diastolic MR) at the AV delay setting. [Case] 60 year old Japanese male with dilated cardiomyopathy. He was repeatedly admitted to our hospital due to congestive heart failure. Ejection fraction was 14%. ECG showed complete left bundle branch block and his PQ interval was 0.22 sec. He was dependent on intravenous injections of catecolamine and could not be discharged from the hospital for over one year. Optimal AV delay was predicted as 80 msec during bi-ventricular pacing by our formula. Cardiac output was 4.9, 6.0, 5.1 l/min when the AV delay was set at 50, 80, 110 msec. Cardiac function was improved from NYHA class III to II and he has been relieved from the dependency on intravenous catecholamine injections. AV delay was optimized (70-100 msec) by our method during follow-up for one year. This case indicates that AV delay optimization is important in bi-ventricular pacing.

Atrioventricular Node↗