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PubMedDate not supplied

Optimization of selective hyperthermia.

Selective hyperthermia can be a feasible treatment modality for deep tissue abnormalities. It is accomplished by using a laser or ultrasound noninvasively to transfer energy to a desired target causing tissue damage. This process has two potential benefits to medical professionals: simplicity of procedure and safety to patient. However, optimizing these selective interactions is difficult due to the number of variables. We propose an optimization coefficient relating the dynamic and geometric parameters of selective hyperthermia, and proceed to measure it in an experimental setup consisting of a near-infrared laser and laser-absorbing dye. To simulate tissue, gelatin phantoms are created using a combination of water, intralipid, and gelatin. Our experiments use a 1.00-cm-diam spherical phantom that is homogeneously enhanced with an indocyanine green (ICG) solution and placed inside a nontarget phantom and irradiated by an 805-nm diode laser. Temperature measurements taken at different locations are analyzed so optimization coefficients can be calculated for different parameters. This optimization coefficient compares the difference in temperatures from inside and outside the target. Analysis of the values after thermal equilibrium provides information about the best parameter selection. Our findings indicate that the optimal ICG concentration and power combination for our tested parameters are 0.083% and 0.97 W, respectively. Based on our analysis, optimization can be obtained by using this coefficient to compare the selectivity of several parameter combinations.

Body Temperature↗

PubMed2002

A comparison of physically and radiobiologically based optimization for IMRT.

Many optimization techniques for intensity modulated radiotherapy have now been developed. The majority of these techniques including all the commercial systems that are available are based on physical dose methods of assessment. Some techniques have also been based on radiobiological models. None of the radiobiological optimization techniques however have assessed the clinically realistic situation of considering both tumor and normal cells within the target volume. This study considers a ratio-based fluence optimizing technique to compare a dose-based optimization method described previously and two biologically based models. The biologically based methods use the values of equivalent uniform dose calculated for the tumor cells and integral biological effective dose for normal cells. The first biologically based method includes only tumor cells in the target volume while the second considers both tumor and normal cells in the target volume. All three methods achieve good conformation to the target volume. The biologically based optimization without the normal tissue in the target volume shows a high dose region in the center of the target volume while this is reduced when the normal tissues are also considered in the target volume. This effect occurs because the normal tissues in the target volume require the optimization to reduce the dose and therefore limit the maximum dose to that volume.

Algorithms↗

PubMed2002

Optimization of Ga-67 imaging for detection and estimation tasks: dependence of imaging performance on spectral acquisition parameters.

UNLABELLED: We have compared the use of two (93 and 185 keV) and three (93, 185, and 300 keV) photopeaks for Ga-67 tumor imaging and optimized the placement of each energy window. METHODS: The bases for optimization and evaluation were ideal and Bayesian signal-to-noise ratios (SNR) for the detection of spheres embedded in a realistic anthropomorphic digital torso phantom and ideal SNR for the estimation of their size and activity concentration. Seven spheres of radii ranging from 1 to 3 cm, located at several sites in the torso, were simulated using a realistic Monte Carlo program. We also calculated the ideal SNR for the detection from simple phantom acquisitions. RESULTS: For detection and estimation tasks, the optimum windows were identical for all sphere sizes and locations. For the 93 keV photopeak, the optimal window was 84-102 keV for the detection and 87-102 keV for estimation; these windows are narrower than the 20% window often used in the clinic (83-101 keV). For the 185 keV photopeak, the optimal window was 170-220 keV for the detection and 170-215 keV for estimation; these are substantially different than the 15% window used in our clinic (171-199 keV). For the 300 keV photopeak, the optimal window for detection was 270-320 keV, and for estimation, 280-320 keV. Using the three optimized, rather than only the two lower-energy, windows yielded a 9% increase in the SNR for the detection of the 3 cm diam sphere (a 12% increase for a 2 cm diam sphere) and a 7% increase in the SNR for estimation of its size. For the acquired phantom data, detection also increased by 9%-12% when using three, rather than two, energy windows.

Abdomen↗

PubMed2003

Optimal marker placement in photogrammetry patient positioning system.

A photogrammetry-based patient positioning system has been used instead of the conventional laser alignment technique for patient set-up in external beam radiotherapy. It tracks skin affixed reflective markers with multiple infrared cameras. The three-dimensional (3D) positions of the markers provide reference information to determine the treatment plan isocenter location and hence provide the ability to position the lesion at the isocenter of the treatment linear accelerator. However, in current clinical practice for lung or liver lesion treatments, fiducial markers are usually randomly affixed onto the patients' chest and abdomen, so that the actual target registration error (TRE) of the internal lesions inside the body may be large, depending on the fiducial registration error (FRE). There exists an optimal marker configuration that can minimize the TRE. In this paper, we developed methods to design the patient-specific optimal configurations of the surface makers to minimize the TRE, given the patient's surface contour, the lesion position and the FRE. Floating genetic algorithm (GA) optimization was used to optimize the positions of the skin markers. The surface curve of the patient body was determined by an automatic segmentation algorithm from the planning CT. The method was evaluated using a body phantom implanted with a metal ball (a simulated target). By registering two CT scans using the surface markers and measuring the displacement of the target, the TRE was measured. The TRE was also measured by taking two orthogonal portal films after positioning the phantom using the photogrammetry based patient positioning system. A 50% reduction in TRE has been achieved by using the optimal configuration compared to the random configuration. This result demonstrates that the optimization of a fiducial configuration can result in improved tumor targeting ability.

Humans↗

PubMed2003

Optimization of technique factors for a silicon diode array full-field digital mammography system and comparison to screen-film mammography with matched average glandular dose.

Contrast-detail experiments were performed to optimize technique factors for the detection of low-contrast lesions using a silicon diode array full-field digital mammography (FFDM) system under the conditions of a matched average glandular dose (AGD) for different techniques. Optimization was performed for compressed breast thickness from 2 to 8 cm. FFDM results were compared to screen-film mammography (SFM) at each breast thickness. Four contrast-detail (CD) images were acquired on a SFM unit with optimal techniques at 2, 4, 6, and 8 cm breast thicknesses. The AGD for each breast thickness was calculated based on half-value layer (HVL) and entrance exposure measurements on the SFM unit. A computer algorithm was developed and used to determine FFDM beam current (mAs) that matched AGD between FFDM and SFM at each thickness, while varying target, filter, and peak kilovoltage (kVp) across the full range available for the FFDM unit. CD images were then acquired on FFDM for kVp values from 23-35 for a molybdenum-molybdenum (Mo-Mo), 23-40 for a molybdenum-rhodium (Mo-Rh), and 25-49 for a rhodium-rhodium (Rh-Rh) target-filter under the constraint of matching the AGD from screen-film for each breast thickness (2, 4, 6, and 8 cm). CD images were scored independently for SFM and each FFDM technique by six readers. CD scores were analyzed to assess trends as a function of target-filter and kVp and were compared to SFM at each breast thickness. For 2 cm thick breasts, optimal FFDM CD scores occurred at the lowest possible kVp setting for each target-filter, with significant decreases in FFDM CD scores as kVp was increased under the constraint of matched AGD. For 2 cm breasts, optimal FFDM CD scores were not significantly different from SFM CD scores. For 4-8 cm breasts, optimum FFDM CD scores were superior to SFM CD scores. For 4 cm breasts, FFDM CD scores decreased as kVp increased for each target-filter combination. For 6 cm breasts, CD scores decreased slightly as kVp increased for Mo-Mo, but did not change significantly as a function of kVp for either Mo-Rh or Rh-Rh. For 8 cm breasts, Rh/Rh FFDM CD scores were superior to other target-filter combinations and increased significantly as kVp increased. These results indicate that low-contrast lesion detection was optimized for FFDM by using a softer x-ray beam for thin breasts and a harder x-ray beam for thick breasts, when AGD was kept constant for a given breast thickness. Under this constraint, optimum low-contrast lesion detection with FFDM was superior to that for SFM for all but the thinnest breasts.

Equipment Failure Analysis↗

PubMed2005

Optimization of radiobiological effects in intensity modulated proton therapy.

Today, inverse treatment planning for intensity modulated proton therapy (IMPT) usually employs a constant relative biological effectiveness (RBE). In this paper, the potential clinical relevance of RBE variations for scanning techniques in IMPT is investigated, and a new strategy to include the RBE into the inverse planning process is presented. Three-dimensional RBE distributions are calculated based on a phenomenological model that describes the RBE as a function of dose, linear energy transfer (LET) and tissue type in the framework of the linear-quadratic model. This RBE model is integrated into the optimization loop of inverse planning by using a modified version of the standard quadratic objective function, where the physical dose is replaced by the biological effect. This system for "biological optimization" was implemented into a research version of the inverse planning software KonRad and allows the direct optimization of the product of RBE and physical dose. Several treatment plans for a prostate case are presented, which compare the biological with the conventional physical dose optimization for IMPT scanning techniques, in particular distal edge tracking (DET) and the full three-dimensional (3D) modulation of beam spots. Mainly due to their different LET distributions, the RBE effects for these two techniques are quite different: while the RBE distribution was more or less homogeneous in the planning target volume (PTV) for 3D modulation, considerable RBE variations within the PTV were observed for DET. These unfavorable effects could be compensated for by employing the new biological objective function, which led to a more homogeneous distribution of the product of RBE and physical dose in the PTV. The computation time increased by a factor of 2 compared to the optimization of the physical dose. In conclusion, the proposed method allows the simultaneous multifield optimization of the biological effect in a reasonable time, and is therefore well suited for studying the influence of a variable RBE in IMPT as well as for minimizing potentially adverse effects.

Body Burden↗

PubMed2006

Constrained segment shapes in direct-aperture optimization for step-and-shoot IMRT.

Previous studies have shown that, by optimizing segment shapes and weights directly, without explicitly optimizing fluence profiles, effective IMRT plans can be generated with fewer segments. This study proposes a method of direct-aperture optimization with aperture shape constraints, which is designed to provide segmental IMRT plans using a minimum of simple, regular segments. The method uses a cubic function to create smoothly curving multileaf collimator shapes. Constraints on segment dimension and equivalent square are applied, and each segment can be constrained to lie within the previous one, for easy generation of fluence profiles with a single maximum. To simply optimize the segment shapes and reject any shapes which violate the constraints is too inefficient, so an innovative method of feedback optimization is used to ensure in advance that viable aperture shapes are generated. The algorithm is demonstrated using a simple cylindrical phantom consisting of a hemi-annular planning target volume and a central cylindrical organ-at-risk. A simple IMRT rectum case is presented, where segments are used to replace a wedge. More complex cases of prostate and seminal vesicles and prostate and pelvic nodes are also shown. The algorithm produces effective plans in each case with three to five segments per beam. For the simple plans, the constraint that each segment should be contained within the previous one adds additional simplicity to the plan, for a small reduction in plan quality. This study confirms that direct-aperture optimization gives efficient solutions to the segmental IMRT inverse problem and provides a method for generating simple apertures. By using such a method, the workload of IMRT verification may be reduced and simplified, as verification of fluence profiles from individual beams may be eliminated.

Algorithms↗

PubMed2006

Inverse plan optimization accounting for random geometric uncertainties with a multiple instance geometry approximation (MIGA).

Radiotherapy treatment plans that are optimized to be highly conformal based on a static patient geometry can be degraded by setup errors and/or intratreatment motion, particularly for IMRT plans. To achieve improved plans in the face of geometrical uncertainties, direct simulation of multiple instances of the patient anatomy (to account for setup and/or motion uncertainties) is used within the inverse planning process. This multiple instance geometry approximation (MIGA) method uses two or more instances of the patient anatomy and optimizes a single beam arrangement for all instances concurrently. Each anatomical instance can represent expected extremes or a weighted distribution of geometries. The current implementation supports mapping between instances that include distortions, but this report is limited to the use of rigid body translations/ rotations. For inverse planning, the method uses beamlet dose calculations for each instance, with the resulting doses combined using a weighted sum of the results for the multiple instances. Beamlet intensities are then optimized using the inverse planning system based on the cost for the composite dose distribution. MIGA can simulate various types of geometrical uncertainties, including random setup error and intratreatment motion. A limited number of instances are necessary to simulate Gaussian-distributed errors. IMRT plans optimized using MIGA show significantly less degradation in the face of geometrical errors, and are robust to the expected (simulated) motions. Results for a complex head/neck plan involving multiple target volumes and numerous normal structures are significantly improved when the MIGA method of inverse planning is used. Inverse planning using MIGA can lead to significant improvements over the use of simple PTV volume expansions for inclusion of geometrical uncertainties into inverse planning, since it can account for the correlated motions of the entire anatomical representation. The optimized plan results reflect the differing patient geometry situations which can be important near the surface or heterogeneities. For certain clinical situations, the MIGA optimization approach can correct for a significant part of the degradation of the plan caused by the setup uncertainties.

Artifacts↗

PubMed2006

Direct aperture optimization for IMRT using Monte Carlo generated beamlets.

This work introduces an EGSnrc-based Monte Carlo (MC) beamlet does distribution matrix into a direct aperture optimization (DAO) algorithm for IMRT inverse planning. The technique is referred to as Monte Carlo-direct aperture optimization (MC-DAO). The goal is to assess if the combination of accurate Monte Carlo tissue inhomogeneity modeling and DAO inverse planning will improve the dose accuracy and treatment efficiency for treatment planning. Several authors have shown that the presence of small fields and/or inhomogeneous materials in IMRT treatment fields can cause dose calculation errors for algorithms that are unable to accurately model electronic disequilibrium. This issue may also affect the IMRT optimization process because the dose calculation algorithm may not properly model difficult geometries such as targets close to low-density regions (lung, air etc.). A clinical linear accelerator head is simulated using BEAMnrc (NRC, Canada). A novel in-house algorithm subdivides the resulting phase space into 2.5 X 5.0 mm2 beamlets. Each beamlet is projected onto a patient-specific phantom. The beamlet dose contribution to each voxel in a structure-of-interest is calculated using DOSXYZnrc. The multileaf collimator (MLC) leaf positions are linked to the location of the beamlet does distributions. The MLC shapes are optimized using direct aperture optimization (DAO). A final Monte Carlo calculation with MLC modeling is used to compute the final dose distribution. Monte Carlo simulation can generate accurate beamlet dose distributions for traditionally difficult-to-calculate geometries, particularly for small fields crossing regions of tissue inhomogeneity. The introduction of DAO results in an additional improvement by increasing the treatment delivery efficiency. For the examples presented in this paper the reduction in the total number of monitor units to deliver is approximately 33% compared to fluence-based optimization methods.

Algorithms↗

PubMedDate not supplied

Clinical implementation of stereotaxic brain implant optimization.

This optimization method for stereotaxic brain implants is based on seed/strand configurations of the basic type developed for the National Cancer Institute (NCI) atlas of regular brain implants. Irregular target volume shapes are determined from delineation in a stack of contrast enhanced computed tomography scans. The neurosurgeon may then select up to ten directions, or entry points, of surgical approach of which the program finds the optimal one under the criterion of smallest target volume diameter. Target volume cross sections are then reconstructed in 5-mm-spaced planes perpendicular to the implantation direction defined by the entry point and the target volume center. This information is used to define a closed line in an implant cross section along which peripheral seed strands are positioned and which has now an irregular shape. Optimization points are defined opposite peripheral seeds on the target volume surface to which the treatment dose rate is prescribed. Three different optimization algorithms are available: linear least-squares programming, quadratic programming with constraints, and a simplex method. The optimization routine is implemented into a commercial treatment planning system. It generates coordinate and source strength information of the optimized seed configurations for further dose rate distribution calculation with the treatment planning system, and also the coordinate settings for the stereotaxic Brown-Roberts-Wells (BRW) implantation device.

Algorithms↗

PubMed1995

Simultaneous optimization of dynamic multileaf collimation and scanning patterns or compensation filters using a generalized pencil beam algorithm.

A very flexible iterative method for simultaneous optimization of dynamic multileaf collimation, scanning patterns and compensation filters has been developed. The algorithm can account for and optimize almost all the degrees of freedom available in a modern radiation therapy clinic. The method has been implemented for three dimensional treatment planning. The algorithm has been tested for a number of cases where both traditional wedge filters and block collimators, and modern equipment such as scanned beams and multileaf collimators are available. It is shown that the algorithm can improve heavily on traditional uniform dose plans with respect to the probability of achieving tumor control without causing severe complications (P+) simply by finding the optimal beam weights and block collimator settings. By allowing more complex equipment to deliver the dose and by accounting for their increased flexibility during the optimization, the dose plan can be substantially improved with respect to the applied objective functions. It is demonstrated that flexible lateral collimation combined with compensators or scanned beams in most cases allow close to optimal dose delivery. Here both the calculation time and the amount of primary computer memory needed has been reduced by performing the dose calculations in a cone beam coordinate system allowing the use of approximately spatially invariant energy deposition kernels. A typical calculation time for optimization of a two-field technique in a three dimensional volume is about 20 s per iteration step on a Hewlett-Packard 735 workstation. A well converged solution is normally obtained within about 50-100 iterations or within 15-30 min.

Algorithms↗

PubMed1999

Optimal configuration of multiple-focused ultrasound transducers for external hyperthermia.

External ultrasound hyperthermia is considered to be a very flexible modality for heating deep-seated tumors owing to its penetration and focusing ability. However, using this flexibility requires that many complicated, interacting decisions be made to obtain optimal treatment. This paper presents the feasibility of arranging multiple-focused ultrasound transducers to produce an appropriate heating pattern for a specific treatment, based on the optimal scan parameters obtained from an optimization algorithm. The variable scan parameters of the heating system optimized are the transducer tilt and rotation angles, focal depth, scan radius, and output acoustical power. After obtaining the optimal scan parameters, multiple transducers are systematically arranged according to these scan parameters. Three-dimensional ultrasound power deposition and temperature distribution for a specific treatment are calculated for this multiple ultrasound transducer system. A more uniform temperature distribution in the treatment region for a large, highly perfused tumor can be achieved by scanning the system with respect to the central scan axis and/or swinging the transducers inwards and outwards. The maximum heating depth of focused ultrasound transducers used in this heating system is also studied. Simulation results demonstrate that the optimal arrangement of this multiple-focused ultrasound transducer system is highly promising for heating deep, large, and highly perfused tumors.

Algorithms↗

PubMed2000

Optimization of inverse treatment planning using a fuzzy weight function.

A fuzzy approach has been applied to inverse treatment planning optimization in radiation therapy. The proposed inverse-planning algorithm optimizes both the intensity-modulated beam (IMB) and the normal tissue prescription. In the IMB optimization, we developed a fast-monotonic-descent (FMD) method that has the property of fast and monotonic convergence to the minimum for a constrained quadratic objective function. In addition, a fuzzy weight function is employed to express the vague knowledge about the importance of matching the calculated dose to the prescribed dose in the normal tissue. Then, a validity function is established to optimize the normal tissue prescription. The performance of this new fuzzy prescription algorithm has been compared to that based on hard prescription methods for two treatment geometries. The FMD method presented here both provides a full-analytical solution to the optimization of intensity-modulated beams, and guarantees fast and monotonic convergence to the minimum. It has been shown that the fuzzy inverse planning technique is capable of achieving an optimal balance between the objective of matching the calculated dose to the prescribed dose for the target volume and the objective of minimizing the normal tissue dose.

Algorithms↗

PubMed2003

Optimal detection of crack echo families in elastic solids.

Optimal detection of a striplike crack residing in an isotropic elastic solid with coarse microstructure by means of ultrasonic nondestructive evaluation (NDE) is considered. A physics-based approach to derive an optimal detector, which achieves the theoretical limitations constrained by the underlying physics, is presented. State-of-the-art physical models of crack echoes and of stochastic backscattering from the material structure in elastic solids are introduced and unified with the theory of optimal detection to yield a practically useful nonlinear filter bank implementation of the optimal detector. Monte Carlo simulations of the detection performance for the special case of a striplike crack with uncertain angular orientation are presented in the form of receiver operating characteristics (ROCs). These new results represent the physical limitations for detecting a crack under the stated conditions and serve as performance bounds to which other detectors should be compared. A physics-based generalized likelihood ratio (GLR) detector, which relies on the same nonlinear filter bank as the optimal detector, is also presented for the special case of a striplike crack. A comparison between the optimal and the GLR detectors shows that the GLR detector only slightly reduces the performance.

Journal Article↗

PubMed1996

Development and evaluation of a Bayesian pharmacokinetic estimator and optimal, sparse sampling strategies for ceftazidime.

Data were gathered during an activity-controlled trial in which seriously ill, elderly patients were randomized to receive intravenous ceftazidime or ciprofloxacin and for which adaptive feedback control of drug concentrations in plasma and activity profiles was prospectively performed. The adaptive feedback control algorithm for ceftazidime used an initial population model, a maximum a posteriori (MAP)-Bayesian pharmacokinetic parameter value estimator, and an optimal, sparse sampling strategy for ceftazidime that had been derived from data in the literature obtained from volunteers. Iterative two-stage population pharmacokinetic analysis was performed to develop an unbiased MAP-Bayesian estimator and updated optimal, sparse sampling strategies. The final median values of the population parameters were follows: the volume of distribution of the central compartment was equal to 0.249 liter/kg, the volume of distribution of the peripheral compartment was equal to 0.173 liter/kg, the distributional clearance between the central and peripheral compartments was equal to 0.2251 liter/h/kg, the slope of the total clearance (CL) versus the creatinine clearance (CLCR) was equal to 0.000736 liter/h/kg of CL/1 ml/min/1.73 m2 of CLCR, and nonrenal clearance was equal to + 0.00527 liter/h/kg. Optimal sampling times were dependent on CLCR; for CLCR of > or = 30 ml/min/1.73 m2, the optimal sampling times were 0.583, 3.0, 7.0, and 16.0 h and, for CLCR of < 30 ml/min/1.73 m2, optimal sampling times were 0.583, 4.15, 11.5, and 24.0 h. The study demonstrates that because pharmacokinetic information from volunteers may often not be reflective of specialty populations such as critically ill elderly individuals, iterative two-stage population pharmacokinetic analysis, MAP-Bayesian parameter estimation, and optimal, sparse sampling strategy can be important tools in characterizing their pharmacokinetics.

Adult↗

PubMed2003

Multicenter study to evaluate the OptiMAL test for rapid diagnosis of malaria in U.S. hospitals.

More than 1,000 cases of malaria are diagnosed each year in the United States. Reported numbers, however, may be artificially low because many clinicians fail to consider the diagnosis on presentation, U.S. hospital laboratory technologists have very limited experience in detecting and identifying malaria parasites, and reporting of malaria to state health departments is sporadic in many states. In this study, a rapid malaria diagnostic test, the OptiMAL test (DiaMed; under license from Flow Inc., Portland, Oreg.) was evaluated in six U.S. hospitals and compared with results of microscopy. The OptiMAL test is a 15-min rapid immunochromatographic test that both identifies and differentiates Plasmodium falciparum from non-P. falciparum malaria parasites on the basis of the detection of parasite lactate dehydrogenase in a drop of patient blood. A total of 216 specimens from patients suspected of having malaria were tested. Results indicated that 43 samples (20%) were positive for malaria parasites by microscopy (32 P. falciparum, 11 non-P. falciparum) while 42 (19%) were positive by OptiMAL (31 P. falciparum, 11 non-P. falciparum). The sensitivity of the OptiMAL test was 98%; its specificity was 100%, with positive and negative predictive values of 100 and 99%, respectively. Participating hospital physicians and laboratory directors independently reported that the OptiMAL rapid malaria test was accurate, easy to use, and well accepted by those working in their diagnostic laboratories. The overall conclusion was that integration of the OptiMAL rapid malaria test into the U.S. health care infrastructure would provide an important and easy-to-use tool for the timely diagnosis of malaria.

Animals↗

PubMed2005

Optimal peak systolic velocity threshold at duplex us for determining the need for carotid endarterectomy: a decision analytic approach.

PURPOSE: To determine the optimal peak systolic velocity (PSV) threshold at duplex ultrasonography (US) required to establish the need for carotid endarterectomy in symptomatic patients on the basis of the long-term cost-effectiveness outcomes of diagnostic testing and subsequent treatment. MATERIALS AND METHODS: From January 1997 through January 2000, a prospective medical ethics committee-approved multicenter study was conducted. After giving informed consent, patients with amaurosis fugax, transient ischemic attack, or minor stroke who underwent duplex US and digital subtraction angiography were included in the study. Selective ipsilateral carotid angiograms were obtained in at least three planes. Arteries that were nearly or totally occluded at duplex US were excluded because the PSV cannot be reliably measured in these vessels. Receiver operating characteristic (ROC) curves were constructed for the diagnoses of 70%-99% and 50%-99% stenoses. Optimal likelihood ratios were calculated on the basis of lifetime costs and quality-adjusted life-years derived at cost-effectiveness analysis and the prevalence of disease. The associated optimal sensitivities, specificities, and PSV thresholds were derived from the ROC curves. RESULTS: In this clinical study, 350 patients were included. The nonoccluded arteries in a total of 236 patients were assessable for ROC analysis. For the diagnosis of 70%-99% stenosis, the optimal likelihood ratio was 0.21, which was associated with a PSV threshold of 220 cm/sec, a sensitivity of 97% (127 of 131 patients; 95% confidence interval [CI]: 94%, 100%), and a specificity of 48% (50 of 105 patients; 95% CI: 38%, 57%). For the diagnosis of 50%-99% stenosis, the optimal likelihood ratio was 0.38, which was associated with a PSV threshold of 180 cm/sec, a sensitivity of 95% (182 of 191 patients; 95% CI: 92%, 98%), and a specificity of 69% (31 of 45 patients; 95% CI: 55%, 82%). CONCLUSION: On the basis of the lifetime outcomes of diagnostic testing and subsequent treatment, the optimal PSV thresholds for the diagnosis of 70%-99% and 50%-99% carotid artery stenoses in patients with amaurosis fugax, transient ischemic attack, or minor stroke were 220 cm/sec and 180 cm/sec, respectively.

Adult↗

PubMed1983

Optimal segments: a method for smoothing tracer data to calculate metabolic fluxes.

Metabolic fluxes (Ra and Rd) are calculated in the nonsteady state using Steele's equations. These calculations require estimates of the values and rates of change of glucose and specific activity at discrete sampling times. Data smoothing minimizes the effect of measurement error that confounds the Ra and Rd calculations. We compared three smoothing methods: a) moving average, b) polynomial fitting, and c) optimal segments, a new technique that utilizes optimization methods. Experimental designs were simulated: 1) constant infusion of glucagon in depancreatized dogs, and 2) glucose oscillations generated by constant high-level glucose infusion. Measurement error was added to raw data. After smoothing, fluxes were calculated and compared to the "actual" Ra and Rd. Ra calculated from unsmoothed noisy data were in error by an average 39%. Error was reduced by smoothing to: 23%, moving average; 18%, polynomial fitting; 15%, optimal segments. Optimal segments was best for calculating Ra (P less than 0.01) and was better than or equal to other methods for Rd. Distortion in flux patterns was greatest for polynomial fitting (P less than 0.01) and least for optimal segments (P less than 0.001). Optimal segments is the method of choice for smoothing tracer data; it improves calculations of Ra and Rd with minimal distortion.

Animals↗