Biomedical subjects

D A Silvern

Publications and source records attributed to D A Silvern.

3 recordsLinked to original sources

PubMed2000

Treatment-plan optimization for soft-tissue sarcoma brachytherapy using a genetic algorithm.

PURPOSE: To describe a treatment-plan optimization system for temporary implant of soft-tissue sarcomas using a genetic algorithm, and evaluate its potential advantages over manual planning. METHODS AND MATERIALS: A planning system that optimizes the distribution of radioactive seeds needed for adequate coverage of the target in the treatment of soft-tissue sarcomas has been designed and implemented. The treatment-planning procedures include simulation, film digitization, target-volume definition, optimized planning, and plan evaluation. The input to the optimization program consists of seed coordinates reconstructed from isocentric films, prescription points, and a list of available seed activities. The optimization is performed using a genetic algorithm. RESULTS: Case studies are presented, which compare plans generated by computer optimization or by trial and error (manually). As expected, computer-optimized plans are often (but not always) superior to manual plans. This is particularly evident for situations where (unavoidably) catheters are far apart or irregularly spaced, in which case the advantages of optimized planning in terms of tumor coverage can be quite dramatic. When the target volume is well contained, the optimized plan minimizes the dose to normal tissue. Computer-based optimization has the additional advantage of being much faster than manual planning; this is valuable because it often reduces the total time the patient will spend in the hospital before implantation. CONCLUSION: Optimized planning with a genetic algorithm and seeds of different activities significantly improves planning efficiency and generally results in improved plan quality. The utility of this optimization system is not limited to sarcoma implants.

Adult↗

PubMed1992

Development of a real-time algorithm for predicting sufentanil plasma levels during cardiopulmonary-bypass surgery using a systems approach.

During cardiopulmonary-bypass (CB) procedures, anesthesiologists have traditionally based the administration of narcotics on general dosage recommendations and past experience. Initial doses are usually based on body weight and supplemental amounts are given in anticipation of, or in response to, the effects of surgical stimuli. There has been considerable recent interest in using the population pharmacokinetics of narcotics to optimize the attainment and maintenance of drug plasma concentrations at analgesic target levels which will blunt the hemodynamic responses to noxious stimuli. Moreover, the undershooting or overshooting of the target can be reduced by application of these principles making drug administration more effective and safer. The present study concerns the development of a model for the computer-guided administration of sufentanil throughout surgical procedures involving CB; there is a paucity of studies which have attempted to model the pharmacokinetics of drugs during CB because of the lack of information on the effects of bypass conditions on the pharmacokinetic parameters. We have attempted to approach the effects of hypothermia on sufentanil clearance by applying a continuous temperature correction to the ultimate elimination rate constant (the terminal eigenvalue). This correction is based primarily on the anticipated effects of temperature on the enzyme-catalyzed reactions which are essential for the elimination of drug from the body. An algorithm for the application of the model is also presented.

Algorithms↗

PubMedDate not supplied

Ventilator risk management using a programmed monitor.

A computer program was written to improve quality control and risk management of patients on ventilators. The software was designed to run on the new-generation Spacelabs PC Monitor interfaced to the Puritan-Bennett 7200a ventilator. Before the program allows connection of the ventilator to a patient, the ventilator is polled for initial hardware status, alarm statuses and alarm limit settings. If there are no hardware failures, alarm violations, or improperly set alarm limits, the program prompts the clinician to connect the ventilator to the patient. Polling is done periodically after patient ventilation begins, and patient data, alarm conditions, or changes to the ventilator settings are automatically written to disk. In addition, real-time data can be displayed at any time during the ventilation session by using a set of touch-screen options. After the ventilation session is complete, the clinician can print the final report in hard copy or to disk.

Equipment Failure↗