Application of Signal Advance Technology to Electrophysiology

Medical instrumentation used in diagnosis and treatment relies on the accurate detection and processing of various physiological events and signals. While signal detection technology has improved greatly in recent years, there remain inherent delays in signal detection/ processing. These delays may have significant negative clinical consequences during various pathophysiological events. Reducing or eliminating such delays would increase the ability to provide successful early intervention in certain disorders thereby increasing the efficacy of treatment. In recent years, a physical phenomenon referred to as Negative Group Delay (NGD), demonstrated in simple electronic circuits, has been shown to temporally advance the detection of analog waveforms. Specifically, the output is temporally advanced relative to the input, as the time delay through the circuit is negative. The circuit output precedes the complete detection of the input signal. This process is referred to as signal advance (SA) detection. An SA circuit model incorporating NGD was designed, developed and tested. It imparts a constant temporal signal advance over a pre-specified spectral range in which the output is almost identical to the input signal (i.e., it has minimal distortion). Certain human patho-electrophysiological events are good candidates for the application of temporally-advanced waveform detection. SA technology has potential in early arrhythmia and epileptic seizure detection and intervention. Demonstrating reliable and consistent temporally advanced detection of electrophysiological waveforms may enable intervention with a pathological event (much) earlier than previously possible. SA detection could also be used to improve the performance of neural computer interfaces, neurotherapy applications, radiation therapy and imaging. In this study, the performance of a single-stage SA circuit model on a variety of constructed input signals, and human ECGs is investigated. The data obtained is used to quantify and characterize the temporal advances and circuit gain, as well as distortions in the output waveforms relative to their inputs. This project combines elements of physics, engineering, signal processing, statistics and electrophysiology. Its success has important consequences for the development of novel interventional methodologies in cardiology and neurophysiology as well as significant potential in a broader range of both biomedical and non-biomedical areas of application.

Development of automated image analysis tools for verification of radiotherapy field accuracy with an electronic portal imaging device

The successful management of cancer with radiation relies on the accurate deposition of a prescribed dose to a prescribed anatomical volume within the patient. Treatment set-up errors are inevitable because the alignment of field shaping devices with the patient must be repeated daily up to eighty times during the course of a fractionated radiotherapy treatment. With the invention of electronic portal imaging devices (EPIDs), patient's portal images can be visualized daily in real-time after only a small fraction of the radiation dose has been delivered to each treatment field. However, the accuracy of human visual evaluation of low-contrast portal images has been found to be inadequate. The goal of this research is to develop automated image analysis tools to detect both treatment field shape errors and patient anatomy placement errors with an EPID. A moments method has been developed to align treatment field images to compensate for lack of repositioning precision of the image detector. A figure of merit has also been established to verify the shape and rotation of the treatment fields. Following proper alignment of treatment field boundaries, a cross-correlation method has been developed to detect shifts of the patient's anatomy relative to the treatment field boundary. Phantom studies showed that the moments method aligned the radiation fields to within 0.5mm of translation and 0.5$\sp\circ$ of rotation and that the cross-correlation method aligned anatomical structures inside the radiation field to within 1 mm of translation and 1$\sp\circ$ of rotation. A new procedure of generating and using digitally reconstructed radiographs (DRRs) at megavoltage energies as reference images was also investigated. The procedure allowed a direct comparison between a designed treatment portal and the actual patient setup positions detected by an EPID. Phantom studies confirmed the feasibility of the methodology. Both the moments method and the cross-correlation technique were implemented within an experimental radiotherapy picture archival and communication system (RT-PACS) and were used clinically to evaluate the setup variability of two groups of cancer patients treated with and without an alpha-cradle immobilization aid. The tools developed in this project have proven to be very effective and have played an important role in detecting patient alignment errors and field-shape errors in treatment fields formed by a multileaf collimator (MLC). ^