Benjamin Finch, Utah Valley University
Physical Sciences
The Breast Cancer Research Laboratory at Utah Valley University has been using high-frequency ultrasound to test the pathology of surgical margins from breast cancer conservation surgery. Their studies have shown that high-frequency ultrasound may be sensitive to a range of breast pathologies. The ultrasonic parameter that has been shown to be the most sensitive to pathology is the number of peaks (peak density) in the frequency spectra from the captured waveforms. During testing, the ultrasonic transducers apply an amount of force to the tissues that can vary depending on the researcher. The central question of this study was to determine the effect that the applied force has on the final peak density reading, and therefore the reliability of the results. In order to determine the correlation of force and peak density, an experiment was designed to measure the force applied to tissue by the ultrasonic transducer during testing and to simultaneously measure the applied force while collecting ultrasonic waveforms. An Arduino Uno R3 instrument was obtained as well as an Interlink Electronics FSR 406 force sensor pad. The Arduino was programmed to read the voltage from the FSR sensor and use that information to provide force (N) and pressure (N/cm2) data from the stage. Peak density readings from bovine mammary tissue (very similar to human breast tissue) were acquired using varying amounts of force. The results obtained exhibited significant changes in peak density with applied force. The results showed that if the applied force is under 1.18N, the peak density will fluctuate significantly and will therefore give inconsistent results. However, if the force applied is greater than 1.18N, the peak densities will maintain a relatively consistent form. In conclusion, if the force applied during testing is above 1.18N, the waveforms captured from high-frequency ultrasound testing on breast cancer tissues will provide consistent and reliable results, thus improving the quality of the data and accuracy of diagnosis.