Computer-aided tool for diagnostic breast ultrasound
Small Business Information
ALMEN LABORATORIES, INC.
ALMEN LABORATORIES, INC., 1672 Gil Way, VISTA, CA, 92084
AbstractDESCRIPTION (provided by applicant): In current medical practice, breast biopsy serves as the gold standard for determining if a breast mass is benign or malignant. Mammography is the main imaging procedure (screening) for detecting suspicious findings wit h its high sensitivity but its lower specificity (false positives) is well documented. With increased emphasis on early detection of breast cancer, it appears the effort to avoid missing a malignant lesion may have led to a low positive biopsy rate for can cer, between 10-31%. Unfortunately, breast biopsy is neither a benign nor an inexpensive process. Besides affecting patients physically and emotionally, the procedure frequently causes internal scarring, which may obscure the results of future mammograms. With approximately 1,700,000 women undergoing breast biopsy per year in the USA, combined with a cost between 750-5000 per procedure, the cost to the U.S. healthcare system is significant. Ultrasound is widely regarded as the adjunct (secondary) procedure of choice to mammography, especially for distinguishing cystic from solid masses in which accuracy is 96-100%. Results suggest that more accurate application of ultrasound could help reduce the number of biopsies by up to 40% with a cost savings in conser vative estimate of well over 1 billion per year in the USA, mainly by reducing the number of False Positives that are biopsied. However, earlier studies in which ultrasound was evaluated largely as a primary screening tool reported a wide variance in Posi tive Predictive Value (PPV) and an unsettling range of False Negative (FN) rate from 0.3-30%. Despite improving scanner technology with excellent near-field imaging and an increasing number of positive clinical reports that show sonography can distinguish benign from malignant solid nodules with, it is likely that a majority of radiologists in the U.S. recommend that breast US be used only to determine whether a lesion is cystic or solid and/or for needle guidance. Although a well defined rule-based system has been developed (BI- RADS) for reporting, describing and scoring the Level of Suspicion (LOS) for cancer based on the ultrasound appearance of breast masses. Also it is difficult to teach the method with high variability between radiologists. Al men Laboratories with its clinical collaborators has developed a sophisticated computer-aided image analysis system for a variety of medical imaging applications. Almen Labs' Computer-Aided Imaging System (CAIS) provides extensive tools to identify objects of interest or concern such as breast masses in a medical image. It also measures numeric features of the mass, analyzes the important information content and then compares the mass of interest to images of masses with known findings and outcomes. The mos t similar known masses are retrieved and displayed nearly instantaneously for the radiologist to review. During our Preliminary Study this software system was optimized for the diagnostic breast ultrasound examination to standardize interpretation. Our goa ls for Accuracy, Sensitivity and Specificity were exceeded and the CAIS also exceeded the performance of four expert radiologists. These results represent the highest performance for any known ultrasound CAD. This Phase I and II Fast Track grant ap plication targets important advancement and more extensive clinical validation of this breast ultrasound tool. The goal is to provide radiologists with a higher degree of confidence to differentiate many benign from more suspicious lesions. We propose to c omplete evaluation and validation of the Computer-Aided Imaging System in the clinical environment. We hypothesize that correct classification of masses on breast ultrasound (specificity of interpretation) can be significantly improved with no significant reduction in detection of cancer (change in sensitivity) by using the CAIS. Lesions of lower LOS such as complex cystic masses will be ruled out as candidates
* information listed above is at the time of submission.