Breast Molecular Imaging (or Breast-Specific Gamma Imaging) has been previously shown to be both sensitive and specific for the detection of breast cancer. The purpose of our study was to retrospectively review all cases of Breast Molecular Imaging (BMI) performed at our institution to determine BMI's potential role in Breast Imaging decision making. A total of 416 cases of BMI from January 2007 to November 2009 were analyzed and the following data were collected: indication for examination, BIRADS assignment after BMI, biopsy outcomes, sensitivity and specificity of the modality and patient follow-up. Fifty-six percent of cases were ordered for an indeterminate asymmetry or focal asymmetry, 14% for evaluation of calcifications, and less than 10% each for the remainder of the indications including palpable lumps with negative imaging, evaluation of extent of disease in patients with known breast cancer and screening of high risk patients who could not undergo MRI. BMI was also shown to be helpful in evaluation of lesions that were difficult to biopsy or for patients that desired further testing rather than biopsy or short term follow-up of abnormalities. Seventy percent of BMI cases performed completed the diagnostic evaluation with BIRADS 1 or BIRADS 2 designations. Only 14% of cases ultimately resulted in biopsy. Contra-lateral findings were discovered in 10% of patients, more than half of which were occult malignancies or high-risk lesions. Of the lesions for which biopsy was recommended, 43% were malignant and 15% were high-risk lesions. Sensitivity of the test at our institution was 93% and specificity 78.9%. Our results show that BMI is both a sensitive and specific test which is useful as an adjunct to standard breast imaging modalities for problem solving in indeterminate cases.

Although Mammography Quality Standards Act requires tracking true positives, tracking false negatives is not required. We describe a peer review process implemented at Lahey Clinic to identify false-negative mammograms. We defined a false-negative mammogram as one which was read as negative within 12 months of a cancer diagnosis, and in which two of three radiologists correctly identified the site of cancer. Reviewing radiologists were blinded to each other and to computer-aided design (CAD), but were aware that somewhere in the mammogram was cancer. 25/64, 983, or 0.038% were classified as misses. The false-negative rate of any one radiologist averaged <0.1% without outliers. Of the false negatives, 60% were in heterogeneously dense tissue, 72% were asymmetries or masses rather than calcifications, and 24% were correctly identified by CAD in two views. We use these data for quality assurance, educational purposes, and to help identify patterns of undetected cancers to aid in earlier and improved detection of breast cancers.