Ultrasound elastography as an adjuvant to conventional ultrasound in the preoperative assessment of axillary lymph nodes in suspected breast cancer: a pilot study.

AIMS: To compare the performance of ultrasound elastography with conventional ultrasound in the assessment of axillary lymph nodes in suspected breast cancer and whether ultrasound elastography as an adjunct to conventional ultrasound can increase the sensitivity of conventional ultrasound used alone. MATERIALS AND METHODS: Fifty symptomatic women with a sonographic suspicion for breast cancer underwent ultrasound elastography of the ipsilateral axilla concurrent with conventional ultrasound being performed as part of triple assessment. Elastograms were visually scored, strain measurements calculated and node area and perimeter measurements taken. Theoretical biopsy cut points were selected. The sensitivity, specificity, positive predictive value (PPV), and negative predictive values (NPV) were calculated and receiver operating characteristic (ROC) analysis was performed and compared for elastograms and conventional ultrasound images with surgical histology as the reference standard. RESULTS: The mean age of the women was 57 years. Twenty-nine out of 50 of the nodes were histologically negative on surgical histology and 21 were positive. The sensitivity, specificity, PPV, and NPV for conventional ultrasound were 76, 78, 70, and 81%, respectively; 90, 86, 83, and 93%, respectively, for visual ultrasound elastography; and for strain scoring, 100, 48, 58 and 100%, respectively. There was no significant difference between any of the node measurements CONCLUSIONS: Initial experience with ultrasound elastography of axillary lymph nodes, showed that it is more sensitive than conventional ultrasound in detecting abnormal nodes in the axilla in cases of suspected breast cancer. The specificity remained acceptable and ultrasound elastography used as an adjunct to conventional ultrasound has the potential to improve the performance of conventional ultrasound alone.

Predictive neural coding of reward preference involves dissociable responses in human ventral midbrain and ventral striatum.

Food preferences are acquired through experience and can exert strong influence on choice behavior. In order to choose which food to consume, it is necessary to maintain a predictive representation of the subjective value of the associated food stimulus. Here, we explore the neural mechanisms by which such predictive representations are learned through classical conditioning. Human subjects were scanned using fMRI while learning associations between arbitrary visual stimuli and subsequent delivery of one of five different food flavors. Using a temporal difference algorithm to model learning, we found predictive responses in the ventral midbrain and a part of ventral striatum (ventral putamen) that were related directly to subjects' actual behavioral preferences. These brain structures demonstrated divergent response profiles, with the ventral midbrain showing a linear response profile with preference, and the ventral striatum a bivalent response. These results provide insight into the neural mechanisms underlying human preference behavior.