Our group is developing a method based on 3D high-frequency ultrasound (HFU) and 3D quantitative ultrasound (QUS) to help pathologists detect micrometastases in freshly-excised lymph nodes of patients with histologically-proven primary cancer. From a signal and image processing perspective, we report on our efforts to acquire and classify lymph-node tissue based on 3D QUS parameter estimates. We evaluated classifier performance against gold-standard histology. Using our database of 134 abdominal cancer-free nodes and 26 fully cancerous abdominal nodes, a conservative threshold gave a sensitivity and specificity of 99.3% and 73.1%, respectively. We also constructed a 3D cancer-likelihood map of a partially metastatic lymph node and compared that map with histology. This representation potentially can be useful for guiding pathologists to suspicious regions requiring histological evaluation.