Sensitive, noninvasive detection of lymph node metastases.

Abstract

Many primary malignancies spread via lymphatic dissemination, and accurate staging therefore still relies on surgical exploration. The purpose of this study was to explore the possibility of semiautomated noninvasive nodal cancer staging using a nanoparticle-enhanced lymphotropic magnetic resonance imaging (LMRI) technique. We measured magnetic tissue parameters of cancer metastases and normal unmatched lymph nodes by noninvasive LMRI using a learning dataset consisting of 97 histologically proven nodes. We then prospectively tested the accuracy of these parameters against 216 histologically validated lymph nodes from 34 patients with primary cancers, in semiautomated fashion. We found unique magnetic tissue parameters that accurately distinguished metastatic from normal nodes with an overall sensitivity of 98% and specificity of 92%. The parameters could be applied to datasets in a semiautomated fashion and be used for three-dimensional reconstruction of complete nodal anatomy for different primary cancers. These results suggest for the first time the feasibility of semiautomated nodal cancer staging by noninvasive imaging.