Sentinel lymph node (SLN) excision is included in various cancer guidelines to identify microscopic metastatic disease. Although effective, SLN excision is an invasive procedure requiring radioactive tracing. Novel imaging approaches assessing SLN metastatic status could improve or replace conventional lymph node excision protocols. In our first-in-human study, we used noninvasive multispectral optoacoustic tomography (MSOT) to image SLNs ex vivo and in vivo in patients with melanoma, to determine metastatic status. MSOT significantly improved the tumor metastasis detection rate in excised SLN (506 SLNs from 214 melanoma patients) compared with the conventional EORTC (European Organisation for Research and Treatment of Cancer) Melanoma Group protocol (22.9% versus 14.2%). MSOT combined with the near-infrared fluorophore indocyanine green reliably visualized SLNs in vivo in 20 patients, up to 5-cm penetration and with 100% concordance with (99m)Tc-marked SLN lymphoscintigraphy. MSOT identified cancer-free SLNs in vivo and ex vivo without a single false negative (189 total lymph nodes), with 100% sensitivity and 48 to 62% specificity. Our findings indicate that a noninvasive, nonradioactive MSOT-based approach can identify and determine SLN status and confidently rule out the presence of metastasis. The study further demonstrates that optoacoustic imaging strategies can improve the identification of SLN metastasis as an alternative to current invasive SLN excision protocols.

Detection of intrinsic or extrinsically administered chromophores and photo-absorbing nanoparticles has been achieved by multi-spectral optoacoustic tomography (MSOT). The detection sensitivity of MSOT depends not only on the signal to noise ratio considerations, as in conventional optoacoustic (photoacoustic) tomography implementations, but also on the ability to resolve the molecular targets of interest from the absorbing tissue background by means of spectral unmixing or sub-pixel detection methods. However, it is not known which unmixing methods are optimally suited for the characteristics of multispectral optoacoustic images. In this work we investigated the performance of different sub-pixel detection methods, typically used in remote sensing hyperspectral imaging, within the context of MSOT. A quantitative comparison of the different algorithmic approaches was carried out in an effort to identify methods that operate optimally under the particulars of molecular imaging applications. We find that statistical sub-pixel detection methods can demonstrate a unique detection performance with up to five times enhanced sensitivity as compared to linear unmixing approximations, under the condition that the optical agent of interest is sparsely present within the tissue volume, as common when using targeted agents and reporter genes.