Perspective on the use of fluorescence molecular imaging for peripheral and deep en face margin assessment

Current standard practice for margin assessment in solid tumor resection often leads to suboptimal results due to the inability to assess margins completely in a time-efficient manner. On the other hand, for small skin cancers, peripheral and deep en face margin assessment (PDEMA) offers 100% assessment of margins while sparing the utmost amount of normal surrounding tissues. Nonetheless, PDEMA is limited in its use owing to its lengthy tissue processing and imaging time as well as its requirement for high-quality frozen sections and real-time histologic analysis.

We aim to explore fluorescence molecular imaging (FMI) as a tool for resolving obstacles and integrating PDEMA into the surgeon-to-pathologist workflow for large solid tumors.

A review of recent pre-clinical and clinical studies using FMI to assess surgical margins was conducted to highlight promising fluorescence imaging technologies utilized in the surgical suite and laboratory.

FMI techniques that provide macroscopic resolution are efficient in time and have a notable ability to identify true negative tissue yet have limited capability in identifying true positive tissues. Moreover, meso- and microscopic FMI methods require additional time to attain a higher resolution but deliver an enhanced sensitivity in detecting true positive tissues. In both cases, experts are still required to learn to interpret the FMI signals, which prohibits a seamless clinical integration.

Our proposed margin assessment platform (MAP) incorporates both macroscopic and, meso- or microscopic imaging with post-processing and machine learning for interpretation, to enable the application of PDEMA into solid tumor surgery. MAP leverages the advantages of each technique and thoroughly tackles the limitations of time and expertise to optimize the efficiency and accuracy of margin assessment and ultimately improve clinical outcomes.