Lower lip as a photoacoustic imaging window for detection of CTC clusters: A feasibility phantom study

Detection and continuous monitoring of circulating tumor cells (CTCs) using photoacoustic imaging remains challenging because of weak transient signals and strong blood-background absorption. This proof-of-concept study investigated the lower lip as a potential photoacoustic imaging window for melanoma CTC detection. A tissue-mimicking lower-lip phantom incorporating vessel-mimicking channels, physiologically relevant flow conditions, and donated human blood was developed. Melanoma-cell targets, including HS936.T and melanin-enhanced Mel624+ $\alpha$ -MSH clusters, were imaged using photoacoustic tomography. Singular value decomposition (SVD)-based background suppression and kymograph-based temporal analysis were applied to enhance and characterize transient target-passage events. A composite kymograph-derived Target Score was developed for both automated classification and temporal guidance of visual inspection. Detectability depended on target size, melanin content, and surrounding medium. Mel624+ $\alpha$ -MSH clusters remained detectable under blood-containing conditions, whereas similarly sized HS936.T clusters were not detected. Single HS936.T cells were also not detected, and the smallest detected cluster at the tested melanin concentrations was $500\mu m$ . Operator-referenced automated classification achieved an F1 score of 0.800 and an AUC of 0.733, while temporal guidance captured 83.3% of visually identified passages and reduced the temporal search space by 91.79%. Limited blood and cell availability constrained systematic evaluation and replication. At this proof-of-concept stage, the framework provides a semi-automated approach combining automatic scoring with focused visual inspection. These findings support further investigation of the lower lip as a potential site for photoacoustic monitoring of circulating melanoma cells and provide a foundation for developing automated and semi-automated CTC detection approaches in future studies.