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Staging of cancers and selection of appropriate treatment requires histological examination of multiple dissected lymph nodes (LNs) per patient, so that a staggering number of nodes require histopathological examination, and the finite resources of pathology facilities create a severe processing bottleneck. Histologically examining the entire 3D volume of every dissected node is not feasible, and therefore, only the central region of each node is examined histologically, which results in severe sampling limitations. In this work, we assess the feasibility of using quantitative photoacoustics (QPA) to overcome the limitations imposed by current procedures and eliminate the resulting under sampling in node assessments. QPA is emerging as a new hybrid modality that assesses tissue properties and classifies tissue type based on multiple estimates derived from spectrum analysis of photoacoustic (PA) radiofrequency (RF) data and from statistical analysis of envelope-signal data derived from the RF signals. Our study seeks to use QPA to distinguish cancerous from non-cancerous regions of dissected LNs and hence serve as a reliable means of imaging and detecting small but clinically significant cancerous foci that would be missed by current methods. Dissected lymph nodes were placed in a water bath and PA signals were generated using a wavelength-tunable (680-950 nm) laser. A 26-MHz, f-2 transducer was used to sense the PA signals. We present an overview of our experimental setup; provide a statistical analysis of multi-wavelength classification parameters (mid-band fit, slope, intercept) obtained from the PA signal spectrum generated in the LNs; and compare QPA performance with our established quantitative ultrasound (QUS) techniques in distinguishing metastatic from non-cancerous tissue in dissected LNs. QPA-QUS methods offer a novel general means of tissue typing and evaluation in a broad range of disease-assessment applications, e.g., cardiac, intravascular, musculoskeletal, endocrine-gland, etc.
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