A rapid and universal method for depth estimation of lesions in heterogeneous tissues via photosafe ratiometric transmission Raman spectroscopy

Abstract

Noninvasive detection of deep lesions remains a long‐standing goal for clinical applications, with depth estimation of a single lesion in heterogeneous tissues being a key challenge. Currently, optical techniques are widely applied for lesion detection, but they face difficulties in achieving rapid and precise lesion depth estimation, particularly when the lesions are buried in thick heterogeneous tissues and the applied irradiance is below clinically maximum permissible exposure. Herein, we theoretically and experimentally demonstrate a universal method for depth prediction of phantom lesions labeled with surface‐enhanced Raman scattering nanotags in thick biological tissues using ratiometric transmission Raman spectroscopy (TRS). We begin by highlighting the linear relationship between the natural logarithm of Raman peak‐to‐peak ratio and the lesion depth and establishing a home‐built TRS system with the clinically safe irradiance. We achieve an accurate depth prediction for phantom lesions hidden in 6‐cm‐thick ex vivo homogeneous tissue with a root mean squared error (RMSE) as low as 2.42%. Additionally, we predict the depth of phantom lesions buried in 5‐cm‐thick ex vivo heterogeneous tissues with an RMSE of down to 8.35%. We also demonstrate the applicability of this method theoretically for highly heterogeneous tissues such as complex in vivo environments. This work provides a rapid, robust, and universal method to estimate the depth of lesions in complex biological samples, demonstrating the potential of ratiometric Raman spectroscopy for lesion localization in clinical applications.

Non‐Invasive Detection, Precise Localization, and Perioperative Navigation of In Vivo Deep Lesions Using Transmission Raman Spectroscopy

“…Our recently proposed “ratiometric Raman spectroscopy” strategy was demonstrated to be able to estimate phantom lesion depth in ex vivo tissues. [ 21 ] The two key observations underlying the strategy are: 1) Raman intensity decays exponentially in tissues, and 2) photons with different wavelengths have different effective attenuation coefficients in tissue and thus different exponential decay rates. Therefore, there is a linear relationship between the natural logarithm of the intensity ratio of two Raman peaks and the light propagation distance, that is, lesion depth.…”

Locating Three-Dimensional Position of Deep-Seated SERS Phantom Lesions in Thick Tissues Using Tomographic Transmission Raman Spectroscopy

“…Second, we built this spatial locating model based on uniform tissue, but this is uncommon in a practical clinical scenario. To remedy this, the prediction method proposed in this work could be further extended to that of highly complex heterogeneous tissues using the approach that we have recently reported for the prediction of lesion depth in heterogeneous ex vivo tissues using multiple Raman peak pairs . This is achieved by constructing an overdetermined system of all the deep prediction results for each PPR.…”

“…To remedy this, the prediction method proposed in this work could be further extended to that of highly complex heterogeneous tissues using the approach that we have recently reported for the prediction of lesion depth in heterogeneous ex vivo tissues using multiple Raman peak pairs. 44 This is achieved by constructing an overdetermined system of all the deep prediction results for each PPR. Applying this method for spatial positioning in a nonuniform heterogeneous model is our next goal.…”

“…We find that the Raman spectral peak ratio is related to the straight-line distance of Raman photon propagation in tissues. 44 There is a linear relationship between the natural logarithm of the Raman spectral peak ratio and this distance, making it possible to predict the distance to a lesion tagged by SERS NPs. Based on this, a two-step tomographic TRS strategy is proposed.…”

“…Our work of our group is built upon theoretical simulations of Raman photon propagation in tissues. We find that the Raman spectral peak ratio is related to the straight-line distance of Raman photon propagation in tissues . There is a linear relationship between the natural logarithm of the Raman spectral peak ratio and this distance, making it possible to predict the distance to a lesion tagged by SERS NPs.…”