Infrared thermal modulation endoscopy for label-free tumor detection

Abstract

In optical imaging of solid tumors, signal contrasts derived from inherent tissue temperature differences have been employed to distinguish tumor masses from surrounding tissue. Moreover, with the advancement of active infrared imaging, dynamic thermal characteristics in response to exogenous thermal modulation (heating and cooling) have been proposed as novel measures of tumor assessment. Contrast factors such as the average rate of temperature changes and thermal recovery time constants have been investigated through an active thermal modulation imaging approach, yielding promising tumor characterization results in a xenograft mouse model. Here, to assess its clinical potential, we developed and deployed an endoscopic infrared thermal modulation imaging system, incorporating anti-reflection germanium lenses. Employing tissue cooling, we evaluated the feasibility of detecting in situ tumors in a syngeneic rectal tumor mouse model. Consequently, early-stage tumors were successfully localized and evaluated based on their heat signatures. Notably, tumors exhibited a higher rate of temperature change induced by thermal modulation compared to adjacent tissues. Through the introduction of this label-free technology, Infrared Thermal Modulation Endoscopy (ITME), our study showcased an effective method for optically delineating and assessing solid tumors. This innovative diagnostic technology holds significant promise for enhancing our ability to detect, classify, and characterize abnormal tissues.

Keywords: Infrared imaging; Rectal tumor model; Thermal contrast; Thermal endoscopy; Thermal modulation; Tumor detection.

Fig. 1

Schematic of the thermal endoscopic imaging system. (a) The experimental setup for thermal endoscopy. (b) Evaluation result of the temperature sensing ability of the ITME. (c) IR images of the 0.1 mm pinhole attached to a heating pad. Two colormaps (gray and jet) from MATLAB are utilized. Scale bar: 0.2 mm. (d) X and Y-axis line profiles of 0.1 mm pinhole images including (c) (gray). The averaged FWHM of the X and Y-axes is calculated from 15 line profiles of each axis. (green and orange). (e) Conceptual diagram illustrating temperature changes in tumor and neighboring tissues during thermal modulation (cooling).

Fig. 2

Thermal contrast imaging using convectional thermal modulation on a subcutaneous tumor mouse model. (a) Schematic representation of imaging subcutaneous tumor mouse model. (b) Comparative visualization of the tumor under white-light (WL) imaging, fluorescence (FL) imaging, and their superimposed image. (c)-(d) IR imaging results during convectional heating. (c) Temperature dynamics in the tumor versus neighboring tissue over time during heating. (d) Sequential IR images captured at 0, 20, and 60 s, showing temperature distribution. (e)-(f) IR thermal imaging results during convectional cooling. (e) Temperature dynamics over time in tumor and neighboring areas during cooling. (f) IR images showing the cooling process recorded at the same intervals as heating.

Fig. 3

Quantitative analysis of thermal contrast parameters in subcutaneous tumor model. The parameters were obtained through convectional heating (a-c) and cooling (d-f) modulation. Panels (a) and (d) display the rate of temperature changes in the tumor and neighboring tissue during thermal modulation. Panels (b) and (e) show the thermal recovery time constants for tumor (τ_T) and neighboring tissues (τ_N) post-modulation. Panels (c) and (f) compare the temperature differentials between tumor and neighboring tissues during passive (∆T_P) and active (∆T_A) thermal imaging. Error bars represent standard deviations calculated from all ROI data. Statistical significance is denoted as follows: ** indicates p < 0.01 and *** indicates p < 0.001.

Fig. 4

Assessment of thermal modulation imaging with convectional cooling to detect early-stage mouse rectal tumors. (a) Schematic of the imaging procedure for a rectal tumor in a mouse. (b) Visual differentiation of the tumor under white-light (WL) and fluorescence (FL) imaging. (c)-(d) IR imaging results following convectional cooling: (c) Temperature trajectories in tumor and neighboring tissues during cooling. (d) IR images captured at 0, 20, and 60 s, illustrating temporal thermal changes. (e)-(g) Quantitative analysis of the thermal contrast parameters: (e) The rate of temperature changes. (f) The thermal recovery time constants for tumor (τ_T) and neighboring tissues (τ_N) post-thermal modulation. (g) Differential temperature analysis between tumor and neighboring tissues under passive (∆T_P) and active (∆T_A) thermal conditions. Error bars represent standard deviations from all the ROI data. Statistical significance is denoted by *: p < 0.05.