In Vivo Method for Determining the Optical Properties of Multilayer Tissues of Gastrointestinal Hollow Organs for the Personalization of Laser-Induced Therapy
Abstract
Gastrointestinal (GI) cancers account for a quarter of all cancer cases worldwide and are responsible for a third of cancer deaths. One of the characteristic features of GI tissue is its multilayered structure, which in addition to multiple scattering, complicates optical-spectral analysis. The risk of lymph node metastasis in GI cancer is primarily related to the depth of tumor invasion. The use of spectroscopic diagnostics and photodynamic therapy for the detection and treatment of GI cancer is a rapidly developing field. The method proposed in this paper for layer-by-layer optical properties assessment, suitable for real-time clinical application to the walls of hollow organs, allows for both determining the depth of tumor invasion into the GI organ wall and calculating the absorbed dose layer-by-layer. This paper proposes a method for recording spectral data in two geometries, diffuse reflectance and transmission, using light delivery from both the external and internal surfaces of the gastrointestinal tract wall. Layer-by-layer assessment of optical properties was performed using a developed algorithm based on the inverse adding-doubling method with initial optical properties values determined using the modified two-stream Kubelka-Munk model with the accuracy equal to 86±13%. The method was approbated in clinical conditions. Based on the results of the work, the developed method for assessing the optical properties of multilayered biological tissues exhibited sufficient speed and accuracy for in vivo application to personalize laser-induced therapy by correction of the laser dose.
Fields of Study & Subjects
Optical Imaging and Spectroscopy Techniques
Optical Coherence Tomography Applications
Photodynamic Therapy Research Studies
Publication details
- Journal / source
- Preprints.org
- Publisher
- MDPI AG
- Publication date
- 26 May 2026
- Document type
- Preprint