*Important notice: This news reports on an unedited version of the paper which has been accepted. and is awaiting final editing. Scientific Reports sometimes publishes preliminary scientific reports that are not fully edited and, therefore, should not be regarded as conclusive or treated as established information.
A reflectance spectroscopy model enables non-contact tissue analysis with high accuracy. It eliminates probe-induced errors, enabling reliable biochemical mapping for medical imaging and diagnostic applications.
Study: Quantitative model for imaging single fiber reflectance spectroscopy. Image Credit: PeopleImages/Shutterstock
Researchers have developed a high-precision framework for assessing tissue health without needing any physical contact. Their study, published in the journal Scientific Reports, introduced a quantitative model for imaging single-fiber reflectance spectroscopy (iSFR).
The approach achieved a median prediction error of 6.2%, demonstrating that light-based analysis can deliver accurate results without direct contact. This enables reliable extraction of biochemical information while overcoming limitations of traditional fiber-optic probes.
Mechanisms of Light Interaction in Tissue Analysis
Reflectance spectroscopy analyzes how light interacts with tissues. As light penetrates tissue, it is absorbed and scattered, providing insights into blood volume, oxygenation, and structural changes due to disease. Traditional single-fiber reflectance (SFR) uses a single fiber to deliver and collect light, requiring direct contact with the tissue. This contact can compress the site, altering blood flow and optical properties, thereby reducing accuracy.
To address these challenges, researchers developed iSFR, which utilizes external optics to project light onto tissue from a distance. This non-contact configuration avoids pressure-related errors and allows for scanning larger surfaces. However, it introduces challenges, such as accounting for the air-tissue interface, which affects how light returns to the detector. Advanced modeling techniques are required to optimize light collection angles.
New Computational Techniques for Light Simulation
Researchers developed a computational pipeline to simulate light transport in the subdiffuse regime, where scattering is limited and standard models are less reliable. They employed a graphical processing unit (GPU) accelerated Monte Carlo eXtreme (MCX) software to track millions of high-speed photon paths. A key innovation was the single-integral approximation (SIA), which simplifies calculations by focusing on the radial distance between light entry and exit points. This significantly reduces computation time across various probe geometries.
The simulations covered a wide range of configurations, with numerical apertures ranging from 0.01 to 0.22 for iSFR and up to 0.50 for conventional SFR. Spot sizes varied from 0.1 mm to 2.5 mm to ensure compatibility with different imaging systems.
To reflect biological variability, three scattering models were included, such as the two-term Henyey-Greenstein and Reynolds-McCormick phase functions. Photon path lengths were stored to enable post-processing using the microscopic Beer-Lambert law. This allowed scientists to evaluate absorption effects without rerunning simulations for each tissue.
iSFR Performance Against Traditional Methods
The study demonstrated that the iSFR model closely matches established contact-based methods. When tested against a dataset of 1.1 million parameter combinations, it achieved a median absolute error of 6.2%. In comparison, the conventional SFR model showed a 4.2% error, indicating comparable accuracy. About 73% of iSFR predictions remained within a 10% error margin, showcasing stability across varying optical properties of the tissue.
The model also showed strong “inverse” performance. Using simulated data from skin and soft tissue, it successfully recovered scattering and absorption coefficients with approximately 10% accuracy. Performance remained stable under realistic noise conditions, maintaining accuracy even with noise levels up to 3%. These results confirm that the fiber-optic spectroscopy principles can be effectively utilized in free-space imaging systems.
Clinical Applications and Integration of iSFR
The findings have significant implications for advanced imaging. The non-contact iSFR model can be integrated into existing surgical and endoscopic systems without disrupting sterile conditions or tissue integrity. In cancer surgery, this method can provide real-time mapping of tissue oxygenation and blood volume, helping surgeons create a "biochemical map" that is invisible to the naked eye and reducing the need for multiple follow-up biopsies.
The model is also compatible with Optical Coherence Tomography (OCT). It has been validated for low numerical apertures down to 0.01. By combining iSFR with OCT, medical devices could enable simultaneous structural imaging and biochemical analysis, particularly useful for Barrett’s esophagus and lung cancer, where tissue structure and function are key.
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Expanding the Scope of Optical Mapping
In summary, this study presents a validated framework for quantitative reflectance spectroscopy in a non-contact format. By optimizing the model for the air-tissue interface, it effectively bridges point-based fiber measurements with wide-area spectral imaging. The model performs accurately across various optical conditions and system designs, eliminating inconsistencies caused by operator pressure and mechanical deformation of the tissue.
Future work should focus on extending the model to more complex tissue structures, such as multilayered tissues and a broader range of biological chromophores. By providing an open-source implementation, researchers encourage further development by the scientific community, supporting the advancement of fast, safe, and fully non-contact “optical biopsy”.
Journal Reference
Zutphen, R.v., Leeuwen, T.G.v. & Attendu, X. (2026). Quantitative model for imaging single fiber reflectance spectroscopy. Sci Rep. DOI: 10.1038/s41598-026-48855-y, https://www.nature.com/articles/s41598-026-48855-y
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