Effect of bile absorption coefficients on the estimation of liver tissue optical properties and related implications in discriminating healthy and tumorous samples

Validation of interventional fiber optic spectroscopy with MR spectroscopy, MAS-NMR spectroscopy, high-performance thin-layer chromatography, and histopathology for accurate hepatic fat quantification

OBJECTIVES

To validate near-infrared (NIR)-based optical spectroscopy measurements of hepatic fat content using a minimally invasive needle-like probe with integrated optical fibers, enabling real-time feedback during percutaneous interventions. The results were compared with magnetic resonance spectroscopy (MRS) as validation and with histopathology, being the clinical gold standard. Additionally, ex vivo magic angle spinning nuclear magnetic resonance spectroscopy and high-performance thin-layer chromatography were performed for comparison.

MATERIALS AND METHODS

Ten mice were used for the study, of which half received a regular chow diet and the other half received a high-fat diet to induce obesity and hepatosteatosis. The mice were imaged with a clinical 3-Tesla MR to select a region of interest within the right and left lobes of the liver, where MRS measurements were acquired in vivo. Subsequently, optical spectra were measured ex vivo at the surface of the liver at 6 different positions immediately after resection. Additionally, hepatic fat was determined by magic angle spinning nuclear magnetic resonance spectroscopy and high-performance thin-layer chromatography. Histopathologic analyses were performed and used as the reference standard. Pearson correlation and linear regression analyses were performed to assess the correlation of the various techniques with NIR. A 1-way analysis of variance including post hoc Tukey multiple comparison tests was used to study the difference in fat estimation between the various techniques.

RESULTS

For both the mice groups, the estimated fat fractions by the various techniques were significantly similar (P = 0.072 and 0.627 for chow diet and high-fat diet group, respectively). The Pearson correlation value between NIR and the other techniques for fat determination showed the same strong linear correlation (P above 0.990; P < 0.001), whereas for histopathologic analyses, which is a rather qualitative measure, the Pearson correlation value was slightly lower (P = 0.925, P < 0.001) . Linear regression coefficient computed to compare NIR with the other techniques resulted in values close to unity with MRS having the narrowest confidence interval (r = 0.935, 95% confidence interval: 0.860-1.009), demonstrating highly correlating results between NIR and MRS.

CONCLUSIONS

NIR spectroscopy measurements from a needle-like probe with integrated optical fibers for sensing at the tip of the needle can quickly and accurately determine hepatic fat content during an interventional procedure and might therefore be a promising novel diagnosing tool in the clinic.

Optical spectroscopy: current advances and future applications in cancer diagnostics and therapy

Optical spectroscopy (OS) is a tissue-sensing technique that could enhance cancer diagnosis and treatment in the near future. With OS, tissue is illuminated with a selected light spectrum. Different tissue types can be distinguished from each other based on specific changes in the reflected light spectrum that are a result of differences on a molecular level between compared tissues. Therefore, OS has the potential to become an important optical tool for cancer diagnosis and treatment monitoring. In recent years, significant progress has been made in the discriminating abilities of OS techniques between normal and cancer tissues of multiple human tissue types. This article provides an overview of the advances made with diffuse reflectance, fluorescence and Raman spectroscopy techniques in the field of clinical oncology, and focuses on the different clinical applications that OS could enhance.

Diagnosis of breast cancer using diffuse optical spectroscopy from 500 to 1600 nm: comparison of classification methods

We report on the use of diffuse optical spectroscopy analysis of breast spectra acquired in the wavelength range from 500 to 1600 nm with a fiber optic probe. A total of 102 ex vivo samples of five different breast tissue types, namely adipose, glandular, fibroadenoma, invasive carcinoma, and ductal carcinoma in situ from 52 patients were measured. A model deriving from the diffusion theory was applied to the measured spectra in order to extract clinically relevant parameters such as blood, water, lipid, and collagen volume fractions, β-carotene concentration, average vessels radius, reduced scattering amplitude, Mie slope, and Mie-to-total scattering fraction. Based on a classification and regression tree algorithm applied to the derived parameters, a sensitivity-specificity of 98%-99%, 84%-95%, 81%-98%, 91%-95%, and 83%-99% were obtained for discrimination of adipose, glandular, fibroadenoma, invasive carcinoma, and ductal carcinoma in situ, respectively; and a multiple classes overall diagnostic performance of 94%. Sensitivity-specificity values obtained for discriminating malignant from nonmalignant tissue were compared to existing reported studies by applying the different classification methods that were used in each of these studies. Furthermore, in these reported studies, either lipid or β-carotene was considered as adipose tissue precursors. We estimate both chromophore concentrations and demonstrate that lipid is a better discriminator for adipose tissue than β-carotene.