Effect of Source-Detector Distance on the Measurement of Hemoglobin Using Near-Infrared Spectroscopy in Breast Cancer

Water and lipid content of breast tissue measured by six-wavelength time-domain diffuse optical spectroscopy

SIGNIFICANCE

The water and lipid content of normal breast tissue showed mammary gland characteristics with less influence from the chest wall using six-wavelength time-domain diffuse optical spectroscopy (TD-DOS) in a reflectance geometry.

AIM

To determine the depth sensitivity of a six-wavelength TD-DOS system and evaluate whether the optical parameters in normal breast tissue can distinguish dense breasts from non-dense breasts.

APPROACH

Measurements were performed in normal breast tissue of 37 breast cancer patients. We employed a six-wavelength TD-DOS system to measure the water and lipid content in addition to the hemoglobin concentration. The breast density in mammography and optical parameters were then compared.

RESULTS

The depth sensitivity of the system for water and lipid content was estimated to be ∼15 mm. Our findings suggest that the influence of the chest wall on the water content is weaker than that on the total hemoglobin concentration. In data with evaluation conditions, the water content was significantly higher (p < 0.001) and the lipid content was significantly lower (p < 0.001) in dense breast tissue. The water and lipid content exhibited a high sensitivity and specificity to distinguish dense from non-dense breasts in receiver-operating-characteristic curve analysis.

CONCLUSIONS

With less influence from the chest wall, the water and lipid content of normal breast tissue measured by a reflectance six-wavelength TD-DOS system, together with ultrasonography, can be applied to distinguish dense from non-dense breasts.

A novel spatially resolved interactance spectroscopy system to estimate degree of red coloration in red-fleshed apple

Reliable information about degree of red coloration in fruit flesh is essential for grading and sorting of red-fleshed apples. We propose a spatially resolved interactance spectroscopy approach as a new rapid and non-destructive technique to estimate degree of red coloration in the flesh of a red-fleshed apple cultivar 'Kurenainoyume'. A novel measurement system was developed to obtain spatially resolved interactance spectra (190-1070 nm) for apple fruits at eight different light source-detector separation (SDS) distances on fruit surface. Anthocyanins in apple were extracted using a solvent extraction technique, and their contents were quantified with a spectrophotometer. Partial least squares (PLS) regression analyses were performed to develop estimation models for anthocyanin content from spatially resolved interactance spectra. Results showed that the PLS models based on interactance spectra obtained at different SDS distances achieved different predictive accuracy. Further, the system demonstrated the possibility to detect the degree of red coloration in the flesh at specific depths by identifying an optimal SDS distance. This might contribute to provide a detailed profile of the red coloration (anthocyanins) that is unevenly distributed among different depths of the flesh. This new approach may be potentially applied to grading and sorting systems for red-fleshed apples in fruit industry.

Methylglyoxal Adducts Levels in Blood Measured on Dried Spot by Portable Near-Infrared Spectroscopy

The altered glucose metabolism characterising cancer cells determines an increased amount of methylglyoxal in their secretome. Previous studies have demonstrated that the methylglyoxal, in turn, modifies the protonation state (PS) of soluble proteins contained in the secretomes of cultivated circulating tumour cells (CTCs). In this study, we describe a method to assess the content of methylglyoxal adducts (MAs) in the secretome by near-infrared (NIR) portable handheld spectroscopy and the extreme learning machine (ELM) algorithm. By measuring the vibration absorption functional groups containing hydrogen, such as C-H, O-H and N-H, NIR generates specific spectra. These spectra reflect alterations of the energy frequency of a sample bringing information about its MAs concentration levels. The algorithm deciphers the information encoded in the spectra and yields a quantitative estimate of the concentration of MAs in the sample. This procedure was used for the comparative analysis of different biological fluids extracted from patients suspected of having cancer (secretome, plasma, serum, interstitial fluid and whole blood) measured directly on the solute left on a surface upon a sample-drop cast and evaporation, without any sample pretreatment. Qualitative and quantitative regression models were built and tested to characterise the different levels of MAs by ELM. The final model we selected was able to automatically segregate tumour from non-tumour patients. The method is simple, rapid and repeatable; moreover, it can be integrated in portable electronic devices for point-of-care and remote testing of patients.