## 5 Applications
### In Vivo Characterization of Biological Tissues
The scattering spectra can be modeled with just two parameters (\(a\) and \(b\)), while the absorption should generally provide information on (at least) 5 constituents for thorough tissue characterization. Thus, measurements need to be performed at least at (at least) 7 distinct wavelengths, spread over a broad spectral range, including marked absorption features of all the constituents of interest (i.e., 600 to 800 nm for blood, and including the range of 900 to 1100 nm for water, lipids, and collagen). The acquisition of the full spectrum provides more robust results, but satisfactory outcomes can be obtained even from data collected at a small set of wavelengths (7), provided that \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{5}{c}{**Tissue Composition**} & \multicolumn{5}{c}{**Scattering Parameters**} \\ \cline{2-7}
**Breast Type** & **tHb (\(\mu\)M)** & **SO\({}_{2}\) (\%)** & **Lipid** & **Water** & **Collagen** & **a (cm\({}^{-1}\))** & **b** \\ \hline Adipose & \(10.0\pm 1.2\) & \(71\pm 10\) & \(737\pm 52\) & \(111\pm 15\) & \(24\pm 5\) & \(13.4\pm 2.0\) & \(0.69\pm 0.28\) \\ Mixed & \(24.1\pm 2.0\) & \(84\pm 1\) & \(428\pm 24\) & \(302\pm 80\) & \(60\pm 1\) & \(16.1\pm 0.5\) & \(0.71\pm 0.03\) \\ Fibrous & \(24.3\pm 1.8\) & \(80\pm 1\) & \(173\pm 56\) & \(615\pm 40\) & \(107\pm 22\) & \(17.6\pm 1.1\) & \(1.16\pm 0.09\) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Inter-subject variability of breast tissue composition [125]. Figure 13: (**a**) Absorption and (**b**) reduced scattering spectra measured in vivo from breasts of different types, highlighting the marked inter-subject variability of this tissue [125]. global data fitting with spectral constrains is performed [113]. Actually, using that spectral approach, optically derived tissue parameters were effectively used in the discrimination between malignant and benign breast lesions [13], in the optical measurement of breast density (important risk factor for developing cancer [134]), and in the identification of women at high risk for their high breast density [123]. The knowledge of the optical properties of the human head is quite valuable for the development of non-invasive optical technologies that aim at imaging or monitoring brain functions or injuries. Understanding the biological variability in the optical properties of head layers (scalp-skull, gray matter, cerebrospinal fluid, white matter) is beneficial for setting up simulation scenarios, optimizing existing technologies, analyzing actual measurements with a priori information (e.g., on the optical pathlength). Figure 14 shows the results of a multilaboratory exercise where 3 different approaches--namely a multi-distance CW system, a 5-wavelength time-resolved instrument, and a broadband TD-DOS workstation--were challenged in retrieving the optical properties of the forehead of 9 subjects [135]. In particular, the broadband TD-DOS system (blue squares) was the only one apt to cover a wide spectral range (600-1100 nm), thus revealing the clear contribution of lipids and water to tissue absorption. The broadband TD-DOS data were analyzed using a homogeneous solution of the diffusion equation. Simulations highlighted that the spatial region determining the retrieved parameters is the brain for what concerns the absorption, and the skull for the scattering. In the case of the few-wavelength TD-DOS system, exploiting a multi-distance approach and longer time-per-wavelength acquisition, it was also possible to apply a two-layer model, to disentangle the scalp-skull properties (black circles) from the brain properties (gray circles). The feasibility to apply heterogeneous models is certainly of great interest also for broadband spectroscopy, with the aim to describe biological tissues more accurately and with higher informative content. Key challenges are surely the strong light attenuation above 900 nm, which limits, in particular, the availability of long-lived (>1 ns) photons carrying information from deeper structures (brain).