## 3 Results
### PLS-DA Classification Models
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Model**} & \multirow{2}{*}{**Model phase**} & \multirow{2}{*}{**Class**} & \multirow{2}{*}{**Sensitivity**} & \multirow{2}{*}{**Specificity**} & \multicolumn{2}{c}{**Number of**} & \multirow{2}{*}{**Error Rate**} & \multirow{2}{*}{**Precision**} & \multirow{2}{*}{**Accuracy**} \\ \cline{5-8} \cline{8-10}  & & & MS biceps & 1 & 1 & 458 & 0 & 1 & 1 \\ \cline{3-8}  & & & Normal biceps & 1 & 1 & 452 & 0 & 1 & 1 \\ \cline{3-8}  & & & Normal biceps & 1 & 1 & 458 & 0 & 1 & 1 \\ \cline{3-8}  & & & Normal biceps & 1 & 1 & 452 & 0 & 1 & 1 \\ \cline{3-8}  & & & MS biceps & 1 & 1 & 192 & 0 & 1 & 1 \\ \cline{3-8}  & & & Normal biceps & 1 & 1 & 198 & 0 & 1 & 1 \\ \hline \multirow{4}{*}{**Model phase**} & \multirow{4}{*}{**CV**} & \multirow{4}{*}{**CV**} & MS Triceps & 1 & 1 & 452 & 0 & 1 & 1 \\ \cline{3-8}  & & & Normal triceps & 1 & 1 & 458 & 0 & 1 & 1 \\ \cline{3-8}  & & & Normal triceps & 1 & 1 & 458 & 0 & 1 & 1 \\ \cline{3-8}  & & & MS Triceps & 1 & 1 & 198 & 0 & 1 & 1 \\ \cline{3-8}  & & & Normal triceps & 1 & 1 & 192 & 0 & 1 & 1 \\ \hline \multirow{4}{*}{**Model phase**} & \multirow{4}{*}{**CV**} & \multirow{4}{*}{**CV**} & MS cortical & 1 & 1 & 182 & 0 & 1 & 1 \\ \cline{3-8}  & & & Normal cortical & 1 & 1 & 182 & 0 & 1 & 1 \\ \cline{3-8}  & & & Normal cortical & 1 & 1 & 182 & 0 & 1 & 1 \\ \cline{3-8}  & & & MS cortical & 1 & 1 & 182 & 0 & 1 & 1 \\ \cline{3-8}  & & & MS cortical & 1 & 1 & 182 & 0 & 1 & 1 \\ \cline{3-8}  & & & MS cortical & 1 & 1 & 78 & 0 & 1 & 1 \\ \cline{3-8}  & & & Normal cortical & 1 & 1 & 78 & 0 & 1 & 1 \\ \hline \multirow{4}{*}{**Model phase**} & \multirow{4}{*}{**CV**} & \multirow{4}{*}{**CV**} & MS brainstem & 1 & 1 & 186 & 0 & 1 & 1 \\ \cline{3-8}  & & & Normal brainstem & 1 & 1 & 186 & 0 & 1 & 1 \\ \cline{3-8}  & & & Normal brainstem & 1 & 1 & 186 & 0 & 1 & 1 \\ \cline{3-8}  & & & Normal brainstem & 1 & 1 & 178 & 0 & 1 & 1 \\ \cline{3-8}  & & & Normal brainstem & 1 & 1 & 178 & 0 & 1 & 1 \\ \cline{3-8}  & & & MS brainstem & 1 & 1 & 74 & 0 & 1 & 1 \\ \cline{3-8}  & & & Normal brainstem & 1 & 1 & 82 & 0 & 1 & 1 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Statistical metrics derived from PLS-DA models for extracranial sites (biceps and triceps) and cranial sites (cortex and brainstem). Model evaluation was performed during the calibration (C), cross-validation (CV), and prediction (P) phases. Table 3 shows the key VIP score peaks derived from the PLS-DA models. At the cortical site, relevant peaks occur at 1050 nm (indicative of second overtone C-H vibrations linked to lipids and proteins [23,24]), 1500 nm (associated with a combination band of C-H and N-H stretching, as well as O-H overtones, commonly found within protein and water content in tissue [23,24]), 1900-2000 nm (related to water and, partially, amide group absorptions [3,23,24]), and 2200-2250 nm (corresponding to O-H, N-H, and C-H combination bands, vibrations, which are linked to proteins, amide groups, and lipids, respectively [3,23,25]). For the brainstem site, key spectral regions include peaks around 1300 nm (that corresponds to the first overtone of O-H stretching and is sensitive to water and hydroxyl-rich compounds [24]), 1800 nm (that captures water and some C-H stretching modes, possibly indicating biochemical variation in hydration and lipid content [3,24]), 2200 nm, and 2300 nm (representing combination bands involving C-H, N-H, and O-H groups, corresponding to complex molecular vibrations in proteins, lipids, and residual water [3,23,25]),  
Figure 8: VIP score plots for “MS cortical/Normal cortical” (**a**) and “MS brainstem/Normal brainstem” (**b**). Figure 7: VIP score plots for “MS biceps/Normal biceps” (**a**) and “MS triceps/Normal triceps” (**b**). which align with molecular absorptions characteristic of biochemical changes in this brain region. These spectral features provide critical insight into the biochemical variations between different tissue types, reinforcing the efficacy of the PLS-DA classification models.