# Ultrasound and Magnetic Resonance Imaging of the Tongue in Obstructive Sleep Apnoea
## 3 Results
### Prediction of OSA and Tongue-Based Obstruction  
The precision of the algorithm to detect patients with OSA, based on MRI and US measurements of the tongue, is summarised in Table 7. Prediction of tongue-based obstruction using USA measurements is presented in Table 8.  
The results of the algorithm indicate that the tongue parameters can be helpful in categorising patients with OSA and tongue-based obstruction (Table 7). The sensitivity of the algorithm in the prognostication of OSA was defined as 84% for US, 79% for MRI, and 91% specificity for both methods, using quadratic discriminant analysis. No significant differences were detected between the specificities and sensitivities of the two methods in diagnosing patients with OSA. However, in the classification of obstruction, the sensitivity \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Tongue Parameters**} & \multicolumn{3}{c}{**BMI (kg/m2)**} \\ \cline{2-5}  & **Normal [A]** & **Overweight [B]** & **Obese [C]** & \multirow{2}{*}{_p-Value_} \\  & **(n = 5)** & **(n = 24)** & **(n = 35)** & \\ \hline \multirow{2}{*}{Anteroposterior diameter (cm)} & \multirow{2}{*}{6.97 \(\pm\) 0.40} & \multirow{2}{*}{7.68 \(\pm\) 0.58} & \multirow{2}{*}{7.75 \(\pm\) 0.66} & 0.0365 ** \\  & & & & [A–C] \\ \hline \multirow{2}{*}{Sagittal diameter (cm)} & \multirow{2}{*}{4.92 \(\pm\) 0.26} & \multirow{2}{*}{5.01 \(\pm\) 0.38} & \multirow{2}{*}{5.27 \(\pm\) 0.48} & 0.0366 ** \\  & & & & [A–C] \\ \hline \multirow{2}{*}{Volume (cm\({}^{3}\))} & \multirow{2}{*}{57.60 \(\pm\) 9.90} & \multirow{2}{*}{64.94 \(\pm\) 10.58} & \multirow{2}{*}{69.76 \(\pm\) 13.42} & 0.0738 * \\  & & & & [A–C] \\ \hline \multirow{2}{*}{Area midsagittal (cm\({}^{2}\))} & \multirow{2}{*}{25.05 \(\pm\) 1.76} & \multirow{2}{*}{27.72 \(\pm\) 2.97} & \multirow{2}{*}{28.70 \(\pm\) 3.45} & 0.054 * \\  & & & & [A–C] \\ \hline \end{tabular}
\end{table} 
Table 5: MRI parameters of the tongue depending on BMI values. Parameters show the mean \(\pm\) SD values. ** indicates the significant difference at \(p\) ¡ 0.05 level and ** the significant difference at \(p\) ¡ 0.1 Only the significantly different parameters are shown in the table. differed significantly (94% for US and 56% for MRI). The US has given a false OSA diagnosis in 9%, while MRI in 18%. To detect the possible location of the obstruction, the US imaging result was incorrect in 11% of cases, whereas the MRI results were incorrect in 13%. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Dependent Variables** & \multicolumn{2}{c}{**Gender**} \\ \hline  & **Men (n = 74)** & **Women (n = 26)** \\ \hline
**US tongue parameters** & **r2** & **r2** \\ \hline Coronal diameter (cm) & 0.28 *** & 0.7 *** \\ \hline Axial diameter (cm) & 0.31 *** & 0.75 *** \\ \hline Sagittal diameter (cm) & 0.30 *** & 0.62 *** \\ \hline Volume (cm\({}^{3}\)) & 0.32 *** & 0.69 *** \\ \hline Coronal diameter during MM (cm) & 0.29 *** & 0.71 *** \\ \hline Axial diameter during MM (cm) & 0.33 *** & 0.59 *** \\ \hline Sagittal diameter during MM (cm) & 0.35 *** & 0.55 *** \\ \hline Volume during MM (cm\({}^{3}\)) & 0.34 *** & 0.5 *** \\ \hline
**MRI tongue parameters** & **r2** & **r2** \\ \hline Anteroposterior diameter (cm) & 0.328 *** & 0.73 *** \\ \hline Sagittal diameter (cm) (s) & 0.32 *** & 0.77 *** \\ \hline Axial diameter (cm) (l) & 0.33 *** & 0.65 *** \\ \hline Coronal diameter (cm) (l) & 0.37 *** & 0.72 *** \\ \hline Volume (cm\({}^{3}\)) (l) & 0.41 *** & 0.712 *** \\ \hline Area midsagittal (cm\({}^{2}\)) (l) & 0.42 *** & 0.463 *** \\ \hline Fat midsagittal (cm\({}^{2}\)) (l) & 0.422 *** & 0.410 *** \\ \hline Fat\% (l) & 0.241 *** & 0.253 *** \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Correlation between BMI (as an independent variable) and the US and MRI parameters of the tongue (as dependent variables) in male and female patients. Parameters show the r2 (determination coefficient) values *** indicates the significant difference at \(p<0.01\) level, (l) linear estimation and (s) sigmoid estimation.