# Quantitative Ultrasound Analysis of Oral Mucosa: An Observational Cross-Sectional Study
## 4 Discussion  
The primary concern in evaluating the precision of an imaging technique is the level to which that procedure corresponds directly with histopathology. The ultrasonic images differentiate the tumor from the surrounding tissues in oral squamous cell carcinoma. Furthermore, the tumor's thickness is strongly correlated with the values obtained with ultrasound scanning and histological sections [20]. Magnetic resonance (MRI) and computed tomography (CT) represent the diagnostic imaging techniques of choice. However, these are expensive, and in the case of CT, the patient is exposed to a dose of radiation. Moreover, ultrasonography would have greater dimensional accuracy for oral squamous cell carcinoma at early stages with a thickness <5 mm [28]. A meta-analysis of studies correlating US tumor thickness (TT) measurements to histopathology concluded that US measures are highly accurate and only slightly over  
Figure 2: Histograms and heatmap showing the comparisons between groups; 95% C.I. is represented; ns = not significant; asterisk = the mean difference is statistically significant (\(p\)\(\leq\) 0.01). (**a**) Echo intensity comparison between groups. (**b**) Greyscale analysis between groups. (**c**) Relative attenuation (mean difference) between groups. (**d**) The heatmap shows the average of the ultrasound intensity variations, in grayscale, among the tissue layers in each analyzed case. estimate TT values [29]. Another review reaffirmed the relationship of US and TT with histopathologic TT. Further, it examined the potential utility of different US parameters in oral tongue cancer management and the use of US as an intraoperative adjunct to resection [30]. The high diagnostic accuracy of US could also be helpful in the diagnosis of hyperplastic pathologies or other non-neoplastic lesions [31]. The major technical limitation of intraoral US is when large or posterior lesions are present, mainly due to difficulty in accessing the posterior tongue with a probe and the induction of vomiting [32]. However, based on the experience of the authors of this work, a probe with a T shape or hockey stick shape has ergonomic advantages, such as being able to cover most areas of the oral cavity, especially when compared with a classic linear one that does not have any angle but has the same handle thickness and scanning area. As an intrinsic limit of this technique, intraoral US is a strongly operator-dependent live examination: consequently, different radiologists with variable experiences may register different information [33]. To our knowledge, this is the first work to analyze the oral mucosa with ultrasonography from a quantitative point of view. For this exploratory study, the healthy mucosa was studied to lay the foundations for subsequent radiomics studies involving groups of patients with oral mucosal diseases. This type of study is already advanced in other areas of medicine, such as thyroid cancer, skeletal muscle pathologies, and breast cancer [24; 25; 34; 35]. In the latter area, artificial intelligence systems are already present that recognize and classify lesions and have good approximations in terms of sensitivity and specificity [24]. The advantages of the clinical application of the quantitative analysis of ultrasounds and attenuation values are especially in ultrasound diagnostic improvement, which is still strongly operator-dependent [33]. Other studies have applied ultrasonography to analyze tissue interfaces in healthy mucosa and oral pathologies [18; 23]. These studies laid the basis for defining tissue layers based on their echogenicity. Some have attributed grayscale values to the images, such as [PERSON] et al. [36]. These authors used a high-frequency ultrasound (70 Mhz--HFUS) to define the tissue layers of the healthy mucosa. They assigned to each pixel a variable value encoded with a number between 0 and 256 using Horos software, which automatically samples the distribution of the gray level within a selected region of interest (ROI).