Oral cancer is among the most common cancers of the head and neck. Despite advancements in targeted cancer therapy, the survival rates of oral cancer patients have plateaued over the last 50 years. Common screening methods for oral lesions, such as visual inspection and palpation of tissue surfaces, are highly dependent on the experience of clinicians. Even if the biopsy or histopathological examination is performed for highly suspicious tissue regions, the limitations of time-consuming, invasive, and label-intensive are still inevitable. In clinical practice, intraoperative frozen section biopsies for surgical margins are routine procedures performed after en bloc resections of oral cancers. However, surgical margins are usually selected according to surgeon estimates of sites that may be suspicious of inadequate resection, resulting in the omission of positive margins. In addition, early detection of oral cancer plays a critical role in improving the prognosis and survival rate, but, accurate identification is difficult based on conventional screening methods.
To improve the clinical diagnosis of oral diseases, researchers have conducted numerous studies on auxiliary diagnostic techniques, including X-ray computed tomography (X-CT), magnetic resonance imaging (MRI), ultrasound imaging (UI), fluorescence imaging (FI), photoacoustic imaging (PAI), and optical coherence tomography (OCT). Based on the associated imaging theories, different imaging technologies have unique advantages in terms of detecting oral diseases, resulting in different application scenarios. In this paper, we review the research on the foregoing auxiliary imaging technologies, summarize their advantages and disadvantages, and discuss the challenges and future developments in oral clinical applications.
Different technologies demonstrate different features in terms of improving diagnostic sensitivity, specificity, resolution, and so on. Notably, X-CT and MRI are the earliest techniques used in oral clinics. They are exceptional in terms of their imaging depth and can evaluate bone invasion and the thicknesses of oral cancers.
In recent years, with improvements in ultrasonic technology, the imaging resolution of UI using ultra-high-frequency ultrasound (30-100 MHz) has considerably improved. Such improved resolutions facilitate the observations of smaller microstructures (approximately 30 μm in size) of oral tissues. One recent study demonstrated that diagnostic sensitivity, specificity, and negative predictivity with values of over 90% were achieved in 150 patients with oral soft tissue lesions using an ultra-high UI system. In addition, Doppler ultrasound plays a major role in evaluating the neovascularization of oral neoplasms and metastatic lymph nodes by obtaining blood flow information (Fig. 3).
Advancements in FI, including both auto- and extrinsic fluorescence, have enabled the exploitation of molecular information. Interestingly, autofluorescence of the oral epithelium and submucosa can be generated by laser excitation at 400-460 nm, which can then be used to identify oral lesions derived from changes in the concentration and properties of fluorophores. In contrast to benign oral mucosal lesions, malignant lesions are associated with autofluorescence loss. However, several benign lesions also exhibit fluorescence decay, resulting in low specificity. Through the continual exploration of fluorescent dyes and targeted tumor biomarkers, FI can achieve higher specificity in the detection of oral tumors.
PAI is an imaging technology that has undergone developments in recent years and is based on the photoacoustic effect. Combining the advantages of optics and ultrasound, this technique has technical advantages in detecting oral tumor neovascularization (Fig. 5).
OCT, which is a high-resolution, non-destruction, and label-free method, has been successfully used in ophthalmology, cardiology, and gastroenterology. Moreover, the feasibility of OCT in distinguishing different oral tumors has been verified (Fig. 6). In addition, for the early detection of oral cancer, OCT has been used to detect different types of oral mucosal leukoplakia (Fig. 7).
To facilitate oral clinical studies, PAI and OCT are also undergoing rapid developments in terms of system miniaturization. In recent years, researchers have developed various miniaturized probes for oral imaging (Fig. 9).
To compensate for the shortcomings of single-imaging techniques, multi-modal systems combining multiple diagnostic techniques have also been developed.
With visual observations or qualitative analysis, misdiagnosis is inevitable. To improve the accuracy of image recognition and reduce the time cost associated with image reading, quantitative analysis and artificial intelligence approaches based on oral tissue images have been widely studied with the aim of extracting rich information from images (Fig. 10).
Imaging technologies with non-destruction, high resolution, high sensitivity, high specificity, and real-time will play a critical role in assisting clinicians in screening and diagnosing oral cancers. Owing to the unique characteristics of different imaging techniques, their clinical application scenarios are different. Single-imaging techniques cannot completely satisfy all the requirements of oral disease diagnoses. Therefore, combining multiple imaging techniques to construct a multi-modal system can provide more abundant diagnostic information. In addition, quantitative and AI-based computer-aided methods that can provide objective screening and diagnostic results are expected to be developed.
