Non-Invasive Early Detection of Oral Cancers Using Fluorescence Visualization with Optical Instruments

Direct healthcare costs of oral cancer: A retrospective study from a tertiary care center

The aim of this study was to retrospectively evaluate the direct costs of OSCC treatment and postsurgical surveillance in a tertiary hospital in northeast Italy. Sixty-three consecutive patients surgically treated for primitive OSCC at S. Orsola Hospital in Bologna (Italy) between January 2018 and January 2020 were analyzed. Billing records of the Emilia Romagna healthcare system and institutional costs were used to derive specific costs for the following clinical categories: operating theatre costs, intensive and ordinary hospitalization, radiotherapy, chemotherapy, postsurgical complications, visits, and examinations during the follow-up period. The study population comprised 17 OSCC patients classified at stage I, 14 at stage II, eight at stage III, and 24 at stage IV. The estimated mean total direct cost for OSCC treatment and postsurgical surveillance was €26 338.48 per patient (stage I: €10 733, stage II: €19 642.9, stage III: €30 361.4, stage IV: €39 957.2). An advanced diagnosis (stages III and IV), complex surgical procedure, and loco-regional recurrences resulted in variables that were significantly associated with a higher cost of OSCC treatment and postsurgical surveillance. Redirection of funds used for OSCC treatment to screening measures may be an effective strategy to improve overall health outcomes and optimize national health resources.

Effectiveness of adjunctive screening tools for potentially malignant oral disorders and oral cancer: A systematic review

Background and objectives

To enhance the abilities of healthcare professionals to make informed treatment decisions and establish accurate diagnoses, it is essential to assess the diagnostic reliability of different adjunctive aids. This systematic review aimed to compare the accuracy of various adjunctive methods for diagnosing suspected oral cancer (OC) or potentially malignant oral disorders (OPMD) in adults against histopathological investigative results.

Materials and methods

The review protocol registered in the PROSPERO database (CRD42023463525) was developed in strict accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis-Diagnostic Test Accuracy checklist. A comprehensive electronic search was conducted to identify relevant research articles published between January 2014 and April 2023 using the PubMed and EBSCO databases. The research question was meticulously structured following the participants' index test, reference standard, target condition, and study setting framework. To evaluate methodological quality and assess the risk of bias (RoB), the Quality Assessment for Diagnostic Accuracy Studies-2 tool was used.

Results

An initial search yielded 483 publications, which were reduced to 278 after removal of duplicates. Finally, 85 publications underwent full-text review by two investigators, which lead to 29 studies that met the inclusion criteria. Among these, 7% had a low RoB, 72% had an unclear RoB, and 21% had a high RoB. Applicability concerns were expressed in 59% of the studies with low concern, 31% with unclear quality evidence of concern, and 10% with high concern.

Conclusion

The review findings support the use of these diagnostic methods as valuable adjuncts to biopsy for the early detection of various OPMD and OC. They also highlight the importance of regular screening and awareness in reducing the global burden of OC, while acknowledging that they cannot replace the gold standards of surgical biopsy and histopathological evaluation.

Effect of fluorescein dye concentration in oral cancer tissue: Statistical and spectroscopic analysis

Oral cancer screening with exogenous agents is highly demanding due to high sensitivity, as the early diagnosis plays a vital role in achieving favorable outcomes for oral squamous cell carcinomas (OSCC) by facilitating prompt detection and comprehensive surgical removal. Optical techniques utilizing the local application of fluorescein dye or fluorescence-guided surgery offer potential for early OSCC detection. The use of fluorescein dye in oral cancer is significantly less, and there is a need to inspect the local application of fluorescein dye in oral cancer patients. Concentration-based investigations of the dye with OSCC patients are essential to ensure accurate fluorescence-guided surgery and screening with fluorescein labeling and to mitigate possible adverse effects. Additionally, analyzing the dye distribution within OSCC tissues can provide insights into their heterogeneity, a critical indicator of malignancy. The present study includes a concentration-based statistical and spectroscopic analysis of fluorescein dye in ex-vivo and in-vivo OSCC patients. In the ex-vivo examination of OSCC tissues, five concentrations (18.66 ± 0.06, 9.51 ±    0.02, 6.38 ± 0.01, 4.80 ± 0.004, and 3.85 ± 0.002 millimolar) are employed for optical analysis. The ex-vivo OSCC tissues are analyzed for multiple statistical parameters at all concentrations, and the results are thoroughly described. Additionally, spectroscopic analysis is conducted on all concentrations for a comprehensive evaluation. Following optical analysis of all five concentrations in the ex-vivo study, two concentrations, 6.38 ± 0.01 and 4.80 ± 0.004 millimolar, are identified as suitable for conducting in-vivo investigations of oral cancer. A detailed spectroscopic and statistical study of OSCC tissues in-vivo has been done using these two concentrations.

Non-invasive detection of oral potentially malignant and malignant lesions using an optical multispectral screening device

Oral carcinogenesis is a multistep process that usually arises in the superficial epithelial layer covering the lining of the body cavities. The early changes in the oral mucosa reflect as oral precancers or oral potentially malignant disorders (OPMD). The most common OPMD are erythroplakia and leukoplakia, with their chances of malignant transformation being approximately 90% and 10%, respectively. The development of epithelial precancers is initiated through changes in nuclear shape, size, and density of cells and overall thickening of the epithelial layer. Conventional oral examination (COE) with white light is the most common technique for detection of malignant changes in the oral cavity. This often poses a diagnostic challenge for the clinicians in differentiation of normal and early malignant changes. Thus, biopsy of the site is the accepted clinical procedure for diagnosis of the lesion. A major hurdle here is to identify visually, the most malignant location for a biopsy. As the selection of a site is subjective, the chosen site may not always be representative of the disease and this often leads to repeated biopsies and discomfort to the patients. A novel device known as OralScan was recently introduced by Sascan Meditech, Thiruvananthapuram, for screening and early detection of oral cancers. The clinical application of the device in different clinical scenarios are discussed in this case series report.

Tumor Recurrence and Follow-Up Intervals in Oral Squamous Cell Carcinoma

Tumor recurrence in oral squamous cell carcinoma (OSCC) is frequent. However, no consensus about follow-up interval is available. The aim of this study was to analyze the recurrence pattern, detection method and associated parameters for possible risk stratification. Histopathological and epidemiological features were obtained retrospectively and correlated with tumor recurrence and overall survival, distant and lymph node metastases. A total of 760 patients were included, of which 216 patients showed tumor recurrence (mean after 24 ± 26 months). Within the first 12 months, 24% of the recurrences were detected. The primary detection method was clinical examination (n = 123, 57%). Tumor recurrence significantly correlated with advanced histopathological grading (G2/3 vs. G1, p < 0.000) and lymph node metastasis (p = 0.004). Tumor recurrence was frequent. Clinical examination was the primary detection method and manifestation within the first 6−12 months was high. The degree of histopathological grading may be useful for risk stratification.

Molybdenum Diphosphide Nanorods with Laser-Potentiated Peroxidase Catalytic/Mild-Photothermal Therapy of Oral Cancer

Chemodynamic therapy (CDT) is an emerging treatment that usually employs chemical agents to decompose hydrogen peroxide (H₂O₂) into hydroxyl radical (•OH) via Fenton or Fenton-like reactions, inducing cell apoptosis or necrosis by damaging biomacromolecules such as, lipids, proteins, and DNA. Generally, CDT shows high tumor-specificity and minimal-invasiveness in patients, thus it has attracted extensive research interests. However, the catalytic reaction efficiency of CDT is largely limited by the relatively high pH at the tumor sites. Herein, a 808 nm laser-potentiated peroxidase catalytic/mild-photothermal therapy of molybdenum diphosphide nanorods (MoP₂ NRs) is developed to improve CDT performance, and simultaneously achieve effective tumor eradication and anti-infection. In this system, MoP₂ NRs exhibit a favorable cytocompatibility due to their inherent excellent elemental biocompatibility. Upon irradiation with an 808 nm laser, MoP₂ NRs act as photosensitizers to efficiently capture the photo-excited band electrons and valance band holes, exhibiting enhanced peroxidase-like catalytic activity to sustainedly decompose tumor endogenous H₂O₂ to •OH, which subsequently destroy the cellular biomacromolecules both in tumor cells and bacteria. As demonstrated both in vitro and in vivo, this system exhibits a superior therapeutic efficiency with inappreciable toxicity. Hence, the work may provide a promising therapeutic technique for further clinical applications.

Role of Artificial Intelligence in the Early Diagnosis of Oral Cancer. A Scoping Review

The early diagnosis of cancer can facilitate subsequent clinical patient management. Artificial intelligence (AI) has been found to be promising for improving the diagnostic process. The aim of the present study is to increase the evidence on the application of AI to the early diagnosis of oral cancer through a scoping review. A search was performed in the PubMed, Web of Science, Embase and Google Scholar databases during the period from January 2000 to December 2020, referring to the early non-invasive diagnosis of oral cancer based on AI applied to screening. Only accessible full-text articles were considered. Thirty-six studies were included on the early detection of oral cancer based on images (photographs (optical imaging and enhancement technology) and cytology) with the application of AI models. These studies were characterized by their heterogeneous nature. Each publication involved a different algorithm with potential training data bias and few comparative data for AI interpretation. Artificial intelligence may play an important role in precisely predicting the development of oral cancer, though several methodological issues need to be addressed in parallel to the advances in AI techniques, in order to allow large-scale transfer of the latter to population-based detection protocols.

A novel lightweight deep convolutional neural network for early detection of oral cancer

OBJECTIVES

To develop a lightweight deep convolutional neural network (CNN) for binary classification of oral lesions into benign and malignant or potentially malignant using standard real-time clinical images.

METHODS

A small deep CNN, that uses a pretrained EfficientNet-B0 as a lightweight transfer learning model, was proposed. A data set of 716 clinical images was used to train and test the proposed model. Accuracy, specificity, sensitivity, receiver operating characteristics (ROC) and area under curve (AUC) were used to evaluate performance. Bootstrapping with 120 repetitions was used to calculate arithmetic means and 95% confidence intervals (CIs).

RESULTS

The proposed CNN model achieved an accuracy of 85.0% (95% CI: 81.0%-90.0%), a specificity of 84.5% (95% CI: 78.9%-91.5%), a sensitivity of 86.7% (95% CI: 80.4%-93.3%) and an AUC of 0.928 (95% CI: 0.88-0.96).

CONCLUSIONS

Deep CNNs can be an effective method to build low-budget embedded vision devices with limited computation power and memory capacity for diagnosis of oral cancer. Artificial intelligence (AI) can improve the quality and reach of oral cancer screening and early detection.

Clinical validation of 13-gene DNA methylation analysis in oral brushing samples for detection of oral carcinoma: Italian multicenter study

BACKGROUND

The aim of this Italian multicenter study was to evaluate the diagnostic performance of a minimally invasive method for the detection of oral squamous cell carcinoma (OSCC) based on 13-gene DNA methylation analysis in oral brushing samples.

METHODS

Oral brushing specimens were collected in 11 oral medicine centers across Italy. Twenty brushing specimens were collected by each center, 10 from patients with OSCC, and 10 from healthy volunteers. DNA methylation analysis was performed in blindness, and each sample was determined as positive or negative based on a predefined cutoff value.

RESULTS

DNA amplification failed in 4 of 220 (1.8%) samples. Of the specimens derived from patients with OSCC, 93.6% (103/110) were detected as positive, and 84.9% (90/106) of the samples from healthy volunteers were negative.

CONCLUSION

These data confirmed the diagnostic performance of our novel procedure in a large cohort of brushing specimens collected from 11 different centers and analyzed in blindness.