Clinical Application of the IllumiScan Fluorescence Visualization Device in Detecting Oral Mucosal Lesions

Flavinated SDHA underlies the change in intrinsic optical properties of oral cancers

The molecular basis of reduced autofluorescence in oral squamous cell carcinoma (OSCC) cells relative to normal cells has been speculated to be due to lower levels of free flavin adenine dinucleotide (FAD). This speculation, along with differences in the intrinsic optical properties of extracellular collagen, lies at the foundation of the design of currently-used clinical optical detection devices. Here, we report that free FAD levels may not account for differences in autofluorescence of OSCC cells, but that the differences relate to FAD as a co-factor for flavination. Autofluorescence from a 70 kDa flavoprotein, succinate dehydrogenase A (SDHA), was found to be responsible for changes in optical properties within the FAD spectral region, with lower levels of flavinated SDHA in OSCC cells. Since flavinated SDHA is required for functional complexation with succinate dehydrogenase B (SDHB), decreased SDHB levels were observed in human OSCC tissue relative to normal tissues. Accordingly, the metabolism of OSCC cells was found to be significantly altered relative to normal cells, revealing vulnerabilities for both diagnosis and targeted therapy. Optimizing non-invasive tools based on optical and metabolic signatures of cancers will enable more precise and early diagnosis leading to improved outcomes in patients.

Flavinated SDHA Underlies the Change in Intrinsic Optical Properties of Oral Cancers

The molecular basis of reduced autofluorescence in oral squamous cell carcinoma (OSCC) cells relative to normal cells has been speculated to be due to lower levels of free flavin adenine dinucleotide (FAD). This speculation, along with differences in the intrinsic optical properties of extracellular collagen, lie at the foundation of the design of currently-used clinical optical detection devices. Here, we report that free FAD levels may not account for differences in autofluorescence of OSCC cells, but that the differences relate to FAD as a co-factor for flavination. Autofluorescence from a 70 kDa flavoprotein, succinate dehydrogenase A (SDHA), was found to be responsible for changes in optical properties within the FAD spectral region with lower levels of flavinated SDHA in OSCC cells. Since flavinated SDHA is required for functional complexation with succinate dehydrogenase B (SDHB), decreased SDHB levels were observed in human OSCC tissue relative to normal tissues. Accordingly, the metabolism of OSCC cells was found to be significantly altered relative to normal cells, revealing vulnerabilities for both diagnosis and targeted therapy. Optimizing non-invasive tools based on optical and metabolic signatures of cancers will enable more precise and early diagnosis leading to improved outcomes in patients.

Evaluation of Oral Mucosal Lesions Using the IllumiScan® Fluorescence Visualisation Device: Distinguishing Squamous Cell Carcinoma

We evaluated whether fluorescence intensity (FI) and its coefficient of variation (CV) can be used to diagnose squamous cell carcinoma (SCC) through IllumiScan®, an oral mucosa fluorescence visualisation (FV) device. Overall, 190 patients with oral mucosal lesions (OMLs; SCC, 59; non-SCC OMLs, 131) and 49 patients with normal oral mucosa (NOM) were enrolled between January 2019 and March 2021. The FI of the images was analysed using image analysis software. After establishing regions of interest for SCC, non-SCC, and NOM, the average FI, standard deviation (SD), and CV were compared. There was a significant difference in the average FI for all pairs of comparisons. The SD was not significantly different between the SCC and NOM groups (p = 0.07). The CV differed significantly for NOM (p < 0.001) and non-SCC groups (p < 0.001) relative to the SCC group but was not different between NOM and non-SCC groups (p = 0.15). Univariate analysis of SCC and non-SCC groups showed significant differences for all factors, except age. However, multivariate analysis showed a significant intergroup difference only in the CV (p = 0.038). Therefore, analysing the CV in FV images of OML may be useful for the diagnosis of oral cancer.

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

Simple Summary

Oral cancer has a high mortality rate. Then, oral cancer screening is needed for early detection and treatment. Fluorescence visualization is non-invasive, convenient, and in real-time, and examinations can be repeated. Our study aimed to show the usefulness of oral cancer screening with fluorescence visualization. A total of 502 patients were performed using fluorescence visualization that was analyzed using subjective and objective evaluation. Results of this study, subjective evaluation for detection oral cancer was high sensitivity and low specificity, while objective evaluation using imaging processing analysis was high sensitivity and high specificity. Therefore, oral cancer screening using fluorescence visualization is useful for the detection of oral cancer. The widespread use of this screening can reduce the mortality rate of oral cancer.

Abstract

Background: Oral cancer screening is important for early detection and early treatment, which help improve survival rates. Biopsy is the gold standard for a definitive diagnosis but is invasive and painful, while fluorescence visualization is non-invasive, convenient, and real-time, and examinations can be repeated using optical instruments. The purpose of this study was to clarify the usefulness of fluorescence visualization in oral cancer screening. Methods: A total of 502 patients, who were examined using fluorescence visualization with optical instruments in our hospitals between 2014 and 2019, were enrolled in this study. The final diagnosis was performed by pathological examination. Fluorescence visualization was analyzed using subjective and objective evaluations. Results: Subjective evaluations for detecting oral cancer offered 96.8% sensitivity and 48.4% specificity. Regarding the objective evaluations, sensitivity and specificity were 43.7% and 84.6% for mean green value, 55.2% and 67.0% for median green value, 82.0% and 44.2% for coefficient of variation of value, 59.6% and 45.3% for skewness, and 85.1% and 75.8% for value ratio. For the sub-analysis of oral cancer, all factors on objective and subjective evaluation showed no significant difference. Conclusions: Fluorescence visualization with subjective and objective evaluation is useful for oral cancer screening.

Method for diagnosing neoplastic lesions by quantitative fluorescence value

Fluorescence visualization devices (FVs) are useful for detecting malignant lesions because of their simple and noninvasive application. However, their quantitative application has been challenging. This study aimed to quantitatively and statistically evaluate the change in fluorescence intensity (FI) during the progression from normal epithelium to squamous cell carcinoma using a reproducible animal tongue carcinogenesis model. To establish this model, rats were treated with 50 ppm 4-Nitroquinoline 1-oxide (4NQO) in their drinking water for 10, 15, and 20 weeks. After 4NQO administration, each rat tongue was evaluated by gross observation, histology, and FI measurements. Fluorescence images were captured by FV, and ImageJ was used to measure FI, which was analyzed quantitatively and statistically. The establishment of a reproducible tumor progression model was confirmed, showing precancerous lesions (low-grade dysplasia [LGD]), early cancers (high-grade dysplasia/carcinoma in situ [HGD/CIS]), and advanced cancers (Cancer). This carcinogenesis model was quantitatively evaluated by FI. The FI of LGD stage was 54.6, which was highest intensity of all groups. Subsequently, the HGD/CIS and Cancer stages showed decreased FI (HGD/CIS: 46.1, Cancer: 49.1) and manifested as dark spots. This result indicates that FI had more variation and a wider range with increasing tumor progression. We demonstrated that FI migration and an uneven distribution are consistent with tumor progression. Since each step of tumor progression occurs reproducibly in this animal model, statistical evaluation was possible. In addition, tumor progression can be monitored by this new FI analysis method in humans.