Prospective evaluation of oral premalignant lesions using a multimodal imaging system: a pilot study

Optical imaging technologies for in vivo cancer detection in low-resource settings

Cancer continues to affect underserved populations disproportionately. Novel optical imaging technologies, which can provide rapid, non-invasive, and accurate cancer detection at the point of care, have great potential to improve global cancer care. This article reviews the recent technical innovations and clinical translation of low-cost optical imaging technologies, highlighting the advances in both hardware and software, especially the integration of artificial intelligence, to improve in vivo cancer detection in low-resource settings. Additionally, this article provides an overview of existing challenges and future perspectives of adapting optical imaging technologies into clinical practice, which can potentially contribute to novel insights and programs that effectively improve cancer detection in low-resource settings.

Multimodal optical imaging with real-time projection of cancer risk and biopsy guidance maps for early oral cancer diagnosis and treatment

SIGNIFICANCE

Despite recent advances in multimodal optical imaging, oral imaging systems often do not provide real-time actionable guidance to the clinician who is making biopsy and treatment decisions.

AIM

We demonstrate a low-cost, portable active biopsy guidance system (ABGS) that uses multimodal optical imaging with deep learning to directly project cancer risk and biopsy guidance maps onto oral mucosa in real time.

APPROACH

Cancer risk maps are generated based on widefield autofluorescence images and projected onto the at-risk tissue using a digital light projector. Microendoscopy images are obtained from at-risk areas, and multimodal image data are used to calculate a biopsy guidance map, which is projected onto tissue.

RESULTS

Representative patient examples highlight clinically actionable visualizations provided in real time during an imaging procedure. Results show multimodal imaging with cancer risk and biopsy guidance map projection offers a versatile, quantitative, and precise tool to guide biopsy site selection and improve early detection of oral cancers.

CONCLUSIONS

The ABGS provides direct visible guidance to identify early lesions and locate appropriate sites to biopsy within those lesions. This represents an opportunity to translate multimodal imaging into real-time clinically actionable visualizations to help improve patient outcomes.

Mildly dysplastic oral lesions with optically-detectable abnormalities share genetic similarities with severely dysplastic lesions

OBJECTIVE

Optical imaging studies of oral premalignant lesions have shown that optical markers, including loss of autofluorescence and altered morphology of epithelial cell nuclei, are predictive of high-grade pathology. While these optical markers are consistently positive in lesions with moderate/severe dysplasia or cancer, they are positive only in a subset of lesions with mild dysplasia. This study compared the gene expression profiles of lesions with mild dysplasia (stratified by optical marker status) to lesions with severe dysplasia and without dysplasia.

MATERIALS AND METHODS

Forty oral lesions imaged in patients undergoing oral surgery were analyzed: nine without dysplasia, nine with severe dysplasia, and 22 with mild dysplasia. Samples were submitted for high throughput gene expression analysis.

RESULTS

The analysis revealed 116 genes differentially expressed among sites without dysplasia and sites with severe dysplasia; 50 were correlated with an optical marker quantifying altered nuclear morphology. Ten of 11 sites with mild dysplasia and positive optical markers (91%) had gene expression similar to sites with severe dysplasia. Nine of 11 sites with mild dysplasia and negative optical markers (82%) had similar gene expression as sites without dysplasia.

CONCLUSION

This study suggests that optical imaging may help identify patients with mild dysplasia who require more intensive clinical follow-up. If validated, this would represent a significant advance in patient care for patients with oral premalignant lesions.

Unmet Needs and Perspectives in Oral Cancer Prevention

Oral potentially malignant disorders (OPMD) may precede oral squamous cell carcinoma (OSCC). Reported rates of malignant transformation of OPMD range from 3 to 50%. While some clinical, histological, and molecular factors have been associated with a high-risk OPMD, they are, to date, insufficiently accurate for treatment decision-making. Moreover, this range highlights differences in the clinical definition of OPMD, variation in follow-up periods, and molecular and biological heterogeneity of OPMD. Finally, while treatment of OPMD may improve outcome, standard therapy has been shown to be ineffective to prevent OSCC development in patients with OPMD. In this perspective paper, several experts discuss the main challenges in oral cancer prevention, in particular the need to (i) to define an OPMD classification system by integrating new pathological and molecular characteristics, aiming (ii) to better identify OPMD at high risk of malignant transformation, and (iii) to develop treatment strategies to eradicate OPMD or prevent malignant transformation.

In Vivo Imaging-Based Techniques for Early Diagnosis of Oral Potentially Malignant Disorders-Systematic Review and Meta-Analysis

Objectives: Oral potentially malignant disorders (OPMDs) are lesions that may undergo malignant transformation to oral cancer. The early diagnosis and surveillance of OPMDs reduce the morbidity and mortality of patients. Diagnostic techniques based on medical images analysis have been developed to diagnose clinical conditions. This systematic review and meta-analysis aimed to evaluate the efficacy of imaging-based techniques compared to the gold standard of histopathology to assess their ability to correctly identify the presence of OPMDs. Design: Literature searches of free text and MeSH terms were performed using MedLine (PubMed), Scopus, Google Scholar, and the Cochrane Library (from 2000 to 30 June 2020). The keywords used in the search strategy were: (“oral screening devices” or “autofluorescence” or “chemiluminescence” or “optical imaging” or “imaging technique”) and (“oral dysplasia” or “oral malignant lesions” or “oral precancerosis”). Results: The search strategy identified 1282 potential articles. After analyzing the results and applying the eligibility criteria, the remaining 43 papers were included in the qualitative synthesis, and 34 of these were included in the meta-analysis. Conclusions: None of the analyzed techniques based on assessing oral images can replace the biopsy. Further studies are needed to explore the role of techniques-based imaging analysis to identify an early noninvasive screening method.

Narrow band imaging observed oral mucosa microvasculature as a tool to detect early oral cancer: an Indian experience

BACKGROUND

Narrow band imaging (NBI) is a novel method with the potential to improve the diagnostic capability of white-light.

METHODS

A prospective observational study of 50 consecutive patients, with suspicious malignant/premalignant lesions. White-light images were assessed as suspicious for malignancy/negative for malignancy, whereas NBI images were classified based on the IPCL patterns. All lesions underwent biopsy and accuracy was compared with the histopathology (Fig. 1). Fig. 1 Representative images of the IPCL patterns from Types I-IV RESULTS: 25 lesions (49%) were positive for malignancy, 2 (3.9%) lesions showed severe dysplasia, and 24(47%) were considered negative on histopathology. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of white light and NBI in detecting invasive carcinoma was 74.07%, 79.17%, 80.00%, 73.08% and 76.47%, and 92.67%, 90.16%, 92.56%, 91.67% and 92.16% respectively. The NBI group had a significantly better sensitivity and specificity to white light. The interobserver concordance was κ = 0.881.

CONCLUSION

NBI is a highly effective tool to detect invasive carcinomas amongst suspicious lesions of the oral cavity.

Algorithm to quantify nuclear features and confidence intervals for classification of oral neoplasia from high-resolution optical images

Purpose: In vivo optical imaging technologies like high-resolution microendoscopy (HRME) can image nuclei of the oral epithelium. In principle, automated algorithms can then calculate nuclear features to distinguish neoplastic from benign tissue. However, images frequently contain regions without visible nuclei, due to biological and technical factors, decreasing the data available to and accuracy of image analysis algorithms. Approach: We developed the nuclear density-confidence interval (ND-CI) algorithm to determine if an HRME image contains sufficient nuclei for classification, or if a better image is required. The algorithm uses a convolutional neural network to exclude image regions without visible nuclei. Then the remaining regions are used to estimate a confidence interval (CI) for the number of abnormal nuclei per   mm 2 , a feature used by a previously developed algorithm (called the ND algorithm), to classify images as benign or neoplastic. The range of the CI determines whether the ND-CI algorithm can classify an image with confidence, and if so, the predicted category. The ND and ND-CI algorithm were compared by calculating their positive predictive value (PPV) and negative predictive value (NPV) on 82 oral biopsies with histopathologically confirmed diagnoses. Results: After excluding the images that could not be classified with confidence, the ND-CI algorithm had higher PPV (65% versus 59%) and NPV (78% versus 75%) than the ND algorithm. Conclusions: The ND-CI algorithm could improve the real-time classification of HRME images of the oral epithelium by informing the user if an improved image is required for diagnosis.

Prospective evaluation of oral premalignant lesions using a multimodal imaging system: a pilot study

BACKGROUND

Multimodal optical imaging, incorporating reflectance and fluorescence modalities, is a promising tool to detect oral premalignant lesions in real-time.

METHODS

Images were acquired from 171 sites in 66 patient visits for clinical evaluation of oral lesions. An automated algorithm was used to classify lesions as high- or low-risk for neoplasia. Biopsies were acquired at clinically indicated sites and those classified as high-risk by imaging, at the surgeon's discretion.

RESULTS

Twenty sites were biopsied based on clinical examination or imaging. Of these, 12 were indicated clinically and by imaging; 58% were moderate dysplasia or worse. Four biopsies were indicated by imaging evaluation only; 75% were moderate dysplasia or worse. Finally, four biopsies were indicated by clinical evaluation only; 75% were moderate dysplasia or worse.

CONCLUSION

Multimodal imaging identified more cases of high-grade dysplasia than clinical evaluation, and can improve detection of high grade precancer in patients with oral lesions.