Evaluation of Vascular Patterns Using Contact Endoscopy and Narrow-Band Imaging (CE-NBI) for the Diagnosis of Vocal Fold Malignancy

Clinical Efficacy of Enhanced Contact Endoscopy in Early Detection of Laryngeal Carcinoma: A Single Center Experience

INTRODUCTION

Enhanced contact endoscopy (ECE) is a non-invasive technique used for the assessment of superficial vascular changes of mucosal lesions in high magnification. The aim of our study was to evaluate the clinical efficacy of ECE in an intraoperative settlement.

METHODS

Structured assessment of laryngeal mucosal lesions using enhanced endoscopy (narrow band imaging (NBI) and ECE) was performed in a prospective clinical trial. Lesions were classified according to the European Laryngological Society Classification into non-suspicious and suspicious. Evaluations of endoscopic methods (NBI and ECE) were correlated with histopathology, histopathology being the gold standard. Sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), area under curve, diagnostic odds ratio (DOR), Kappa, incremental yield, and Youden´s index for NBI and ECE were calculated.

RESULTS

A total of 110 patients with 136 lesions were enrolled, 50 benign non-neoplastic lesions, eight squamous cell papillomas, 45 dysplasias, and 33 squamous cell invasive cancers. Compared to NBI, ECE demonstrated higher sensitivity (91.0% vs 83.1%) and accuracy (90.4% vs 86.8%). NBI achieved higher specificity (91.8% vs 89.7%). PPV and NPV for ECE were 92.2% and 88.1%, whereas for NBI 93.1% and 80.4%. ECE showed greater overall diagnostic performance, with a DOR of 88.3 vs 55.2 and Kappa index of 0.805 vs 0.736.

CONCLUSIONS

ECE enhances diagnostic sensitivity and accuracy and represents a valuable addition to laryngeal cancer diagnostics.

Binary Classification of Laryngeal Images Utilising ResNet-50 CNN Architecture

In India, laryngeal cancer is a significant health concern, underlining the critical need for early detection methods. This study introduces a novel approach to classify laryngeal lesions into nine morphological categories; due to data scarcity for all the nine classes, the data is divided into cancer and non-cancer classes, including both non-cancerous and Squamous Cell Carcinoma (SCC), by analysing endoscopy images with advanced convolutional neural networks, deep learning, and image processing techniques. A dataset of 1978 endoscopy images from 960 patients at a tertiary care center in Lucknow, between May 2015 and December 2023, was utilised for this purpose. These images, captured using an Olympus CV-170 processor and annotated via the CVAT tool, were processed to highlight Regions of Interest (ROI) for detailed examination. The dataset was split, with 90% for training/validation and 10% for testing. A total of 197 images out of 1978 were selected for testing, which included 43 cancerous and 154 non-cancerous images. For the feature extraction, ResNet50 was utilised. The model's evaluation through the Receiver Operating Characteristic (ROC) curve demonstrated high effectiveness, with areas of 0.95, 0.98, and 0.93 for combined, NBI-only, and WL-only datasets, respectively. The accuracy rates were notably high across all datasets, highlighting the potential of this model to significantly aid in the early detection and classification of laryngeal cancer. In India, where the incidence of head and neck cancer is high and there is a lack of both advanced instruments and expertise in Narrow Band Imaging (NBI), this model could be instrumental in the early detection of laryngopharyngeal cancer. Level of Evidence: 2 C.

Applying Deep Learning with Convolutional Neural Networks to Laryngoscopic Imaging for Automated Segmentation and Classification of Vocal Cord Leukoplakia

Objectives: Vocal cord leukoplakia is clinically described as a white plaque or patch on the vocal cords observed during macroscopic examination, which does not take into account histological features or prognosis. A clinical challenge in managing vocal cord leukoplakia is to assess the potential malignant transformation of the lesion. This study aims to investigate the potential of deep learning (DL) for the simultaneous segmentation and classification of vocal cord leukoplakia using narrow band imaging (NBI) and white light imaging (WLI). The primary objective is to assess the model's accuracy in detecting and classifying lesions, comparing its performance in WLI and NBI. Methods: We applied DL to segment and classify NBI and WLI of vocal cord leukoplakia, and used pathological diagnosis as the gold standard. Results: The DL model autonomously detected lesions with an average intersection-over-union (IoU) >70%. In classification tasks, the model differentiated between lesions in the surgical group with a sensitivity of 93% and a specificity of 94% for WLI, and a sensitivity of 99% and a specificity of 97% for NBI. In addition, the model achieved a mean average precision of 81% in WLI and 92% in NBI, with an IoU threshold >0.5. Conclusions: The model proposed by us is helpful in assisting in accurate diagnosis of vocal cord leukoplakia from NBI and WLI.

Contact neuro-endoscopy-assisted cerebral hematoma evacuation under direct vision

Neuro-endoscopic hematoma evacuation is a crucial therapeutic approach for intracerebral hemorrhage. Our research team has developed a portable and contact neuro-endoscopy technique to enhance the conventional endoscopy procedure. compared to traditional endoscopy, this innovative approach involves miniaturizing the lens, light source, and camera system. These components are integrated into a stainless steel tube with a diameter of 4 mm, referred to as the portable endoscopy in this study. The portable endoscopy is powered by a USB cable and the video is displayed on a tablet computer. This portable endoscope facilitates easier operation with both hands by a single surgeon.

Clinical significance of type IV vascularization of laryngeal lesions according to the Ni classification

Background

Scattered, small, dot-like intraepithelial papillary capillary loops (IPCLs) represent type IV epithelial vascularization according to "Ni classification" and are considered to be nonmalignant. According to the European Laryngological Society classification, these loops are malignant vascular changes. This contradiction has high clinical importance; therefore, clarification of the clinical significance of type IV vascularization according to the Ni classification is needed.

Methods

The study was performed between June 2015 and December 2022. All recruited patients (n = 434) were symptomatic, with macroscopic laryngeal lesions (n = 674). Patients were investigated using the enhanced endoscopic methods of narrow band imaging (NBI) and the Storz Professional Image Enhancement System (IMAGE1 S). The microvascular patterns in the lesions were categorized according to Ni classification from 2011 and all lesions were examined histologically.

Results

A total of 674 lesions (434 patients) were investigated using flexible NBI endoscopy and IMAGE1 S endoscopy. Type IV vascularization was recognized in 293/674 (43.5%) lesions. Among these 293 lesions, 178 (60.7%) were benign (chronic laryngitis, hyperplasia, hyperkeratosis, polyps, cysts, granulomas, Reinkeho oedema and recurrent respiratory papillomatosis); 9 (3.1%) were squamous cell carcinoma; 61 (20.8%) were mildly dysplastic, 29 (9.9%) were moderately dysplastic, 14 (4.8%) were severe dysplastic and 2 (0.7%) were carcinoma in situ. The ability to recognize histologically benign lesions in group of nonmalignant vascular pattern according to Ni (vascularization type I-IV) and distinguish them from precancers and malignancies was with accuracy 75.5%, sensitivity 54.4%, specificity 94.4%, positive predictive value 89.6% and negative predictive value 69.9%.

Conclusion

Laryngeal lesions with type IV vascularization as defined by Ni present various histological findings, including precancerous and malignant lesions. Patients with type IV vascularization must be followed carefully and, in case of progression mucosal lesion microlaryngoscopy and excision are indicated.

Contact Endoscopy - Narrow Band Imaging (CE-NBI) data set for laryngeal lesion assessment

The endoscopic examination of subepithelial vascular patterns within the vocal fold is crucial for clinicians seeking to distinguish between benign lesions and laryngeal cancer. Among innovative techniques, Contact Endoscopy combined with Narrow Band Imaging (CE-NBI) offers real-time visualization of these vascular structures. Despite the advent of CE-NBI, concerns have arisen regarding the subjective interpretation of its images. As a result, several computer-based solutions have been developed to address this issue. This study introduces the CE-NBI data set, the first publicly accessible data set that features enhanced and magnified visualizations of subepithelial blood vessels within the vocal fold. This data set encompasses 11144 images from 210 adult patients with pathological vocal fold conditions, where CE-NBI images are annotated using three distinct label categories. The data set has proven invaluable for numerous clinical assessments geared toward diagnosing laryngeal cancer using Optical Biopsy. Furthermore, given its versatility for various image analysis tasks, we have devised and implemented diverse image classification scenarios using Machine Learning (ML) approaches to address critical clinical challenges in assessing laryngeal lesions.

Magnetic resonance imaging to assess cartilage invasion in recurrent laryngeal carcinoma after transoral laser microsurgery

Objective

To evaluate the diagnostic performance of magnetic resonance (MR) with surface coils in assessing cartilage invasion in recurrent laryngeal carcinoma after carbon dioxide transoral laser microsurgery (CO₂ TOLMS).

Methods

Two expert head and neck radiologists assessed cartilage invasion (infiltrated or non-infiltrated) in submucosal recurrences of laryngeal carcinoma after CO₂ TOLMS: results were compared with histopathological report after salvage laryngectomy.

Results

Thirty patients met the inclusion criteria and 90 cartilages were assessed. Overall sensitivity, specificity, and positive and negative predictive values for cartilage infiltration were 76, 93, 72 and 94%, respectively; for thyroid cartilage, the values were 82, 79, 69 and 88% respectively; for cricoid cartilage, all values were 100%; and for arytenoids, the values were 33, 96, 56 and 93% respectively.

Conclusions

MR with surface coils was able to detect most thyroid and cricoid infiltration in the complex setting of post-CO₂ TOLMS laryngeal carcinoma recurrence. In particular, the optimal performance in assessing cricoid invasion can be valuable in choosing the most appropriate treatment among total laryngectomy, open partial horizontal laryngectomies and non-surgical strategies.

Endoscopic Imaging Technology Today

One of the most applied imaging methods in medicine is endoscopy. A highly specialized image modality has been developed since the first modern endoscope, the "Lichtleiter" of Bozzini was introduced in the early 19th century. Multiple medical disciplines use endoscopy for diagnostics or to visualize and support therapeutic procedures. Therefore, the shapes, functionalities, handling concepts, and the integrated and surrounding technology of endoscopic systems were adapted to meet these dedicated medical application requirements. This survey gives an overview of modern endoscopic technology's state of the art. Therefore, the portfolio of several manufacturers with commercially available products on the market was screened and summarized. Additionally, some trends for upcoming developments were collected.

Deep Convolution Neural Network for Laryngeal Cancer Classification on Contact Endoscopy-Narrow Band Imaging

(1) Background: Contact Endoscopy (CE) and Narrow Band Imaging (NBI) are optical imaging modalities that can provide enhanced and magnified visualization of the superficial vascular networks in the laryngeal mucosa. The similarity of vascular structures between benign and malignant lesions causes a challenge in the visual assessment of CE-NBI images. The main objective of this study is to use Deep Convolutional Neural Networks (DCNN) for the automatic classification of CE-NBI images into benign and malignant groups with minimal human intervention. (2) Methods: A pretrained Res-Net50 model combined with the cut-off-layer technique was selected as the DCNN architecture. A dataset of 8181 CE-NBI images was used during the fine-tuning process in three experiments where several models were generated and validated. The accuracy, sensitivity, and specificity were calculated as the performance metrics in each validation and testing scenario. (3) Results: Out of a total of 72 trained and tested models in all experiments, Model 5 showed high performance. This model is considerably smaller than the full ResNet50 architecture and achieved the testing accuracy of 0.835 on the unseen data during the last experiment. (4) Conclusion: The proposed fine-tuned ResNet50 model showed a high performance to classify CE-NBI images into the benign and malignant groups and has the potential to be part of an assisted system for automatic laryngeal cancer detection.

[Contact endoscopy with narrow-band imaging for detection of perpendicular vascular changes in benign, dysplastic, and malignant lesions of the vocal folds]

BACKGROUND

Perpendicular vascular changes (PVC) are markers of tumor-induced neoangiogenesis at the vocal folds. Contact endoscopy with narrow-band imaging (CE-NBI) allows a detailed analysis of such vascular changes.

OBJECTIVE

This work intends to evaluate the potential of CE-NBI for diagnosis of benign, dysplastic, and malignant lesions of the vocal folds. In addition, it should be determined whether CE-NBI offers an additional benefit in detecting PVC compared to white-light endoscopy (WLE) and NBI alone.

MATERIALS AND METHODS

Three examiners evaluated histologically verified cases of benign, dysplastic, and malignant lesions of the larynx in WLE, NBI, and CE-NBI (n = 60). In each mode, they examined the lesion for PVC and assessed the lesion's dignity. The proportion of lesions with detected PVC, the statistical measures of performance in detecting high-grade dysplasia and carcinoma, and the interrater variability for each mode were calculated.

RESULTS

CE-NBI proved superior to the other investigated diagnostic methods in terms of detecting PVC and in terms of sensitivity and accuracy in the diagnosis of high-grade dysplasia and carcinoma. A clear association of such pathologies with PVC was seen.

CONCLUSION

CE-NBI detects PVC more frequently and reliably than the other methods investigated. The association of these vascular patterns to high-grade dysplasia and vocal fold carcinomas could be confirmed. Compared to WLE and NBI endoscopy, the diagnostic quality for detecting high-grade dysplasia and carcinoma is increased. Thus, CE-NBI can improve endoscopic differentiation between benign and malignant lesions of the vocal folds by enhancing the detection of PVC.

Narrow-Band Imaging in oncologic otorhinolaryngology: State of the art

OBJECTIVES

To describe the diagnostic performance of Narrow Band Imaging (NBI) combined with White Light Imaging (WLI) in the diagnosis of mucosal lesions at each location of the upper aerodigestive tract, for detection of primary tumor in case of carcinoma of unknown primary, for determination of intraoperative resection margins, and to describe its main diagnostic pitfalls.

MATERIAL AND METHODS

A PubMed search was carried out according to the PRISMA method.

RESULTS

Four hundred and seventy-seven articles published between 2007 and 2020 were identified, 133 of which met the study inclusion criteria and were assessed.

CONCLUSION

The current literature seems to support the use of NBI in diagnosis and/or follow-up of (pre-)malignant head & neck tumors, and in the determination of intraoperative resection margins.

Cyclist Effort Features: A Novel Technique for Image Texture Characterization Applied to Larynx Cancer Classification in Contact Endoscopy-Narrow Band Imaging

BACKGROUND

Feature extraction is an essential part of a Computer-Aided Diagnosis (CAD) system. It is usually preceded by a pre-processing step and followed by image classification. Usually, a large number of features is needed to end up with the desired classification results. In this work, we propose a novel approach for texture feature extraction. This method was tested on larynx Contact Endoscopy (CE)-Narrow Band Imaging (NBI) image classification to provide more objective information for otolaryngologists regarding the stage of the laryngeal cancer.

METHODS

The main idea of the proposed methods is to represent an image as a hilly surface, where different paths can be identified between a starting and an ending point. Each of these paths can be thought of as a Tour de France stage profile where a cyclist needs to perform a specific effort to arrive at the finish line. Several paths can be generated in an image where different cyclists produce an average cyclist effort representing important textural characteristics of the image. Energy and power as two Cyclist Effort Features (CyEfF) were extracted using this concept. The performance of the proposed features was evaluated for the classification of 2701 CE-NBI images into benign and malignant lesions using four supervised classifiers and subsequently compared with the performance of 24 Geometrical Features (GF) and 13 Entropy Features (EF).

RESULTS

The CyEfF features showed maximum classification accuracy of 0.882 and improved the GF classification accuracy by 3 to 12 percent. Moreover, CyEfF features were ranked as the top 10 features along with some features from GF set in two feature ranking methods.

CONCLUSION

The results prove that CyEfF with only two features can describe the textural characterization of CE-NBI images and can be part of the CAD system in combination with GF for laryngeal cancer diagnosis.

Laryngeal Mid-Cord Erythroleukoplakias: How to Modulate the Transoral CO2 Laser Excisional Biopsy

Background: The endoscopic appearance of glottic erythroleukoplakias is non-predictive of their histopathology, potentially ranging from keratosis to invasive squamous cell carcinoma (SCC). The aim of this study was to assess a comprehensive workup for the one-step diagnosis and treatment of mid-cord erythroleukoplakias, using CO₂ laser excisional biopsy. Methods: We evaluated 147 untreated patients affected by 155 mid-cord erythroleukoplakias submitted to excisional biopsy by subepithelial (Type I) or subligamental cordectomy (Type II), across two academic institutions. Patients were evaluated by preoperative videolaryngostroboscopy, pre- and intraoperative videoendoscopy with biologic endoscopy (narrow band imaging, NBI, or the Storz professional image enhancement system, SPIES), either with or without intraoperative saline infusion into the Reinke’s space. Adequacy of treatment was the primary outcome. Results: The histopathologic diagnosis was keratosis in 26 (17%) cases, squamous intraepithelial neoplasia (SIN1-2) in 47 (30%), carcinoma in situ in 21 (14%), and SCC in 61 (39%) patients. The adequacy of treatment across the entire cohort was 89%. The intraoperative saline infusion procedure, facing not clearly suspicious lesions, raised the adequacy of treatment from 60% to 90% (p = 0.006). Conclusions: Excisional biopsy by Type I–II cordectomies, after a comprehensive diagnostic workup, should be accepted as an adequate and cost-effective treatment of unilateral mid-cord glottic erythroleukoplakias.

Laryngeal Lesion Classification Based on Vascular Patterns in Contact Endoscopy and Narrow Band Imaging: Manual Versus Automatic Approach

Longitudinal and perpendicular changes in the vocal fold’s blood vessels are associated with the development of benign and malignant laryngeal lesions. The combination of Contact Endoscopy (CE) and Narrow Band Imaging (NBI) can provide intraoperative real-time visualization of the vascular changes in the laryngeal mucosa. However, the visual evaluation of vascular patterns in CE-NBI images is challenging and highly depends on the clinicians’ experience. The current study aims to evaluate and compare the performance of a manual and an automatic approach for laryngeal lesion’s classification based on vascular patterns in CE-NBI images. In the manual approach, six observers visually evaluated a series of CE+NBI images that belong to a patient and then classified the patient as benign or malignant. For the automatic classification, an algorithm based on characterizing the level of the vessel’s disorder in combination with four supervised classifiers was used to classify CE-NBI images. The results showed that the manual approach’s subjective evaluation could be reduced by using a computer-based approach. Moreover, the automatic approach showed the potential to work as an assistant system in case of disagreements among clinicians and to reduce the manual approach’s misclassification issue.

Interrater variation of vascular classifications used in enhanced laryngeal contact endoscopy

PURPOSE

Combined use of contact endoscopy (CE) and Narrow Band Imaging (NBI, Olympus^®) is suggested for the visualization of specific vascular changes indicative of glottic neoplasia. We investigated the interrater reliability and agreement in 3 recognized classification systems of vascular changes applied to images from CE + NBI in patients suspected for glottic neoplasia.

METHODS

Six experienced head and neck surgeons familiar with NBI rated 120 images obtained by CE + NBI by 3 classification systems of vascular changes as suggested by Ni et al. (N-C), Puxeddu et al. (P-C), and the European Laryngological Society (ELS-C). Three raters were experienced in CE, and three raters had only limited experience with CE. Crude agreement and Fleiss' kappa with 95% confidence interval were estimated for all 6 raters, and for the 2 levels of expertise for each original classification system and for dichotomized versions of the N-C and the P-C based on suggested neoplastic potential.

RESULTS

The interrater crude agreement and the corresponding kappa values for the ELS-C were good and significantly higher than those for the N-C and P-C for all raters, irrespective of the level of experience with CE (p < 0.0001). There were no significant differences between the N-C and the P-C (p = 0.16). Kappa was considerably improved for both the N-C and the P-C to a level not different from the ELS-C (p = 0.21-0.71) when their 5 original categories were pooled into dichotomized classifications.

CONCLUSION

Difficulties in reliably classifying vascular changes in CE + NBI are evident. Two-tier classification systems are the most reliable.