Multi-Instance Learning for Vocal Fold Leukoplakia Diagnosis Using White Light and Narrow-Band Imaging: A Multicenter Study.

OBJECTIVES: Vocal fold leukoplakia (VFL) is a precancerous lesion of laryngeal cancer, and its endoscopic diagnosis poses challenges. We aim to develop an artificial intelligence (AI) model using white light imaging (WLI) and narrow-band imaging (NBI) to distinguish benign from malignant VFL. METHODS: A total of 7057 images from 426 patients were used for model development and internal validation. Additionally, 1617 images from two other hospitals were used for model external validation. Modeling learning based on WLI and NBI modalities was conducted using deep learning combined with a multi-instance learning approach (MIL). Furthermore, 50 prospectively collected videos were used to evaluate real-time model performance. A human-machine comparison involving 100 patients and 12 laryngologists assessed the real-world effectiveness of the model. RESULTS: The model achieved the highest area under the receiver operating characteristic curve (AUC) values of 0.868 and 0.884 in the internal and external validation sets, respectively. AUC in the video validation set was 0.825 (95% CI: 0.704-0.946). In the human-machine comparison, AI significantly improved AUC and accuracy for all laryngologists (p < 0.05). With the assistance of AI, the diagnostic abilities and consistency of all laryngologists improved. CONCLUSIONS: Our multicenter study developed an effective AI model using MIL and fusion of WLI and NBI images for VFL diagnosis, particularly aiding junior laryngologists. However, further optimization and validation are necessary to fully assess its potential impact in clinical settings. LEVEL OF EVIDENCE: 3 Laryngoscope, 134:4321-4328, 2024.

Revealing molecular and cellular heterogeneity in hypopharyngeal carcinogenesis through single-cell RNA and TCR/BCR sequencing.

Introduction: Hypopharyngeal squamous cell carcinoma (HSCC) is one of the malignant tumors with the worst prognosis in head and neck cancers. The transformation from normal tissue through low-grade and high-grade intraepithelial neoplasia to cancerous tissue in HSCC is typically viewed as a progressive pathological sequence typical of tumorigenesis. Nonetheless, the alterations in diverse cell clusters within the tissue microenvironment (TME) throughout tumorigenesis and their impact on the development of HSCC are yet to be fully understood. Methods: We employed single-cell RNA sequencing and TCR/BCR sequencing to sequence 60,854 cells from nine tissue samples representing different stages during the progression of HSCC. This allowed us to construct dynamic transcriptomic maps of cells in diverse TME across various disease stages, and experimentally validated the key molecules within it. Results: We delineated the heterogeneity among tumor cells, immune cells (including T cells, B cells, and myeloid cells), and stromal cells (such as fibroblasts and endothelial cells) during the tumorigenesis of HSCC. We uncovered the alterations in function and state of distinct cell clusters at different stages of tumor development and identified specific clusters closely associated with the tumorigenesis of HSCC. Consequently, we discovered molecules like MAGEA3 and MMP3, pivotal for the diagnosis and treatment of HSCC. Discussion: Our research sheds light on the dynamic alterations within the TME during the tumorigenesis of HSCC, which will help to understand its mechanism of canceration, identify early diagnostic markers, and discover new therapeutic targets.

Multi-instance learning based artificial intelligence model to assist vocal fold leukoplakia diagnosis: A multicentre diagnostic study.

OBJECTIVE: To develop a multi-instance learning (MIL) based artificial intelligence (AI)-assisted diagnosis models by using laryngoscopic images to differentiate benign and malignant vocal fold leukoplakia (VFL). METHODS: The AI system was developed, trained and validated on 5362 images of 551 patients from three hospitals. Automated regions of interest (ROI) segmentation algorithm was utilized to construct image-level features. MIL was used to fusion image level results to patient level features, then the extracted features were modeled by seven machine learning algorithms. Finally, we evaluated the image level and patient level results. Additionally, 50 videos of VFL were prospectively gathered to assess the system's real-time diagnostic capabilities. A human-machine comparison database was also constructed to compare the diagnostic performance of otolaryngologists with and without AI assistance. RESULTS: In internal and external validation sets, the maximum area under the curve (AUC) for image level segmentation models was 0.775 (95 % CI 0.740-0.811) and 0.720 (95 % CI 0.684-0.756), respectively. Utilizing a MIL-based fusion strategy, the AUC at the patient level increased to 0.869 (95 % CI 0.798-0.940) and 0.851 (95 % CI 0.756-0.945). For real-time video diagnosis, the maximum AUC at the patient level reached 0.850 (95 % CI, 0.743-0.957). With AI assistance, the AUC improved from 0.720 (95 % CI 0.682-0.755) to 0.808 (95 % CI 0.775-0.839) for senior otolaryngologists and from 0.647 (95 % CI 0.608-0.686) to 0.807 (95 % CI 0.773-0.837) for junior otolaryngologists. CONCLUSIONS: The MIL based AI-assisted diagnosis system can significantly improve the diagnostic performance of otolaryngologists for VFL and help to make proper clinical decisions.

Narrow band imaging-based radiogenomics for predicting radiosensitivity in nasopharyngeal carcinoma.

Objectives: This study aims to assess the efficacy of narrow band imaging (NBI) endoscopy in utilizing radiomics for predicting radiosensitivity in nasopharyngeal carcinoma (NPC), and to explore the associated molecular mechanisms. Materials: The study included 57 NPC patients who were pathologically diagnosed and underwent RNA sequencing. They were categorized into complete response (CR) and partial response (PR) groups after receiving radical concurrent chemoradiotherapy. We analyzed 267 NBI images using ResNet50 for feature extraction, obtaining 2048 radiomic features per image. Using Python for deep learning and least absolute shrinkage and selection operator for feature selection, we identified differentially expressed genes associated with radiomic features. Subsequently, we conducted enrichment analysis on these genes and validated their roles in the tumor immune microenvironment through single-cell RNA sequencing. Results: After feature selection, 54 radiomic features were obtained. The machine learning algorithm constructed from these features showed that the random forest algorithm had the highest average accuracy rate of 0.909 and an area under the curve of 0.961. Correlation analysis identified 30 differential genes most closely associated with the radiomic features. Enrichment and immune infiltration analysis indicated that tumor-associated macrophages are closely related to treatment responses. Three key NBI differentially expressed immune genes (NBI-DEIGs), namely CCL8, SLC11A1, and PTGS2, were identified as regulators influencing treatment responses through macrophages. Conclusion: NBI-based radiomics models introduce a novel and effective method for predicting radiosensitivity in NPC. The molecular mechanisms may involve the functional states of macrophages, as reflected by key regulatory genes.

Laryngoscopy-based scoring system for the diagnosis of vocal fold leukoplakia.

OBJECTIVE: To propose a scoring system based on laryngoscopic characteristics for the differential diagnosis of benign and malignant vocal fold leukoplakia. METHODS: Laryngoscopic images from 200 vocal fold leukoplakia cases were retrospectively analysed. The laryngoscopic signs of benign and malignant vocal fold leukoplakia were compared, and statistically significant features were assigned and accumulated to establish the leukoplakia finding score. RESULTS: A total of five indicators associated with malignant vocal fold leukoplakia were included to construct the leukoplakia finding score, with a possible range of 0-10 points. A score of 6 points or more was indicative of a diagnosis of malignant vocal fold leukoplakia. The sensitivity, specificity and accuracy values of the leukoplakia finding score were 93.8 per cent, 83.6 per cent and 86.0 per cent, respectively. The consistency in the leukoplakia finding score obtained by different laryngologists was strong (kappa = 0.809). CONCLUSION: This scoring system based on laryngoscopic characteristics has high diagnostic value for distinguishing benign and malignant vocal fold leukoplakia.

Tislelizumab and radiation therapy in low-risk early-stage extranodal natural killer/T-cell lymphoma, nasal type: a phase II study protocol.

Low-risk early-stage extranodal natural killer/T-cell lymphoma, nasal type has a favorable outcome with radiation therapy alone, and the addition of chemotherapy shows no survival benefit. Nonetheless, a proportion of patients will relapse or progress, with a dismal outcome, highlighting the need for a novel therapeutic strategy. Promising preliminary findings indicate the efficacy of PD-1/PD-L1 inhibitors in extranodal natural killer/T-cell lymphoma, nasal type, with good toxicity profiles. Here we describe the design of a phase II study (CLCG-NKT-2101), which is evaluating the safety and efficacy of adding anti-PD-1 antibody to the current radiation therapy regimen in low-risk early-stage extranodal natural killer/T-cell lymphoma, nasal type patients. Tislelizumab will be added in an inductive and concurrent way to radiation therapy. The primary end point will be the complete response rate after induction immunotherapy. Clinical trial registration: ClinicalTrials.gov (NCT05149170).

The Detection of Nasopharyngeal Carcinomas Using a Neural Network Based on Nasopharyngoscopic Images.

OBJECTIVE: To construct and validate a deep convolutional neural network (DCNN)-based artificial intelligence (AI) system for the detection of nasopharyngeal carcinoma (NPC) using archived nasopharyngoscopic images. METHODS: We retrospectively collected 14107 nasopharyngoscopic images (7108 NPCs and 6999 noncancers) to construct a DCNN model and prepared a validation dataset containing 3501 images (1744 NPCs and 1757 noncancers) from a single center between January 2009 and December 2020. The DCNN model was established using the You Only Look Once (YOLOv5) architecture. Four otolaryngologists were asked to review the images of the validation set to benchmark the DCNN model performance. RESULTS: The DCNN model analyzed the 3501 images in 69.35 s. For the validation dataset, the precision, recall, accuracy, and F1 score of the DCNN model in the detection of NPCs on white light imaging (WLI) and narrow band imaging (NBI) were 0.845 ± 0.038, 0.942 ± 0.021, 0.920 ± 0.024, and 0.890 ± 0.045, and 0.895 ± 0.045, 0.941 ± 0.018, and 0.975 ± 0.013, 0.918 ± 0.036, respectively. The diagnostic outcome of the DCNN model on WLI and NBI images was significantly higher than that of two junior otolaryngologists (p < 0.05). CONCLUSION: The DCNN model showed better diagnostic outcomes for NPCs than those of junior otolaryngologists. Therefore, it could assist them in improving their diagnostic level and reducing missed diagnoses. LEVEL OF EVIDENCE: 3 Laryngoscope, 134:127-135, 2024.

Convolutional neural network based anatomical site identification for laryngoscopy quality control: A multicenter study.

OBJECTIVES: Video laryngoscopy is an important diagnostic tool for head and neck cancers. The artificial intelligence (AI) system has been shown to monitor blind spots during esophagogastroduodenoscopy. This study aimed to test the performance of AI-driven intelligent laryngoscopy monitoring assistant (ILMA) for landmark anatomical sites identification on laryngoscopic images and videos based on a convolutional neural network (CNN). MATERIALS AND METHODS: The laryngoscopic images taken from January to December 2018 were retrospectively collected, and ILMA was developed using the CNN model of Inception-ResNet-v2 + Squeeze-and-Excitation Networks (SENet). A total of 16,000 laryngoscopic images were used for training. These were assigned to 20 landmark anatomical sites covering six major head and neck regions. In addition, the performance of ILMA in identifying anatomical sites was validated using 4000 laryngoscopic images and 25 videos provided by five other tertiary hospitals. RESULTS: ILMA identified the 20 anatomical sites on the laryngoscopic images with a total accuracy of 97.60 %, and the average sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 100 %, 99.87 %, 97.65 %, and 99.87 %, respectively. In addition, multicenter clinical verification displayed that the accuracy of ILMA in identifying the 20 targeted anatomical sites in 25 laryngoscopic videos from five hospitals was ≥95 %. CONCLUSION: The proposed CNN-based ILMA model can rapidly and accurately identify the anatomical sites on laryngoscopic images. The model can reflect the coverage of anatomical regions of the head and neck by laryngoscopy, showing application potential in improving the quality of laryngoscopy.

Deep Learning for nasopharyngeal Carcinoma Identification Using Both White Light and Narrow-Band Imaging Endoscopy.

OBJECTIVES/HYPOTHESIS: To develop a deep-learning-based automatic diagnosis system for identifying nasopharyngeal carcinoma (NPC) from noncancer (inflammation and hyperplasia), using both white light imaging (WLI) and narrow-band imaging (NBI) nasopharyngoscopy images. STUDY DESIGN: Retrospective study. METHODS: A total of 4,783 nasopharyngoscopy images (2,898 WLI and 1,885 NBI) of 671 patients were collected and a novel deep convolutional neural network (DCNN) framework was developed named Siamese deep convolutional neural network (S-DCNN), which can simultaneously utilize WLI and NBI images to improve the classification performance. To verify the effectiveness of combining the above-mentioned two modal images for prediction, we compared the proposed S-DCNN with two baseline models, namely DCNN-1 (only considering WLI images) and DCNN-2 (only considering NBI images). RESULTS: In the threefold cross-validation, an overall accuracy and area under the curve of the three DCNNs achieved 94.9% (95% confidence interval [CI] 93.3%-96.5%) and 0.986 (95% CI 0.982-0.992), 87.0% (95% CI 84.2%-89.7%) and 0.930 (95% CI 0.906-0.961), and 92.8% (95% CI 90.4%-95.3%) and 0.971 (95% CI 0.953-0.992), respectively. The accuracy of S-DCNN is significantly improved compared with DCNN-1 (P-value <.001) and DCNN-2 (P-value = .008). CONCLUSION: Using the deep-learning technology to automatically diagnose NPC under nasopharyngoscopy can provide valuable reference for NPC screening. Superior performance can be obtained by simultaneously utilizing the multimodal features of NBI image and WLI image of the same patient. LEVEL OF EVIDENCE: 3 Laryngoscope, 132:999-1007, 2022.

Laryngoscopic characteristics related to the risk of cancerization of vocal cord leukoplakia.

BACKGROUND: The diagnosis of vocal cord leukoplakia mainly relies on laryngoscopy. The morphology of vocal cord leukoplakia under laryngoscope is closely related to the pathological nature of leukoplakia. The specific manifestations associated with high-risk vocal cord leukoplakia remain to be explored. OBJECTIVE: To investigate the characteristics of low-risk and high-risk vocal cord leukoplakia under conventional white light imaging (WLI) laryngoscopy and its correlations with narrow band imaging (NBI) laryngoscopy. METHODS: One hundred and seventy-five cases of vocal cord leukoplakia were divided into low-risk and high-risk groups. The characteristics of low-risk and high-risk vocal cord leukoplakia under WLI laryngoscopy and its correlations with NBI laryngoscopy were analyzed. RESULTS: Logistic regression analysis showed that thickness and hyperemia were independent factors (p < .05). Hyperemia had a strong consistency with the visualization of spots under NBI laryngoscopy (kappa = 0.758). The sign of hyperemia and the NBI classification had equivalent diagnostic efficacy for predicting the risk of cancerization of vocal cord leukoplakia. CONCLUSION: The sign of hyperemia under WLI laryngoscopy is significantly correlated with the visualized spots under NBI laryngoscopy. Hyperemia is an important feature for predicting malignant potential of vocal cord leukoplakia.

Posttreatment Non-Improved Vocal Cord Mobility Indicates the Need of Salvage Surgery for Hypopharyngeal Carcinomas.

INTRODUCTION: We aimed to analyze the relationship between the changed status of vocal cord mobility and survival outcomes. METHODS: Seventy-eight patients with dysfunctional vocal cords and hypopharyngeal carcinomas accepted non-surgical treatment as the initial therapy between May 2009 and December 2016. Vocal cord mobility was assessed before and after the initial non-surgical treatment. The cord mobility status was classified as normal, impaired, and fixed. Patients with improved mobility (IM) (n =56) were retrospectively analyzed for disease-free survival (DFS), recurrence-free survival (RFS), and overall survival (OS) and compared with 22 patients with non-improved mobility (non-IM). RESULTS: Fifty-six (71.8%) patients had improved cord mobility after the initial non-surgical treatment. The non-improved cord mobility was significantly associated with shortened DFS (P=0.005), RFS (P=0.002), and OS (P<0.001). If non-improved cord mobility was regarded as an indicator for local-regional recurrence within 1 year, the sensitivity and the specificity were 60.9%, 87.5% respectively. The multivariate analysis showed that improved cord mobility (P=0.006) and salvage surgery (P=0.015) were both independent protective factors for OS. CONCLUSION: Changes in cord mobility are a key marker for predicting prognosis. Non-improved cord mobility may indicate a high possibility of a residual tumor, therefore, patients whose cord mobility remains dysfunctional or worsens after non-surgical treatment might need an aggressive salvage strategy.

Clinical utility and effectiveness of a training programme in the application of a new classification of narrow-band imaging for vocal cord leukoplakia: A multicentre study.

OBJECTIVE: To analyse the application of a new narrow-band imaging (NBI) classification in the diagnosis of vocal cord leukoplakia by laryngologists with different levels of laryngoscopic experience and to explore the impact of NBI training programmes on laryngologists' identification of benign and malignant leukoplakia. DESIGN: Prospective multicentre study. SETTING: Tertiary hospitals. PARTICIPANTS: Sixteen laryngologists were divided into less-experienced and experienced groups and received NBI training course. Thirty cases of vocal cord leukoplakia were investigated. MAIN OUTCOME MEASURES: Diagnostic accuracy and interobserver agreement under white light imaging (WLI), before and after NBI training, were analysed among doctors with varying levels of experience. RESULTS: The accuracy in the less-experienced group was significantly lower than that of experience group (0.59 vs 0.69) under WLI. There was no significant difference in the diagnostic accuracy between the less-experienced group and the experienced group before NBI training (0.75 vs 0.74) and after NBI training (0.79 vs 0.83). NBI training could improve the interobserver agreement from fair or moderate to good agreement. CONCLUSION: The new NBI diagnostic classification is helpful for identifying benign and malignant vocal cord leukoplakia. In addition, the NBI training programme can improve the diagnostic accuracy and interobserver agreement of less-experienced doctors to the level of experienced laryngologists.

Diagnosis of vocal cord leukoplakia: The role of a novel narrow band imaging endoscopic classification.

OBJECTIVES: The purpose of this study was to introduce a new narrow band imaging (NBI) endoscopic classification for the diagnosis of vocal cord leukoplakia. STUDY DESIGN: Case series. METHODS: From January 2010 to February 2018, a total of 120 cases of vocal cord leukoplakia were enrolled in this study. The NBI endoscopic system was used to examine the vocal cords. Each lesion was observed by NBI endoscopy and evaluated according to the detailed morphologic findings of intraepithelial papillary capillary loop (IPCL). The superficial IPCL patterns were classified into six types (types I-VI). The differential diagnosis abilities of NBI classification for benign and malignant leukoplakia were investigated. RESULTS: Out of the 120 cases of vocal cord leukoplakia, 81% (97 of 120) related to benign lesions (including inflammation, epithelial proliferation, hyperkeratosis, dyskeratosis, mild dysplasia, and moderate dysplasia); the remaining 19% (23 of 120) consisted of malignant lesions (including severe dysplasia, carcinoma in situ, and invasive carcinoma). The accuracy of differential diagnosis for vocal cord leukoplakia using NBI endoscopy was up to 90.8% (109 of 120), significantly higher than that of white light imaging (70.0%, 84 of 120) (χ2 = 16.536, P = 0.000). The sensitivity, specificity, and positive and negative predictive values of the diagnosis for malignant vocal cord leukoplakia under the NBI endoscope were 82.6%, 92.8%, 73.1%, and 95.7%, respectively. There is relatively good consistency between the NBI endoscopic diagnosis and pathological diagnosis (kappa = 0.718, P = 0.000). CONCLUSION: The new NBI endoscopic classification of vocal cord leukoplakia can improve the accuracy of distinguishing benign and malignant leukoplakia. LEVEL OF EVIDENCE: 4 Laryngoscope, 129:429-434, 2019.

Classification of nasopharyngeal microvessels detected by narrow band imaging endoscopy and its role in the diagnosis of nasopharyngeal carcinoma.

CONCLUSIONS: The new NBI classification of nasopharyngeal mucosal microvessels was helpful in differential diagnosis for benign and malignant lesions of the nasopharyngeal region. NBI endoscopy facilitates the detection of superficial nasopharyngeal lesions and might enable early diagnoses of NPC. OBJECTIVES: To propose a new microvessel diagnostic classification using narrow band imaging (NBI) endoscopy and to investigate the role of an NBI classification in the diagnosis of nasopharyngeal carcinoma (NPC). METHODS: Between January 2009 and December 2010, a total of 290 patients with a suspected nasopharyngeal tumor were enrolled in this study. The NBI endoscopic system was used to examine the nasopharynx. Each lesion was observed by NBI endoscopy and judged according to the detailed morphologic findings of epithelial microvessels. The superficial microvessel patterns were classified into five types (types I-V). The diagnostic effectiveness of NBI for benign and malignant nasopharyngeal lesions was evaluated. RESULTS: Approximately 93.5% (29/31) of lymphoid hyperplasia appeared as the type II microvessel pattern under NBI endoscopy, whereas 96.2% (51/53) of nasopharyngeal radiation-induced inflammation exhibited the type III or IV microvessel pattern. The characteristics of NPC under NBI endoscopy mainly appeared as a type V microvessel pattern (79.5%, 167/210), and the sensitivity, specificity, predictive value (PPV), and negative predictive value (NPV) of type V in the diagnosis of NPC were 79.5%, 91.3%, 96.0%, and 62.9%, respectively. NBI endoscopy could significantly improve the detection of superficial lesions (χ2 = 12.789, p = .000).

The Role of Narrow Band Imaging in Head and Neck Cancers.

Early diagnosis of malignant tumors in the head and neck region is very difficult. Therefore, endoscopic systems with narrow band imaging (NBI), which enhances image contrast, have an important clinical value in detecting superficial mucosal lesions. In particular, highlighting of the intraepithelial microvasculature helps determine the nature of the lesion. This new image-enhanced technology already has proven effective in the early diagnosis of head and neck squamous cell carcinoma, including laryngeal, hypopharyngeal, oropharyngeal, nasopharyngeal, and oral cancers, as well as of unknown primary cervical lymph node metastasis. NBI laryngoscopy can be applied easily in clinical practice and has become a valuable tool in diagnosing head and neck cancers early, providing the option of minimally invasive treatment such as endoscopic or partial surgical resection.

[Value of narrow band imaging endoscopy in the detection of unknown primary site with cervical lymph node metastasis of squamous cell carcinoma].

OBJECTIVE: To investigate the value of narrow band imaging (NBI) endoscopy in the detection of unknown primary tumor site with cervical lymph node metastases of squamous cell carcinoma. METHODS: Fifty-three patients with cervical lymph node metastases of squamous cell carcinoma treated in our department between June 2009 and December 2011 were enrolled in this study. Their primary tumor site was not detected by routine computed tomography, magnetic resonance imaging and laryngoscopy. The nasopharyngolarynx was examined by NBI endoscopy to explore the primary tumor site. RESULTS: A total of 53 cases with cervical lymph node metastasis of squamous cell carcinoma from an unknown primary were examined under NBI endoscopy. The primary tumor site was confirmed by NBI examination in 47.2% (25/53) of patients, significantly better than routine radiology and endoscopy (0, P < 0.001). These primary tumors were small and superficial, with characteristic mucosal vascular morphologies. The superficial nasopharyngeal carcinomas under NBI examination showed the superficial thin branch-like or torturous line microvessels. The notable characteristics of the squamous cell carcinoma of oropharynx, hypopharynx and larynx was the well demarcated brownish area and scattered brown dots. CONCLUSION: The NBI endoscopy can provide better visualization of the morphology of superficial mucosal vasculature and improve the ability to detect possible primary cancer in patients with primary unknown cervical lymph node metastasis.

[Comparative study of endoscopic mucous resection with transparent cap and endoscopic multi-band mucosectomy for early esophageal cancer and precancerous lesion].

OBJECTIVE: To evaluate the efficacy and safety of endoscopic mucous resection with transparent cap (EMR-Cap) and endoscopic multi-band mucosectomy (MBM) in the treatment of early esophageal cancer and precancerous lesion. METHODS: A retrospective study was performed to review 30 EMR-Cap cases from December 2008 to December 2009 and 32 MBM cases from January 2010 to January 2011 of early esophageal cancer and precancerous lesions. The differences between these two techniques in efficacy, safety, and cost were compared. RESULTS: In EMR-Cap group, the median resection time was 26(10-56) min and median procedure time was 43(22-81) min, significantly longer than those in MBM group [10(7-18) min and 32(28-45) min, P=0.036 and 0.038, respectively]. There were no significant differences between the two groups in total thickness and depth of resected lesions (P>0.05). In EMR-Cap group, the median cost was significantly higher than that of MBM group [(5466±354) vs. (4014±368) RMB, P=0.008)]. CONCLUSIONS: EMR-Cap and MBM are minimally invasive, safe and effective methods in the treatment of early esophageal cancer and precancerous lesions. Compared to the EMR-Cap, MBM is simple with shorter treatment time and lower cost.

[Display of esophageal entrance by injecting gas through the laryngoscopic biopsy channel in hypopharyngeal cancer].

OBJECTIVE: To investigate the method displaying the hypopharynx and esophageal entrance under laryngoscopy to determine the invasion range of hypopharyngeal cancer. METHODS: A total of 113 patients with hypopharyngeal cancer was enrolled in this study and they previously underwent conventional laryngoscopic and radiologic examinations. The esophageal entrance was exposed by injecting gas through the biopsy channel of laryngoscope. The invasion of esophageal entrance in hypopharyngeal cancers was evaluated by this method and compared with that evaluated with radiology. RESULTS: Conventional laryngoscopy was unable to evaluate appreciably esophageal entrance involvement in the 113 patients with hypopharyngeal cancer. After injecting gas through the laryngoscopic biopsy channel, the esophageal entrance was clearly displayed in 96.5% (109/113) patients, showing the presence (33 cases) and absence (76 cases) of esophageal entrance invasion. Imaging examinations only showed the invasion of the esophageal entrance in 25 patients of these patients,but did not in other 8 patients. Laryngoscopy with injecting gas through the biopsy channel was superior to radiological imaging examinations in determining the invasion of the esophageal entrance (χ² = 9.103, P = 0.003). CONCLUSION: Laryngoscopy with injecting gas through the biopsy channel is a useful method for determining the presence or absence of esophageal entrance invasion in hypopharyngeal cancer prior to surgery.

[Value of endobronchial ultrasound-guided transbronchial needle aspiration in hilar and mediastinal lesions].

OBJECTIVE: To evaluate the diagnostic yield of endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) in cases of undiagnosed intrapulmonary lesions. METHODS: A total of 89 patients with intrathoracic lesions underwent EBUS-TBNA, including 56 pulmonary lesions, 7 lymph node staging in lung cancer patients, 21 unknown hilar and/or mediastinal lymphadenopathies and 5 mediastinal tumors. All samples were evaluated for cytological and pathological examinations. RESULTS: No complication of EBUS-TBNA was observed. Among 89 cases, 76 had positive results, 5 negative and 5 cases excluded as unsatisfied samples. In 56 patients with pulmonary lesions, EBUS-TBNA demonstrated 45 malignant tumors, 5 benign diseases, 3 suspicious cancers, 1 negative and 2 unsatisfied samples. In 7 lung cancer patients staged by EBUS-TBNA, 5 showed metastasis and 2 showed no metastasis. In 21 cases with mediastinal and/or hilar lymphadenopathy, EBUS-TBNA demonstrated 3 malignant tumors, 13 benign diseases, 2 negative and 3 unsatisfied samples. All 5 mediastinal lesions were malignant. Three suspicious cancers were confirmed, 1 by CT-guided percutaneous transthoracic needle biopsy and 2 by clinical follow-ups. In 2 lung cancer patients EBUS-TBNA showed negative, 1 surgical sample showed metastasis and another no metastasis by PET-CT. Three negative cases were diagnosed as benign by clinical follow-ups. The diagnostic sensitivity, specificity, positive predictive value and negative predictive value of EBUS-TBNA were 95%, 100%, 100% and 20% respectively. CONCLUSION: EBUS-TBNA is both effective and safe in making a diagnosis of intrathoracic lesions.

[Application of narrow band imaging endoscopy in the diagnosis of laryngeal cancer].

OBJECTIVE: To investigate the value of narrow band imaging (NBI) endoscopy in the detection of laryngeal cancer and its precursor lesions. METHODS: Between December 2008 and July 2009, a total of 122 consecutive patients with suspected precancerous or cancerous lesions of the larynx were enrolled in this study. High performance endoscopic system equipped with the white light mode and NBI mode was introduced in the examination of larynx. Full pharyngeal and laryngeal examination was performed first under white light endoscope and then under NBI. Each lesion was observed by NBI endoscopy and classified according to the detailed morphologic findings of epithelial microvessels. Histological results were then compared to the corresponding white light and NBI images. RESULTS: Among the 122 patients, a total of 149 lesions were detected by white light and NBI modes. The histological diagnoses of these lesions were as follows: 16 laryngeal polyp, 7 laryngitis, 24 simple hyperplasia, 17 mild dysplasia, 6 moderate dysplasia, 6 severe dysplasia, 9 carcinoma in situ, 64 invasive cancer. The diagnostic accuracy by NBI for the laryngeal lesions was 90.6% (135/149), which was significantly higher than that of white light (75.2%, 112/149, chi² = 12.514, P < 0.001). The sensitivity of NBI and white light to detect laryngeal carcinoma was 93.2% (68/73) and 68.5% (50/73), respectively (chi² = 14.317, P < 0.001). CONCLUSIONS: NBI endoscopy was a promising tool for the differentiation of non-malignant from malignant laryngeal lesions in vivo by detection of the morphology of mucosal capillary vessels. NBI endoscopy was easy to application in the routine pharyngolaryngeal examination with high sensitivity, and facilitated to improve the abilities of preoperative diagnosis and postoperative surveillance.