Differentiating malignant and benign lymph nodes using endobronchial ultrasound elastography

TransEBUS: The interpretation of endobronchial ultrasound image using hybrid transformer for differentiating malignant and benign mediastinal lesions

The purpose of this study is to establish a deep learning automatic assistance diagnosis system for benign and malignant classification of mediastinal lesions in endobronchial ultrasound (EBUS) images. EBUS images are in the form of video and contain multiple imaging modes. Different imaging modes and different frames can reflect the different characteristics of lesions. Compared with previous studies, the proposed model can efficiently extract and integrate the spatiotemporal relationships between different modes and does not require manual selection of representative frames. In recent years, Vision Transformer has received much attention in the field of computer vision. Combined with convolutional neural networks, hybrid transformers can also perform well on small datasets. This study designed a novel deep learning architecture based on hybrid transformer called TransEBUS. By adding learnable parameters in the temporal dimension, TransEBUS was able to extract spatiotemporal features from insufficient data. In addition, we designed a two-stream module to integrate information from three different imaging modes of EBUS. Furthermore, we applied contrastive learning when training TransEBUS, enabling it to learn discriminative representation of benign and malignant mediastinal lesions. The results show that TransEBUS achieved a diagnostic accuracy of 82% and an area under the curve of 0.8812 in the test dataset, outperforming other methods. It also shows that several models can improve performance by incorporating two-stream module. Our proposed system has shown its potential to help physicians distinguishing benign and malignant mediastinal lesions, thereby ensuring the accuracy of EBUS examination.

Minimally Invasive Sampling of Mediastinal Lesions

This narrative review examines the existing literature on minimally invasive image-guided sampling techniques of mediastinal lesions gathered from international databases (Medline, PubMed, Scopus, and Google Scholar). Original studies, systematic reviews with meta-analyses, randomized controlled trials, and case reports published between January 2009 and November 2023 were included. Four authors independently conducted the search to minimize bias, removed duplicates, and selected and evaluated the studies. The review focuses on the recent advancements in mediastinal sampling techniques, including EBUS-TBNA, EUS-FNA and FNB, IFB, and nodal cryobiopsy. The review highlights the advantages of an integrated approach using these techniques for diagnosing and staging mediastinal diseases, which, when used competently, significantly increase diagnostic yield and accuracy.

Quantitative evaluation of endobronchial ultrasound elastography in the diagnosis of benign and malignant mediastinal and hilar lymph nodes

OBJECTIVE

To compare the diagnostic value of different quantitative methods of endobronchial ultrasound elastography in benign and malignant mediastinal and hilar lymph nodes.

METHODS

This retrospective study included patients who underwent endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) for mediastinal and hilar lymph node enlargement in our hospital between January 2019 and August 2022. We compared different quantitative elastography parameters [red area ratio (RAR, lymph node red area/lymph node area), green area ratio (GAR, lymph node green area/lymph node area), blue area ratio (SAR, lymph node blue area/lymph node area), mixed area ratio (MAR, lymph node green area/lymph node area), blue-green lymph node area/lymph node area), strain rate ratio (SR), strain rate in the target lymph node (LPA), ratio of blue area to total lymph node area outside the center of the target lymph node (PAR), and average grey value (MGV)], in order to find the best quantitative evaluation method.

RESULTS

A total of 244 patients (346 lymph nodes) were included in this study. All quantitative elastography parameters were statistically significant for the differentiation of benign and malignant lesions except the average grey value of the target lymph nodes. The area under the receiver operating characteristic curve of SAR was 0.872 (95% confidence interval: 0.83-0.91), the cutoff value was 0.409, and the sensitivity, specificity, positive and negative predictive values were 85.4%, 78.0%, 80.4%, and 83.4%, respectively.

CONCLUSION

Compared with other types of quantitative analysis, SAR has a higher predictive significance for benign and malignant lymph nodes.

Quantitative analysis of endobronchial elastography combined with serum tumour markers of lung cancer in the diagnosis of benign and malignant mediastinal and hilar lymph nodes

Purpose: In malignant tumours, elastography and serum tumour markers have shown high diagnostic efficacy. Therefore, we aimed to quantitatively analyse the results of endobronchial elastography combined with serum tumour markers of lung cancer to accurately distinguish benign and malignant mediastinal and hilar lymph nodes. Methods: Data of patients who underwent endobronchial ultrasound-guided transbronchial needle aspiration for mediastinal lymph node enlargement in our hospital between January 2018 and August 2022 were retrospectively collected. The characteristics of quantitative elastography and serum tumour markers were evaluated. Results: We enrolled 197 patients (273 lymph nodes). In the differential diagnosis of benign and malignant mediastinal and hilar lymph nodes, the stiffness area ratio (SAR), strain ratio (SR), and strain rate in lymph nodes were significant, among which SAR had the highest diagnostic value (cut-off value, 0.409). The combination of the four tumour markers had a high diagnostic value (AUC, 0.886). Three types of quantitative elastography indices combined with serum tumour markers for lung cancer showed a higher diagnostic value (AUC, 0.930; sensitivity, 83.5%; specificity, 89.3%; positive predictive value, 88.1%; negative predictive value, 85%) (p < 0.05). In the differential diagnosis of pathological types of lung cancer, different quantitative elastography indicators and serum tumour markers for lung cancer have different diagnostic significance for the differential diagnosis of lung cancer pathological types. Conclusion: The quantitative analysis of endobronchial ultrasound elastography combined with tumour markers can improve the diagnosis rate of benign and malignant mediastinal and hilar lymph nodes, help guide the puncture of false negative lymph nodes, and reduce the misdiagnosis rate.

Associations of Real-Time Ultrasound and Strain and Shear Wave Elastography with Gastrointestinal Organs: A Systematic Review

Ultrasound elastography is gaining attention for its diagnostic potential across various medical fields, and its physical properties make it valuable in modern clinical medicine. However, its specific attributes, especially in the context of recent medical advancements, remain relatively unexplored. This study aimed to identify instrument-specific characteristics and applications of real-time ultrasound elastography, shear wave elastography, and strain elastography, particularly within gastroenterology. Following PRISMA guidelines, the study examined elastography articles on databases like PubMed, resulting in 78 included articles. Data on patient demographics, organ involvement, specificity, sensitivity, accuracy, positive predictive value, and negative predictive value were extracted. Statistical analysis involved SPSS version 21, with significance set at p < 0.05. The majority of patients were male (50.50%), with a mean age of 42.73 ± 4.41 years. Shear wave elastography was the most prevalent technique (48.7%), and liver investigations were predominant in gastroenterology (34.6%). Gastrointestinal applications showed higher sensitivity, positive predictive value, and negative predictive values (p < 0.05) but lower specificity (p < 0.05). Real-time ultrasound elastography exhibited increased specificity, accuracy, and predictive values (p < 0.05). Ultrasound elastography appears more accurate and effective in gastroenterological settings. Nonetheless, its performance depends on instrument-specific and operator-dependent factors. While promising, further studies are necessary to ascertain optimal utilization in both gastrointestinal and non-gastrointestinal conditions.

Research to develop a diagnostic ultrasound nomogram to predict benign or malignant lymph nodes in HIV-infected patients

BACKGROUND

This study aimed to establish an effective ultrasound diagnostic nomogram for benign or malignant lymph nodes in HIV-infected patients.

METHODS

The nomogram is based on a retrospective study of 131 HIV-infected patients who underwent ultrasound assess at the Shanghai Public Health Clinical Center from December 2017 to July 2022. The nomogram's predictive accuracy and discriminative ability were determined by concordance index (C-index) and calibration curve analysis. A nomogram combining the lymph node US characteristics were generated based on the multivariate logistic regression results.

RESULTS

Predictors contained in the ultrasound diagnostic nomogram included age (OR 1.044 95%CI: 1.014-1.074 P = 0.004), number of enlarged lymph node regions (OR 5.445 95%CI: 1.139-26.029 P = 0.034), and color Doppler flow imaging (CDFI) grades (OR 9.614 95%CI: 1.889-48.930 P = 0.006). The model displayed good discrimination with a C (ROC) of 0.775 and good calibration.

CONCLUSIONS

The proposed nomogram may result in more-accurate diagnostic predictions for benign or malignant lymph nodes in patients with HIV infection.

The role of endobronchial ultrasonography elastography in the diagnosis of hilar and mediastinal lymph nodes

BACKGROUND

Endobronchial ultrasonography (EBUS) is a minimally invasive diagnostic tool in the diagnosis of mediastinal lymph nodes (LNs) and has sonographic features. We aimed to investigate the diagnostic accuracy of EBUS elastography, which evaluates tissue compressibility integrated into EBUS, on malignant vs. benign mediastinal-hilar LNs.

METHODS

A single-center, prospective study was conducted at the University of Health Sciences Yedikule Chest Diseases and Thoracic Surgery Training and Research Hospital between 01/10/2019 and 15/11/2019. The features of 219 LNs evaluated by thoracic computed tomography (CT), positron emission tomography (PET)/CT, EBUS sonography and EBUS elastography were recorded. The LNs sampled by EBUS-guided fine needle aspiration were classified according to EBUS elastography color distribution findings as follows: type 1, predominantly nonblue (green, yellow, and red); type 2, part blue, part nonblue; type 3, predominantly blue. The strain ratio (SR) was calculated based on normal tissue with the relevant region.

RESULTS

The average age of 131 patients included in the study was 55.86 ± 13 years, 76 (58%) were male. Two hundred and nineteen lymph nodes were sampled from different stations. Pathological diagnosis of 75 (34.2%) LNs was malignant, the rest was benign. When EBUS B-mode findings and pathological results were compared, sensitivity was 65.33%, specificity 63.19%, positive predictive value (PPV) 48%, negative predictive value (NPV) 77.8%, and diagnostic yield (DY) 64%. When the pathological diagnoses and EBUS elastography findings were compared, while type 1 LNs were considered to be benign and type 3 LNs malignant, sensitivity 94.12%, specificity 86.54%, PPV 82.1%, NPV 95.7%, and DY 89.5%. SR of malignant LNs was significantly higher than benign LNs (p < 0.001). When the classification according to color scale and SR were compared, no difference was found in DY (p = 0.155).

DISCUSSION

The diagnostic accuracy of EBUS elastography is high enough to distinguish malignant LN from benign ones with the SR option. When compared with EBUS-B mode sonographic findings, it was found to have a higher diagnostic yield.

Predicting Malignant Lymph Nodes Using a Novel Scoring System Based on Multi-Endobronchial Ultrasound Features

Endobronchial ultrasound (EBUS) features with B-, power/color Doppler, and elastography modes help differentiate between benign and malignant lymph nodes (MLNs) during transbronchial needle aspiration (TBNA); however, only few studies have assessed them simultaneously. We evaluated the diagnostic accuracy of each EBUS feature and aimed to establish a scoring system to predict MLNs. EBUS features of consecutive patients and final diagnosis per lymph node (LN) were examined retrospectively. In total, 594 LNs from 301 patients were analyzed. Univariable analyses revealed that EBUS features, except for round shape, could differentiate MLNs from benign LNs. Multivariable analysis revealed that short axis (>1 cm), heterogeneous echogenicity, absence of central hilar structure, presence of coagulation necrosis sign, and blue-dominant elastographic images were independent predictors of MLNs. At three or more EBUS features predicting MLNs, our scoring system had high sensitivity (77.9%) and specificity (91.8%). The area under the receiver operating curve (AUC) was 0.894 (95% confidence interval (CI): 0.868−0.920), which was higher than that of B-mode features alone (AUC: 0.840 (95% CI: 0.807−0.873)). The novel scoring system could predict MLNs more accurately than B-mode features alone. Multi-EBUS features may increase EBUS-TBNA efficiency for LN evaluation.

Utility of Elastography for Differentiating Malignant and Benign Lymph Nodes During EBUS-TBNA: A Systematic Review and Meta-analysis

BACKGROUND

Ultrasound elastography noninvasively estimates tissue hardness. Studies have evaluated elastography for differentiating malignant from benign lymph nodes during endobronchial ultrasound-guided transbronchial needle aspiration. Several methods of performing elastography are described with variable diagnostic accuracy.

METHODS

The aim of this study was to evaluate endobronchial ultrasound-guided elastography in differentiating malignant from benign mediastinal lymphadenopathy. We performed a systematic search of the PubMed and Embase databases to extract the relevant studies. A diagnostic accuracy meta-analysis was carried out to calculate the pooled sensitivity and specificity [with 95% confidence intervals (CIs)], and positive and negative likelihood ratios of elastography.

RESULTS

After a systematic search, 20 studies (1600 patients, 2712 nodes) were selected. The pooled sensitivity and specificity of elastography were 0.90 (95% CI, 0.84-0.94) and 0.79 (95% CI, 0.73-0.84), respectively. The summary receiver operating curve demonstrated an area under the curve for elastography of 0.90 (0.88-0.93). The positive and negative likelihood ratios and the diagnostic odds ratio were 4.3 (95% CI, 3.3-5.5), 0.12 (95% CI, 0.07-0.20), and 35 (95% CI, 19-63), respectively. Of the most commonly described methods, the color classification method (type 3 malignant vs. type 1 benign) demonstrated the highest area under the curve of 0.91 (0.88-0.93). There was significant heterogeneity and publication bias. Subgroup analyses indicated no significant difference between the sensitivity and specificity of quantitative and qualitative elastography methods.

CONCLUSIONS

Ultrasound elastography is useful in differentiating malignant and benign lymph nodes during endobronchial ultrasound-guided transbronchial needle aspiration. However, elastography does not replace the requirement of lymph node aspiration.

Diagnostic value of endobronchial ultrasound elastography combined with rapid onsite cytological evaluation in endobronchial ultrasound-guided transbronchial needle aspiration

Background

Endobronchial ultrasound (EBUS) elastography has been used in EBUS-guided transbronchial needle aspiration (EBUS-TBNA) to identify malignant lymph nodes based on tissue stiffness. Rapid onsite cytological evaluation (ROSE) has been widely utilized for onsite evaluation of sample adequacy and for guiding sampling during EBUS-TBNA. The aim of this study was to investigate the diagnostic value of combined EBUS elastography and ROSE in evaluating mediastinal and hilar lymph node status.

Methods

Retrospective chart review was performed from December 2018 to September 2020. Patient demographics, EBUS elastography scores, and ROSE, pathologic, and clinical outcome data were collected. The EBUS elastography scores were classified as follows: Type 1, predominantly nonblue; Type 2, partially blue and partially nonblue; and Type 3, predominantly blue. A receiver operating characteristic curve was used to compare the sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, and negative likelihood ratio for evaluation of malignant lymph nodes among the EBUS elastography, ROSE, and EBUS combined with ROSE groups.

Results

A total of 245 patients (345 lymph nodes) were included. The sensitivity and specificity of the EBUS elastography group for the diagnosis of malignant lymph nodes were 90.51% and 57.26%, respectively. The sensitivity and specificity in the ROSE group were 96.32% and 79.05%, respectively. The sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio of EBUS elastography combined with ROSE were 86.61%, 92.65%, 11.78, and 0.14, respectively, and the area under the curve was 0.942.

Conclusions

Combining EBUS elastography and ROSE significantly increased the diagnostic value of EBUS-TBNA in evaluating mediastinal and hilar lymph node status compared to each method alone.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-021-01748-4.

Ultrasound Elastography for the Evaluation of Lymph Nodes

The differential diagnosis of lymphadenopathy is important for predicting prognosis, staging, and monitoring the treatment, especially for cancer patients. Conventional computed tomography and magnetic resonance imaging characterize lymph node (LN) with disappointing sensitivity and specificity. Conventional ultrasound with the advantage of high resolution has been widely used for the LN evaluation. Ultrasound elastography (UE) using color map or shear wave velocity can non-invasively demonstrate the stiffness and homogeneity of both the cortex and medulla of LNs and can detect early circumscribed malignant infiltration. There is a need of a review to comprehensively discuss the current knowledge of the applications of various UE techniques in the evaluation of LNs. In this review, we discussed the principles of strain elastography and shear wave-based elastography, and their advantages and limitations in the evaluation of LNs. In addition, we comprehensively introduced the applications of various UE techniques in the differential diagnosis of reactive LNs, lymphoma, metastatic LNs, and other lymphadenopathy. Moreover, the applications of endoscopic UE and endobronchial UE are also discussed, including their use for improving the positive rate of diagnosis of fine-needle aspiration biopsy.

Automatic Image Selection Model Based on Machine Learning for Endobronchial Ultrasound Strain Elastography Videos

Background

Endoscopic ultrasound (EBUS) strain elastography can diagnose intrathoracic benign and malignant lymph nodes (LNs) by reflecting the relative stiffness of tissues. Due to strong subjectivity, it is difficult to give full play to the diagnostic efficiency of strain elastography. This study aims to use machine learning to automatically select high-quality and stable representative images from EBUS strain elastography videos.

Methods

LNs with qualified strain elastography videos from June 2019 to November 2019 were enrolled in the training and validation sets randomly at a quantity ratio of 3:1 to train an automatic image selection model using machine learning algorithm. The strain elastography videos in December 2019 were used as the test set, from which three representative images were selected for each LN by the model. Meanwhile, three experts and three trainees selected one representative image severally for each LN on the test set. Qualitative grading score and four quantitative methods were used to evaluate images above to assess the performance of the automatic image selection model.

Results

A total of 415 LNs were included in the training and validation sets and 91 LNs in the test set. Result of the qualitative grading score showed that there was no statistical difference between the three images selected by the machine learning model. Coefficient of variation (CV) values of the four quantitative methods in the machine learning group were all lower than the corresponding CV values in the expert and trainee groups, which demonstrated great stability of the machine learning model. Diagnostic performance analysis on the four quantitative methods showed that the diagnostic accuracies were range from 70.33% to 73.63% in the trainee group, 78.02% to 83.52% in the machine learning group, and 80.22% to 82.42% in the expert group. Moreover, there were no statistical differences in corresponding mean values of the four quantitative methods between the machine learning and expert groups (p >0.05).

Conclusion

The automatic image selection model established in this study can help select stable and high-quality representative images from EBUS strain elastography videos, which has great potential in the diagnosis of intrathoracic LNs.

Deep learning with convex probe endobronchial ultrasound multimodal imaging: A validated tool for automated intrathoracic lymph nodes diagnosis

Background and Objectives:

Along with the rapid improvement of imaging technology, convex probe endobronchial ultrasound (CP-EBUS) sonographic features play an increasingly important role in the diagnosis of intrathoracic lymph nodes (LNs). Conventional qualitative and quantitative methods for EBUS multimodal imaging are time-consuming and rely heavily on the experience of endoscopists. With the development of deep-learning (DL) models, there is great promise in the diagnostic field of medical imaging.

Materials and Methods:

We developed DL models to retrospectively analyze CP-EBUS images of 294 LNs from 267 patients collected between July 2018 and May 2019. The DL models were trained on 245 LNs to differentiate benign and malignant LNs using both unimodal and multimodal CP-EBUS images and independently evaluated on the remaining 49 LNs to validate their diagnostic efficiency. The human comparator group consisting of three experts and three trainees reviewed the same test set as the DL models.

Results:

The multimodal DL framework achieves an accuracy of 88.57% (95% confidence interval [CI] [86.91%–90.24%]) and area under the curve (AUC) of 0.9547 (95% CI [0.9451–0.9643]) using the three modes of CP-EBUS imaging in comparison to the accuracy of 80.82% (95% CI [77.42%–84.21%]) and AUC of 0.8696 (95% CI [0.8369–0.9023]) by experts. Statistical comparison of their average receiver operating curves shows a statistically significant difference (P < 0.001). Moreover, the multimodal DL framework is more consistent than experts (kappa values 0.7605 vs. 0.5800).

Conclusions:

The DL models based on CP-EBUS imaging demonstrated an accurate automated tool for diagnosis of the intrathoracic LNs with higher diagnostic efficiency and consistency compared with experts.

Diagnostic value of endobronchial ultrasound image features: A specialized review

Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) technology is important in the diagnosis of intrathoracic benign and malignant lymph nodes (LNs). With the development of EBUS imaging technology, its role in noninvasive diagnosis, as a supplement to pathology diagnosis, has been given increasing attention in recent years. Many studies have explored qualitative and quantitative methods for the three EBUS modes, as well as a variety of multimodal analysis methods, to find the optimal method for the noninvasive diagnosis using EBUS for LNs. Here, we review and comment on the research methods and predictive diagnostic value, discuss the existing problems, and look ahead to the future application of EBUS imaging.

CT texture analysis of mediastinal lymphadenopathy: Combining with US-based elastographic parameter and discrimination between sarcoidosis and lymph node metastasis from small cell lung cancer

Objectives

To investigate the potential of computed tomography (CT)-based texture analysis and elastographic data provided by endobronchial ultrasonography (EBUS) for differentiating the mediastinal lymphadenopathy by sarcoidosis and small cell lung cancer (SCLC) metastasis.

Methods

Sixteen patients with sarcoidosis and 14 with SCLC were enrolled. On CT images showing the largest mediastinal lymph node, a fixed region of interest was drawn on the node, and texture features were automatically measured. Among the 30 patients, 19 (12 sarcoidosis and 7 SCLC) underwent endobronchial ultrasound transbronchial needle aspiration, and the fat-to-lesion strain ratio (FLR) was recorded. Texture features and FLRs were compared between the 2 patient groups. Logistic regression analysis was performed to evaluate the diagnostic accuracy of these measurements.

Results

Of the 31 texture features, the differences between 11 texture features of CT ROIs in the patients with sarcoidosis versus patients with SCLC were significant. Among them, the grey-level run length matrix with high gray-level run emphasis (GLRLM-HGRE) showed the greatest difference (P<0.01). Differences between FLRs were significant (P<0.05). Logistic regression analysis together with receiver operating characteristic curve analysis demonstrated that the FLR combined with the GLRLM-HGRE showed a high diagnostic accuracy (100% sensitivity, 92% specificity, 0.988 area under the curve) for discriminating between sarcoidosis and SCLC.

Conclusion

Texture analysis, particularly combined with the FLR, is useful for discriminating between mediastinal lymphadenopathy caused by sarcoidosis from that caused by metastasis from SCLC.

Recent developments in advanced diagnostic bronchoscopy

The field of bronchoscopy is advancing rapidly. Minimally invasive diagnostic approaches are replacing more aggressive surgical ones for the diagnosis and staging of lung cancer. Evolving diagnostic modalities allow early detection and serve as an adjunct to early treatment, ideally influencing patient outcomes. In this review, we will elaborate on recent bronchoscopic developments as well as some promising investigational tools and approaches in development. We aim to offer a concise overview of the significant advances in the field of advanced bronchoscopy and to put them into clinical context. We will also address potential complications and current diagnostic challenges associated with sampling central and peripheral lung lesions.

Quantitative analysis of endobronchial ultrasound elastography in computed tomography-negative mediastinal and hilar lymph nodes

Background

Endobronchial ultrasound (EBUS) elastography assists in the differentiation of benign and malignant lymph nodes (LNs) during transbronchial needle aspiration (TBNA). However, previous studies have not compared B‐mode sonographic images (BSIs) and EBUS elastography images (EEIs) with final pathological diagnoses in radiologically normal‐sized (computed tomography [CT]‐negative) LNs.

Methods

Consecutive patients with CT‐negative LNs, who received EBUS‐TBNA, were retrospectively reviewed. Images of BSIs and EEIs of each LN were stored and independently evaluated. EEIs were assessed by calculating the stiffness area ratio (SAR, blue/overall areas). The receiver operating characteristic curve was used to calculate the cutoff value for the SAR. Diagnostic test parameters were evaluated for each EBUS finding.

Results

A total of 132 patients (149 LNs) were enrolled, and the median SAR of malignant LNs was significantly higher than that of benign LNs (0.58 vs. 0.32, P < 0.001). At the SAR cutoff of 0.41, the sensitivity, specificity, positive predictive value, negative predictive value (NPV), and diagnostic accuracy rate (DAR) of elastography were 88.2%, 80.2%, 78.9%, 89.0%, and 83.9%, respectively. The logistic regression analysis showed that elastography was the strongest predictor of malignancy (odds ratio, 18.5; 95% confidence interval [CI]: 6.48–52.6; P < 0.001). The highest NPV (96.6%) was achieved with a combination of BSIs and EEIs.

Conclusions

EBUS elastography predicted malignant LNs with a high DAR and NPV in CT‐negative LNs. The NPV was highest when EEIs were combined with BSIs. Therefore, the combined evaluation of CT‐negative LNs using EEIs and BSIs may help bronchoscopists perform EBUS‐TBNA more efficiently.

Key points

Significant findings of the study

Endobronchial ultrasound elastography accurately predicted malignancy with a high diagnostic accuracy rate and negative predictive value in radiologically normal‐sized lymph nodes. The additional use of B‐mode sonographic features resulted in a higher negative predictive value.

What this study adds

Endobronchial ultrasound elastography can guide the accurate collection of specimens with transbronchial needle aspiration, even in radiologically normal‐sized lymph nodes. It can also readily distinguish benign and malignant lymph nodes, thus avoiding unnecessary punctures.

The utility of elastography during EBUS-TBNA in a population with a high prevalence of anthracosis

BACKGROUND

Ultrasound elastography, is a pioneer sonographic modality that is conducted during endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) in order to increase the accuracy of sampling location. The current study aims to evaluate the usefulness of elastography during EBUS-TBNA in a population with a high prevalence of anthracosis.

METHODS

This prospective single-blinded study was performed on 69 lymph nodes (LNs) of patients with mediastinal lymphadenopathy undergoing EBUS-TBNA and EBUS-elastography from October 2017 to July 2018. The stiffness level of the tissue was translated into a color to demonstrate the hardness of tissue. Blue and total areas of each section were measured to calculate the hardness of each LN.

RESULTS

Sixty-nine LNs were evaluated by elastography. Twenty percent of LNs were malignant. There was a statistical difference between malignant and non-malignant nodes based on color dominancy (P = 0.032). However, with the exclusion of anthracosis nodes from the analysis, the difference was more significant (P < 0.001). Moreover, when the blue dominancy was used as the predictor of malignancy or anthracosis, the results showed a significant correlation (P < 001).

CONCLUSION

The usefulness of elastography in selecting the hardest area of tissue that is appropriate for diagnosing diseases has been proven previously. Since in countries with a high prevalence of anthracosis, blue color achieved using elastography predicts either malignancy or anthracosis so, cases with blue dominancy of LNs in elastography and the white color in the EBUS-TBNA indicate anthracosis-caused calcification should be reconsidered.

The role of endobronchial ultrasonography elastography for predicting malignancy

Background

This study aims to investigate the role of endobronchial ultrasonography elastography in predicting malignancy.

Methods

Between January 2016 and December 2016, a total of 221 lymph nodes were biopsied using the endobronchial ultrasonography-guided transbronchial needle aspiration from 119 consecutive patients (69 males, 50 females; mean age 63.2±12.4 years; range, 16 to 86 years) were included. Lymph nodes were scored by elastography according to their colors in four categories before the procedure. The strain ratio was calculated based on the region of interest after three measurements.

Results

Of the patients, 93 were diagnosed with a malignancy through endobronchial ultrasonography-guided transbronchial needle aspiration biopsy. The mean lymph node score of benign versus malignant lesions was 2.2±1.0 and 3.2±1, respectively (p<0.001). There was a positive correlation between the lymph node scores and lymph node diameter, strain ratio, ≥3 of lymph node scoring, the sensitivity for malignancy was 79% and specificity was 60%. The mean strain ratio for malignant and benign lymph nodes was 22.2±30.1 and 5.2±1.7, respectively (p<0.001). With a cut-off value of ≥2.47 of strain ratio, the sensitivity for malignancy was 75% and specificity was 65%. The combined use of positron emission tomography and lymph node score or strain ratio yielded 80.4% and 61.2% sensitivity and 80% and 70.3% specificity for malignancy, respectively.

Conclusion

Endobronchial ultrasonography elastography is useful in predicting malignancy of the lymph nodes. When combined with positron emission tomography, specificity and positive predictive value for malignancy increase.