Sonographic Features of Endobronchial Ultrasound in Differentiation of Benign Lymph Nodes

A risk-scoring model based on endobronchial ultrasound multimodal imaging for predicting metastatic lymph nodes in lung cancer patients

Background and Objectives

Endobronchial ultrasound (EBUS) imaging is a valuable tool for predicting lymph node (LN) metastasis in lung cancer patients. This study aimed to develop a risk-scoring model based on EBUS multimodal imaging (grayscale, Doppler mode, elastography) to predict LN metastasis in lung cancer patients.

Patients and Methods

This retrospective study analyzed 350 metastatic LNs in 314 patients with lung cancer and 124 reactive LNs in 96 patients with nonspecific inflammation. The sonographic findings were compared with the final pathology results and clinical follow-up. Univariate and multivariate logistic regression analyses were performed to evaluate the independent risk factors of metastatic LNs. According to the β coefficients of corresponding indicators in logistic regression analysis, a risk-scoring model was established. Receiver operating characteristic curve was applied to evaluate the predictive capability of model.

Results

Multivariate analysis showed that short axis >10 mm, distinct margin, absence of central hilar structure, presence of necrosis, nonhilar vascularity, and elastography score 4 to 5 were independent predictors of metastatic LNs. Both short axis and margin were scored 1 point, and the rest of independent predictors were scored 2 points. The combination of 3 EBUS modes had the highest area under the receiver operating characteristic and accuracy of 0.884 (95% confidence interval, 0.846-0.922) and 87.55%, respectively. The risk stratification was as follows: 0 to 2 points, malignancy rate of 11.11%, low suspicion; 3 to 10 points, malignancy rate of 86.77%, high suspicion.

Conclusions

The risk-scoring model based on EBUS multimodal imaging can effectively evaluate metastatic LNs in lung cancer patients to support clinical decision making.

A Nomogram to Predict Benign/Malignant Mediastinal Lymph Nodes Based on EBUS Sonographic Features

Background

Endobronchial ultrasound (EBUS) sonographic features help identify benign/malignant lymph nodes while conducting transbronchial needle aspiration (TBNA). This study aims to identify risk factors for malignancy based on EBUS sonographic features and to estimate the risk of malignancy in lymph nodes by constructing a nomogram.

Methods

1082 lymph nodes from 625 patients were randomly enrolled in training (n = 760) and validation (n = 322) sets. The subgroup of EBUS-TBNA postoperative negative lymph nodes (n = 317) was randomly enrolled in a training (n = 224) set and a validation (n = 93) set. Logistic regression analysis was used to identify the EBUS features of malignant lymph nodes. A nomogram was formulated using the EBUS features in the training set and later validated in the validation set.

Results

Multivariate analysis revealed that long-axis, short-axis, echogenicity, fusion, and central hilar structure (CHS) were the independent predictors of malignant lymph nodes. Based on these risk factors, a nomogram was constructed. Both the training and validation sets of 5 EBUS features nomogram showed good discrimination, with area under the curve values of 0.880 (sensitivity = 0.829 and specificity = 0.807) and 0.905 (sensitivity = 0.819 and specificity = 0.857). Subgroup multivariate analysis revealed that long-axis, echogenicity, and CHS were the independent predictors of malignancy outcomes of EBUS-TBNA postoperative negative lymph nodes. Based on these risk factors, a nomogram was constructed. Both the training and validation sets of 3 EBUS features nomogram showed good discrimination, with the area under the curve values of 0.890 (sensitivity = 0.882 and specificity = 0.786) and 0.834 (sensitivity = 0.930 and specificity = 0.636).

Conclusions

Our novel scoring system based on two nomograms can be utilized to predict malignant lymph nodes.

Effect of Needle Size on Diagnosis of Sarcoidosis with Endobronchial Ultrasound-guided Transbronchial Needle Aspiration: Systematic Review and Meta-Analysis

Background: Sarcoidosis is a multisystem disease characterized by noncaseating granulomatous inflammation that most commonly involves the lungs. Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) has become an invaluable tool in the assessment of patients with mediastinal and/or hilar lymphadenopathy. Objective: It has been hypothesized that use of the larger 19-gauge (G) needle with EBUS-TBNA improves diagnostic sensitivity in sarcoidosis. However, it is unclear whether the existing literature supports this supposition. Data Sources: A literature search of Embase and Medline was performed by two reviewers. Included articles were evaluated for bias using the QUADAS-2 tool. Data Extraction: For quantitative analysis, we performed a meta-analysis using a binary random-effects model to determine pooled sensitivity. Subgroup analysis was performed based on needle size, use of rapid on-site evaluation (ROSE), study design, and prevalence of sarcoidosis in study group. Synthesis: Sixty-five studies with a total of 4,242 patients were included in the meta-analysis. Overall pooled sensitivity for diagnosis of sarcoidosis was 83.99% (95% confidence interval [CI], 81.22-86.53) among all studies. The 19G subgroup had a significantly higher sensitivity (93.73%; 95% CI, 89.72-97.74%; I² = 0.00%; P < 0.01) compared with the 21G subgroup (84.61%; 95% CI, 78.80-90.42%; I² = 69.83%), 22G subgroup (84.07%; 95% CI, 80.90-87.24%; I² = 85.21%) or unspecified 21G/22G subgroup (78.85%; 95% CI, 70.81-86.90%; I² = 84.47%). There were no significant differences with use of ROSE or prevalence of sarcoidosis or by study design. Conclusions: The use of 19G needles during EBUS-TBNA had the highest diagnostic sensitivity based on available studies. Further randomized controlled trials using 19G needles should be considered in patients with suspected sarcoidosis.

Clinical Validation of the Canada Lymph Node Score for Endobronchial Ultrasound

BACKGROUND

The Canada Lymph Node Score (CLNS) uses four sonographic criteria to predict the risk of malignancy in lymph nodes during endobronchial ultrasound (EBUS). CLNS may play a role in identifying targets for biopsy or re-biopsy during invasive mediastinal staging for lung cancer. However, CLNS has not yet been prospectively validated in routine clinical practice.

METHODS

CLNS scores for each lymph node biopsied during EBUS were prospectively captured for one year (2019). CLNS and the presence of malignancy in each node were compared. Univariate binary logistic regression was completed for each ultrasonographic feature, as well as a multivariate logistic regression model.

RESULTS

CLNS and diagnostic pathology results were available for 367 lymph nodes. Incidence of malignancy increased with higher scores. Scores ≥3 were significantly associated with malignancy (specificity 84.4%, positive likelihood ratio 4.0). Area under the curve was 0.76, indicating a good ability of the model to predict presence or absence of malignancy. Nodes scoring <2 and negative on CT and PET were malignant in 10.1%.

CONCLUSIONS

CLNS correlates with the presence or absence of malignancy in thoracic lymph nodes, and may serve as an adjunct to currently available methods of invasive and non-invasive mediastinal staging. CLNS may be most helpful to select which non-diagnostic nodes require re-biopsy. There is a significant risk of a false negative result even with a score of 0, and using a combination of low CLNS and negative conventional radiology to obviate the need for any initial biopsy remains to be studied in prospective trials.

Application of neck ultrasound in the diagnosis of sarcoidosis

Objective

To explore the significance of neck ultrasound (NUS) combined with contrast-enhanced ultrasound (CEUS) in the diagnosis of sarcoidosis.

Methods

88 patients with evidence of intrathoracic lymphadenopathy and suspected sarcoidosis with enlarged cervical lymph nodes underwent NUS, CEUS, fine-needle aspiration and core needle biopsy when technically feasible were retrospectively analyzed in this study. Seven characteristics such as enhanced mode (EM), resolution time, color Doppler flow imaging (CDFI), fading time, peaking state-uniformity, strengthen the area and symmetry were considered to perform the logistic regression model.

Results

Of 88 patients included in this study, sarcoidosis was accounted in 20 cases, tuberculosis in 23 cases, malignancy in 22 cases and inflammatory lymph node in 23 cases. There were statistically significant differences in symmetry, lymphatic hilum, homogeneity, CDFI pattern and elasticity score between the sarcoidosis and non-sarcoidosis groups via NUS. Similarly, we also acknowledged a statistically significant differences in EM, homogeneity, presence or absence of necrosis between the sarcoidosis and non-sarcoidosis groups via CEUS to further group the non-sarcoidosis into tuberculosis, malignancy or inflammatory disorder. The percentage correction of prediction was 90% (18/20).

Conclusion

NUS combined with CEUS has characteristic features in sarcoidosis with cervical lymph node involvement, which is helpful for its diagnosis and differential diagnosis. The binary classification model of NUS combined with CEUS features can help differentiate sarcoidosis from non-sarcoidosis groups.

Endobronchial Ultrasound-Guided Transbronchial Needle Aspiration (EBUS-TBNA): Technical Updates and Pathological Yield

Since the endobronchial ultrasound bronchoscope was introduced to clinical practice, endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) has become the procedure of choice to sample hilar and mediastinal adenopathy. Multiple studies have been conducted in the last two decades to look at the different technical aspects of the procedure and their effects on the final cytopathological yield. In addition, newer modes of ultrasound scanning and newer tools with the potential to optimize the selection and sampling of the target lymph node have been introduced. These have the potential to reduce the number of passes, reduce the procedure time, and increase the diagnostic yield, especially in rare tumors and benign diseases. Herein, we review the latest updates related to the technical aspects of EBUS-TBNA and their effects on the final cytopathological yield in malignant and benign diseases.

Endobronchial Ultrasound Multimodal Imaging for the Diagnosis of Intrathoracic Lymph Nodes

BACKGROUND

Endobronchial ultrasound (EBUS) imaging is valuable in diagnosing intrathoracic lymph nodes (LNs), but there has been little analysis of multimodal imaging. This study aimed to comprehensively compare the diagnostic performance of single and multimodal combinations of EBUS imaging in differentiating benign and malignant intrathoracic LNs.

METHODS

Subjects from July 2018 to June 2019 were consecutively enrolled in the model group and July 2019 to August 2019 in the validation group. Sonographic features of three EBUS modes were analysed in the model group for the identification of malignant LNs from benign LNs. The validation group was used to verify the diagnostic efficiency of single and multimodal diagnostic methods built in the model group.

RESULTS

373 LNs (215 malignant and 158 benign) from 335 subjects and 138 LNs (79 malignant and 59 benign) from 116 subjects were analysed in the model and validation groups, respectively. For single mode, elastography had the best diagnostic value, followed by grayscale and Doppler. The corresponding accuracies in the validation group were 83.3%, 76.8%, and 71.0%, respectively. Grayscale with elastography had the best diagnostic efficiency of multimodal methods. When at least two of the three features (absence of central hilar structure, heterogeneity, and qualitative elastography score 4-5) were positive, the sensitivity, specificity, and accuracy in the validation group were 88.6%, 78.0%, and 84.1%, respectively.

CONCLUSIONS

In both model and validation groups, elastography performed the best in single EBUS modes, as well as grayscale combined with elastography in multimodal imaging. Elastography alone or combined with grayscale are feasible to help predict intrathoracic benign and malignant 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.

Can artificial intelligence distinguish between malignant and benign mediastinal lymph nodes using sonographic features on EBUS images?

AIMS

This study aimed to develop a new intelligent diagnostic approach using an artificial neural network (ANN). Moreover, we investigated whether the learning-method-guided quantitative analysis approach adequately described mediastinal lymphadenopathies on endobronchial ultrasound (EBUS) images.

METHODS

In total, 345 lymph nodes (LNs) from 345 EBUS images were used as source input datasets for the application group. The group consisted of 300 and 45 textural patterns as input and output variables, respectively. The input and output datasets were processed using MATLAB. All these datasets were utilized for the training and testing of the ANN.

RESULTS

The best diagnostic accuracy was 82% of that obtained from the textural patterns of the LNs pattern (89% sensitivity, 72% specificity, and 78.2% area under the curve). The negative predictive values were 81% compared to the corresponding positive predictive values of 83%. Due to the application group's pattern-based evaluation, the LN pattern was statistically significant (p = .002).

CONCLUSIONS

The proposed intelligent approach could be useful in making diagnoses. Further development is required to improve the diagnostic accuracy of the visual interpretation.

Comparison of Ultrasound Features of Major Salivary Glands in Sarcoidosis, Amyloidosis, and Sjögren's Syndrome

OBJECTIVE

While salivary gland ultrasound (SGU) has gained prominence for evaluating Sjögren's syndrome, little information exists on SGU appearance of sarcoidosis and amyloidosis, potential mimics of Sjögren's syndrome. Our goal in this study was to estimate the diagnostic accuracy of major SGU features in differentiating Sjögren's syndrome from sarcoidosis, amyloidosis, and controls.

METHODS

We enrolled consecutive adult ambulatory patients with a clinical diagnosis of Sjögren's syndrome fulfilling the 2016 American College of Rheumatology (ACR) classification criteria; we also enrolled patients with a clinical diagnosis of sarcoidosis or systemic immunoglobulin light chain (AL) amyloidosis, with histologic confirmation from any tissue, and rheumatology outpatients without diagnoses affecting salivary glands. Subjects underwent major SGU using the Hočevar protocol, with resulting video clips reviewed blind to clinical diagnosis.

RESULTS

Sjögren's syndrome SGU scores were greater than in patients from the other groups, but there were no distinguishing salivary gland features from AL amyloidosis or sarcoidosis. None of the patients in the control group scored higher than 17, a cutoff previously suggested for Sjögren's syndrome, but 27% of patients with AL amyloidosis and 19% with sarcoidosis scored higher than 17. Adding Hočevar SGU scores of ≥17 to the 2016 ACR/European League Against Rheumatism criteria in a parallel scheme increased the sensitivity for Sjögren's syndrome from 87% to 98%, while combining the 2 criteria in series increased specificity from 81% to 98%.

CONCLUSION

Sjögren's syndrome, sarcoidosis, and AL amyloidosis share common SGU features that can help distinguish these conditions from patients without systemic rheumatologic disease. Clinicians should carefully consider these potential mimics when interpreting salivary gland US results.

The role of endobronchial ultrasound-guided transbronchial needle aspiration in isolated intrathoracic lymphadenopathy in non-neoplastic patients: a common dilemma in clinical practice

Objective:

To determine the diagnostic yield of endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) in non-neoplastic patients with isolated intrathoracic lymphadenopathy (IL).

Methods:

This was a retrospective study of patients with isolated IL referred for EBUS-TBNA. We calculated the sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) of EBUS-TBNA in the diagnosis of granulomatous, reactive, and neoplastic lymphadenopathy. In cases of nonspecific granulomas, reactive lymphadenopathy, or inconclusive results, a definitive diagnosis was established by other diagnostic procedures or during a follow-up period of at least 18 months.

Results:

Among the 58 patients included in the study, EBUS-TBNA established a diagnosis of granulomatous disease in 22 (38%), reactive lymphadenopathy in 15 (26%), cancer in 8 (14%), and other diseases in 3 (5%). Results were inconclusive in 10 (17%), the diagnosis being established by other bronchoscopic procedures in 2 (20%) and by surgical procedures in 8 (80%). A final diagnosis of reactive lymphadenopathy was established in 12. Of those, 11 (92%) had their diagnosis confirmed during follow-up and 1 (8%) had their diagnosis confirmed by mediastinoscopy. In another 3, a final diagnosis of sarcoidosis or neoplasm was established. For the diagnosis of granulomatous disease, neoplasms, and reactive lymphadenopathy, EBUS-TBNA was found to have a sensitivity of 73%, 68%, and 92%, respectively; a specificity of 100%, 100%, and 93%, respectively; an accuracy of 86%, 93%, and 93%, respectively; a PPV of 100%, 100%, and 80%, respectively; and an NPV of 78%, 92%, and 98%, respectively.

Conclusions:

In non-neoplastic patients, granulomatous disease and reactive lymphadenopathy appear to be common causes of isolated IL. EBUS-TBNA shows promising results as a first-line minimally invasive diagnostic procedure. The results obtained by EBUS-TBNA can be optimized by examining clinical and radiological findings during follow-up or by comparison with the results obtained with other bronchoscopic methods.

Endobronchial ultrasound-guided transbronchial needle aspiration in sarcoidosis: Beyond the diagnostic yield

Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is the commonly used technique for pathological confirmation of clinically suspected sarcoidosis, mostly owing to its consistently high success rate in the detection of granulomas. However, other possible advantages, which are less appreciated and often poorly studied, may also contribute to the wider use of EBUS-TBNA in the future. These advantages include refinement of differential diagnoses through the study of lymph node characteristics during B-mode examination; reduction of complications associated with bronchoscopy, as well as improved triage of the specimen for ancillary studies with the use of rapid on-site evaluation; optimization of the quality of the sample through the selection of a target area for biopsy with minimal vascularity and absence of calcifications by using the colour Doppler and the B-mode; and prediction of the presence of extensive lymph node fibrosis by using the strain elastography module. Yet, limitations and possible clinical drawbacks should also be acknowledged. Indeed, due to the lack of specificity of the pathology findings in EBUS-derived samples, the diagnosis of sarcoidosis is one of the exclusion and should remain essentially clinical. The external validity of EBUS-TBNA results in sarcoidosis is questionable, as they mainly derive from studies in populations with a high disease prevalence. Finally, the risk exists that the low morbidity and high diagnostic yield of EBUS-TBNA may lead to its overuse in patients with clinical/radiological findings specific enough to secure a clinical diagnosis of sarcoidosis.

Echogenic lymph nodes in the differential diagnosis of pediatric sarcoidosis

We present a delayed diagnosis of sarcoidosis in an 11-year-old girl by demonstrating ultrasonographic imaging findings of granulomatous cervical and abdominal lymph node involvement. Pulmonary interstitial fibrosis in addition to multi-compartmental enlarged echogenic lymph nodes could be considered sarcoidosis. Punctate echogenic foci in the cervical lymph nodes should be considered in the differential diagnosis of sarcoidosis.