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

Morishita, Momoko; Uchimura, Keigo; Furuse, Hideaki; Imabayashi, Tatsuya; Tsuchida, Takaaki

doi:10.3390/cancers14215355

Cited by 6 publications

(9 citation statements)

References 40 publications

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“…In predicting malignant lymph nodes, our 5 EBUS features nomogram consisted of long-axis, short-axis, echogenicity, fusion, and CHS. The optimal AUC value for this nomogram was 0.905 which was better than the Canada LN score (AUC = 0.72) and eight EBUS features (AUC = 0.857) [ 13 , 14 ] and also had a good predictive efficacy in predicting various cancer cell types. In predicting malignancy outcomes of EBUS-TBNA postoperative negative lymph nodes, our 3 EBUS features nomogram consisted of long-axis, echogenicity, and CHS.…”

Section: Discussionmentioning

confidence: 99%

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

Ling,

Xie,

Zhong

et al. 2024

International Journal of Clinical Practice

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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.

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Section: Discussionmentioning

confidence: 99%

“…A distinct margin, round shape, heterogeneous echogenicity, and coagulation necrosis sign were independent predictors of metastasis in multivariate analysis, each with an OR of 3.05, 3.1, 1.96, and 5.64. Morishita et al reported on multi-EBUS features [ 14 ]. A total of 597 lymph nodes were evaluated retrospectively from 302 patients.…”

Section: Discussionmentioning

confidence: 99%

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

Ling,

Xie,

Zhong

et al. 2024

International Journal of Clinical Practice

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“…Other studies that used blood flow grade instead of vascular distribution to predict metastasis found that it was not significant independent predictors of LNs metastasis. [ 21 , 32 ] This reason might be that blood flow grade was more affected by external factors, such as pulsation of great vessels and respiratory movement. [ 14 ] The elastography had the accuracy of 77.64%, which was a useful EBUS modality to detect the tissue stiffness.…”

Section: Discussionmentioning

confidence: 99%

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

Huang,

Wang,

Chen

et al. 2024

Endosc Ultrasound

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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.

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“…Consequently, most studies investigating the performance characteristics of B-mode endosonography findings in predicting malignant ILN involvement have not included calcifications in the analysis. [13][14][15][16][17][18][19][20][21][22] Moreover, previous studies examining the predictive value of ILN calcifications were conducted in countries with a high prevalence of tuberculosis, did not differentiate between macrocalcifications and microcalcifications, and reported a low prevalence of calcifications, limiting robust statistical analysis. [23][24][25][26] associated with a high prevalence of malignancy and actionable driver mutations in the setting of lung cancer.…”

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confidence: 99%

“…Intrathoracic lymph node (ILN) calcifications have traditionally been attributed to prior granulomatous inflammatory conditions (eg, sarcoidosis) or infectious diseases (eg, tuberculosis, histoplasmosis). Consequently, most studies investigating the performance characteristics of B-mode endosonography findings in predicting malignant ILN involvement have not included calcifications in the analysis 13–22 . Moreover, previous studies examining the predictive value of ILN calcifications were conducted in countries with a high prevalence of tuberculosis, did not differentiate between macrocalcifications and microcalcifications, and reported a low prevalence of calcifications, limiting robust statistical analysis 23–26 …”

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confidence: 99%

Intrathoracic Lymph Node Microcalcifications are Associated With a High Prevalence of Malignancy and Anaplastic Lymphoma Kinase Rearrangement

Leoncini,

Sotgiu,

Cancellieri

et al. 2024

Journal of Bronchology &Amp; Interventional Pulmonology

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Background: Microcalcifications are acknowledged as a malignancy risk factor in multiple cancers. However, the prevalence and association of intrathoracic lymph node (ILN) calcifications with malignancy remain unexplored. Methods: In this cross-sectional study, we enrolled patients with known/suspected malignancy and an indication for endosonography for diagnosis or ILN staging. We assessed the prevalence and pattern of calcified ILNs and the prevalence of malignancy in ILNs with and without calcifications. In addition, we evaluated the genomic profile and PD-L1 expression in lung cancer patients, stratifying them based on the presence or absence of ILN calcifications. Results: A total of 571 ILNs were sampled in 352 patients. Calcifications were detected in 85 (24.1%) patients and in 94 (16.5%) ILNs, with microcalcifications (78/94, 83%) being the predominant type. Compared with ILNs without calcifications (214/477, 44.9%), the prevalence of malignancy was higher in ILNs with microcalcifications (73/78, 93.6%; P<0.0001) but not in those with macrocalcifications (7/16, 43.7%; P=0.93). In patients with lung cancer, the high prevalence of metastatic involvement in ILNs displaying microcalcifications was independent of lymph node size (< or >1 cm) and the clinical stage (advanced disease; cN2/N3 disease; cN0/N1 disease). The anaplastic lymphoma kinase (ALK) rearrangement was significantly more prevalent in patients with than in those without calcified ILNs (17.4% vs. 1.7%, P<0.001), and all of them exhibited microcalcifications. Conclusion: ILN microcalcifications are common in patients undergoing endosonography for suspected malignancy, and they are associated with a high prevalence of metastatic involvement and ALK rearrangement.

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

Cited by 6 publications

References 40 publications

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

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

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

Intrathoracic Lymph Node Microcalcifications are Associated With a High Prevalence of Malignancy and Anaplastic Lymphoma Kinase Rearrangement

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