0
Original Research: Lung Cancer |

Spectrum Analysis of Endobronchial Ultrasound Radiofrequency of Lymph Nodes in Patients With Lung Cancer

Takahiro Nakajima, MD, PhD, FCCP; Masato Shingyoji, MD, PhD; Takashi Anayama, MD, PhD; Hideki Kimura, MD, PhD; Kazuhiro Yasufuku, MD, PhD, FCCP; Ichiro Yoshino, MD, PhD
Author and Funding Information

FUNDING/SUPPORT: This research was supported by a JFE (The Japanese Foundation for Research and Promotion of Endoscopy) grant and JSPS KAKENHI (Grant-in-Aid for Scientific Research [C]; grant number 26462122, T. N.) for data analysis and preparation of the manuscript.

CORRESPONDENCE TO: Takahiro Nakajima, MD, PhD, FCCP, Department of General Thoracic Surgery, Chiba University Graduate School of Medicine, 1-8-1 Inohana, Chuo-ku, Chiba, 260-8670 Japan


Copyright 2016, American College of Chest Physicians. All Rights Reserved.


Chest. 2016;149(6):1393-1399. doi:10.1016/j.chest.2016.01.015
Text Size: A A A
Published online

Objective  The aim of this study was to analyze the spectral features of the radiofrequency of lymph nodes during endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) and to determine its diagnostic value for detecting metastatic nodes in patients with lung cancer.

Methods  Ultrasound spectrums of lymph nodes during EBUS-TBNA were retrospectively analyzed. A linear regression of frequency spectrum and the ultrasonic spectral parameters midband-fit, slope, and intercept were calculated. Mean values for these parameters within lymph nodes were computed. The cutoff values for each parameter for distinguishing metastatic vs benign lymph nodes were first determined within the training set; these cutoff values were then applied to the testing set for validation.

Results  Overall, 362 lymph nodes (112 metastatic, 250 benign) were analyzed as the training set, and 284 lymph nodes (74 metastatic, 210 benign) were evaluated as the testing set. In the training set, all of the parameters showed a significant difference between metastatic and benign lymph nodes (P < .001). The metastatic nodes tended to show low midband-fit, high slope, and low intercept. When midband-fit and intercept were combined, the diagnostic accuracy was maximized in the training set. In the testing set, the combination of intercept and slope produced the highest diagnostic accuracy, with the following outcomes: sensitivity, 79.7%; specificity, 84.3%; diagnostic accuracy, 83.1%; positive predictive value, 64.1%; and negative predictive value, 92.2%.

Conclusions  Metastatic lymph nodes possess unique ultrasonic spectrum features, and spectrum analysis can be used as a novel diagnostic tool for differentiating between benign and malignant nodes in patients with lung cancer.

Figures in this Article

Sign In to Access Full Content

MEMBER & INDIVIDUAL SUBSCRIBER

Want Access?

NEW TO CHEST?

Become a CHEST member and receive a FREE subscription as a benefit of membership.

Individuals can purchase this article on ScienceDirect.

Individuals can purchase a subscription to the journal.

Individuals can purchase a subscription to the journal or buy individual articles.

Learn more about membership or Purchase a Full Subscription.

INSTITUTIONAL ACCESS

Institutional access is now available through ScienceDirect and can be purchased at myelsevier.com.

Sign In to Access Full Content

MEMBER & INDIVIDUAL SUBSCRIBER

Want Access?

NEW TO CHEST?

Become a CHEST member and receive a FREE subscription as a benefit of membership.

Individuals can purchase this article on ScienceDirect.

Individuals can purchase a subscription to the journal.

Individuals can purchase a subscription to the journal or buy individual articles.

Learn more about membership or Purchase a Full Subscription.

INSTITUTIONAL ACCESS

Institutional access is now available through ScienceDirect and can be purchased at myelsevier.com.

Figures

Tables

References

NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Sign In to Access Full Content

MEMBER & INDIVIDUAL SUBSCRIBER

Want Access?

NEW TO CHEST?

Become a CHEST member and receive a FREE subscription as a benefit of membership.

Individuals can purchase this article on ScienceDirect.

Individuals can purchase a subscription to the journal.

Individuals can purchase a subscription to the journal or buy individual articles.

Learn more about membership or Purchase a Full Subscription.

INSTITUTIONAL ACCESS

Institutional access is now available through ScienceDirect and can be purchased at myelsevier.com.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Find Similar Articles
CHEST Journal Articles
PubMed Articles
  • CHEST Journal
    Print ISSN: 0012-3692
    Online ISSN: 1931-3543