Roel L J Verhoeven1,2,3, Chris L de Korte1,2, Erik H F M van der Heijden4. 1. Medical Ultrasound Imaging Center (MUSIC), Radboud University Medical Center, Nijmegen, The Netherlands. 2. Faculty of Science and Technology, Twente University, Enschede, The Netherlands. 3. Department of Pulmonology, Radboud University Medical Center, Nijmegen, The Netherlands. 4. Department of Pulmonology, Radboud University Medical Center, Nijmegen, The Netherlands, erik.vanderheijden@radboudumc.nl.
Abstract
BACKGROUND: In lung cancer staging, mediastinal lymph nodes are currently aspirated using endobronchial ultrasound transbronchial needle aspiration (EBUS-TBNA) based on size and FDG-PET avidity. EBUS strain elastography (SE) is a new technique that may help predict the presence of malignancy. However, a standardized assessment strategy for EBUS-SE measurement is lacking. OBJECTIVES: The aim of this study was to determine the optimal assessment strategy for investigating the predictive value of EBUS-SE in mediastinal lymph nodes. METHODS: Two qualitative visual analogue scale strain scores and two semiquantitative strain elastography measurements (a strain histogram and strain ratio) were acquired in 120 lymph nodes of 63 patients with (suspected) lung cancer. The dataset was randomized into an 80% training dataset to determine cut-off values. Performance was consecutively tested on the remaining 20% and the overall dataset. RESULTS: The semiquantitative mean histogram scoring strategy with a cut-off value of 78 (range 0-255) showed the best and most reproducible performance in prediction of malignancy with 93% overall sensitivity, 75% specificity, 69% positive predictive value, 95% negative predictive value, and 82% accuracy. Combining the EBUS-SE mean histogram scoring outcome with PET-CT information increased the post-test probability of disease in relevant clinical scenarios, having a positive test likelihood ratio of 4.16 (95% CI 2.98-8.13) and a negative test likelihood ratio of 0.14 (95% CI 0.04-2.81) in suspicious lymph nodes based on FDG-PET or CT imaging. CONCLUSIONS: EBUS-SE can potentially help predict lymph node malignancy in patients with lung cancer. The best semiquantitative assessment method is the mean strain histogram technique. The Author(s). Published by S. Karger AG, Basel.
BACKGROUND: In lung cancer staging, mediastinal lymph nodes are currently aspirated using endobronchial ultrasound transbronchial needle aspiration (EBUS-TBNA) based on size and FDG-PET avidity. EBUS strain elastography (SE) is a new technique that may help predict the presence of malignancy. However, a standardized assessment strategy for EBUS-SE measurement is lacking. OBJECTIVES: The aim of this study was to determine the optimal assessment strategy for investigating the predictive value of EBUS-SE in mediastinal lymph nodes. METHODS: Two qualitative visual analogue scale strain scores and two semiquantitative strain elastography measurements (a strain histogram and strain ratio) were acquired in 120 lymph nodes of 63 patients with (suspected) lung cancer. The dataset was randomized into an 80% training dataset to determine cut-off values. Performance was consecutively tested on the remaining 20% and the overall dataset. RESULTS: The semiquantitative mean histogram scoring strategy with a cut-off value of 78 (range 0-255) showed the best and most reproducible performance in prediction of malignancy with 93% overall sensitivity, 75% specificity, 69% positive predictive value, 95% negative predictive value, and 82% accuracy. Combining the EBUS-SE mean histogram scoring outcome with PET-CT information increased the post-test probability of disease in relevant clinical scenarios, having a positive test likelihood ratio of 4.16 (95% CI 2.98-8.13) and a negative test likelihood ratio of 0.14 (95% CI 0.04-2.81) in suspicious lymph nodes based on FDG-PET or CT imaging. CONCLUSIONS: EBUS-SE can potentially help predict lymph node malignancy in patients with lung cancer. The best semiquantitative assessment method is the mean strain histogram technique. The Author(s). Published by S. Karger AG, Basel.
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