Open AccessIncorporation of shear wave elastography into a prediction model in the assessment of cervical lymph nodes
Author(s) -
WuChia Lo,
WanLun Hsu,
ChiTe Wang,
PoWen Cheng,
LiJen Liao
Publication year - 2019
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0221062
Subject(s) - medicine , cutoff , logistic regression , malignancy , elastography , receiver operating characteristic , cervical lymph nodes , ultrasound , radiology , statistics , mathematics , cancer , metastasis , physics , quantum mechanics
Rationale and objectives To assess the performance of shear wave elastography (SWE) and an extended model in predicting malignant cervical lymph nodes (LNs). Materials and methods 109 patients who underwent ultrasound (US) and SWE before needle biopsy were enrolled. The optimal cutoff value of elasticity indices (EIs) was determined by receiver operating characteristic (ROC) curves. The c-statistic, net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were used to compare extended model and traditional one. Results Malignant LNs had higher EIs than benign nodes (p < 0.001). The optimal cutoff point was 42 kilopascal, corresponding to 83.3% sensitivity, 64.7% specificity, and 68.8% overall accuracy. A multivariable logistic regression analysis confirmed that EI was an independent predictor for malignancy. The new extended prediction model had a positive NRI (0.96) and IDI (0.10) for predicting malignant neck LNs. Nevertheless, the c-statistic was not significantly different between the two models. Conclusion The parameter of SWE theoretically improve the model performance. However, its real clinical impact is minor, as the parameters of US-based model is already very robust. SWE can be considered as an adjunctive quantitative tool beyond conventional US examination.