Role of shear-wave and strain elastography to differentiate malignant vs benign subpleural lung lesions

Abstract

Elastosonography is a non-invasive diagnostic method to evaluate tissue stiffness. The aim of our study was to demonstrate the applicability and efficacy of elastosonography to differentiate benign vs malignant subpleural lung lesions compared to clinical, radiological and histological findings. We performed both strain and shear wave velocity (SWV) elastosonography on subpleural lung lesions. Moreover, we elaborated a composite score called ”elasto index”. Fourteen patients, 10 males and 4 females were recruited. On strain elastography, 9 lesions showed a hard pattern (type 3), 3 lesions showed an intermediate pattern (type 2), and 2 lesions a soft pattern (type 1). All lesions showed a mean SWV value of 4.46 ± 2.37 m/second. The mean SWV for malignant lesions (n = 6) was 5.92 ± 2.8 m/second. The mean SWV for benign lesions (n = 8) was 3.36 ± 1.20 m/second. SWV shows an area under the curve (AUC) of 0.792, and the Youden index shows a value of 3.6 m/second. The ROC curve elaborated for the diagnosis of malignancy by strain elastography showed an AUC of 0.688. ROC curve for the diagnosis of malignancy by elasto index demonstrated an AUC of 0.802. SWV values obtained by ARFI elastosonographic method are higher in malignant lung lesions (mean SWV: 5.92 m/second) than in benign ones (mean SWV: 3.36); a composite score (elasto index) is characterized by better statistical significance for the differentiation of the lesions.

Infectious Pneumonia and Lung Ultrasound: A Review

“…Recent studies evaluated the role of elastosonography in differentiating benign vs. malignant consolidation. Our group reported a preliminary report on patients with subpleural consolidations that performed elastosonography evaluation; malignant lesions were characterized by higher values of tissue stiffness than benign ones [ 59 ].…”

The Diagnostic Role of Lung Ultrasound and Contrast-Enhanced Ultrasound in Pulmonary Embolism

“…9,12 When there is a critical reduction of alveolar air, the portion of pathological lung parenchyma acquires such a density as to be seen on ultrasound as a solid parenchyma, defined as the consolidation or hepatization process. 9,[13][14][15] The semiotics of LUS is mainly based on the study of alveolar-interstitial and pleural pathologies. 16 Hence, the reason why lung pathologies of vascular etiology cannot be evaluated by LUS, as they appear on ultrasound imaging as diffuse A-line pattern.…”

A diagnostic biomarker of acid glycoprotein 1 for distinguishing malignant from benign pulmonary lesions

“…At present, according to radiological technology, the most common instrumental diagnostic methods for differentiating malignant from benign lung lesions mainly include low-dose computed tomography (CT), positron emission tomography (PET), and magnetic resonance imaging, which help to improve the survival rate. 4 Bianconi et al 5 reported that deep learning was a viable approach for semiautomated segmentation of pulmonary nodules on CT scans and further found that the four form factors, ACO, AFL, KFL, and MPS, could be evaluated on lung nodules on CT scans and can improve the differential diagnosis between benign and malignant lesions. 6 Dual-energy spectral CT also has high accuracy in the differential diagnosis of benign and malignant pulmonary necrotic lesions.…”