Predictive value of comb-push ultrasound shear elastography for the differentiation of reactive and metastatic axillary lymph nodes: A preliminary investigation

Noninvasive prediction of axillary lymph node breast cancer metastasis using morphometric analysis of nodal tumor microvessels in a contrast-free ultrasound approach

PURPOSE

Changes in microcirculation of axillary lymph nodes (ALNs) may indicate metastasis. Reliable noninvasive imaging technique to quantify such variations is lacking. We aim to develop and investigate a contrast-free ultrasound quantitative microvasculature imaging technique for detection of metastatic ALN in vivo.

EXPERIMENTAL DESIGN

The proposed ultrasound-based technique, high-definition microvasculature imaging (HDMI) provides superb images of tumor microvasculature at sub-millimeter size scales and enables quantitative analysis of microvessels structures. We evaluated the new HDMI technique on 68 breast cancer patients with ultrasound-identified suspicious ipsilateral axillary lymph nodes recommended for fine needle aspiration biopsy (FNAB). HDMI was conducted before the FNAB and vessel morphological features were extracted, analyzed, and the results were correlated with the histopathology.

RESULTS

Out of 15 evaluated quantitative HDMI biomarkers, 11 were significantly different in metastatic and reactive ALNs (10 with P << 0.01 and one with 0.01 < P < 0.05). We further showed that through analysis of these biomarkers, a predictive model trained on HDMI biomarkers combined with clinical information (i.e., age, node size, cortical thickness, and BI-RADS score) could identify metastatic lymph nodes with an area under the curve of 0.9 (95% CI [0.82,0.98]), sensitivity of 90%, and specificity of 88%.

CONCLUSIONS

The promising results of our morphometric analysis of HDMI on ALNs offer a new means of detecting lymph node metastasis when used as a complementary imaging tool to conventional ultrasound. The fact that it does not require injection of contrast agents simplifies its use in routine clinical practice.

Ultrasound elastography using a regularized modified error in constitutive equations (MECE) approach: a comprehensive phantom study

Many of the current techniques in transient elastography, such as shear wave elastography (SWE) assume a dominant planar shear wave propagating in an infinite medium. This underlying assumption, however, can be easily violated in real scenarios in vivo, leading to image artifacts and reconstruction errors. Other approaches that are not bound to planar shear wave assumption, such solutions based on the partial differential equation, can potentially overcome the shortcomings of the conventional SWE. The main objective of this paper is to demonstrate the advantages of the modified error in constitutive equations (MECE) formulation with total variation regularization (MECE + TV) over SWE in reconstructing the elastic moduli of different tissue-mimicking phantoms. Experiments were conducted on phantoms with inclusions of well-defined shapes to study the reconstruction of specific features relevant to practical applications. We compared the performances of MECE + TV and SWE in terms of quantitative metrics to estimate reconstruction accuracy, inclusion shape recovery, edge preservation and edge sharpness, inclusion size representation, and shear elasticity and contrast accuracies. The results indicate that the MECE + TV approach outperforms SWE based on several of these metrics. It is concluded that, with further development, the proposed method may offer elastography reconstructions that are superior to SWE in clinical applications.

Individualized-thresholding Shear Wave Elastography combined with clinical factors improves specificity in discriminating breast masses

PURPOSE

To investigate the diagnostic role of new metrics, defined as individualized-thresholding of Shear Wave Elastography (SWE) parameters, in association with clinical factors (such as age, mammographic density, lesion size and depth) and the BI-RADS features in differentiating benign from malignant breast lesions.

METHODS

Of 644 consecutive patients (median age, 55 years), prospectively referred for evaluation, 659 ultrasound detected breast lesions underwent SWE measurements. Multivariable logistic regression analysis was used to estimate the probability of malignancy. The area under the curve (AUC), optimal cutoff value, and the corresponding sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were determined.

RESULTS

265 of 659 (40.2%) masses were malignant. Using two E_mean cutoffs, 69.6 kPa for large superficial lesions (size >10 mm, depth ≤5 mm) and 39.2 kPa for the rest, the overall specificity, sensitivity, PPV and NPV were 92.6%, 86.8%, 88.8% and 91.3%, respectively. Combining multiple factors, including E_mean with two cutoffs, age and BI-RADS, the new ROC curve based on the malignancy probability calculation showed the highest AUC (0.954, 95% CI: 0.938-0.969). Using the optimal probability threshold of 0.514, the corresponding specificity, sensitivity, PPV and NPV were 92.9%, 89.1%, 89.4% and 92.7%, respectively.

CONCLUSIONS

The false-positive rate can be significantly reduced when applying two E_mean cutoffs based on lesion size and depth. Moreover, the combination of age, E_mean with two cutoffs and BI-RADS can further reduce the false negatives and false positives. Overall, this multifactorial analysis improves the specificity of ultrasound while maintaining a high sensitivity.