Quantitative analysis of thyroid tumors vascularity: A comparison between 3-D contrast-enhanced ultrasound and 3-D Power Doppler on benign and malignant thyroid nodules

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.

Quantitative Biomarkers Derived from a Novel Contrast-Free Ultrasound High-Definition Microvessel Imaging for Distinguishing Thyroid Nodules

Low specificity in current ultrasound modalities for thyroid cancer detection necessitates the development of new imaging modalities for optimal characterization of thyroid nodules. Herein, the quantitative biomarkers of a new high-definition microvessel imaging (HDMI) were evaluated for discrimination of benign from malignant thyroid nodules. Without the help of contrast agents, this new ultrasound-based quantitative technique utilizes processing methods including clutter filtering, denoising, vessel enhancement filtering, morphological filtering, and vessel segmentation to resolve tumor microvessels at size scales of a few hundred microns and enables the extraction of vessel morphological features as new tumor biomarkers. We evaluated quantitative HDMI on 92 patients with 92 thyroid nodules identified in ultrasound. A total of 12 biomarkers derived from vessel morphological parameters were associated with pathology results. Using the Wilcoxon rank-sum test, six of the twelve biomarkers were significantly different in distribution between the malignant and benign nodules (all p < 0.01). A support vector machine (SVM)-based classification model was trained on these six biomarkers, and the receiver operating characteristic curve (ROC) showed an area under the curve (AUC) of 0.9005 (95% CI: [0.8279,0.9732]) with sensitivity, specificity, and accuracy of 0.7778, 0.9474, and 0.8929, respectively. When additional clinical data, namely TI-RADS, age, and nodule size were added to the features, model performance reached an AUC of 0.9044 (95% CI: [0.8331,0.9757]) with sensitivity, specificity, and accuracy of 0.8750, 0.8235, and 0.8400, respectively. Our findings suggest that tumor vessel morphological features may improve the characterization of thyroid nodules.

Ultrasound high-definition microvasculature imaging with novel quantitative biomarkers improves breast cancer detection accuracy

OBJECTIVES

To overcome the limitations of power Doppler in imaging angiogenesis, we sought to develop and investigate new quantitative biomarkers of a contrast-free ultrasound microvasculature imaging technique for differentiation of benign from malignant pathologies of breast lesion.

METHODS

In this prospective study, a new high-definition microvasculature imaging (HDMI) was tested on 521 patients with 527 ultrasound-identified suspicious breast masses indicated for biopsy. Four new morphological features of tumor microvessels, microvessel fractal dimension (mvFD), Murray's deviation (MD), bifurcation angle (BA), and spatial vascularity pattern (SVP) as well as initial biomarkers were extracted and analyzed, and the results correlated with pathology. Multivariable logistic regression analysis was used to study the performance of different prediction models, initial biomarkers, new biomarkers, and combined new and initial biomarkers in differentiating benign from malignant lesions.

RESULTS

The new HDMI biomarkers, mvFD, BA, MD, and SVP, were statistically significantly different in malignant and benign lesions, regardless of tumor size. Sensitivity and specificity of the new biomarkers in lesions > 20 mm were 95.6% and 100%, respectively. Combining the new and initial biomarkers together showed an AUC, sensitivity, and specificity of 97% (95% CI: 95-98%), 93.8%, and 89.2%, respectively, for all lesions regardless of mass size. The classification was further improved by adding the Breast Imaging Reporting and Data System (BI-RADS) score to the prediction model, showing an AUC, sensitivity, and specificity of 97% (95% CI: 95-98%), 93.8%, and 89.2%, respectively.

CONCLUSION

The addition of new quantitative HDMI biomarkers significantly improved the accuracy in breast lesion characterization when used as a complementary imaging tool to the conventional ultrasound.

KEY POINTS

• Novel quantitative biomarkers extracted from tumor microvessel images increase the sensitivity and specificity in discriminating malignant from benign breast masses. • New HDMI biomarkers Murray's deviation, bifurcation angles, microvessel fractal dimension, and spatial vascularity pattern outperformed the initial biomarkers. • The addition of BI-RADS scores based on US descriptors to the multivariable analysis using all biomarkers remarkably increased the sensitivity, specificity, and AUC in all size groups.

Hybrid high-definition microvessel imaging/shear wave elastography improves breast lesion characterization

BACKGROUND

Low specificity in current breast imaging modalities leads to increased unnecessary follow-ups and biopsies. The purpose of this study is to evaluate the efficacy of combining the quantitative parameters of high-definition microvasculature imaging (HDMI) and 2D shear wave elastography (SWE) with clinical factors (lesion depth and age) for improving breast lesion differentiation.

METHODS

In this prospective study, from June 2016 through April 2021, patients with breast lesions identified on diagnostic ultrasound and recommended for core needle biopsy were recruited. HDMI and SWE were conducted prior to biopsies. Two new HDMI parameters, Murray's deviation and bifurcation angle, and a new SWE parameter, mass characteristic frequency, were included for quantitative analysis. Lesion malignancy prediction models based on HDMI only, SWE only, the combination of HDMI and SWE, and the combination of HDMI, SWE and clinical factors were trained via elastic net logistic regression with 70% (360/514) randomly selected data and validated with the remaining 30% (154/514) data. Prediction performances in the validation test set were compared across models with respect to area under the ROC curve as well as sensitivity and specificity based on optimized threshold selection.

RESULTS

A total of 508 participants (mean age, 54 years ± 15), including 507 female participants and 1 male participant, with 514 suspicious breast lesions (range, 4-72 mm, median size, 13 mm) were included. Of the lesions, 204 were malignant. The SWE-HDMI prediction model, combining quantitative parameters from SWE and HDMI, with AUC of 0.973 (95% CI 0.95-0.99), was significantly higher than the result predicted with the SWE model or HDMI model alone. With an optimal cutoff of 0.25 for the malignancy probability, the sensitivity and specificity were 95.5% and 89.7%, respectively. The specificity was further improved with the addition of clinical factors. The corresponding model defined as the SWE-HDMI-C prediction model had an AUC of 0.981 (95% CI 0.96-1.00).

CONCLUSIONS

The SWE-HDMI-C detection model, a combination of SWE estimates, HDMI quantitative biomarkers and clinical factors, greatly improved the accuracy in breast lesion characterization.

Quantitative Biomarkers for Cancer Detection Using Contrast-Free Ultrasound High-Definition Microvessel Imaging: Fractal Dimension, Murray's Deviation, Bifurcation Angle & Spatial Vascularity Pattern

A growing body of evidence indicates that there is a strong correlation between microvascular morphological features and malignant tumors. Therefore, quantification of these features might allow more accurate differentiation of benign and malignant tumors. The main objective of this research project is to improve the quantification of microvascular networks depicted in contrast-free ultrasound microvessel images. To achieve this goal, a new series of quantitative microvessel morphological parameters are introduced for differentiation of breast masses using contrast-free ultrasound-based high-definition microvessel imaging (HDMI). Using HDMI, we quantified and analyzed four new parameters: 1) microvessel fractal dimension (mvFD), a marker of tumor microvascular complexity; 2) Murray's deviation (MD), the diameter mismatch, defined as the deviation from Murray's law; 3) bifurcation angle (BA), abnormally decreased angle; and 4) spatial vascular pattern (SVP), indicating tumor vascular distribution pattern, either intratumoral or peritumoral. The new biomarkers have been tested on 60 patients with breast masses. Validation of the feature's extraction algorithm was performed using a synthetic data set. All the proposed parameters had the power to discriminate the breast lesion malignancy (p < 0.05), displaying BA as the most sensitive test, with a sensitivity of 90.6%, and mvFD as the most specific test, with a specificity of 92%. The results of all four new biomarkers showed an AUC = 0.889, sensitivity of 80% and specificity of 91.4% In conclusion, the added value of the proposed quantitative morphological parameters, as new biomarkers of angiogenesis within breast masses, paves the way for more accurate breast cancer detection with higher specificity.

Usefulness of Color Doppler Ultrasonography in the Risk Stratification of Thyroid Nodules

INTRODUCTION

Thyroid ultrasound (US) is crucial for clinical decision in the management of thyroid nodules. In this cross-sectional study, we aimed to test if the evaluation of thyroid nodules' vascularization could improve the risk stratification ability of the American College of Radiology (ACR) TI-RADS classification system.

METHODS

A total of 873 thyroid nodules undergoing fine-needle aspiration were classified according to ACR TI-RADS US classification. Three types of vascularization were identified: type 0, no vascular signals; type 1, peripheral vascular signals; type 2, peripheral and intralesional vascular signals. Cytology specimens were evaluated conforming to the Italian Reporting System for Thyroid Cytology, and TIR3b, TIR4, and TIR5 were defined as high risk for malignancy. Odds ratios (ORs) with 95% confidence intervals (CI) and the areas under the receiver operating characteristic curves (ROC-AUC) for high-risk cytology categories were calculated.

RESULTS

The 3 vascular patterns were differently distributed within the cytology categories: 52.4% of TIR1c, 15.9% of TIR2, 5.9% of TIR3a, 6.7% of TIR3b, 12.5% of TIR4, and 28.9% of TIR5 nodules had no vascular signals (p < 0.001). Nodule vascularity alone was not associated with a higher risk of malignant cytology (OR [95% CI] 0.75 [0.43-1.32], p = 0.32), without differences between peripheral (OR [95% CI] 0.65 [0.35-1.20]) and intranodular (OR [95% CI] 0.88 [0.48-1.62]) vascularization (p = 0.22). The ROC-AUC (95% CI) for the diagnosis of malignant cytology was similar when considering TI-RADS classification alone (0.736 [0.684-0.786]) and when considering TI-RADS classification plus the presence/absence of vascular signals (0.736 [0.683-0.789], p value for differences between the ROC-AUCs: 0.91). Among TR1, TR2, and TR3 TI-RADS classes, no nodules without vascular signals showed a malignant cytology, allowing the identification of nodules with benign cytology with 100% specificity within these US classes.

CONCLUSIONS

Color Doppler study of thyroid nodules does not improve the risk stratification ability of the ACR TI-RADS US classification system.

Optical Coherence Tomography Angiography Monitors Cutaneous Wound Healing under Angiogenesis-Promoting Treatment in Diabetic and Non-Diabetic Mice

During wound healing, the rapid re-establishment of a functional microcirculation in the wounded tissue is of utmost importance. We applied optical coherence tomography (OCT) angiography to evaluate vascular remodeling in an excisional wound model in the pinnae of C57BL/6 and db/db mice receiving different proangiogenic topical treatments. Analysis of the high-resolution OCT angiograms, including the four quantitative parameters vessel density, vessel length, number of bifurcations, and vessel tortuosity, revealed changes of the microvasculature and allowed identification of the overlapping wound healing phases hemostasis, inflammation, proliferation, and remodeling. Angiograms acquired in the inflammatory phase in the first days showed a dilation of vessels and recruitment of pre-existing capillaries. In the proliferative phase, angiogenesis with the sprouting of new capillaries into the wound tissue led to an increase of the OCT angiography parameters vessel density, normalized vessel length, number of bifurcations, and vessel tortuosity by 28–47%, 39–52%, 33–48%, and 3–8% versus baseline, respectively. After the peak observed on study days four to seven, the parameters slowly decreased but remained still elevated 18 days after wounding, indicating a continuing remodeling phase. Our study suggests that OCT angiography has the potential to serve as a valuable preclinical research tool in studies investigating impaired vascular remodeling during wound healing and potential new treatment strategies.

"Double-Flash": An Innovative Method to Diagnose Papillary Thyroid Microcarcinomas

The aim of the study was to investigate the diagnostic ability of an innovative method called "Double-Flash" during contrast-enhanced ultrasound (CEUS) examination in papillary thyroid microcarcinomas. A total of 43 nodules measuring <10 mm and with definite pathology confirmed by surgery or fine-needle aspiration biopsy (FNAB) were included in this study. The bottom of "Flash" was pressed in the 40th and 60th seconds, respectively, defined as "Double-Flash." The curve of reperfusion was evaluated and the diagnostic value of "Double-Flash" was compared with that of CEUS. Pathologic results obtained by surgery or FNAB revealed there were 27 malignant and 16 benign nodules. The sensitivity, specificity and accuracy of CEUS were 70.0%, 53.8% and 65.1%. With "Double-Flash," the sensitivity, specificity and accuracy were 92.3%, 82.3% and 88.4%, respectively. The difference was statistically significant. Higher diagnostic ability is obtained with "Double-Flash." The parameter based on the new method could improve the diagnostic performance of quantitative diagnosis in CEUS. The change in the perfusion curve after "Flash" may be a strong indicator of malignancy.

Contrast-enhanced ultrasound for the differential diagnosis of thyroid nodules: An updated meta-analysis with comprehensive heterogeneity analysis

The diagnostic accuracy of contrast-enhanced ultrasound (CEUS) for distinguishing malignant thyroid nodules from benign thyroid nodules remains controversial. This meta-analysis was performed to evaluate the overall diagnostic value of CEUS for the characterization of thyroid nodules. Relevant studies were identified by searching PubMed, Embase and the Cochrane Library until August 1th 2019 to assess the overall diagnostic accuracy of CEUS. 37 eligible studies were included in the present meta-analysis. The pooled sensitivity, specificity, positive likelihood rate, negative likelihood rate and diagnostic odds ratio of CEUS were 0.87, 0.83, 5.38, 0.17 and 38.94, respectively, with the AUC of 0.9263. Subgroup analysis showed the heterogeneity was greatly reduced in small nodules group (≤ 1 cm) (I2 = 0.0%), while heterogeneity was still observed in the group of variable sizes group (I2 = 69.5%). However, meta-regression analysis revealed that only diagnostic criterion was the major source of heterogeneity (p = 0.0259). The risk of publication bias was negligible (p = 0.35). CEUS exhibited high accuracy for the identification of thyroid nodules and might provide additional perfusion information for the current US imaging reporting systems.

TI-RADS Diagnostic Performance: Which Algorithm is Superior and How Elastography and 4D Vascularity Improve the Malignancy Risk Assessment

Given the increased prevalence of thyroid nodules in the general population (~50%), the real challenge resides in correctly recognizing the suspicious ones. This study proposes to compare four important Thyroid Imaging and Reporting Data Systems (TI-RADS) and evaluate the contribution of elastography and 4D Color Doppler assessment of vascularity in estimating the risk of malignancy. In the study, 133 nodules with histopathological examination were included. Of these, 35 (26.31%) proved to be malignant. All nodules were classified using the four selected systems and our proposed improved score. The American College of Radiology (ACR) and EU TI-RADS had good sensitivity (94.28%, 97.14%) and NPV (93.33%, 95.83%), but fairly poor specificity (31.81%, 23.46%) and PPV (35.48%, 31.19%), with an accuracy of 42.8% and 45.8%, respectively. Horvath TI-RADS had better accuracy of 66.9% and somewhat improved specificity (62.24%), but poorer sensitivity (80%). Russ’ French TI-RADS includes elastography in the risk assessment strategy. This classification proved superior in all aspects (Se: 91.42%, Sp:82.65%, NPV:96.42%, PPV:65.30%, and Acc of 84.96%). The mean strain ratio (SR) value for malignant lesions was 5.56, while the mean SR value for benign ones was significantly lower, 2.54 (p < 0.05). It also correlated well with the response variable: histopathological result (p < 0.001). Although, adding 4D vascularity to the French score generated a similar calculated accuracy and from a statistical point of view, the parameter itself proved beneficial for predicting the malignancy risk (p < 0.001) and may add important knowledge in uncertain situations. Advanced ultrasound techniques definitely improved the risk estimation and should be used more extensively.

Use of 3-D Contrast-Enhanced Ultrasound to Evaluate Tumor Microvasculature After Nanoparticle-Mediated Modulation

A cost-effective method for serial in vivo imaging of tumor microvasculature has been developed. We evaluated acoustic angiography (AA) for visualizing and assessing non-small cell lung tumor (A549) microvasculature in mice before and after tumor vascular disruption by vascular-targeted gold nanoparticles and radiotherapy. Standard B-mode and microbubble-enhanced AA images were acquired at pre- and post-treatment time points. Using these modes, a new metric, 50% vessel penetration depth, was developed to characterize the 3-D spatial heterogeneity of microvascular networks. We observed an increase in tumor perfusion after radiation-induced vascular disruption, relative to control animals. This was also visualized in vessel morphology mode, which revealed a loss in vessel integrity. We found that tumors with poorly perfused vasculature at day 0 exhibited a reduced growth rate over time. This suggested a new method to reduce in-group treatment response variability using pre-treatment microvessel maps to objectively identify animals for study removal.

Effectiveness evaluation of computer-aided diagnosis system for the diagnosis of thyroid nodules on ultrasound: A systematic review and meta-analysis

BACKGROUND

More and more automated efficient ultrasound image analysis techniques, such as ultrasound-based computer-aided diagnosis system (CAD), were developed to obtain accurate, reproducible, and more objective diagnosis results for thyroid nodules. So far, whether the diagnostic performance of existing CAD systems can reach the diagnostic level of experienced radiologists is still controversial. The aim of the meta-analysis was to evaluate the accuracy of CAD for thyroid nodules' diagnosis by reviewing current literatures and summarizing the research status.

METHODS

A detailed literature search on PubMed, Embase, and Cochrane Libraries for articles published until December 2018 was carried out. The diagnostic performances of CAD systems vs radiologist were evaluated by meta-analysis. We determined the sensitivity and the specificity across studies, calculated positive and negative likelihood ratios and constructed summary receiver-operating characteristic (SROC) curves. Meta-analysis of studies was performed using a mixed-effect, hierarchical logistic regression model.

RESULTS

Five studies with 536 patients and 723 thyroid nodules were included in this meta-analysis. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio (DOR) for CAD system were 0.87 (95% confidence interval [CI], 0.73-0.94), 0.79 (95% CI 0.63-0.89), 4.1 (95% CI 2.5-6.9), 0.17 (95% CI 0.09-0.32), and 25 (95% CI 15-42), respectively. The SROC curve indicated that the area under the curve was 0.90 (95% CI 0.87-0.92). The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and DOR for experienced radiologists were 0.82 (95% CI 0.69-0.91), 0.83 (95% CI 0.76-0.89), 4.9 (95% CI 3.4-7.0), 0.22 (95% CI 0.12-0.38), and 23 (95% CI 11-46), respectively. The SROC curve indicated that the area under the curve was 0.96 (95% CI 0.94-0.97).

CONCLUSION

The sensitivity of the CAD system in the diagnosis of thyroid nodules was similar to that of experienced radiologists. However, the CAD system had lower specificity and DOR than experienced radiologists. The CAD system may play the potential role as a decision-making assistant alongside radiologists in the thyroid nodules' diagnosis. Future technical improvements would be helpful to increase the accuracy as well as diagnostic efficiency.

Ultrasonic Classification of Multicategory Thyroid Nodules Based on Logistic Regression

This study aims to screen out significant ultrasonic features to establish different predictive models of thyroid nodules based on logistic regression, with different indicators being included and nodular size being differentiated, and then compare them.Ultrasonic features of 1906 thyroid nodules in 1761 patients who had undergone sonography and fine-needle aspiration or surgery in our hospital were retrospectively analyzed. According to nodule size and whether vascular or elastographic indicators being included or not, nodules were divided into 12 groups. By univariate and multivariate analysis, the significant sonographic features to diagnose nodules of each group were screened and compared. The logistic regression models were built, and the cutoff values were calculated. The diagnostic performance of newly established models was validated, and the best model was compared with the American College of Radiology Thyroid Imaging Reporting and Data System.Significant features used to diagnose nodules in all models were hypoechoic, irregular margin, and microcalcification. Predominantly solid was an important indicator to differentiate benign and malignant macronodules. A taller-than-wide shape was a significant indicator of malignant micronodules. Strain elastographic character did show diagnostic value. The area under the curve of logistic regression models for malignant risk prediction were all higher than 0.7, and the best one was model 7, but the diagnostic performance was significantly reduced when models performed bivariate prediction.The most valuable indicators of malignant thyroid nodules are hypoechoic, irregular margin, and microcalcification. New models are suitable for nodules of different sizes and with or without vascular or elastographic features being described.