Accurate evaluation of axillary sentinel lymph node metastasis using contrast-enhanced ultrasonography with Sonazoid in breast cancer: a preliminary clinical trial

Combining Contrast-Enhanced Ultrasound with Methylene Blue for Detection of Sentinel Lymph Nodes in Early Breast Cancer

Aims/Background Sentinel lymph nodes (SLNs) are an important prognostic factor for breast cancer patients, but traditional axillary lymph node dissection methods have many complications, while sentinel lymph node biopsy has been developed as a better method. This study aimed to evaluate the efficiency of combining contrast-enhanced ultrasound (CEUS) with methylene blue for identifying SLNs in early-stage breast cancer patients. Methods This retrospective study included clinical data from 163 female patients with lymph node-negative and T1-2 early breast cancer admitted to China-Japan Friendship Hospital between August 2022 and November 2023. All patients received a periareolar injection of SonoVue followed by ultrasonography to identify SLNs. The methylene blue was used to detect SLNs during the surgery, and the patients underwent sentinel lymph node biopsy. We compared the methylene blue method with combined CEUS and methylene blue to identify the number of SLNs per patient. Furthermore, these two methods were compared to determine the number of SLNs and the number of SLNs positive in 34 SLNs positive patients. Results This study included 163 patients with tumor (T)1-2 node (N)0-3 metastasis (M)0. The identification rate of SLNs was 100% for CEUS. We detected 376 SLNs using a combined CEUS and methylene blue method, with a median of 2 (1, 5). Furthermore, methylene blue identified 627 SLNs, with a median of 3 (1, 12). However, CEUS detected a significantly lower number of SLNs than those identified by methylene blue (p < 0.001). Additionally, metastasis frequency was substantially higher for the combined CEUS and methylene blue method (66.3%, 53/80) compared to methylene blue approach alone (39.5%, 58/147) (p < 0.001). Conclusion Combining CEUS with methylene blue is expected to improve the accuracy of axillary staging in breast cancer patients while reducing surgical trauma and postoperative complications.

Prediction of axillary lymph node metastasis using a magnetic resonance imaging radiomics model of invasive breast cancer primary tumor

BACKGROUND

This study investigated the clinical value of breast magnetic resonance imaging (MRI) radiomics for predicting axillary lymph node metastasis (ALNM) and to compare the discriminative abilities of different combinations of MRI sequences.

METHODS

This study included 141 patients diagnosed with invasive breast cancer from two centers (center 1: n = 101, center 2: n = 40). Patients from center 1 were randomly divided into training set and test set 1. Patients from center 2 were assigned to the test set 2. All participants underwent preoperative MRI, and four distinct MRI sequences were obtained. The volume of interest (VOI) of the breast tumor was delineated on the dynamic contrast-enhanced (DCE) postcontrast phase 2 sequence, and the VOIs of other sequences were adjusted when required. Subsequently, radiomics features were extracted from the VOIs using an open-source package. Both single- and multisequence radiomics models were constructed using the logistic regression method in the training set. The area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, and precision of the radiomics model for the test set 1 and test set 2 were calculated. Finally, the diagnostic performance of each model was compared with the diagnostic level of junior and senior radiologists.

RESULTS

The single-sequence ALNM classifier derived from DCE postcontrast phase 1 had the best performance for both test set 1 (AUC = 0.891) and test set 2 (AUC = 0.619). The best-performing multisequence ALNM classifiers for both test set 1 (AUC = 0.910) and test set 2 (AUC = 0.717) were generated from DCE postcontrast phase 1, T2-weighted imaging, and diffusion-weighted imaging single-sequence ALNM classifiers. Both had a higher diagnostic level than the junior and senior radiologists.

CONCLUSIONS

The combination of DCE postcontrast phase 1, T2-weighted imaging, and diffusion-weighted imaging radiomics features had the best performance in predicting ALNM from breast cancer. Our study presents a well-performing and noninvasive tool for ALNM prediction in patients with breast cancer.

Ceusia-Breast: computer-aided diagnosis with contrast enhanced ultrasound image analysis for breast lesions

BACKGROUND

In recent years, contrast-enhanced ultrasonography (CEUS) has been used for various applications in breast diagnosis. The superiority of CEUS over conventional B-mode imaging in the ultrasound diagnosis of the breast lesions in clinical practice has been widely confirmed. On the other hand, there have been many proposals for computer-aided diagnosis of breast lesions on B-mode ultrasound images, but few for CEUS. We propose a semi-automatic classification method based on machine learning in CEUS of breast lesions.

METHODS

The proposed method extracts spatial and temporal features from CEUS videos and breast tumors are classified as benign or malignant using linear support vector machines (SVM) with combination of selected optimal features. In the proposed method, tumor regions are extracted using the guidance information specified by the examiners, then morphological and texture features of tumor regions obtained from B-mode and CEUS images and TIC features obtained from CEUS video are extracted. Then, our method uses SVM classifiers to classify breast tumors as benign or malignant. During SVM training, many features are prepared, and useful features are selected. We name our proposed method "Ceucia-Breast" (Contrast Enhanced UltraSound Image Analysis for BREAST lesions).

RESULTS

The experimental results on 119 subjects show that the area under the receiver operating curve, accuracy, precision, and recall are 0.893, 0.816, 0.841 and 0.920, respectively. The classification performance is improved by our method over conventional methods using only B-mode images. In addition, we confirm that the selected features are consistent with the CEUS guidelines for breast tumor diagnosis. Furthermore, we conduct an experiment on the operator dependency of specifying guidance information and find that the intra-operator and inter-operator kappa coefficients are 1.0 and 0.798, respectively.

CONCLUSION

The experimental results show a significant improvement in classification performance compared to conventional classification methods using only B-mode images. We also confirm that the selected features are related to the findings that are considered important in clinical practice. Furthermore, we verify the intra- and inter-examiner correlation in the guidance input for region extraction and confirm that both correlations are in strong agreement.

Different Imaging Modalities for the Diagnosis of Axillary Lymph Node Metastases in Breast Cancer: A Systematic Review and Network Meta-Analysis of Diagnostic Test Accuracy

BACKGROUND

Accurate diagnosis of axillary lymph node metastasis (ALNM) of breast cancer patients is important to guide local and systemic treatment.

PURPOSE

To evaluate the diagnostic performance of different imaging modalities for ALNM in patients with breast cancer.

STUDY TYPE

Systematic review and network meta-analysis (NMA).

SUBJECTS

Sixty-one original articles with 8011 participants.

FIELD STRENGTH

1.5 T and 3.0 T.

ASSESSMENT

We used the QUADAS-2 and QUADAS-C tools to assess the risk of bias in eligible studies. The identified articles assessed ultrasonography (US), MRI, mammography, ultrasound elastography (UE), PET, CT, PET/CT, scintimammography, and PET/MRI.

STATISTICAL ANALYSIS

We used random-effects conventional meta-analyses and Bayesian network meta-analyses for data analyses. We used sensitivity and specificity, relative sensitivity and specificity, superiority index, and summary receiver operating characteristic curve (SROC) analysis to compare the diagnostic value of different imaging modalities.

RESULTS

Sixty-one studies evaluated nine imaging modalities. At patient level, sensitivities of the nine imaging modalities ranged from 0.27 to 0.84 and specificities ranged from 0.84 to 0.95. Patient-based NMA showed that UE had the highest superiority index (5.95) with the highest relative sensitivity of 1.13 (95% confidence interval [CI]: 0.93-1.29) among all imaging methods when compared to US. At lymph node level, MRI had the highest superiority index (6.91) with highest relative sensitivity of 1.13 (95% CI: 1.01-1.23) and highest relative specificity of 1.11 (95% CI: 0.95-1.23) among all imaging methods when compared to US. SROCs also showed that UE and MRI had the largest area under the curve (AUC) at patient level and lymph node level of 0.92 and 0.94, respectively.

DATA CONCLUSION

UE and MRI may be superior to other imaging modalities in the diagnosis of ALNM in breast cancer patients at the patient level and the lymph node level, respectively. Further studies are needed to provide high-quality evidence to validate our findings.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 2.

Techniques for sentinel node biopsy in breast cancer

INTRODUCTION

Sentinel node biopsy (SNB) is the standard of care in women with breast cancer (BC) and clinically non suspicious axillary lymph nodes (LNs), due to its high negative predictive value (NPV) in the assessment of nodal status. SNB has significantly reduced complications related to the axillary lymph node dissection, such as lymphedema and upper limb dysfunction.

EVIDENCE ACQUISITION

The gold standard technique for SNB is the blue dye (BD) and technetium labelled nanocolloid (Tc-99m) double technique. However, nuclear medicine is not available in all Institutions and several new tracers and devices have been proposed, such as indocyanine green (ICG) and superparamagnetic iron oxides (SPIO). All these techniques show an accuracy and detection rate not inferior to that of the standard technique, with different specific pros and cons. The choice of how to perform a SNB primarily depends on the surgeon's confidence with the procedure, the availability of nuclear medicine and the economic resources of the Institutions. In this setting, new tracers, hybrid tracers and imaging techniques are being evaluated in order to improve the detection rate of sentinel lymph nodes (SNs) and minimize the number of unnecessary axillary surgeries through an accurate preoperative assessment of nodal status and to guide new minimally invasive diagnostic procedures of SNs. In particular, the contrast-enhanced ultrasound (CEUS) is an active field of research but cannot be recommended for clinical use at this time.

EVIDENCE SYNTHESIS

The ICG fluorescence technique was superior in terms of DR, as well as having the lowest FNR. The DR descending order was SPIO, Tc, dual modality (Tc/BD), CEUS and BD.

CONCLUSIONS

This paper is a narrative review of the most common SNB techniques in BC with a focus on recent innovations.

The combination of contrast-enhanced ultrasonography with blue dye for sentinel lymph node detection in clinically negative node breast cancer

PURPOSE

The aim of this prospective study was to evaluate the value of the combination of contrast-enhanced ultrasonography (CEUS) and blue dye (BD) for SLN detection in patients with clinically negative node breast cancer.

METHODS

Patients with clinically negative node breast cancer were randomized into two cohorts for SLN biopsy (SLNB): the combination method cohort using CEUS and BD together, and the single BD method cohort. Standard axillary lymph node dissection was performed if any of the SLNs confirmed positive by pathology. The identification rate, the number of SLNs removed and recurrence-free survival (RFS) rates were evaluated between two cohorts. In addition, we assessed the sensitivity, specificity, accuracy, false-negative rate of CEUS for diagnosis of SLNs based on patterns of CEUS enhancement.

RESULTS

144 consecutive patients with clinically negative node breast cancer were randomized into two cohorts. Each cohort consisted of 72 cases. In the combination method cohort, contrast-enhanced lymphatic vessels were clearly visualized and SLNs were accurately localized in 72 cases. The identification rate and the mean number of SLNs detected by the combination method were 100% (72/72) and 3.26 (1-9), respectively. In contrast, in the single BD method cohort, SLNs in 69 cases were successfully identified. The identification rate and the mean number of SLNs using BD alone were 95.8% (69/72) and 2.21 (1-4), respectively. According to patterns of CEUS enhancement, the sensitivity, specificity, accuracy, and the FNR of CEUS for SLN diagnosis were 69.2%, 96.6%, 91.7%, and 30.8%, respectively. After a median follow-up of 50 months for the combination method cohort and 51 months for the blue dye alone cohort, five patients in the combination method cohort and nine in the blue dye alone cohort had recurrence. RFS rates showed no significant difference (P = 0.26) between two cohorts.

CONCLUSION

The combination of CEUS and BD is more effective than BD alone for SLNB in clinically negative node patients with an identification rate as high as 100%. Use of BD and CEUS in combination may provide the possibility of a non-radioactive alternative method for SLNB in centers without access to radioisotope.

Comparative study of two contrast agents for intraoperative identification of sentinel lymph nodes in patients with early breast cancer

Background

The use of contrast-enhanced ultrasound (CEUS) to locate sentinel lymph nodes (SLNs) in breast cancer has been studied more and more in recent years. This prospective study aimed to compare periareolar injection of two different contrast agents, SonoVue^® (SNV) and Sonazoid^® (SNZ), followed by CEUS to identify SLNs in breast cancer patients with clinically negative nodes.

Methods

A total of 205 patients with T1-2N0M0 breast cancer were divided into the SNV group and SNZ group. All were administered a periareolar injection of SNV or SNZ and underwent US to identify contrast-enhanced SLNs. Each contrast-enhanced SLN underwent a biopsy with blue dye and examined again by CEUS in vitro.

Results

In all cases, contrast-enhanced lymphatic vessels were clearly visualized using US soon after the periareolar injection of SNZ, and the SLNs were easily identified. The SLN identification rates were 75.27% (210/279) for SNV and 93.58% (102/109) for SNZ. Although the accuracy of detecting SLN metastasis was slightly different between the two groups, there was no statistically significant difference between those groups (P=0.615). Moreover, it was possible to identify SLNs in vitro in the SNZ group, and these could be compared with the lymph nodes (LNs) located using SNZ during the preoperative stage and with blue dye during the procedure. This helped in determining the resection requirements.

Conclusions

When comparing the subdermal use of SNV and SNZ, no significant differences in the number of detected SLNs and the diagnosis of metastatic LNs were observed. Because SLNs can be detected for a longer time in living tissues with SNZ, this contrast agent may provide more intraoperative information for complete resection of all preoperative localization of SLN.

Preoperative evaluation and influencing factors of sentinel lymph node detection for early breast cancer with contrast-enhanced ultrasonography: What matters

Sentinel lymph node (SLN) is important in the early diagnosis of breast cancer. We aimed to evaluate the role of contrast-enhanced ultrasonography (CEUS) in the preoperative evaluation for SLN and potentially influencing factors, to provide evidence to the management of breast cancer.Patients with breast cancer who treated in our hospital from May 2018 to May 2020 were selected. All patients underwent CEUS examination to find SLN and judged whether the lymph node had cancer metastasis. We evaluated the sensitivity, specificity, and accuracy of CEUS in predicting SLN, and its differences in pathological diagnosis results and related influencing factors were also analyzed.A total of 108 patients with breast cancer were included. And a total of 248 SLNs were detected. The sensitivity of CEUS to the preoperative evaluation of SLN was 84.67%, the specificity was 81.14%, the positive predictive value was 76.08%, and the negative predictive value was 89.27%, the positive likelihood ratio was 4.06, and the negative likelihood ratio was 0.14. The area under the curve of the preoperative evaluation of SLN in CEUS examination was 0.813 (95% confidence interval: 0.765-0.911), and there was significant difference in the size of SLNs between SLN-negative and SLN-positive groups (P = .043).Preoperative CEUS has good predictive value for the SLN detection in patients with breast cancer, and it is worthy of clinical application.

Predictive risk factors for sentinel lymph node metastasis using preoperative contrast-enhanced ultrasound in early-stage breast cancer patients

Background

Sentinel lymph node biopsy (SLNB) is the standard procedure for axillary staging in clinically node-negative (cN0) breast cancer patients. The positive rate of SLNs in cN0 stage patients ranges from 20.5% to 25.5%, so identifying appropriate candidates for SLNB is quite challenging. The aims of this study were to assess whether contrast-enhanced ultrasound (CEUS) could be utilized to noninvasively predict SLN metastasis, and to explore the predictive value of the involved factors.

Methods

Between May 2016 and May 2018, 217 consenting breast cancer patients undergoing SLNB were enrolled. Before the surgery, CEUS was utilized to identify the SLNs, and predict whether metastasis had occurred according to their enhancement pattern. Blue dye was also used to identify the SLNs during SLNB. The rates of identification and accuracy of both methods were recorded. The predictive outcomes of SLNs identified by CEUS were recorded and compared with the pathological diagnosis.

Results

Of the 217 cases, SLNs in 212 cases were successfully identified, comprising 208 cases identified by CEUS and 206 cases by blue dye, with no significant difference between the two methods (P=0.6470). A total of 78 cases were predicted SLN-positive preoperatively by CEUS, comprising 61 cases of SLN metastasis confirmed by pathology and 17 cases of no SLN metastasis, and 130 cases were predicted SLN-negative by CEUS, comprising 6 cases of SLN metastasis and 124 cases of no SLN metastasis. The sensitivity of CEUS preoperative prediction was 91.0%, the specificity was 87.9%, the positive and negative predictive values were 78.2% and 95.4%, respectively, and the accuracy was 88.9%. The maximum diameter size of positive SLNs predicted by CEUS was greater than that of negative SLNs (mean value 1.67±0.06 vs. 1.40±0.05 cm, P=0.0007). Similarly, the primary tumor size predicted SLN-positive by CEUS was greater than that in patients with negative SLNs (mean value 2.64±0.12 vs. 1.79±0.09 cm, P<0.0001).

Conclusions

CEUS accurately identified SLNs and can be used to noninvasively predict SLN metastasis in early-stage breast cancer patients. However, the primary tumor size and the SLN size should not be overlooked by clinicians when judging the status of SLNs. This novel method may be a recommended strategy for identifying appropriate SLNB candidates.

Percutaneous Sonazoid-enhanced ultrasonography combined with in vitro verification for detection and characterization of sentinel lymph nodes in early breast cancer

Objectives

To assess the efficacy of percutaneous Sonazoid-enhanced ultrasound and in vitro verification for identification sentinel lymph nodes (SLNs) and diagnosis of metastatic SLNs in patients with early breast cancer (BC).

Methods

Sixty-eight patients with early BC were enrolled finally. After the induction of general anesthesia, 0.4 ml of Sonazoid (SNZ), a new second-generation tissue-specific ultrasound contrast agent (UCA), mixed with 0.6 ml of methylene blue, was injected intradermally. The lymphatic vessels and connected SLNs were immediately observed and marked. After being resected, these SLNs were soaked in saline water and examined still in the mode of contrast-enhanced ultrasound (CEUS) in vitro. This procedure could ensure that all the enhanced nodes had been removed as much as possible. The numbers of SLNs detected by UCA and blue dye were recorded. The enhancement patterns of SLNs were compared with the final pathological results.

Results

SLNs detection rate by SNZ-CEUS was 100%, which was higher than that by blue dye (95.59%). CEUS identified a median of 1.5 nodes, while blue dye identified a median of 1.9 nodes per case (p = 0.0012). When homogeneous high perfusion and complete annular high perfusion were regarded as negative nodes, the sensitivity and negative predictive value were 92.31% and 96.79% respectively, while the specificity was 84.21%.

Conclusions

Percutaneous SNZ-enhanced ultrasonography combined with in vitro verification is a feasible and reliable method for SLNs identification intraoperatively. Enhancement patterns can be helpful in determining the status of SLNs.

Key Points

• CEUS with percutaneous injection of Sonazoid can successfully identify SLNs with the rate of 100% in early breast cancer patients, higher than 95.59% of blue dye.

• Sonazoid, with high affinity with reticuloendothelial cells, increases the imaging time of SLNs and facilitates biopsy intraoperatively better than Sonovue as a lymphatic tracer.

• Homogenous high and complete annular high perfusions have a sensitivity of 92.31% and a negative predictive value of 96.79% in the prediction of uninvolved SLNs.

Clinical Utility of Contrast-enhanced Ultrasound for the Diagnosis of Lymphadenopathy

This meta-analysis aimed to evaluate the diagnostic accuracy of contrast-enhanced ultrasonography (CEUS) in identifying lymphazdenopathy. PubMed, Web of Science, Embase and the Cochrane Library were searched for relevant articles through September 2020. A total of 16 articles, which included 1787 participants, were analyzed. The summary sensitivity, specificity, positive likelihood ratio (LR), negative LR and diagnostic odds ratio of CEUS for diagnosing lymphadenopathy were 0.88 (0.86-0.90), 0.90 (0.88-0.92), 6.04 (3.67-9.95), 0.15 (0.10-0.21) and 47.38 (23.45-95.66), respectively. The summary receiver operating characteristic (SROC) area under the curve (AUC) was 0.9405. After omitting outliers identified in a bivariate box plot and forest plot, heterogeneity was decreased, and the pooled sensitivity and specificity were 0.87 (0.84-0.90) and 0.87 (0.84-0.90), respectively. Furthermore, the SROC AUC was 0.9327. In conclusion, CEUS has the potential to be a valuable tool for characterizing lymphadenopathy and could provide clinical decision support.

Accuracy of CEUS-guided sentinel lymph node biopsy in early-stage breast cancer: a study review and meta-analysis

Objective

To investigate whether preoperative localization of sentinel lymph node (SLN) by contrast-enhanced ultrasound (CEUS) can further improve the accuracy of sentinel lymph node biopsy (SLNB).

Method

Collect published literatures or conference reports by searching electronic databases. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) evaluation method is used to evaluate the quality of the screened literatures. The pooled risk ratio of cancer metastasis of SLN identified by CEUS (CE-SLN) compared with SLN not identified by CEUS (nonCE-SLN) is calculated, and the pooled diagnostic accuracy of CE-SLN for pathological status of all SLNs is also evaluated.

Result

Through search and screening, a total of 16 studies were included, of which five and seven studies, respectively, entered the meta-analysis of metastatic risk ratio and diagnostic accuracy. The localization rate of preoperative CEUS for sentinel lymph nodes was 70 to 100%. The meta-analysis shows that the risk of metastasis of SLN identified by CEUS is significantly higher than that not identified by CEUS, 26.0% vs 4.6%, and risk ratio (RR) is 6.08 (95% CI 4.17–8.85). In early-stage breast cancer, the pathological status of CE-SLN is a good representative of all SLNs, with a pooled sensitivity of 98% (95% CI 0.94–1.00), pooled specificity of 100% (95% CI 0.99–1.00), diagnostic odds ratio (DOR) of 2153.18 (95% CI 476.53–9729.06), and area under the subject receiver operating characteristic (SROC) curve of 0.9968.

Conclusion

In early-stage breast cancer, preoperative localization of SLN by CEUS is expected to further improve the accuracy of sentinel lymph node biopsy (SLNB).

Real-Time Visualization of Lymphatic Flow to Sentinel Lymph Nodes by Contrast-Enhanced Ultrasonography with Sonazoid in Patients with Breast Cancer

Contrast-enhanced ultrasonography with Sonazoid (SNZ) enables real-time visualization, resulting in more precise identification of lymphatic flow to sentinel lymph nodes (SLNs). This study aimed to classify lymphatic drainage patterns to SLNs. Patients (n = 75) with T1-2 N0 M0 breast cancer received a periareolar injection of SNZ to identify SNZ-enhanced SLNs (SNZ-SLNs), followed by SLN biopsy with blue dye. The lymphatic drainage patterns were classified into four types: type A, single lymphatic route/single SLN; type B, multiple lymphatic routes/single SLN; type C, single lymphatic route/multiple SLNs; and type D, multiple lymphatic routes/multiple SLNs. SLNs were successfully identified in all patients using both blue dye and SNZ. The drainage lymphatic pathways identified were as follows: type A in 53 cases (70.7%), type B in seven (9.3%), type C in eight cases (10.7%) and type D in seven (9.3%). SNZ-SLN biopsy is a technically simple method with a 100% identification rate, enabling the real-time visualization of lymphatic flow to SNZ-SLNs.

Sentinel Lymph Node Characterization with a Dual-Targeted Molecular Ultrasound Contrast Agent

PURPOSE

The purpose of this study was to assess the performance of molecular ultrasound with dual-targeted microbubbles to detect metastatic disease in the sentinel lymph nodes (SLNs) in swine model of naturally occurring melanoma. The SLN is the first lymph node in the lymphatic chain draining primary tumor, and early detection of metastatic SLN involvement is critical in the appropriate management of melanoma.

PROCEDURE

Nine Sinclair swine (weight 3-7 kg; Sinclair BioResources, Columbia, MO, USA) with naturally occurring melanoma were examined. Siemens S3000 scanner with a 9L4 probe was used for imaging (Siemens Healthineers, Mountain View, CA). Dual-targeted contrast agent was created using Targestar SA microbubbles (Targeson, San Diego, CA, USA) labeled with α_νβ₃-integrin and P-selectin antibodies. Targestar SA microbubbles labeled with IgG-labeled were used as control. First, peritumoral injection of Sonazoid contrast agent (GE Healthcare, Oslo, Norway) was performed to detect SLNs. After that, dual-targeted and IGG control Targestar SA microbubbles were injected intravenously with a 30-min interval between injections. Labeled Targestar SA microbubbles were allowed to circulate for 4 min to enable binding. After that, two sets of image clips were acquired several seconds before and after a high-power destruction sequence. The mean intensity difference pre- to post-bubble destruction within the region of interest placed over SLN was calculated as a relative measure of targeted microbubble contrast agent retention. This process was repeated for non-SLNs as controls. All lymph nodes evaluated on imaging were surgically removed and histologically examined for presence of metastatic involvement.

RESULTS

A total of 43 lymph nodes (25 SLNs and 18 non-SLNs) were included in the analysis with 18 SLNs demonstrating metastatic involvement greater than 5 % on histology. All non-SLNs were benign. The mean intensity (± SD) of the dual-targeted microbubbles for metastatic SLNs was significantly higher than that of benign LNs (18.05 ± 19.11 vs. 3.30 ± 6.65 AU; p = 0.0008), while IgG-labeled control microbubbles demonstrated no difference in retained contrast intensity between metastatic and benign lymph nodes (0.39 ± 1.14 vs. 0.03 ± 0.24 AU; p = 0.14).

CONCLUSIONS

The results indicate that dual-targeted microbubbles labeled with P-selectin and α_νβ₃-integrin antibodies may aid in detecting metastatic involvement in SLNs of melanoma.

Detection of sentinel lymph node using contrast-enhanced agent, Sonazoid™, and evaluation of its metastasis with superb microvascular imaging in oral and oropharyngeal cancers: a preliminary clinical study

BACKGROUND

In sentinel lymph node (SLN) biopsy for head and neck cancers, the radioisotope method has been the gold standard. However, this method has several problems, such as unavoidable radiation exposure and requirements of expensive equipment.

AIMS/OBJECTIVES

To overcome these problems, we evaluated the contrast-enhanced ultrasonography (CEUS)-guided SLN-detection method, and predicted the SLN metastatic status using novel ultrasound technology, superb microvascular imaging (SMI).

METHODS

Ten patients (6 with oral and 4 with oropharyngeal cancers) without neck lymph node metastasis were enrolled in this study. Ultrasound contrast agent, Sonazoid^™, was infiltrated into the mucosa at the primary site to observe the lymphatic ducts and SLNs in the neck field. The detected SLNs were examined for blood flow using SMI to categorize the SLNs metastases-positive or negative.

RESULTS

SLNs were successfully detected in 8 out of 10 cases. In 7 out of the 8 cases, in whom SLNs were successfully detected, the metastatic status of SLNs was correctly diagnosed with SMI.

CONCLUSIONS AND SIGNIFICANCE

Although more clinical data are needed based on a larger cohort, establishing the CEUS-guided SLN-detection and criteria for the accurate diagnosis of SLN-metastases using SMI would be valuable as an alternative to radioisotope method, in oral and oropharyngeal cancers.

Multimodal photoacoustic imaging as a tool for sentinel lymph node identification and biopsy guidance

As a minimally invasive method, sentinel lymph node biopsy (SLNB) in conjunction with guidance methods is the standard method to determine cancer metastasis in breast. The desired guidance methods for SLNB should be capable of precise SLN localization for accurate diagnosis of micro-metastases at an early stage of cancer progression and thus facilitate reducing the number of SLN biopsies for minimal surgical complications. For this, high sensitivity to the administered dyes, high spatial and contrast resolutions, deep imaging depth, and real-time imaging capability are pivotal requirements. Currently, various methods have been used for SLNB guidance, each with their own advantages and disadvantages, but no methods meet the requirements. In this review, we discuss the conventional SLNB guidance methods in this perspective. In addition, we focus on the role of the PA imaging modality on real-time SLN identification and biopsy guidance. In particular, PA-based hybrid imaging methods for precise SLN identification and efficient biopsy guidance are introduced, and their unique features, advantages, and disadvantages are discussed.

Preoperative prediction of sentinel lymph node metastasis in breast cancer based on radiomics of T2-weighted fat-suppression and diffusion-weighted MRI

OBJECTIVES

To predict sentinel lymph node (SLN) metastasis in breast cancer patients using radiomics based on T₂-weighted fat suppression (T₂-FS) and diffusion-weighted MRI (DWI).

METHODS

We enrolled 146 patients with histologically proven breast cancer. All underwent pretreatment T₂-FS and DWI MRI scan. In all, 10,962 texture and four non-texture features were extracted for each patient. The 0.623 + bootstrap method and the area under the curve (AUC) were used to select the features. We constructed ten logistic regression models (orders of 1-10) based on different combination of image features using stepwise forward method.

RESULTS

For T₂-FS, model 10 with ten features yielded the highest AUC of 0.847 in the training set and 0.770 in the validation set. For DWI, model 8 with eight features reached the highest AUC of 0.847 in the training set and 0.787 in the validation set. For joint T₂-FS and DWI, model 10 with ten features yielded an AUC of 0.863 in the training set and 0.805 in the validation set.

CONCLUSIONS

Full utilisation of breast cancer-specific textural features extracted from anatomical and functional MRI images improves the performance of radiomics in predicting SLN metastasis, providing a non-invasive approach in clinical practice.

KEY POINTS

• SLN biopsy to access breast cancer metastasis has multiple complications. • Radiomics uses features extracted from medical images to characterise intratumour heterogeneity. • We combined T ₂ -FS and DWI textural features to predict SLN metastasis non-invasively.

Association between contrast-enhanced ultrasonography and histopathological findings of the metastatic lymph nodes of patients with head and neck cancer: A preliminary study

The present study aimed to investigate the usefulness of contrast-enhanced ultrasonography (CEUS) and a newly developed analysis software for the detection of microcapillary network distribution in lymph nodes of patients with head and neck cancer (HNC) by comparing the CEUS and histopathological findings. Patients that were diagnosed with HNC between February and September 2016 were enrolled. A total of five patients underwent resection of the primary tumor and neck dissection as their initial treatment. The cervical lymph nodes of these patients were analyzed by CEUS intraoperatively, and their surgical specimens were examined histopathologically. The patients were diagnosed using a combination of physical examination, computed tomography, magnetic resonance imaging and fluorodeoxyglucose-positron emission tomography. For CEUS examination, the microbubble contrast agent Sonazoid™ was injected into a peripheral vein. Video images of the metastatic lymph nodes were captured, and these were subjected to analysis by a newly developed image-analysis software. It was possible to perform intraoperative CEUS of metastatic lymph nodes and obtain accurate matched sections for histopathological examination. Hematoxylin and eosin and cluster of differentiation (CD)34 staining revealed that the software was able to accurately detect capillary vessels in metastatic lymph nodes. However, a number of perfusion deficits were observed in these lymph nodes. In conclusion, by using CEUS with the analysis software, the density and distribution of blood vessels in the metastatic lymph nodes of patients with HNC was revealed. Although the present study was limited and preliminary, it was concluded that this method may be useful to evaluate and to map the capillary vessels in the metastatic lymph nodes of patients with HNC.

Axillary Nodal Staging with Contrast-Enhanced Ultrasound

Purpose of Review

Axillary staging in the context of breast cancer is a contentious topic due to the varied practices across UK, Europe, and America. The ACOSOG Z0011 trial has questioned the role of axillary ultrasound in women with breast cancer. Published data has shown that women with ultrasound-positive lymph nodes have a worse prognosis than those with ultrasound-negative lymph nodes. Axillary ultrasound is limited as the sentinel lymph node (SLN) cannot be identified using B-mode ultrasound; however, with the advent of contrast-enhanced ultrasound (CEUS), this has now changed.

Recent Findings

The published literature has shown that the sentinel lymph node can be identified using CEUS. The rates are equivalent to blue dye alone but currently inferior to the dual technique of sentinel lymph node biopsy. There are several different contrast agents that can be used and the agents that remain in the sentinel lymph node for longer can identify areas of poor enhancement, allowing for targeted biopsy.

Summary

CEUS has the potential to revolutionize the way we manage the axilla in the future and may even replace surgical staging.

Identification of sentinel lymph nodes by contrast-enhanced ultrasonography with Sonazoid in patients with breast cancer: a feasibility study in three hospitals

The aim of this prospective study was to evaluate the feasibility of periareolar injection of the contrast agent Sonazoid (SNZ) followed by ultrasonography (US) for the identification of sentinel lymph node (SLN) in breast cancer patients with clinically negative node. Patients (n = 100) with T1-2N0M0 breast cancer received a periareolar injection of SNZ followed by US to identify contrast-enhanced SLN. Each contrast-enhanced SLN underwent fine needle aspiration cytology (FNAC) followed by SLN biopsy with a conventional method using blue dye and/or radiocolloid (B/R). In almost all cases, contrast-enhanced lymphatic vessels were clearly visualized by US soon after the periareolar injection of SNZ and the SLNs were easily identified with an identification rate of 98% (98/100) for SNZ and 100% (100/100) for B/R. The number of SLNs identified by SNZ (SNZ-SLN) (mean per patient, 1.52) was significantly lower than that identified by B/R (B/R-SLN) (2.19) (P < 0.0001). Twenty-five patients with positive SLNs had at least one positive SNZ-SLN. On a node-by-node basis, sensitivity, specificity, and accuracy of FNAC for SNZ-SLNs (n = 149) were 33.3%, 99.2%, and 85.9%, respectively. Identification of SLN by periareolar injection of SNZ is a technically simple method with an identification rate as high as 98%. SNZ-SLN thus seems to be a good target for FNAC, but sensitivity of FNAC for SNZ-SLNs needs to be improved.

Pre-Operative Evaluation of Axillary Lymph Node Status in Patients with Suspected Breast Cancer Using Shear Wave Elastography

The aim of this study was to evaluate shear wave elastography (SWE) for pre-operative evaluation of axillary lymph node (LN) status in patients with suspected breast cancer. A total of 130 axillary LNs in 130 patients who underwent SWE before fine-needle aspiration, core biopsy or surgery were analyzed. On gray-scale images, long and short axes, shape (elliptical or round), border (sharp or unsharp) and cortical thickening (concentric, eccentric or no fatty hilum) of LNs were assessed. On SWE, mean, maximum, minimum, standard deviation and the lesion-to-fat ratio (E_ratio) values of elasticity were collected. Gray-scale and SWE features were compared statistically between metastatic and benign LNs using the χ²-test and independent t-test. Diagnostic performance of each feature was evaluated using the area under the receiver operating characteristic curve (AUC). Logistic regression analysis was used to determine gray-scale or SWE features independently associated with metastatic LNs. Of the 130 LNs, 65 (50%) were metastatic and 65 (50%) were benign after surgery. Metastatic LNs were significantly larger (p = 0.018); had higher elasticity indexes at SWE (p < 0.0001); and had higher proportions of round shape (p = 0.033), unsharp border (p = 0.048) and eccentric cortical thickening or no fatty hilum (p = 0.005) compared with benign LNs. On multivariate analysis, E_ratio was independently associated with metastatic LNs (odds ratio = 3.312, p = 0.008). E_ratio had the highest AUC among gray-scale (0.582-0.719) and SWE (0.900-0.950) variables. SWE had good diagnostic performance in metastatic axillary LNs, and E_ratio was independently associated with metastatic LNs.

Role of contrast-enhanced endoscopic ultrasound in lymph nodes

Diagnosing unclear lymph node (LN) enlargements in the mediastinum and abdomen is the most important indication of endoscopic ultrasound (EUS)-fine needle aspiration (FNA) after the diagnosis and treatment of pancreatic diseases. Investigating LNs in these areas can happen in different clinical settings. Mostly, it is the first modality in general LN diseases without any peripheral LN enlargements. On the other hand, it can be the question of LN involvement in a known or suspected primary tumor. Due to EUS-FNA cytology, those questions can be answered highly, accurately. However, a primary discrimination of LNs might be helpful to increase the diagnostic value of the FNA cytology, especially in cases with multiple LN enlargements and hard to reach enlarged LNs for example by vessel interposition. Because of the unreliability of B-mode criteria, further diagnostic improvements such as elastography and contrast-enhanced EUS are investigated to increase the accuracy of the initial diagnosis.