MRI and FDG-PET/CT based assessment of axillary lymph node metastasis in early breast cancer: a meta-analysis

Comparison of an Affibody-based Molecular Probe and 18F-FDG for Detecting HER2-Positive Breast Cancer at PET/CT

Background Human epidermal growth factor receptor 2 (HER2) affibody-based tracers could be an alternative to nonspecific radiotracers for noninvasive detection of HER2 expression in breast cancer lesions at PET/CT. Purpose To compare an affibody-based tracer, Al18F-NOTA-HER2-BCH, and fluorine 18 (18F) fluorodeoxyglucose (FDG) for detecting HER2-positive breast cancer lesions on PET/CT images. Materials and Methods In this prospective study conducted from June 2020 to July 2023, participants with HER2-positive breast cancer underwent both Al18F-NOTA-HER2-BCH and 18F-FDG PET/CT. HER2 positivity was confirmed with pathologic assessment (immunohistochemistry test results of 3+, or 2+ followed by fluorescence in situ hybridization, indicated HER2 amplification). Two independent readers visually assessed the uptake of tracers on images. Lesion uptake was quantified using the maximum standardized uptake value (SUVmax) and target to background ratio (TBR) and compared using a general linear mixed model. Results A total of 42 participants (mean age, 56.3 years ± 10.1 [SD]; 41 female) with HER2-positive breast cancer were included; 42 (100%) had tumors that were detected with Al18F-NOTA-HER2-BCH PET/CT and 40 (95.2%) had tumors detected with 18F-FDG PET/CT. Primary tumors in two of 21 participants, lymph node metastases in four of 21 participants, bone metastases in four of 15 participants, and liver metastases in three of nine participants were visualized only with Al18F-NOTA-HER2-BCH. Lung metastasis in one of nine participants was visualized only with 18F-FDG. Al18F-NOTA-HER2-BCH enabled depiction of more suspected HER2-positive primary tumors (26 vs 21) and lymph node (170 vs 130), bone (92 vs 66), and liver (55 vs 27) metastases than 18F-FDG. The SUVmax and TBR values of primary tumors and lymph node, bone, and liver metastases were all higher on Al18F-NOTA-HER2-BCH images than on 18F-FDG images (median SUVmax range, 10.4-13.5 vs 3.4-6.2; P value range, <.001 to .02; median TBR range, 2.7-17.6 vs 1.2-7.8; P value range, <.001 to .001). No evidence of differences in the SUVmax and TBR for chest wall or lung metastases was observed between Al18F-NOTA-HER2-BCH and 18F-FDG (P value range, .06 to .53). Conclusion PET/CT with the affibody-based tracer Al18F-NOTA-HER2-BCH enabled detection of more primary lesions and lymph node, bone, and liver metastases than PET/CT using 18F-FDG. ClinicalTrials.gov Identifier: NCT04547309 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Ulaner in this issue.

Internal mammary node abnormality in imaging studies and treatment outcomes in patients with breast cancer

The clinical significance of mild internal mammary node (IMN) enlargement (Mild-IMN) is uncertain. This study aimed to evaluate the relationship between treatment outcomes and IMN status in patients with breast cancer who underwent postmastectomy radiation therapy between January 2010 and December 2018. Overall, 250 patients were categorized based on IMN status: Clinically normal IMN (Normal-IMN; n=172), Mild-IMN (n=39) and clinically metastatic IMN (cMet-IMN; n=39). None of the patients in the Normal- or Mild-IMN groups received IMN irradiation. In the cMet-IMN group, 25 patients underwent IMN irradiation with an IMN boost (10 Gy in 5 fractions), while 14 patients did not. The median follow-up time was 80.0 months (range, 7.2-147.6 months). The 7-year overall survival (OS), disease-free survival (DFS) and IMN recurrence-free survival (IRF) rates were 80.2, 73.0 and 93.4%, respectively. Multivariate analyses indicated that only cMet-IMN had a significant impact on OS [hazard ratio (HR), 1.66; 95% CI, 1.01-3.68; P=0.05] and DFS (HR, 1.91; 95% CI, 1.08-3.39; P=0.03), while cMet-IMN did not have a significant impact on IRF (HR, 1.66; 95% CI, 0.41-6.78; P=0.48). Additionally, receiving an IMN boost had no influence on OS (HR, 1.11; 95% CI, 0.37-2.34; P=0.84), DFS (HR, 1.28; 95% CI, 0.51-3.22; P=0.60) or IRF (HR, 1.94; 95% CI, 0.22-17.47; P=0.55). In conclusion, the impact of Mild-IMN on clinical outcomes was small. Although irradiation for cMet-IMN is important, the impact of the cMet-IMN boost with 10 Gy in 5 fractions on clinical outcomes may also be limited.

Increased lesion detectability in patients with locally advanced breast cancer-A pilot study using dynamic whole-body [18F]FDG PET/CT

BACKGROUND

Accurate diagnosis of axillary lymph node (ALN) metastases is essential for prognosis and treatment planning in breast cancer. Evaluation of ALN is done by ultrasound, which is limited by inter-operator variability, and by sentinel lymph node biopsy and/or ALN dissection, none of which are without risks and/or long-term complications. It is known that conventional 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) positron emission tomography/computed tomography (PET/CT) has limited sensitivity for ALN metastases. However, a recently developed dynamic whole-body (D-WB) [18F]FDG PET/CT scanning protocol, allowing for imaging of tissue [18F]FDG metabolic rate (MRFDG), has been shown to have the potential to increase lesion detectability. The study purpose was to examine detectability of malignant lesions in D-WB [18F]FDG PET/CT compared to conventional [18F]FDG PET/CT.

RESULTS

This study prospectively included ten women with locally advanced breast cancer who were referred for an [18F]FDG PET/CT as part of their diagnostic work-up. They all underwent D-WB [18F]FDG PET/CT, consisting of a 6 min single bed dynamic scan over the chest region started at the time of tracer injection, a 64 min dynamic WB PET scan consisting of 16 continuous bed motion passes, and finally a contrast-enhanced CT scan, with generation of MRFDG parametric images. Lesion visibility was assessed by tumor-to-background and contrast-to-noise ratios using volumes of interest isocontouring tumors with a set limit of 50% of SUVmax and background volumes placed in the vicinity of tumors. Lesion visibility was best in the MRFDG images, with target-to-background values 2.28 (95% CI: 2.04-2.54) times higher than target-to-background values in SUV images, and contrast-to-noise values 1.23 (95% CI: 1.12-1.35) times higher than contrast-to-noise values in SUV images. Furthermore, five imaging experts visually assessed the images and three additional suspicious lesions were found in the MRFDG images compared to SUV images; one suspicious ALN, one suspicious parasternal lymph node, and one suspicious lesion located in the pelvic bone.

CONCLUSIONS

D-WB [18F]FDG PET/CT with MRFDG images show potential for improved lesion detectability compared to conventional SUV images in locally advanced breast cancer. Further validation in larger cohorts is needed.

CLINICAL TRIAL REGISTRATION

The trial is registered in clinicaltrials.gov, NCT05110443, https://www.

CLINICALTRIALS

gov/study/NCT05110443?term=NCT05110443&rank=1 .

Diagnostic performance of MRI for assessing axillary lymph node status after neoadjuvant chemotherapy in breast cancer: a systematic review and meta-analysis

OBJECTIVE

This systematic review examined the diagnostic performance of magnetic resonance imaging (MRI) for assessing axillary lymph node status (ALNS) after neoadjuvant chemotherapy (NAC) in breast cancer patients.

METHODS

We searched PubMed, Embase, Cochrane Library, and Web of Science to identify relevant studies and used the QUADAS-2 tool to assess methodological quality of eligible studies. We used STATA version 12.0 to perform data pooling, heterogeneity testing, subgroup analysis, and sensitivity analysis.

RESULTS

For the 21 enrolled studies, including 2875 patients, the pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were respectively 0.63 (95% CI: 0.53-0.72), 0.75 (95% CI: 0.68-0.81), 2.52 (95% CI: 1.98-3.19), 0.50 (95% CI: 0.39-0.63), and 5.08 (95% CI: 3.38-7.63). The AUC was 0.76 (95% CI: 0.72-0.79). I2 values of sensitivity (I2 = 94.41%) and specificity (I2 = 88.97%) were both > 50%. For the initial positive ALN patients, the pooled sensitivity and specificity were 0.64 (95% CI: 0.53-0.75) and 0.74 (95% CI: 0.64-0.82), respectively. Sensitivity analyses by focusing on studies with MRI performed post-NAC, studies using DCE-MRI, or studies with low risk of bias showed similar results to the primary analyses.

CONCLUSION

MRI may have suboptimal diagnostic value in assessing ALNS after NAC for breast cancer patients. Due to the inconsistency of NAC regimens, the variability of axillary surgery, and the lack of time interval between MRI and surgery, further studies are needed to confirm our findings.

CLINICAL RELEVANCE STATEMENT

Our study provided the diagnostic value of MRI in assessing axillary lymph node status after neoadjuvant chemotherapy for breast cancer patients.

KEY POINTS

• MRI may have suboptimal diagnostic value in assessing axillary lymph node status after NAC for general breast cancer patients. • The initial axillary lymph node status has little impact on the diagnostic efficacy of MRI. • The substantial heterogeneity among studies highlights the need for further studies to provide more high-quality evidence in this field.

A multivariable model of ultrasound and clinicopathological features for predicting axillary nodal burden of breast cancer: potential to prevent unnecessary axillary lymph node dissection

BACKGROUND

To develop a clinical model for predicting high axillary nodal burden in patients with early breast cancer by integrating ultrasound (US) and clinicopathological features.

METHODS AND MATERIALS

Patients with breast cancer who underwent preoperative US examination and breast surgery at the Affiliated Hospital of Nantong University (centre 1, n = 250) and at the Affiliated Hospital of Jiangsu University (centre 2, n = 97) between January 2012 and December 2016 and between January 2020 and March 2022, respectively, were deemed eligible for this study (n = 347). According to the number of lymph node (LN) metastasis based on pathology, patients were divided into two groups: limited nodal burden (0-2 metastatic LNs) and heavy nodal burden (≥ 3 metastatic LNs). In addition, US features combined with clinicopathological variables were compared between these two groups. Univariate and multivariate logistic regression analysis were conducted to identify the most valuable variables for predicting ≥ 3 LNs in breast cancer. A nomogram was then developed based on these independent factors.

RESULTS

Univariate logistic regression analysis revealed that the cortical thickness (p < 0.001), longitudinal to transverse ratio (p = 0.001), absence of hilum (p < 0.001), T stage (p = 0.002) and Ki-67 (p = 0.039) were significantly associated with heavy nodal burden. In the multivariate logistic regression analysis, cortical thickness (p = 0.001), absence of hilum (p = 0.042) and T stage (p = 0.012) were considered independent predictors of high-burden node. The area under curve (AUC) of the nomogram was 0.749.

CONCLUSION

Our model based on US variables and clinicopathological characteristics demonstrates that can help select patients with ≥ 3 LNs, which can in turn be helpful to predict high axillary nodal burden in early breast cancer patients and prevent unnecessary axillary lymph node dissection.

Research Progress of CXCR4-Targeting Radioligands for Oncologic Imaging

C-X-C motif chemokine receptor 4 (CXCR4) plays a key role in various physiological functions, such as immune processes and disease development, and can influence angiogenesis, proliferation, and distant metastasis in tumors. Recently, several radioligands, including peptides, small molecules, and nanoclusters, have been developed to target CXCR4 for diagnostic purposes, thereby providing new diagnostic strategies based on CXCR4. Herein, we focus on the recent research progress of CXCR4-targeting radioligands for tumor diagnosis. We discuss their application in the diagnosis of hematological tumors, such as lymphomas, multiple myelomas, chronic lymphocytic leukemias, and myeloproliferative tumors, as well as nonhematological tumors, including tumors of the esophagus, breast, and central nervous system. Additionally, we explored the theranostic applications of CXCR4-targeting radioligands in tumors. Targeting CXCR4 using nuclear medicine shows promise as a method for tumor diagnosis, and further research is warranted to enhance its clinical applicability.

Designing clinical trials based on modern imaging and metastasis-directed treatments in patients with oligometastatic breast cancer: a consensus recommendation from the EORTC Imaging and Breast Cancer Groups

Breast cancer remains the most common cause of cancer death among women. Despite its considerable histological and molecular heterogeneity, those characteristics are not distinguished in most definitions of oligometastatic disease and clinical trials of oligometastatic breast cancer. After an exhaustive review of the literature covering all aspects of oligometastatic breast cancer, 35 experts from the European Organisation for Research and Treatment of Cancer Imaging and Breast Cancer Groups elaborated a Delphi questionnaire aimed at offering consensus recommendations, including oligometastatic breast cancer definition, optimal diagnostic pathways, and clinical trials required to evaluate the effect of diagnostic imaging strategies and metastasis-directed therapies. The main recommendations are the introduction of modern imaging methods in metastatic screening for an earlier diagnosis of oligometastatic breast cancer and the development of prospective trials also considering the histological and molecular complexity of breast cancer. Strategies for the randomisation of imaging methods and therapeutic approaches in different subsets of patients are also addressed.

Detection of Axillary Lymph Node Involvement in Early-Stage Breast Cancer: Comparison between Staging 18F-2-Fluoro-2-Deoxy-D-Glucose Positron Emission Tomography-Computed Tomography Scans, Mammography, and Sentinel Lymph Node Biopsy

Aims

The aim of this study was to evaluate the role of 18F-2-fluoro-2-deoxy-D-glucose (18F-FDG) positron emission tomography-computed tomography (PET-CT) scan in the detection of axillary lymph node (ALN) involvement and comparison with sentinel lymph node biopsy (SLNB) in operable early-stage breast cancer (EBC).

Settings and Design

It is a retrospective analysis of staging PET-CT scan of EBC.

Methods

A total of 128 patients with histopathologically proven breast cancer (BC) were included in the study. Preoperative mammography supplemented with ultrasonography and staging 18F-FDG PET-CT scan was done for all patients. Surgery was done within 30 (mean ± standard deviation = 13.8 ± 10.5) days of staging. SLNB was performed in patients without PET-positive ALNs. All patients with positive sentinel nodes and PET-positive ALNs underwent axillary lymph node dissection (ALND).

Statistical Analysis Used

The comparison between categorical variables was made by Chi-square/Fisher's exact test as applicable. For continuous variables comparisons, Student's t-test and one-way analysis of variance tests were used.

Results

Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of PET-CT scan for detection of ALN involvement were 41.7%, 93.2%, 92.1%, and 45.6%, respectively. Sensitivity, specificity, PPV, and NPV of mammography were 84.5%, 54.5%, 78.0%, and 68.6%, respectively. Sixteen out of 46 (34.7%) patients with negative ALNs in PET-CT scan finally showed involvement in histopathology report after SLNB resulting in upstage of the disease. The size of tumor deposits in sentinel nodes was significantly smaller than PET-positive ALNs (P = 0.01). Our observations correlate with the results of earlier studies published in the literature.

Conclusions

18F-FDG PET-CT scan cannot substitute SLNB for ALN screening in EBC. The limitations are most marked in smaller and micrometastatic tumor deposits in ALNs and may be attributed to limitations of PET resolution. However, PET-positive nodes showed good specificity for disease involvement in our study. Therefore, ALND can safely be performed by omitting SLNB in such cases.

IONPs-Based Medical Imaging in Cancer Care: Moving Beyond Traditional Diagnosis and Therapeutic Assessment

Cancer-related burden of morbidity and mortality is rapidly rising worldwide. Medical imaging plays an important role in every phase of cancer management, including diagnosis, staging, treatment planning and evaluation. Iron oxide nanoparticles (IONPs) could serve as contrast agents or labeling agents to enhance the identification and visualization of pathological tissues as well as target cells. Multimodal or multifunctional imaging can be easily acquired by modifying IONPs with other imaging agents or functional groups, allowing the accessibility of combined imaging techniques and providing more comprehensive information for cancer care. To date, IONPs-enhanced medical imaging has gained intensive application in early diagnosis, monitoring treatment as well as guiding radio-frequency ablation, sentinel lymph node dissection, radiotherapy and hyperthermia therapy. Besides, IONPs mediated imaging is also capable of promoting the development of anti-cancer nanomedicines through identifying patients potentially sensitive to nanotherapeutics. Based on versatile imaging modes and application fields, this review highlights and summarizes recent research advances of IONPs-based medical imaging in cancer management. Besides, currently existing challenges are also discussed to provide perspectives and advices for the future development of IONPs-based imaging in cancer management.

Radiomics model of diffusion-weighted whole-body imaging with background signal suppression (DWIBS) for predicting axillary lymph node status in breast cancer

BACKGROUND

In breast cancer diagnosis and treatment, non-invasive prediction of axillary lymph node (ALN) metastasis can help avoid complications related to sentinel lymph node biopsy.

OBJECTIVE

This study aims to develop and evaluate machine learning models using radiomics features extracted from diffusion-weighted whole-body imaging with background signal suppression (DWIBS) examination for predicting the ALN status.

METHODS

A total of 100 patients with histologically proven, invasive, clinically N0 breast cancer who underwent DWIBS examination consisting of short tau inversion recovery (STIR) and DWIBS sequences before surgery were enrolled. Radiomic features were calculated using segmented primary lesions in DWIBS and STIR sequences and were divided into training (n = 75) and test (n = 25) datasets based on the examination date. Using the training dataset, optimal feature selection was performed using the least absolute shrinkage and selection operator algorithm, and the logistic regression model and support vector machine (SVM) classifier model were constructed with DWIBS, STIR, or a combination of DWIBS and STIR sequences to predict ALN status. Receiver operating characteristic curves were used to assess the prediction performance of radiomics models.

RESULTS

For the test dataset, the logistic regression model using DWIBS, STIR, and a combination of both sequences yielded an area under the curve (AUC) of 0.765 (95% confidence interval: 0.548-0.982), 0.801 (0.597-1.000), and 0.779 (0.567-0.992), respectively, whereas the SVM classifier model using DWIBS, STIR, and a combination of both sequences yielded an AUC of 0.765 (0.548-0.982), 0.757 (0.538-0.977), and 0.779 (0.567-0.992), respectively.

CONCLUSIONS

Use of machine learning models incorporating with the quantitative radiomic features derived from the DWIBS and STIR sequences can potentially predict ALN status.

Predicting of axillary lymph node metastasis in invasive breast cancer using multiparametric MRI dataset based on CNN model

Purpose

To develop a multiparametric MRI model for predicting axillary lymph node metastasis in invasive breast cancer.

Methods

Clinical data and T2WI, DWI, and DCE-MRI images of 252 patients with invasive breast cancer were retrospectively analyzed and divided into the axillary lymph node metastasis (ALNM) group and non-ALNM group using biopsy results as a reference standard. The regions of interest (ROI) in T2WI, DWI, and DCE-MRI images were segmented using MATLAB software, and the ROI was unified into 224 × 224 sizes, followed by image normalization as input to T2WI, DWI, and DCE-MRI models, all of which were based on ResNet 50 networks. The idea of a weighted voting method in ensemble learning was employed, and then T2WI, DWI, and DCE-MRI models were used as the base models to construct a multiparametric MRI model. The entire dataset was randomly divided into training sets and testing sets (the training set 202 cases, including 78 ALNM, 124 non-ALNM; the testing set 50 cases, including 20 ALNM, 30 non-ALNM). Accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of models were calculated. The receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to evaluate the diagnostic performance of each model for axillary lymph node metastasis, and the DeLong test was performed, P< 0.05 statistically significant.

Results

For the assessment of axillary lymph node status in invasive breast cancer on the test set, multiparametric MRI models yielded an AUC of 0.913 (95% CI, 0.799-0.974); T2WI-based model yielded an AUC of 0.908 (95% CI, 0.792-0.971); DWI-based model achieved an AUC of 0.702 (95% CI, 0.556-0.823); and the AUC of the DCE-MRI-based model was 0.572 (95% CI, 0.424-0.711). The improvement in the diagnostic performance of the multiparametric MRI model compared with the DWI and DCE-MRI-based models were significant (P< 0.01 for both). However, the increase was not meaningful compared with the T2WI-based model (P = 0.917).

Conclusion

Multiparametric MRI image analysis based on an ensemble CNN model with deep learning is of practical application and extension for preoperative prediction of axillary lymph node metastasis in invasive breast cancer.

Radiomics model based on features of axillary lymphatic nodes to predict axillary lymphatic node metastasis in breast cancer

BACKGROUND

Breast cancer (BC) is among the most common cancers worldwide. Machine learning-based radiomics model could predict axillary lymph node metastasis (ALNM) of BC accurately.

PURPOSE

The purpose is to develop a machine learning model to predict ALNM of BC by focusing on the radiomics features of axillary lymphatic node (ALN).

METHODS

A group of 398 BC patients with 800 ALNs were retrospectively collected. A set of patient characteristics were obtained to form clinical factors. Three hundred and twenty-six radiomics features were extracted from each region of interest for ALN in contrast-enhanced computed tomography (CECT) image. A framework composed of four feature selection methods and 14 machine learning classification algorithms was systematically applied. A clinical model, a radiomics model, and a combined model were developed using a cross-validation approach and compared. Metrics of the area under the curve (AUC), accuracy, sensitivity, and specificity were calculated to evaluate the performance of these models in the prediction of ALNM in BC.

RESULTS

Among the 800 cases of ALNs, there were 388 cases of positive metastasis (48.50%) and 412 cases of negative metastasis (51.50%). The baseline clinical model achieved the performance with an AUC = 0.8998 (95% CI [0.8540, 0.9457]). The radiomics model achieved an AUC = 0.9081 (95% CI [0.8640, 0.9523]). The combined model using the clinical factors and radiomics features achieved the best results with an AUC = 0.9305 (95% CI [0.8928, 0.9682]).

CONCLUSIONS

Combinations of feature selection methods and machine learning-based classification algorithms can develop promising predictive models to predict ALNM in BC using CECT features. The combined model of clinical factors and radiomics features outperforms both the clinical model and the radiomic model.

Beyond N Staging in Breast Cancer: Importance of MRI and Ultrasound-based Imaging

The correct N-staging in breast cancer is crucial to tailor treatment and stratify the prognosis. N-staging is based on the number and the localization of suspicious regional nodes on physical examination and/or imaging. Since clinical examination of the axillary cavity is associated with a high false negative rate, imaging modalities play a central role. In the presence of a T1 or T2 tumor and 0–2 suspicious nodes, on imaging at the axillary level I or II, a patient should undergo sentinel lymph node biopsy (SLNB), whereas in the presence of three or more suspicious nodes at the axillary level I or II confirmed by biopsy, they should undergo axillary lymph node dissection (ALND) or neoadjuvant chemotherapy according to a multidisciplinary approach, as well as in the case of internal mammary, supraclavicular, or level III axillary involved lymph nodes. In this scenario, radiological assessment of lymph nodes at the time of diagnosis must be accurate. False positives may preclude a sentinel lymph node in an otherwise eligible woman; in contrast, false negatives may lead to an unnecessary SLNB and the need for a second surgical procedure. In this review, we aim to describe the anatomy of the axilla and breast regional lymph node, and their diagnostic features to discriminate between normal and pathological nodes at Ultrasound (US) and Magnetic Resonance Imaging (MRI). Moreover, the technical aspects, the advantage and limitations of MRI versus US, and the possible future perspectives are also analyzed, through the analysis of the recent literature.

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.

Predicting axillary lymph node metastasis in breast cancer using the similarity of quantitative dual-energy CT parameters between the primary lesion and axillary lymph node

PURPOSE

To evaluate the similarity of quantitative dual-energy computed tomography (DECT) parameters between the primary breast cancer lesion and axillary lymph node (LN) for predicting LN metastasis.

MATERIALS AND METHODS

This retrospective study included patients with breast cancer who underwent contrast-enhanced DECT between July 2019 and April 2021. Relationships between LN metastasis and simple DECT parameters, similarity of DECT parameters, and pathological and morphological features were analyzed. ROC curve analysis was used to evaluate diagnostic ability.

RESULTS

Overall, 137 LNs (39 metastases and 98 non-metastases) were evaluated. Significant differences were observed in some pathological (nuclear grade, estrogen receptor status, and Ki67 index) and morphological characteristics (shortest and longest diameters of the LN, longest-to-shortest diameter ratio, and hilum), most simple DECT parameters, and all DECT similarity parameters between the LN metastasis and non-metastasis groups (all, P < 0.001-0.004). The shortest diameter of the LN (odds ratio 2.22; 95% confidence interval 1.47, 3.35; P < 0.001) and the similarity parameter of 40-keV attenuation (odds ratio, 2.00; 95% confidence interval 1.13, 3.53; P = 0.017) were independently associated with LN metastasis compared to simple DECT parameters of 40-keV attenuation (odds ratio 1.01; 95% confidence interval 0.99, 1.03; P =0.35). The AUC value of the similarity parameters for predicting metastatic LN was 0.78-0.81, even in cohorts with small LNs (shortest diameter < 5 mm) (AUC value 0.73-0.78).

CONCLUSION

The similarity of the delayed-phase DECT parameters could be a more useful tool for predicting LN metastasis than simple DECT parameters in breast cancer, regardless of LN size.

ACR Appropriateness Criteria® Imaging of the Axilla

This publication reviews the current evidence supporting the imaging approach of the axilla in various scenarios with broad differential diagnosis ranging from inflammatory to malignant etiologies. Controversies on the management of axillary adenopathy results in disagreement on the appropriate axillary imaging tests. Ultrasound is often the appropriate initial imaging test in several clinical scenarios. Clinical information (such as age, physical examinations, risk factors) and concurrent complete breast evaluation with mammogram, tomosynthesis, or MRI impact the type of initial imaging test for the axilla. Several impactful clinical trials demonstrated that selected patient's population can received sentinel lymph node biopsy instead of axillary lymph node dissection with similar overall survival, and axillary lymph node dissection is a safe alternative as the nodal staging procedure for clinically node negative patients or even for some node positive patients with limited nodal tumor burden. This approach is not universally accepted, which adversely affect the type of imaging tests considered appropriate for axilla. This document is focused on the initial imaging of the axilla in various scenarios, with the understanding that concurrent or subsequent additional tests may also be performed for the breast. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

Avoiding unnecessary intraoperative sentinel lymph node frozen section biopsy of patients with early breast cancer

Purpose

After the publication of the ACOSOG (American College of Surgeons Oncology Group) Z0011 trial, the rate of axillary lymph node dissection has reduced. Thus, the need for intraoperative frozen section biopsy of sentinel lymph nodes (SLNs) has become controversial. We identified patients for whom intraoperative SLN frozen section biopsy could be omitted and found that frozen section biopsy rate can be reduced.

Methods

We reviewed the records of patients with tumors ≤5 cm in diameter who underwent breast-conserving surgery between January 2013 and December 2019 at Seoul St. Mary’s Hospital. Clinicopathological and imaging characteristics were compared according to number of positive SLNs (0–2 SLNs positive vs. ≥3 SLNs positive).

Results

A total of 1,983 patients were included in this study. Thirty-two patients (1.6%) had at least 3 positive SLNs. Patients with ≥3 positive SLNs had significantly larger tumors and were more frequently high-grade tumors (P < 0.001 and P = 0.002, respectively). Identification of suspicious lymph nodes on imaging studies was also associated with the presence of ≥3 positive SLNs (hazard ratio, 11.54; 95% confidence interval, 4.42–30.10). All patients with none or only 1 suspicious lymph node on any imaging modality (n = 647, 32.6%) had 0–2 positive SLNs. Also, among patients with clinical T1-stage tumors and at least 2 suspicious lymph nodes on only 1 imaging modality (n = 514, 25.9%), only 2 cases had ≥3 positive SLNs.

Conclusion

We found that intraoperative SLN frozen biopsy could be omitted in patients using tumor size and axillary lymph node status on imaging modality.

Diagnostic Performance of FDG-PET/CT Scan as Compared to US-Guided FNA in Prediction of Axillary Lymph Node Involvement in Breast Cancer Patients

Purpose

The aim of this study was to evaluate the diagnostic ability of 2-deoxy-2-[fluorine-18]fluoro-d-glucose (¹⁸F-FDG) PET/non-contrast CT compared with those of ultrasound (US)-guided fine needle aspiration (FNA) for axillary lymph node (ALN) staging in breast cancer patients.

Patients and Methods

Preoperative ¹⁸F-FDG PET/non-contrast CT was performed in 268 women with breast cancer, as well as ALN dissection or sentinel lymph node (SLN) biopsy. One hundred sixty-four patients underwent US-guided FNA in combination with ¹⁸F-FDG PET/CT. The diagnostic performance of each modality was evaluated using histopathologic assessments as the reference standard. The receiver operating characteristic (ROC) curves were compared to evaluate the diagnostic ability of several imaging modalities.

Results

Axillary ¹⁸F-FDG uptake was positive in 180 patients, and 125 patients had axillary metastases according to the final pathology obtained by ALN dissection and/or SLN dissection. Of the patients with positive ¹⁸F-FDG uptake in the axilla, 21% had false-positive results, whereas 79% were truly positive. Eighty-eight patients had negative ¹⁸F-FDG uptake in the axilla, among which 25% were false-negative. ¹⁸F-FDG-PET/CT had a sensitivity of 86.59% and a specificity of 63.46% in the assessment of ALN metastasis; on the other hand, US-guided FNA had a sensitivity of 91.67% and a specificity of 87.50%. The mean primary cancer size (p = 0.04) and tumor grade (p = 0.04) in combination were the only factors associated with the accuracy of ¹⁸F-FDG PET/CT for detecting metastatic ALNs.

Conclusion

The diagnostic performance of ¹⁸F-FDG PET/CT for the detection of axillary node metastasis in breast cancer patients was not significantly different from that of US-guided FNA. Combining ¹⁸F-FDG PET/CT with US-guided FNA or SLN biopsy could improve the diagnostic performance compared to ¹⁸F-FDG PET/CT alone.

PET Imaging for Breast Cancer

Imaging plays an integral role in the clinical care of patients with breast cancer. This review article focuses on the use of PET imaging for breast cancer, highlighting the clinical indications and limitations of 2-deoxy-2-[¹⁸F]fluoro-d-glucose (FDG) PET/CT, the potential use of PET/MRI, and 16α-[¹⁸F]fluoroestradiol (FES), a newly approved radiopharmaceutical for estrogen receptor imaging.

Image quality and diagnostic performance evaluation in transcatheter aortic valve implantation candidates with atrial fibrillation using a whole-heart coverage CT scanner

OBJECTIVE

To evaluate the image quality and diagnostic performance for obstructive coronary artery disease of transcatheter aortic valve implantation (TAVI) patients with atrial fibrillation (AF) during TAVI planning CT using a whole-heart coverage CT scanner.

METHODS

Eighty-eight consecutive TAVI candidates with AF (50 men, 74 ± 6 years) who underwent both TAVI planning CT and invasive coronary catheter angiography (ICA) were retrospectively analyzed. With ICA results as the reference standard, the accuracy of TAVI planning CT for lesion detection on a per-vessel and per-patient level was calculated. Meanwhile, image quality, contrast volume, and effective dose (ED) were evaluated. A 5-point visual scale (1-5) was used to assess the subjective image quality. The CT value and signal-to-noise ratio were measured for the left main coronary artery (LM), left anterior descending (LAD), left circumflex (LCX), and right coronary arteries (RCA).

RESULTS

The ED for CCTA was 3.25 ± 1.39 mSv and contrast volume was 58.14 ± 12.34 mL. A total of 1371 (1371/1408 = 97.4%) segments with diameter > 1.5 mm were analyzed. For the subjective evaluation, the mean score was 3.99 ± 0.96 for overall image quality. The mean CT values in LM, RCA, LCX, and LAD were all above 400 HU. For the detection of > 50% stenosis, TAVI planning CT provided on the per-vessel and per-patient basis 97.06% and 100% in sensitivity, 96.23% and 89.06% in specificity, 99.7% and 100% in negative predictive value, and 73.3% and 77.4% in positive predictive value, respectively.

CONCLUSION

TAVI planning CT with whole-heart coverage demonstrates good CCTA image quality and a high sensitivity and NPV in excluding obstructive CAD in TAVI candidates with AF.

KEY POINTS

• Transcatheter aortic valve implantation planning (TAVI) CT with whole-heart coverage enables good image quality of CCTA in TAVI candidates with atrial fibrillation. • Obstructive coronary artery disease may be excluded with high accuracy in transcatheter aortic valve implantation (TAVI) candidates with atrial fibrillation with the usage of whole-heart coverage TAVI planning CT.

Convolutional Neural Network of Multiparametric MRI Accurately Detects Axillary Lymph Node Metastasis in Breast Cancer Patients With Pre Neoadjuvant Chemotherapy

BACKGROUND

Accurate assessment of the axillary lymph nodes (aLNs) in breast cancer patients is essential for prognosis and treatment planning. Current radiological staging of nodal metastasis has poor accuracy. This study aimed to investigate the machine learning convolutional neural networks (CNNs) on multiparametric MRI to detect nodal metastasis with 18FDG-PET as ground truths.

MATERIALS AND METHODS

Data were obtained via a retrospective search. Inclusion criteria were patients with bilateral breast MRI and 18FDG-PETand/or CT scans obtained before neoadjuvant chemotherapy. In total, 238 aLNs were obtained from 56 breast cancer patients with 18FDG-PET and/or CT and breast MRI data. Radiologists scored each node based on all MRI as diseased and non-diseased nodes. Five models were built using T1-W MRI, T2-W MRI, DCE MRI, T1-W + T2-W MRI, and DCE + T2-W MRI model. Performance was evaluated using receiver operating curve (ROC) analysis, including area under the curve (AUC).

RESULTS

All CNN models yielded similar performance with an accuracy ranging from 86.08% to 88.50% and AUC ranging from 0.804 to 0.882. The CNN model using T1-W MRI performed better than that using T2-W MRI in detecting nodal metastasis. CNN model using combined T1- and T2-W MRI performed the best compared to all other models (accuracy = 88.50%, AUC = 0.882), but similar in AUC to the DCE + T2-W MRI model (accuracy = 88.02%, AUC = 0.880). All CNN models performed better than radiologists in detecting nodal metastasis (accuracy = 65.8%).

CONCLUSION

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Usefulness and Prospects of Sentinel Lymph Node Biopsy for Patients With Breast Cancer Using the Medical Imaging Projection System

Background

The Medical Imaging Projection System (MIPS) projects indocyanine green (ICG) fluorescence images directly on the surgical field using a projection mapping technique. We conducted an observational study of sentinel lymph node (SLN) biopsy using the prototype MIPS; we found a high identification rate. However, the number of SLN-positive cases was small, and the sensitivity could not be evaluated. The aim of this study was to investigate the clinical usefulness of the MIPS assisted ICG fluorescence method using commercially available equipment.

Methods

This was a retrospective observational study. Patients with primary breast cancer who underwent SLN biopsy using the MIPS at Kyoto University Hospital from April to December 2020 were included in the study. The primary endpoints were the identification rate of SLNs and detection of positive SLNs by the MIPS. The secondary endpoint was the number of SLNs excised using the MIPS per patient. We also conducted a questionnaire survey focused on the utility of the MIPS; it involved doctors with an experience in using the MIPS.

Results

Seventy-nine patients (84 procedures) were included in the study. In 60 (71%) procedures, both the radioisotope (RI) method and MIPS were used. At least one SLN could be detected by the MIPS in all the procedures, with an identification rate of 100% (95% confidence interval 95.6–100%). A total of 19 (7%) positive SLNs were removed, which were identifiable by the MIPS. Among 57 patients in whom the MIPS and RI methods were used, there was no positive SLN only identified by the RI method. The results of the questionnaire survey showed that the MIPS enabled the operator and assistant to share the ICG fluorescence image in the surgical field and to communicate with each other easily.

Conclusion

The current study demonstrated that the identification rate of SLNs using the MIPS was high, and the MIPS can be used for detecting positive SLNs. It was suggested that the MIPS will be useful in learning SLN biopsy procedures.

Pretherapeutic Imaging for Axillary Staging in Breast Cancer: A Systematic Review and Meta-Analysis of Ultrasound, MRI and FDG PET

BACKGROUND

This systematic review aimed at comparing performances of ultrasonography (US), magnetic resonance imaging (MRI), and fluorodeoxyglucose positron emission tomography (PET) for axillary staging, with a focus on micro- or micrometastases.

METHODS

A search for relevant studies published between January 2002 and March 2018 was conducted in MEDLINE database. Study quality was assessed using the QUality Assessment of Diagnostic Accuracy Studies checklist. Sensitivity and specificity were meta-analyzed using a bivariate random effects approach; Results: Across 62 studies (n = 10,374 patients), sensitivity and specificity to detect metastatic ALN were, respectively, 51% (95% CI: 43-59%) and 100% (95% CI: 99-100%) for US, 83% (95% CI: 72-91%) and 85% (95% CI: 72-92%) for MRI, and 49% (95% CI: 39-59%) and 94% (95% CI: 91-96%) for PET. Interestingly, US detects a significant proportion of macrometastases (false negative rate was 0.28 (0.22, 0.34) for more than 2 metastatic ALN and 0.96 (0.86, 0.99) for micrometastases). In contrast, PET tends to detect a significant proportion of micrometastases (true positive rate = 0.41 (0.29, 0.54)). Data are not available for MRI.

CONCLUSIONS

In comparison with MRI and PET Fluorodeoxyglucose (FDG), US is an effective technique for axillary triage, especially to detect high metastatic burden without upstaging majority of micrometastases.

Extra-axillary nodal metastases in breast cancer: comparison of ultrasound, MRI, PET/CT, and CT

PURPOSE

To evaluate how ultrasound (US), MRI, PET/CT, and CT predict extra-axillary nodal metastases.

SUBJECTS AND METHODS

This IRB approved, retrospective study consisted of 124 suspicious supraclavicular and 88 internal mammary (IM) nodal cases with US and at least one additional cross-sectional examination (MRI, PET/CT or CT) from a total of 1472 invasive cancers with staging nodal US between January 2016-January 2019. Imaging findings were compared with the true node status, determined by fine needle aspirate (FNA) biopsy or evidence of response to chemotherapy on follow up imaging.

RESULTS

In the supraclavicular region, US had accuracy 98.2%, consisting of 97 true positives (TP), 27 false positives (FP), and 1348 true negative (TN). 93.5% of suspicious supraclavicular nodes had FNA for a PPV 78.2%. PET/CT had accuracy 88.6% (26 TP, 5 TN and 4 false negatives (FN)). CT exams had accuracy 61.7% (42 TP, 16 TN, 7 FP, and 29 FN). In the IM region, US had accuracy 93.2% (82 TP, 1 FP, 5 FN, and 1384 TN) but only 43.2% of suspicious IM nodes had FNA for a PPV 98.8%. MRI had accuracy 100.0% (all 47 TP). PET/CT exams had accuracy 96.8% (30 TP and 1FN). CT exams had accuracy 62.7% (36 TP, 1 TN, and 22 FN).

CONCLUSION

US/FNA has accuracy 98.2% and 93.2% in the supraclavicular and IM regions, however only 43.2% of suspicious IM nodes are directly sampled. In these cases, MRI or PET/CT can be used to problem solve and guide treatment decisions.

Radiomics MRI for lymph node status prediction in breast cancer patients: the state of art

OBJECTIVES

To create a review of the existing literature on the radiomic approach in predicting the lymph node status of the axilla in breast cancer (BC).

MATERIALS AND METHODS

Two reviewers conducted the literature search on MEDLINE databases independently. Ten articles on the prediction of sentinel lymph node metastasis in breast cancer with a radiomic approach were selected. The study characteristics and results were reported. The quality of the methodology was evaluated according to the Radiomics Quality Score (RQS).

RESULTS

All studies were retrospective in design and published between 2017 and 2020. The majority of studies used DCE-MRI sequences and two investigated only pre-contrast images. The sample size was lower than 200 patients for 7 studies. The pre-processing used software, feature extraction and selection methods and classifier development are heterogeneous and a standardization of results is not yet possible. The average RQS score was 11.1 (maximum possible value = 36). The criteria with the lowest scores were the type of study, validation, comparison with a gold standard, potential clinical utility, cost-effective analysis and open science data.

CONCLUSION

The field of radiomics is a diagnostic approach of relative recent development. The results in predicting axillary lymph node status are encouraging, but there are still weaknesses in the quality of studies that may limit the reproducibility of the results.

Radiomic features of axillary lymph nodes based on pharmacokinetic modeling DCE-MRI allow preoperative diagnosis of their metastatic status in breast cancer

OBJECTIVE

To study the feasibility of use of radiomic features extracted from axillary lymph nodes for diagnosis of their metastatic status in patients with breast cancer.

MATERIALS AND METHODS

A total of 176 axillary lymph nodes of patients with breast cancer, consisting of 87 metastatic axillary lymph nodes (ALNM) and 89 negative axillary lymph nodes proven by surgery, were retrospectively reviewed from the database of our cancer center. For each selected axillary lymph node, 106 radiomic features based on preoperative pharmacokinetic modeling dynamic contrast enhanced magnetic resonance imaging (PK-DCE-MRI) and 5 conventional image features were obtained. The least absolute shrinkage and selection operator (LASSO) regression was used to select useful radiomic features. Logistic regression was used to develop diagnostic models for ALNM. Delong test was used to compare the diagnostic performance of different models.

RESULTS

The 106 radiomic features were reduced to 4 ALNM diagnosis-related features by LASSO. Four diagnostic models including conventional model, pharmacokinetic model, radiomic model, and a combined model (integrating the Rad-score in the radiomic model with the conventional image features) were developed and validated. Delong test showed that the combined model had the best diagnostic performance: area under the curve (AUC), 0.972 (95% CI [0.947-0.997]) in the training cohort and 0.979 (95% CI [0.952-1]) in the validation cohort. The diagnostic performance of the combined model and the radiomic model were better than that of pharmacokinetic model and conventional model (P<0.05).

CONCLUSION

Radiomic features extracted from PK-DCE-MRI images of axillary lymph nodes showed promising application for diagnosis of ALNM in patients with breast cancer.

Establishing a prediction model of axillary nodal burden based on the combination of CT and ultrasound findings and the clinicopathological features in patients with early-stage breast cancer

Background

Axillary lymph node (ALN) management in early-stage breast cancer (ESBC) patients has become less invasive during the past decades. Here, we tried to explore whether high nodal burden (HNB) in ESBC patients could be predicted preoperatively, so as to avoid unnecessary sentinel lymph node biopsy (SLNB).

Methods

The clinicopathological and imaging data of patients with early invasive breast cancer (cT_1-2N₀M₀) were analyzed retrospectively. Univariate and multivariate analyses were performed for the risk factors of axillary HNB in ESBC patients, and a risk prediction model of HNB was established.

Results

HNB was identified in 105 (8.0%) of 1,300 ESBC patients. Multivariate analysis showed that estrogen receptors (ER) status, human epidermal growth factor receptor 2 (HER2) status, number of abnormal lymph nodes (LNs) on computed tomography (CT), and axillary score on ultrasound (US) were the risk factors of HNB (all P<0.05). The area under the receiver operating characteristic (ROC) curve in the prediction model was 0.914, with the sensitivity being 85.7% and the specificity being 82.4%. The calibration curve showed that the prediction model had good performance.

Conclusions

As a valuable tool for predicting HNB in ESBC patients, this newly established model helps clinicians to make reasonable axillary surgery decisions and thus avoid unnecessary SLNB.

Preliminary study of AI-assisted diagnosis using FDG-PET/CT for axillary lymph node metastasis in patients with breast cancer

Background

To improve the diagnostic accuracy of axillary lymph node (LN) metastasis in breast cancer patients using 2-[¹⁸F]FDG-PET/CT, we constructed an artificial intelligence (AI)-assisted diagnosis system that uses deep-learning technologies.

Materials and methods

Two clinicians and the new AI system retrospectively analyzed and diagnosed 414 axillae of 407 patients with biopsy-proven breast cancer who had undergone 2-[¹⁸F]FDG-PET/CT before a mastectomy or breast-conserving surgery with a sentinel lymph node (LN) biopsy and/or axillary LN dissection. We designed and trained a deep 3D convolutional neural network (CNN) as the AI model. The diagnoses from the clinicians were blended with the diagnoses from the AI model to improve the diagnostic accuracy.

Results

Although the AI model did not outperform the clinicians, the diagnostic accuracies of the clinicians were considerably improved by collaborating with the AI model: the two clinicians' sensitivities of 59.8% and 57.4% increased to 68.6% and 64.2%, respectively, whereas the clinicians' specificities of 99.0% and 99.5% remained unchanged.

Conclusions

It is expected that AI using deep-learning technologies will be useful in diagnosing axillary LN metastasis using 2-[¹⁸F]FDG-PET/CT. Even if the diagnostic performance of AI is not better than that of clinicians, taking AI diagnoses into consideration may positively impact the overall diagnostic accuracy.

Diagnostic performance of PET/computed tomography versus PET/MRI and diffusion-weighted imaging in the N- and M-staging of breast cancer patients

OBJECTIVE

To provide a systematic review regarding the diagnostic performance of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/magnetic resonance imaging (PET/MRI) and diffusion-weighted imaging (DWI) compared to 18F-FDG PET/computed tomography (CT) focused on nodal and distant staging in breast cancer patients.

METHODS

The PubMed and Embase databases were searched for relevant publications until April 2020. Two independent reviewers searched for eligible articles based on predefined in- and exclusion criteria, assessed quality and extracted data.

RESULTS

Eleven eligible studies were selected from 561 publications identified by the search. In seven studies, PET/CT was compared with PET/MRI, and in five, PET/CT with DWI. Significantly higher sensitivity for PET/MRI compared to PET/CT in a lesion-based analysis was reported for all lesions together (77% versus 89%) in one study, osseous metastases (69-99% versus 92-98%) in two studies and hepatic metastases (70-75% versus 80-100%) in one study. Moreover, PET/MRI revealed a significantly higher amount of osseous metastases (90 versus 141) than PET/CT. PET/CT is associated with a statistically higher specificity than PET/MRI in the lesion detection of all lesions together (98% versus 96%) and of osseous metastases (100% versus 95%), both in one study. None of the reviewed studies reported significant differences between PET/CT and DWI for any of the evaluated sites. There is a trend toward higher specificity for PET/CT.

CONCLUSION

In general, there is a trend toward higher sensitivity and lower specificity of PET/MRI when compared to PET/CT. Results on the diagnostic performance of DWI are conflicting. Rather than evaluating it separate, it seems to have complementary value when combined with other MR sequences.

Preoperative Prediction of Axillary Lymph Node Metastasis in Breast Carcinoma Using Radiomics Features Based on the Fat-Suppressed T2 Sequence

RATIONALE AND OBJECTIVES

To investigate the value of radiomics method based on the fat-suppressed T2 sequence for preoperative predicting axillary lymph node (ALN) metastasis in breast carcinoma.

MATERIALS AND METHODS

The data of 329 invasive breast cancer patients were divided into the primary cohort (n = 269) and validation cohort (n = 60). Radiomics features were extracted from the fat-suppressed T2-weighted images on breast MRI, and ALN metastasis-related radiomics feature selection was performed using Mann-Whitney U-test and support vector machines with recursive feature elimination; then a radiomics signature was constructed by linear support vector machine. The predictive models were constructed using a linear regression model based on the clinicopathologic factors and radiomics signature, and nomogram was used for a visual prediction of the combined model. The predictive performances are evaluated with the sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve.

RESULTS

A total of 647 radiomics features were extracted from each patient. About 23 ALN metastasis-related radiomics features were selected to construct the radiomics signature, including 17 texture features, 5 first-order statistical features, and one shape feature; patient age, tumor size, HER2 status, and vascular cancer thrombus accompanied or not were selected to construct the cilinicopathologic feature model. The sensitivity, specificity, accuracy, and are under the curve value of radiomics signature, clinicopathologic feature model, and the nomogram were 65.22%, 81.08%, 75.00%, and 0.819 (95% confidence interval [CI]: 0.776-0.861), 30.44%, 81.08%, 61.67%, and 0.605 (95% CI: 0.571-0.624) and 60.87%, 89.19%, 78.33%, and 0.810 (95% CI: 0.761-0.855), respectively.

CONCLUSION

Radiomics methods based on the fat-suppressed T2 sequence and the nomogram are helpful for preoperative accurate predicting ALN metastasis.

Application of PET Tracers in Molecular Imaging for Breast Cancer

PURPOSE OF REVIEW

Molecular imaging with positron emission tomography (PET) is a powerful tool to visualize breast cancer characteristics. Nonetheless, implementation of PET imaging into cancer care is challenging, and essential steps have been outlined in the international "imaging biomarker roadmap." In this review, we identify hurdles and provide recommendations for implementation of PET biomarkers in breast cancer care, focusing on the PET tracers 2-[18F]-fluoro-2-deoxyglucose ([18F]-FDG), sodium [18F]-fluoride ([18F]-NaF), 16α-[18F]-fluoroestradiol ([18F]-FES), and [89Zr]-trastuzumab.

RECENT FINDINGS

Technical validity of [18F]-FDG, [18F]-NaF, and [18F]-FES is established and supported by international guidelines. However, support for clinical validity and utility is still pending for these PET tracers in breast cancer, due to variable endpoints and procedures in clinical studies. Assessment of clinical validity and utility is essential towards implementation; however, these steps are still lacking for PET biomarkers in breast cancer. This could be solved by adding PET biomarkers to randomized trials, development of imaging data warehouses, and harmonization of endpoints and procedures.

Diagnostic performance of time-of-flight PET/CT for evaluating nodal metastasis of the axilla in breast cancer

OBJECTIVE

The aim of this study was to evaluate the performance of preoperative axillary lymph node assessment in breast cancer using time-of-flight 18F-fluorodeoxyglucose PET/computed tomography (TOF [F-18]FDG-PET/CT).

METHODS

Eighty-two women with breast cancer (mean age, 59.3 years; range, 30-84 years) underwent TOF [F-18]FDG-PET/CT scanning before surgery between January 2016 and June 2018 at our hospital. Visual analysis of FDG uptake and the maximum standardized uptake value (SUVmax) of axillary lymph nodes were compared with the pathological diagnoses.

RESULTS

There were 77 patients with invasive breast carcinoma (mean invasive long diameter, 18.5 mm; range, 2-90 mm) and five patients with noninvasive carcinoma. Axillary lymph node metastases were histologically confirmed in 13 of 82 patients (15.9%). SUVmax showed an area under a receiver operating characteristic curve of 0.916, and the cut-off value of 1.1 was appropriate. By visual assessment, there were 11 true positives, 15 false positives, 54 true negatives and two false negatives; the sensitivity, specificity, positive predictive value, negative predictive value and accuracy were 85%, 78%, 42%, 96% and 79%, respectively. SUVmax showed values of 69%, 99%, 90%, 94% and 94%, respectively.

CONCLUSIONS

The sensitivity of TOF [F-18]FDG-PET/CT was as high as 85% by visual analysis. SUVmax using TOF [F-18]FDG-PET/CT showed high diagnostic performance for N-staging in breast cancer patients, especially high negative predictive value. The specificity, positive predictive value and accuracy of SUVmax were higher than those of visual analysis.

Role of sonoelastography in assessment of axillary lymph nodes in breast cancer: a systematic review and meta-analysis

AIM

To evaluate the effectiveness of shear-wave elastography (SWE) and strain elastography (SE) for axillary lymph nodes (ALNs).

MATERIALS AND METHODS

PubMed, Embase, and Cochrane Library databases were searched until September 2018. Weighted mean difference was calculated for continuous variables. The accuracy of sonoelastography was assessed by calculating pooled sensitivity, specificity, area under the curve (AUC), positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR). All data were analysed using Stata 12.0.

RESULTS

Ten studies with 1,038 ALNs were included in the meta-analysis. Five studies evaluated the use of SE, and the other five evaluated the SWE. The SWE stiffness values of malignant ALNs were significantly higher than those of benign nodes. Both SE and SWE have relatively high specificity and sensitivity. The max stiffness in SWE showed the highest specificity (0.94; 95% confidence interval [CI], 0.81-0.98), PLR (12.1; 95% CI, 4-36.5), NLR (0.29; 95% CI, 0.12-0.69), AUC (0.94; 95% CI, 0.91-0.96), and DOR (42; 95% CI, 12-154); in contrast, the mean stiffness showed the highest sensitivity (0.80; 95% CI, 0.61-0.91).

CONCLUSION

Sonoelastography demonstrated high sensitivity and specificity for differentiating between malignant and benign ALNs. The max and mean stiffness on SWE appeared to exhibit the highest accuracy. Thus, SWE is an effective accompaniment to sentinel node biopsy, and is appropriate for preoperative assessment of ALNs in the post-Z0011 era.

Convolutional Neural Network Detection of Axillary Lymph Node Metastasis Using Standard Clinical Breast MRI

BACKGROUND

Axillary lymph node status is important for breast cancer staging and treatment planning as the majority of breast cancer metastasis spreads through the axillary lymph nodes. There is currently no reliable noninvasive imaging method to detect nodal metastasis associated with breast cancer.

MATERIALS AND METHODS

Magnetic resonance imaging (MRI) data were those from the peak contrast dynamic image from 1.5 Tesla MRI scanners at the pre-neoadjuvant chemotherapy stage. Data consisted of 66 abnormal nodes from 38 patients and 193 normal nodes from 61 patients. Abnormal nodes were those determined by expert radiologist based on ¹⁸Fluorodeoxyglucose positron emission tomography images. Normal nodes were those with negative diagnosis of breast cancer. The convolutional neural network consisted of 5 convolutional layers with filters from 16 to 128. Receiver operating characteristic analysis was performed to evaluate prediction performance. For comparison, an expert radiologist also scored the same nodes as normal or abnormal.

RESULTS

The convolutional neural network model yielded a specificity of 79.3% ± 5.1%, sensitivity of 92.1% ± 2.9%, positive predictive value of 76.9% ± 4.0%, negative predictive value of 93.3% ± 1.9%, accuracy of 84.8% ± 2.4%, and receiver operating characteristic area under the curve of 0.91 ± 0.02 for the validation data set. These results compared favorably with scoring by radiologists (accuracy of 78%).

CONCLUSION

The results are encouraging and suggest that this approach may prove useful for classifying lymph node status on MRI in clinical settings in patients with breast cancer, although additional studies are needed before routine clinical use can be realized. This approach has the potential to ultimately be a noninvasive alternative to lymph node biopsy.

Diagnostic performance of axillary ultrasound and standard breast MRI for differentiation between limited and advanced axillary nodal disease in clinically node-positive breast cancer patients

Preoperative differentiation between limited (pN1; 1–3 axillary metastases) and advanced (pN2–3; ≥4 axillary metastases) nodal disease can provide relevant information regarding surgical planning and guiding adjuvant radiation therapy. The aim was to evaluate the diagnostic performance of preoperative axillary ultrasound (US) and breast MRI for differentiation between pN1 and pN2–3 in clinically node-positive breast cancer. A total of 49 patients were included with axillary metastasis confirmed by US-guided tissue sampling. All had undergone breast MRI between 2008–2014 and subsequent axillary lymph node dissection. Unenhanced T2-weighted MRI exams were reviewed by two radiologists independently. Each lymph node on the MRI exams was scored using a confidence scale (0–4) and compared with histopathology. Diagnostic performance parameters were calculated for differentiation between pN1 and pN2–3. Interobserver agreement was determined using Cohen’s kappa coefficient. At final histopathology, 67.3% (33/49) and 32.7% (16/49) of patients were pN1 and pN2–3, respectively. Breast MRI was comparable to US in terms of accuracy (MRI reader 1 vs US, 71.4% vs 69.4%, p = 0.99; MRI reader 2 vs US, 73.5% vs 69.4%, p = 0.77). In the case of 1–3 suspicious lymph nodes, pN2–3 was observed in 30.4% on US (positive predictive value (PPV) 69.6%) and in 22.2–24.3% on MRI (PPV 75.7–77.8%). In the case of ≥4 suspicious lymph nodes, pN1 was observed in 33.3% on US (negative predictive value (NPV) 66.7%) and in 38.5–41.7% on MRI (NPV 58.3–61.5%). Interobserver agreement was considered good (k = 0.73). In clinically node-positive patients, the diagnostic performance of axillary US and breast MRI is comparable and limited for accurate differentiation between pN1 and pN2–3. Therefore, there seems no added clinical value of preoperative breast MRI regarding nodal staging in patients with positive axillary US.

Identification of Axillary Lymph Node Metastasis in Patients With Breast Cancer Using Dual-Phase FDG PET/CT

OBJECTIVE. The aim of this study was to assess the diagnostic performance of dual-phase ¹⁸F-FDG PET/CT in detecting axillary lymph node metastasis in patients with breast cancer. MATERIALS AND METHODS. A total of 826 patients with breast cancer were retrospectively evaluated. PET/CT scans were performed 1 hour and 2 hours after FDG administration before treatment. The maximum standardized uptake value (SUV_max) in the axillary lymph node at both time points (hereafter referred to as SUV_max1 and SUV_max2, respectively) and the retention index (RI) were calculated. RESULTS. Axillary lymph node metastasis was detected in 285 of 826 patients (34.5%). The median axillary SUV_max1, SUV_max2, and RI in patients with nodal metastasis were higher than those in patients without metastasis (1.5 vs 0.6, 1.6 vs 0.5, and 7.7 vs -3.7, respectively; all p < 0.001). The diagnostic accuracy of axillary SUV_max1 and SUV_max2 was equivalent, and the sensitivity and specificity of SUV_max1 were 74.7% and 83.4%, respectively. Although the performance of the axillary RI was inferior to that of SUV_max1 and SUV_max2, both the SUV_max and the RI were independent predictors of nodal metastasis, and a positive RI suggested axillary lymph node involvement when the SUV_max1 was significantly high. Of 533 patients with category T1-2 breast cancer without lymph node swelling, 101 (19.0%) had pathologic lymph node involvement; the negative predictive value of axillary SUV_max1 was 86.8%. CONCLUSION. Delayed phase imaging identified axillary lymph node metastasis as accurately as standard PET/CT. A high negative predictive value of PET/CT for the detection of nodal metastasis is helpful to avoid surgical axillary assessment in patients with category T1-2 breast cancer without lymph node swelling.

Diagnostic value of MRI combined with ultrasound for lymph node metastasis in breast cancer: Protocol for a meta-analysis

BACKGROUND

Early diagnosis and treatment of breast cancer are important to prevent fatal tumor progression. Axillary lymph node (ALN) status is the most significant prognostic factor for diagnosing overall survival in breast cancer patients. Axillary lymph node dissection (ALND) is regarded as the reference standard for determining ALN status. However, ALND is an invasive therapy with high morbidity and complications such as lymphedema, seroma and nerve injury. Comparatively, magnetic resonance imaging (MRI) and ultrasound are noninvasive and non-radiative techniques that are common imaging methods to diagnose breast cancer lymph node metastasis. Many studies have investigated the diagnostic value of MRI combined with ultrasound for breast cancer ALN metastasis, but the evidence has been insufficient to apply these modalities when diagnosing new patients.

METHODS

We will search electronic databases including PubMed, EMbase, The Cochrane Library, Chinese Biomedical Database, WangFang Database, and China National Knowledge Infrastructure. The language of studies is limited in English or Chinese. The final search includes articles published in June, 2018. Stata 14.0 software will be used for all statistical analyses, and Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) will be utilized to evaluate the quality of the included studies. Meta-regression and subgroup analyses will be performed to explore heterogeneity, which will be derived from the different countries of origin of the included studies. Deeks' funnel plot asymmetry test will be demonstrated the inexistence of publication bias.

RESULT

This study will provide a rational synthesis of current evidences for magnetic resonance imaging combined with ultrasound for breast cancer.

CONCLUSION

The conclusion of this study will provide evidence for the diagnostic value of MRI combined with ultrasound for lymph node metastasis in breast cancer.

REGISTRATION

PROS-PERO CRD42019134474.

Can Complete Axillary Node Dissection Be Safely Omitted in Patients with Early Breast Cancer When the Sentinel Node Biopsy Is Positive for Malignancy? An Update for Clinical Practice

The sentinel lymph node biopsy (SLNB) has become the new standard-of-care for patients with clinically node-negative invasive breast cancer. The focused examination of fewer lymph nodes in addition to improvements in histopathological and molecular analysis have increased the rate at which micrometastases and isolated tumor cells are identified. We reviewed the literature and summarized the evidence regarding the need for complete axillary lymph node dissection (ALND) following the finding of a positive sentinel node biopsy through the identification of the most important outcomes and evaluation of quality of evidence. The article focuses on the safe omission of complete ALND when the axillary lymph nodes contain macrometastases and provides an overview of the topic primarily based on level 1 evidence derived from randomized clinical trials with a critical appraisal of the ACOSOG Z0011 trial.

Second-generation motion correction algorithm improves diagnostic accuracy of single-beat coronary CT angiography in patients with increased heart rate

OBJECTIVE

To assess the effect of a second-generation motion correction algorithm on the diagnostic accuracy of coronary computed tomography angiography (CCTA) using a 256-detector row CT in patients with increased heart rates.

METHODS

Eighty-one consecutive symptomatic cardiac patients with increased heart rates (≥ 75 beats per min) were enrolled. All patients underwent CCTA and invasive coronary angiography (ICA). CCTA was performed with a 256-detector row CT using prospectively ECG-triggered single-beat protocol. Images were reconstructed using standard (STD) algorithm, first-generation intra-cycle motion correction (MC1) algorithm, and second-generation intra-cycle motion correction (MC2) algorithm. The image quality of coronary artery segments was assessed by two experienced radiologists using a 4-point scale (1: non-diagnostic and 4: excellent), according to the 18-segment model. Diagnostic performance for segments with significant lumen stenosis (≥ 50%) was compared between STD, MC1, and MC2 by using ICA as the reference standard.

RESULTS

The mean effective dose of CCTA was 1.0 mSv. On per-segment level, the overall image quality score and interpretability were improved to 3.56 ± 0.63 and 99.2% due to the use of MC2, as compared to 2.81 ± 0.85 and 92.5% with STD and 3.21 ± 0.79 and 97.2% with MC1. On per-segment level, compared to STD and MC1, MC2 improved the sensitivity (92.2% vs. 79.2%, 80.7%), specificity (97.8% vs. 82.1%, 90.8%), positive predictive value (89.9% vs. 48.4%, 65.1%), negative predictive value (98.3% vs. 94.9%, 95.7%), and diagnostic accuracy (96.8% vs. 81.5%, 89.0%).

CONCLUSION

A second-generation intra-cycle motion correction algorithm for single-beat CCTA significantly improves image quality and diagnostic accuracy in patients with increased heart rate.

KEY POINTS

• A second-generation motion correction (MC2) algorithm can further improve the image quality of all coronary arteries than a first-generation motion correction (MC1). • MC2 algorithm can significantly reduce the number of false positive segments compared to standard and MC1 algorithm.

L’exploration axillaire : un standard du bilan préthérapeutique

L’exploration préthérapeutique axillaire est une étape majeure du bilan initial du cancer du sein. L’échographie associée à un prélèvement est actuellement recommandée en première intention. L’IRM et la TEP/TDM au 18FDG sont utiles dans l’évaluation ganglionnaire axillaire. Les sensibilités et spécificités des examens d’imagerie sont globalement identiques, et leur combinaison permet d’obtenir les meilleures performances. Actuellement, la technique du ganglion sentinelle est indispensable en cas de tumeurs mammaires T1-T2 N0 et en cas d’adénopathie suspecte échographiquement avec cytoponction ou microbiopsie négative.

Use of Breast-Specific PET Scanners and Comparison with MR Imaging

The goals of this article are to discuss the role of breast-specific PET imaging of women with breast cancer, compare the clinical performance of positron emission mammography (PEM) and MR imaging for current indications, and provide recommendations for when women should undergo PEM instead of breast MR imaging.

PET imaging of chemokine receptor CXCR4 in patients with primary and recurrent breast carcinoma

Background

CXCR4 is a chemokine receptor frequently overexpressed in invasive breast cancer that has been shown to play a major role in signaling pathways involved in metastasis. The aim of this retrospective analysis was to assess the diagnostic performance of CXCR4-directed PET imaging in patients with breast cancer using the recently introduced CXCR4-targeted PET probe ⁶⁸Ga-Pentixafor.

Results

Thirteen patients with first diagnosis of breast cancer, four patients with recurrent disease after primary breast cancer, and one patient with axillary lymph node metastasis of unknown primary underwent CXCR4-targeted PET imaging using ⁶⁸Ga-Pentixafor. Maximum standardized uptake values (SUVmax) and tumor-to-background (T/B) ratios of tumor lesions were measured and compared with pathological prognostic factors and molecular subtypes. ¹⁸F-FDG PET/CT images were available in 8/18 cases and were compared semi-quantitatively. Comparison with CXCR4 expression determined by immunohistochemistry was performed in 7/18 patients.

Nine of 13 primary breast cancers were visually detectable on ⁶⁸Ga-Pentixafor PET images (mean SUVmax of 3.0). The visually undetectable lesions included both cases of invasive lobular carcinoma (ILC) and two cases of invasive carcinoma of no special type (NST) without any hormone receptor and HER2 expression (triple negative). Metastases of recurrent breast cancer and unknown primary cancer were visually detectable in all five cases, exhibiting a mean SUVmax of 3.5. ¹⁸F-FDG PET demonstrated higher SUVmax in all patients compared to ⁶⁸Ga-Pentixafor PET. A correlation between SUVmax obtained from ⁶⁸Ga-Pentixafor PET and prognostic factors including estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) status, proliferation index, tumor grade, or molecular subtypes was not observed.

Conclusions

CXCR4-directed PET imaging in patients with primary and recurrent breast cancer is feasible; however, tumor detectability is significantly lower compared to ¹⁸F-FDG PET. Moreover, we did not find any correlation between aforementioned prognostic factors of breast cancer and CXCR4-targeted tracer accumulation. Based on these results in a small patient cohort, CXCR4-targeted PET imaging does not seem to be suitable as a general diagnostic tool for imaging of breast cancer. Future CXCR4 imaging studies should investigate whether this modality might be useful in more specific applications, e.g., in therapeutic approaches especially under the view of current developments in targeted immune cell and immune checkpoint inhibitory therapy.

Real-time navigation system for sentinel lymph node biopsy in breast cancer patients using projection mapping with indocyanine green fluorescence

BACKGROUND

Inability to visualize indocyanine green fluorescence images in the surgical field limits the application of current near-infrared fluorescence imaging (NIR) systems for real-time navigation during sentinel lymph node (SLN) biopsy in breast cancer patients. The aim of this study was to evaluate the usefulness of the Medical Imaging Projection System (MIPS), which uses active projection mapping, for SLN biopsy.

METHODS

A total of 56 patients (59 procedures) underwent SLN biopsy using the MIPS between March 2016 and November 2017. After SLN biopsy using the MIPS, residual SLNs were removed using a conventional NIR camera and/or radioisotope method. The primary endpoint of this study was identification rate of SLNs using the MIPS.

RESULTS

In all procedures, at least one SLN was detected by the MIPS, giving an SLN identification rate of 100% [95% confidence interval (CI) 94-100%]. SLN biopsy was successfully performed without operating lights in all procedures. In total, 3 positive SLNs were excised using MIPS, but were not included in the additional SLNs excised by other methods. The median number of SLNs excised using the MIPS was 3 (range 1-7). Of procedures performed after preoperative systemic therapy, the median number of SLNs excised using the MIPS was 3 (range 2-6).

CONCLUSIONS

The MIPS is effective in detecting SLNs in patients with breast cancer, providing continuous and accurate projection of fluorescence signals in the surgical field, without need for operating lights, and could be useful in real-time navigation surgery for SLN biopsy.