Evaluation of Axillary Lymph Node Status in Breast Cancer with MRI

A comprehensive approach for evaluating lymphovascular invasion in invasive breast cancer: Leveraging multimodal MRI findings, radiomics, and deep learning analysis of intra- and peritumoral regions

PURPOSE

To evaluate lymphovascular invasion (LVI) in breast cancer by comparing the diagnostic performance of preoperative multimodal magnetic resonance imaging (MRI)-based radiomics and deep-learning (DL) models.

METHODS

This retrospective study included 262 patients with breast cancer-183 in the training cohort (144 LVI-negative and 39 LVI-positive cases) and 79 in the validation cohort (59 LVI-negative and 20 LVI-positive cases). Radiomics features were extracted from the intra- and peritumoral breast regions using multimodal MRI to generate gross tumor volume (GTV)_radiomics and gross tumor volume plus peritumoral volume (GPTV)_radiomics. Subsequently, DL models (GTV_DL and GPTV_DL) were constructed based on the GTV and GPTV to determine the LVI status. Finally, the most effective radiomics and DL models were integrated with imaging findings to establish a hybrid model, which was converted into a nomogram to quantify the LVI risk.

RESULTS

The diagnostic efficiency of GPTV_DL was superior to that of GTV_DL (areas under the curve [AUCs], 0.771 and 0.720, respectively). Similarly, GPTV_radiomics outperformed GTV_radiomics (AUC, 0.685 and 0.636, respectively). Univariate and multivariate logistic regression analyses revealed an association between imaging findings, such as MRI-axillary lymph nodes and peritumoral edema (AUC, 0.665). The hybrid model achieved the highest accuracy by combining GPTV_DL, GPTV_radiomics, and imaging findings (AUC, 0.872).

CONCLUSION

The diagnostic efficiency of the GPTV-derived radiomics and DL models surpassed that of the GTV-derived models. Furthermore, the hybrid model, which incorporated GPTV_DL, GPTV_radiomics, and imaging findings, demonstrated the effective determination of LVI status prior to surgery in patients with breast cancer.

Delta-Radiomics Based on Dynamic Contrast-Enhanced MRI for Predicting Lymphovascular Invasion in Invasive Breast Cancer

RATIONALE AND OBJECTIVES

Treatment strategies for invasive breast cancer require accurate lymphovascular invasion (LVI) predictions. This study aimed to investigate the effectiveness of delta radiomics based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for assessing LVI and develop a nomogram to aid treatment decisions.

MATERIALS AND METHODS

Overall, 293 patients with resectable invasive breast cancer underwent preoperative DCE-MRI. Radiomic features were extracted from pre-contrast (A0), first post-contrast (A1), and subtracted images of A0 and A1. Three radiomics models were developed using several data analyses; logistic analyses were performed to identify radiological features to predict the LVI status. A hybrid model integrating both radiological features and optimal radiomics was developed. Receiver operating characteristic analysis was employed to evaluate model performance, using the area under the curve (AUC) as a quantitative metric for discriminative ability.

RESULTS

In the test set, the Radiomics-Delta model, with 17 radiomic features, had an AUC of 0.781 and accuracy of 0.705. Radiomics-A0, with 10 features, had an AUC of 0.619 and accuracy of 0.523, while Radiomics-A1, with 8 features, had an AUC of 0.715 and accuracy of 0.591. The hybrid model exhibited better performance, with an AUC of 0.868 and accuracy of 0.875, than the radiological and Radiomics-Delta models, with an AUC of 0.759 and 0.781, respectively, and accuracy of 0.773 and 0.705, respectively.

CONCLUSION

Compared to Radiomics-A0 and Radiomics-A1, Radiomics-Delta demonstrated superior performance. Moreover, the hybrid model incorporating Radiomics-Delta and radiological features exhibited excellent performance in determining the LVI status in cases of invasive breast cancer.

Clinically node-negative invasive lobular carcinoma of the breast showing multiple lymph node metastases

A 73-year-old woman was pointed out of her right breast tumor on screening computed tomography (CT). Mammography showed distortion of the mammary gland and skin retraction. Ultrasound (US) showed an irregular tumor with hyperechoic haloes adjacent to the anterior tumor borders. Neither lymphadenopathy nor image findings suggesting lymph node metastasis were detected on US and CT. Core needle biopsy pathologically showed the tumor to be invasive lobular carcinoma. Under the preoperative diagnosis of node-negative breast cancer, the patient underwent mastectomy and sentinel node biopsy. Due to no sentinel node detection, a small but hard lymph node was identified and submitted for frozen section as a sampling node. After confirming the lymph node metastasis on frozen section, axillary lymph node dissection revealed 12 lymph node metastases. Postoperative pathological study showed cancer cell infiltration to the dermis near the nipple-areolar complex. In addition, immmunostaining showed the tumor to have low proliferative biology, i.e., Ki-67 labelling index of 10%. Breast surgeons should note that indolent invasive lobular carcinoma with cancer cell infiltration to the skin near the nipple-areolar complex can have multiple lymph node metastases even though showing neither lymphadenopathy nor image findings suggesting lymph node metastasis.

Machine learning based on optimal VOI of multi-sequence MR images to predict lymphovascular invasion in invasive breast cancer

Objectives

Lymphovascular invasion serves as a crucial prognostic indicator in invasive breast cancer, influencing treatment decisions. We aimed to develop a machine learning model utilizing optimal volumes of interest extracted from multisequence magnetic resonance images to predict lymphovascular invasion in patients with invasive breast cancer.

Materials and methods

This study comprised 191 patients postoperatively diagnosed with invasive breast cancer through multi-sequence magnetic resonance imaging. Independent predictors were identified through univariate and multivariate logistic regression analyses, culminating in the construction of a clinical model. Radiomic features were extracted from multi-sequence magnetic resonance imaging images across various volume of interest scales (-2 mm, entire, +2 mm, +4 mm, and +6 mm). Subsequently, various radiomic models were developed using machine learning model algorithms, including logistic regression, support vector machine, k-nearest neighbor, gradient boosting machine, classification and regression tree, and random forest. A hybrid model was then formulated, amalgamating optimal radiomic and clinical models.

Results

The area under the curve of the clinical model was 0.757. Among the radiomic models, the most efficient diagnosis was achieved by the k-nearest neighbor-based radiomics-volume of interest (+2 mm), resulting in an area under the curve of 0.780. The hybrid model, integrating the k-nearest neighbor-based radiomics-volume of interest (+2 mm), and the clinical model surpassed the individual clinical and radiomics models, exhibiting a superior area under the curve of 0.864.

Conclusion

Utilizing a hybrid approach integrating clinical data and multi-sequence magnetic resonance imaging-derived radiomics models based on the multiscale tumor region volume of interest (+2 mm) proved effective in determining lymphovascular invasion status in patients with invasive breast cancer. This innovative methodology may offer valuable insights for treatment planning and disease management.

Review on Lymph Node Metastases, Sentinel Lymph Node Biopsy, and Lymphadenectomy in Sarcoma

Soft tissue sarcomas (STS) originating from connective tissue rarely affect the lymph nodes. However, involvement of lymph nodes in STS is an important aspect of prognosis and treatment. Currently, there is no consensus on the diagnosis and management of lymph node metastases in STS. The key risk factor for nodal involvement is the histological subtype of sarcoma. Radiological and pathological evaluation seems to be the most effective method of assessing lymph nodes in these neoplasms. Thus, sentinel lymph node biopsy (SLNB), which has been shown to be valuable in the management of melanoma or breast cancer, may also be a beneficial diagnostic option in some high-risk STS subtypes. This review summarizes data on the risk factors and clinical characteristics of lymph node involvement in STS. Possible management and therapeutic options are also discussed.

Diagnostic accuracy of pre-operative breast magnetic resonance imaging (MRI) in predicting axillary lymph node metastasis: variations in intrinsic subtypes, and strategy to improve negative predictive value-an analysis of 2473 invasive breast cancer patients

BACKGROUND

The value and utility of axillary lymph node (ALN) evaluation with MRI in breast cancer were not clear for various intrinsic subtypes. The aim of the current study is to test the potential of combining breast MRI and clinicopathologic factors to identify low-risk groups of ALN metastasis and improve diagnostic performance.

MATERIAL AND METHODS

Patients with primary operable invasive breast cancer with pre-operative breast MRI and post-operative pathologic reports were retrospectively collected from January 2009 to December 2021 in a single institute. The concordance of MRI and pathology of ALN status were determined, and also analyzed in different intrinsic subtypes. A stepwise strategy was designed to improve MRI-negative predictive value (NPV) on ALN metastasis.

RESULTS

2473 patients were enrolled. The diagnostic performance of MRI in detecting metastatic ALN was significantly different between intrinsic subtypes (p = 0.007). Multivariate analysis identified tumor size and histologic type as independent predictive factors of ALN metastases. Patients with HER-2 (MRI tumor size ≤ 2 cm), or TNBC (MRI tumor size ≤ 2 cm) were found to have MRI-ALN-NPV higher than 90%, and these false cases were limited to low axillary tumor burden.

CONCLUSION

The diagnostic performance of MRI to predict ALN metastasis varied according to the intrinsic subtype. Combined pre-operative clinicopathologic factors and intrinsic subtypes may increase ALN MRI NPV, and further identify some groups of patients with low risks of ALN metastasis, high NPV, and low burdens of axillary disease even in false-negative cases.

The prognostic value of the histological shape of tumor negative sentinel nodes in breast cancer

Introduction

Sentinel lymph node (SLN) metastasis is an important predictor of prognosis in breast cancer (BC) patients, guiding treatment decisions. However, patients with the same BC subtype and tumor negative SLN (SLNneg) can have different survival outcomes. We hypothesized that the host anti-tumor immune reaction in SLNneg is important and results in morphometrically measurable changes in SLN size or shape which are related to patient prognosis.

Methods

Surface area, circumference, long axis and short axis were histologically measured in 694 SLNneg from 356 cases of invasive BC and 67 ductal carcinoma in situ cases. The area occupied by fat was categorized as less or more than 50%. The long to short axis (L/S) ratio was calculated. The relationship between SLNneg morphometries and clinicopathological variables like tumor-infiltrating lymphocytes (TILs) within the primary tumor, as well as prognosis at 10 years follow up were analyzed.

Results

The mean SLNneg surface area was 78.7mm2, circumference 40.3mm, long axis 13.1mm, short axis 8.2mm and L/S ratio 1.7. Larger surface area, long axis and short axis, including age >55 years were associated with higher body mass index (BMI) and SLN fat over 50% (p<0.003). In invasive BC, a high SLNneg L/S ratio (≥1.9) was related to poorer disease-free (HR=1.805, 95%CI 1.182-2.755, p=0.006) and overall (HR=2.389, 95%CI 1.481-3.851, p<0.001) survival. A low SLNneg L/S ratio (<1.9) was associated with high TILs in the primary BC (≥10%) (p=0.005). However a high TIL count was not of prognostic relevance.

Conclusions

This is the first study to suggest that morphometric characteristics of axillary SLNneg, like L/S ratio, could be used to predict prognosis in patients with SLNneg invasive BC of all subtypes. The association between low L/S ratio and high TILs suggest that SLN shape is related to immunological functioning of the SLN and could be used in addition to TIL evaluation. Regarding the dubious role of TILs in hormone receptor positive breast cancer, SLNneg morphometry to gain information about host immune status could especially be of benefit in this subtype. Further studies are warranted to better understand the underlying biological mechanisms.

Prediction of Residual Axillary Nodal Metastasis Following Neoadjuvant Chemotherapy for Breast Cancer: Radiomics Analysis Based on Chest Computed Tomography

OBJECTIVE

To evaluate the diagnostic performance of chest computed tomography (CT)-based qualitative and radiomics models for predicting residual axillary nodal metastasis after neoadjuvant chemotherapy (NAC) for patients with clinically node-positive breast cancer.

MATERIALS AND METHODS

This retrospective study included 226 women (mean age, 51.4 years) with clinically node-positive breast cancer treated with NAC followed by surgery between January 2015 and July 2021. Patients were randomly divided into the training and test sets (4:1 ratio). The following predictive models were built: a qualitative CT feature model using logistic regression based on qualitative imaging features of axillary nodes from the pooled data obtained using the visual interpretations of three radiologists; three radiomics models using radiomics features from three (intranodal, perinodal, and combined) different regions of interest (ROIs) delineated on pre-NAC CT and post-NAC CT using a gradient-boosting classifier; and fusion models integrating clinicopathologic factors with the qualitative CT feature model (referred to as clinical-qualitative CT feature models) or with the combined ROI radiomics model (referred to as clinical-radiomics models). The area under the curve (AUC) was used to assess and compare the model performance.

RESULTS

Clinical N stage, biological subtype, and primary tumor response indicated by imaging were associated with residual nodal metastasis during the multivariable analysis (all P < 0.05). The AUCs of the qualitative CT feature model and radiomics models (intranodal, perinodal, and combined ROI models) according to post-NAC CT were 0.642, 0.812, 0.762, and 0.832, respectively. The AUCs of the clinical-qualitative CT feature model and clinical-radiomics model according to post-NAC CT were 0.740 and 0.866, respectively.

CONCLUSION

CT-based predictive models showed good diagnostic performance for predicting residual nodal metastasis after NAC. Quantitative radiomics analysis may provide a higher level of performance than qualitative CT features models. Larger multicenter studies should be conducted to confirm their performance.

Diagnostic Usefulness of Diffusion-Weighted MRI for Axillary Lymph Node Evaluation in Patients with Breast Cancer

This study aimed to determine whether apparent diffusion coefficient (ADC) and morphological features on diffusion-weighted MRI (DW-MRI) can discriminate metastatic axillary lymph nodes (ALNs) from benign in patients with breast cancer. Two radiologists measured ADC, long and short diameters, long-to-short diameter ratio, and cortical thickness and assessed eccentric cortical thickening, loss of fatty hilum, irregular margin, asymmetry in shape or number, and rim sign of ALNs on DW-MRI and categorized them into benign or suspicious ALNs. Pathologic reports were used as a reference standard. Statistical analysis was performed using the Mann-Whitney U test and chi-square test. Overall sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy of DW-MRI were calculated. The ADC of metastatic ALNs was 0.905 × 10^-3 mm²/s, and that of benign ALNs was 0.991 × 10^-3 mm²/s (p = 0.243). All morphologic features showed significant difference between the two groups. The sensitivity, specificity, PPV, NPV, and diagnostic accuracy of the final categorization on DW-MRI were 77.1%, 93.3%, 79.4%, 92.5%, and 86.2%, respectively. Our results suggest that morphologic evaluation of ALNs on DWI can discriminate metastatic ALNs from benign. The ADC value of metastatic ALNs was lower than that of benign nodes, but the difference was not statistically significant.

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.

Multiple-parameter MRI after neoadjuvant systemic therapy combining clinicopathologic features in evaluating axillary pathologic complete response in patients with clinically node-positive breast cancer

OBJECTIVE

This study aimed to evaluate axillary pathologic complete response (pCR) after neoadjuvant systemic therapy (NST) in clinically node-positive breast cancer (BC) patients based on post-NST multiple-parameter MRI and clinicopathological characteristics.

METHODS

In this retrospective study, females with clinically node-positive BC who received NST and followed by surgery between January 2017 and September 2021 were included. All axillary lymph nodes (ALNs) on MRI were matched with pathology by ALN markers or sizes. MRI morphological parameters, signal intensity curve (TIC) patterns and apparent diffusion coefficient (ADC) values of post-NST ALNs were measured. The clinicopathological characteristics was also collected and analyzed. Univariable and multivariable logistic regression analyses were performed to evaluate the independent predictors of axillary pCR.

RESULTS

Pathologically confirmed 137 non-pCR ALNs in 71 patients and 87 pCR ALNs in 87 patients were included in this study. Cortical thickness, fatty hilum, and TIC patterns of ALNs, hormone receptor, and human epidermal growth factor receptor 2 (HER2) status were significantly different between the two groups (all, p < 0.05). There was no significant difference for ADC values (p = 0.875). On multivariable analysis, TIC patterns (odds ratio [OR], 2.67, 95% confidence interval [CI]: 1.33, 5.34, p = 0.006), fatty hilum (OR, 2.88, 95% CI:1.39, 5.98, p = 0.004), hormone receptor (OR, 8.40, 95% CI: 2.48, 28.38, p = 0.001) and HER2 status (OR, 8.57, 95% CI: 3.85, 19.08, p < 0.001) were identified as independent predictors associated with axillary pCR. The area under the curve of the multivariate analysis using these predictors was 0.85 (95% CI: 0.79, 0.91).

CONCLUSION

Combining post-NST multiple-parameter MRI and clinicopathological characteristics allowed more accurate identification of BC patients who had received axillary pCR after NST.

ADVANCES IN KNOWLEDGE

A combined model incorporated multiple-parameter MRI and clinicopathologic features demonstrated good performance in evaluating axillary pCR preoperatively and non-invasively.

What's in a node? The clinical and radiologic significance of Virchow's node

In 1848, Rudolf Ludwig Karl Virchow described an association of left supraclavicular lymphadenopathy with abdominal malignancy. The left supraclavicular lymph node later became commonly referred to as Virchow's node. Charles-Emile Troisier went on to describe the physical exam finding of an enlarged left supraclavicular lymph node, later termed Troisier's sign. Subsequent studies confirmed a predilection of abdominal and pelvic malignancies to preferentially metastasize to the left supraclavicular node. Identification of a pathologically enlarged left supraclavicular node raises the suspicion for abdominopelvic malignancy, particularly in the absence of right supraclavicular lymphadenopathy, and provides a safe and easy target for biopsy. Supraclavicular lymph nodes also represent a great target for diagnosis of metastatic thoracic malignancies, although thoracic malignancies can involve either right or left supraclavicular nodes and do not show a predilection for either. This article presents a review of the history, anatomy, pathophysiology, clinical significance, radiological appearance, and biopsy of Virchow's node. Key points are illustrated with relevant cases.

The impact of body mass index (BMI) on MRI diagnostic performance and surgical management for axillary lymph node in breast cancer

Background

We hypothesized that different BMI might have different impact on pre-operative MRI axillary lymph node (ALN) prediction accuracy and thereby subsequent surgical lymph node management. The aim of this study is to evaluate the effect of BMI on presentation, surgical treatment, and MRI performance characteristics of breast cancer with the main focus on ALN metastasis evaluation.

Methods

The medical records of patients with primary invasive breast cancer who had pre-operative breast MRI and underwent surgical resection were retrospectively reviewed. They were categorized into 3 groups in this study: underweight (BMI < 18.5), normal (BMI of 18.5 to 24), and overweight (BMI > 24). Patients’ characteristics, surgical management, and MRI performance for axillary evaluation between the 3 groups were compared.

Results

A total of 2084 invasive breast cancer patients with a mean age of 53.4 ± 11.2 years were included. Overweight women had a higher rate of breast conserving surgery (56.7% vs. 54.5% and 52.1%) and initial axillary lymph node dissection (15.9% vs. 12.2% and 8.5%) if compared to normal and underweight women. Although the post-operative ALN positive rates were similar between the 3 groups, overweight women were significantly found to have more axillary metastasis on MRI compared with normal and underweight women (50.2% vs 37.7% and 18.3%). There was lower accuracy in terms of MRI prediction in overweight women (65.1%) than in normal and underweight women (67.8% and 76.1%).

Conclusion

Our findings suggest that BMI may influence the diagnostic performance on MRI on ALN involvement and the surgical management of the axilla in overweight to obese women with breast cancer.

Prediction of the number of metastatic axillary lymph nodes in breast cancer by radiomic signature based on dynamic contrast-enhanced MRI

BACKGROUND

The number of metastatic axillary lymph nodes (ALNs) play a crucial role in the staging, prognosis and therapy of patients with breast cancer.

PURPOSE

To predict the number of metastatic ALNs in breast cancer via radiomics.

MATERIAL AND METHODS

We enrolled 197 patients with breast cancer who underwent dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). A total of 3386 radiomic features were extracted from the early- and delayed-phase subtraction images. To classify the number of metastatic ALNs, logistic regression was used to develop a radiomic signature and nomogram.

RESULTS

The radiomic signature were constructed to distinguish the N₀ group from the N₊ (metastatic ALNs ≥ 1) group, which yielded area under the curve (AUC) values of 0.82 and 0.81 in the training and test group, respectively. Based on the radiomic signature and BI-RADS category, a nomogram was further developed and showed excellent predictive performance with AUC values of 0.85 and 0.89 in the training and test groups, respectively. Another radiomic signature was constructed to distinguish the N₁ (1-3 ALNs) group from the N_2-3 (≥4 metastatic ALNs) group and showed encouraging performance with AUC values of 0.94 and 0.84 in training and test group, respectively.

CONCLUSIONS

We developed a nomogram and a radiomic signature that can be used to predict ALN metastasis and distinguish the N₁ from the N_2-3 group. Both nomogram and radiomic signature may be potential tools to assist clinicians in assessing ALN metastasis in patients with breast cancer.

Added Value of MRI for Invasive Breast Cancer including the Entire Axilla for Evaluation of High-Level or Advanced Axillary Lymph Node Metastasis in the Post-ACOSOG Z0011 Trial Era

Background In the post-American College of Surgeons Oncology Group Z0011 trial era, radiologists have increasingly focused on excluding high-level or advanced axillary lymph node metastasis (ALNM) by using an additional MRI scan positioned higher than lower axillae; however, the value of these additional scans remains undetermined. Purpose To evaluate whether a standard MRI protocol is sufficient to exclude high-level or advanced ALNM in breast cancer or additional MRI of entire axilla is needed. Materials and Methods This retrospective study evaluated women with invasive breast cancer who underwent breast MRI from April 2015 to December 2016. Some underwent neoadjuvant chemotherapy (NAC) and others underwent upfront surgery. Standard (routine axial scans including the lower axillae) and combined (routine axial scans plus additional scans including the entire axilla) MRI protocols were compared for high-level or advanced ALNM detection. Clinical-pathologic characteristics were analyzed. Uni- and multivariable logistic regression was performed to identify predictors of high-level or advanced ALNM. Results A total of 435 women (mean age ± standard deviation, 52 years ± 11) were evaluated (65 in the NAC group, 370 in the non-NAC group). With the standard MRI protocol, predictors of high-level ALNM were peritumoral edema (odds ratio [OR], 12.3; 95% CI: 3.9, 39.4; P < .001) and positive axilla (OR, 5.9; 95% CI: 2.0, 15.2; P < .001). Only three of 289 women with negative axillae without peritumoral edema had high-level ALNM. Predictors of advanced ALNM were positive axillae (OR, 8.9; 95% CI: 3.7, 21.5; P < .001) and peritumoral edema (OR, 2.8; 95% CI: 1.1, 6.9; P = .03). Only six of 310 women who had negative axillae without peritumoral edema had advanced ALNM. Conclusion The performance of standard MRI was satisfactory in excluding high-level and advanced axillary lymph node metastasis in most patients with breast cancer. However, the presence of peritumoral edema or positive axillae in the MRI findings emphasizes the benefits of a combined MRI protocol. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Abe in this issue.

Radiomics Nomogram of DCE-MRI for the Prediction of Axillary Lymph Node Metastasis in Breast Cancer

Purpose

This study aimed to establish and validate a radiomics nomogram based on dynamic contrast-enhanced (DCE)-MRI for predicting axillary lymph node (ALN) metastasis in breast cancer.

Method

This retrospective study included 296 patients with breast cancer who underwent DCE-MRI examinations between July 2017 and June 2018. A total of 396 radiomics features were extracted from primary tumor. In addition, the least absolute shrinkage and selection operator (LASSO) algorithm was used to select the features. Radiomics signature and independent risk factors were incorporated to build a radiomics nomogram model. Calibration and receiver operator characteristic (ROC) curves were used to confirm the performance of the nomogram in the training and validation sets. The clinical usefulness of the nomogram was evaluated by decision curve analysis (DCA).

Results

The radiomics signature consisted of three ALN-status-related features, and the nomogram model included the radiomics signature and the MR-reported lymph node (LN) status. The model showed good calibration and discrimination with areas under the ROC curve (AUC) of 0.92 [95% confidence interval (CI), 0.87-0.97] in the training set and 0.90 (95% CI, 0.85-0.95) in the validation set. In the MR-reported LN-negative (cN0) subgroup, the nomogram model also exhibited favorable discriminatory ability (AUC, 0.79; 95% CI, 0.70-0.87). DCA findings indicated that the nomogram model was clinically useful.

Conclusions

The MRI-based radiomics nomogram model could be used to preoperatively predict the ALN metastasis of breast cancer.

[Comparative imaging study of mediastinal lymph node from pre-surgery dual energy CT versus post-surgeron verifications in non-small cell lung cancer patients]

OBJECTIVE

To validate the value of dual energy CT (DECT) in the differentiation of mediastinal metastatic lymph nodes from non-metastatic lymph nodes in non-small cell lung cancer (NSCLC).

METHODS

In the study, 57 surgically confirmed NSCLC patients who underwent enhanced DECT scan within 2 weeks before operation were enrolled. Two radiologists analyzed the CT images before operation. All mediastinal lymph nodes with short diameter≥5 mm on axial images were included in this study. The morphological parameters [long-axis diameter (L), short-axis diameter (S) and S/L of lymph nodes] and the DECT parameters [iodine concentration (IC), normalized iodine concentration (NIC), slope of spectral hounsfield unit curve (λHU) and effective atomic number (Zeff) in arterial and venous phase] were measured. The differences of morphological parameters and DECT parameters between metastatic and non-metastatic lymph nodes were compared. The parameters with significant difference were analyzed by the Logistic regression model, then a new predictive variable was established. Receiver operator characteristic (ROC) analyses were performed for S, NIC in venous phase and the new predictive variable.

RESULTS

In 57 patients, 49 metastatic lymph nodes and 938 non-metastatic lymph nodes were confirmed by surgical pathology. A total of 163 mediastinal lymph nodes (49 metastatic, 114 non-metastatic) with S≥5 mm were detected on axial CT images. The S, L and S/L of metastatic lymph nodes were significantly higher than those of non-metastatic lymph nodes (P < 0.05). The DECT parameters of metastatic lymph nodes were significantly lower than those of non-metastatic lymph nodes (P < 0.05). The best single morphological parameter for differentiation between metastatic and nonmetastatic lymph nodes was S (AUC, 0.752; threshold, 8.5 mm; sensitivity, 67.4%; specificity, 73.7%; accuracy, 71.8%). The best single DECT parameter for differentiation between metastatic and nonmetastatic lymph nodes was NIC in venous phase (AUC, 0.861; threshold, 0.53; sensitivity, 95.9%; specificity, 70.2%; accuracy, 77.9%). Multivariate analysis showed that S and NIC were independent predictors of lymph node metastasis. The AUC of combined S and NIC in the venous phase was 0.895(sensitivity, 79.6%; specificity, 87.7%; accuracy, 85.3%), which were significantly higher than that of S (P < 0.001) and NIC (P=0.037).

CONCLUSIONS

The ability of quantitative DECT parameters to distinguish mediastinal lymph node metastasis in NSCLC patients is better than that of morphological parameters. Combined S and NIC in venous phase can be used to improve preoperative diagnostic accuracy of metastatic lymph nodes.

Textural Characteristics of Biopsy-proven Metastatic Axillary Nodes on Preoperative Breast MRI in Breast Cancer Patients: A Feasibility Study

OBJECTIVE

To determine the diagnostic accuracy of MRI textural analysis (TA) to differentiate malignant from benign axillary lymph nodes in patients with breast cancer.

METHODS

This was an institutional review board-approved retrospective study of axillary lymph nodes in women with breast cancer that underwent ultrasound-guided biopsy and contrast-enhanced (CE) breast MRI from January 2015 to December 2018. TA of axillary lymph nodes was performed on 3D dynamic CE T1-weighted fat-suppressed, 3D delayed CE T1-weighted fat-suppressed, and T2-weighted fat-suppressed MRI sequences. Quantitative parameters used to measure TA were compared with pathologic diagnoses. Areas under the curve (AUC) were calculated using receiver operating characteristic curve analysis to distinguish between malignant and benign lymph nodes.

RESULTS

Twenty-three biopsy-proven malignant lymph nodes and 24 benign lymph nodes were analyzed. The delayed CE T1-weighted fat-suppressed sequence had the greatest ability to differentiate malignant from benign outcome at all spatial scaling factors, with the highest AUC (0.84-0.93), sensitivity (0.78 [18/23] to 0.87 [20/23]), and specificity (0.76 [18/24] to 0.88 [21/24]). Kurtosis on the 3D delayed CE T1-weighted fat-suppressed sequence was the most prominent TA parameter differentiating malignant from benign lymph nodes (P < 0.0001).

CONCLUSION

This study suggests that MRI TA could be helpful in distinguishing malignant from benign axillary lymph nodes. Kurtosis has the greatest potential on 3D delayed CE T1-weighted fat-suppressed sequences to distinguish malignant and benign lymph nodes.

Diagnostic performance of standard breast MR imaging compared to dedicated axillary MR imaging in the evaluation of axillary lymph node

BACKGROUND

Breast magnetic resonance (MR) imaging does not usually assess axillary lymph nodes -using dedicated axillary sequence. The additional utility of dedicated axillary sequence is poorly understood. We evaluated the diagnostic performance of dedicated axillary imaging sequence for evaluation of axillary lymph node.

METHODS

In this retrospective study from January 2018 to March 2018, 750 consecutive women underwent breast MR imaging. 263 patients were excluded, due to neoadjuvant chemotherapy (n = 235), incomplete histopathological information (n = 14) and follow-up loss (n = 14), 487 women were included. Two radiologists scored lymph node on confidence level scale from 0 (definitely benign) to 4 (definitely malignant), -using standard MR and dedicated axillary imaging sequences. Diagnostic performance parameters were compared and calculated correlation coefficient of quantitative features (largest dimension, cortical thickness, and the ratio of cortical thickness to largest dimension of lymph node).

RESULTS

68 (14.0%) were node-positive and 419 (86.0%) were node-negative. The sensitivity, specificity, positive, negative predictive values and accuracy were respectively, 66.2, 93.3, 61.6, 94.4, and 89.5% for dedicated axillary sequence and 64.7, 94.0, 63.8, 94.3, 89.9% for standard MR sequence The dedicated axillary and standard sequences s did not exhibit significant differences in detection of positive lymph nodes (AUC, 0.794 for standard and 0.798 for dedicated axillary sequence, P = 0.825). The cortical thickness appeared to be the most discriminative quantitative measurement using both axillary (AUC, 0.846) and standard sequences (AUC, 0.823), with high correlation coefficient (0.947).

CONCLUSION

Evaluation of axillary nodal status using standard breast MR imaging is comparable to dedicated axillary MR imaging.

Diagnostic performance of standard breast MRI compared to dedicated axillary MRI for assessment of node-negative and node-positive breast cancer

Objectives

To investigate whether breast MRI has comparable diagnostic performance as dedicated axillary MRI regarding assessment of node-negative and node-positive breast cancer.

Methods

Forty-seven patients were included. All had undergone both breast MRI and dedicated axillary MRI, followed by surgery. All included breast MRI exams had complete field of view (FOV) of the axillary region. First, unenhanced T2-weighted (T2W) and subsequent diffusion-weighted (DW) images of both MRI exams were independently analyzed by two breast radiologists using a confidence scale and compared to histopathology. ADC values were measured by two researchers independently. Diagnostic performance parameters were calculated on a patient-by-patient basis.

Results

T2W breast MRI had the following diagnostic performance: sensitivity of 50.0% and 62.5%, specificity of 92.3%, PPV of 57.1% and 62.5%, NPV of 90.0% and 92.3%, and AUC of 0.72 for reader 1 and 0.78 for reader 2. T2W dedicated axillary MRI had the following diagnostic performance: sensitivity of 37.5% and 62.5%, specificity of 82.1% and 92.3%, PPV of 44.6% and 50.0%, NPV of 87.8% and 91.4%, and AUC of 0.65 for reader 1 and 0.73 for reader 2. In both evaluations, addition of DW images resulted in comparable diagnostic performance. For both breast MRI and dedicated axillary MRI, there was no significant difference between mean ADC values of benign and malignant lymph nodes.

Conclusions

T2W breast MRI with complete FOV of the axillary region has comparable diagnostic performance as T2W dedicated axillary MRI regarding assessment of node-negative and node-positive breast cancer. Optimization of T2W breast MRI protocol by including a complete FOV of the axillary region can, therefore, be recommended in clinical practice.

Key Points

• Breast MRI with complete field of view of the axillary region has comparable diagnostic performance as dedicated axillary MRI regarding assessment of node-negative and node-positive breast cancer.

• Optimization of breast MRI protocol by including a complete field of view of the axillary region is recommended in clinical practice.

• For both breast MRI and dedicated axillary MRI, DW imaging (including ADC measurements) is of no added value.

Utility of Ultrasound and Mammography in Detection of Negative Axillary Nodal Metastasis in Breast Cancer

Objective The status of axillary lymph nodes is one of the most important prognostic factors in patients with breast cancer. A precise noninvasive evaluation of axillary lymph node status preoperatively, although challenging, is vital for optimization of the treatment plan for patients. The objective of our study was to assess the utility of ultrasound and mammography in detecting the absence of axillary lymph nodal metastasis in patients of breast cancer, taking histopathology as gold standard. Methods A cross-sectional study was conducted in the Department of Radiology, Aga Khan University Hospital, Karachi. All female patients between 20 and 95 years of age with a known diagnosis of breast cancer with mammographic and ultrasound imaging done at our institute were included. Patients with abnormal lymph nodes on mammography or on ultrasound, patients already operated for breast cancer, patients who already underwent axillary lymph node dissection and those whose histopathology reports were not available or who did not undergo surgery were excluded. Results A total of 262 women with breast carcinoma who had both ultrasound and mammography done and also had surgery performed at our institution were included. At final surgical pathology, a total of 45 of the 262 patients (17.2%) with breast carcinoma had one or more positive lymph nodes. Out of the total 262 patients, 217 patients were found to be true negatives as they had absent axillary nodal metastasis on imaging as well as on histopathology. In all, 45 out of 262 patients were found to be false negatives as they had absent axillary nodal metastasis on imaging; however, they were found to be positive for metastasis on histopathology. The negative predictive value was 82.8%. Patient age was considered as a factor that may influence the outcome of results; the patients were stratified into age ranges seven groups with the age range of 10 years, ranging from 26 to 95 years. Chi-square test showed a p-value of 0.148, which showed no significant difference in the effect of age on diagnosing the absence of metastasis by ultrasound and mammography. Conclusion Our study shows that ultrasound and mammography even when used in combination cannot safely exclude axillary metastasis and thus cannot eliminate the need for sentinel 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.

Preoperative prediction of lymphovascular invasion in invasive breast cancer with dynamic contrast-enhanced-MRI-based radiomics

BACKGROUND

Lymphovascular invasion (LVI) status facilitates the selection of optimal therapeutic strategy for breast cancer patients, but in clinical practice LVI status is determined in pathological specimens after resection.

PURPOSE

To explore the use of dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI)-based radiomics for preoperative prediction of LVI in invasive breast cancer.

STUDY TYPE

Prospective.

POPULATION

Ninety training cohort patients (22 LVI-positive and 68 LVI-negative) and 59 validation cohort patients (22 LVI-positive and 37 LVI-negative) were enrolled.

FIELD STRENGTH/SEQUENCE

1.5 T and 3.0 T, T₁ -weighted DCE-MRI.

ASSESSMENT

Axillary lymph node (ALN) status for each patient was evaluated based on MR images (defined as MRI ALN status), and DCE semiquantitative parameters of lesions were calculated. Radiomic features were extracted from the first postcontrast DCE-MRI. A radiomics signature was constructed in the training cohort with 10-fold cross-validation. The independent risk factors for LVI were identified and prediction models for LVI were developed. Their prediction performances and clinical usefulness were evaluated in the validation cohort.

STATISTICAL TESTS

Mann-Whitney U-test, chi-square test, kappa statistics, least absolute shrinkage and selection operator (LASSO) regression, logistic regression, receiver operating characteristic (ROC) analysis, DeLong test, and decision curve analysis (DCA).

RESULTS

Two radiomic features were selected to construct the radiomics signature. MRI ALN status (odds ratio, 10.452; P < 0.001) and the radiomics signature (odds ratio, 2.895; P = 0.031) were identified as independent risk factors for LVI. The value of the area under the curve (AUC) for a model combining both (0.763) was higher than that for MRI ALN status alone (0.665; P = 0.029) and similar to that for the radiomics signature (0.752; P = 0.857). DCA showed that the combined model added more net benefit than either feature alone.

DATA CONCLUSION

The DCE-MRI-based radiomics signature in combination with MRI ALN status was effective in predicting the LVI status of patients with invasive breast cancer before surgery.

LEVEL OF EVIDENCE

1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:847-857.

The use of single-photon emission computed tomography-computed tomography in detecting multiple metastatic lymph nodes in patients with breast cancer

AIM

The aim of the present study was to determine the accuracy of single-photon emission computed tomography-computed tomography (SPECT-CT) with technetium-99m-sestamibi (Tc-MIBI) for detecting multiple (>2 nodes) axillary lymph node involvement in patients with breast cancer (BC).

PATIENTS AND METHODS

A total of 184 women with BC were examined. Clinically, axillary lymph nodes were classified as N0 in all cases. Patients underwent SPECT-CT breast and axillary region imaging 10-15 min after a 740 mBq intravenous injection of Tc-MIBI. SPECT-CT data were then verified by definitive histopathological examination (sentinel-node biopsy and/or axillary lymph node dissection were used as reference standard). Diagnostic values of different CT and SPECT signs of multiple (>2) lymph node involvement were evaluated.

RESULTS

Histological examination of excised lymph nodes showed metastatic involvement in 62 (33.7%) out of 184 patients. In fact, 25 (13.6%) patients had more than two lymph node involvements. In another 37 (20.1%) cases the metastasis was revealed in one or two sentinel lymph nodes only. The main SPECT-CT criteria of multiple (>2) lymph node involvement were as follows: the maximum size of the primary tumor (>20 mm), lymph node dimensions (>12 mm along the long axis and >10 mm along the short axis), nodal cortical thickness (>4 mm), round shape, solid structure, quantity of identified abnormal lymph nodes (>1), and intensity of tracer uptake. The developed integrated model offers the possibility to exclude multiple lymph node metastasis (>2) in BC patients with a probability of 99%.

CONCLUSION

This single-center study showed that in patients with BC, a combination of functional and anatomical data that were obtained by using SPECT-CT with Tc-MIBI can significantly improve detectability of multiple (>2) axillary metastases.

Introduction of a New Staging System of Breast Cancer for Radiologists: An Emphasis on the Prognostic Stage

In 2017, the American Joint Committee on Cancer announced the 8th edition of its cancer staging system. For breast cancer, the most significant change in the staging system is the incorporation of biomarkers into the anatomic staging to create prognostic stages. Different prognostic stages are assigned to tumors with the same anatomic stages according to the tumor grade, hormone receptor (estrogen receptor; progesterone receptor) status, and HER2 status. A Clinical Prognostic Stage is assigned to all patients regardless of the type of therapy used; in contrast, a Pathologic Prognosis Stage is assigned to patients in whom surgery is the initial treatment. In a few situations, low Oncotype DX recurrence scores can change the prognostic stage. The radiologists need to understand the importance of the biologic factors that can influence cancer staging.

Can We Skip Intraoperative Evaluation of Sentinel Lymph Nodes? Nomogram Predicting Involvement of Three or More Axillary Lymph Nodes before Breast Cancer Surgery

Purpose

The American College of Surgeons Oncology Group Z0011 trial reported that complete dissection of axillary lymph nodes (ALNs) may not be warranted in women with clinical T1-T2 tumors and one or two involved ALNs who were undergoing lumpectomy plus radiation followed by systemic therapy. The present study was conducted to identify preoperative imaging predictors of ≥ 3 ALNs.

Materials and Methods

The training set consisted of 1,917 patients with clinical T1-T2 and node negative invasive breast cancer. Factors associated with ≥ 3 involved ALNs were evaluated by logistic regression analysis. The validation set consisted of 378 independent patients. The nomogram was applied prospectively to 512 patients who met the Z0011 criteria.

Results

Of the 1,917 patients, 204 (10.6%) had ≥ 3 positive nodes. Multivariate analysis showed that involvement of ≥ 3 nodes was significantly associated with ultrasonographic and chest computed tomography findings of suspicious ALNs (p < 0.001 each). These two imaging criteria, plus patient age, were used to develop a nomogram calculating the probability of involvement of ≥ 3 ALNs. The areas under the receiver operating characteristic curve of the nomogram were 0.852 (95% confidence interval [CI], 0.820 to 0.883) for the training set and 0.896 (95% CI, 0.836 to 0.957) for the validation set. Prospective application of the nomogram showed that 60 of 512 patients (11.7%) had scores above the cut-off. Application of the nomogram reduced operation time and cost, with a very low re-operation rate (1.6%).

Conclusion

Patients likely to have ≥ 3 positive ALNs could be identified by preoperative imaging. The nomogram was helpful in selective intraoperative examination of sentinel lymph nodes.

Breast Magnetic Resonance Imaging for Assessment of Internal Mammary Lymph Node Status in Breast Cancer

Purpose

The purpose of this study was to assess magnetic resonance imaging (MRI) features of malignant internal mammary lymph nodes (IMLNs) and benign IMLNs in breast cancer patients.

Methods

From 2009 to 2014, the records of 85 patients with IMLNs were archived using MRI report data; 26 patients with small size (long axis diameter <5 mm) nodes were subsequently excluded. The current study evaluated internal mammary lymph nodes in 59 patients who underwent breast MRI for breast cancer staging and for posttherapy follow-up. All MRI findings were retrospectively evaluated. Malignancy was determined based on pathologic examination and positron emission tomography computed tomography findings. Independent t-tests, Mann-Whitney U tests, chi-square tests, and receiver operating characteristics (ROC) curve analysis were used.

Results

Among MRI features, there were statistically significant differences between benign and malignant IMLN groups, in short axis length (3.6±1.3 vs. 8.2±2.9 mm, respectively), long axis length (8.1±2.4 vs. 14.5±4.8 mm, respectively), short/long axis ratio (0.45±0.10 vs. 0.59±0.17, respectively), absent fatty hilum (mean, 0% vs. 95%, respectively), and restricted diffusion (15.8% vs. 85.0%, respectively) (p<0.050). Multiplicity and location of intercostal spaces was not different between the two groups. Short axis length was the most discriminative variable for predicting metastatic nodes (area under the ROC curve, 0.951; threshold, 4 mm; sensitivity, 92.5%; specificity, 84.2%).

Conclusion

Conventional MRI and diffusion-weighted MRI are helpful to detect metastasis of internal mammary lymph nodes in breast cancer.

Preoperative axillary lymph node evaluation in breast cancer patients by breast magnetic resonance imaging (MRI): Can breast MRI exclude advanced nodal disease?

OBJECTIVES

To evaluate the diagnostic performance of breast magnetic resonance imaging (MRI) in preoperative evaluation of axillary lymph node metastasis (ALNM) in breast cancer patients and to assess whether breast MRI can be used to exclude advanced nodal disease.

METHODS

A total of 425 patients were included in this study and breast MRI findings were retrospectively reviewed. The diagnostic performance of breast MRI for diagnosis of ALNM was evaluated in all patients, patients with neoadjuvant chemotherapy (NAC), and those without NAC (no-NAC). We evaluated whether negative MRI findings (cN0) can exclude advanced nodal disease (pN2-pN3) using the negative predictive value (NPV) in each group.

RESULTS

The sensitivity and NPV of breast MRI in evaluation of ALNM was 51.3 % (60/117) and 83.3 % (284/341), respectively. For cN0 cases on MRI, pN2-pN3 manifested in 1.8 % (6/341) of the overall patients, 0.4 % (1/257) of the no-NAC group, and 6 % (5/84) of the NAC group. The NPV of negative MRI findings for exclusion of pN2-pN3 was higher for the no-NAC group than for the NAC group (99.6 % vs. 94.0 %, p = 0.039).

CONCLUSIONS

Negative MRI findings (cN0) can exclude the presence of advanced nodal disease with an NPV of 99.6 % in the no-NAC group.

KEY POINTS

• Breast MRI can be used to exclude advanced nodal disease (pN2-3). • Negative MRI allows breast cancer patients to avoid unnecessary axillary surgery (98.2 %). • Negative MRI findings exclude 99.6 % of pN2-pN3 in the no-NAC group. • Negative MRI findings exclude 96.0 % of pN2-pN3 in the NAC group.

Evaluation of lymph node status after neoadjuvant chemotherapy in breast cancer patients: comparison of diagnostic performance of ultrasound, MRI and ¹⁸F-FDG PET/CT

Objective:

To evaluate the diagnostic performance of ultrasound, MRI and fluorine-18 fludeoxyglucose positron emission tomography (¹⁸F-FDG PET)/CT for the diagnosis of metastatic axillary lymph node (ALN) after neoadjuvant chemotherapy (NAC) and to find out histopathological factors affecting the diagnostic performance of these imaging modalities.

Methods:

From January 2012 to November 2014, 191 consecutive patients with breast cancer who underwent NAC before surgery were retrospectively reviewed. We included 139 patients with ALN metastasis that was confirmed on fine needle aspiration or core needle biopsy at initial diagnosis.

Results:

After NAC, 39 (28%) patients showed negative conversion of ALN on surgical specimens of sentinel lymph node (LN) or ALN. The sensitivity of ultrasound, MRI and PET/CT was 50% (48/96), 72% (70/97) and 22% (16/73), respectively. The specificity of ultrasound, MRI and PET/CT was 77% (30/39), 54% (21/39) and 85% (22/26), respectively. The Az value of combination of ultrasound and PET/CT was the highest (0.634) followed by ultrasound (0.626) and combination of ultrasound, MRI and PET/CT (0.617). The size of tumour deposit in LN and oestrogen receptor was significantly associated with the diagnostic performance of ultrasound (p < 0.001 and p = 0.009, respectively) and MRI (p = 0.045 and p = 0.036, respectively). The percentage diameter decrease, size of tumour deposit in LN, progesterone receptor, HER2 and histological grade were significantly associated with the diagnostic performance of PET/CT (p = 0.023, p = 0.002, p = 0.036, p = 0.044 and p = 0.008, respectively). On multivariate logistic regression analysis, size of tumour deposit within LN was identified as being independently associated with diagnostic performance of ultrasound [odds ratio, 13.07; 95% confidence interval (CI), 2.95–57.96] and PET/CT (odds ratio, 6.47; 95% CI, 1.407–29.737).

Conclusion:

Combination of three imaging modalities showed the highest sensitivity, and PET/CT showed the highest specificity for the evaluation of ALN metastasis after NAC. Ultrasound alone or combination of ultrasound and PET/CT showed the highest positive-predictive value. The size of tumour deposit within ALN was significantly associated with diagnostic performance of ultrasound and PET/CT.

Advances in knowledge:

This study is about the diagnostic performance of ultrasound, MRI, PET/CT and combination of each imaging modality for the evaluation of metastatic ALN after NAC. Of many histopathological factors, only the size of tumour deposit within ALN was an independent factor associated with the diagnostic performance of ultrasound and PET/CT.

Locoregional Recurrence Risk in Breast Cancer Patients with Estrogen Receptor Positive Tumors and Residual Nodal Disease following Neoadjuvant Chemotherapy and Mastectomy without Radiation Therapy

Among breast cancer patients treated with neoadjuvant chemotherapy (NAC) and mastectomy, locoregional recurrence (LRR) rates are unclear in women with ER+ tumors treated with adjuvant endocrine therapy without postmastectomy radiation (PMRT). To determine if PMRT is needed in these patients, we compared LRR rates of patients with ER+ tumors (treated with adjuvant endocrine therapy) with women who have non-ER+ tumors. 85 consecutive breast cancer patients (87 breast tumors) treated with NAC and mastectomy without PMRT were reviewed. Patients were divided by residual nodal disease (ypN) status (ypN+ versus ypN0) and then stratified by receptor subtype. Among ypN+ patients (n = 35), five-year LRR risk in patients with ER+, Her2+, and triple negative tumors was 5%, 33%, and 37%, respectively (p = 0.02). Among ypN+/ER+ patients, lymphovascular invasion and grade three disease increased the five-year LRR risk to 13% and 11%, respectively. Among ypN0 patients (n = 52), five-year LRR risk in patients with ER+, Her2+, and triple negative tumors was 7%, 22%, and 6%, respectively (p = 0.71). In women with ER+ tumors and residual nodal disease, endocrine therapy may be sufficient adjuvant treatment, except in patients with lymphovascular invasion or grade three tumors where PMRT may still be indicated.

The role of MRI in axillary lymph node imaging in breast cancer patients: a systematic review

Objectives

To assess whether MRI can exclude axillary lymph node metastasis, potentially replacing sentinel lymph node biopsy (SLNB), and consequently eliminating the risk of SLNB-associated morbidity.

Methods

PubMed, Cochrane, Medline and Embase databases were searched for relevant publications up to July 2014. Studies were selected based on predefined inclusion and exclusion criteria and independently assessed by two reviewers using a standardised extraction form.

Results

Sixteen eligible studies were selected from 1,372 publications identified by the search. A dedicated axillary protocol [sensitivity 84.7 %, negative predictive value (NPV) 95.0 %] was superior to a standard protocol covering both the breast and axilla simultaneously (sensitivity 82.0 %, NPV 82.6 %). Dynamic, contrast-enhanced MRI had a lower median sensitivity (60.0 %) and NPV (80.0 %) compared to non-enhanced T1w/T2w sequences (88.4, 94.7 %), diffusion-weighted imaging (84.2, 90.6 %) and ultrasmall superparamagnetic iron oxide (USPIO)- enhanced T2*w sequences (83.0, 95.9 %). The most promising results seem to be achievable when using non-enhanced T1w/T2w and USPIO-enhanced T2*w sequences in combination with a dedicated axillary protocol (sensitivity 84.7 % and NPV 95.0 %).

Conclusions

The diagnostic performance of some MRI protocols for excluding axillary lymph node metastases approaches the NPV needed to replace SLNB. However, current observations are based on studies with heterogeneous study designs and limited populations.

Main Messages

• Some axillary MRI protocols approach the NPV of an SLNB procedure.

• Dedicated axillary MRI is more accurate than protocols also covering the breast.

• T1w/T2w protocols combined with USPIO-enhanced sequences are the most promising sequences.

The clinical value of hybrid sentinel lymphoscintigraphy to predict metastatic sentinel lymph nodes in breast cancer

PURPOSE

Hybrid imaging techniques can provide functional and anatomical information about sentinel lymph nodes in breast cancer. Our aim in this study was to evaluate which imaging parameters on hybrid sentinel lymphoscintigraphy predicted metastatic involvement of sentinel lymph nodes (SLNs) in patients with breast cancer.

METHODS

Among 56 patients who underwent conventional sentinel lymphoscintigraphy, 45 patients (age, 53.1 ± 9.5 years) underwent hybrid sentinel lymphoscintigraphy using a single-photon emission computed tomography (SPECT)/computed tomography (CT) gamma camera. On hybrid SPECT/CT images, we compared the shape and size (long-to-short axis [L/S] ratio) of the SLN, and SLN/periareolar injection site (S/P) count ratio between metastatic and non-metastatic SLNs. Metastatic involvement of sentinel lymph nodes was confirmed by pathological biopsy.

RESULTS

Pathological biopsy revealed that 21 patients (46.7 %) had metastatic SLNs, while 24 (53.3 %) had non-metastatic SLNs. In the 21 patients with metastatic SLNs, the SLN was mostly round (57.1 %) or had an eccentric cortical rim (38.1 %). Of 24 patients with non-metastatic SLNs, 13 patients (54.1 %) had an SLN with a C-shape rim or eccentric cortex. L/S ratio was 2.04 for metastatic SLNs and 2.38 for non-metastatic SLNs. Seven (33 %) patients had T1 primary tumors and 14 (66 %) had T2 primary tumors in the metastatic SLN group. In contrast, 18 (75 %) patients had T1 primary tumors and six (25 %) had T2 tumors in the non-metastatic SLN group. S/P count ratio was significantly lower in the metastatic SLN group than the non-metastatic SLN group for those patients with a T1 primary tumor (p = 0.007).

CONCLUSIONS

Hybrid SPECT/CT offers the physiologic data of SPECT together with the anatomic data of CT in a single image. This hybrid imaging improved the anatomic localization of SLNs in breast cancer patients and predicted the metastatic involvement of SLNs in the subgroup of breast cancer patients with T1 primary tumors.

Role of diffusion-weighted MRI: predicting axillary lymph node metastases in breast cancer

BACKGROUND

Ultrasound (US) is probably the standard imaging procedure in most centers, and US-guided fine needle aspiration can be added if suspicious lymph nodes are found. However, US-guided fine needle aspiration is an invasive method to diagnose a metastasis and has showed relatively low sensitivity. In general, diffusion-weighted (DW) magnetic resonance imaging (MRI) has become an emerging technique for discriminating benign from malignant breast lesions in a short imaging acquisition time.

PURPOSE

To evaluate the potential for using DW MRI with an apparent diffusion coefficient (ADC) value to predict axillary lymph node metastases in patients with invasive breast cancer.

MATERIAL AND METHODS

This study enrolled 110 axillary lymph nodes from 110 consecutive women who were diagnosed with invasive breast cancer for preoperative breast MRI and US. The largest enhancing ipsilateral axillary lymph nodes were included in this study, and benign and metastatic axillary lymph nodes were compared according to the pathologic reports. The cut-off ADC value to differentiate between benign and metastatic axillary lymph nodes was evaluated with receiver-operating characteristic curve analysis. Diagnostic performance of ultrasound and DW MRI was calculated for enhancing lymph node in dynamic contrast-enhanced MRI.

RESULTS

Nodal metastases were documented in 68 (62%) axillary lymph nodes. The mean size of metastatic axillary lymph nodes was larger than that of benign axillary lymph nodes (15.5 mm vs. 10.9 mm, P < 0.001). The mean ADC value (0.69 × 10(-3 )mm(2)/s) of the metastases was significantly lower than that of the benign axillary lymph nodes (1.04 × 10(-3 )mm(2)/s) (P < 0.001). The ADC value cut-off between metastatic and benign axillary lymph nodes was 0.90 × 10(-3 )mm(2)/s. Using ADC cut-off, sensitivity, specificity, and accuracy of DW MRI were 100%, 83.3%, and 93.6%, respectively. The sensitivity, specificity, and accuracy of US showed 94.1%, 54.8%, and 79.1%, respectively.

CONCLUSION

DW MRI of axillary lymph nodes can provide reliable information for the differentiation of benign from metastatic axillary lymph nodes in invasive breast cancer patients.

Diagnostic value of breast MRI for predicting metastatic axillary lymph nodes in breast cancer patients: diffusion-weighted MRI and conventional MRI

PURPOSES

To evaluate the diagnostic value of diffusion-weighted MRI (DWI) and combination of conventional MRI and DWI to predict metastatic axillary lymph nodes in breast cancer.

MATERIALS AND METHODS

Two hundred fifty-two breast cancer patients with 253 axillae were included. The morphological parameters on axial T2-weighted images without fat saturation and apparent diffusion coefficient (ADC) values were retrospectively analyzed. An independent t-test/chi-square test and receiver operating characteristics (ROC) curve analysis were used.

RESULTS

On conventional MRI, short and long axis length, maximal cortical thickness, relative T2 value, loss of fatty hilum (p<0.001 for each), and eccentric cortical thickening (p<0.003) were statistically significantly different between the metastatic and nonmetastatic groups. The short axis to long axis ratio was not a statistically significant parameter. The ADC value was significantly different between the 2 groups, with an AUC that was higher than that of conventional MR parameters (AUC, 0.815; threshold, ≤0.986×10-3 mm(2)/sec; sensitivity, 75.8%; specificity, 83.9%). Using the adopted thresholds for each parameter, a total number of findings suggesting malignancy of 4 or higher was determined as the threshold, with high specificity (90.1%).

CONCLUSION

Using conventional MRI and DWI, we can evaluate the axilla in breast cancer with high specificity.

Lymph node shape in computed tomography imaging as a predictor for axillary lymph node metastasis in patients with breast cancer

The aim of the present study was to evaluate whether preoperative computed tomography (CT) is a useful modality for the diagnosis of axillary lymph node metastasis. The axillary lymph node status was examined in patients with primary breast cancer who had undergone surgery. In total, 75 patients were analyzed with preoperative contrast CT images, following which the patients underwent an intraoperative sentinel lymph node biopsy to determine possible predictors of axillary lymph node metastasis. The lymph node shape was classified into three groups, which included fat-, clear-and obscure-types. Multivariate analysis revealed that clear-type lymph nodes in preoperative contrast CT imaging may be an independent predictor of lymph node metastasis (odds ratio, 15; P=0.003). Therefore, the results indicated that preoperative CT examination is useful to predict axillary lymph node metastasis.

Discrimination of benign and malignant lymph nodes at 7.0T compared to 1.5T magnetic resonance imaging using ultrasmall particles of iron oxide: a feasibility preclinical study

RATIONALE AND OBJECTIVES

To investigate the feasibility and performance of 7T magnetic resonance imaging compared to 1.5T imaging to discriminate benign (normal and inflammatory changed) from tumor-bearing lymph nodes in rabbits using ultrasmall particles of iron oxide (USPIO)-based contrast agents.

MATERIALS AND METHODS

Six New Zealand White rabbits were inoculated with either complete Freund's adjuvant cell suspension (n = 3) to induce reactively enlarged lymph nodes or with VX2 tumor cells to produce metastatic lymph nodes (n = 3). Image acquisition was performed before and 24 hours after bolus injection of an USPIO contrast agent at 1.5T and afterward at 7T using T1-weighted and T2*-weighted sequences. Sensitivities, specificities, and negative and positive predictive values for the detection of lymph node metastases were calculated for both field strengths with histopathology serving as reference standard. Sizes of lymph nodes with no, inflammatory, and malignant changes were compared using a Mann-Whitney U-test.

RESULTS

All 24 lymph nodes were detected at 1.5T as well as at 7T. At 1.5T, sensitivity amounted to 0.67, while specificity reached a value of 1. At the higher field strength (7T), imaging was able to reach sensitivity and specificity values of 1. No statistical differences were detected concerning lymph node sizes.

CONCLUSIONS

Magnetic resonance lymphography with USPIO contrast agents allows for differentiation of normal and reactively enlarged lymph nodes compared to metastatic nodes. First experiments at 7T show promising results compared to 1.5T, which have to be evaluated in further trials.

Diagnostic performance of 18F-FDG PET/CT, ultrasonography and MRI. Detection of axillary lymph node metastasis in breast cancer patients

The aim of this study was to evaluate the diagnostic abilities of 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography(PET/CT) compared with those of ultrasonography and magnetic resonance imaging (MRI) for axillary lymph node staging in breast cancer patients.

PATIENTS, METHODS

Preoperative 18F-FDG PET/non-contrast CT, ultrasonography and MRI were performed in 215 women with breast cancer. Axillary lymph node dissection was performed in all patients and the diagnostic performance of each modality was evaluated using histopathologic assessments as the reference standard. ROC curves were compared to evaluate the diagnostic ability of several imaging modalities (i. e., ultrasonography, MRI and 18F-FDG PET/CT).

RESULTS

In total, 132 patients (61.4%) had axillary lymph node metastasis. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy for the detection of axillary lymph node metastasis were 72.3%, 77.3%, 66.7%, 81.6%, 75.3% for ultrasonography, 67.5%, 78.0%, 65.9%, 79.2%, 74.0% for MRI, and 62.7%, 88.6%, 77.6%, 79.1%, 78.6% for 18F-FDG PET/CT, respectively. There was no significant difference in diagnostic ability among the imaging modalities (i.e., ultrasonography, MRI and 18F-FDG PET/CT). The diagnostic ability of 18F-FDG PET/CT was significantly improved by combination with MRI (p = 0.0002) or ultrasonography (p < 0.0001). The combination of 18F-FDG PET/CT with ultrasonography had a similar diagnostic ability to that of all three modalities combined (18F-FDG PET/CT+ultrasonography+MRI, p = 0.05).

CONCLUSION

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

Comparison of two different iron oxide-based contrast agents for discrimination of benign and malignant lymph nodes

OBJECTIVES

The aim of this study was to investigate the performance of 2 different ultrasmall superparamagnetic iron oxide particles-based contrast agents for intravascular magnetic resonance lymphography in normal, inflammatory, and tumor-bearing lymph nodes in rabbits.

MATERIALS AND METHODS

Two USPIO agents were assessed: Sinerem and P904 (both Guerbet Research, Aulnay-sous-Bois, France). Signal change of popliteal and paraaortic lymph nodes were studied in VX-2 tumor-bearing rabbits (n = 4) and rabbits in whom complete Freund adjuvant had been applied (n = 6). Image acquisition was performed before and 5 to 120 minutes and 24 hours after bolus injection of Sinerem (n = 5) and P904 (n = 5). Lymph node size was assessed and signal-to-noise ratios of lymph nodes were calculated. The contrast agents were compared regarding nodal signal changes over time. Furthermore, sensitivities, specificities, and negative and positive predictive values were calculated for both contrast agents, with histopathology serving as the standard of reference.

RESULTS

No statistically significant size differences were detected between normal, reactively enlarged and tumor-infiltrated lymph nodes. Signal change over time showed greater differences between benign and metastatic lymph nodes for P904 especially at 24 hours after injection, whereas Sinerem showed the highest signal loss in benign nodes. After 24 hours, P904 showed a higher sensitivity (0.75 vs 0.67) and higher specificity (1 vs 0.94) compared with Sinerem. At earlier time points, sensitivity for Sinerem was lower (0.33), whereas for P904, sensitivity at 120 minutes was as good as after 24 hours (0.75).

CONCLUSION

Magnetic resonance lymphography with USPIO contrast agents allows for differentiation of reactively enlarged lymph nodes compared with metastatic nodes. P904 yielded higher sensitivity and specificity values, with higher signal differences between benign and malignant enlarged lymph nodes. Furthermore, diagnosis seems to be possible earlier. This agent therefore seems to be a promising tool for staging cancer patient.