Ex vivo MRI of axillary lymph nodes in breast cancer

Investigation of synthetic MRI with quantitative parameters for discriminating axillary lymph nodes status in invasive breast cancer

OBJECTIVE

To investigate the potential value of quantitative parameters derived from synthetic magnetic resonance imaging (syMRI) for discriminating axillary lymph nodes metastasis (ALNM) in breast cancer patients.

MATERIALS AND METHODS

A total of 56 females with histopathologically proven invasive breast cancer who underwent both conventional breast MRI and additional syMRI examinations were enrolled in this study, including 30 patients with ALNM and 26 with non-ALNM. SyMRI has enabled quantification of T1 relaxation time (T1), T2 relaxation time (T2) and proton density (PD). The syMRI quantitative parameters of breast primary tumors before (T1tumor, T2tumor, PDtumor) and after (T1+tumor, T2+tumor, PD+tumor) contrast agent injection were obtained. Similarly, measurements were taken for axillary lymph nodes before (T1LN, T2LN, PDLN) and after (T1+LN, T2+LN, PD+LN) the injection, then theΔT1 (T1-T1+), ΔT2 (T2-T2+), ΔPD (PD-PD+), T1/T2 and T1+/T2+ were calculated. All parameters were compared between ANLM and non-ALNM group. Intraclass correlation coefficient for assessing interobserver agreement. The independent Student's t test or Mann-Whitney U test to determine the relationship between the mean quantitative values and the ALNM. Multivariate logistic regression analyses followed by receiver operating characteristics (ROC) analysis for discriminating ALN status. A P value < 0.05 was considered statistically significant.

RESULTS

The short-diameter of lymph nodes (DLN) in ALNM group was significantly longer than that in the non-ALNM group (10.22 ± 3.58 mm vs. 5.28 ± 1.39 mm, P < 0.001). The optimal cutoff value was determined to be 5.78 mm, with an AUC of 0.894 (95 % CI: 0.838-0.939), a sensitivity of 86.7 %, and a specificity of 90.2 %. In syMRI quantitative parameters of breast tumors, T2tumor, ΔT2tumor and ΔPDtumor values showed statistically significant differences between the two groups (P < 0.05). T2tumor value had the best performance in discriminating ALN status (AUC = 0.712), and the optimal cutoff was 90.12 ms, the sensitivity and specificity were 65.0 % and 83.6 % respectively. In terms of syMRI quantitative parameters of lymph nodes, T1LN, T2LN, T1LN/T2LN, T2+LN and ΔT1LN values were significantly different between the two groups (P < 0.05), and their AUCs were 0.785, 0.840, 0.886, 0.702 and 0.754, respectively. Multivariate analyses indicated that the T1LN value was the only independent predictor of ALNM (OR=1.426, 95 % CI: 1.130-1.798, P = 0.039). The diagnostic sensitivity and specificity of T1LN was 86.7 % and 69.4 % respectively at the best cutoff point of 1371.00 ms. The combination of T1LN, T2LN, T1LN/T2LN, ΔT1LN and DLN had better performance for differentiating ALNM and non-ALNM, with AUCs of 0.905, 0.957, 0.964 and 0.897, respectively.

CONCLUSION

The quantitative parameters derived from syMRI have certain value for discriminating ALN status in invasive breast cancer, with T2tumor showing the highest diagnostic efficiency among breast lesions parameters. Moreover, T1LN acted as an independent predictor of ALNM.

Comparison of Axillary Lymph Nodes on Breast MRI Before and After COVID-19 Booster Vaccination

RATIONALE AND OBJECTIVES

Vaccine-related lymphadenopathy is a frequent finding following initial coronavirus disease 2019 (COVID-19) vaccination, but the frequency after COVID-19 booster vaccination is still unknown. In this study we compare axillary lymph node morphology on breast MRI before and after COVID-19 booster vaccination.

MATERIALS AND METHODS

This retrospective, single-center, IRB-approved study included patients who underwent breast MRI between October 2021 and December 2021 after the COVID-19 booster vaccination. The axillary lymph node with the greatest cortical thickness ipsilateral to the side of vaccination was measured on MRI after booster vaccination and before initial COVID-19 vaccination. Comparisons were made between patients with and without increase in cortical thickness of ≥ 0.2 cm. Continuous covariates were compared using Wilcoxon rank-sum test and categorical covariates were compared using Fisher's exact test. Multiple comparison adjustment was made using the Benjamini-Hochberg procedure.

RESULTS

All 128 patients were included. Twenty-four of 128 (19%) displayed an increase in lymph node cortical thickness of ≥ 0.2 cm. Patients who received the booster more recently were more likely to present cortical thickening, with a median of 9 days (IQR 5, 20) vs. 36 days (IQR 18, 59) (p < 0.001). Age (p = 0.5) and type of vaccine (p = 0.7) were not associated with thickening. No ipsilateral breast cancer or malignant lymphadenopathy were diagnosed on follow-up.

CONCLUSION

Axillary lymphadenopathy on breast MRI following COVID-19 booster vaccination is a frequent finding, especially in the first 3 weeks after vaccination. Additional evaluation or follow-up may be omitted in patients with low concern for malignancy.

Radiomics-based signature of breast cancer on preoperative contrast-enhanced MRI to predict axillary metastasis

Aim: This study aimed to predict axillary metastasis using radiology features in dynamic contrast-enhanced MRI. Methods: This study included 243 breast lesions confirmed as malignant based on axillary status. Most outcome-predictive features were selected using four machine-learning algorithms. Receiver operating characteristic analysis was used to reflect diagnostic performance. Results: Least absolute shrinkage and selection operator was used to dimensionally reduce 1137 radiomics features to three features. Three optimal radiomics features were used to model construction. The logistic regression model achieved an accuracy of 97% and 85% in the training and test groups. Clinical utility was evaluated using decision curve analysis. Conclusion: The novel combination of radiomics analysis and machine-learning algorithm could predict axillary metastasis and prevent invasive manipulation.

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.

Validation of In Vivo Nodal Assessment of Solid Malignancies with USPIO-Enhanced MRI: A Workflow Protocol

Background: In various cancer types, the first step towards extended metastatic disease is the presence of lymph node metastases. Imaging methods with sufficient diagnostic accuracy are required to personalize treatment. Lymph node metastases can be detected with ultrasmall superparamagnetic iron oxide (USPIO)-enhanced magnetic resonance imaging (MRI), but this method needs validation. Here, a workflow is presented, which is designed to compare MRI-visible lymph nodes on a node-to-node basis with histopathology. Methods: In patients with prostate, rectal, periampullary, esophageal, and head-and-neck cancer, in vivo USPIO-enhanced MRI was performed to detect lymph nodes suspicious of harboring metastases. After lymphadenectomy, but before histopathological assessment, a 7 Tesla preclinical ex vivo MRI of the surgical specimen was performed, and in vivo MR images were radiologically matched to ex vivo MR images. Lymph nodes were annotated on the ex vivo MRI for an MR-guided pathological examination of the specimens. Results: Matching lymph nodes of ex vivo MRI to pathology was feasible in all cancer types. The annotated ex vivo MR images enabled a comparison between USPIO-enhanced in vivo MRI and histopathology, which allowed for analyses on a nodal, or at least on a nodal station, basis. Conclusions: A workflow was developed to validate in vivo USPIO-enhanced MRI with histopathology. Guiding the pathologist towards lymph nodes in the resection specimens during histopathological work-up allowed for the analysis at a nodal basis, or at least nodal station basis, of in vivo suspicious lymph nodes with corresponding histopathology, providing direct information for validation of in vivo USPIO-enhanced, MRI-detected lymph nodes.

MRI Findings Suggestive of Metastatic Axillary Lymph Nodes in Patients with Invasive Breast Cancer

Purpose

This study aimed to investigate the diagnostic performance of features suggestive of nodal metastasis on preoperative MRI in patients with invasive breast cancer.

Materials and Methods

We retrospectively reviewed the preoperative breast MRI of 192 consecutive patients with surgically proven invasive breast cancer. We analyzed MRI findings of axillary lymph nodes with regard to the size, long/short ratio, cortical thickness, shape and margin of the cortex, loss of hilum, asymmetry, signal intensity (SI) on T2-weighted images (T2WI), degree of enhancement in the early phase, and enhancement kinetics. Receiver operating characteristic (ROC) analysis, chi-square test, t test, and McNemar’s test were used for statistical analysis.

Results

Increased shorter diameter, uneven cortical shape, increased cortical thickness, loss of hilum, asymmetry, irregular cortical margin, and low SI on T2WI were significantly suggestive of metastasis. ROC analysis revealed the cutoff value for the shorter diameter and cortical thickness as 8.05 mm and 2.75 mm, respectively. Increased cortical thickness (> 2.75 mm) and uneven cortical shape showed significantly higher sensitivity than other findings in McNemar’s test. Irregular cortical margins showed the highest specificity (100%).

Conclusion

Cortical thickness > 2.75 mm and uneven cortical shape are more sensitive parameters than other findings, and an irregular cortical margin is the most specific parameter for predicting axillary metastasis in patients with invasive breast cancer.

Fat fractions from high-resolution 3D radial Dixon MRI for predicting metastatic axillary lymph nodes in breast cancer patients

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High-Resolution 3D radial Dixon MRI allows for the creation of quantitative fat fraction images.

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Lymph node fat fractions improves diagnostic performance of MRI to detect axillary lymph node metastases.

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Lymph node fat fractions are a promising quantitative indicator of metastases in axillary lymph nodes.

Purpose

To assess diagnostic performance of fat fractions (FF) from high-resolution 3D radial Dixon MRI for differentiating metastatic and non-metastatic axillary lymph nodes in breast cancer patients.

Method

High-resolution 3D radial Dixon MRI was prospectively performed on 1.5 T in 70 biopsy-verified breast cancer patients. 35 patients were available for analysis with histopathologic and imaging data. FF images were calculated as fat / in-phase. Two radiologists measured lymph node FF and assessed morphological features in one ipsilateral and one contralateral lymph node in consensus. Diagnostic performance of lymph node FF and morphological criteria were compared using histopathology as reference.

Results

22 patients had metastatic axillary lymph nodes. Mean lymph node FF were 0.20 ± 0.073, 0.31 ± 0.079, and 0.34 ± 0.15 (metastatic, non-metastatic ipsi- and non-metastatic contralateral lymph nodes, respectively). Metastatic lymph node FF were significantly lower than non-metastatic ipsi- (p <  0.001) and contralateral lymph nodes (p <  0.001). Area under the receiver operating characteristics curve for lymph node FF was 0.80 compared to 0.76 for morphological criteria (p =  0.29). Lymph node FF yielded sensitivity 0.91, specificity 0.69, positive predictive value (PPV) 0.83, and negative predictive value (NPV) 0.82, while morphological criteria yielded sensitivity 0.91, specificity 0.62, PPV 0.80, and NPV 0.80 (p =  0.71). Combining lymph node FF and morphological criteria increased diagnostic performance with sensitivity 1.00, specificity 0.67, PPV 0.86, NPV 1.00, and AUC 0.83.

Conclusions

Lymph node FF from high-resolution 3D Dixon images are a promising quantitative indicator of metastases in axillary lymph nodes.

Does axillary lymph node size predict better metastatic involvement than apparent diffusion coefficient (ADC) value in women with newly diagnosed breast cancer?

BACKGROUND

It has been demonstrated that the number of metastatic axillary lymph nodes (mALNs) influence disease-free and overall survival in patients with breast cancer.

PURPOSE

To determine if the ALN size is more accurate than the ALN apparent diffusion coefficient (ADC) value to predict metastatic involvement in newly diagnosed breast cancer.

MATERIAL AND METHODS

A total of 44 patients with breast cancer were included. Magnetic resonance imaging (MRI) examinations were performed on a 1.5-T system with sagittal T1-weighted fast spin-echo non-fat saturated, sagittal T2-weighted fast spin-echo non-fat saturated, axial diffusion-weighted imaging echo-planar (b values of 0 and 700 s/mm²), and non-contrast axial VIBRANT sequences. The size and the ADC value were obtained for ALN ipsilateral and contralateral to breast cancer. The reference standard was the histopathologic lymph node status.

RESULTS

mALN had a greater cortical thickness compared to contralateral non-mALN (10.3 ± 5.32 mm vs. 4 ± 1.17 mm, P ≤ 0.001). The threshold of ≥6.7 mm for predicting axillary metastatic involvement had a sensitivity and a specificity of 80.0% and 97.7%, respectively. The ADC value of mALN was significantly higher than the contralateral non-mALN (0.90 ± 0.12 × 10^-3mm²/s vs. 0.78 ± 0.12 × 10^-3mm²/s; P = 0.001). The threshold of ≥0.86 × 10^-3mm²/s had a sensitivity and a specificity of 66.7% and 76.7%, respectively.

CONCLUSION

Our results indicate that the cortical thickness has a better diagnostic performance in the differentiation of metastatic and non-metastatic lymph nodes than the lymph node ADC.

A Nomogram Combined Radiomics and Kinetic Curve Pattern as Imaging Biomarker for Detecting Metastatic Axillary Lymph Node in Invasive Breast Cancer

Objective: To construct and validate a nomogram model integrating the magnetic resonance imaging (MRI) radiomic features and the kinetic curve pattern for detecting metastatic axillary lymph node (ALN) in invasive breast cancer preoperatively. Materials and Methods: A total of 145 ALNs from two institutions were classified into negative and positive groups according to the pathologic or surgical results. One hundred one ALNs from institution I were taken as the training cohort, and the other 44 ALNs from institution II were taken as the external validation cohort. The kinetic curve was computed using dynamic contrast-enhanced MRI software. The preprocessed images were used for radiomic feature extraction. The LASSO regression was applied to identify optimal radiomic features and construct the Radscore. A nomogram model was constructed combining the Radscore and the kinetic curve pattern. The discriminative performance was evaluated by receiver operating characteristic analysis and calibration curve.

Results: Five optimal features were ultimately selected and contributed to the Radscore construction. The kinetic curve pattern was significantly different between negative and positive lymph nodes. The nomogram model showed a better performance in both training cohort [area under the curve (AUC) = 0.91, 95% CI = 0.83–0.96] and external validation cohort (AUC = 0.86, 95% CI = 0.72–0.94); the calibration curve indicated a better accuracy of the nomogram model for detecting metastatic ALN than either Radscore or kinetic curve pattern alone.

Conclusion: A nomogram model integrated the Radscore and the kinetic curve pattern could serve as a biomarker for detecting metastatic ALN in patients with invasive breast cancer.

MRI evaluation of axillary and intramammary lymph nodes in the postoperative period

Our study aimed to evaluate if breast‐conserving surgery and adjuvant treatment could affect the morphological features of axillary and intramammary lymph nodes on magnetic resonance imaging (MRI) in patients with invasive breast cancer and clinically negative axilla. In this single‐center study, we retrospectively evaluated 50 patients who had (a) breast‐conserving surgery, (b) clinically negative axilla, (c) preoperative MRI within 3 months before surgery, and (d) postoperative MRI within 12 months after surgery. Axillary and intramammary lymph nodes on postoperative MRI were identified and then compared with preoperative MRI by two breast radiologists with regards to the following: enlargement, cortical thickening, presence of fatty hilum, irregularity, heterogeneity, matting, and axillary lymph node asymmetry. Three hundred and two axillary and eight intramammary lymph nodes were evaluated. Enlargement and cortical thickening were seen in 5/50 (10%) patients in three axillary and two intramammary lymph nodes. None of the lymph nodes on postoperative MRI demonstrated occurrence of lack of fatty hilum, irregularity, heterogeneity, matting or axillary lymph node asymmetry. No evidence of recurrence was observed on 2‐year follow‐up. Lymph node enlargement and cortical thickening may be observed in a few patients in the postoperative period. Nevertheless, in patients with clinically negative axilla, these changes in morphology are often related to treatment rather than malignancy and favor short‐term follow‐up as an alternative to lymph node biopsy.

Use of Quantitative Morphological and Functional Features for Assessment of Axillary Lymph Node in Breast Dynamic Contrast-Enhanced Magnetic Resonance Imaging

Background

Axillary lymph-node assessment is considered one of the most important prognostic factors concerning breast cancer survival.

Objective

We investigated the discriminative power of morphological and functional features in assessing the axillary lymph node.

Methods

We retrospectively analysed data from 52 consecutive patients who undergone DCE-MRI and were diagnosed with primary breast carcinoma: 94 lymph nodes were identified. Per each lymph node, we extracted morphological features: circularity, compactness, convexity, curvature, elongation, diameter, eccentricity, irregularity, radial length, entropy, rectangularity, roughness, smoothness, sphericity, spiculation, surface, and volume. Moreover, we extracted functional features: time to peak (TTP), maximum signal difference (MSD), wash-in intercept (WII), wash-out intercept (WOI), wash-in slope (WIS), wash-out slope (WOS), area under gadolinium curve (AUGC), area under wash-in (AUWI), and area under wash-out (AUWO). Selection of important features in predicting metastasis has been done by means of receiver operating characteristic (ROC) analysis. Performance of linear discriminant analysis was analysed.

Results

All morphological features but circularity showed a significant difference between median values of metastatic lymph nodes group and nonmetastatic lymph nodes group. All dynamic parameters except for MSD and WOS showed a statistically significant difference between median values of metastatic lymph nodes group and nonmetastatic lymph nodes group. Best results for discrimination of metastatic and nonmetastatic lymph nodes were obtained by AUGC (accuracy 75.8%), WIS (accuracy 71.0%), WOS (accuracy 71.0%), and AUCWO (accuracy 72.6%) for dynamic features and by compactness (accuracy 82.3%), curvature (accuracy 71.0%), radial length (accuracy 71.0%), roughness (accuracy 74.2%), smoothness (accuracy 77.2%), and speculation (accuracy 72.6%) for morphological features. Linear combination of all morphological and/or of all dynamic features did not increase accuracy in metastatic lymph nodes discrimination.

Conclusions

Compactness as morphological feature and area under time-intensity curve as dynamic feature were the best parameters in identifying metastatic lymph nodes on breast MRI.

Supine MRI for regional breast radiotherapy: imaging axillary lymph nodes before and after sentinel-node biopsy

Regional radiotherapy (RT) is increasingly used in breast cancer treatment. Conventionally, computed tomography (CT) is performed for RT planning. Lymph node (LN) target levels are delineated according to anatomical boundaries. Magnetic resonance imaging (MRI) could enable individual LN delineation. The purpose was to evaluate the applicability of MRI for LN detection in supine treatment position, before and after sentinel-node biopsy (SNB). Twenty-three female breast cancer patients (cTis-3N0M0) underwent 1.5 T MRI, before and after SNB, in addition to CT. Endurance for MRI was monitored. Axillary levels were delineated. LNs were identified and delineated on MRI from before and after SNB, and on CT, and compared by Wilcoxon signed-rank tests. LN locations and LN-based volumes were related to axillary delineations and associated volumes. Although postoperative effects were visible, LN numbers on postoperative MRI (median 26 LNs) were highly reproducible compared to preoperative MRI when adding excised sentinel nodes, and higher than on CT (median 11, p  <  0.001). LN-based volumes were considerably smaller than respective axillary levels. Supine MRI of LNs is feasible and reproducible before and after SNB. This may lead to more accurate RT target definition compared to CT, with potentially lower toxicity. With the MRI techniques described here, initiation of novel MRI-guided RT strategies aiming at individual LNs could be possible.

Diagnostic accuracy of metastatic axillary lymph nodes in breast MRI

Purpose

The most important prognostic variable for early stage breast cancer is the status of axillary lymph nodes. The aim of this study was to evaluate the diagnostic accuracy of preoperative magnetic resonance imaging (MRI) for metastatic axillary lymph node in breast cancer cases with post-operative sentinel lymph node biopsy (SLNB) results.

Materials and methods

Women aged between 21 and 73 years who were diagnosed with malignant mass lesion of the breast between 2013 and 2015 were included in this study. The preoperative MR images of patients with diagnosis of breast cancer was evaluated to determine axillary lymph node status. Axillary lymph node size, long axis to short axis ratio, lymph node contours, cortical thickness to anteroposterior diameter ratio, the presence of a fatty hilum and contrast enhancement patterns (homogenous or heterogenous) was noted. Additionally, the presence of comet tail sign which a tail extending from an enhancing breast lesion into the parenchyma and might represent ductal infiltration on post-contrast series was also noted. All data obtained from this evaluation was compared with postoperative SLNB results.

Results

Metastatic nodes were found to have a longer short axis when compared to reactive nodes (p = 0.042; p < 0.05). The long axis to short axis ratio was notably lower in metastatic nodes when compared to reactive nodes. Cortical thickness was higher in metastatic nodes when compared to reactive nodes (p = 0.024; p < 0.05). Comet sign was observed in 15 of metastatic nodes (73.3 %) and in one (5 %) reactive node. This difference was statistically significant (p = 0.001; p < 0.01). While fatty hilum was seen in 40 % of metastatic nodes (n = 6), it was seen in all (n = 20) reactive nodes. This difference was statistically significant (p = 0.001; p < 0.01).

Conclusions

MRI is a non invasive sensitive and specific imaging modality for evaluating the axilla. We have shown that with the help of comet tail sign and status of fatty hilum contrast enhanced MRI has the highest sensitivity of 84.7 % for detecting axillary lymph node metastases (Singletary et al. in Semin Surg Oncol 21(1):53–59, 2003).

MRI sequences for the detection of individual lymph nodes in regional breast radiotherapy planning

OBJECTIVE

In regional radiotherapy (RT) for patients with breast cancer, lymph node (LN) targets are delineated on CT, defined by anatomical boundaries. By identifying individual LNs, MRI-based delineations may reduce target volumes and thereby toxicity. We optimized MRI sequences for this purpose. Our aim was to evaluate the techniques for LN delineation in RT planning.

METHODS

Supine MRI was explored at 1.5 T in RT position (arms in abduction). 5 MRI techniques were optimized in 10 and evaluated in 12 healthy female volunteers. The scans included one T1 weighted (T1w), three T2 weighted (T2w) and a diffusion-weighted imaging (DWI) technique. Quantitative evaluation was performed by scoring LN numbers per volunteer and per scan. Qualitatively, scans were assessed on seven aspects, including LN contrast, anatomical information and insensitivity to motion during acquisition.

RESULTS

Two T2w fast spin-echo (FSE) methods showed the highest LN numbers (median 24 axillary), high contrast, excellent fat suppression and relative insensitivity to motion during acquisition. A third T2w sequence and DWI showed significantly fewer LNs (14 and 10) and proved unsuitable due to motion sensitivity and geometrical uncertainties. T1w MRI showed an intermediate number of LNs (17), provided valuable anatomical information, but lacked LN contrast.

CONCLUSION

Explicit LN imaging was achieved, in supine RT position, using MRI. Two T2w FSE techniques had the highest detection rates and were motion insensitive. T1w MRI showed anatomical information. MRI enables direct delineation of individual LNs.

ADVANCES IN KNOWLEDGE

Our optimized MRI scans enable accurate target definition in MRI-guided regional breast RT and development of personalized treatments.

Ipsilateral breast cancer recurrence after Deep Inferior Epigastric Perforator (DIEP) flap reconstruction: Incidence and radiological presentation

PURPOSE

To assess the incidence and presentation of ipsilateral cancer recurrences (ICR) after deep inferior epigastric perforator (DIEP) flap reconstruction for breast cancer.

PATIENTS AND METHODS

Data of 247 consecutive women with DIEP flap reconstruction after breast cancer in our institution between 1997 and 2009 were retrospectively reviewed.

RESULTS

Mean follow-up time was 4.1years±3.2 (SD) (median: 3years; range: 1month - 14years). Thirty-one patients (12.5%, 95%CI: =8.7-17.3) presented 34 relapses, in average 4.1years±2.6 after mastectomy: 14 (41%) were ipsilateral, 6 (18%) contralateral and 14 (41%) metastatic. ICRs occurred earlier (3.9 vs. 5.8years; P<0.05) than non-ICRs. Most ICRs (10/14, 71%) involved the periphery of the flap and presented as palpable nodules. The remaining (4/14, 29%) involved the axilla and 3/4 (75%) were palpable. Imaging procedures detected infra-clinical ICRs in 3 of 10 imaged patients (30%).

CONCLUSION

ICRs after DIEP flap reconstruction are more frequent than contralateral recurrences suggesting the need for imaging follow-up of the reconstructed breast.

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.

The value of T2* in differentiating metastatic from benign axillary lymph nodes in patients with breast cancer--a preliminary in vivo study

BACKGROUND

Accurate detection and determination of axillary lymph node metastasis are crucial for the clinical management of patients with breast cancer. Noninvasive imaging methods including ultrasound (US), computed tomography (CT), or conventional magnetic resonance imaging (MRI) are not yet accurate enough. The purpose of this study was to investigate the value of in vivo T2* in differentiating metastatic from benign axillary lymph nodes in patients with breast cancer.

METHODOLOGY/PRINCIPAL FINDINGS

In this institutional review board approved study, 35 women with breast cancer underwent multi-echo T2* weighted imaging (T2*WI) of the axillary area on a 3.0 T clinical magnetic resonance (MR) imaging system. T2* values of pathologically proven benign and metastatic axillary lymph nodes were calculated and compared. Receiver operating characteristics (ROC) analysis was conducted to evaluate the diagnostic ability. The areas under the ROC curve (AUCs) and the confidence intervals (CIs) were assessed. In total, 56 metastatic and 65 benign axillary lymph nodes were identified in this study. For metastatic lymph nodes, the average T2* value (55.96±11.87 ms) was significantly longer than that of the benign lymph nodes (26.00±5.51 ms, P<0.05). The AUC of T2* in differentiating benign from metastatic lymph nodes was 0.993. The cut-off value of 37.5 milliseconds (ms) gave a sensitivity of 94.6%, a specificity of 98.5%, a positive predictive value of 98.17 and a negative predictive value 95.54.

CONCLUSIONS

In vivo T2* can differentiate benign from metastatic axillary lymph nodes in patients with breast cancer. The high sensitivity and specificity as well as the easiness suggest its high potential for use in clinical practice.

Is imaging the future of axillary staging in breast cancer?

Axillary management in patients with breast cancer has become much less invasive with the introduction of sentinel lymph node biopsy (SLNB). However, over 70 % of SLNBs are negative, questioning the generic use of this invasive procedure. Emerging evidence indicates that breast cancer patients with a low axillary burden of disease do not benefit from axillary lymph node dissection (ALND). Non-invasive techniques such as paramagnetic iron oxide contrast-enhanced magnetic resonance imaging (MRI) may provide genuine alternatives to axillary staging and should be evaluated within clinical trials. Selective axillary surgery could then be offered based on imaging findings and for therapeutic intent. This non-operative approach would reduce morbidity further and facilitate interpretation of follow-up imaging. Key Points • Modern imaging and biopsy greatly help the axillary staging of breast cancer. • Superparamagnetic iron oxide (SPIO)-enhanced MRI offers a further advance. • Sentinel lymph node biopsy may become redundant with SPIO-enhanced MRI. • Selective therapeutic axillary surgery should be based upon preoperative imaging findings.

Translational imaging of lymphatics in cancer

Imaging in the lymphatic system has gone through much advancement over the past 70 years since its beginnings. In this review, we will examine the modalities available for lymphatic imaging. We will explore the modern uses of early modalities, such as ultrasound as well as more modern modalities, such as Positron-Emission Tomography (PET). We will also describe some of the new modalities currently in development and their potential uses for the future as well as some of the current imaging modalities being studied in animal models.

Dissected sentinel lymph nodes of breast cancer patients: characterization with high-spatial-resolution 7-T MR imaging

PURPOSE

To investigate the association of 7-T magnetic resonance (MR) imaging characteristics with metastatic nodal invasion, determined with histopathologic assessment in dissected sentinel lymph nodes of breast cancer patients.

MATERIALS AND METHODS

Institutional review board approval and informed consent were obtained. From November 2008 to July 2010, 114 dissected lymph nodes from 33 women (mean age, 57 years; range, 31-80 years) with breast cancer were included. For morphological analysis, three-dimensional (3D) T1-weighted fat-suppressed fast field- (gradient-) echo (isotropic resolution, 180 μm) MR was performed; 3D nodal dimensions, maximum cortical thickness, and presence of fatty hilum were noted. For quantitative parametric analysis, two-dimensional T1-weighted and 3D T2-, T2*-, and diffusion-weighted images were acquired. Statistical analysis included generalized estimating equations (GEEs), forward and backward stepwise regression analyses, and calculation of positive predictive value (PPV) and negative predictive value (NPV).

RESULTS

Of 114 nodes, 26 (23%) were malignant. Morphological criteria showed weak discriminatory power: A fatty center was absent in 35% of malignant nodes and 30% of benign nodes (P = .9). Nodal volume and length-width ratio were not significantly different (P = .11 and .75, respectively). Cortical thickness (threshold level, 3 mm; P = .02) showed 91% NPV for malignancy and 95% NPV for presence of macrometastases. Quantitative parametric analyses showed comparable mean T1, T2, and T2* relaxation time constants and apparent diffusion coefficient for metastatic and benign nodes: 991 msec, 30 msec, and 18 msec and 0.17 mm²/sec versus 1035 msec (P = .14), 31 msec (P = .001; not significant after GEE), and 15 msec (P = .002) and 0.20 mm²/sec (P = .38), respectively. Mean T2* alone offered an additive discriminatory effect for identification of metastatic nodes. Consistent with the notion of pannodal changes accompanying tumor infiltration, mean T2* differed significantly even if only micrometastases were present. The interindividual differences were small, precluding easy clinical implementation.

CONCLUSION

Morphological criteria showed poor discriminatory power, even with very-high-spatial-resolution imaging. T2* quantification allowed identification of metastatic nodal invasion.

Characterization of ex vivo healthy human axillary lymph nodes with high resolution 7 Tesla MRI

Objective

To characterize ex vivo healthy human axillary lymph nodes on 7 Tesla MRI and to correlate the findings with pathological analysis as a first step towards non-invasive staging of breast cancer patients in the future.

Methods

Four axillary lymph node dissection (ALND) specimens from 2 autopsy patients, who had no cancer, were examined on a clinical 7 Tesla MRI system. For morphological analysis a 3D T1-weighted fat-suppressed fast-field-echo [isotropic resolution 180 μm] was acquired. For quantitative analyses 2D T1-, 3D T2-, T2*- and diffusion-weighted images were acquired. The ALNDs were mapped and stained for precise correlation of MRI to pathology. Nodes were sliced in 3 μm sections, Haematoxylin & Eosin stained, and examined by an experienced pathologist.

Results

MRI detected all 45 nodes and 6 additional nodes that were not detected at pathological analysis. B-cell follicles, efferent- and afferent lymph vessels and blood vessels were identified. Mean T1, T2, T2*, ADC values (± standard deviation) were 944 ± 113 ms, 32 ± 2 ms, 16 ± 2 ms, 0.39 ± 0.09·10⁻³ mm²/s, respectively.

Conclusions

7 Tesla MRI of ex vivo human axillary lymph nodes correlated well with pathology. MRI detected all nodes present in the specimens and allowed visualization of fine structural detail. Pathology-correlated quantitative MRI data are presented.