Assessment of axillary lymph nodes in patients with breast cancer with diffusion-weighted MR imaging in combination with routine and dynamic contrast MR imaging

A Comprehensive Assessment of Radial Scars on Core Needle Biopsy in Patients with or without Breast Cancer: Upgrade Rate and Implications on Management

BACKGROUND

Radial scars/radial sclerosing lesions (RS) are benign breast lesions identified on core needle biopsy (CNB) which can upgrade to malignancy at excision. There is limited data on RS detection and upgrade rates with more sensitive imaging such as magnetic resonance imaging (MRI) and none during their detection for breast cancer workup and its implication on patient treatment decisions.

METHODS

A retrospective institutional study of RS diagnosed on CNB between January 2008 and December 2017 was conducted. Clinicopathologic and radiologic features of RS, patient treatment decisions, upgrade rates and long-term follow-up were examined.

RESULTS

We identified 133 patients with RS on CNB, of whom 106 opted for surgery for an upgrade rate to malignancy of 1.9%, 2 patients. Radial scar was diagnosed on mammogram in 60%, MRI in 25% and ultrasound in 15% of patients. In this cohort, 32 patients had their RS detected during breast cancer workup (coexistent group) and they were more likely to have their radial scar detected by MRI (60% vs. 14%, P < .001) and undergo more extensive surgery (94% vs. 75%, P = .02). Among the 27 patients electing observation of their RS, only one (3.7%) developed breast cancer.

CONCLUSIONS

Our results show an extremely low upgrade rate to malignancy of RS, regardless if there is coexisting breast cancer elsewhere. Despite this, RS still prompted more extensive surgical excisions. The findings do not support excision of RS even among breast cancer patients when identified at a separate site from their cancer.

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.

The role of diffusion-weighted MR imaging in discrimination between benign and malignant axillary lymph nodes in breast cancer patients

Background

Noninvasive preoperative evaluation of axillary lymph nodes proved to have a significant role not only on the protocol of treatment of breast cancer but also impact the whole life of the patient. Complications of lymph node biopsy or axillary clearance increase the need for noninvasive reliable diagnostic tool. We aimed in the current study to evaluate the role of diffusion-weighted magnetic resonance imaging (DW-MRI) and apparent diffusion coefficient (ADC) in discrimination between benign and malignant axillary lymph nodes. We included 44 suspicious lymph nodes from 29 patients. Qualitative DW-MRI was analyzed into restricted or not; ADC maps and cut-off value were calculated, and they were correlated with histopathological results, which were the gold standard tool of the current study.

Results

The cut-off value of ADC-differentiated between malignant and benign lymph nodes was 0.89 × 10−3 mm2/s. The statistical indices including the sensitivity, specificity, PPV, NPV and accuracy were 89.66%, 86.67%, 93.9, 81.2% and 87.8%, respectively, with P value < 0.001, while DW-MRI results were classified into restricted or not restricted with qualitative statistical indices of 96.6%, 80%, 90.3%, 92.3% and 90.9% for sensitivity, specificity, PPV, NPV and accuracy, respectively, with P value < 0.001.

Conclusion

DW-MRI and ADC both have significant role in discrimination between benign and malignant axillary lymph nodes increasing the accuracy of MRI examination in breast cancer patients.

Preoperative Prediction of Axillary Lymph Node Metastasis in Breast Cancer Using CNN Based on Multiparametric MRI

BACKGROUND

Multiparametric magnetic resonance imaging (MRI) is widely used in breast cancer screening. Accurate prediction of the axillary lymph nodes metastasis (ALNM) is essential for breast cancer surgery and treatment. However, there is no mature and effective discerning method for ALNM based on multiparametric MRI.

PURPOSE

To evaluate the ALNM using T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and diffusion-weighted imaging (DWI) sequences, respectively, and construct a quantitative ALNM discerning model of integrated multiparametric MRI.

STUDY TYPE

Retrospective.

POPULATION

Three-hundred forty-eight breast cancer patients, 163 with ALNM (99.39% females), and 185 without ALNM (100% females). The dataset was randomly divided into the training set (315 cases) and the testing set (33 cases).

FIELD STRENGTH/SEQUENCE

1.5 T; T1WI (VIBRANT), T2WI (FSE), and DWI (echo planar imaging [EPI]).

ASSESSMENT

The lesion region of interest images were cropped and sent to a pretrained ResNet50 network. Then, the results of different sequences were sent to a classifier for ensemble learning to construct the ALNM model of multiparametric MRI.

STATISTICAL TESTS

Performance indicators such as accuracy, the receiver operating characteristic (ROC) curve, and the area under the ROC curve (AUC) were calculated. Student's t-test, chi-square test, Fisher's exact test, and Delong test were performed, and P < 0.05 was considered statistically significant.

RESULTS

T2WI performed the best among the three sequences, and achieved the accuracy and AUC of 0.933/0.989 in the testing set. Compared to T1WI with the accuracy and AUC of 0.691/0.806, the increase is significant. While compared to DWI with the accuracy and AUC of 0.800/0.910, the improvement is not significant (P = 0.126). After integrating three sequences, the accuracy and AUC improved to 0.970 and 0.996.

DATA CONCLUSION

T2WI performed better than DWI and T1WI in discerning ALNM in this breast cancer dataset. The proposed quantitative model of integrated multiparametric MRI could effectively help the ALNM diagnosis.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY STAGE: 2.

Diagnostic performance of T2-weighted imaging and intravoxel incoherent motion diffusion-weighted MRI for predicting metastatic axillary lymph nodes in T1 and T2 stage breast cancer

BACKGROUND

Non-invasive modalities for assessing axillary lymph node (ALN) are needed in clinical practice.

PURPOSE

To investigate the suspicious ALN on unenhanced T2-weighted (T2W) imaging and intravoxel incoherent motion diffusion-weighted imaging (IVIM DWI) for predicting ALN metastases (ALNM) in patients with T1-T2 stage breast cancer and clinically negative ALN.

MATERIAL AND METHODS

Two radiologists identified the most suspicious ALN or the largest ALN in negative axilla by T2W imaging features, including short axis (Size-S), long axis (Size-L)/S ratio, fatty hilum, margin, and signal intensity on T2W imaging. The IVIM parameters of these selected ALNs were also obtained. The Mann-Whitney U test or t-test was used to compare the metastatic and non-metastatic ALN groups. Finally, logistic regression analysis with T2W imaging and IVIM features for predicting ALNM was conducted.

RESULTS

This study included 49 patients with metastatic ALNs and 50 patients with non-metastatic ALNs. Using the above conventional features on T2W imaging, the sensitivity and specificity in predicting ALNM were not high. Compared with non-metastatic ALNs, metastatic ALNs had lower pseudo-diffusion coefficient (D*) (P = 0.043). Logistic regression analysis showed that the most useful features for predicting ALNM were signal intensity and D*. The sensitivity and specificity predicting ALNM that satisfied abnormal signal intensity and lower D* were 73.5% and 84%, respectively.

CONCLUSIONS

The abnormal signal intensity on T2W imaging and one IVIM feature (D*) were significantly associated with ALNM, with sensitivity of 73.5% and specificity of 84%.

Differentiation Between Benign and Metastatic Breast Lymph Nodes Using Apparent Diffusion Coefficients

The aim of this study was to determine the range of apparent diffusion coefficient (ADC) values for benign axillary lymph nodes in contrast to malignant axillary lymph nodes, and to define the optimal ADC thresholds for three different ADC parameters (minimum, maximum, and mean ADC) in differentiating between benign and malignant lymph nodes. This retrospective study included consecutive patients who underwent breast MRI from January 2017–December 2020. Two-year follow-up breast imaging or histopathology served as the reference standard for axillary lymph node status. Area under the receiver operating characteristic curve (AUC) values for minimum, maximum, and mean ADC (min ADC, max ADC, and mean ADC) for benign vs malignant axillary lymph nodes were determined using the Wilcoxon rank sum test, and optimal ADC thresholds were determined using Youden’s Index. The final study sample consisted of 217 patients (100% female, median age of 52 years (range, 22–81), 110 with benign axillary lymph nodes and 107 with malignant axillary lymph nodes. For benign axillary lymph nodes, ADC values (×10⁻³ mm²/s) ranged from 0.522–2.712 for mean ADC, 0.774–3.382 for max ADC, and 0.071–2.409 for min ADC; for malignant axillary lymph nodes, ADC values (×10⁻³ mm²/s) ranged from 0.796–1.080 for mean ADC, 1.168–1.592 for max ADC, and 0.351–0.688 for min ADC for malignant axillary lymph nodes. While there was a statistically difference in all ADC parameters (p<0.001) between benign and malignant axillary lymph nodes, boxplots illustrate overlaps in ADC values, with the least overlap occurring with mean ADC, suggesting that this is the most useful ADC parameter for differentiating between benign and malignant axillary lymph nodes. The mean ADC threshold that resulted in the highest diagnostic accuracy for differentiating between benign and malignant lymph nodes was 1.004×10⁻³ mm²/s, yielding an accuracy of 75%, sensitivity of 71%, specificity of 79%, positive predictive value of 77%, and negative predictive value of 74%. This mean ADC threshold is lower than the European Society of Breast Imaging (EUSOBI) mean ADC threshold of 1.300×10⁻³ mm²/s, therefore suggesting that the EUSOBI threshold which was recently recommended for breast tumors should not be extrapolated to evaluate the axillary lymph nodes.

Multiparametric Magnetic Resonance Imaging in Evaluation of Benign and Malignant Breast Masses with Pathological Correlation

Background

Dynamic contrast-enhanced (DCE) MRI sequences plays a vital role in diagnosing breast masses with high sensitivity and specificity as compared to other diagnostic modalities. The addition of diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) values significantly improves diagnostic accuracy. This study aimed to study the breast masses on DCE-MRI, restricted diffusion on DWI, ADC values, and choline peak on spectroscopy in breast cancer diagnosis.

Material and methods

This study was a prospective observational study which involved subjects with breast lumps. Baseline data was collected from the patients along with pertinent clinical history and relevant laboratory investigations. MR mammography (MRM) was performed on a 1.5 Tesla MR Scanner (MAGNETOM® Avanto, Siemens AG, Munich Germany) using a dedicated double breast coil.

Results

Forty-one subjects were included with a total of 54 breast masses in them. The mean age of the study population was 47.1±14.7 years. From the MRI final diagnosis, the majority (53.70%) were diagnosed as malignant lesions and 46.30% as benign. Out of 20 lesions diagnosed as benign on histopathology, only five percent had ADC value <1.3 ×10⁻³mm²/s, and the majority (95%) had ADC value >1.3 ×10⁻³mm²/s. All 20 lesions were circumscribed, ovoid, or round in shape showing no restricted diffusion on DWI, with corresponding ADC value of >1.3×10⁻³mm²/s, homogeneous post-contrast enhancement, or with dark internal septations, type I kinetic enhancement curve, and they showed no choline peak on spectroscopy. Out of 34 malignant lesions diagnosed on histopathology, the majority (85.29%) displayed restricted diffusion on DWI and had an ADC value of <1.3×10⁻³mm²/s, most of them had spiculated margins, type II/ III kinetic curve with choline peak on spectroscopy.

Conclusion

Multiparametric MR mammography, which included DCE-MRM, DWI, ADC values, and spectroscopy, correlated well with the histopathological diagnosis of benign and malignant breast masses.

Feasibility and efficiency of contrast enhanced ultrasound real time guided fine needle aspiration for sentinel lymph node of breast cancer

AIM

To assess the feasibility and efficiency of contrast-enhanced ultrasound (CEUS) real-time guided fine needle aspiration (FNA) for sentinel lymph node (SLN) of breast cancer.

MATERIALS AND METHODS

This retrospective study reviewed 21 breast cancer patients who scheduled for surgical resection performed CEUS real-time guided SLN-FNA and intraoperative SLN biopsy (SLNB). The success rate of CEUS real-time guided SLN-FNA was analyzed. The FNA diagnostic efficiency of SLN metastasis was analyzed compared to SLNB.

RESULTS

Twenty-six SLNs were detected by intradermal CEUS whereas 130 SLNs were detected by SLNB. The median SLNs detected by intradermal CEUS (n = 1) and by SLNB (n = 5) was significantly difference (p < 0.001). All 26 CE-SLNs of 21 patients were successfully performed intradermal CEUS dual image real-time guided SLN-FNA including 5 SLNs of 4 patients which were difficult to distinguish in conventional ultrasound. Compared to SLNB, FNA found 2 of 5 cases of SLN metastasis, the diagnosis sensitivity, specificity, positive predictive value, negative predictive value, false negative rate, false positive rate and Yoden index were 40%, 100%, 100%, 84.2%, 60%, 0%and 40%, respectively.

CONCLUSION

SLN-FNA real-time guided by dual CEUS image mode was technically feasible. Patients with a positive SLN-FNA should be advised to ALND without intraoperative SLNB according to Chinese surgeon and patients' conservatism attitude. But a negative SLN-FNA did not obviate the need of conventional SLNB because of the high false negative rate.

The additive role of diffusion-weighted magnetic resonance imaging to axillary nodal status evaluation in cases of newly diagnosed breast cancer

Background

Axillary nodal status is crucial for the management of cases with recently diagnosed breast cancer; usually addressed via axillary ultrasonography (US) along with tissue sampling in case of suspicion. Axillary nodal dissection and sentinel biopsy may be done, but are rather invasive, carrying a potential complication risk, which raises the need for non-invasive, reliable, pre-operative axillary imaging. We aimed at evaluating the performance of diffusion-weighted imaging (DWI) regarding preoperative axillary evaluation, using functional information derived from diffusion capacity differences between benign and malignant tissue. We included 77 axillary nodes from 77 patients (age range 20–78 years, mean 50 ± 12.6 SD) in our prospective study, presenting with variable clinical breast complaints, all scoring BIRADS 4/5 on sonomammography (SM). They underwent axillary evaluation by both US and DW-MRI where US classified nodes into benign, indeterminate, or malignant by evaluating nodal size, shape, cortical thickness, and hilar fat. Qualitative DWI classified them into either restricted or not and a cut-off apparent diffusion coefficient (ADC) value was calculated to differentiate benign and malignant nodal involvement. Results for each modality were correlated to those of final histopathology, which served as the standard of reference.

Results

The calculated sensitivity, specificity, accuracy, PPV, and NPV for US was 100%, 36.6%, 75.3%, 71.2%, and 100%, respectively. Statistical indices for qualitative DWI were 76.6%, 63.3%, 76.6%, 63.3%, and 71.4%, respectively (P value < 0.001). The calculated cut off value for ADC between infiltrated and non-infiltrated nodes was 0.95 × 10−3 mm2/s concluding statistical indices of 76.6%, 63.3%, 76.6%, 63.3%, and 71.4%, respectively (P value < 0.001).

Conclusion

Combining DW-MRI to conventional US improves diagnostic specificity and overall accuracy of preoperative axillary evaluation of patients with recently discovered breast cancer.

The characteristics associated with upgrade on surgical pathology of conventional imaging occult DCIS diagnosed by MRI

PURPOSE

To characterize the clinical, pathological, and imaging features of DCIS occult on conventional imaging diagnosed on MRI-guided biopsy associated with increased risk of invasive disease on surgical excision.

MATERIALS AND METHODS

All consecutive patients with MRI-detected DCIS occult on conventional imaging between January 2009 and December 2018 were included. Women were divided into two groups based on final pathology: Pure DCIS or DCIS with invasive component. Clinical, imaging, and pathological risk factors for upgrade to invasion were evaluated.

RESULTS

Of 50 patients who met the inclusion criteria, 12 (24%) were upgraded to invasive malignancy in the final pathology. The only parameters that showed statistically significant association with upgrade were related to kinetic characteristics: 53% of patients with the combination of fast early upstroke and either plateau or washout curve were upgraded, compared to 12% of women without this combination (p = 0.006). The sensitivity of combined kinetic features for predicting upgrade was 67% (95% CI 35-90%), specificity was 84% (CI 95% 68-94%), positive predictive value was 57% (CI 95% 37-75%), negative predictive value was 89% (CI 95% 77-95%), and OR was 78% (64-88%).

CONCLUSION

Kinetic characteristics show the strongest association with upgrade to invasion in DCIS occult on mammogram and US. Larger studies should be encouraged to consolidate our findings, which may have implication for treatment planning.

Coronary artery disease imaging reporting and data system (CAD-RADS): what radiologists need to know?

The aim of this work is to review Coronary Artery Disease Imaging Reporting and Data System (CAD-RADS) that was designed to standardize reporting language and improve the communication of data among radiologists and clinicians. Stenotic lesions are graded into 5 grades ranging from 0 (no stenosis) to 5 (total occlusion), where the highest grade represents the final score. The expert consensus platform has added 4 special modifiers (non-diagnostic, stent, graft, and vulnerability) to aid patient management through linking these scores with decision algorithm and treatment plan. Adherence to standard imaging protocol; knowledge of normal, variant, and anomalous anatomy; and skillful evaluation of stenosis are important for proper utilization of this reporting system. Lastly, radiologists should be aware of the inherited benefits, limitations, and common pitfalls of this classification system.

Breast cancer preoperative 18FDG-PET, overall survival prognostic separation compared with the lymph node ratio

PURPOSE

To evaluate the overall survival prognostic value of preoperative 18F-fluorodeoxyglucose positron emission tomography (PET) in breast cancer, as compared with the lymph node ratio (LNR).

METHODS

Data were abstracted at a median follow-up 14.7 years from a retrospective cohort of 104 patients who underwent PET imaging before curative surgery. PET-Axillary|Sternal was classified as PET-positive if hypermetabolism was visualized in ipsilateral nodal axillary and/or sternal region, else as PET-negative. The differences of 15 years restricted mean survival time ∆RMST according to PET and LNR were computed from Kaplan-Meier overall survival. The effect of PET and other patients' characteristics was analyzed through rankit normalization, which provides with Cox regression the Royston-Sauerbrei D measure of separation to compare the characteristics (0 indicating no prognostic value). Multivariate analysis of the normalized characteristics used stepwise selection with the Akaike information criterion.

RESULTS

In Kaplan-Meier analysis, LNR > 0.20 versus ≤ 0.20 showed ∆RMST = 3.4 years, P = 0.003. PET-Axillary|Sternal positivity versus PET-negative showed a ∆RMST = 2.6 years, P = 0.008. In Cox univariate analyses, LNR appeared as topmost prognostic separator, D = 1.50, P < 0.001. PET ranked below but was also highly significant, D = 1.02, P = 0.009. In multivariate analyses, LNR and PET-Axillary|Sternal were colinear and mutually exclusive. PET-Axillary|Sternal improved as prognosticator in a model excluding lymph nodes, yielding a normalized hazard ratio of 2.44, P = 0.062.

CONCLUSION

Pathological lymph node assessment remains the gold standard of prognosis. However, PET appears as a valuable surrogate in univariate analysis at 15-year follow-up. There was a trend towards significance in multivariate analysis that warrants further investigation.

Diffusion tensor imaging of vertebral bone marrow in children with Gaucher's disease type I and III: Pre- and post-therapy

PURPOSE

To assess diffusion tensor imaging (DTI) of the vertebral bone marrow (BM) in children with Gaucher's disease (GD) types I and III before and after therapy.

METHODS

Prospective study was conducted upon 25 children with GD type I (n = 17) and III (n = 8) and 13 age and sex-matched controls underwent DTI of vertebral BM. Mean diffusivity (MD) and fractional anisotropy (FA) of vertebral BM was calculated and correlated with genotyping, chitotriosidase, hemoglobin (HB) and, platelet count.

RESULTS

There was a statistically significant difference in MD and FA of BM between patients and controls (P = 0.001 and 0.02). The area under the curve (AUC) of MD and FA used to differentiate untreated patients from controls was 0.902 and 0.68 with sensitivity, specificity, and, accuracy 92%, 84.6%, and, 89.5% respectively. There was a significant difference in MD and FA of BM between untreated and treated patients (P = 0.001 and 0.02). AUC of MD and FA used to differentiate untreated from treated patients was 0.93 and 0.649 with sensitivity, specificity, and accuracy of 92%, 80%, and 86% respectively. There was a significant difference in MD and FA (P = 0.03, 0.001 respectively) of BM in GD with homozygous L444P mutation (n = 9) and other mutations (n = 14). Chiotriptase, HB and platelet count of patients was correlated with MD (r = -0.36, 0.42, -0.41) and FA (r = -0.47, -0.37, -0.46) respectively.

CONCLUSION

DTI of vertebral BM can help in diagnosis and monitoring patients with GD after therapy and correlated with genotyping, and hematological biomarkers of GD.

Differentiation Between Phenotypes of Polycystic Ovarian Syndrome With Sonography

Objectives:

To differentiate between the classic (A/B) from the nonclassic (C/D) phenotypes of the polycystic ovarian syndrome (PCOS) with sonography.

Materials & Methods:

Retrospective analysis was performed upon 72 female patients with PCOS. All patients underwent transvaginal sonography. The patients were classified into classic and nonclassic phenotypes of PCOS. Image analysis was performed for the ovarian volume, follicle counts, follicle size, and endometrial plate thickness.

Results:

There were significant differences in the ovarian volume ( P = .001), follicle counts ( P = .001), follicle size ( P = .001), and endometrial plate thickness ( P = .001) between classic and nonclassic phenotypes of PCOS. The threshold value for ovarian volume, follicle count, follicle size, and endometrial plate thickness used to differentiate classic from nonclassic phenotypes were 12.5, 10.5, 5.25, and 5.75, respectively, with an area under the curve of 0.79, 0.82, 0.83, 0.77 and an accuracy of 75%, 73.6%, 79.2%, and 68.1%, respectively. The serum testosterone level and the body mass index were significantly higher in patients with classic than nonclassic phenotypes of PCOS ( P = .001, .04), respectively.

Conclusion:

Sonography findings can differentiate classic from nonclassic phenotypes of PCOS.

Prediction of pathological complete response after neoadjuvant chemotherapy in breast cancer: comparison of diagnostic performances of dedicated breast PET, whole-body PET, and dynamic contrast-enhanced MRI

PURPOSE

To compare the diagnostic performance of ring-type dedicated breast PET (dbPET), whole-body PET (WBPET), and DCE-MRI for predicting pathological complete response (pCR) after neoadjuvant chemotherapy (NAC).

METHODS

This prospective study included 29 women with histologically proven breast cancer on needle biopsy between July 2016 and July 2019 (age: mean 55 years; range 35-78). Patients underwent WBPET followed by ring-type dbPET and DCE-MRI pre- and post-NAC for preoperative evaluation. pCR was defined as an invasive tumor that disappeared in the breast. Standardized uptake values corrected for lean body mass (SULpeak) were calculated for dbPET and WBPET scans. Maximum tumor length was measured in DCE-MRI images. Reduction rates were calculated for quantitative evaluation. Two radiologists independently evaluated the qualitative findings. Reduction rates and qualitative findings were compared between the pCR (n = 7) and non-pCR (n = 22) groups for each modality. Differences in quantitative and qualitative data between the two groups were analyzed statistically.

RESULTS

Significant differences were observed in the reduction rates of dbPET and DCE-MRI (P = 0.01 and 0.03, respectively) between the two groups. Univariate and multiple logistic regression analyses revealed that SULpeak reduction rates in WBPET and dbPET (P = 0.02 and P = 0.01, respectively) and in dbPET (odds ratio, 16.00; 95% CI 1.57-162.10; P = 0.01) were significant indicators associated with pCR, respectively. No between-group differences were observed in qualitative findings in the three modalities.

CONCLUSION

SULpeak reduction rate of dbPET > 82% was an independent indicator associated with pCR after NAC in breast cancer.

Primary breast cancer patient with poliomyelitis: A case report

BACKGROUND

Poliomyelitis is an acute infection caused by an enterovirus, which primarily infects the human gastrointestinal tract. In general, patients with polio have no association with the occurrence of cancer. The present case study presents a rare case of poliomyelitis combined with primary breast cancer.

CASE SUMMARY

A 61-year-old woman who was diagnosed with poliomyelitis at 5 years old and confirmed invasive breast cancer by core needle biopsy (CNB) after hospitalization. The patient received a modified radical mastectomy and four cycles of chemotherapy with the TC (docetaxel and cyclophosphamide) regimen. The patient was also prescribed endocrine therapy without radiotherapy after chemotherapy. The patient had no evidence of lymphedema in the right upper extremities and no evidence of either regression or distant metastasis at the 1-year follow-up.

CONCLUSION

The pectoral muscles of patients with polio are easily damaged in traumatic procedures, such as CNB, local anesthesia for tumor excision, and general anesthesia for surgery. A CNB, modified radical mastectomy, and four cycles of TC chemotherapy were successfully completed for the present case and the adverse reactions were found to be tolerable. This case may indicate the relationship between breast cancer and polio, and the examination and treatment methods used could be used as a guide for similar cases in the future.

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.

Is the level of diffusion restriction in celiac and cervico-thoracic sympathetic ganglia helpful in their proper recognition on PSMA ligand PET/MR?

AIM

 To check if diffusion weighted imaging (DWI) might be helpful in proper recognition of celiac (CG) and cervicothoracic (CTG) sympathetic ganglia on the whole-body multimodal PSMA-ligand PET/MR imaging, in the view of their common misleading avidity on PET potentially suggestive of malignant lesions, including metastatic lymph nodes.

METHODS

 The thickness and the level of diffusion restriction was assessed qualitatively and quantitatively in 406 sympathetic ganglia (189 CTG in 101 males and 217 CG in 116 males) on DWI maps (b-value 0 and 800 s/mm2) and apparent diffusion coefficient (ADC) maps (mean ADC) of the whole-body PET/MR 68Ga-PSMA-11 PET/MR. To form a reference group of a matching ganglia size, the smallest lymph node was chosen from each patient with metastases and underwent the same procedure.

RESULTS

 Very low and low level of diffusion restriction was noted in the majority of sympathetic ganglia (81.0 % CTG, 67.3 % CG, and 73.6 % of all). In the majority (91.7 %) of metastatic lymph nodes the level of diffusion restriction was moderate to high.The mean ADC values in sympathetic ganglia were statistically significantly higher in CTG, CG and all ganglia than in metastatic lymph nodes (p < 0.001; the effect size was large).

CONCLUSIONS

 Sympathetic celiac and cervicothoracic ganglia present very low and low level of diffusion restriction in visual DWI assessment, and significantly higher than metastatic lymph nodes mean ADC values in the majority of cases, which may serve as additional factors aiding differential diagnosis on multimodal PSMA-ligand PET/MR imaging.Therefore, PSMA-ligand PET/MR appears potentially superior to PSMA-ligand PET/CT in proper identification of sympathetic ganglia.

Role of diffusion-weighted imaging in prediction of nipple-areolar complex invasion by breast cancer

THE AIM OF THIS WORK

The aim of this work was to estimate the role of diffusion-weighted imaging (DWI) in predicting malignant invasion of the nipple-areolar complex (NAC) by underlying breast cancer.

MATERIAL AND METHODS

This prospective study included 70 female patients with breast cancer with a mean age of 45.8 years (range: 28-68). DWI of the breast was done for all patients. Apparent diffusion coefficient (ADC) maps were automatically constructed. The mean ADC values of NAC were independently measured by two observers who are experts in breast imaging and correlated with the results of histopathological examinations.

RESULTS

Both observers found a significantly lower ADC value of malignant NAC invasion (n = 18) when compared with free NAC (n = 52), with mean ADC value for malignant NAC invasion was 0.86 ± 0.35 × 10^-3 mm²/s and 0.84 ± 0.08 × 10^-3 mm²/s for observer one and two respectively versus mean ADC value of 1.34 ± 0.25 × 10^-3 mm²/s and 1.4 ± 0.26 × 10^-3 mm²/s for free NAC by observer one and two respectively (P-value =0.001). Observer one found that a cutoff ADC value of 1.05 × 0^-3 mm²/s can predict malignant NAC invasion with 0.975 AUC, 92.8% accuracy, 94.4% sensitivity, and 92.3% specificity. Observer two found that a cutoff ADC value of 0.95 × 10^-3 mm²/s can predict malignant NAC invasion with 0.992 AUC, 95.7% accuracy, 88.9% sensitivity, and 98.1% specificity.

CONCLUSION

DWI can predict malignant NAC invasion in patients with breast cancer.

Assessment of Tamoxifen-Related Endometrial Changes in Premenopausal Female Patients With Diffusion-Weighted Magnetic Resonance Imaging

PURPOSE

To evaluate tamoxifen-related endometrial changes in premenopausal female patients with diffusion-weighted magnetic resonance imaging (DWI).

METHODS

This prospective study was performed on 71 premenopausal female patients (mean age, 41 years) who were receiving tamoxifen therapy. All patients underwent magnetic resonance imaging with DWI of the pelvis and hysteroscopic-guided endometrial biopsy. The apparent diffusion coefficient (ADC) values of the endometrial plate were calculated and correlated with pathological results.

RESULTS

The mean ADCs of tamoxifen-related benign endometrial lesions (1.35 ± 0.19 and 1.32 ± 0.13 × 10 mm/s) were significantly higher (P = 0.001) than those of normal endometrial plate (0.95 ± 0.11 and 0.93 ± 0.11 × 10 mm/s) by both reviewers, respectively. The cutoff ADC values used to differentiate tamoxifen-related benign endometrial lesions from normal endometrium were 1.07 and 1.02 × 10 mm/s with areas under the curve of 0.94 and 0.93 and accuracy of 94.4 and 95.8 by both reviewers, respectively. The mean ADC values of endometrial polyp (EP) (1.44 ± 0.19 and 1.42 ± 0.22 × 10 mm/s) were significantly higher (P = 0.001) than those of endometrial hyperplasia (EH) (1.25 ± 0.19 and 1.23 ± 0.19 × 10 mm/s) by both reviewers, respectively. The cutoff ADC values used to differentiate EP from EH were 1.38 × 10 and 1.36 × 10 mm/s with areas under the curve of 0.81 and 0.77 and accuracy of 80% and 70% by both reviewers, respectively. There was an insignificant difference in ADC value between typical and atypical EH. The ADC values of endometrial cancer (0.80 and 0.78 × 10 mm/s) were lower than those of tamoxifen-related benign endometrial lesions. The final diagnosis was normal endometrium (n = 36), benign endometrial lesions either EH (n = 17), or EP (n = 16), and endometrial cancer in only 2 patients.

CONCLUSIONS

We concluded that DWI helps in detection and characterization of different tamoxifen-related endometrial changes in the premenopausal female patients.

Prediction of skull base osteomyelitis in necrotising otitis externa with diffusion-weighted imaging

OBJECTIVE

To predict skull base osteomyelitis in patients with necrotising otitis externa using diffusion-weighted imaging.

METHODS

A retrospective analysis was conducted of 25 necrotising otitis externa patients with skull base osteomyelitis (n = 10) or without skull base involvement (n = 14) who underwent a single-shot diffusion-weighted imaging of the skull base.

RESULTS

The respective mean apparent diffusion coefficient values of the skull base, as determined by two reviewers, were 0.851 ± 0.15 and 0.841 ± 0.14 ×10-3mm2/s for the skull base osteomyelitis patients, and 1.065 ± 0.19 and 1.045 ± 0.20 ×10-3mm2/s for the necrotising otitis externa patients without skull base involvement. The difference in apparent diffusion coefficients between the groups was significant, for both reviewers (p = 0.008 and 0.012). The optimal threshold apparent diffusion coefficient for predicting skull base osteomyelitis in necrotising otitis externa patients was 0.945 ×10-3mm2/s and 0.915 ×10-3mm2/s, with an area under the curve of 0.825 and 0.800, accuracy of 87.5 and 83.3 per cent, sensitivity of 85.7 and 90.0 per cent, and specificity of 90.0 and 78.6 per cent, for each reviewer respectively.

CONCLUSION

Apparent diffusion coefficient is a non-invasive imaging parameter useful for predicting skull base osteomyelitis in necrotising otitis externa patients.

Diffusion-weighted magnetic resonance imaging of primary cervical cancer in the detection of sub-centimetre metastatic lymph nodes

BACKGROUND

Magnetic resonance imaging (MRI) has limited accuracy in detecting pelvic lymph node (PLN) metastasis. This study aimed to examine the use of intravoxel incoherent motion (IVIM) in classifying pelvic lymph node (PLN) involvement in cervical cancer patients.

METHODS

Fifty cervical cancer patients with pre-treatment magnetic resonance imaging (MRI) were examined for PLN involvement by one subspecialist and one non-subspecialist radiologist. PLN status was confirmed by positron emission tomography or histology. The tumours were then segmented by both radiologists. Kruskal-Wallis tests were used to test for differences between diffusion tumour volume (DTV), apparent diffusion coefficient (ADC), pure diffusion coefficient (D), and perfusion fraction (f) in patients with no malignant PLN involvement, those with sub-centimetre and size-significant PLN metastases. These parameters were then considered as classifiers for PLN involvement, and were compared with the accuracies of radiologists.

RESULTS

Twenty-one patients had PLN involvement of which 10 had sub-centimetre metastatic PLNs. DTV increased (p = 0.013) while ADC (p = 0.015), and f (p = 0.006) decreased as the nodal status progressed from no malignant involvement to sub-centimetre and then size-significant PLN metastases. In determining PLN involvement, a classification model (DTV + f) had similar accuracies (80%) as the non-subspecialist (76%; p = 0.73) and subspecialist (90%; p = 0.31). However, in identifying patients with sub-centimetre PLN metastasis, the model had higher accuracy (90%) than the non-subspecialist (30%; p = 0.01) but had similar accuracy with the subspecialist (90%, p = 1.00). Interobserver variability in tumour delineation did not significantly affect the performance of the classification model.

CONCLUSION

IVIM is useful in determining PLN involvement but the added value decreases with reader experience.

Measurement of apparent diffusion coefficient in discrimination of benign and malignant axillary lymph nodes

Purpose

We aimed to determine the contribution of the apparent diffusion coefficient (ADC) value in the detection of axillary lymph node metastasis.

Material and methods

Breast magnetic resonance of 58 patients, performed in the radiology clinic of our hospital between 2015 and 2017 were examined retrospectively, and 43 lymph nodes in 43 patients were included in the study. They were evaluated morphologically on T1W and T2W sequences, and the lymph nodes showing rounded shape, focal or diffuse cortical thickness of more than 3 mm, and partial or total effacement of fatty hilum were included in the study. Subsequently, their ADC values were measured.

Results

There were 43 lymph nodes, 20 of which were malignant and 23 of which were benign. While the mean ADC value of malignant axillary lymph nodes was 0.749 10^-3 mm²/s (0.48-1.342), it was 0.982 10^-3 mm²/s (0.552-1.986) for benign lymph nodes. When the ADC cut-off value was taken as ≤ 0.753 × 10^-3 mm²/s, its discrimination power between benign and malignant axillary lymph nodes was as follows: sensitivity - 60%; specificity - 91.3%; accuracy - 76.7%; positive predictive value - 85.7%; and negative predictive value - 72.4%.

Conclusions

There was no significant difference between mean ADC value of 12 lymphadenopathies (LAP) associated with inflammatory breast diseases (granulomatous mastitis and acute suppurative mastitis) and mean ADC value of metastatic lymph nodes. However, the ADC value of lymph nodes showing thickened cortex due to systemic inflammatory diseases was over 1, and there was a statistically significant difference when compared with metastatic lymph nodes.

The kinetic analysis of breast cancer: An investigation of the optimal temporal resolution for dynamic contrast-enhanced MR imaging

INTRODUCTION

There is wide agreement that morphologic features and enhancement kinetics should be evaluated for MRI of the breast, although there has been no clear consensus concerning optimal temporal resolutions. The objective of this study was to investigate the optimal temporal resolution for the kinetic analysis of breast cancers.

METHODS

Thirty-four patients with 34 enhancing lesions of breast cancer who underwent dynamic contrast-enhanced MRI (DCE-MRI) on a 3.0-T scanner were included in this retrospective study. DCE-MRI was performed with an original temporal resolution of 10-s, and the values of pharmacokinetic parameters (Ktrans, Ve, Kep, and area under the curve (AUC)) were compared with selected data of 30-s and 60-s time intervals.

RESULTS

Among the 34 lesions, 10 showed a wash out pattern, 16 showed a plateau pattern, and 8 showed a persistent enhancement pattern. The Ktrans value in the wash-out pattern was significantly higher than that of other time-intensity curve patterns (p < 0.01). The Kep and AUC also showed significant differences between the wash-out pattern and other types (p < 0.01). On comparing the perfusion parameters among different temporal resolutions, simulations showed that only the AUC differed significantly between the data acquired at a 10-s temporal resolution and that acquired at a 60-s time interval (p < 0.01). Although the comparison of the AUC between the 30-s and 60-s data also showed significant differences (p = 0.01), there was no significant difference between the 10-s and 30-s data (p = 0.17).

CONCLUSIONS

DCE-MRI with a temporal resolution of 30-s preserves the kinetic information. Further prospective studies will be needed to investigate the trade-off between temporal and spatial resolution in DCE-MRI.

Whole-body diffusion-weighted imaging with background body signal suppression in the detection of osseous and extra-osseous metastases

Purpose

To assess the reproducibility of detection of osseous and extra-osseous metastases in cancer patients using whole-body diffusion-weighted imaging with background body signal suppression (WB-DWIBS).

Material and methods

A prospective study was conducted on 39 consecutive patients (21 females, 18 males; mean age 48 years) with metastases, who underwent WB-DWIBS on a 1.5-T MR scanner. Image analysis was performed independently by two blinded observers. Inter-observer agreement was assessed for the detection of osseous (spinal, appendicular) and extra-osseous (hepatic, pulmonary, nodal, and peritoneal) metastases.

Results

The overall inter-observer agreement of WB-DWIBS in the detection of osseous and extra-osseous metastases was excellent (κ = 0.887, agreement = 94.44%, p = 0.001). There was excellent inter-observer agreement of both observers for the detection of osseous spinal (κ = 0.846, agreement = 92.3%), osseous appendicular (κ = 0.898, agreement = 94.8 %), hepatic (κ = 0.847, agreement = 92.3%), pulmonary (κ = 0.938, agreement = 97.4%), nodal metastases (κ = 0.856, agreement = 94.9%), and peritoneal metastasis (κ = 0.772, agreement = 94.9%).

Conclusion

We concluded that WB-DWIBS is reproducible for detection of osseous and extra-osseous metastases in cancer patients.

Nodal staging in the rectal cancer follow-up MRI after chemoradiotherapy: use of morphology, size, and diffusion criteria

AIM

To analyse changes in post-neoadjuvant follow-up magnetic resonance imaging (MRI) staging accuracy for malignant adenopathies in rectal cancer, by comparing size criteria with morphological criteria using high-resolution T2-weighted sequences, as well as variations when adding diffusion-weighted imaging.

METHODS AND MATERIALS

The present study was a cross-sectional study of a database including 46 1.5-T MRI examinations (2011-2016) from patients with biopsy-proven rectal cancer and chemoradiotherapy treatment before surgery. All cases were reviewed by three radiologists individually, who were blinded to any clinical information. The radiologists were experienced in rectal cancer (3-6 years) and evaluated the presence of malignant nodes in each patient. Malignancy was determined using morphological, size (5 mm), and diffusion criteria separately, as well as morphology plus diffusion. Each case was assessed four times: (1) evaluation of morphological criteria; (2) size criteria; (3) evaluation only using diffusion (b-values 50, 400, and 800); and (4) diffusion plus morphological criteria. Histological staging of surgical specimens was the reference standard. Statistical analysis included accuracy (area under the receiver operating characteristic [ROC] curve [AUC]), sensitivity, specificity, and positive/negative predictive values (PPV/NPV) for each radiologist, and group agreement (Fleiss' kappa).

RESULTS

Mean values using morphological criteria were: AUC 0.78, sensitivity 77.7%, specificity 73.8%, PPV 66.1%, NPV 85.2%. Using size criterion: AUC 0.75, sensitivity 62.9%, specificity 83.2%, PPV 74.1%, NPV 80%. Added diffusion yielded no improvement, and yielded worse results by itself.

CONCLUSIONS

Although morphological criteria showed better results in accuracy, sensitivity, and NPV, size criterion yielded the best specificity and PPV. Adding diffusion did not demonstrate a clear advantage over the criteria by themselves. Thus, mixed size-morphology criteria could have the greatest diagnostic value for follow-up N-staging.

Risk stratification of triple-negative breast cancer with core gene signatures associated with chemoresponse and prognosis

PURPOSE

Neoadjuvant chemotherapy studies have consistently reported a strong correlation between pathologic response and long-term outcome in triple-negative breast cancer (TNBC). We aimed to define minimal gene signatures for predicting chemoresponse by a three-step approach and to further develop a risk-stratification method of TNBC.

METHODS

The first step involved the detection of genes associated with resistance to docetaxel in eight TNBC cell lines, leading to identification of thousands of candidate genes. Through subsequent second and third step analyses with gene set enrichment analysis and survival analysis using public expression profiles, the candidate gene list was reduced to prognostic core gene signatures comprising ten or four genes.

RESULTS

The prognostic core gene signatures include three up-regulated (CEBPD, MMP20, and WLS) and seven down-regulated genes (ASF1A, ASPSCR1, CHAF1B, DNMT1, GINS2, GOLGA2P5, and SKA1). We further develop a simple risk-stratification method based on expression profiles of the core genes. Relative expression values of the up-regulated and down-regulated core genes were averaged into two scores, Up and Down scores, respectively; then samples were stratified by a diagonal line in a xy plot of the Up and Down scores. Based on this method, the patients were successfully divided into subgroups with distinct chemoresponse and prognosis. The prognostic power of the method was validated in three independent public datasets containing 230, 141, and 117 TNBC patients with chemotherapy. In multivariable Cox regression analysis, the core gene signatures were significantly associated with prognosis independent of tumor stage and age at diagnosis. In meta-analysis, we found that five core genes (CEBPD, WLS, CHAF1B, GINS2, and SKA1) play opposing roles, either tumor promoter or suppressor, in TNBC and non-TNBC tumors respectively, depending on estrogen receptor status.

CONCLUSIONS

The results may provide a promising prognostic tool for predicting chemotherapy responders among TNBC patients prior to initiation of chemotherapeutic treatment.

Deep learning networks find unique mammographic differences in previous negative mammograms between interval and screen-detected cancers: a case-case study

Background

To determine if mammographic features from deep learning networks can be applied in breast cancer to identify groups at interval invasive cancer risk due to masking beyond using traditional breast density measures.

Methods

Full-field digital screening mammograms acquired in our clinics between 2006 and 2015 were reviewed. Transfer learning of a deep learning network with weights initialized from ImageNet was performed to classify mammograms that were followed by an invasive interval or screen-detected cancer within 12 months of the mammogram. Hyperparameter optimization was performed and the network was visualized through saliency maps. Prediction loss and accuracy were calculated using this deep learning network. Receiver operating characteristic (ROC) curves and area under the curve (AUC) values were generated with the outcome of interval cancer using the deep learning network and compared to predictions from conditional logistic regression with errors quantified through contingency tables.

Results

Pre-cancer mammograms of 182 interval and 173 screen-detected cancers were split into training/test cases at an 80/20 ratio. Using Breast Imaging-Reporting and Data System (BI-RADS) density alone, the ability to correctly classify interval cancers was moderate (AUC = 0.65). The optimized deep learning model achieved an AUC of 0.82. Contingency table analysis showed the network was correctly classifying 75.2% of the mammograms and that incorrect classifications were slightly more common for the interval cancer mammograms. Saliency maps of each cancer case found that local information could highly drive classification of cases more than global image information.

Conclusions

Pre-cancerous mammograms contain imaging information beyond breast density that can be identified with deep learning networks to predict the probability of breast cancer detection.

Contrast ultrasound versus ultrasound elastography for diagnosis of breast lumps: A cross-sectional study

Chinese women have dense and small breasts. Therefore, in China, contrast ultrasound and ultrasound elastography are commonly used for detection of the breast lumps. Purpose of the study was to compare the sensitivity and accuracy of ultrasound elastography with contrast ultrasound for the diagnosis of the breast lumps.A total of 1000 women with a damp in breast mass, breast pain, nipple discharge, and/or breast skin discharge were subjected to contrast ultrasound and ultrasound elastography. Women were subjected to stereotactic vacuum-assisted biopsy under B-mode ultrasonography (n = 750). The ultrasound examinations were graded on a 5-points scale method. Data were subjected to the Chi-square Independence test at 99% of confidence level.Ultrasound elastography was detected the same numbers of benign lesions (648 vs 651, P = .88), malignant lesions (90 vs 99, P = .53), and false positive lesions (5 vs 0, P = .07) as those detected by biopsies. However, diagnostic parameters for contrast ultrasound had a significant difference with those detected by biopsies (P < .0001 for all). For contrast ultrasound and ultrasound elastography, the working area to detect deformation in the image of the breast lesions at least 1 time were 0% to 45% and 5% to 100%.Ultrasound elastography is the most reliable diagnostic method for detection of the breast lumps.

Differentiating the lymph node metastasis of breast cancer through dynamic contrast-enhanced magnetic resonance imaging

Objective:

Lymph node metastasis is an important trait of breast cancer, and tumors with different lymph node statuses require various clinical treatments. This study was designed to evaluate the lymph node metastasis of breast cancer through pharmacokinetic and histogram analysis via dynamic contrast-enhanced (DCE) MRI.

Methods and materials:

A retrospective analysis was conducted to quantitatively evaluate the lymph node statuses of patients with breast cancer. A total of 75 patients, i.e. 34 patients with lymph node metastasis and 41 patients without lymph node metastasis, were involved in this research. Of the patients with lymph node metastases, 19 had sentinel lymph node metastasis, and 15 had axillary lymph node metastasis. MRI was conducted using a 3.0 T imaging device. Segmentation was carried out on the regions of interest (ROIs) in breast tumors under DCE-MRI, and pharmacokinetic and histogram parameters were calculated from the same ROIs. Mann–Whitney U test was performed, and receiver operating characteristic curves for the parameters of the two groups were constructed to determine their diagnostic values.

Results:

Pharmacokinetic parameters, including Ktrans, Kep, area under the curve of time–concentration, and time to peak, which were derived from the extended Tofts linear model for DCE-MRI, could highlight the tumor areas in the breast and reveal the increased perfusion. Conversely, the pharmacokinetic parameters showed no significant difference between the patients with and without lymph node metastases. By contrast, the parameters from the histogram analysis yielded promising results. The entropy of the ROIs exhibited the best diagnostic ability between patients with and without lymph node metastases (p < 0.01, area under the curve of receiver operating characteristic = 0.765, specificity = 0.706, sensitivity = 0.780).

Conclusion:

In comparison with the pharmacokinetic parameters, the histogram analysis of the MR images could reveal the differences between patients with and without lymph node metastases. The entropy from the histogram indicated that the diagnostic ability was highly sensitive and specific.

Advances in knowledge:

This research gave out a promising result on the differentiating lymph node metastases through histogram analysis on tumors in DCE-MR images. Histogram could reveal the tumors heterogenicity between patients with different lymph node status.

The incidence of unexpected poor ovarian response in Chinese young women

Unexpected poor ovarian response (UPOR) is a problem for both clinicians and infertile couples, because our understanding of this situation is limited. This article investigated incidence of UPOR in women <35 years with normal ovarian reserve function with further analysis.This is a retrospective study, which included 567 women who accepted their first IVF-ET/ICSI. Based on the number of oocytes retrieved, clinic pregnancy rate of fresh cycle, and cycle cancellation rate of fresh cycle, the included cycles were divided into three groups namely unexpected poor ovarian response (UPOR) (n = 120), for which number of oocytes retrieved was not more than 6; normal ovarian response (NOR) (n = 223), for which number of oocytes retrieved was between 7 and 12; and unexpected high ovarian response (UHOR) (n = 224), for which the number of oocytes retrieved was 13 at least. The comparisons of clinical outcomes and correlated hormones among groups were carried out.The incidence of UPOR in Chinese women is 21.16%. Patient age (χ = 6.177, P = .0129), basic FSH (χ = 20.585, P < .0001), basic LH (χ = 11.689, P = .0006), and AFC (χ = 8.053, P = .0045) might be helpful for diagnosis of UPOR.The basic evaluation of ovarian function may no longer be simplified into normal and abnormal ovarian reserve function; rather, by using a detailed numerical analysis, such as basal FSH and LH levels, the ovarian response to ovulation induction may be predicted to some extent.

Development and Validation of Nomograms Predictive of Axillary Nodal Status to Guide Surgical Decision-Making in Early-Stage Breast Cancer

Purpose: To develop and validate nomogram models using noninvasive imaging parameters with related clinical variables to predict the extent of axillary nodal involvement and stratify treatment options based on the essential cut-offs for axillary surgery according to the ACOSOG Z0011 criteria.

Materials and Methods: From May 2007 to December 2017, 1799 patients who underwent preoperative breast and axillary magnetic resonance imaging (MRI) were retrospectively studied. Patients with data on axillary ultrasonography (AUS) were enrolled. The MRI images were interpreted according to Breast Imaging Reporting and Data system (BI-RADS). Using logistic regression analyses, nomograms were developed to visualize the associations between the predictors and each lymph node (LN) status endpoint. Predictive performance was assessed based on the area under the receiver operating characteristic curve (AUC). Bootstrap resampling was performed for internal validation. Goodness-of-fit of the models was evaluated using the Hosmer-Lemeshow test.

Results: Of 397 early breast cancer patients, 200 (50.4%) had disease-free axilla, 119 (30.0%) had 1 or 2 positive LNs, and 78 (19.6%) had ≥3 positive LNs. Patient age, MRI features (mass margin, LN margin, presence/absence of LN hilum, and LN symmetry/asymmetry), and AUS descriptors (presence of cortical thickening or hilum) were identified as predictors of nodal disease. Nomograms with these predictors showed good calibration and discrimination; the AUC was 0.809 for negative axillary node (N0) vs. any LN metastasis, 0.749 for 1 or 2 involved nodes vs. N0, and 0.874 for ≥3 nodes vs. ≤2 metastatic nodes. The predictive ability of the 3 nomograms with additional pathological variables was significantly greater.

Conclusion: The nomograms could predict the extent of ALN metastasis and facilitate decision-making preoperatively.

Predictive Value of Preoperative Multidetector-Row Computed Tomography for Axillary Lymph Nodes Metastasis in Patients With Breast Cancer

Introduction: Axillary lymph nodes (ALN) status is an essential component in tumor staging and treatment planning for patients with breast cancer. The aim of present study was to evaluate the predictive value of preoperative multidetector-row computed tomography (MDCT) for ALN metastasis in breast cancer patients.

Methods: A total of 148 cases underwent preoperative MDCT examination and ALN surgery were eligible for the study. Logistic regression analysis of MDCT variates was used to estimate independent predictive factors for ALN metastasis. The prediction of ALN metastasis was determined with MDCT variates through receiver operating characteristic (ROC) analysis.

Results: Among the 148 cases, 61 (41.2%) cases had ALN metastasis. The cortical thickness in metastatic ALN was significantly thicker than that in non-metastatic ALN (7.5 ± 5.0 mm vs. 2.6 ± 2.8 mm, P < 0.001). Multi-logistic regression analysis indicated that cortical thickness of >3 mm (OR: 12.32, 95% CI: 4.50–33.75, P < 0.001) and non-fatty hilum (OR: 5.38, 95% CI: 1.51–19.19, P = 0.009) were independent predictors for ALN metastasis. The sensitivity, specificity and AUC of MDCT for ALN metastasis prediction based on combined-variated analysis were 85.3%, 87.4%, and 0.893 (95% CI: 0.832–0.938, P < 0.001), respectively.

Conclusions: Cortical thickness (>3 mm) and non-fatty hilum of MDCT were independent predictors for ALN metastasis. MDCT is a potent imaging tool for predicting ALN metastasis in breast cancer. Future prospective study on the value of contrast enhanced MDCT in preoperative ALN evaluation is warranted.

Diffusion tensor imaging parameters in differentiation recurrent breast cancer from post-operative changes in patients with breast-conserving surgery

AIM OF THE WORK

To investigate mean diffusivity (MD) and fractional anisotropy (FA) measured by diffusion tensor imaging (DTI) as complementary tools to differentiate recurrent breast cancer from post-operative changes in patients with breast-conserving surgery (BCS).

PATIENTS AND METHODS

Prospective study was conducted upon 30 patients with BCS that underwent DTI and dynamic contrast MR imaging. DTI was performed using an axial two-dimensional spin-echo echo-planar imaging sequence. The MD and FA of the lesions were calculated by 2 observers. A single pixel seed isotropic region of interest was placed in the solid part of the tumor on the axial color FA map guided by an enhanced part of the tumor. The final diagnosis was done by biopsy for all patients.

RESULTS

/s) used for differentiation between entities revealed sensitivity (76.9%, 92.3%), specificity (82.4%, 64.7%) and accuracy (80%, 76.7%) of both observers respectively. At ROC curve analysis of FA, the AUC was 0.82 and 0.75 by both observers. The threshold FA (0.82, 0.75) was used for differentiation between entities revealed sensitivity (92.3%, 76.9%), specificity (70.6%, 70.6%) and accuracy of (80.0%, 73.3%) of both observers respectively. There was a strong positive correlation of MD (r = 0.86) and FA (r = 0.73) of both observers. Combined analysis of FA and MD used for differentiation between entities had AUC (0.90, 0.88) revealed sensitivity (92.3%, 92.3%), specificity (82.4%, 70.6%) and accuracy of (86.7%, 80.0%) for both observers respectively.

CONCLUSIONS

Combined analysis of MD and FA of DTI may play an important role as a non-invasive method for differentiation recurrent breast cancer from post-operative changes in patients with BCS.

Upregulated delta-like protein 3 expression is a diagnostic and prognostic marker in endometrial cancer: A retrospective study

Upregulated delta-like protein 3 (DLL3) functions as a Notch ligand and has been a target for cancer therapy. The present study assessed DLL3 expression as a tumor marker for endometrial cancer.RNA-Seq expression data and clinicopathologic records from 545 patients with endometrial cancer were downloaded from The Cancer Genome Atlas database. Mann-Whitney U and logistic regression tests were applied to associate the level of DLL3 expression with clinical variables from the patients. Kaplan-Meier curves and log-rank tests were performed to compare overall survival of patients stratified by different levels of DLL3 expression. Multivariate Cox regression tests were used to analyze independent predictors for endometrial cancer. DLL3 expression was upregulated in endometrial cancer tissues compared to para-carcinoma tissues (P = .0003). High DLL3 expression was associated with the age of patients (odds ratio [OR] = 1.74), advanced stages of the International Federation of Gynecology and Obstetrics system (OR = 2.9), grade III/IV (OR = 5.1), myometrial invasion (OR = 2.2), pelvic involvement (OR = 12.9), and para-aortic lymph node metastasis (OR = 9.9) (all P ≤ .001). Furthermore, upregulated DLL3 expression was also associated with a median overall survival of 112 months (HR = 1.85, confidence internal 1.202-2.846, P = .005). The multivariate analysis showed that DLL3 overexpression and advanced tumor stages, grades, and lymph node metastases were all independent prognostic predictors for endometrial cancer.The DLL3 expression could be a potential and novel tumor marker for early diagnosis and an independent predictor of poor survival for patients with endometrial cancer.

Radial scars/complex sclerosing lesions of the breast: radiologic and clinicopathologic correlation

Background

We investigated the radiologic and clinical findings of radial scar and complex sclerosing lesions, and evaluated the rate of pathologic upgrade and predicting factors.

Methods

From review of our institution’s database from January 2006 to December 2012, we enrolled 82 radial scars/complex sclerosing lesions in 80 women; 51 by ultrasound guided core needle biopsy, 1 by mammography-guided stereotactic biopsy, and 38 by surgical excision. The initial biopsy pathology revealed that 53 lesions were without high risk lesions and 29 were with high risk lesions. Radiologic, clinical and pathological results were analyzed statistically and upgrade rates were calculated.

Results

Of the 82 lesions, 64 (78.0%) were surgically excised. After surgical excision, two were upgraded to DCIS and two were upgraded to lesions with high risk lesions. The rate of radial scar with high risk lesions was significantly higher in the surgical excision group (11.1% vs. 42.2%, p = 0.015), which also demonstrated larger lesion size (10.7 ± 6.5 vs. 7.1 ± 2.6 mm, p = 0.001). The diagnoses with high risk lesions on final pathological results showed older age (52.9 ± 6.0 years vs. 48.4 ± 6.7 years, p = 0.018).

Conclusions

Radial scars with and without high risk lesions showed no statistically significant differences in imaging, and gave relatively low cancer upgrade rates.

Electronic supplementary material

The online version of this article (10.1186/s12880-018-0279-z) contains supplementary material, which is available to authorized users.

Pre-operative stromal stiffness measured by shear wave elastography is independently associated with breast cancer-specific survival

INTRODUCTION

With the increased use of neoadjuvant therapy for breast cancer, there is a need for pre-operative prediction of prognosis. We aimed to assess the prognostic value of tumour stiffness measured by ultrasound shear wave elastography (SWE).

METHODS

A consecutive cohort of patients with invasive breast cancer underwent breast ultrasound (US) including SWE. The following were recorded prospectively: US diameter, stiffness at SWE, presentation source, core biopsy grade, oestrogen receptor (ER) status and pre-operative nodal status. Breast cancer-specific survival (BCSS) was analysed with regard to US size and stiffness, tumour grade on core biopsy, ER status, presentation mode and pre-operative nodal status. Analysis used Cox proportional hazards regression.

RESULTS

Of the 520 patients, 42 breast cancer and 53 non-breast cancer deaths were recorded at mean follow-up of 5.4 years. Hazard ratios (HR) for tertiles of stiffness were 1, 4.8 and 8.1 (P = 0.0001). HR for 2 groups based on US size < or ≥ 20 mm were 1 and 5.1 (P < 0.0001). HR for each unit increase in tumour grade on core biopsy was 3.9 (P < 0.0001). The HR for ER positivity compared to ER negativity was 0.21 (P < 0.001). BCSS was also associated with presentation mode and pre-operative nodal status. In a multivariable model, stiffness, US size and ER status were independently associated with BCSS.

CONCLUSION

Multiple pre-operative factors including stromal stiffness at SWE have independent prognostic significance. A larger dataset with longer follow-up could be used in the future to construct a pre-operative prognostic model to guide treatment decisions.

Prognostic impact of skeletal muscle volume derived from cross-sectional computed tomography images in breast cancer

PURPOSE

This study aimed to determine whether the prognosis of breast cancer is affected by muscle or fat volume as measured from computed tomography (CT) images.

METHODS

We identified 1460 patients with chest CT who were diagnosed as having breast cancer at the National Cancer Center, Korea, between January 2001 and December 2009. Using CT images of 10-mm slices, we measured the cross-sectional areas of skeletal muscle and adipose tissue at the 3rd lumbar vertebrae, and derived their volumes. The skeletal muscle volume, fat volume, and muscle-to-fat ratio were evaluated for association with overall survival (OS) and recurrence-free survival (RFS).

RESULTS

The median skeletal muscle and fat volumes among the patients were 93.3 cc (range 39.6-236.9) and 420.1 cc (range 19.5-1392.3), respectively. Patients with higher muscle volume had better prognosis than those with lower muscle volume [hazard ratio (HR) 0.56, 95% confidence interval (CI) 0.34-0.92, P = 0.022 for OS; HR 0.72, 95% CI 0.52-0.99, P = 0.046 for RFS]. However, body mass index (BMI) and fat volume were not associated with prognosis. In addition, muscle volume was a significant prognosticator for OS, regardless of BMI (HR 0.55, 95% CI 0.32-0.93, P = 0.034 in BMI < 25.0; HR 0.44, 95% CI 0.21-0.91, P = 0.026 in BMI ≥ 25.0). Among older patients (≥ 50), those with higher muscle volume showed better OS and RFS (HR 0.44, 95% CI 0.23-0.85, P = 0.015; HR 0.55, 95% CI 0.34-0.90, P = 0.017, respectively).

CONCLUSION

This study demonstrated that breast cancer patients with higher skeletal muscle volume showed more favorable prognosis.

Quantitative evaluation of intravoxel incoherent motion diffusion-weighted imaging (IVIM) for differential diagnosis and grading prediction of benign and malignant breast lesions

BACKGROUND

That breast carcinoma is the most common malignant lesion in women. This study aimed to differentiate benign from malignant breast lesions and to predict grading of the latter by comparing the diagnostic value of different parameters in intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI).

MATERIALS AND METHODS

Retrospective analysis was performed utilizing imaging and pathological data from 112 patients with 124 breast lesions that underwent IVIM-DWI examination with 3.0 T MRI. Out of 124, 47 benign and 77 malignant lesions were confirmed by pathological diagnosis. The diagnostic performance of f, D, and D* value to distinguish benign from malignant breast lesions, was evaluated using pathological results as the gold standard. Correlation between D value and Ki-67 index was evaluated to predict grading of malignant breast lesions.

RESULTS

The D value (0.99 ± 0.21) of patients with malignant lesions was significantly lower than that (1.34 ± 0.18) of patients harboring benign lesions (P = .00). The D* value (7.60 ± 2.10) in malignant lesion group was higher than that (6.83 ± 2.13) of the benign lesion group (P = .113). The f value (8.50 ± 2.13) in malignant lesion group was remarkably higher than that (7.68 ± 1.98) of benign lesion group (P = .035). For differential diagnosis of benign from malignant breast lesions, optimal diagnostic threshold of D value and f value were 1.21 and 7.86, respectively. The areas of D and f values under the ROC curve were 0.883 and 0.601, respectively. The sensitivity, specificity, and accuracy of D value were 83.0%, 86.7%, and 85.5%, respectively. Accordingly, those indexes of f value were 64.9%, 57.4%, and 62.1%, respectively. Furthermore, the Ki-67 staining index of malignant lesions was robustly negatively correlated with D value (r = -0.395, P < .01).

CONCLUSION

Concrete parameters of IVIM-DWI can help to improve the specificity and accuracy in differential diagnosis of breast benign and malignant lesions. D value is most relevant and valuable in predicting the grading of malignant breast lesions.

Intravoxel incoherent motion diffusion-weighted magnetic resonance imaging in characterization of axillary lymph nodes: Preliminary animal experience

PURPOSE

To investigate the diagnostic value of intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) for discriminating axillary metastatic from non-metastatic lymph nodes (LNs) in rabbit models.

MATERIALS AND METHODS

The institutional animal care and use committee approved this study. Forty New Zealand white rabbits were randomly divided into two groups. The axillary LN models were created by inoculating VX2 cell suspension and complete Freund's adjuvant in the mammary glands of 20 female rabbits of each group, respectively. Conventional MRI and IVIM DWI were performed after animal models successfully established. Images of axillary LNs were analyzed with regard to long-axis diameter (L), short-axis diameter (S), apparent diffusion coefficient (ADC) and IVIM parameters (D, D*, f). Receiver operating characteristic analyses were conducted to determine the diagnostic performance of aforementioned criteria.

RESULTS

A total of 42 metastatic and 30 non-metastatic LNs were successfully isolated. ADC and D of metastatic LNs were significantly lower than those of non-metastatic ones (all P < 0.001), whereas D* was statistically higher (P = 0.033). L, S, and f showed no significant difference between the two groups (P = 0.089, 0.058, 0.054, respectively). Optimal cutoff values, area under the curve, sensitivity, and specificity for differentiation were as follows: ADC = 1.101 × 10^-3 mm²/s, 0.886, 78.6%, 90.0%; D = 0.938 × 10^-3 mm²/s, 0.927, 83.3%, 93.3%; and D* = 12.635 × 10^-3 mm²/s, 0.657, 52.4%, 80.0%.

CONCLUSION

IVIM DWI is useful to distinguish metastatic from non-metastatic LNs in axilla. D was the most discriminative variable for predicting metastatic LNs.

Developments in Breast Imaging: Update on New and Evolving MR Imaging and Molecular Imaging Techniques

This article reviews new developments in breast imaging. There is growing interest in creating a shorter, less expensive MR protocol with broader applicability. There is an increasing focus on and consideration for the additive impact that functional analysis of breast pathology have on identifying and characterizing lesions. These developments apply to MR imaging and molecular imaging. This article reviews evolving breast imaging techniques with attention to strengths, weaknesses, and applications of these approaches. We aim to give the reader familiarity with the state of current developments in the field and to increase awareness of what to expect in breast imaging.

Computed Tomography Assessment of Hepatic Metastases of Breast Cancer with Revised Response Evaluation Criteria in Solid Tumors (RECIST) Criteria (Version 1.1): Inter-Observer Agreement

Background

To assess inter-observer agreement of revised RECIST criteria (version 1.1) for computed tomography assessment of hepatic metastases of breast cancer.

Material/Methods

A prospective study was conducted in 28 female patients with breast cancer and with at least one measurable metastatic lesion in the liver that was treated with 3 cycles of anthracycline-based chemotherapy. All patients underwent computed tomography of the abdomen with 64-row multi- detector CT at baseline and after 3 cycles of chemotherapy for response assessment. Image analysis was performed by 2 observers, based on the RECIST criteria (version 1.1).

Results

Computed tomography revealed partial response of hepatic metastases in 7 patients (25%) by one observer and in 10 patients (35.7%) by the other observer, with good inter-observer agreement (k=0.75, percent agreement of 89.29%). Stable disease was detected in 19 patients (67.8%) by one observer and in 16 patients (57.1%) by the other observer, with good agreement (k=0.774, percent agreement of 89.29%). Progressive disease was detected in 2 patients (7.2%) by both observers, with perfect agreement (k=1, percent agreement of 100%). The overall inter-observer agreement in the CT-based response assessment of hepatic metastasis between the two observers was good (k=0.793, percent agreement of 89.29%).

Conclusions

We concluded that computed tomography is a reliable and reproducible imaging modality for response assessment of hepatic metastases of breast cancer according to the RECIST criteria (version 1.1).

Use of Breast Magnetic Resonance Imaging and Ultrasonography for Identifying Nonpalpable Axillae Metastases in Newly Diagnosed Breast Cancer Patients

BACKGROUND

The metastasis of axillary lymph node (ALNs) is a critical step in the initial cancer staging of newly diagnosed breast cancer (BC) patients. Various imaging modalities can enhance the sensitivity of clinical examination in assessing the ALN status.

PATIENTS AND METHODS

We enrolled 135 patients with BC, confirmed via histopathology, including 4 bilateral BC cases. A total of 139 ipsilateral ALNs adjacent to the breast lesion were examined via physical examination, ultrasonography (US), and magnetic resonance imaging (MRI); of these, 100 were nonpalpable ALNs, as determined by experienced breast surgeons and physicians. The relative size parameters on MRI and US images were recorded. Receiver operating characteristic (ROC) analyses were conducted, and the area under the ROC curve (AUC) was compared.

RESULTS

Of 139 ALNs, 67 (48%) were malignant and 72 (52%) were benign on pathological examination. In all of the ALNs, the US short diameter appeared to be the most discriminative quantitative measurement for detecting positive findings (AUC, 0.854). In nonpalpable ALNs as well, the US short diameter exhibited the greatest discriminability (AUC, 0.746). However, the 2-dimensional and 3-dimensional parameters on MRI did not exhibit any significant differences between the enrolled and nonpalpable ALNs (P > .05).

CONCLUSION

The shortest diameter on US exhibited better discriminative ability than MRI for predicting positive ALNs in nonpalpable axillae. Moreover, the 2-dimensional and 3-dimensional parameters on MRI did not differ in terms of discriminability.

Diagnostic Value of Diffusion Weighted Magnetic Resonance Imaging in Evaluation of Metastatic Axillary Lymph Nodes in a Sample of Iranian Women with Breast Cancer

Objective:

To evaluate the diagnostic value of diffusion weighted magnetic resonance imaging (DW-MRI) in assessment of metastases in axillary lymph nodes (ALNs) in a sample of Iranian women with breast cancer.

Methods:

A total of 50 axillary lymph nodes from 30 female patients with histologically verified breast cancer were assessed by 1.5 T MRI. DWI was implemented at b-values of 50, 400 and 800 s/mm². Short axis diameter, presence of fatty hilum and apparent diffusion coefficient (ADC) values (min, max and mean) of metastatic and non-metastatic ALNs was compared. Cutoff ADC values to discriminate between benign and malignant axillary lymph nodes were analyzed with receiver coefficient characteristic (ROC) curves.

Result:

The final histopathological examination revealed 46% (n=23) metastatic and 54% (n=27) non-metastatic ALNs. There was no statistically significant difference in short axis diameter between the two groups (p = 0.537). However there was significantly correlation between loss of fatty hilum and presence of metastases (p < 0.001) and ADC values (0.255 ± 0.19×10^-3 mm²/s vs 0.616 ±0.3×10^-3 mm²/s (ADC min), 1.088 ± 0.22×10^-3 mm²/s vs 1.497 ± 0.24×10^-3 mm²/s (ADC max) and 0.824 ± 0.103 ×10^-3 mm²/s vs 1.098 ± 0.23 ×10^-3 mm²/s (ADC mean)) of metastatic ALNs were significantly lower than those of non-metastatic ALNs (p < 0.001). The optimal mean ADC cut-off value for differentiation between metastatic and non-metastatic ALNs was 0.904×10^-3 mm²/s which had a higher specificity (88.9%) and accuracy (91.8%) as compared with ADC min and ADC max.

Conclusion:

DWI-MRI and ADC values are promising imaging methods which can assess metastatic ALNs in breast cancer with high sensitivity, specificity and accuracy.