Meta analysis of lymph node metastasis of breast cancer patients: Clinical value of DWI and ADC value

Non-contrast Breast MR Imaging

Considering the high cost of dynamic contrast-enhanced MR imaging and various contraindications and health concerns related to administration of intravenous gadolinium-based contrast agents, there is emerging interest in non-contrast-enhanced breast MR imaging. Diffusion-weighted MR imaging (DWI) is a fast, unenhanced technique that has wide clinical applications in breast cancer detection, characterization, prognosis, and predicting treatment response. It also has the potential to serve as a non-contrast MR imaging screening method. Standardized protocols and interpretation strategies can help to enhance the clinical utility of breast DWI. A variety of other promising non-contrast MR imaging techniques are in development, but currently, DWI is closest to clinical integration, while others are still mostly used in the research setting.

Breast MRI Segmentation and Ki-67 High- and Low-Expression Prediction Algorithm Based on Deep Learning

Background and Objective. Breast cancer is a common malignant tumor that seriously threatens the health of women in my country and even around the world. The proliferation marker Ki-67 has been utilized to distinguish luminal B from luminal A tumors and is a reliable indicator of more aggressive breast cancer growth. If a reliable prediction method for breast cancer patients to avoid invasive damage can be found to predict Ki-67 before pathological examination, it will be very beneficial for doctors to formulate later treatment plans and provide more useful treatment options. Methodology. This paper proposes a tumor segmentation and prediction framework based on the combination of improved attention U-Net and SVM. The framework first improves on attention U-Net by introducing coefficients for learning multidimensional attention. Make the attention mechanism more aware of the main situation in the segmentation process. At the same time, the segmented breast MRI results and corresponding labels were input into the SVM classifier to accurately predict the expression of Ki-67. Results. The DSC, PPV, and sensitivity of our combined model are 0.94, 0.93, and 0.94, respectively, with better segmentation performance. And we compare with the segmentation frameworks of other papers and find that our combined model can make accurate segmentation of breast tumors. Conclusion. Our method can adapt to the variability of breast tumors and segment breast tumors accurately and efficiently. In the future, it can be widely used in clinical practice, so as to help the clinic better formulate a reasonable diagnosis and treatment plan for breast cancer patients.

ACR Appropriateness Criteria® Imaging of the Axilla

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

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%.

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

Background

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

Methods

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

Results

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

Conclusion

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

Apparent diffusion coefficient cannot discriminate metastatic and non-metastatic lymph nodes in rectal cancer: a meta-analysis

BACKGROUND

Our aim was to provide data regarding use of diffusion-weighted imaging (DWI) for distinguishing metastatic and non-metastatic lymph nodes (LN) in rectal cancer.

METHODS

MEDLINE library, EMBASE, and SCOPUS database were screened for associations between DWI and metastatic and non-metastatic LN in rectal cancer up to February 2021. Overall, 9 studies were included into the analysis. Number, mean value, and standard deviation of DWI parameters including apparent diffusion coefficient (ADC) values of metastatic and non-metastatic LN were extracted from the literature. The methodological quality of the studies was investigated according to the QUADAS-2 assessment. The meta-analysis was undertaken by using RevMan 5.3 software. DerSimonian, and Laird random-effects models with inverse-variance weights were used to account the heterogeneity between the studies. Mean DWI values including 95% confidence intervals were calculated for metastatic and non-metastatic LN.

RESULTS

ADC values were reported for 1376 LN, 623 (45.3%) metastatic LN, and 754 (54.7%) non-metastatic LN. The calculated mean ADC value (× 10^-3 mm²/s) of metastatic LN was 1.05, 95%CI (0.94, 1.15). The calculated mean ADC value of the non-metastatic LN was 1.17, 95%CI (1.01, 1.33). The calculated sensitivity and specificity were 0.81, 95%CI (0.74, 0.89) and 0.67, 95%CI (0.54, 0.79).

CONCLUSION

No reliable ADC threshold can be recommended for distinguishing of metastatic and non-metastatic LN in rectal 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.

Diffusion MRI of the breast: Current status and future directions

Diffusion-weighted imaging (DWI) is increasingly being incorporated into routine breast MRI protocols in many institutions worldwide, and there are abundant breast DWI indications ranging from lesion detection and distinguishing malignant from benign tumors to assessing prognostic biomarkers of breast cancer and predicting treatment response. DWI has the potential to serve as a noncontrast MR screening method. Beyond apparent diffusion coefficient (ADC) mapping, which is a commonly used quantitative DWI measure, advanced DWI models such as intravoxel incoherent motion (IVIM), non-Gaussian diffusion MRI, and diffusion tensor imaging (DTI) are extensively exploited in this field, allowing the characterization of tissue perfusion and architecture and improving diagnostic accuracy without the use of contrast agents. This review will give a summary of the clinical literature along with future directions. Level of Evidence: 5 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;52:70-90.

Z-Score transformation of ADC values: A way to universal cut off between malignant and benign lymph nodes

PURPOSE

To determine the possibility of a universal cut off value between benign and malignant lymph nodes in patients with tumour by Z-Score transformation method.

MATERIALS AND METHODS

Diffusion weighted imaging, ADC measurements of malignant and benign lymph nodes of 6 studies (4 body parts), conducted for 5 times, in two institutions with variable technical details were analyzed in their original value as well as the standardized Z-Score value. The standardized Z-Score value was obtained by subtracting the population mean of the control group from an individual raw score and then dividing the difference by the population standard deviation of the control group. General cut off values were obtained by both Mega-analysis by receiver operator characteristic curve analysis, when data from the 6 studies were combined and Meta-analysis with weighting coefficients and cut off values of the six individual studies. Sensitivity, specificity and accuracy with cut offs from individual studies, meta-analysis and mega-analysis were calculated. Kappa test was performed to assess the consistency of diagnostic test accuracy, between optimized cut offs of individual studies and the proposed universal cut offs obtained from meta-analysis and mega-analysis.

RESULTS

The ADC values of benign and malignant lymph nodes are significantly different, but with large overlap across the studies. The overlap can be minimized by Z-Score transformation. The result of ROC analysis of the collective Z-Score transformed ADC values of 6 studies was superior to that of the collective original ADC values (sensitivity: 87.4% versus 67.2%, specificity: 90.5% versus 87.9%, accuracy: 89.6% versus 81.4%). The universal Z-Score cut off from Meta-analysis is also better than the original ADC cut off (sensitivity: 82.8% versus 76.3%, specificity 92.6% versus 62.9%, accuracy 89.6% versus 67.1%). Applied to the individual studies, the universal transformed Z-Score cut offs produced superior consistency with the individual optimal cut offs (individual and meta Z-Score: 0.7228-0.9793; individual and mega Z-Score: 0.7111-0.9169) compared with the universal original ADC cut offs (individual and meta ADC: 0.3030-1.0000; individual and mega ADC 0.3268-0.9618).

CONCLUSION

Z-Score transformation could minimize inter-study variations due to heterogeneity of MR systems and sequence parameters, and provide a more consistent universal cut off value between benign and malignant nodes across studies.

Diffusion-weighted breast imaging

Magnetic resonance imaging (MRI) of the breast represents one of the most sensitive imaging modalities in breast cancer detection. Diffusion-weighted imaging (DWI) is a sequence variation introduced as a complementary MRI technique that relies on mapping the diffusion process of water molecules thereby providing additional information about the underlying tissue. Since water diffusion is more restricted in most malignant tumors than in benign ones owing to the higher cellularity of the rapidly proliferating neoplasia, DWI has the potential to contribute to the identification and characterization of suspicious breast lesions. Thus, DWI might increase the diagnostic accuracy of breast MRI and its clinical value. Future applications including optimized DWI sequences, technical developments in MR devices, and the application of radiomics/artificial intelligence algorithms may expand the potential of DWI in breast imaging beyond its current supplementary role.

Accuracy of Whole-Body DWI for Metastases Screening in a Diverse Group of Malignancies: Comparison With Conventional Cross-Sectional Imaging and Nuclear Scintigraphy

OBJECTIVE

The purpose of this study is to assess the role of whole-body (WB) DWI as a screening modality for the detection of metastases and to compare it to conventional cross-sectional imaging modalities or nuclear scintigraphy in a population with various histopathologic malignancies.

SUBJECTS AND METHODS

WB DWI and conventional imaging (CT, MRI, or scintigraphy) were performed for patients with known malignancies for metastatic workup, and these patients were followed up for a period of 1 year. Two radiologists assessed WB DW images separately, and conventional images were assessed by the senior radiologist. The metastatic lesions were classified into four regions: liver, lung, skeletal system, and lymph nodes. The reference standard was considered on the basis of histopathologic confirmation or clinical follow-up of the metastatic lesions.

RESULTS

WB DWI was slightly inferior to conventional imaging modalities for the detection of hepatic metastases (sensitivity, 86.6% vs 93.3%; specificity, 91.6% vs 95.8%; and accuracy, 89.7% vs 94.8%) and skeletal metastases (sensitivity, 81.8% vs 89.4%; specificity, 86.4% vs 94.3%; and accuracy, 85.2% vs 93.0%); however, the differences were not statistically significant (p = 0.625 for hepatic metastases and p = 0.0953 for skeletal metastases, McNemar test). WB DWI was statistically significantly inferior to conventional imaging for the detection of lymph node metastases (sensitivity, 74.0% vs 81.5%; specificity, 87.9% vs 90.1%; accuracy, 81.4% vs 86.0%; p = 0.0389). WB DWI was statistically significantly inferior to conventional imaging for the detection of pulmonary metastases (sensitivity, 33.3% vs 100.0%; specificity, 90.9% vs 100.0%; accuracy, 60.8% vs 100.0%; p = 0.045).

CONCLUSION

WB DWI can be used for screening hepatic and skeletal metastases, but its reliability as the sole imaging sequence for the detection of lymph nodal and pulmonary metastases is poor and, at present, it cannot replace conventional imaging modalities.

Diffusion-weighted breast MRI: Clinical applications and emerging techniques

Diffusion-weighted MRI (DWI) holds potential to improve the detection and biological characterization of breast cancer. DWI is increasingly being incorporated into breast MRI protocols to address some of the shortcomings of routine clinical breast MRI. Potential benefits include improved differentiation of benign and malignant breast lesions, assessment and prediction of therapeutic efficacy, and noncontrast detection of breast cancer. The breast presents a unique imaging environment with significant physiologic and inter-subject variations, as well as specific challenges to achieving reliable high quality diffusion-weighted MR images. Technical innovations are helping to overcome many of the image quality issues that have limited widespread use of DWI for breast imaging. Advanced modeling approaches to further characterize tissue perfusion, complexity, and glandular organization may expand knowledge and yield improved diagnostic tools.

LEVEL OF EVIDENCE

5 J. Magn. Reson. Imaging 2016 J. Magn. Reson. Imaging 2017;45:337-355.