Introduction of a Contrast Enhanced Breast Mammography service in place of existing breast MRI service: A costing analysis

Abstract Contrast-enhanced mammography (CEM) is a promising new imaging modality that uses a dual-energy acquisition to provide both morphologic and vascular assessment of breast lesions. Although no official BI-RADS lexicon exists, interpretation entails using the mammographic BI-RADS lexicon in combination with that for breast MRI. CEM has comparable performance to breast MRI, with sensitivity of 93–100% and specificity of 80–94%. Currently FDA approved for diagnostic imaging, this technology can be helpful in determining disease extent in patients with newly diagnosed breast malignancy, monitoring response to neoadjuvant therapy, identifying mammographically occult malignancies, and diagnostic problem-solving. Studies are ongoing about its role in screening, especially in women with dense breasts or at elevated risk. There are some challenges to successful implementation into practice, but overall, patients tolerate the study well, and exam times are less than the full breast MRI protocol.

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Detection and Diagnosis of Breast Cancer Using Artificial Intelligence Based Assessment of Maximum Intensity Projection Dynamic Contrast-Enhanced Magnetic Resonance Images

Diagnostics ◽

10.3390/diagnostics10050330 ◽

2020 ◽

Vol 10 (5) ◽

pp. 330

Author(s):

Mio Adachi ◽

Tomoyuki Fujioka ◽

Mio Mori ◽

Kazunori Kubota ◽

Yuka Kikuchi ◽

...

Keyword(s):

Artificial Intelligence ◽

Magnetic Resonance ◽

Diagnostic Performance ◽

Maximum Intensity Projection ◽

Breast Mri ◽

Magnetic Resonance Images ◽

Maximum Intensity ◽

Validation Data ◽

Dynamic Contrast Enhanced ◽

Contrast Enhanced

We aimed to evaluate an artificial intelligence (AI) system that can detect and diagnose lesions of maximum intensity projection (MIP) in dynamic contrast-enhanced (DCE) breast magnetic resonance imaging (MRI). We retrospectively gathered MIPs of DCE breast MRI for training and validation data from 30 and 7 normal individuals, 49 and 20 benign cases, and 135 and 45 malignant cases, respectively. Breast lesions were indicated with a bounding box and labeled as benign or malignant by a radiologist, while the AI system was trained to detect and calculate possibilities of malignancy using RetinaNet. The AI system was analyzed using test sets of 13 normal, 20 benign, and 52 malignant cases. Four human readers also scored these test data with and without the assistance of the AI system for the possibility of a malignancy in each breast. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were 0.926, 0.828, and 0.925 for the AI system; 0.847, 0.841, and 0.884 for human readers without AI; and 0.889, 0.823, and 0.899 for human readers with AI using a cutoff value of 2%, respectively. The AI system showed better diagnostic performance compared to the human readers (p = 0.002), and because of the increased performance of human readers with the assistance of the AI system, the AUC of human readers was significantly higher with than without the AI system (p = 0.039). Our AI system showed a high performance ability in detecting and diagnosing lesions in MIPs of DCE breast MRI and increased the diagnostic performance of human readers.

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Screening Breast MRI and Gadolinium Deposition: Cause for Concern?

Journal of Breast Imaging ◽

10.1093/jbi/wbab074 ◽

2021 ◽

Author(s):

Colleen H Neal

Keyword(s):

Breast Cancer ◽

Renal Function ◽

Contrast Agents ◽

Biological Significance ◽

Breast Mri ◽

Reliable Data ◽

Breast Cancer Data ◽

Cancer Data ◽

Contrast Enhanced ◽

Gadolinium Retention

Abstract Gadolinium-based contrast agents (GBCAs) have been used worldwide for over 30 years and have enabled lifesaving diagnoses. Contrast-enhanced breast MRI is frequently used as supplemental screening for women with an elevated lifetime risk of breast cancer. Data have emerged that indicate a fractional amount of administered gadolinium is retained in the bone, skin, solid organs, and brain tissues of patients with normal renal function, although there are currently no reliable data regarding the clinical or biological significance of this retention. Linear GBCAs are associated with a higher risk of gadolinium retention than macrocyclic agents. Over the course of their lives, screened women may receive high cumulative doses of GBCA. Therefore, as breast MRI screening utilization increases, thoughtful use of GBCA is indicated in this patient population.

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Variable spatiotemporal resolution three-dimensional dixon sequence for rapid dynamic contrast-enhanced breast MRI

Journal of Magnetic Resonance Imaging ◽

10.1002/jmri.24797 ◽

2014 ◽

Vol 40 (6) ◽

pp. spcone-spcone

Author(s):

Manojkumar Saranathan ◽

Dan W. Rettmann ◽

Brian A. Hargreaves ◽

Jafi A. Lipson ◽

Bruce L. Daniel

Keyword(s):

Three Dimensional ◽

Breast Mri ◽

Spatiotemporal Resolution ◽

Dynamic Contrast Enhanced ◽

Contrast Enhanced

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Characterization of Metastatic Sternal Lesions on Dynamic Contrast-Enhanced Breast MRI in Women with Invasive Breast Cancer

Academic Radiology ◽

10.1016/j.acra.2018.11.011 ◽

2019 ◽

Vol 26 (10) ◽

pp. 1358-1362

Author(s):

Amie Y. Lee ◽

Ryan Navarro ◽

Lindsay P. Busby ◽

Heather I. Greenwood ◽

Matthew D. Bucknor ◽

...

Keyword(s):

Breast Cancer ◽

Invasive Breast Cancer ◽

Breast Mri ◽

Dynamic Contrast Enhanced ◽

Contrast Enhanced

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Association between breast cancer’s prognostic factors and 3D textural features of non-contrast-enhanced T1-weighted breast MRI

British Journal of Radiology ◽

10.1259/bjr.20210702 ◽

2021 ◽

Author(s):

Anni Lepola ◽

Otso Arponen ◽

Hidemi Okuma ◽

Kirsi Holli-Helenius ◽

Heikki Junkkari ◽

...

Keyword(s):

Prognostic Factors ◽

Texture Analysis ◽

Proportional Hazards Model ◽

Histological Grade ◽

Prognostic Index ◽

Disease Free Survival ◽

Breast Mri ◽

Cox Proportional Hazards Model ◽

Tumour Grade ◽

Contrast Enhanced

Objectives: The aim of this exploratory study was to evaluate whether three-dimensional texture analysis (3D-TA) features of non-contrast-enhanced T1-weighted MRI associate with traditional prognostic factors and disease-free survival (DFS) of breast cancer. Methods: 3D-T1-weighted images from 78 patients with 81 malignant histopathologically verified breast lesions were retrospectively analysed using standard-size volumes of interest. Grey-level co-occurrence matrix (GLCM) based features were selected for statistical analysis. In statistics the Mann–Whitney U and the Kruskal–Wallis tests, the Cox proportional hazards model and the Kaplan-Meier method were used. Results: Tumours with higher histological grade were significantly associated with higher contrast (1voxel: p = 0.033, two voxels: p = 0.036). All the entropy parameters showed significant correlation with tumour grade (p = 0.015–0.050) but there were no statistically significant associations between other TA parameters and tumour grade. The Nottingham Prognostic Index (NPI) was correlated with contrast and sum entropy parameters. A higher sum variance TA parameter was a significant predictor of shorter DFS. Conclusion: Texture parameters, assessed by 3D-TA from non-enhanced T1-weighted images, indicate tumour heterogeneity but have limited independent prognostic value. However, they are associated with tumour grade, NPI, and DFS. These parameters could be used as an adjunct to contrast-enhanced TA parameters. Advances in knowledge: 3D texture analysis of non-contrast enhanced T1-weighted breast MRI associates with tumour grade, NPI, and DFS. The use of non-contrast 3D TA parameters in adjunct with contrast-enhanced 3D TA parameters warrants further research.

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BIRADS 4 breast lesions: comparison of contrast-enhanced spectral mammography and contrast-enhanced MRI

Egyptian Journal of Radiology and Nuclear Medicine ◽

10.1186/s43055-019-0043-6 ◽

2019 ◽

Vol 50 (1) ◽

Cited By ~ 2

Author(s):

Rabab Yasin ◽

Enas Abd El Ghany

Keyword(s):

Breast Cancer ◽

Developing Countries ◽

Statistical Significance ◽

Breast Mri ◽

Excision Biopsy ◽

Breast Lesions ◽

Common Cancer ◽

Contrast Enhanced ◽

Histopathological Result ◽

Contrast Enhanced Mri

Abstract Background Breast cancer is the most common cancer in women worldwide. It is responsible for about 23% of cancer in females in both developed and developing countries [1]. We aimed to assess the accuracy of contrast-enhanced spectral mammography (CESM) versus contrast-enhanced breast MRI in the evaluation of BIRADS 4 breast lesions. Results Fifty patients were included in this study; there were 28 malignant cases and 22 benign cases; all cases were proved by histopathological result either by core biopsy or excision biopsy. CESM was found to have less sensitivity (94.1%) than MRI (100%) but CESM has higher specificity (100%) than MRI (95.5%). The accuracy of CESM was 96.4%, while the accuracy of MRI was 98.2% with no statistical significance (P value 0.827). Conclusion CESM can be used as a sensitive diagnostic tool in the detection and staging of breast cancer with higher specificity and less sensitivity as compared to contrast enhanced breast MRI.

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Evaluation of Shimming Techniques on MRI Breast Image Quality at 1.5T

Journal of Breast Imaging ◽

10.1093/jbi/wbz045 ◽

2019 ◽

Vol 1 (3) ◽

pp. 199-204

Author(s):

Wei Zhou ◽

Christopher P Favazza ◽

Jessica A Axmacher ◽

Joshua D Trzasko ◽

Jennifer R Geske ◽

...

Keyword(s):

Image Quality ◽

Statistical Significance ◽

Breast Mri ◽

Fat Saturation ◽

Institutional Review ◽

Breast Image ◽

Contrast Enhanced ◽

Preparatory Phase ◽

Clinical Mri

Abstract Objective The quality of all clinical MRI is dependent on B0 homogeneity, which is optimized during the shimming part of a prescan or preparatory phase before image acquisition. The purpose of this study was to assess shimming techniques clinically employed for breast MRI across our practice, and to determine factors that correlate with higher image quality for contrast-enhanced breast MRI at 1.5T. Methods One hundred consecutive female patients were retrospectively collected with Institutional Review Board approval. Shimming-related parameters, including shim-box placement and shimming gradient offsets were extracted from prior contrast-enhanced 3D fat-suppressed T1-weighted gradient echo image acquisitions. Three breast radiologists evaluated these images for fat saturation, breast density, overall image quality, and artifacts. Technologist experience was also evaluated for variability of shimming. Generalized linear mixed models were used to compare acquisition parameters between fat saturation. P < 0.05 was considered as statistical significance. Results The percentage of soft tissue inside the field of view (FOV) (ie, Tissue/FOV) in the good fat-saturation group (0.37 ± 0.06) was significantly lower (P < 0.01) than that in the poor fat-saturation group (0.39 ± 0.06). Other shimming-related parameters were found not significantly affecting the fat-saturation outcomes. Technologists with more experience tended to have less variable shimming performance than junior technologists did. Conclusions The quality of clinical MRI and especially breast MRI is highly dependent on shimming. Decreasing Tissue/FOV was associated with good image quality (good fat saturation). Optimization of shimming may require manual shimming or higher-order field-correction strategies.

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