Quantitative 3D breast magnetic resonance imaging fibroglandular tissue analysis and correlation with qualitative assessments: a feasibility study

Ha, Richard; Mema, Eralda; Guo, X. Edward; Mango, Victoria L.; Desperito, Elise; Ha, Jason; Wynn, Ralph; Zhao, Binsheng

doi:10.21037/qims.2016.03.03

Cited by 9 publications

(20 citation statements)

References 16 publications

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“…So US can not accurately measure the volume of the lesion and not accurately observe the spatial distribution of lesional blood flow (13). Breast MRI is the most sensitive examination for breast tumor detection and it can be used to detect the spatial relationship between the lesion and the surrounding tissue, the spatial distribution of lesional blood flow as well (14)(15)(16)(17)(18). What's more, MRI can be used to assess tissue necrosis after ablation by administrating contrast agent (19,20).…”

Section: Discussionmentioning

confidence: 99%

Ultrasound-guided percutaneous microwave ablation for benign breast lesions: evaluated by contrast-enhanced ultrasound combined with magnetic resonance imaging

Zhang¹,

Li²,

et al. 2017

J. Thorac. Dis.

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Background: Minimally invasive ablative techniques in the treatment of breast tumor has become popularly in recent years. Methods:We analyzed gray-scale and contrast-enhanced ultrasound (CEUS) features of 205 microwave ablated breast benign lesions from 182 consecutive patients, compared with magnetic resonance imaging (MRI) and histopathology findings. The follow-up was implemented at 3, 6 and 12 months after the ablation treatment.Results: Before the MWA, the mean of largest diameter and volume of the lesions were 14.41±6.54 and 3,224±961 mm 3 , respectively. However, those of the lesions respectively were 8.48±6.30 and 2,116±732 mm 3 one year after the treatment. The longest diameter and the volume of the ablative lesions were gradually decreased 3, 6 or 12 months after the MWA. 44 (/205, 21.5%) ablative lesions were disappeared one year after the MWA. One hundred and forty-two (/205, 69.3%) ablative lesions presented a hypoechoic halo surrounding it on gray-scale US after the MWA. The success rate of the MWA treatment in the benign breast lesion was 87.32% and 82.93% evaluated by CEUS and enhanced MRI, respectively. During the ablation, no patient had serious complications, such as hemorrhage, serious pain and fat necrosis, etc.Conclusions: Microwave ablation was a safe and efficient method in the treatment of the benign breast tumors. CEUS and enhanced MRI could accurately assess whether the MWA treatment is effective.

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Section: Discussionmentioning

confidence: 99%

Ultrasound-guided percutaneous microwave ablation for benign breast lesions: evaluated by contrast-enhanced ultrasound combined with magnetic resonance imaging

Zhang¹,

Li²,

et al. 2017

J. Thorac. Dis.

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“…Breast cancer risk primarily depends on family history, hormonal risk factors and genetic mutations (eg, BRCA 1, 2) and current clinical practice employs several risk reduction strategies that target these factors, such as lifestyle changes, chemoprevention, and invasive surgical measures including prophylactic mastectomy and salpingo‐oophorectomy . While these measures are often effective at reducing breast cancer risk, they can be associated with substantial side effects, which considerably reduce quality of life …”

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confidence: 99%

“…Several studies have shown a strong correlation between FGT and mammographic density . FGT can be evaluated three‐dimensionally on magnetic resonance imaging (MRI), providing a more accurate assessment of the total epithelial and stromal elements . Similar to mammographic density, the amount of FGT is also modifiable, with many studies showing the effects of chemoprevention medications on the amount of FGT …”

mentioning

confidence: 99%

“…[5][6][7][8] While these measures are often effective at reducing breast cancer risk, they can be associated with substantial side effects, which considerably reduce quality of life. [9][10][11] In addition to family history and genetic factors, patient's mammographic breast density has been shown to be an independent risk factor for breast cancer. Wolfe 3,4 was the first to propose a strong association between mammographic parenchymal density and breast cancer risk, a finding that has been confirmed in many subsequent studies.…”

mentioning

confidence: 99%

“…[8][9][10] FGT can be evaluated three-dimensionally on magnetic resonance imaging (MRI), providing a more accurate assessment of the total epithelial and stromal elements. 11 Similar to mammographic density, the amount of FGT is also modifiable, with many studies showing the effects of chemoprevention medications on the amount of FGT. [12][13][14] Two recently published studies show that the amount of breast MRI parenchymal enhancement (BPE) is a significant risk factor for breast cancer, independent of the amount of FGT.…”

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confidence: 99%

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Does breast MRI background parenchymal enhancement indicate metabolic activity? Qualitative and 3D quantitative computer imaging analysis

Mema

Mango

Guo

et al. 2017

Magnetic Resonance Imaging

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Breast MRI Background Parenchymal Enhancement Categorization Using Deep Learning: Outperforming the Radiologist

Eskreis‐Winkler

Sutton

D’Alessio

et al. 2022

Magnetic Resonance Imaging

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Background Background parenchymal enhancement (BPE) is assessed on breast MRI reports as mandated by the Breast Imaging Reporting and Data System (BI‐RADS) but is prone to inter and intrareader variation. Semiautomated and fully automated BPE assessment tools have been developed but none has surpassed radiologist BPE designations. Purpose To develop a deep learning model for automated BPE classification and to compare its performance with current standard‐of‐care radiology report BPE designations. Study Type Retrospective. Population Consecutive high‐risk patients (i.e. >20% lifetime risk of breast cancer) who underwent contrast‐enhanced screening breast MRI from October 2013 to January 2019. The study included 5224 breast MRIs, divided into 3998 training, 444 validation, and 782 testing exams. On radiology reports, 1286 exams were categorized as high BPE (i.e., marked or moderate) and 3938 as low BPE (i.e., mild or minimal). Field Strength/Sequence A 1.5 T or 3 T system; one precontrast and three postcontrast phases of fat‐saturated T1‐weighted dynamic contrast‐enhanced imaging. Assessment Breast MRIs were used to develop two deep learning models (Slab artificial intelligence (AI); maximum intensity projection [MIP] AI) for BPE categorization using radiology report BPE labels. Models were tested on a heldout test sets using radiology report BPE and three‐reader averaged consensus as the reference standards. Statistical Tests Model performance was assessed using receiver operating characteristic curve analysis. Associations between high BPE and BI‐RADS assessments were evaluated using McNemar's chi‐square test (α* = 0.025). Results The Slab AI model significantly outperformed the MIP AI model across the full test set (area under the curve of 0.84 vs. 0.79) using the radiology report reference standard. Using three‐reader consensus BPE labels reference standard, our AI model significantly outperformed radiology report BPE labels. Finally, the AI model was significantly more likely than the radiologist to assign “high BPE” to suspicious breast MRIs and significantly less likely than the radiologist to assign “high BPE” to negative breast MRIs. Data Conclusion Fully automated BPE assessments for breast MRIs could be more accurate than BPE assessments from radiology reports. Level of Evidence 4 Technical Efficacy Stage 3

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Quantitative 3D breast magnetic resonance imaging fibroglandular tissue analysis and correlation with qualitative assessments: a feasibility study

Cited by 9 publications

References 16 publications

Ultrasound-guided percutaneous microwave ablation for benign breast lesions: evaluated by contrast-enhanced ultrasound combined with magnetic resonance imaging

Ultrasound-guided percutaneous microwave ablation for benign breast lesions: evaluated by contrast-enhanced ultrasound combined with magnetic resonance imaging

Does breast MRI background parenchymal enhancement indicate metabolic activity? Qualitative and 3D quantitative computer imaging analysis

Breast MRI Background Parenchymal Enhancement Categorization Using Deep Learning: Outperforming the Radiologist

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