Quantitative evaluation of background parenchymal enhancement (BPE) on breast MRI. A feasibility study with a semi-automatic and automatic software compared to observer-based scores

Tagliafico, Alberto; Bignotti, Bianca; Tagliafico, Giulio; Tosto, Simona; Signori, Alessio; Calabrese, Massimo

doi:10.1259/bjr.20150417

Cited by 19 publications

(27 citation statements)

References 29 publications

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“…Qualitative background parenchymal enhancement assessment Among the 39 (28111) studies that assessed BPE qualitatively, 7,8,[10][11][12][13]15,17, 38% (15/39) studies were published in 2015 (January-October 2015) and 62% (24/39) studies were published during 2010-2014. Most of the studies were performed in the USA (17/39 studies), the Korea (10/39 studies) and Japan (6/39 studies).…”

Section: Resultsmentioning

confidence: 99%

“…Only 3/39 (8%) studies used a high-relaxivity contrast agent. 7,35,42 All the studies graded BPE on a four-point scale as minimal, mild, moderate or marked in accordance with the BI-RADS categories. 16 Iacconi et al 28 classified BPE according to the BI-RADS lexicon but for statistical purpose, clumped the studies into two groups (low and high BPE).…”

Section: Resultsmentioning

confidence: 99%

“…7,8,17,25,39,[44][45][46]49 In particular, four studies 7,8,17,49 evaluated both intrareader and interreader agreements and the other five studies evaluated only interreader agreement. Kappa values for intrareader agreement were moderate to almost perfect, while more variability was The unenhanced images were not used.…”

Section: Resultsmentioning

confidence: 99%

“…[8][9][10][11][12][13][14][15] BPE can be visually assessed qualitatively using the Breast Imaging-Reporting and Data System (BI-RADS) scores or quantitatively using software. 7,16 However, radiologist agreement for BPE qualitative evaluation is fair 17 and, to the best of our knowledge, there is a lack of uniformity on quantitative measurements of BPE on breast MRI. Indeed, an absolute categorizing method based on percentage is not supported by the American College of Radiology (ACR), suggesting the need for further research in this topic.…”

Section: Introductionmentioning

confidence: 99%

“…6 In this perspective, background parenchymal enhancement (BPE), the term used to describe the enhancement of the normal breast tissue, is emerging as an imaging biomarker. 7 The "degree" of BPE is linked to the risk of developing breast cancer, may affect the reading of breast MRI, the staging and the risk of cancer and even the long-term outcome, particularly in patients with certain subtypes at immunohistochemistry. [8][9][10][11][12][13][14][15] BPE can be visually assessed qualitatively using the Breast Imaging-Reporting and Data System (BI-RADS) scores or quantitatively using software.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of background parenchymal enhancement on breast MRI: a systematic review

Bignotti¹,

Signori²,

Valdora³

et al. 2017

The British Journal of Radiology

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Objective: To perform a systematic review of the methods used for background parenchymal enhancement (BPE) evaluation on breast MRI. Methods: Studies dealing with BPE assessment on breast MRI were retrieved from major medical libraries independently by four reviewers up to 6 October 2015. The keywords used for database searching are "background parenchymal enhancement", "parenchymal enhancement", "MRI" and "breast". The studies were included if qualitative and/or quantitative methods for BPE assessment were described. Results: Of the 420 studies identified, a total of 52 articles were included in the systematic review. 28 studies performed only a qualitative assessment of BPE, 13 studies performed only a quantitative assessment and 11 studies performed both qualitative and quantitative assessments. A wide heterogeneity was found in the MRI sequences and in the quantitative methods used for BPE assessment. Conclusion: A wide variability exists in the quantitative evaluation of BPE on breast MRI. More studies focused on a reliable and comparable method for quantitative BPE assessment are needed. Advances in knowledge: More studies focused on a quantitative BPE assessment are needed.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Evaluation of background parenchymal enhancement on breast MRI: a systematic review

Bignotti¹,

Signori²,

Valdora³

et al. 2017

The British Journal of Radiology

Self Cite

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Comparison between qualitative and quantitative assessment of background parenchymal enhancement on breast MRI

Pujara

Mikheev

Rusinek

et al. 2017

Magnetic Resonance Imaging

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Machine learning‐based prediction of future breast cancer using algorithmically measured background parenchymal enhancement on high‐risk screening MRI

Saha

Grimm

Ghate

et al. 2019

Magnetic Resonance Imaging

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Background Preliminary work has demonstrated that background parenchymal enhancement (BPE) assessed by radiologists is predictive of future breast cancer in women undergoing high‐risk screening MRI. Algorithmically assessed measures of BPE offer a more precise and reproducible means of measuring BPE than human readers and thus might improve the predictive performance of future cancer development. Purpose To determine if algorithmically extracted imaging features of BPE on screening breast MRI in high‐risk women are associated with subsequent development of cancer. Study Type Case–control study. Population In all, 133 women at high risk for developing breast cancer; 46 of these patients developed breast cancer subsequently over a follow‐up period of 2 years. Field Strength/Sequence 5 T or 3.0 T T1‐weighted precontrast fat‐saturated and nonfat‐saturated sequences and postcontrast nonfat‐saturated sequences. Assessment Automatic features of BPE were extracted with a computer algorithm. Subjective BPE scores from five breast radiologists (blinded to clinical outcomes) were also available. Statistical Tests Leave‐one‐out crossvalidation for a multivariate logistic regression model developed using the automatic features and receiver operating characteristic (ROC) analysis were performed to calculate the area under the curve (AUC). Comparison of automatic features and subjective features was performed using a generalized regression model and the P‐value was obtained. Odds ratios for automatic and subjective features were compared. Results The multivariate model discriminated patients who developed cancer from the patients who did not, with an AUC of 0.70 (95% confidence interval: 0.60–0.79, P < 0.001). The imaging features remained independently predictive of subsequent development of cancer (P < 0.003) when compared with the subjective BPE assessment of the readers. Data Conclusion Automatically extracted BPE measurements may potentially be used to further stratify risk in patients undergoing high‐risk screening MRI. Level of Evidence: 3 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2019;50:456–464.

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Quantitative evaluation of background parenchymal enhancement (BPE) on breast MRI. A feasibility study with a semi-automatic and automatic software compared to observer-based scores

Abstract: Computerized BPE quantitative evaluation is feasible with both semi-automatic and automatic software. Computerized BPE quantitative scores correlate with radiologists' estimation.

Cited by 19 publications

References 29 publications

Evaluation of background parenchymal enhancement on breast MRI: a systematic review

Evaluation of background parenchymal enhancement on breast MRI: a systematic review

Comparison between qualitative and quantitative assessment of background parenchymal enhancement on breast MRI

Machine learning‐based prediction of future breast cancer using algorithmically measured background parenchymal enhancement on high‐risk screening MRI

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