Clinical MR-Mammography

Baltzer, Pascal; Freiberg, Christian; Beger, Sebastian; Vag, Tibor; Dietzel, Matthias; Herzog, Aimee; Gajda, Mieczysław; Camara, O.; Kaiser, Werner A.

doi:10.1016/j.acra.2009.03.017

Cited by 44 publications

(24 citation statements)

References 29 publications

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“…In 5 [23, 24, 26–28] studies a selection was made of patients with suspect findings based on mammography and ultrasound examinations. In the other 5 studies [20–22, 25, 29] patients with a suspect lesion on MRI were included.…”

Section: Resultsmentioning

confidence: 99%

“…of malignantNo. of benignType of analysisMRICAD systemArazi-Kleinman [22] 200953R, c1347 (26–68)562234TB1.5TCAD-GaeaMeeuwis [27] 200965R, c1449 (29–71)714922TB3.0TCADstreamBaltzer [23] 200951R, c1251 (13)904644TB1.5TDynaCADBaltzer [24] 2009329P, c1353 (15–83)469279190TB1.5TDynaCADVeltman [29] 2009NRR,c11NR522527TB1.5T3-Time-PointRenz [28] 200848P, c1151 (31)884345TB1.5TDynaCAD Full-time PointHauth [25] 2008137R10NR18361122TB1.5T3-Time-PointWilliams [21] 2006126R, c1452 (27–86)15441113TB1.5TCADstreamLehman [20] 200529R, c14NR33924TB1.5TCADstreamKelcz [26] 200257P, c1452 (31–80)683137TB1.5T3-Time-Point…”

Section: Resultsmentioning

confidence: 99%

“…Six [20–24, 27] studies analysed the presence or absence of “threshold enhancement” at different minimum thresholds. Lehman et al [20], Williams et al [21] and Meeuwis et al [27] used the CAD system CADstream.…”

Section: Resultsmentioning

confidence: 99%

“…The study by Meeuwis et al [27] showed a higher specificity than the other two studies. In the studies by Baltzer et al [23, 24] DynaCAD was used. In these studies, the sensitivity decreased and the specificity increased at higher minimum thresholds.…”

Section: Resultsmentioning

confidence: 99%

“…1). Eight studies were in the English language [20–24, 26, 27, 29]; the other 2 were in the German Language [25, 28].

Fig.…”

Section: Methodsmentioning

confidence: 99%

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Computer-aided detection in breast MRI: a systematic review and meta-analysis

et al. 2011

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ObjectivesTo evaluate the additional value of computer-aided detection (CAD) in breast MRI by assessing radiologists’ accuracy in discriminating benign from malignant breast lesions.MethodsA literature search was performed with inclusion of relevant studies using a commercially available CAD system with automatic colour mapping. Two independent researchers assessed the quality of the studies. The accuracy of the radiologists’ performance with and without CAD was presented as pooled sensitivity and specificity.ResultsOf 587 articles, 10 met the inclusion criteria, all of good methodological quality. Experienced radiologists reached comparable pooled sensitivity and specificity before and after using CAD (sensitivity: without CAD: 89%; 95% CI: 78–94%, with CAD: 89%; 95%CI: 81–94%) (specificity: without CAD: 86%; 95% CI: 79–91%, with CAD: 82%; 95% CI: 76–87%). For residents the pooled sensitivity increased from 72% (95% CI: 62–81%) without CAD to 89% (95% CI: 80–94%) with CAD, however, not significantly. Concerning specificity, the results were similar (without CAD: 79%; 95% CI: 69–86%, with CAD: 78%; 95% CI: 69–84%).ConclusionsCAD in breast MRI has little influence on the sensitivity and specificity of experienced radiologists and therefore their interpretation remains essential. However, residents or inexperienced radiologists seem to benefit from CAD concerning breast MRI evaluation.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

“…1). Eight studies were in the English language [20–24, 26, 27, 29]; the other 2 were in the German Language [25, 28].

Fig.…”

Section: Methodsmentioning

confidence: 99%

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Computer-aided detection in breast MRI: a systematic review and meta-analysis

et al. 2011

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Association between survival in patients with primary invasive breast cancer and computer aided MRI

Dietzel

Zoubi

Vag

et al. 2012

Magnetic Resonance Imaging

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This study demonstrates the significant relationship between semi-quantitative enhancement analysis in breast MRI and disease-related death of breast cancer patients. As results were extracted from a routine staging examination, MRI noninvasively provides not only diagnostic information but also outcome data at one step. Future studies should address the impact of these findings on patient management and therapeutic approach.

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CAD and Machine Learning for Breast MRI

Martel

2020

Breast MRI for High-Risk Screening

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Clinical MR-Mammography

Cited by 44 publications

References 29 publications

Computer-aided detection in breast MRI: a systematic review and meta-analysis

Computer-aided detection in breast MRI: a systematic review and meta-analysis

Association between survival in patients with primary invasive breast cancer and computer aided MRI

CAD and Machine Learning for Breast MRI

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