Diagnostic performance of initial enhancement analysis using ultra-fast dynamic contrast-enhanced MRI for breast lesions

Goto, Mariko; Sakai, Koji; Yokota, Hajime; Kiba, Maki; Yoshida, Misao; Imai, Hiroshi; Weiland, Elisabeth; Yokota, Isao; Yamada, Kazuo

doi:10.1007/s00330-018-5643-4

Cited by 48 publications

(54 citation statements)

References 37 publications

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“…Some previous studies showed the discriminating power of the MS and TTE when adopting UF‐DCE MRI with a view‐sharing technique, while there remains limited data for CS. Owing to better image quality achieved by CS, our data showed the value of UF‐DCE MRI for not only a kinetic evaluation but also a morphological evaluation.…”

Section: Discussionmentioning

confidence: 99%

“…Ultrafast DCE (UF‐DCE) MRI is an attempt to extract both morphologic and kinetic information in the early postcontrast period, and thus capture the inflow of contrast in breast lesions. Most studies have used reconstruction techniques, such as view sharing or compressed sensing (CS), to achieve high spatial and high temporal resolution, and thus acquire images with high spatial resolution at many timepoints in the early postcontrast period …”

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confidence: 99%

“…These new parameters are suitable for evaluating UF‐DCE of the breast. Some studies have shown the efficacy of these parameters; however, the evidence for their diagnostic performance is still limited and most previous studies used view‐sharing techniques . The aim of the present work is therefore to evaluate the diagnostic performances of MS, TTE, and AVI in differentiating malignant lesions from benign lesions when applied to UF‐DCE MRI using a CS technique.…”

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confidence: 99%

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New parameters of ultrafast dynamic contrast‐enhanced breast MRI using compressed sensing

Honda

Kataoka

Onishi

et al. 2019

Magnetic Resonance Imaging

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Background: Ultrafast dynamic contrast-enhanced (UF-DCE) breast MRI is considered a promising method of accelerated breast MRI. However, the value of new kinetic parameters derived from UF-DCE need clinical evaluation. Purpose: To evaluate the diagnostic performance of the maximum slope (MS), time to enhancement (TTE), and time interval between arterial and venous visualization (AVI) derived from UF-DCE MRI using compressed sensing (CS). Study Type: Retrospective. Population: Seventy-five patients with histologically proven breast lesions. The total number of analyzed lesions was 90 (61 malignant and 29 benign). Field Strength/Sequence: 3T MRI with UF-DCE MRI based on the 3D gradient-echo volumetric interpolated breath-hold examination (VIBE) sequence using incoherent k-space sampling combined with a CS reconstruction followed by conventional DCE MRI. Assessment: The diagnostic performance of the MS, TTE, AVI, and conventional kinetic analysis was analyzed and compared with histology. Statistical Tests: Wilcoxon rank sum test, receiver operating characteristic analysis. Results: The MS was larger and the TTE and AVI were smaller for malignant lesions compared with benign lesions: MS: 29.3%/s and 18.4%/s (P < 0.001), TTE: 7.0 and 12.0 seconds (P < 0.001), AVI: 2.7 and 4.4 frames (P = 0.006) for malignant and benign lesions. The discriminating power of the MS (area under the curve [AUC], 0.76) was slightly better than that of conventional kinetic analysis (AUC, 0.69) and comparable to that of the TTE and AVI (AUC, 0.78 and 0.76 for TTE and AVI, respectively). Invasive lobular carcinoma had smaller MS (21.8%/s) among malignant lesions (29.3%/s). Data Conclusion: The MS, TTE, and AVI can be used to evaluate breast lesions with clinical performance equivalent to that of conventional kinetic analysis. These parameters vary among histologies. Level of Evidence: 3 Technical Efficacy: Stage 2

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Section: Discussionmentioning

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New parameters of ultrafast dynamic contrast‐enhanced breast MRI using compressed sensing

Honda

Kataoka

Onishi

et al. 2019

Magnetic Resonance Imaging

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“…The pathological and pharmacokinetic mechanisms differed in benign and malignant lesions. Malignant tumors had abundant vascularity and highly permeable vessel walls that allowed easier transfer of the contrast agent from vessels to the extravascular space was easier; thus, malignant lesions had shorter TTE and larger MS, while the benign lesions showed the opposite ndings [32,33]. This could explain why in the combined model, the texture features extracted from the 2nd and 5th contrast sequences were independently relevant to discriminate benign and malignant NME.…”

Section: Discussionmentioning

confidence: 99%

Additive Value of Texture Analysis Based on Breast MRI for Distinguishing Between Benign and Malignant Non-mass Enhancement in Premenopausal Women

Tan

Mai

Huang

et al. 2020

Preprint

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Background: Non-mass enhancement (NME) is a diagnostic dilemma. Texture analysis (TA) could serve as an objective method to quantify tumor characteristics and growth patterns. However, there are few reports about TA use in NME diagnosis. To our knowledge, NME diagnosis based on the combination of the features noted on routine MRI and TA has not been reported.. The purpose of this study was to explore the value of TA in distinguishing between benign and malignant NME in premenopausal women. Methods: Women in whom NME was histologically proven (n = 147) were enrolled (benign: 58; malignant: 89) was retrospective. Then, 102 and 45 patients were classified as the training and validation groups, respectively. Scanning sequences included Fat-suppressed T2-weighted and fat-suppressed contrast-enhanced T1-weighted which were acquired on a 1.5T MRI system. Clinical and routine MR characteristics (CRMC) were evaluated by two radiologists according to the Breast Imaging and Reporting and Data system (2013). Texture features were extracted from all post-contrast sequences in the training group. The combination model was built and then assessed in the validation group. Pearson’s chi-square test and Mann-Whitney U test were used to compare categorical variables and continuous variables, respectively. Logistic regression analysis and receiver operating characteristic curve were employed to assess the diagnostic performance of CRMC, TA, and their combination model in NME diagnosis.Results: The combination model showed a superior diagnostic performance in differentiating between benign and malignant NME compared to that of CRMC or TA alone (AUC, 0.887 vs 0.832 vs 0.74). Moreover, compared to CRMC, the model showed high specificity (72.5% vs 80%). The results obtained in the validation group confirmed the model was promising.Conclusion: The combined use of TA and CRMC could afford an improved diagnostic performance in differentiating between benign and malignant NME.

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“…Diagnostic accuracy was also improved when data from the initial enhancement analysis was combined with conventional BI-RADS categorization, compared with BI-RADS alone, especially for non-mass breast lesions (3). Moreover, screening results using breast ultrafast DCE-MRI showed higher specificity, shorter reading times, and non-inferior accuracy compared to full diagnostic MRI (4).…”

Section: Introductionmentioning

confidence: 97%

Ultrafast Dynamic Contrast-Enhanced Breast MRI: Lesion Conspicuity and Size Assessment according to Background Parenchymal Enhancement

et al. 2020

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Diagnostic performance of initial enhancement analysis using ultra-fast dynamic contrast-enhanced MRI for breast lesions

Abstract: • Ultra-fast dynamic MRI effectively differentiates benign from malignant breast lesions. • Ultra-fast dynamic MRI contributes to BI-RADS categorisation in non-mass enhancement. • Management of non-mass breast lesions becomes more appropriate.

Cited by 48 publications

References 37 publications

New parameters of ultrafast dynamic contrast‐enhanced breast MRI using compressed sensing

New parameters of ultrafast dynamic contrast‐enhanced breast MRI using compressed sensing

Additive Value of Texture Analysis Based on Breast MRI for Distinguishing Between Benign and Malignant Non-mass Enhancement in Premenopausal Women

Ultrafast Dynamic Contrast-Enhanced Breast MRI: Lesion Conspicuity and Size Assessment according to Background Parenchymal Enhancement

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