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KMID : 1144720230270010021
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Investigative Magnetic Resonance Imaging
2023 Volume.27 No. 1 p.21 ~ p.31
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Response Evaluation to Neoadjuvant Chemotherapy in Breast Cancer Patients: Sequential Dynamic Contrast-Enhanced MRI Using Computer-Aided Detection
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Chae In-Hye
Cha Eun-Suk
Lee Jee-Eun
Chung Jin
Kim Jeoung-Hyun
Sung Sun-Hee
Han Mi-Ra
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Abstract
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Purpose : We evaluated whether there is an association between sequential changes in kinetic profiles by computer-aided detection (CAD) during neoadjuvant chemotherapy (NAC) and pathologic complete response (pCR) and residual cancer burden (RCB) in dynamic contrast-enhanced MRI (DCE-MRI) of patients with invasive breast cancer.
Materials and Methods : This retrospective study involved 51 patients (median age, 48 years; range, 33?60 years) who underwent pre-, interim-, and post-NAC DCE-MRIs at 3 T. The tumor size and CAD-generated kinetic profiles (peak enhancement and delayed enhancement [persistent, plateau, and washout] components) were measured. Percentage changes in pre- and interim-NAC (ΔMRI value1) and pre- and post-NAC (ΔMRI value2) were compared between pCR and non-pCR cases, and according to RCB. Receiver operating characteristic curve analysis was performed to evaluate the association between pCR and MRI parameters (including CAD-generated kinetic profiles).
Results : The pCR rate was 19.6% (10/51). There were statistically significant differences in Δtumor size2 (p < 0.01), Δpeak enhancement2 (p = 0.01), Δpersistent2 (p = 0.01), Δplateau2 (p = 0.02), and Δwashout2 (p = 0.03) between pCR and non-pCR. ΔTumor size2 provided very good diagnostic accuracy for pCR (cut-off, -90%; area under the curve, 0.88). There were differences in Δtumor size2, Δpeak enhancement2, Δplateau2, and Δwashout2 between RCB classes (p < 0.01).
Conclusion : DCE-MRI using CAD has the potential for predicting pCR and RCB classes.
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KEYWORD
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Breast neoplasm, Neoadjuvant therapy, Magnetic resonance imaging, Computer-aided
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