Application of dynamic magnetic resonance imaging information technology in adjuvant chemotherapy for breast cancer

Yang, Caixian; Zhao, Hongguang

doi:10.1016/j.jiph.2019.06.020

Cited by 3 publications

(2 citation statements)

References 6 publications

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“…Theoretically, they can reflect the cellular information of tissue cell components, extracellular space, capillary permeability, microcirculation and perfusion, thus may precede the morphological size during NAT. Yang et al [57] found the effective group has statistically significant changes in Ktrans and Kep, which were consistent with the morphological RECIST 1.1 criteria assessment before and after NAT. Some studies also found that Ktrans [58], Kep [9,59], Ve [60] appeared to predict treatment response when measured early during NAT.…”

Section: Pharmacokinetic Parameters For Predicting Pcr Before and Dursupporting

confidence: 64%

The role of magnetic resonance imaging on evaluating response of neoadjuvant therapy for breast cancer

Guo

Yang

et al. 2020

Chin J Acad Radiol

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Breast magnetic resonance imaging (MRI) is always considered to be more accurate for evaluating neoadjuvant therapy (NAT) response than mammography, ultrasound and clinical examination. Preoperative MRI aims to evaluate residual disease to facilitate surgical planning. MRI scans performed before and/or during NAT aim to predict the treatment response and thus adjust the NAT plan at an early stage. MRI accuracy depends on tumor morphology, histology, shrinkage pattern and molecular subtype. Combining multiparameter functional MRI can improve the prediction accuracy. In addition, radiomics offers high-dimensional and high-throughput signatures and were shown to predict treatment response before NAT. This article reviews the indicators of breast MRI for evaluating NAT response, including morphological MRI features, enhancement and pharmacokinetic parameters, apparent diffusion coefficient (ADC), choline concentration, etc., even radiomic signatures and illustrates their advantages, limitations and future directions.

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Section: Pharmacokinetic Parameters For Predicting Pcr Before and Dursupporting

confidence: 64%

The role of magnetic resonance imaging on evaluating response of neoadjuvant therapy for breast cancer

Guo

Yang

et al. 2020

Chin J Acad Radiol

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“…The Miller-Payne grading system [22] is a 5-level classification method used to evaluate the pathological response. Grade 5: no identifiable malignant cells seen in the sections, although ductal carcinoma in situ may exist.…”

Section: Pathological Assessmentmentioning

confidence: 99%

Early prediction of pathological complete response to neoadjuvant chemotherapy combining DCE-MRI and apparent diffusion coefficient values in breast Cancer

et al. 2022

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Introduction Improving the early prediction of neoadjuvant chemotherapy (NAC) efficacy in breast cancer can lead to an improved prediction of the final prognosis of patients, which would be useful for promoting individualized treatment. This study aimed to explore the value of the combination of dynamic contrast-enhanced (DCE)-MRI parameters and apparent diffusion coefficient (ADC) values in the early prediction of pathological complete response (pCR) to NAC for breast cancer. Methods A total of 119 (range, 28−69 years) patients with biopsy-proven breast cancer who received two cycles of NAC before breast surgery were retrospectively enrolled from our hospital database. Patients were divided into pCR and non pCR groups according to their pathological responses; a total of 24 patients achieved pCR, while 95 did not. The quantitative (Ktrans; Kep; Ve; IAUC) and semiquantitative parameters (W-in; W-out; TTP) of DCE-MRI that were significantly different between groups were combined with ADC values to explore their value in the early prediction of pCR to NAC for breast cancer. The independent T test was performed to compare the differences in DCE-MRI parameters and ADC values between the two groups. Receiver operating characteristic (ROC) curves were plotted, and the area under the ROC curve (AUC), sensitivity and specificity were calculated to evaluate the performance of the prediction. Results The Ktrans, Kep, IAUC, ADC, W-in and TTP values were significantly different between the pCR and non pCR groups after NAC. The AUC (0.845) and specificity (95.79%) of the combined Ktrans, Kep, IAUC and ADC values were both higher than those of the individual parameters. The combination of W-in, TTP and ADC values had the highest AUC value (0.886) in predicting pCR, with a sensitivity and specificity of 87.5% and 82.11%, respectively. Conclusions The results suggested that the combination of ADC values and quantitative and semiquantitative DCE-MRI parameters, especially the combination of W-in, TTP, and ADC values, may improve the early prediction of pCR in breast cancer.

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Analysis of Clinical Diagnostic Value of Dynamic Contrast-Enhanced Magnetic Resonance Imaging Combined with MRI in Early Breast Cancer

Ge,

Yin,

Wang

et al. 2024

j biomed nanotechnol

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A study involving 73 patients with early breast space-occupying diseases (41 malignant, 32 benign) utilized 1.5T quantitative dynamic enhanced magnetic resonance imaging to measure lesion-specific parameters. These included the contrast medium’s transfer rate from intravascular to extravascular (Ktrans), return rate to blood vessels (Kep), and tumor vessel volume fraction (Vp). Pathological results post-surgery served as the gold standard. Comparisons between benign and malignant groups, as well as malignant subtypes, were made. Malignant lesions exhibited varied Ktrans (0.108–2.810 min−1) and Vp (0.0018–0.743 ml) values. Benign lesions had Ktrans (0.125–2.472 min−1), Kep (0.008–1.760 min−1), and Vp (0.006–0.816 ml) values. Significant differences were observed in Ktrans and Vp (P < 0.05), but not in Kep and Vp (P > 0.05). While differences between hormonal and HER2 statuses were minimal, Kep in HER2-positive tumors was notable (P < 0.05). Subtype comparisons showed no significant Ktrans variation (P > 0.05) but differences in Kep and Vp. In conclusion, Ktrans is crucial for diagnosing early breast cancer and distinguishing between benign and malignant diseases. The study underscores the potential of quantitative dynamic contrast-enhanced MRI in breast cancer diagnosis

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Application of dynamic magnetic resonance imaging information technology in adjuvant chemotherapy for breast cancer

Cited by 3 publications

References 6 publications

The role of magnetic resonance imaging on evaluating response of neoadjuvant therapy for breast cancer

The role of magnetic resonance imaging on evaluating response of neoadjuvant therapy for breast cancer

Early prediction of pathological complete response to neoadjuvant chemotherapy combining DCE-MRI and apparent diffusion coefficient values in breast Cancer

Analysis of Clinical Diagnostic Value of Dynamic Contrast-Enhanced Magnetic Resonance Imaging Combined with MRI in Early Breast Cancer

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