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乳腺癌的合成磁共振成像:鉴别良恶性病变及预测免疫组化表达状态。

Synthetic MRI in breast cancer: differentiating benign from malignant lesions and predicting immunohistochemical expression status.

机构信息

Department of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi, China.

Department of Radiology, Cancer Hospital Chinese Academy of Medical Sciences, Shenzhen Center, Shenzhen, China.

出版信息

Sci Rep. 2023 Oct 20;13(1):17978. doi: 10.1038/s41598-023-45079-2.


DOI:10.1038/s41598-023-45079-2
PMID:37864025
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10589282/
Abstract

To evaluate and compare the performance of synthetic magnetic resonance imaging (SyMRI) in classifying benign and malignant breast lesions and predicting the expression status of immunohistochemistry (IHC) markers. We retrospectively analysed 121 patients with breast lesions who underwent dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and SyMRI before surgery in our hospital. DCE-MRI was used to assess the lesions, and then regions of interest (ROIs) were outlined on SyMRI (before and after enhancement), and apparent diffusion coefficient (ADC) maps to obtain quantitative values. After being grouped according to benign and malignant status, the malignant lesions were divided into high and low expression groups according to the expression status of IHC markers. Logistic regression was used to analyse the differences in independent variables between groups. The performance of the modalities in classification and prediction was evaluated by receiver operating characteristic (ROC) curves. In total, 57 of 121 lesions were benign, the other 64 were malignant, and 56 malignant lesions performed immunohistochemical staining. Quantitative values from proton density-weighted imaging prior to an injection of the contrast agent (PD-Pre) and T2-weighted imaging (T2WI) after the injection (T2-Gd), as well as its standard deviation (SD of T2-Gd), were valuable SyMRI parameters for the classification of benign and malignant breast lesions, but the performance of SyMRI (area under the curve, AUC = 0.716) was not as good as that of ADC values (AUC = 0.853). However, ADC values could not predict the expression status of breast cancer markers, for which SyMRI had excellent performance. The AUCs of androgen receptor (AR), estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER-2), p53 and Ki-67 were 0.687, 0.890, 0.852, 0.746, 0.813 and 0.774, respectively. SyMRI had certain value in distinguishing between benign and malignant breast lesions, and ADC values were still the ideal method. However, to predict the expression status of IHC markers, SyMRI had an incomparable value compared with ADC values.

摘要

为了评估和比较合成磁共振成像(SyMRI)在鉴别良恶性乳腺病变和预测免疫组织化学(IHC)标志物表达状态方面的性能。我们回顾性分析了 121 例在我院接受手术前动态对比增强磁共振成像(DCE-MRI)和 SyMRI 检查的乳腺病变患者。DCE-MRI 用于评估病变,然后在 SyMRI(增强前后)和表观扩散系数(ADC)图上勾画感兴趣区(ROI)以获得定量值。根据良恶性分组后,根据 IHC 标志物的表达状态,将恶性病变分为高表达和低表达组。采用逻辑回归分析组间独立变量的差异。通过受试者工作特征(ROC)曲线评估两种模式的分类和预测性能。121 个病灶中,57 个为良性,64 个为恶性,56 个恶性病灶行免疫组织化学染色。对比剂注射前质子密度加权成像(PD-Pre)和注射后 T2 加权成像(T2-Gd)的定量值及其标准差(T2-Gd 的 SD)是鉴别良恶性乳腺病变的有价值的 SyMRI 参数,但 SyMRI(曲线下面积,AUC=0.716)的性能不如 ADC 值(AUC=0.853)。然而,ADC 值不能预测乳腺癌标志物的表达状态,而 SyMRI 具有优异的性能。雄激素受体(AR)、雌激素受体(ER)、孕激素受体(PR)、人表皮生长因子受体 2(HER-2)、p53 和 Ki-67 的 AUC 分别为 0.687、0.890、0.852、0.746、0.813 和 0.774。SyMRI 在鉴别良恶性乳腺病变方面具有一定价值,ADC 值仍是理想方法。然而,预测 IHC 标志物的表达状态时,SyMRI 的价值无法与 ADC 值相比。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4ea/10589282/65dd2ccf1412/41598_2023_45079_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4ea/10589282/52167a5ea0f3/41598_2023_45079_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4ea/10589282/e0edd7c24f4a/41598_2023_45079_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4ea/10589282/2c6eec02bb1c/41598_2023_45079_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4ea/10589282/035715f95f9e/41598_2023_45079_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4ea/10589282/65dd2ccf1412/41598_2023_45079_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4ea/10589282/52167a5ea0f3/41598_2023_45079_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4ea/10589282/e0edd7c24f4a/41598_2023_45079_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4ea/10589282/2c6eec02bb1c/41598_2023_45079_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4ea/10589282/035715f95f9e/41598_2023_45079_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4ea/10589282/65dd2ccf1412/41598_2023_45079_Fig5_HTML.jpg

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Synthetic MRI in breast cancer: differentiating benign from malignant lesions and predicting immunohistochemical expression status.

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[3]
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[4]
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[5]
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[7]
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[8]
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本文引用的文献

[1]
Palbociclib for Residual High-Risk Invasive HR-Positive and HER2-Negative Early Breast Cancer-The Penelope-B Trial.

J Clin Oncol. 2021-5-10

[2]
Diffusion-weighted Imaging Allows for Downgrading MR BI-RADS 4 Lesions in Contrast-enhanced MRI of the Breast to Avoid Unnecessary Biopsy.

Clin Cancer Res. 2021-4-1

[3]
The diagnostic performance of quantitative mapping in breast cancer patients: a preliminary study using synthetic MRI.

Cancer Imaging. 2020-12-14

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The effect of gadolinium-based contrast agent administration on magnetic resonance fingerprinting-based T relaxometry in patients with prostate cancer.

Sci Rep. 2020-11-24

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Pretreatment structural and arterial spin labeling MRI is predictive for p53 mutation in high-grade gliomas.

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[7]
Contrast-enhanced magnetic resonance (MR) T1 mapping with low-dose gadolinium-diethylenetriamine pentaacetic acid (Gd-DTPA) is promising in identifying clear cell renal cell carcinoma histopathological grade and differentiating fat-poor angiomyolipoma.

Quant Imaging Med Surg. 2020-5

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Cells. 2020-4-24

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Utility of synthetic MRI in predicting the Ki-67 status of oestrogen receptor-positive breast cancer: a feasibility study.

Clin Radiol. 2020-5

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Can apparent diffusion coefficient (ADC) distinguish breast cancer from benign breast findings? A meta-analysis based on 13 847 lesions.

BMC Cancer. 2019-10-15

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