表观扩散系数直方图在新辅助化疗前预测luminal型乳腺癌疗效的价值

耿小川; 华佳; 庄治国; 陈洁; 张科蓓; 张庆; 成芳

doi:10.19732/j.cnki.2096-6210.2019.06.005

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表观扩散系数直方图在新辅助化疗前预测luminal型乳腺癌疗效的价值

论著 | 更新时间：2025-12-15

- 表观扩散系数直方图在新辅助化疗前预测luminal型乳腺癌疗效的价值
- Magnetic resonance imaging with apparent diffusion coef f icient histogram analysis: evaluation of luminal type breast cancer prior to neoadjuvant chemotherapy
- 肿瘤影像学 2019年28卷第6期页码：377-383
- 作者机构：
  
  上海交通大学医学院附属仁济医院放射科,上海,200127
- 作者简介：
- 基金信息：
  
  上海申康医院发展中心专科疾病临床“五新”转化项目（16CR3024A）;上海市科学技术委员会高新技术领域重点项目（18511102900;18511102901）。
- DOI：10.19732/j.cnki.2096-6210.2019.06.005
  中图分类号：
- 网络出版：2019-12-28，
  
  纸质出版：2019-12-28
- 稿件说明：
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耿小川,华佳,庄治国,等. 表观扩散系数直方图在新辅助化疗前预测luminal型乳腺癌疗效的价值[J]. 肿瘤影像学, 2019, 28(6): 377-383 https://doi.

org/10.19732/j.cnki.2096-6210.2019.06.005
耿小川,华佳,庄治国,等. 表观扩散系数直方图在新辅助化疗前预测luminal型乳腺癌疗效的价值[J]. 肿瘤影像学, 2019, 28(6): 377-383 https://doi. DOI： 10.19732/j.cnki.2096-6210.2019.06.005.

org/10.19732/j.cnki.2096-6210.2019.06.005 DOI：

摘要

目的：

探讨表观扩散系数（apparent diffusion coefficient，ADC）直方图在新辅助化疗（neoadjuvant chemotherapy，NAC）前预测luminal型乳腺癌疗效的临床价值。

方法：

回顾性分析NAC前穿刺病理及免疫组织化学证实为luminal型乳腺癌、完善磁共振成像（magnetic resonance imaging，MRI）检查［包括扩散加权成像（diffusion-weighted imaging，DWI）序列］、NAC后手术的患者57例，其中有效组17例。记录乳腺癌的ADC直方图参数，包括平均值、最小值、标准差、最大值、10%、25%、50%、75%及90%百分位数、偏度和峰度。用组内相关系数（intraclass correlation coefficient，ICC）分析观察者间和观察者内一致性。有效组和无效组间各参数的比较采用独立样本t检验。应用受试者工作特征（receiver operating characteristic，ROC）曲线评价ADC直方图参数预测NAC疗效的诊断效能。

结果：

ADC直方图参数观察者间ICC（0.089~0.845）均低于观察者内（0.306~0.916）。最小值、10%、25%及50%的一致性较好。有效组的最小值、10%和25%的ADC值分别为（0.540.36）10

-3

、（0.900.23）10

-3

、（1.020.23）10

-3

/s。无效组的最小值、10%和25%的ADC值分别为（0.290.28）10

-3

、（0.710.20）10

-3

、（0.850.19）10

-3

/s。有效组的最小值、10%和25%的ADC值均高于无效组，差异有统计学意义（

＜0.05）。10%的ROC曲线的曲线下面积最大（0.746），以0.74610

-3

/s为最佳界值，灵敏度、特异度分别为82.35%、65.00%。但10%的诊断效能未明显高于25%（ROC曲线的曲线下面积0.724，

=0.505）。

结论：

ADC直方图在NAC前预测luminal型乳腺癌有

一定的诊断价值，10%、25%的诊断价值较高且一致性较好。

Abstract

Objective:

To determine response prior to neoadjuvant chemotherapy (NAC) in patients with luminal type breast cancer by using magnetic resonance imaging (MRI) apparent diffusion coeff icient (ADC) histogram analysis.

Methods:

Fifty-seven patients with luminal type breast cancer conf irmed by core needle biopsy underwent MRI (including diffusion-weighted imaging sequence) before NAC. Surgery was performed after NAC. Seventeen patients were responders. ADC histogram parameters were recorded

including mean

minimum

standard deviation

maximum

10%

25%

50%

75%

and 90% percentiles

skewness and kurtosis. Inter-observer and intra-observer agreement were analyzed using intraclass correlation coeff icient (ICC). ADC histogram parameters between responders and non-responders were compared using an independent sample t test. The receiver operatingcharacteristic (ROC) curve was used to evaluate the diagnostic performance of ADC histogram parameters in the response prediction.

Results:

The inter-observer ICCs (0.089~0.845) of the ADC histogram parameters were lower than that of the intra-observer (0.306~0.916). The agreement of minimum

10%

25% and 50% were excellent. The minimum

10% and 25% of responders were (0.540.36)10

-3

(0.900.23)10

-3

and (1.020.23)10

-3

/s. The minimum

10% and 25% of non-responders were (0.290.28)10

-3

(0.710.20)10

-3

and (0.850.19)10

-3

/s. The minimum

10% and 25% of responders were higher than non-responders (

＜0.05)

and the area under curve (AUC) of the 10% percentile was the largest (0.746). When a cut-off value of 0.74610

-3

/s in 10% percentile was used

the sensitivity of 82.35% and specif icity of 65.00% were achieved. However

the diagnostic performance of 10% percentile was not signif

icantly higher than 25% (AUC was 0.724

=0.505).

Conclusion:

In patients with luminal type breast cancer

the ADC histogram analysis was useful in the response prediction prior to NAC

and 10% and 25% percentiles had better diagnostic performance and excellent agreement.

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