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基于乳腺病变全容积图像的扩散峰度成像直方图分析

Histogram analysis of diffusion kurtosis imaging based on whole-volume images of breast lesions.

作者信息

Li Ting, Hong Yuan, Kong Dexing, Li Kangan

机构信息

The Department of Radiology, First People's Hospital of Changzhou, Jiangsu, P.R. China.

School of Mathematical Sciences, Zhejiang University, Hangzhou, P.R. China.

出版信息

J Magn Reson Imaging. 2020 Feb;51(2):627-634. doi: 10.1002/jmri.26884. Epub 2019 Aug 5.

Abstract

BACKGROUND

Breast diffusion kurtosis imaging (DKI) is a novel MRI technique to assess breast cancer but the effectivity still remains to be improved.

PURPOSE

To investigate the performance of whole-volume histogram parameters derived from a DKI model for differentiating benign and malignant breast lesions.

STUDY TYPE

Retrospective.

POPULATION

In all, 120 patients with breast lesions (62 malignant, 58 benign).

SEQUENCE

DKI sequence with seven b-values (0, 500, 1000, 1500, 2000, 2500, and 3000 s/mm ) and DWI sequence with two b-values (0 and 1000 s/mm ) on 3.0T MRI.

ASSESSMENT

Histogram parameters of the DKI model (K and D) and the DWI model (ADC), including the minimum, maximum, mean, percentile values (25th, 50th, 75th, and 95th), standard deviation, kurtosis and skewness, were calculated by two radiologists for the whole lesion volume.

STATISTICAL TESTS

Student's t-test was used to compare malignant and benign lesions. The diagnostic performances were evaluated by receiver operating characteristic (ROC) analysis.

RESULTS

K , D , and ADC had the highest area under the curve (AUC) (0.875, 0.830, and 0.847, respectively), sensitivity (85.5%, 74.2%, and 77.4%, respectively), and accuracy (85.0%, 79.2%, and 81.7%, respectively) in their individual histogram parameter groups, and K was found to outperform D and ADC . ADC histogram parameters (from ADC to ADC ) were significantly lower than D histogram parameters in all groups.

DATA CONCLUSION

K , D , and ADC were found to be better metrics than the corresponding average values for differentiating benign from malignant tumors. Histogram parameters derived from the DKI model provided more information and had better diagnostic performance than ADC parameters derived from the DWI model.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:627-634.

摘要

背景

乳腺扩散峰度成像(DKI)是一种用于评估乳腺癌的新型磁共振成像(MRI)技术,但其有效性仍有待提高。

目的

探讨基于DKI模型的全容积直方图参数在鉴别乳腺良恶性病变中的性能。

研究类型

回顾性研究。

研究对象

共120例乳腺病变患者(62例恶性,58例良性)。

序列

在3.0T MRI上采用具有七个b值(0、500、1000、1500、2000、2500和3000 s/mm²)的DKI序列和具有两个b值(0和1000 s/mm²)的扩散加权成像(DWI)序列。

评估

由两名放射科医生计算DKI模型(K和D)和DWI模型(表观扩散系数[ADC])的直方图参数,包括最小值、最大值、平均值、百分位数(第25、50、75和95百分位数)、标准差、峰度和偏度,针对整个病变体积进行计算。

统计检验

采用学生t检验比较恶性和良性病变。通过受试者操作特征(ROC)分析评估诊断性能。

结果

在各自的直方图参数组中,K、D和ADC的曲线下面积(AUC)最高(分别为0.875、0.830和0.847),灵敏度最高(分别为85.5%、74.2%和77.4%),准确性最高(分别为85.0%、79.2%和81.7%),且发现K优于D和ADC。在所有组中,ADC直方图参数(从ADC₁到ADC₉)均显著低于D直方图参数。

数据结论

发现K、D和ADC在鉴别良性与恶性肿瘤方面比相应的平均值是更好的指标。基于DKI模型的直方图参数比基于DWI模型的ADC参数提供了更多信息且具有更好的诊断性能。

证据水平

3 技术效能:2级 《磁共振成像杂志》2020年;51:627 - 634。

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