扩散梯度非线性偏差校正可降低乳腺癌骨转移灶表观扩散系数（ADC）值的偏差。

Diffusion gradient nonlinearity bias correction reduces bias of breast cancer bone metastasis ADC values.

作者信息

Buus Thomas W, Jensen Anders B, Pedersen Erik M

机构信息

The Department of Radiology, Aarhus University Hospital, Aarhus N, Denmark.

Department of Oncology, Aarhus University Hospital, Aarhus N, Denmark.

出版信息

J Magn Reson Imaging. 2020 Mar;51(3):904-911. doi: 10.1002/jmri.26873. Epub 2019 Jul 16.

CONTRACT GRANT SPONSOR

Health Research Fund of Central Denmark Region.

BACKGROUND

Diffusion gradient nonlinearity (DGNL) bias causes apparent diffusion coefficient (ADC) values to drop with increasing superior-inferior (SI) isocenter offset. This is a concern when performing quantitative diffusion-weighted imaging (DWI).

PURPOSE/HYPOTHESIS: To investigate if DGNL ADC bias can be corrected in breast cancer bone metastases using a clinical DWI protocol and an online correction algorithm.

STUDY TYPE

Prospective.

SUBJECTS/PHANTOM: A diffusion phantom (Model 128, High Precision Devices, Boulder, CO) was used for in vitro validation. Twenty-three women with bone-metastasizing breast cancer were enrolled to assess DGNL correction in vivo.

FIELD STRENGTH/SEQUENCE: DWI was performed on a 1.5T MRI system as single-shot, spin-echo, echo-planar imaging with short-tau inversion recovery (STIR) fat-saturation. ADC maps with and without DGNL correction were created from the b50 and b800 images.

ASSESSMENT

Uncorrected and DGNL-corrected ADC values were measured in phantom and bone metastases by placing regions of interest on b800 images and copying them to the ADC map. The SI offset was recorded.

STATISTICAL TESTS

In all, 79 bone metastases were assessed. ADC values with and without DGNL correction were compared at 14 cm SI offset using a two-tailed t-test.

RESULTS

In the diffusion phantom, DGNL correction increased SI offset, where ADC bias was lower than 5%, from 7.3-13.8 cm. Of the 23 patients examined, six had no metastases in the covered regions. In the remaining patients, bias of uncorrected bone metastasis ADC values was 19.1% (95% confidence interval [CI]: 15.4-22.9%) at 14 cm SI offset. After DGNL correction, ADC bias was significantly reduced to 3.5% (95% CI: 0.7-6.3%, P < 0.001), thus reducing bias due to DGNL by 82%.

DATA CONCLUSION

Online DGNL correction corrects DGNL ADC value bias and allows increased station lengths in the SI direction.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:904-911.

合同授予方

丹麦中部地区健康研究基金。

背景

扩散梯度非线性（DGNL）偏差导致表观扩散系数（ADC）值随上下（SI）等中心偏移增加而下降。这在进行定量扩散加权成像（DWI）时是一个问题。

目的/假设：研究使用临床DWI方案和在线校正算法能否校正乳腺癌骨转移中的DGNL ADC偏差。

研究类型

前瞻性研究。

研究对象/模型：使用扩散模型（128型，高精度设备公司，科罗拉多州博尔德市）进行体外验证。招募了23名患有骨转移乳腺癌的女性，以评估体内DGNL校正情况。

场强/序列：在1.5T MRI系统上进行DWI，采用单次激发、自旋回波、回波平面成像以及短反转时间反转恢复（STIR）脂肪饱和技术。从b50和b800图像创建有无DGNL校正的ADC图。

评估

通过在b800图像上放置感兴趣区域并将其复制到ADC图，测量模型和骨转移灶中未校正和经DGNL校正的ADC值。记录SI偏移。

统计检验

共评估了79个骨转移灶。使用双尾t检验比较在14 cm SI偏移时有无DGNL校正的ADC值。

结果

在扩散模型中，DGNL校正增加了SI偏移，其中ADC偏差低于5%时，SI偏移从7.3 cm增加到13.8 cm。在检查的23例患者中，6例在覆盖区域无转移灶。在其余患者中，在14 cm SI偏移时，未校正的骨转移灶ADC值偏差为19.1%（95%置信区间[CI]：15.4 - 22.9%）。经DGNL校正后，ADC偏差显著降低至3.5%（95% CI：0.7 - 6.3%，P < 0.001），从而将DGNL引起的偏差降低了82%。

数据结论

在线DGNL校正可校正DGNL ADC值偏差，并允许在SI方向增加扫描长度。

证据水平

2 技术效能：2级《磁共振成像杂志》2020年；51:904 - 911。