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基于伽马分布的统计模型对前列腺癌进行扩散加权成像。

Diffusion-weighted imaging of prostate cancer using a statistical model based on the gamma distribution.

作者信息

Shinmoto Hiroshi, Oshio Koichi, Tamura Chiharu, Soga Shigeyoshi, Okamura Teppei, Yamada Kentaro, Kaji Tastumi, Mulkern Robert V

机构信息

Department of Radiology, National Defense Medical College, Saitama, Japan.

Department of Diagnostic Radiology, Keio University School of Medicine, Tokyo, Japan.

出版信息

J Magn Reson Imaging. 2015 Jul;42(1):56-62. doi: 10.1002/jmri.24761. Epub 2014 Sep 15.

Abstract

PURPOSE

To assess the adequacy of a statistical model based on the gamma distribution for diffusion signal decays of prostate cancer (PCa) using b-values ranging up to 2000 sec/mm(2) , and to evaluate the differences in gamma model parameters for PCa, benign prostatic hyperplasia (BPH), and peripheral zone (PZ).

MATERIALS AND METHODS

Twenty-six patients with histologically proven PCa underwent diffusion-weighted magnetic resonance imaging using five b-values (0, 500, 1000, 1500, 2000 sec/mm(2) ). The acquired signal decay curves were fit with both gamma and truncated Gaussian models and a statistical comparison between the two fits was performed. The acquired parameters using the gamma model (mean, standard deviation, the area fraction for D < 1.0 mm(2) /s [Frac<1.0], the area fraction of D > 3.0 mm(2) /s [Frac>3.0]) were compared between PCa, BPH, and PZ.

RESULTS

The gamma model provided a statistically improved fit over the truncated Gaussian model in PCa. The mean and the standard deviation were significantly lower in PCa than in BPH and PZ (P < 0.01). Frac<1.0 was significantly higher in PCa than in BPH and PZ, and Frac>3.0 was significantly lower in PCa than in BPH and PZ (P < 0.01).

CONCLUSION

A statistical model based on the gamma distribution proved suitable for describing diffusion signal decay curves of PCa. This approach may provide better correlation between diffusion signal decay and histological information in the prostate gland.

摘要

目的

使用高达2000秒/平方毫米的b值,评估基于伽马分布的统计模型对前列腺癌(PCa)扩散信号衰减的拟合程度,并评估PCa、良性前列腺增生(BPH)和外周带(PZ)的伽马模型参数差异。

材料与方法

26例经组织学证实的PCa患者接受了使用五个b值(0、500、1000、1500、2000秒/平方毫米)的扩散加权磁共振成像。采集的信号衰减曲线分别用伽马模型和截断高斯模型进行拟合,并对两种拟合结果进行统计学比较。比较PCa、BPH和PZ之间使用伽马模型获得的参数(平均值、标准差、D<1.0平方毫米/秒的面积分数[Frac<1.0]、D>3.0平方毫米/秒的面积分数[Frac>3.0])。

结果

在PCa中,伽马模型比截断高斯模型提供了统计学上更好的拟合。PCa的平均值和标准差显著低于BPH和PZ(P<0.01)。PCa的Frac<1.0显著高于BPH和PZ,PCa的Frac>3.0显著低于BPH和PZ(P<0.01)。

结论

基于伽马分布的统计模型被证明适用于描述PCa的扩散信号衰减曲线。这种方法可能在前列腺中扩散信号衰减与组织学信息之间提供更好的相关性。

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