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在前列腺扩散加权成像中使用复数平均的增强图像处理:对图像质量和病变可检测性的影响。

Enhanced Image Processing Using Complex Averaging in Diffusion-Weighted Imaging of the Prostate: The Impact on Image Quality and Lesion Detectability.

作者信息

Werner Sebastian, Zinsser Dominik, Esser Michael, Nickel Dominik, Nikolaou Konstantin, Othman Ahmed E

机构信息

Department of Diagnostic and Interventional Radiology, Eberhard Karls University, Tuebingen University Hospital, 72076 Tuebingen, Germany.

MR Application Predevelopment, Siemens Healthineers, 91052 Erlangen, Germany.

出版信息

Diagnostics (Basel). 2023 Jul 10;13(14):2325. doi: 10.3390/diagnostics13142325.

Abstract

Diffusion-weighted images of the prostate can suffer from a "hazy" background in low signal-intensity areas. We hypothesize that enhanced image processing (EIP) using complex averaging reduces artifacts, noise, and distortion in conventionally acquired diffusion-weighted images and synthesized high b-value images, thus leading to higher image quality and better detection of potentially malignant lesions. Conventional DWI trace images with a b-value of 1000 s/mm (b1000), calculated images with a b-value of 2000 s/mm (cb2000), and ADC maps of 3T multiparametric prostate MRIs in 53 patients (age 68.8 ± 10 years) were retrospectively evaluated. Standard images were compared to images using EIP. In the standard images, 36 lesions were detected in the peripheral zone and 20 in the transition zone. In 13 patients, EIP led to the detection of 8 additional lesions and the upgrading of 6 lesions; 6 of these patients were diagnosed with prostate carcinoma Gleason 7 or 8. EIP improved qualitative ratings for overall image quality and lesion detectability. Artifacts were significantly reduced in the cb2000 images. Quantitative measurements for lesion detectability expressed as an SI ratio were significantly improved. EIP using complex averaging led to image quality improvements in acquired and synthesized DWI, potentially resulting in elevated diagnostic accuracy and management changes.

摘要

前列腺的扩散加权图像在低信号强度区域可能会出现“模糊”背景。我们假设,使用复数平均的增强图像处理(EIP)可减少传统采集的扩散加权图像和合成高b值图像中的伪影、噪声和失真,从而提高图像质量,并更好地检测潜在的恶性病变。回顾性评估了53例患者(年龄68.8±10岁)的3T多参数前列腺MRI的常规扩散加权成像(DWI)迹线图像(b值为1000 s/mm²,即b1000)、计算图像(b值为2000 s/mm²,即cb2000)和表观扩散系数(ADC)图。将标准图像与使用EIP的图像进行比较。在标准图像中,在外周区检测到36个病变,在移行区检测到20个病变。在13例患者中,EIP导致额外检测到8个病变,并使6个病变的分级提高;其中6例患者被诊断为Gleason 7或8级前列腺癌。EIP提高了整体图像质量和病变可检测性的定性评分。cb2000图像中的伪影显著减少。以信号强度比表示的病变可检测性的定量测量结果显著改善。使用复数平均的EIP可提高采集和合成DWI的图像质量,可能会提高诊断准确性并改变治疗方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/deae/10378377/560b51430e2d/diagnostics-13-02325-g001.jpg

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