基于体模的低剂量和超低剂量Transformer增强型2048矩阵CT成像图像质量评估

Phantom-based evaluation of image quality in Transformer-enhanced 2048-matrix CT imaging at low and ultralow doses.

作者信息

Li Qingyao, Liu Ling, Zhang Yaping, Zhang Lu, Wang Lingyun, Pan Zhijie, Xu Min, Zhang Shuai, Xie Xueqian

机构信息

School of Health Science and Engineering, University of Shanghai for Science and Technology, Jun Gong Rd. 516, Shanghai, 200093, China.

Radiology department, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Hai Ning Rd. 100, Shanghai, 200080, China.

出版信息

Jpn J Radiol. 2025 Apr 7. doi: 10.1007/s11604-025-01755-z.

DOI:10.1007/s11604-025-01755-z

PMID:40193009

Abstract

PURPOSE

To compare the quality of standard 512-matrix, standard 1024-matrix, and Swin2SR-based 2048-matrix phantom images under different scanning protocols.

MATERIALS AND METHODS

The Catphan 600 phantom was scanned using a multidetector CT scanner under two protocols: 120 kV/100 mA (CT dose index volume = 3.4 mGy) to simulate low-dose CT, and 70 kV/40 mA (0.27 mGy) to simulate ultralow-dose CT. Raw data were reconstructed into standard 512-matrix images using three methods: filtered back projection (FBP), adaptive statistical iterative reconstruction at 40% intensity (ASIR-V), and deep learning image reconstruction at high intensity (DLIR-H). The Swin2SR super-resolution model was used to generate 2048-matrix images (Swin2SR-2048), while the super-resolution convolutional neural network (SRCNN) model generated 2048-matrix images (SRCNN-2048). The quality of 2048-matrix images generated by the two models (Swin2SR and SRCNN) was compared. Image quality was evaluated by ImQuest software (v7.2.0.0, Duke University) based on line pair clarity, task-based transfer function (TTF), image noise, and noise power spectrum (NPS).

RESULTS

At equivalent radiation doses and reconstruction method, Swin2SR-2048 images identified more line pairs than both standard-512 and standard-1024 images. Except for the 0.27 mGy/DLIR-H/standard kernel sequence, TTF-50% of Teflon increased after super-resolution processing. Statistically significant differences in TTF-50% were observed between the standard 512, 1024, and Swin2SR-2048 images (all p < 0.05). Swin2SR-2048 images exhibited lower image noise and NPS compared to both standard 512- and 1024-matrix images, with significant differences observed in all three matrix types (all p < 0.05). Swin2SR-2048 images also demonstrated superior quality compared to SRCNN-2048, with significant differences in image noise (p < 0.001), NPS (p < 0.05), and TTF-50% for Teflon (p < 0.05).

CONCLUSION

Transformer-enhanced 2048-matrix CT images improve spatial resolution and reduce image noise compared to standard-512 and -1024 matrix images.

摘要

目的

比较不同扫描协议下标准512矩阵、标准1024矩阵以及基于Swin2SR的2048矩阵体模图像的质量。

材料与方法

使用多排CT扫描仪在两种协议下对Catphan 600体模进行扫描：120 kV/100 mA（CT剂量指数容积 = 3.4 mGy）以模拟低剂量CT，以及70 kV/40 mA（0.27 mGy）以模拟超低剂量CT。使用三种方法将原始数据重建为标准512矩阵图像：滤波反投影（FBP）、40%强度的自适应统计迭代重建（ASIR-V）以及高强度深度学习图像重建（DLIR-H）。使用Swin2SR超分辨率模型生成2048矩阵图像（Swin2SR-2048），而超分辨率卷积神经网络（SRCNN）模型生成2048矩阵图像（SRCNN-2048）。比较由这两种模型（Swin2SR和SRCNN）生成的2048矩阵图像的质量。通过ImQuest软件（v7.2.0.0，杜克大学）基于线对清晰度、基于任务的传递函数（TTF）、图像噪声和噪声功率谱（NPS）对图像质量进行评估。

结果

在等效辐射剂量和重建方法下，Swin2SR-2048图像识别出的线对比标准512和标准1024图像更多。除了0.27 mGy/DLIR-H/标准核序列外，超分辨率处理后聚四氟乙烯的TTF-50%增加。在标准512、1024和Swin2SR-2048图像之间观察到TTF-50%存在统计学显著差异（所有p < 0.05）。与标准512和1024矩阵图像相比，Swin2SR-2048图像表现出更低的图像噪声和NPS，在所有三种矩阵类型中均观察到显著差异（所有p < 0.05）。Swin2SR-2048图像与SRCNN-2048相比也显示出更高的质量，在图像噪声（p < 0.001）、NPS（p < 0.05）以及聚四氟乙烯的TTF-50%（p < 0.05）方面存在显著差异。