Feasibility of deep learning combined with compressed sensing technology to improve breath-hold three-dimensional magnetic resonance cholangiopancreatography image quality
10.3760/cma.j.cn112149-20230927-00244
- VernacularTitle:深度学习结合压缩感知技术改善屏气三维磁共振胰胆管成像图像质量的可行性研究
- Author:
Ye YUAN
1
;
Yu ZHANG
;
Hanyu LI
;
Dao'en ZHANG
;
Tingting YANG
;
Zhenlin LI
;
Chunchao XIA
Author Information
1. 四川大学华西医院放射科，成都 610041
- Keywords:
Magnetic resonance imaging;
Cholangiopancreatography;
Deep learning;
Compressed sensing;
Acceleration factor
- From:
Chinese Journal of Radiology
2024;58(9):935-940
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the improvement of image quality of different acceleration factors in breath-hold three-dimensional magnetic resonance cholangiopancreatography (3D MRCP) using deep learning (DL) and compressed sensing (CS) technology.Methods:A total of 68 patients who underwent upper abdominal 3D MRCP examination at West China Hospital of Sichuan University from March to August 2023 were prospectively included. The patients were subdivided into three groups randomly with the following paramters: CS group with an acceleration factor of 24 (CS-24); DL-CS group with acceleration factors 24 (DL-CS-24) and 33 (DL-CS-33) respectively. The signal-to-noise ratio (SNR), contrast ratio (CR) and contrast-to-noise ratio (CNR) of the three sets of images were measured, and the overall image quality, background suppression, artifacts, and visibility of bile ducts and pancreatic ducts at all levels were subjectively evaluated. Chi-square test and Friedman test were used to perform statistical analysis on the number of unsatisfactory diagnostic images and subjective and objective indicators of the three groups of sequences respectively.Results:The scanning time of the DL-CS-33 group (9 s) was 30% shorter than that of the CS-24 group and DL-CS-24 group (13s). The images of DL-CS-33 group from 68 patients all met the clinical diagnostic requirements and statistically differences were found between the images from CS-24 group and DL-CS-24 group (all P<0.05). There were no statistically differences in SNR, CR, CNR, overall image quality, artifacts, and visibility scores of bile ducts and pancreatic ducts at all levels between the DL-CS-33 group and the CS-24 group (all P>0.05). The SNR, CR, CNR, intrahepatic bile duct, main pancreatic duct and overall image quality of the DL-CS -24 group were better than those of the CS-24 group (all P<0.05). Conclusions:DL-CS technology could improves breath-hold 3D MRCP image quality with the 24 acceleration factor with no additioanl scanning time. DL-CS technology combined with a high acceleration factor of 33 further reduces scanning time while ensuring overall image quality, providing a fast breath-hold scanning solution.
