In European journal of radiology ; h5-index 47.0
PURPOSE : To evaluate the feasibility of isotropic 3D high-resolution T2-weighted imaging (T2WI) MRI sequences and compare the images reconstructed by integrating artificial intelligence-compressed sensing (AI-CS), compressed sensing (CS), and conventional 2D T2WI sequences for quality.
MATERIALS AND METHODS : Fifty-two female patients (ages: 26-80 years) with suspected breast cancer were enrolled. They underwent breast MRI examinations using three sequences: conventional T2WI, CS 3D T2WI, and AI-CS 3D T2WI. Image quality, signal-to-noise ratio (SNR), contrast-to-noise ratio, tumor volume, and maximal tumor diameter were compared using the Friedman test. Image quality was scored on a 5-point scale, with 1 indicating nonassessable quality and 5 indicating excellent quality. Tumor volume and maximal tumor diameter were compared based on AI-CS 3D T2WI (slightly high signal), conventional T2WI, and dynamic contrast-enhanced (DCE) sequences.
RESULTS : All three T2WI were successfully performed in all patients. 3D CS and AI-CS were significantly better than conventional T2WI in terms of lesion conspicuity and morphology, structural details, overall image quality, diagnostic information for breast lesions, and breast tissue delineation (P < 0.001). The SNR of conventional T2WI was significantly higher for 3D T2WI sequences. The contrast-to-noise ratio was significantly higher for AI-CS 3D T2WI than for conventional T2WI sequence. There was no significant difference in tumor volume between DCE (8.08 ± 16.51) and AI-CS 3D T2WI (8.25 ± 16.29) sequences and no significant differences in tumor diameter among DCE, AI-CS 3D T2WI, and conventional T2WI sequences.
CONCLUSION : Isotropic-resolution 3D T2WI sequences can be acquired using AI-CS while maintaining image quality and diagnostic value, which may pave the way for isotropic 3D high-resolution T2WI for clinical application.
Yang Fan, Pan Xuelin, Zhu Ke, Xiao Yitian, Yue Xun, Peng Pengfei, Zhang Xiaoyong, Huang Juan, Chen Jie, Yuan Yuan, Sun Jiayu
3D T2WI, Breast MRI, Compressed sensing, Integrating artificial intelligence