ArticleQuantitative imaging in medicine and surgery2025
AI-assisted compressed sensing MRI improves imaging quality in rectal cancer: a comparative study with conventional acceleration techniques.
Article in Quantitative imaging in medicine and surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- AI-Assisted Compressed Sensing for Optimized Inner Ear Imaging: a Multi-Rater MRI Evaluation of CSAI T2-DRIVE.Clinical neuroradiology · 2026Article
- Temporal AI-assisted compressed sensing for high-resolution, motion-robust small-bowel MR enterography without antiperistaltic agents: a feasibility study.European radiology · 2026Article
- Validation and feasibility of fast knee MRI using a deep learning-assisted 3D iterative image enhancement system.Quantitative imaging in medicine and surgery · 2026Article
- Feasibility of artificial intelligence-assisted fast magnetic resonance imaging technology in the ankle joint injury: a comparison of the proton density-weighted image.Frontiers in radiology · 2025Article
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Abstract
Background: Artificial intelligence (AI)-assisted compressed sensing (ACS) is widely used in various parts of the body, but the application of this technology in the rectum is still rare. This study aimed to evaluate the feasibility of super-resolution (SR) T2-weighted imaging (T2WI) based on ACS in rectal cancer (RC) by comparing with compressed sensing (CS) and parallel imaging (PI). Methods: In this prospective study, 29 patients with rectal adenocarcinoma were enrolled, and three groups of SR rectal T2WI images based on ACS, CS, and PI (ACS-T2WI, CS-T2WI, and PI-T2WI) were obtained, using the same scanning time for each group. Two radiologists independently assessed the visibility of structures, tissue edge sharpness, image artifacts, overall image quality, and confidence in N staging for the three sequences using a five-point Likert scale; the scores of the three sequences were compared and the agreement between two readers was assessed. In addition, the quantitative parameters of the three groups, sharpness, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were compared. T staging based on magnetic resonance imaging (MRI) was performed by two readers separately using the three sequences combined with other conventional scanning sequences. The consistency between T staging based on MRI (mrT staging) and pathological T staging (PT staging) of the two readers and the diagnostic accuracy of every sequence was compared. Results: The scores of ACS-T2WI were higher in visibility of structures, tissue edge sharpness, overall image quality, and confidence in N staging than CS-T2WI and PI-T2WI (P<0.001). There was no statistical difference in the scores of image artifacts among the three sequences (P=0.18). The sharpness of ACS-T2WI was higher than that of CS-T2WI and PI-T2WI (P<0.001). The SNR of CS-T2WI was slightly higher than that of ACS-T2WI and PI-T2WI (P=0.004). There was no statistically significant difference in CNR among the three sequences (P=0.425). The consistency between mrT staging of ACS-T2WI and PT staging was higher than that of CS-T2WI and PI-T2WI. The two readers had a higher diagnostic accuracy for ACS-T2WI (89.66%) than for CS-T2WI (79.31%) and PI-T2WI (75.86%), but the difference was not statistically significant. Conclusions: By using ACS to increase the resolution through a larger matrix size, higher quality images can be obtained within the same scanning time as traditional acceleration techniques. The SR T2WI based on ACS can be well applied in the clinical scanning of RC.
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