Deep-learning-accelerated T1-MPRAGE MRI for quantification and visual grading of cerebral volume in memory loss patients.

Radiology advances Pub Date : 2025-06-02 eCollection Date: 2025-07-01 DOI:10.1093/radadv/umaf022
Nelson Gil, Azadeh Tabari, Dominik Nickel, Wei-Ching Lo, Bryan Clifford, Stephen Cauley, Min Lang, Sittaya Buathong, Azadeh Hajati, Shohei Fujita, Seonghwan Yee, John Conklin, Susie Huang
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Abstract

Purpose: To evaluate a physics-based deep-learning-accelerated super-resolution T1-weighted MPRAGE sequence (DL-MPRAGE) against standard 3-dimensional T1-weighted MPRAGE (STD-MPRAGE) for quantitative and qualitative regional cortical volume assessment.

Materials and methods: This prospective single-center study included patients undergoing evaluation for memory loss on 3T MRI scanners (MAGNETOM Vida, Siemens Healthineers, Forchheim, Germany) from October 2023 to January 2024. The absolute symmetrized percent change in cortical volume and thickness was assessed on DL- and STD-MPRAGE images using the FreeSurfer brain segmentation algorithm. Bland-Altman analysis evaluated the agreement in volumetrics for each anatomical region. Additionally, 2 blinded radiologists independently qualitatively rated image quality metrics and cortical volume loss for anatomical regions based on standardized scales.

Results: A total of 64 participants (29 women [45%], mean age 62 years ±16 [SD]) were evaluated. DL-MPRAGE increased spatial resolution from 1 mm to 0.5 mm while reducing scan time by more than half (2:11 vs. 5:21). Mean regional volumes for DL-MPRAGE were systematically lower than for STD-MPRAGE (eg, 17 226 ± 2011 vs. 17 923 ± 2185 mm3, corresponding to an absolute difference between the means of 697 mm3, for the cingulate gyrus, P < .004). Corresponding absolute symmetrized percent change values averaged 2.8% across brain regions, with the largest mean value being 5.08% for the cingulate gyrus. Bland-Altman analysis demonstrated high agreement in quantitative measurements for both volume and thickness. On reader assessment, DL-MPRAGE was noninferior to STD-MPRAGE across image quality metrics (P < .01) and equivalent in assessing volume loss.

Conclusions: DL-MPRAGE offers quantitatively and qualitatively equivalent volumetric estimation compared to STD-MPRAGE while improving spatial resolution and acquisition speed for patients undergoing evaluation for memory loss.

Abstract Image

Abstract Image

Abstract Image

深度学习加速T1-MPRAGE MRI对记忆丧失患者脑容量的量化和视觉分级。
目的:评估基于物理的深度学习加速超分辨率t1加权MPRAGE序列(DL-MPRAGE)与标准三维t1加权MPRAGE (STD-MPRAGE)的定量和定性区域皮质体积评估。材料和方法:本前瞻性单中心研究纳入了2023年10月至2024年1月在3T MRI扫描仪(MAGNETOM Vida, Siemens Healthineers, Forchheim, Germany)上进行记忆丧失评估的患者。使用FreeSurfer脑分割算法评估DL和STD-MPRAGE图像上皮层体积和厚度的绝对对称变化百分比。Bland-Altman分析评估了每个解剖区域的体积一致性。此外,2名盲法放射科医生独立定性评价了基于标准化尺度的解剖区域的图像质量指标和皮质体积损失。结果:共纳入64例受试者(女性29例[45%],平均年龄62岁±16岁[SD])。DL-MPRAGE将空间分辨率从1毫米提高到0.5毫米,同时将扫描时间缩短了一半以上(2:11 vs. 5:21)。DL-MPRAGE的平均区域体积系统性低于STD-MPRAGE(例如,17 226±2011 vs. 17 923±2185 mm3,对应于扣带回平均值697 mm3的绝对差异,P .004)。相应的绝对对称百分比变化值在大脑各区域平均为2.8%,其中扣带回的平均值最大,为5.08%。Bland-Altman分析表明,体积和厚度的定量测量结果高度一致。在读者评估方面,DL-MPRAGE在图像质量指标上不逊于STD-MPRAGE (P < 0.01),在评估体积损失方面也相当。结论:与STD-MPRAGE相比,DL-MPRAGE提供了定量和定性等效的体积估计,同时提高了记忆丧失评估患者的空间分辨率和获取速度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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