From Faster Frames to Flawless Focus: Deep Learning HASTE in Postoperative Single Sequence MRI.

IF 3.8 2区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Clarissa Hosse, Uli Fehrenbach, Fabio Pivetta, Thomas Malinka, Moritz Wagner, Thula Walter-Rittel, Bernhard Gebauer, Johannes Kolck, Dominik Geisel
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引用次数: 0

Abstract

Background: This study evaluates the feasibility of a novel deep learning-accelerated half-fourier single-shot turbo spin-echo sequence (HASTE-DL) compared to the conventional HASTE sequence (HASTES) in postoperative single-sequence MRI for the detection of fluid collections following abdominal surgery. As small fluid collections are difficult to visualize using other techniques, HASTE-DL may offer particular advantages in this clinical context.

Materials and methods: A retrospective analysis was conducted on 76 patients (mean age 65±11.69 years) who underwent abdominal MRI for suspected septic foci following abdominal surgery. Imaging was performed using 3-T MRI scanners, and both sequences were analyzed in terms of image quality, contrast, sharpness, and artifact presence. Quantitative assessments focused on fluid collection detectability, while qualitative assessments evaluated visualization of critical structures. Inter-reader agreement was measured using Cohen's kappa coefficient, and statistical significance was determined with the Mann-Whitney U test.

Results: HASTE-DL achieved a 46% reduction in scan time compared to HASTES, while significantly improving overall image quality (p<0.001), contrast (p<0.001), and sharpness (p<0.001). The inter-reader agreement for HASTE-DL was excellent (κ=0.960), with perfect agreement on overall image quality and fluid collection detection (κ=1.0). Fluid detectability and characterization scores were higher for HASTE-DL, and visualization of critical structures was significantly enhanced (p<0.001). No relevant artifacts were observed in either sequence.

Conclusion: HASTE-DL offers superior image quality, improved visualization of critical structures, such as drainages, vessels, bile and pancreatic ducts, and reduced acquisition time, making it an effective alternative to the standard HASTE sequence, and a promising complementary tool in the postoperative imaging workflow.

从更快的帧到完美的焦点:术后单序列MRI的深度学习加速。
背景:本研究评估了一种新型的深度学习加速半傅立叶单次涡轮自旋回波序列(HASTE- dl)与传统的HASTE序列(HASTES)在腹部手术后单序列MRI中检测积液的可行性。由于使用其他技术很难看到小的液体收集,因此在这种临床情况下,HASTE-DL可能具有特殊的优势。材料与方法:回顾性分析76例腹部手术后疑似脓毒性病灶行腹部MRI检查的患者(平均年龄65±11.69岁)。使用3-T MRI扫描仪进行成像,并根据图像质量,对比度,清晰度和伪影存在对两个序列进行分析。定量评估侧重于流体收集的可检测性,而定性评估则侧重于关键结构的可视化。使用Cohen’s kappa系数测量读者间一致性,使用Mann-Whitney U检验确定统计显著性。结果:与HASTES相比,HASTE- dl的扫描时间减少了46%,同时显著提高了整体图像质量(p结论:HASTE- dl提供了卓越的图像质量,改善了关键结构(如引流、血管、胆汁和胰管)的可视化,缩短了采集时间,使其成为标准匆忙序列的有效替代方案,是术后成像工作流程中有希望的补充工具。
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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来源期刊
Academic Radiology
Academic Radiology 医学-核医学
CiteScore
7.60
自引率
10.40%
发文量
432
审稿时长
18 days
期刊介绍: Academic Radiology publishes original reports of clinical and laboratory investigations in diagnostic imaging, the diagnostic use of radioactive isotopes, computed tomography, positron emission tomography, magnetic resonance imaging, ultrasound, digital subtraction angiography, image-guided interventions and related techniques. It also includes brief technical reports describing original observations, techniques, and instrumental developments; state-of-the-art reports on clinical issues, new technology and other topics of current medical importance; meta-analyses; scientific studies and opinions on radiologic education; and letters to the Editor.
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