Enhanced image quality in head and neck MRI with PROPELLER and deep learning reconstruction

医学 图像质量 威尔科克森符号秩检验 螺旋桨 工件(错误) 头颈部 放射科 核医学 人工智能 磁共振成像 迭代重建 深度学习 卡帕 病变 医学物理学 计算机视觉 质量评定 主管(地质) 科恩卡帕 靶病变
作者
Yuki Takano,Noriyuki Fujima,Motoma Kanaya,Yukie Shimizu,Yohei Ikebe,Hiroyuki Kameda,Taisuke Harada,Satoshi Kano,Akihiro Homma,Kohsuke Kudo
出处
期刊:European Journal of Radiology Open [Elsevier BV]
卷期号:16: 100771-100771
标识
DOI:10.1016/j.ejro.2026.100771
摘要

Purpose: To evaluate the benefits of combining the Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction (PROPELLER) acquisition technique and deep learning-based reconstruction (DLR) for fat-suppressed T2-weighted imaging (Fs-T2WI) and diffusion-weighted imaging (DWI) in head and neck MRI. Materials and methods: This retrospective study included 34 patients who underwent 3.0-T head and neck MRI. Imaging protocols comprised PROPELLER-based Fs-T2WI and DWI, which were compared against conventional multiplanar fast spin-echo Fs-T2WI and single-shot echo-planar imaging DWI. All sequences were reconstructed using a DLR algorithm. Two radiologists independently performed qualitative assessment, evaluating overall image quality, lesion conspicuity, anatomical delineation, and artifact severity using a 5-point Likert scale. The quantitative assessment involved measurements of the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) in the lesions, adjacent muscle, parotid glands, and submandibular glands. Interobserver agreement was determined using weighted kappa statistics, and Wilcoxon signed-rank test was used for statistical comparisons. Results: The PROPELLER sequences exhibited significantly higher qualitative scores for all evaluated parameters in both Fs-T2WI and DWI compared to the conventional sequences (p < 0.001). The interobserver agreement for the Fs-T2WI was moderate (0.47-0.53), and that for DWI was good (0.76-0.83). The quantitative analysis further demonstrated significantly higher SNRs and lesion-to-muscle CNRs with the PROPELLER sequences (p < 0.001). Conclusion: The combination of PROPELLER acquisition and DLR significantly improves the image quality and lesion conspicuity in head and neck MRI. This approach effectively suppresses artifacts and improves quantitative image metrics, thereby positioning it as a reliable imaging strategy for routine clinical assessments of head and neck lesions.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
我是老大应助ye采纳,获得10
1秒前
1秒前
aaaa发布了新的文献求助10
1秒前
小葵完成签到,获得积分10
1秒前
火苗完成签到,获得积分10
1秒前
2秒前
王韩旭应助江子川采纳,获得10
3秒前
科研通AI6.2应助江子川采纳,获得10
3秒前
科研通AI6.2应助江子川采纳,获得10
3秒前
4秒前
甜蜜的手套应助江子川采纳,获得10
4秒前
可爱的函函应助研友_8WdzPL采纳,获得20
4秒前
甜蜜的手套应助江子川采纳,获得10
4秒前
狂野紫丝应助江子川采纳,获得10
4秒前
科研通AI6.2应助江子川采纳,获得10
4秒前
科研通AI6.2应助江子川采纳,获得10
4秒前
4秒前
核桃应助江子川采纳,获得30
4秒前
科研通AI2S应助李密采纳,获得10
4秒前
XX应助江子川采纳,获得10
4秒前
5秒前
yan259发布了新的文献求助10
5秒前
5秒前
5秒前
RUSTY完成签到,获得积分10
6秒前
6秒前
Andy1201完成签到,获得积分10
6秒前
6秒前
6秒前
7秒前
Sunny完成签到,获得积分10
8秒前
难过飞瑶发布了新的文献求助10
8秒前
脑洞疼应助故意的靳采纳,获得10
8秒前
典雅听枫发布了新的文献求助10
8秒前
9秒前
XX应助一身正气采纳,获得10
9秒前
9秒前
bkagyin应助eleven采纳,获得10
9秒前
dada完成签到,获得积分10
10秒前
snow发布了新的文献求助10
10秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Principles of town planning: translating concepts to applications 1000
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The Great Hymn to Šamaš 500
Positive Obsession: The Life and Times of Octavia E. Butler 500
Interpolation and Regression Models for the Chemical Engineer: Solving Numerical Problems 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7693440
求助须知:如何正确求助?哪些是违规求助? 9254216
关于积分的说明 19988310
捐赠科研通 7266686
什么是DOI,文献DOI怎么找? 3291605
关于科研通互助平台的介绍 2447624
邀请新用户注册赠送积分活动 2297000