Accuracy of Dual-Energy CT-derived Fat Maps and Bone Marrow Edema Maps in Pedal Osteomyelitis Diagnosis.

IF 12.1 1区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Radiology Pub Date : 2025-04-01 DOI:10.1148/radiol.232900
Christoph Stern, Andrea B Rosskopf, Adrian A Marth, Georg C Feuerriegel, Martin C Berli, Benjamin Fritz, Reto Sutter
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引用次数: 0

Abstract

"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. Background In patients who cannot undergo MRI, dual-energy CT (DECT) with bone marrow edema (BME) maps are used as an approach for diagnosing pedal osteomyelitis, but with lower accuracy. Purpose To compare the diagnostic accuracy of additional bone marrow fat maps with that of DECT with BME maps and MRI for pedal osteomyelitis detection. Materials and Methods In this prospective study, thirty-one participants with clinically suspected osteomyelitis of the mid- and forefoot underwent noncontrast DECT (80 kV/140 kV) and MRI between October 2020 and February 2022. With image postprocessing, DECT-derived BME and fat maps were generated. Four independent readers evaluated 3 different image sets for osteomyelitis: DECT and BME maps (set 1); DECT, BME maps and fat maps (set 2); and MRI (set 3). Sensitivity, specificity and accuracy were calculated for each image set, with clinical and microbiological data as the reference standards. In a subanalysis, the DECT BME map, DECT fat map and DECT erosion map were analyzed for their accuracy in predicting bone marrow fat loss at T1-weighted MRI. Results Of the 31 participants included in the study (mean age, 61.7 years ±14.6 [SD]; 21 males) 17 (55%) had osteomyelitis. Sensitivity, specificity and accuracy for detecting osteomyelitis were 47% (8/17), 79% (11/14), and 61% (19/31) (set 1); 77% (13/17), 86% (12/14) and 81% (25/31) (set 2); and 82% (14/17), 93% (13/14) and 87% (27/31) (set 3), respectively. Thirty-one of 661 individual bones (0.5%) showed bone marrow fat loss on T1-weighted MRI; in the subanalysis, DECT fat map specificity was higher than that of the DECT BME map for predicting bone marrow fat loss in individual bones (97% (612/630) vs. 89% (560/630)) (P<.001). Conclusion Pedal osteomyelitis detection with novel DECT-derived fat map imaging in addition to DECT and BME maps was accurate. See also the editorial by Khurana in this issue.

"刚刚接受 "的论文经过了全面的同行评审,已被接受在《放射学》上发表。这篇文章将经过校对、排版和校样审核,然后以最终版本发表。请注意,在制作最终稿件的过程中,可能会发现一些错误,从而影响文章内容。背景 在无法接受核磁共振成像检查的患者中,双能 CT(DECT)与骨髓水肿(BME)图可作为诊断足骨髓炎的一种方法,但准确性较低。目的 比较附加骨髓脂肪图与带骨髓水肿图的 DECT 和核磁共振成像在检测足骨髓炎方面的诊断准确性。材料和方法 在这项前瞻性研究中,31 名临床怀疑患有中足和前足骨髓炎的参与者在 2020 年 10 月至 2022 年 2 月期间接受了非对比 DECT(80 千伏/140 千伏)和核磁共振成像检查。通过图像后处理,生成了由 DECT 导出的 BME 和脂肪图。四位独立读者对 3 组不同的图像进行了骨髓炎评估:DECT和BME图(第1组);DECT、BME图和脂肪图(第2组);MRI(第3组)。以临床和微生物学数据为参考标准,计算每组图像的敏感性、特异性和准确性。在一项子分析中,分析了 DECT BME 图、DECT 脂肪图和 DECT 侵蚀图在 T1 加权核磁共振成像中预测骨髓脂肪丢失的准确性。结果 在纳入研究的 31 名参与者(平均年龄为 61.7 岁 ±14.6 [SD];21 名男性)中,17 人(55%)患有骨髓炎。检测骨髓炎的敏感性、特异性和准确性分别为 47%(8/17)、79%(11/14)和 61%(19/31)(第 1 组);77%(13/17)、86%(12/14)和 81%(25/31)(第 2 组);以及 82%(14/17)、93%(13/14)和 87%(27/31)(第 3 组)。在 661 块骨骼中,有 31 块(0.5%)在 T1 加权磁共振成像中显示骨髓脂肪缺失;在子分析中,DECT 脂肪图预测个别骨骼骨髓脂肪缺失的特异性高于 DECT BME 图(97% (612/630) vs. 89% (560/630))(P
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来源期刊
Radiology
Radiology 医学-核医学
CiteScore
35.20
自引率
3.00%
发文量
596
审稿时长
3.6 months
期刊介绍: Published regularly since 1923 by the Radiological Society of North America (RSNA), Radiology has long been recognized as the authoritative reference for the most current, clinically relevant and highest quality research in the field of radiology. Each month the journal publishes approximately 240 pages of peer-reviewed original research, authoritative reviews, well-balanced commentary on significant articles, and expert opinion on new techniques and technologies. Radiology publishes cutting edge and impactful imaging research articles in radiology and medical imaging in order to help improve human health.
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