利用双层光谱检测器CT衍生的电子密度图像评估非增强CT图像上的肺栓塞:一项在急诊科进行的单中心前瞻性研究

IF 1.1 4区 医学 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Huayang Du, Xin Sui, Ruijie Zhao, Jiaru Wang, Ying Ming, Sirong Piao, Jinhua Wang, Xiaomei Lu, Lan Song, Wei Song
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引用次数: 0

摘要

目的评估非增强光谱成像、电子密度(ED)和覆盖电子密度(OED)图像在评估疑似或确诊急性肺栓塞(APE)患者肺栓塞中的应用价值。从光谱检测器CT (SDCT)、ED和OED图像中可以推断出多光谱图像。ED和OED图像对富含水分的组织高度敏感。在非增强胸部CT图像中检测肺动脉血栓的潜在用途。目的评价SDCT非增强图像上ED和OED图像检测肺栓塞的敏感性、特异性和准确性。方法回顾性研究于2021年11月至2022年4月期间,采用双层光谱检测器CT进行非增强和CT肺血管造影评估APE的79例患者。根据未增强的光谱和CTPA图像,两名放射科医生在ED和OED图像上确定了主要、大叶和节段肺动脉的高密度区域,并使用咨询方法在增强图像上检测肺栓塞(PE)。CTPA结果被认为是金标准。分析ED和OED对PE的诊断效果。结果40例(40/79)患者检出PE,其中主动脉17例,大叶动脉69例,节段动脉20例。PE在ED图像上的灵敏度为69.7-94.7%,特异性为58.5-98.2%。对OED影像的敏感性为94.1 ~ 95.2%,特异性为80.0 ~ 98.1%。ED影像的阳性预测值(PPV)为53.6 ~ 87.7%,阴性预测值(NPV)为69.7 ~ 95.9%,OED影像的阳性预测值为48.5 ~ 88.9%,阴性预测值为94.1 ~ 98.9%。ED和OED的准确率分别为76.0 ~ 98.9%和87.3 ~ 96.2%。研究发现,无论是有血栓的肺动脉主干、肺叶还是肺节段动脉,EDW值在108.1- 108.8%之间,比无血栓的动脉EDW值高3.9- 4.2%。栓塞肺动脉ED标准化值为103.6- 104.3% EDW。结论不使用造影剂的频谱CT诊断ED和OED具有较高的诊断价值,可提高PE的可视化程度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessing Pulmonary Embolisms on Unenhanced CT Images Using Electron Density Images Derived from Dual-Layer Spectral Detector CT: A Single-centre Prospective Study Conducted at the Emergency Department.

Aims To evaluate the utility of unenhanced spectral imaging, electron density (ED) and overlay electron density (OED) images for assessing pulmonary embolisms in patients with suspected or confirmed acute pulmonary embolism (APE). Background Multiple spectral images can be extrapolated from spectral detector CT (SDCT), ED and OED images. ED and OED images are highly sensitive to moisture-rich tissues. Potential use for detecting pulmonary artery thrombi in non-enhanced chest CT images. Objective To assess the sensitivity, specificity and accuracy of ED and OED images obtained using SDCT for the detection of pulmonary embolism on non-enhanced images. Method Seventy-nine patients who underwent unenhanced and CT pulmonary angiography using dual-layer spectral detector CT to evaluate APE between November 2021 and April 2022 were enrolled in this retrospective study. Based on unenhanced spectral and CTPA images, two radiologists identified areas of high density in the main, lobar, and segmental pulmonary arteries on ED and OED images and detected pulmonary embolism (PE) on enhanced images using a consultative approach. CTPA results were considered the gold standard. The diagnostic performance of ED and OED in detecting PE was analyzed. Results PE was detected in 40 patients (40/79), and 17, 69, and 20 PEs were detected in the main, lobar, and segmental arteries, respectively. The PE detection sensitivity on ED images was 69.7-94.7%, and the specificity was 58.5-98.2% for the individual, main, lobe, and segmental pulmonary arteries. The sensitivity and specificity for OED images were 94.1-95.2% and 80.0-98.1%, respectively. The positive predictive value (PPV) and negative predictive value (NPV) were 53.6-87.7% and 69.7-95.9% for ED images, and 48.5-88.9% and 94.1-98.9% for OED images, respectively. The accuracy was 76.0-98.9% and 87.3-96.2% when using ED and OED images, respectively. The research identified that whether main, lobar or segmental pulmonary arteries with blood clots, EDW values ranged from 108.1-108.8 %EDW, 3.9-4.2 %EDW higher than those of arteries without emboli. Pulmonary arteries with emboli standardised ED values were 103.6-104.3 %EDW. Conclusion ED and OED images using spectral CT without contrast media demonstrated high diagnostic performance and could improve the visualization of PE.

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来源期刊
CiteScore
2.60
自引率
0.00%
发文量
246
审稿时长
1 months
期刊介绍: Current Medical Imaging Reviews publishes frontier review articles, original research articles, drug clinical trial studies and guest edited thematic issues on all the latest advances on medical imaging dedicated to clinical research. All relevant areas are covered by the journal, including advances in the diagnosis, instrumentation and therapeutic applications related to all modern medical imaging techniques. The journal is essential reading for all clinicians and researchers involved in medical imaging and diagnosis.
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