Comparison of different iterative reconstruction algorithms with contrast-enhancement boost technique on the image quality of CT pulmonary angiography for obese patients.

IF 2.9 3区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING BMC Medical Imaging Pub Date : 2024-10-18 DOI:10.1186/s12880-024-01447-6
Mei Ye, Li Wang, Yan Xing, Yuxiang Li, Zicheng Zhao, Min Xu, Wenya Liu
{"title":"Comparison of different iterative reconstruction algorithms with contrast-enhancement boost technique on the image quality of CT pulmonary angiography for obese patients.","authors":"Mei Ye, Li Wang, Yan Xing, Yuxiang Li, Zicheng Zhao, Min Xu, Wenya Liu","doi":"10.1186/s12880-024-01447-6","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>To evaluate the effect of the contrast-enhancement-boost (CE-boost) postprocessing technique on improving the image quality of obese patients in computed tomography pulmonary angiography (CTPA) compared to hybrid iterative reconstruction (HIR) and model-based iterative reconstruction (MBIR) algorithms.</p><p><strong>Methods: </strong>This prospective study was conducted on 100 patients who underwent CTPA for suspected pulmonary embolism. Non-obese patients with a body mass index (BMI) under 25 were designated as group 1, while obese patients (group 2) had a BMI exceeding 25. The CE-boost images were generated by subtracting non-contrast HIR images from contrast-enhanced HIR images to improve the visibility of pulmonary arteries further. The CT value, image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were quantitatively assessed. Two chest radiologists independently reviewed the CT images (5, best; 1, worst) across three subjective characteristics including diagnostic confidence, subjective image noise, and vascular contrast. The Friedman test and Dunn-Bonferroni correction were used for statistical analysis.</p><p><strong>Results: </strong>The CE-boost had significantly higher CT values than HIR and MBIR in both groups (all p < 0.001). The MBIR yielded the lowest image noise compared with HIR and CE-boost (all p < 0.001). The SNR and CNR of main pulmonary artery (MPA) were significantly higher in CE-boost than in MBIR (all p < 0.05), with HIR showing the lowest values (all p < 0.001). Group 2 MBIR received significantly better subjective image noise scores, while the diagnostic confidence and vascular contrast scored highest with the group 2 CE-boost (all p < 0.05).</p><p><strong>Conclusion: </strong>Compared to the HIR algorithm, both the CE-boost technique and the MBIR algorithm can improve the image quality of CTPA in obese patients. CE-boost had the greatest potential in increasing the visualization of pulmonary artery and its branches.</p>","PeriodicalId":9020,"journal":{"name":"BMC Medical Imaging","volume":"24 1","pages":"279"},"PeriodicalIF":2.9000,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11488249/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Medical Imaging","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12880-024-01447-6","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0

Abstract

Objective: To evaluate the effect of the contrast-enhancement-boost (CE-boost) postprocessing technique on improving the image quality of obese patients in computed tomography pulmonary angiography (CTPA) compared to hybrid iterative reconstruction (HIR) and model-based iterative reconstruction (MBIR) algorithms.

Methods: This prospective study was conducted on 100 patients who underwent CTPA for suspected pulmonary embolism. Non-obese patients with a body mass index (BMI) under 25 were designated as group 1, while obese patients (group 2) had a BMI exceeding 25. The CE-boost images were generated by subtracting non-contrast HIR images from contrast-enhanced HIR images to improve the visibility of pulmonary arteries further. The CT value, image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were quantitatively assessed. Two chest radiologists independently reviewed the CT images (5, best; 1, worst) across three subjective characteristics including diagnostic confidence, subjective image noise, and vascular contrast. The Friedman test and Dunn-Bonferroni correction were used for statistical analysis.

Results: The CE-boost had significantly higher CT values than HIR and MBIR in both groups (all p < 0.001). The MBIR yielded the lowest image noise compared with HIR and CE-boost (all p < 0.001). The SNR and CNR of main pulmonary artery (MPA) were significantly higher in CE-boost than in MBIR (all p < 0.05), with HIR showing the lowest values (all p < 0.001). Group 2 MBIR received significantly better subjective image noise scores, while the diagnostic confidence and vascular contrast scored highest with the group 2 CE-boost (all p < 0.05).

Conclusion: Compared to the HIR algorithm, both the CE-boost technique and the MBIR algorithm can improve the image quality of CTPA in obese patients. CE-boost had the greatest potential in increasing the visualization of pulmonary artery and its branches.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
不同迭代重建算法与造影剂增强技术对肥胖患者 CT 肺血管造影图像质量的比较。
目的与混合迭代重建(HIR)和基于模型的迭代重建(MBIR)算法相比,评估对比度增强增强(CE-boost)后处理技术对改善肥胖患者计算机断层扫描肺动脉造影(CTPA)图像质量的影响:这项前瞻性研究的对象是 100 名因疑似肺栓塞而接受 CTPA 检查的患者。体重指数(BMI)低于 25 的非肥胖患者被指定为第 1 组,而体重指数超过 25 的肥胖患者(第 2 组)被指定为第 2 组。CE 增强图像是通过从对比增强 HIR 图像中减去非对比 HIR 图像生成的,以进一步提高肺动脉的可见度。对 CT 值、图像噪声、信噪比(SNR)和对比度-噪声比(CNR)进行了定量评估。两名胸部放射科医生对 CT 图像(5 分,最佳;1 分,最差)的诊断信心、主观图像噪声和血管对比度等三个主观特征进行了独立审查。统计分析采用 Friedman 检验和 Dunn-Bonferroni 校正:在两组中,CE-boost 的 CT 值均明显高于 HIR 和 MBIR(均为 p 结论:CE-boost 的 CT 值明显高于 HIR 和 MBIR:与 HIR 算法相比,CE-boost 技术和 MBIR 算法均可改善肥胖患者 CTPA 的图像质量。CE-boost 在提高肺动脉及其分支的可视化方面潜力最大。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
BMC Medical Imaging
BMC Medical Imaging RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-
CiteScore
4.60
自引率
3.70%
发文量
198
审稿时长
27 weeks
期刊介绍: BMC Medical Imaging is an open access journal publishing original peer-reviewed research articles in the development, evaluation, and use of imaging techniques and image processing tools to diagnose and manage disease.
期刊最新文献
In vitro detection of cancer cells using a novel fluorescent choline derivative. Prediction of esophageal fistula in radiotherapy/chemoradiotherapy for patients with advanced esophageal cancer by a clinical-deep learning radiomics model : Prediction of esophageal fistula in radiotherapy/chemoradiotherapy patients. Prior information guided deep-learning model for tumor bed segmentation in breast cancer radiotherapy. The predictive value of nomogram for adnexal cystic-solid masses based on O-RADS US, clinical and laboratory indicators. The study on ultrasound image classification using a dual-branch model based on Resnet50 guided by U-net segmentation results.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1