Dual-energy computed tomography with new virtual monoenergetic image reconstruction enhances prostate lesion image quality and improves the diagnostic efficacy for prostate cancer

IF 2.9 3区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING BMC Medical Imaging Pub Date : 2024-08-12 DOI:10.1186/s12880-024-01393-3
Nina Fan, Xiaofeng Chen, Yulin Li, Zhiqiang Zhu, Xiangguang Chen, Zhiqi Yang, Jiada Yang
{"title":"Dual-energy computed tomography with new virtual monoenergetic image reconstruction enhances prostate lesion image quality and improves the diagnostic efficacy for prostate cancer","authors":"Nina Fan, Xiaofeng Chen, Yulin Li, Zhiqiang Zhu, Xiangguang Chen, Zhiqi Yang, Jiada Yang","doi":"10.1186/s12880-024-01393-3","DOIUrl":null,"url":null,"abstract":"Prostate cancer is one of the most common malignant tumors in middle-aged and elderly men and carries significant prognostic implications, and recent studies suggest that dual-energy computed tomography (DECT) utilizing new virtual monoenergetic images can enhance cancer detection rates. This study aimed to assess the impact of virtual monoenergetic images reconstructed from DECT arterial phase scans on the image quality of prostate lesions and their diagnostic performance for prostate cancer. We conducted a retrospective analysis of 83 patients with prostate cancer or prostatic hyperplasia who underwent DECT scans at Meizhou People’s Hospital between July 2019 and December 2023. The variables analyzed included age, tumor diameter and serum prostate-specific antigen (PSA) levels, among others. We also compared CT values, signal-to-noise ratio (SNR), subjective image quality ratings, and contrast-to-noise ratio (CNR) between virtual monoenergetic images (40–100 keV) and conventional linear blending images. Receiver operating characteristic (ROC) curve analyses were performed to evaluate the diagnostic efficacy of virtual monoenergetic images (40 keV and 50 keV) compared to conventional images. Virtual monoenergetic images at 40 keV showed significantly higher CT values (168.19 ± 57.14) compared to conventional linear blending images (66.66 ± 15.5) for prostate cancer (P < 0.001). The 50 keV images also demonstrated elevated CT values (121.73 ± 39.21) compared to conventional images (P < 0.001). CNR values for the 40 keV (3.81 ± 2.13) and 50 keV (2.95 ± 1.50) groups were significantly higher than the conventional blending group (P < 0.001). Subjective evaluations indicated markedly better image quality scores for 40 keV (median score of 5) and 50 keV (median score of 5) images compared to conventional images (P < 0.05). ROC curve analysis revealed superior diagnostic accuracy for 40 keV (AUC: 0.910) and 50 keV (AUC: 0.910) images based on CT values compared to conventional images (AUC: 0.849). Virtual monoenergetic images reconstructed at 40 keV and 50 keV from DECT arterial phase scans substantially enhance the image quality of prostate lesions and improve diagnostic efficacy for prostate cancer.","PeriodicalId":9020,"journal":{"name":"BMC Medical Imaging","volume":null,"pages":null},"PeriodicalIF":2.9000,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Medical Imaging","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12880-024-01393-3","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

Prostate cancer is one of the most common malignant tumors in middle-aged and elderly men and carries significant prognostic implications, and recent studies suggest that dual-energy computed tomography (DECT) utilizing new virtual monoenergetic images can enhance cancer detection rates. This study aimed to assess the impact of virtual monoenergetic images reconstructed from DECT arterial phase scans on the image quality of prostate lesions and their diagnostic performance for prostate cancer. We conducted a retrospective analysis of 83 patients with prostate cancer or prostatic hyperplasia who underwent DECT scans at Meizhou People’s Hospital between July 2019 and December 2023. The variables analyzed included age, tumor diameter and serum prostate-specific antigen (PSA) levels, among others. We also compared CT values, signal-to-noise ratio (SNR), subjective image quality ratings, and contrast-to-noise ratio (CNR) between virtual monoenergetic images (40–100 keV) and conventional linear blending images. Receiver operating characteristic (ROC) curve analyses were performed to evaluate the diagnostic efficacy of virtual monoenergetic images (40 keV and 50 keV) compared to conventional images. Virtual monoenergetic images at 40 keV showed significantly higher CT values (168.19 ± 57.14) compared to conventional linear blending images (66.66 ± 15.5) for prostate cancer (P < 0.001). The 50 keV images also demonstrated elevated CT values (121.73 ± 39.21) compared to conventional images (P < 0.001). CNR values for the 40 keV (3.81 ± 2.13) and 50 keV (2.95 ± 1.50) groups were significantly higher than the conventional blending group (P < 0.001). Subjective evaluations indicated markedly better image quality scores for 40 keV (median score of 5) and 50 keV (median score of 5) images compared to conventional images (P < 0.05). ROC curve analysis revealed superior diagnostic accuracy for 40 keV (AUC: 0.910) and 50 keV (AUC: 0.910) images based on CT values compared to conventional images (AUC: 0.849). Virtual monoenergetic images reconstructed at 40 keV and 50 keV from DECT arterial phase scans substantially enhance the image quality of prostate lesions and improve diagnostic efficacy for prostate cancer.
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
采用新型虚拟单能图像重建技术的双能计算机断层扫描提高了前列腺病灶的图像质量,改善了前列腺癌的诊断效果
前列腺癌是中老年男性最常见的恶性肿瘤之一,对预后有重要影响,最近的研究表明,利用新型虚拟单能图像的双能计算机断层扫描(DECT)可提高癌症检出率。本研究旨在评估由 DECT 动脉期扫描重建的虚拟单能图像对前列腺病变图像质量及其前列腺癌诊断性能的影响。我们对2019年7月至2023年12月期间在梅州市人民医院接受DECT扫描的83名前列腺癌或前列腺增生患者进行了回顾性分析。分析的变量包括年龄、肿瘤直径和血清前列腺特异性抗原(PSA)水平等。我们还比较了虚拟单能量图像(40-100 keV)和传统线性混合图像之间的 CT 值、信噪比(SNR)、主观图像质量评分和对比度-噪声比(CNR)。为了评估虚拟单能量图像(40 keV 和 50 keV)与传统图像相比的诊断效果,进行了接收者操作特征(ROC)曲线分析。与传统线性混合图像(66.66 ± 15.5)相比,40 keV 虚拟单能量图像显示的前列腺癌 CT 值(168.19 ± 57.14)明显更高(P < 0.001)。50 keV 图像的 CT 值(121.73 ± 39.21)也高于传统图像(P < 0.001)。40 keV 组(3.81 ± 2.13)和 50 keV 组(2.95 ± 1.50)的 CNR 值明显高于传统混合组(P < 0.001)。主观评价显示,与传统图像相比,40 keV(中位数为 5 分)和 50 keV(中位数为 5 分)图像的图像质量得分明显更高(P < 0.05)。ROC 曲线分析显示,基于 CT 值的 40 keV(AUC:0.910)和 50 keV(AUC:0.910)图像的诊断准确性优于传统图像(AUC:0.849)。从 DECT 动脉相扫描重建的 40 keV 和 50 keV 虚拟单能量图像大大提高了前列腺病变的图像质量,提高了前列腺癌的诊断效果。
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
Computed tomography enterography radiomics and machine learning for identification of Crohn's disease. Computer vision applications for the detection or analysis of tuberculosis using digitised human lung tissue images - a systematic review. Computerized tomography features acting as predictors for invasive therapy in the management of Crohn's disease-related spontaneous intra-abdominal abscess: experience from long-term follow-up. Correction: CT coronary fractional flow reserve based on artificial intelligence using different software: a repeatability study. Diagnostic significance of ultrasound characteristics in discriminating follicular thyroid carcinoma from adenoma.
×
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