验证肝脏 CT 个性化造影剂注射方案的多参数算法。

IF 3.7 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Hugues G Brat, Benoit Dufour, Natalie Heracleous, Pauline Sastre, Cyril Thouly, Benoit Rizk, Federica Zanca
{"title":"验证肝脏 CT 个性化造影剂注射方案的多参数算法。","authors":"Hugues G Brat, Benoit Dufour, Natalie Heracleous, Pauline Sastre, Cyril Thouly, Benoit Rizk, Federica Zanca","doi":"10.1186/s41747-024-00492-8","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>In liver computed tomography (CT), tailoring the contrast injection to the patient's specific characteristics is relevant for optimal imaging and patient safety. We evaluated a novel algorithm engineered for personalized contrast injection to achieve reproducible liver enhancement centered on 50 HU.</p><p><strong>Methods: </strong>From September 2020 to August 31, 2022, CT data from consecutive adult patients were prospectively collected at our multicenter premises. Inclusion criteria consisted of an abdominal CT referral for cancer staging or follow-up. For all examinations, a web interface incorporating data from the radiology information system (patient details and examination information) and radiographer-inputted data (patient fat-free mass, imaging center, kVp, contrast agent details, and imaging phase) were used. Calculated contrast volume and injection rate were manually entered into the CT console controlling the injector. Iopamidol 370 mgI/mL or Iohexol 350 mgI/mL were used, and kVp varied (80, 100, or 120) based on patient habitus.</p><p><strong>Results: </strong>We enrolled 384 patients (mean age 61.2 years, range 21.1-94.5). The amount of administered iodine dose (gI) was not significantly different across contrast agents (p = 0.700), while a significant increase in iodine dose was observed with increasing kVp (p < 0.001) and in males versus females (p < 0.001), as expected. Despite the differences in administered iodine load, image quality was reproducible across patients with 72.1% of the examinations falling within the desirable range of 40-60 HU.</p><p><strong>Conclusion: </strong>This study validated a novel algorithm for personalized contrast injection in adult abdominal CT, achieving consistent liver enhancement centered at 50 HU.</p><p><strong>Relevance statement: </strong>In healthcare's ongoing shift towards personalized medicine, the algorithm offers excellent potential to improve diagnostic accuracy and patient management, particularly for the detection and follow-up of liver malignancies.</p><p><strong>Key points: </strong>The algorithm achieves reproducible liver enhancement, promising improved diagnostic accuracy and patient management in diverse clinical settings. The real-world study demonstrates this algorithm's adaptability to different variables ensuring high-quality liver imaging. A personalized algorithm optimizes liver CT, improving the visibility, conspicuity, and follow-up of liver lesions.</p>","PeriodicalId":36926,"journal":{"name":"European Radiology Experimental","volume":"8 1","pages":"112"},"PeriodicalIF":3.7000,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11465069/pdf/","citationCount":"0","resultStr":"{\"title\":\"Validation of a multi-parameter algorithm for personalized contrast injection protocol in liver CT.\",\"authors\":\"Hugues G Brat, Benoit Dufour, Natalie Heracleous, Pauline Sastre, Cyril Thouly, Benoit Rizk, Federica Zanca\",\"doi\":\"10.1186/s41747-024-00492-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>In liver computed tomography (CT), tailoring the contrast injection to the patient's specific characteristics is relevant for optimal imaging and patient safety. We evaluated a novel algorithm engineered for personalized contrast injection to achieve reproducible liver enhancement centered on 50 HU.</p><p><strong>Methods: </strong>From September 2020 to August 31, 2022, CT data from consecutive adult patients were prospectively collected at our multicenter premises. Inclusion criteria consisted of an abdominal CT referral for cancer staging or follow-up. For all examinations, a web interface incorporating data from the radiology information system (patient details and examination information) and radiographer-inputted data (patient fat-free mass, imaging center, kVp, contrast agent details, and imaging phase) were used. Calculated contrast volume and injection rate were manually entered into the CT console controlling the injector. Iopamidol 370 mgI/mL or Iohexol 350 mgI/mL were used, and kVp varied (80, 100, or 120) based on patient habitus.</p><p><strong>Results: </strong>We enrolled 384 patients (mean age 61.2 years, range 21.1-94.5). The amount of administered iodine dose (gI) was not significantly different across contrast agents (p = 0.700), while a significant increase in iodine dose was observed with increasing kVp (p < 0.001) and in males versus females (p < 0.001), as expected. Despite the differences in administered iodine load, image quality was reproducible across patients with 72.1% of the examinations falling within the desirable range of 40-60 HU.</p><p><strong>Conclusion: </strong>This study validated a novel algorithm for personalized contrast injection in adult abdominal CT, achieving consistent liver enhancement centered at 50 HU.</p><p><strong>Relevance statement: </strong>In healthcare's ongoing shift towards personalized medicine, the algorithm offers excellent potential to improve diagnostic accuracy and patient management, particularly for the detection and follow-up of liver malignancies.</p><p><strong>Key points: </strong>The algorithm achieves reproducible liver enhancement, promising improved diagnostic accuracy and patient management in diverse clinical settings. The real-world study demonstrates this algorithm's adaptability to different variables ensuring high-quality liver imaging. A personalized algorithm optimizes liver CT, improving the visibility, conspicuity, and follow-up of liver lesions.</p>\",\"PeriodicalId\":36926,\"journal\":{\"name\":\"European Radiology Experimental\",\"volume\":\"8 1\",\"pages\":\"112\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2024-10-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11465069/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Radiology Experimental\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1186/s41747-024-00492-8\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Radiology Experimental","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/s41747-024-00492-8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0

摘要

背景:在肝脏计算机断层扫描(CT)中,根据患者的具体特征进行造影剂注射对于优化成像和患者安全至关重要。我们评估了一种为实现以 50 HU 为中心的可重现肝脏增强而设计的个性化造影剂注射新算法:从 2020 年 9 月到 2022 年 8 月 31 日,我们在多中心大楼前瞻性地收集了连续成年患者的 CT 数据。纳入标准包括因癌症分期或随访而转诊的腹部 CT 患者。所有检查均使用网络界面,其中包含来自放射学信息系统的数据(患者详细信息和检查信息)和放射医师输入的数据(患者去脂质量、成像中心、kVp、造影剂详细信息和成像阶段)。计算出的造影剂量和注射速率被手动输入控制注射器的 CT 控制台。使用碘帕米多 370 毫克I/毫升或碘海醇 350 毫克I/毫升,kVp 根据患者的体型而变化(80、100 或 120):我们共招募了 384 名患者(平均年龄 61.2 岁,21.1-94.5 岁不等)。不同造影剂的碘剂量(gI)无明显差异(p = 0.700),而随着 kVp 的增加,碘剂量显著增加(p 结论:该研究验证了一种新型算法,可根据患者的不同体型,选择不同的造影剂(80、100 或 120):这项研究验证了成人腹部 CT 个性化造影剂注射的新算法,实现了以 50 HU 为中心的一致的肝脏增强:在医疗保健不断向个性化医疗转变的过程中,该算法为提高诊断准确性和患者管理,尤其是肝脏恶性肿瘤的检测和随访提供了巨大的潜力:该算法实现了可重复的肝脏增强,有望在不同的临床环境中提高诊断准确性和患者管理水平。真实世界研究证明了该算法对不同变量的适应性,确保了高质量的肝脏成像。个性化算法优化了肝脏 CT,提高了肝脏病变的可见性、明显性和随访性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Validation of a multi-parameter algorithm for personalized contrast injection protocol in liver CT.

Background: In liver computed tomography (CT), tailoring the contrast injection to the patient's specific characteristics is relevant for optimal imaging and patient safety. We evaluated a novel algorithm engineered for personalized contrast injection to achieve reproducible liver enhancement centered on 50 HU.

Methods: From September 2020 to August 31, 2022, CT data from consecutive adult patients were prospectively collected at our multicenter premises. Inclusion criteria consisted of an abdominal CT referral for cancer staging or follow-up. For all examinations, a web interface incorporating data from the radiology information system (patient details and examination information) and radiographer-inputted data (patient fat-free mass, imaging center, kVp, contrast agent details, and imaging phase) were used. Calculated contrast volume and injection rate were manually entered into the CT console controlling the injector. Iopamidol 370 mgI/mL or Iohexol 350 mgI/mL were used, and kVp varied (80, 100, or 120) based on patient habitus.

Results: We enrolled 384 patients (mean age 61.2 years, range 21.1-94.5). The amount of administered iodine dose (gI) was not significantly different across contrast agents (p = 0.700), while a significant increase in iodine dose was observed with increasing kVp (p < 0.001) and in males versus females (p < 0.001), as expected. Despite the differences in administered iodine load, image quality was reproducible across patients with 72.1% of the examinations falling within the desirable range of 40-60 HU.

Conclusion: This study validated a novel algorithm for personalized contrast injection in adult abdominal CT, achieving consistent liver enhancement centered at 50 HU.

Relevance statement: In healthcare's ongoing shift towards personalized medicine, the algorithm offers excellent potential to improve diagnostic accuracy and patient management, particularly for the detection and follow-up of liver malignancies.

Key points: The algorithm achieves reproducible liver enhancement, promising improved diagnostic accuracy and patient management in diverse clinical settings. The real-world study demonstrates this algorithm's adaptability to different variables ensuring high-quality liver imaging. A personalized algorithm optimizes liver CT, improving the visibility, conspicuity, and follow-up of liver lesions.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
European Radiology Experimental
European Radiology Experimental Medicine-Radiology, Nuclear Medicine and Imaging
CiteScore
6.70
自引率
2.60%
发文量
56
审稿时长
18 weeks
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信