• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

CT 图像中脂肪组织分割的采集参数的意义。

Significance of Acquisition Parameters for Adipose Tissue Segmentation on CT Images.

机构信息

Department of Radiology, Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114.

Department of Radiation Oncology, University Hospital Münster, Münster, Germany.

出版信息

AJR Am J Roentgenol. 2021 Jul;217(1):177-185. doi: 10.2214/AJR.20.23280. Epub 2021 Mar 17.

DOI:10.2214/AJR.20.23280
PMID:33729886
Abstract

CT-based body composition analysis quantifies skeletal muscle and adipose tissue. However, acquisition parameters and quality can vary between CT images obtained for clinical care, which may lead to unreliable measurements and systematic error. The purpose of this study was to estimate the influence of IV contrast medium, tube current-exposure time product, tube potential, and slice thickness on cross-sectional area (CSA) and mean attenuation of subcutaneous (SAT), visceral (VAT), and inter-muscular adipose tissue (IMAT). We retrospectively analyzed 244 images from 105 patients. We applied semiautomated threshold-based segmentation to CTA, dual-energy CT, and CT images acquired as part of PET examinations. An axial image at the level of the third lumbar vertebral body was extracted from each examination to generate 139 image pairs. Images from each pair were obtained with the same scanner, from the same patient, and during the same examination. Each image pair varied in only one acquisition parameter, which allowed us to estimate the effect of the parameter using one-sample or median tests and Bland-Altman plots. IV contrast medium application reduced CSA in each adipose tissue compartment, with percentage change ranging from -0.4% ( = .03) to -9.3% ( < .001). Higher tube potential reduced SAT CSA (median percentage change, -4.2%; < .001) and VAT CSA (median percentage change, -2.8%; = .001) and increased IMAT CSA (median percentage change, -5.4%; = .001). Thinner slices increased CSA in the VAT (mean percentage change, 3.0%; = .005) and IMAT (median percentage change, 17.3%; < .001) compartments. Lower tube current-exposure time product had a variable effect on CSA (median percentage change, -3.2% for SAT [ < .001], -12.6% for VAT [ = .001], and 58.8% for IMAT [ < .001]). IV contrast medium and higher tube potential increased mean attenuation, with percentage change ranging from 0.8% to 1.7% ( < .05) and from 6.2% to 20.8% ( < .001), respectively. Conversely, thinner slice and lower tube current-exposure time product reduced mean attenuation, with percentage change ranging from -5.4% to -1.0% ( < .001) and from -8.7% to -1.8% ( < .001), respectively. Acquisition parameters significantly affect CSA and mean attenuation of adipose tissue. Details of acquisition parameters used for CT-based body composition analysis need to be scrutinized and reported to facilitate interpretation of research studies.

摘要

CT 基础的身体成分分析定量评估骨骼肌和脂肪组织。然而,临床护理中获得的 CT 图像的采集参数和质量可能存在差异,这可能导致测量结果不可靠和系统误差。本研究的目的是评估 IV 对比剂、管电流-曝光时间乘积、管电压和层厚对皮下(SAT)、内脏(VAT)和肌间脂肪组织(IMAT)的横截面积(CSA)和平均衰减的影响。

我们回顾性分析了 105 例患者的 244 幅图像。我们应用半自动基于阈值的分割对 CTA、双能 CT 和 PET 检查中获得的 CT 图像进行了分析。从每项检查中提取第三腰椎水平的轴向图像,生成 139 对图像。每对图像均来自同一台扫描仪、同一患者且在同一检查中获得。每对图像的采集参数只有一项不同,这使我们能够使用单样本或中位数检验和 Bland-Altman 图来估计参数的影响。

IV 对比剂的应用降低了每个脂肪组织隔室的 CSA,百分比变化范围为-0.4%( =.03)至-9.3%( <.001)。较高的管电压降低了 SAT CSA(中位数百分比变化,-4.2%; <.001)和 VAT CSA(中位数百分比变化,-2.8%; =.001),并增加了 IMAT CSA(中位数百分比变化,-5.4%; =.001)。更薄的切片增加了 VAT(平均百分比变化,3.0%; =.005)和 IMAT(中位数百分比变化,17.3%; <.001)隔室的 CSA。较低的管电流-曝光时间乘积对 CSA 有不同的影响(SAT 的中位数百分比变化,-3.2%[ <.001],VAT 的-12.6%[ =.001],IMAT 的 58.8%[ <.001])。IV 对比剂和较高的管电压增加了平均衰减,百分比变化范围为 0.8%至 1.7%( <.05)和 6.2%至 20.8%( <.001)。相反,更薄的切片和更低的管电流-曝光时间乘积降低了平均衰减,百分比变化范围为-5.4%至-1.0%( <.001)和-8.7%至-1.8%( <.001)。

采集参数会显著影响脂肪组织的 CSA 和平均衰减。需要仔细检查和报告 CT 基础身体成分分析中使用的采集参数的详细信息,以促进研究结果的解释。

相似文献

1
Significance of Acquisition Parameters for Adipose Tissue Segmentation on CT Images.CT 图像中脂肪组织分割的采集参数的意义。
AJR Am J Roentgenol. 2021 Jul;217(1):177-185. doi: 10.2214/AJR.20.23280. Epub 2021 Mar 17.
2
Quantifying the effect of slice thickness, intravenous contrast and tube current on muscle segmentation: Implications for body composition analysis.量化切片厚度、静脉对比剂和管电流对肌肉分割的影响:对身体成分分析的意义。
Eur Radiol. 2018 Jun;28(6):2455-2463. doi: 10.1007/s00330-017-5191-3. Epub 2018 Jan 9.
3
Comparison between skeletal muscle and adipose tissue measurements with high-dose CT and low-dose attenuation correction CT of F-FDG PET/CT in elderly Hodgkin lymphoma patients: a two-centre validation.老年霍奇金淋巴瘤患者 F-FDG PET/CT 高剂量 CT 与低剂量衰减校正 CT 测量骨骼肌和脂肪组织的比较:一项两中心验证。
Br J Radiol. 2021 Jul 1;94(1123):20200672. doi: 10.1259/bjr.20200672. Epub 2021 Jun 9.
4
Concordance of Computed Tomography Regional Body Composition Analysis Using a Fully Automated Open-Source Neural Network versus a Reference Semi-Automated Program with Manual Correction.基于全自动开源神经网络与参考半自动程序(带手动校正)的 CT 区域身体成分分析的一致性研究。
Sensors (Basel). 2022 Apr 27;22(9):3357. doi: 10.3390/s22093357.
5
Body composition evaluation with computed tomography: Contrast media and slice thickness cause methodological errors.体成分评估的 CT 检查:对比剂和层厚可致方法学错误。
Nutrition. 2019 Mar;59:50-55. doi: 10.1016/j.nut.2018.08.001. Epub 2018 Aug 9.
6
Chest Fat Quantification via CT Based on Standardized Anatomy Space in Adult Lung Transplant Candidates.基于标准化解剖空间的胸部CT对成年肺移植受者胸部脂肪的量化分析
PLoS One. 2017 Jan 3;12(1):e0168932. doi: 10.1371/journal.pone.0168932. eCollection 2017.
7
Body composition from single versus multi-slice abdominal computed tomography: Concordance and associations with colorectal cancer survival.单层面与多层面腹部 CT 测量体成分:与结直肠癌生存的一致性及相关性。
J Cachexia Sarcopenia Muscle. 2022 Dec;13(6):2974-2984. doi: 10.1002/jcsm.13080. Epub 2022 Sep 2.
8
Fat Attenuation at CT in Anorexia Nervosa.神经性厌食症患者CT检查中的脂肪衰减
Radiology. 2016 Apr;279(1):151-7. doi: 10.1148/radiol.2015151104. Epub 2015 Oct 28.
9
Quantification of body-torso-wide tissue composition on low-dose CT images via automatic anatomy recognition.利用自动解剖识别技术对低剂量 CT 图像进行全身组织成分定量分析。
Med Phys. 2019 Mar;46(3):1272-1285. doi: 10.1002/mp.13373. Epub 2019 Feb 5.
10
Deep learning method for localization and segmentation of abdominal CT.深度学习方法在腹部 CT 定位与分割中的应用。
Comput Med Imaging Graph. 2020 Oct;85:101776. doi: 10.1016/j.compmedimag.2020.101776. Epub 2020 Aug 14.

引用本文的文献

1
Opportunistic Screening on Chest CT, From the Special Series on Screening.胸部CT的机会性筛查,来自筛查专题系列。
AJR Am J Roentgenol. 2025 Jul 16. doi: 10.2214/AJR.25.33069.
2
Body composition as a potential biomarker of recurrence risk in patients with triple-negative breast cancer.身体成分作为三阴性乳腺癌患者复发风险的潜在生物标志物。
Breast Cancer Res Treat. 2025 Jun;211(3):627-635. doi: 10.1007/s10549-025-07675-w. Epub 2025 Mar 11.
3
Subcutaneous adipose tissue measured by computed tomography could be an independent predictor for early outcomes of patients with severe COVID-19.
通过计算机断层扫描测量的皮下脂肪组织可能是重症新型冠状病毒肺炎患者早期预后的独立预测指标。
Front Nutr. 2024 Oct 14;11:1432251. doi: 10.3389/fnut.2024.1432251. eCollection 2024.
4
A Cross-Sectional Validation of Horos and CoreSlicer Software Programs for Body Composition Analysis in Abdominal Computed Tomography Scans in Colorectal Cancer Patients.用于结直肠癌患者腹部计算机断层扫描中身体成分分析的Horos和CoreSlicer软件程序的横断面验证
Diagnostics (Basel). 2024 Aug 5;14(15):1696. doi: 10.3390/diagnostics14151696.
5
Subcutaneous and Visceral Adipose Tissue Reference Values From the Framingham Heart Study Thoracic and Abdominal CT.来自弗雷明汉心脏研究胸部和腹部CT的皮下及内脏脂肪组织参考值。
Invest Radiol. 2025 Feb 1;60(2):95-104. doi: 10.1097/RLI.0000000000001104. Epub 2024 Jul 25.
6
Ethnic differences in CT derived abdominal body composition measures: a comparative retrospect pilot study between European and Inuit study population.CT 衍生的腹部身体成分测量中的种族差异:欧洲和因纽特人研究人群之间的比较回顾性初步研究
Int J Circumpolar Health. 2024 Dec;83(1):2312663. doi: 10.1080/22423982.2024.2312663. Epub 2024 Feb 5.
7
Relationship Between Preoperative Psoas Major Muscle Quality and Forgotten Joint Score-12 in Patients After Total Hip Arthroplasty.全髋关节置换术后患者术前腰大肌质量与遗忘关节评分-12之间的关系
Arthroplast Today. 2023 Mar 7;20:101118. doi: 10.1016/j.artd.2023.101118. eCollection 2023 Apr.
8
Adipose tissue radiodensity and mortality among patients with nonmetastatic breast cancer.非转移性乳腺癌患者的脂肪组织辐射密度与死亡率。
Clin Nutr. 2022 Dec;41(12):2607-2613. doi: 10.1016/j.clnu.2022.09.016. Epub 2022 Oct 4.
9
Higher subcutaneous adipose tissue radiodensity is associated with increased mortality in patients with cirrhosis.较高的皮下脂肪组织放射密度与肝硬化患者死亡率增加相关。
JHEP Rep. 2022 Apr 27;4(7):100495. doi: 10.1016/j.jhepr.2022.100495. eCollection 2022 Jul.
10
A Fully Automated Deep Learning Pipeline for Multi-Vertebral Level Quantification and Characterization of Muscle and Adipose Tissue on Chest CT Scans.一种用于胸部CT扫描中多椎体水平肌肉和脂肪组织定量与特征分析的全自动深度学习流程
Radiol Artif Intell. 2022 Jan 5;4(1):e210080. doi: 10.1148/ryai.210080. eCollection 2022 Jan.