Overcoming calcium blooming and improving the quantification accuracy of percent area luminal stenosis by material decomposition of multi-energy computed tomography datasets

被引:7
|
作者
Li, Zhoubo [1 ,2 ]
Leng, Shuai [1 ]
Halaweish, Ahmed F. [3 ]
Yu, Zhicong [1 ]
Yu, Lifeng [1 ]
Ritman, Erik L. [4 ]
McCollough, Cynthia H. [1 ]
机构
[1] Mayo Clin, Dept Radiol, Rochester, MN 55905 USA
[2] Mayo Grad Sch, Biomed Engn & Physiol Grad Program, Rochester, MN USA
[3] Siemens Healthcare Imaging & Therapy Syst, Malvern, PA USA
[4] Mayo Clin, Dept Physiol & Biomed Engn, Rochester, MN USA
基金
美国国家卫生研究院;
关键词
computed tomography; CT angiography; stenosis; atherosclerosis; material decomposition; calcium blooming; CAROTID-ARTERY STENOSIS; CROSS-SECTIONAL AREAS; CT ANGIOGRAPHY; CEREBRAL-ANGIOGRAPHY; MAGNETIC-RESONANCE; LUMEN SEGMENTATION; OCCLUSIVE DISEASE; VESSEL ANALYSIS; MR-ANGIOGRAPHY; ENHANCED MR;
D O I
10.1117/1.JMI.7.5.053501
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose: Conventional stenosis quantification from single-energy computed tomography (SECT) images relies on segmentation of lumen boundaries, which suffers from partial volume averaging and calcium blooming effects. We present and evaluate a method for quantifying percent area stenosis using multienergy CT (MECT) images. Approach: We utilize material decomposition of MECT images to measure stenosis based on the ratio of iodine mass between vessel locations with and without a stenosis, thereby eliminating the requirement for segmentation of iodinated lumen. The method was first assessed using simulated MECT images created with different spatial resolutions. To experimentally assess this method, four phantoms with different stenosis severity (30% to 51%), vessel diameters (5.5 to 14 mm), and calcification densities (700 to 1100 mgHA/cc) were fabricated. Conventional SECT images were acquired using a commercial CT system and were analyzed with commercial software. MECT images were acquired using a commercial dual-energy CT (DECT) system and also from a research photon-counting detector CT (PCD-CT) system. Three-material-decomposition was performed on MECT data, and iodine density maps were used to quantify stenosis. Clinical radiation doses were used for all data acquisitions. Results: Computer simulation verified that this method reduced partial volume and blooming effects, resulting in consistent stenosis measurements. Phantom experiments showed accurate and reproducible stenosis measurements from MECT images. For DECT and two-threshold PCD-CT images, the estimation errors were 4.0% to 7.0%, 2.0% to 9.0%, 10.0% to 18.0%, and -1.0% to -5.0% (ground truth: 51%, 51%, 51%, and 30%). For four-threshold PCD-CT images, the errors were 1.0% to 3.0%, 4.0% to 6.0%, -1.0% to 9.0%, and 0.0% to 6.0%. Errors using SECT were much larger, ranging from 4.4% to 46%, and were especially worse in the presence of dense calcifications. Conclusions: The proposed approach was shown to be insensitive to acquisition parameters, demonstrating the potential to improve the accuracy and precision of stenosis measurements in clinical practice. (C) 2020 Society of Photo-Optical Instrumentation Engineers (SPIE)
引用
收藏
页数:16
相关论文
共 5 条
  • [1] Material decomposition with dual- and multi-energy computed tomography
    Rajesh Bhayana
    Anushri Parakh
    Avinash Kambadakone
    [J]. MRS Communications, 2020, 10 : 558 - 565
  • [2] Material decomposition with dual- and multi-energy computed tomography
    Bhayana, Rajesh
    Parakh, Anushri
    Kambadakone, Avinash
    [J]. MRS COMMUNICATIONS, 2020, 10 (04) : 558 - 565
  • [3] Multi-energy computed tomography and material quantification: Current barriers and opportunities for advancement
    Jacobsen, Megan C.
    Thrower, Sara L.
    Ger, Rachel B.
    Leng, Shuai
    Court, Laurence E.
    Brock, Kristy K.
    Tamm, Eric P.
    Cressman, Erik N. K.
    Cody, Dianna D.
    Layman, Rick R.
    [J]. MEDICAL PHYSICS, 2020, 47 (08) : 3752 - 3771
  • [4] Impact of iron deposit on the accuracy of quantifying liver fat fraction using multi-material decomposition algorithm in dual-energy spectral computed tomography
    Du, Dandan
    Wu, Xingwang
    Wang, Jinchuan
    Chen, Hua
    Song, Jian
    Liu, Bin
    [J]. JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS, 2021, 22 (08): : 236 - 242
  • [5] Hepatic Fat Quantification with the Multi-Material Decomposition Algorithm by Using Low-Dose Non-Contrast Material-Enhanced Dual-Energy Computed Tomography in a Prospectively Enrolled Cohort
    Hong, Seung Baek
    Lee, Nam Kyung
    Kim, Suk
    Um, Kyunga
    Kim, Keunyoung
    Kim, In Joo
    [J]. MEDICINA-LITHUANIA, 2022, 58 (10):