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Pakizer D, Kozel J, Elmers J, Feber J, Michel P, Školoudík D, Sirimarco G. Diagnostics Accuracy of Magnetic Resonance Imaging in Detection of Atherosclerotic Plaque Characteristics in Carotid Arteries Compared to Histology: A Systematic Review. J Magn Reson Imaging 2024. [PMID: 38981139 DOI: 10.1002/jmri.29522] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Revised: 06/12/2024] [Accepted: 06/17/2024] [Indexed: 07/11/2024] Open
Abstract
Carotid plaque composition represents one of the main risk factors of future ischemic stroke. MRI provides excellent soft tissue contrast that can distinguish plaque characteristics. Our objective was to analyze the diagnostic accuracy of MRI imaging in the detection of carotid plaque characteristics compared to histology in patients with symptomatic and asymptomatic carotid atherosclerosis through a systematic review. After prospective registration in PROSPERO (ID CRD42022329690), Medline Ovid, Embase.com, Cochrane Library, and Web of Science Core were searched without any search limitation up to May 27, 2022 to identify eligible articles. Of the 8168 studies, 53 (37 × 1.5 T MRI, 17 × 3 T MRI) evaluated MRI accuracy in the detection of 13 specific carotid plaque characteristics in 169 comparisons. MRI demonstrated high diagnostic accuracy for detection of calcification (3 T MRI: mean sensitivity 92%/mean specificity 90%; 1.5 T MRI: mean sensitivity 81%/mean specificity 91%), fibrous cap (1.5 T: 89%/87%), unstable plaque (1.5 T: 89%/87%), intraplaque hemorrhage (1.5 T: 86%/88%), and lipid-rich necrotic core (1.5 T: 89%/79%). MRI also proved to have a high level of tissue discrimination for the carotid plaque characteristics investigated, allowing potentially for a better risk assessment and follow-up of patients who may benefit from more aggressive treatments. These results emphasize the role of MRI as the first-line imaging modality for comprehensive assessment of carotid plaque morphology, particularly for unstable plaque. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- David Pakizer
- Centre for Health Research, Department of Clinical Neurosciences, Faculty of Medicine, University of Ostrava, Ostrava, Czech Republic
| | - Jiří Kozel
- Centre for Health Research, Department of Clinical Neurosciences, Faculty of Medicine, University of Ostrava, Ostrava, Czech Republic
| | - Jolanda Elmers
- Medical Library, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Janusz Feber
- Centre for Health Research, Department of Clinical Neurosciences, Faculty of Medicine, University of Ostrava, Ostrava, Czech Republic
- Division of Nephrology, Department of Pediatrics, Children's Hospital of Eastern Ontario, University of Ottawa, Ottawa, Ontario, Canada
| | - Patrik Michel
- Stroke Center, Service of Neurology, Department of Clinical Neurosciences, Lausanne University Hospital, Lausanne, Switzerland
| | - David Školoudík
- Centre for Health Research, Department of Clinical Neurosciences, Faculty of Medicine, University of Ostrava, Ostrava, Czech Republic
| | - Gaia Sirimarco
- Stroke Center, Service of Neurology, Department of Clinical Neurosciences, Lausanne University Hospital, Lausanne, Switzerland
- Neurology Unit, Department of Internal Medicine, Riviera Chablais Hospital, Rennaz, Switzerland
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Elsaid NMH, Peters DC, Galiana G, Sinusas AJ. Clinical physiology: the crucial role of MRI in evaluation of peripheral artery disease. Am J Physiol Heart Circ Physiol 2024; 326:H1304-H1323. [PMID: 38517227 DOI: 10.1152/ajpheart.00533.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 03/19/2024] [Accepted: 03/19/2024] [Indexed: 03/23/2024]
Abstract
Peripheral artery disease (PAD) is a common vascular disease that primarily affects the lower limbs and is defined by the constriction or blockage of peripheral arteries and may involve microvascular dysfunction and tissue injury. Patients with diabetes have more prominent disease of microcirculation and develop peripheral neuropathy, autonomic dysfunction, and medial vascular calcification. Early and accurate diagnosis of PAD and disease characterization are essential for personalized management and therapy planning. Magnetic resonance imaging (MRI) provides excellent soft tissue contrast and multiplanar imaging capabilities and is useful as a noninvasive imaging tool in the comprehensive physiological assessment of PAD. This review provides an overview of the current state of the art of MRI in the evaluation and characterization of PAD, including an analysis of the many applicable MR imaging techniques, describing the advantages and disadvantages of each approach. We also present recent developments, future clinical applications, and future MRI directions in assessing PAD. The development of new MR imaging technologies and applications in preclinical models with translation to clinical research holds considerable potential for improving the understanding of the pathophysiology of PAD and clinical applications for improving diagnostic precision, risk stratification, and treatment outcomes in patients with PAD.
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Affiliation(s)
- Nahla M H Elsaid
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut, United States
| | - Dana C Peters
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut, United States
- Department of Biomedical Engineering, Yale University, New Haven, Connecticut, United States
| | - Gigi Galiana
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut, United States
- Department of Biomedical Engineering, Yale University, New Haven, Connecticut, United States
| | - Albert J Sinusas
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut, United States
- Department of Biomedical Engineering, Yale University, New Haven, Connecticut, United States
- Department of Medicine, Yale University School of Medicine, New Haven, Connecticut, United States
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Huang LX, Wu XB, Liu YA, Guo X, Liu CC, Cai WQ, Wang SW, Luo B. High-resolution magnetic resonance vessel wall imaging in ischemic stroke and carotid artery atherosclerotic stenosis: A review. Heliyon 2024; 10:e27948. [PMID: 38571643 PMCID: PMC10987942 DOI: 10.1016/j.heliyon.2024.e27948] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 03/02/2024] [Accepted: 03/08/2024] [Indexed: 04/05/2024] Open
Abstract
Ischemic stroke is a significant burden on human health worldwide. Carotid Atherosclerosis stenosis plays an important role in the comprehensive assessment and prevention of ischemic stroke patients. High-resolution vessel wall magnetic resonance imaging has emerged as a successful technique for assessing carotid atherosclerosis stenosis. This advanced imaging modality has shown promise in effectively displaying a wide range of characteristics associated with the condition, leading to a comprehensive evaluation. High-resolution vessel wall magnetic resonance imaging not only enables a comprehensive evaluation of the instability of carotid atherosclerosis stenosis plaques but also provides valuable information for understanding the pathogenesis and predicting the prognosis of ischemic stroke patients. The purpose of this article is to review the application of high-resolution magnetic resonance imaging in ischemic stroke and carotid atherosclerotic stenosis.
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Affiliation(s)
- Li-Xin Huang
- Department of Neurosurgery, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
- Department of Neurosurgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Department of Neurosurgery, The Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen, China
| | - Xiao-Bing Wu
- Department of Neurosurgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yi-Ao Liu
- Department of Neurosurgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Department of Neurosurgery, The Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen, China
| | - Xin Guo
- Department of Neurosurgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Department of Neurosurgery, The Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen, China
| | - Chi-Chen Liu
- Department of Neurosurgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Department of Neurosurgery, The Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen, China
| | - Wang-Qing Cai
- Department of Neurosurgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Sheng-Wen Wang
- Department of Neurosurgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Bin Luo
- Department of Neurosurgery, The Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen, China
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Wen L, Fu X, Zhang H, Ye P, Fu H, Zhou Z, Sun R, Xu T, Fu C, Zhu C, Guo Y, Fan H. Tailoring Zinc Ferrite Nanoparticle Surface Coating for Macrophage-Affinity Magnetic Resonance Imaging of Atherosclerosis. ACS APPLIED MATERIALS & INTERFACES 2024; 16:13496-13508. [PMID: 38449094 DOI: 10.1021/acsami.3c17212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/08/2024]
Abstract
Atherosclerosis is a chronic inflammatory disease characterized by the formation of atherosclerotic plaques, while macrophages as key players in plaque progression and destabilization are promising targets for atherosclerotic plaque imaging. Contrast-enhanced magnetic resonance imaging (CE-MRI) has emerged as a powerful noninvasive imaging technique for the evaluation of atherosclerotic plaques within arterial walls. However, the visualization of macrophages within atherosclerotic plaques presents considerable challenges due to the intricate pathophysiology of the disease and the dynamic behavior of these cells. Biocompatible ferrite nanoparticles with diverse surface ligands possess the potential to exhibit distinct relaxivity and cellular affinity, enabling improved imaging capabilities for macrophages in atherosclerosis. In this work, we report macrophage-affinity nanoparticles for magnetic resonance imaging (MRI) of atherosclerosis via tailoring nanoparticle surface coating. The ultrasmall zinc ferrite nanoparticles (Zn0.4Fe2.6O4) as T1 contrast agents were synthesized and modified with dopamine, 3,4-dihydroxyhydrocinnamic acid, and phosphorylated polyethylene glycol to adjust their surface charges to be positively, negatively, and neutrally charged, respectively. In vitro MRI evaluation shows that the T1 relaxivity for different surface charged Zn0.4Fe2.6O4 nanoparticles was three higher than that of the clinically used Gd-DTPA. Furthermore, in vivo atherosclerotic plaque MR imaging indicates that positively charged Zn0.4Fe2.6O4 showed superior MRI efficacy on carotid atherosclerosis than the other two, which is ascribed to high affinity to macrophages of positively charged nanoparticles. This work provides improved diagnostic capability and a better understanding of the molecular imaging of atherosclerosis.
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Affiliation(s)
- Lingyi Wen
- Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu 614001, China
| | - Xiaomin Fu
- Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu 614001, China
| | - Huan Zhang
- Key Laboratory of Synthetic and Natural Functional Molecule Chemistry of the Ministry of Education, College of Chemistry and Materials Science, Northwest University, Xi'an 710127, China
- School of Medicine, Northwest University, Xi'an 710069, China
- Department of Radiology, Zhuhai People's Hospital (Zhuhai Clinical Medical College of Jinan University), Zhuhai 519000, China
| | - Pengfei Ye
- Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu 614001, China
| | - Hang Fu
- Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu 614001, China
| | - Zhongqin Zhou
- Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu 614001, China
| | - Ran Sun
- Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu 614001, China
| | - Ting Xu
- Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu 614001, China
| | - Chuan Fu
- Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu 614001, China
| | - Chengcheng Zhu
- Department of Radiology, University of Washington, Seattle, Washington 98105, United States
| | - Yingkun Guo
- Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu 614001, China
| | - Haiming Fan
- Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu 614001, China
- Key Laboratory of Synthetic and Natural Functional Molecule Chemistry of the Ministry of Education, College of Chemistry and Materials Science, Northwest University, Xi'an 710127, China
- School of Medicine, Northwest University, Xi'an 710069, China
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Koppara T, Dregely I, Nekolla SG, Nährig J, Langwieser N, Bradaric C, Ganter C, Laugwitz KL, Schwaiger M, Ibrahim T. Simultaneous 18-FDG PET and MR imaging in lower extremity arterial disease. Front Cardiovasc Med 2024; 11:1352696. [PMID: 38404725 PMCID: PMC10884315 DOI: 10.3389/fcvm.2024.1352696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Accepted: 01/22/2024] [Indexed: 02/27/2024] Open
Abstract
Background Simultaneous positron emission tomography (PET) and magnetic resonance imaging (MRI) is a novel hybrid imaging method integrating the advances of morphological tissue characterization of MRI with the pathophysiological insights of PET applications. Aim This study evaluated the use of simultaneous 18-FDG PET/MR imaging for characterizing atherosclerotic lesions in lower extremity arterial disease (LEAD). Methods Eight patients with symptomatic stenoses of the superficial femoral artery (SFA) under simultaneous acquisition of 18-FDG PET and contrast-enhanced MRI using an integrated whole-body PET/MRI scanner. Invasive plaque characterization of the SFA was performed by intravascular imaging using optical coherence tomography. Histological analysis of plaque specimens was performed after directional atherectomy. Results MRI showed contrast enhancement at the site of arterial stenosis, as assessed on T2-w and T1-w images, compared to a control area of the contralateral SFA (0.38 ± 0.15 cm vs. 0.23 ± 0.11 cm; 1.77 ± 0.19 vs. 1.57 ± 0.15; p-value <0.05). On PET imaging, uptake of 18F-FDG (target-to-background ratio TBR > 1) at the level of symptomatic stenosis was observed in all but one patient. Contrast medium-induced MR signal enhancement was detected in all plaques, whereas FDG uptake in PET imaging was increased in lesions with active fibroatheroma and reduced in fibrocalcified lesions. Conclusion In this multimodal imaging study, we report the feasibility and challenges of simultaneous PET/MR imaging of LEAD, which might offer new perspectives for risk estimation.
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Affiliation(s)
- Tobias Koppara
- Department of Internal Medicine I, Cardiology and Angiology, School of Medicine and Health, Technical University of Munich, Munich, Germany
- DZHK (German Center for Cardiovascular Research)—Partner Site Munich Heart Alliance, Munich, Germany
| | - Isabel Dregely
- Department of Nuclear Medicine, School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Stephan G. Nekolla
- DZHK (German Center for Cardiovascular Research)—Partner Site Munich Heart Alliance, Munich, Germany
- Department of Nuclear Medicine, School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Jörg Nährig
- Institute of Pathology, School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Nicolas Langwieser
- Department of Internal Medicine I, Cardiology and Angiology, School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Christian Bradaric
- Department of Internal Medicine I, Cardiology and Angiology, School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Carl Ganter
- Institute of Radiology, School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Karl-Ludwig Laugwitz
- Department of Internal Medicine I, Cardiology and Angiology, School of Medicine and Health, Technical University of Munich, Munich, Germany
- DZHK (German Center for Cardiovascular Research)—Partner Site Munich Heart Alliance, Munich, Germany
| | - Markus Schwaiger
- DZHK (German Center for Cardiovascular Research)—Partner Site Munich Heart Alliance, Munich, Germany
- Department of Nuclear Medicine, School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Tareq Ibrahim
- Department of Internal Medicine I, Cardiology and Angiology, School of Medicine and Health, Technical University of Munich, Munich, Germany
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Irie R, Amemiya S, Ueyama T, Suzuki Y, Takao H, Abe O. Rapid MR Angiography Using 3D Gradient-echo Imaging and the Two-point Dixon Method to Evaluate Carotid Plaque. Magn Reson Med Sci 2023; 22:373-378. [PMID: 35387960 PMCID: PMC10449555 DOI: 10.2463/mrms.tn.2022-0002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Accepted: 03/01/2022] [Indexed: 11/09/2022] Open
Abstract
Liver acquisition with volume acceleration-flex (LAVA-Flex) acquires out-of-phase and in-phase echo images and automatically generates water-only and fat-only images from one single acquisition. The scan time of carotid MR angiography (MRA) using LAVA-Flex (LAVA MRA) is about one-fifth that of conventional time-of-flight MRA (cTOF MRA). We aimed to investigate whether LAVA MRA could provide useful information for the diagnosis of carotid plaque by utilizing the ability to acquire multiple sequences simultaneously. Comparing LAVA MRA and cTOF MRA images for carotid plaque, low-intensity plaques were more clearly identified in the in-phase images, and high-intensity plaques were more clearly identified in the water-only or out-of-phase images. None of the plaques exhibited superior visualization with the cTOF sequence. We concluded that LAVA MRA can provide more useful information on plaque evaluation using multiple sequences than cTOF MRA.
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Affiliation(s)
- Ryusuke Irie
- Department of Radiology, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
- Department of Radiology, Juntendo University Shizuoka Hospital, Izunokuni, Shizuoka, Japan
| | - Shiori Amemiya
- Department of Radiology, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
| | - Tsuyoshi Ueyama
- Radiology Center, the University of Tokyo Hospital, Tokyo, Japan
| | - Yuichi Suzuki
- Radiology Center, the University of Tokyo Hospital, Tokyo, Japan
| | - Hidemasa Takao
- Department of Radiology, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
| | - Osamu Abe
- Department of Radiology, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
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Varadarajan V, Gidding S, Wu C, Carr J, Lima JA. Imaging Early Life Cardiovascular Phenotype. Circ Res 2023; 132:1607-1627. [PMID: 37289903 PMCID: PMC10501740 DOI: 10.1161/circresaha.123.322054] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 04/30/2023] [Indexed: 06/10/2023]
Abstract
The growing epidemics of obesity, hypertension, and diabetes, in addition to worsening environmental factors such as air pollution, water scarcity, and climate change, have fueled the continuously increasing prevalence of cardiovascular diseases (CVDs). This has caused a markedly increasing burden of CVDs that includes mortality and morbidity worldwide. Identification of subclinical CVD before overt symptoms can lead to earlier deployment of preventative pharmacological and nonpharmacologic strategies. In this regard, noninvasive imaging techniques play a significant role in identifying early CVD phenotypes. An armamentarium of imaging techniques including vascular ultrasound, echocardiography, magnetic resonance imaging, computed tomography, noninvasive computed tomography angiography, positron emission tomography, and nuclear imaging, with intrinsic strengths and limitations can be utilized to delineate incipient CVD for both clinical and research purposes. In this article, we review the various imaging modalities used for the evaluation, characterization, and quantification of early subclinical cardiovascular diseases.
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Affiliation(s)
- Vinithra Varadarajan
- Division of Cardiology, Department of Medicine Johns Hopkins University, Baltimore, MD
| | | | - Colin Wu
- Department of Medicine, National Heart, Lung and Blood Institute, Bethesda, MD
| | - Jeffrey Carr
- Department Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN
| | - Joao A.C. Lima
- Division of Cardiology, Department of Medicine Johns Hopkins University, Baltimore, MD
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Li Y, Feng Y, Liu R, Dang M, Li T, Zhao L, Lu J, Lu Z, Yang Y, Wang X, Jian Y, Wang H, Huang W, Zhang L, Zhang G. The fibrinogen-to-albumin ratio is associated with intracranial atherosclerosis plaque enhancement on contrast-enhanced high-resolution magnetic resonance imaging. Front Neurol 2023; 14:1153171. [PMID: 37305748 PMCID: PMC10249607 DOI: 10.3389/fneur.2023.1153171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 05/09/2023] [Indexed: 06/13/2023] Open
Abstract
Background Contrast-enhanced high-resolution magnetic resonance imaging (CE-HR-MRI) is a useful imaging modality to assess vulnerable plaques in intracranial atherosclerotic stenosis (ICAS) patients. We studied the relationship between the fibrinogen-to-albumin ratio (FAR) and plaque enhancement in patients with ICAS. Methods We retrospectively enrolled consecutive ICAS patients who had undergone CE-HR-MRI. The degree of plaque enhancement on CE-HR-MRI was evaluated both qualitatively and quantitatively. Enrolled patients were classified into no enhancement, mild enhancement, and obvious enhancement groups. An independent association of the FAR with plaque enhancement was identified by multivariate logistic regression and receiver operating characteristic (ROC) curve analyses. Results Of the 69 enrolled patients, 40 (58%) were classified into the no/mild enhancement group, and 29 (42%) into the obvious enhancement group. The obvious enhancement group had a significantly higher FAR than the no/mild enhancement group (7.36 vs. 6.05, p = 0.001). After adjusting for potential confounders, the FAR was still significantly independently associated with obvious plaque enhancement in multiple regression analysis (odds ratio: 1.399, 95% confidence interval [CI]: 1.080-1.813; p = 0.011). ROC curve analysis revealed that FAR >6.37 predicted obvious plaque enhancement with 75.86% sensitivity and 67.50% specificity (area under the ROC curve = 0.726, 95% CI: 0.606-0.827, p < 0.001). Conclusion The FAR can serve as an independent predictor of the degree of plaque enhancement on CE-HR-MRI in patients with ICAS. Also, as an inflammatory marker, the FAR has potential as a serological biomarker of intracranial atherosclerotic plaque vulnerability.
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Affiliation(s)
- Ye Li
- Department of Neurology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Yuxuan Feng
- Department of Neurology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Rui Liu
- Department of Neurology, The First Hospital of Yulin, Yulin, Shaanxi, China
| | - Meijuan Dang
- Department of Neurology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Tao Li
- Department of Neurology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Lili Zhao
- Department of Neurology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Jialiang Lu
- Department of Neurology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Ziwei Lu
- Department of Neurology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Yang Yang
- Department of Neurology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Xiaoya Wang
- Department of Neurology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Yating Jian
- Department of Neurology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Heying Wang
- Department of Neurology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Wei Huang
- Department of Medical Imaging, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Lei Zhang
- Department of Neurology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Guilian Zhang
- Department of Neurology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
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Wang Y, Liu X, Wang J, Wang Y, Qi H, Kong X, Liu D, Liu J, Zheng H, Xiong F, Zhang L, Fu X, Zhang X, Guo R, Qiao H, Chen Z, Si D, Chen H. Simultaneous T1, T2, and T2* Mapping of Carotid Plaque: The SIMPLE* Technique. Radiology 2023; 307:e222061. [PMID: 36853181 DOI: 10.1148/radiol.222061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/01/2023]
Abstract
Background Quantitative T1, T2, and T2* measurements of carotid atherosclerotic plaque are important in evaluating plaque vulnerability and monitoring its progression. Purpose To develop a sequence to simultaneously quantify T1, T2, and T2* of carotid plaque. Materials and Methods The simultaneous T1, T2, and T2* mapping of carotid plaque (SIMPLE*) sequence is composed of three modules with different T2 preparation pulses, inversion-recovery pulses, and acquisition schemas. Single-echo data were used for T1 and T2 quantification, while the multiecho (ME) data were used for T2* quantification. The quantitative accuracy of SIMPLE* was tested in a phantom study by comparing its measurements with those of reference standard sequences. In vivo feasibility of the technique was prospectively evaluated between November 2020 and February 2022 in healthy volunteers and participants with carotid atherosclerotic plaque. The Pearson or Spearman correlation test, Student t test, and Wilcoxon rank-sum test were used. Results T1, T2, and T2* estimated with SIMPLE* strongly correlated with inversion-recovery spin-echo (SE) (correlation coefficient [r] = 0.99), ME-SE (r = 0.99), and ME gradient-echo (r = 0.99) sequences in the phantom study. In five healthy volunteers (mean age, 25 years ± 3 [SD]; three women), measurements were similar between SIMPLE* and modified Look-Locker inversion recovery, or MOLLI (1151 msec ± 71 vs 1098 msec ± 64; P = .14), ME turbo SE (31 msec ± 1 vs 31 msec ± 1; P = .32), and ME turbo field echo (24 msec ± 2 vs 25 msec ± 2; P = .19). In 18 participants with carotid plaque (mean age, 65 years ± 9; 16 men), quantitative T1, T2, and T2* of plaque components were consistent with their signal characteristics on multicontrast images. Conclusion A quantitative technique for simultaneous T1, T2, and T2* mapping of carotid plaque with 100-mm3 coverage and 0.8-mm3 resolution was developed using the proposed SIMPLE* sequence and demonstrated high accuracy and in vivo feasibility. © RSNA, 2023 Supplemental material is available for this article.
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Affiliation(s)
- Yajie Wang
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Xiaoming Liu
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Jing Wang
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Yishi Wang
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Haikun Qi
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Xiangchuang Kong
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Dingxi Liu
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Jia Liu
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Hanpei Zheng
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Fu Xiong
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Lan Zhang
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Xiaona Fu
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Xinli Zhang
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Rui Guo
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Huiyu Qiao
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Zhensen Chen
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Dongyue Si
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
| | - Huijun Chen
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Haidian District, Beijing, China 100084 (Yajie Wang, H. Qiao, D.S., H.C.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (X.L., J.W., X.K., D.L., J.L., H.Z., F.X., L.Z., X.F., X.Z.); Philips Healthcare, Beijing, China (Yishi Wang); School of Biomedical Engineering, ShanghaiTech University, Shanghai, China (H. Qi); School of Medical Technology, Beijing Institution of Technology, Beijing, China (R.G.); and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Z.C.)
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10
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Saba L, Loewe C, Weikert T, Williams MC, Galea N, Budde RPJ, Vliegenthart R, Velthuis BK, Francone M, Bremerich J, Natale L, Nikolaou K, Dacher JN, Peebles C, Caobelli F, Redheuil A, Dewey M, Kreitner KF, Salgado R. State-of-the-art CT and MR imaging and assessment of atherosclerotic carotid artery disease: standardization of scanning protocols and measurements-a consensus document by the European Society of Cardiovascular Radiology (ESCR). Eur Radiol 2023; 33:1063-1087. [PMID: 36194267 PMCID: PMC9889495 DOI: 10.1007/s00330-022-09024-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 06/26/2022] [Accepted: 06/30/2022] [Indexed: 02/04/2023]
Abstract
The European Society of Cardiovascular Radiology (ESCR) is the European specialist society of cardiac and vascular imaging. This society's highest priority is the continuous improvement, development, and standardization of education, training, and best medical practice, based on experience and evidence. The present intra-society consensus is based on the existing scientific evidence and on the individual experience of the members of the ESCR writing group on carotid diseases, the members of the ESCR guidelines committee, and the members of the executive committee of the ESCR. The recommendations published herein reflect the evidence-based society opinion of ESCR. We have produced a twin-papers consensus, indicated through the documents as respectively "Part I" and "Part II." The first document (Part I) begins with a discussion of features, role, indications, and evidence for CT and MR imaging-based diagnosis of carotid artery disease for risk stratification and prediction of stroke (Section I). It then provides an extensive overview and insight into imaging-derived biomarkers and their potential use in risk stratification (Section II). Finally, detailed recommendations about optimized imaging technique and imaging strategies are summarized (Section III). The second part of this consensus paper (Part II) is focused on structured reporting of carotid imaging studies with CT/MR. KEY POINTS: • CT and MR imaging-based evaluation of carotid artery disease provides essential information for risk stratification and prediction of stroke. • Imaging-derived biomarkers and their potential use in risk stratification are evolving; their correct interpretation and use in clinical practice must be well-understood. • A correct imaging strategy and scan protocol will produce the best possible results for disease evaluation.
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Affiliation(s)
- Luca Saba
- Department of Radiology, University of Cagliari, Cagliari, Italy
| | - Christian Loewe
- Division of Cardiovascular and Interventional Radiology, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Thomas Weikert
- Department of Radiology, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Michelle C Williams
- BHF Centre for Cardiovascular Science, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH164SB, UK
- Edinburgh Imaging Facility QMRI, University of Edinburgh, Edinburgh, UK
| | - Nicola Galea
- Policlinico Umberto I, Department of Radiological, Oncological and Pathological Sciences, Sapienza University of Rome, Rome, Italy
| | - Ricardo P J Budde
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - Rozemarijn Vliegenthart
- Department of Radiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ, Groningen, The Netherlands
| | - Birgitta K Velthuis
- Department of Radiology, Utrecht University Medical Center, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
| | - Marco Francone
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, Pieve Emanuele, 20072, Milan, Italy
- IRCCS Humanitas Research Hospital, Via Manzoni 56, Rozzano, 20089, Milan, Italy
| | - Jens Bremerich
- Department of Radiology, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Luigi Natale
- Department of Radiological Sciences - Institute of Radiology, Catholic University of Rome, "A. Gemelli" University Hospital, Rome, Italy
| | - Konstantin Nikolaou
- Department of Diagnostic and Interventional Radiology, University of Tuebingen, Tübingen, Germany
| | - Jean-Nicolas Dacher
- Department of Radiology, Normandie University, UNIROUEN, INSERM U1096 - Rouen University Hospital, F 76000, Rouen, France
| | - Charles Peebles
- Department of Cardiothoracic Radiology, University Hospital Southampton, Southampton, UK
| | - Federico Caobelli
- University Clinic of Nuclear Medicine Inselspital Bern, University of Bern, Bern, Switzerland
| | - Alban Redheuil
- Institute of Cardiometabolism and Nutrition (ICAN), Paris, France
- Department of Cardiovascular and Thoracic, Imaging and Interventional Radiology, Institute of Cardiology, APHP, Pitié-Salpêtrière University Hospital, Paris, France
- Laboratoire d'Imagerie Biomédicale, Sorbonne Universités, UPMC Univ Paris 06, INSERM 1146, CNRS 7371, Paris, France
| | - Marc Dewey
- Department of Radiology, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
| | - Karl-Friedrich Kreitner
- Department of Diagnostic and Interventional Radiology, University Medical Center, Mainz; Langenbeckstraße 1, 55131, Mainz, Germany
| | - Rodrigo Salgado
- Department of Radiology, Antwerp University Hospital & Antwerp University, Holy Heart Lier, Belgium.
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11
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Wang Y, Liu X, Wang Y, Qi H, Liu X, Kong X, Zhang Q, Dou J, Wang J, Chen H. Optimization of the Contrast Agent Injection Protocol for Carotid Artery Dynamic Contrast-Enhanced Magnetic Resonance Imaging. J Magn Reson Imaging 2022; 56:1372-1381. [PMID: 35324034 DOI: 10.1002/jmri.28175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 03/11/2022] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND The injection protocol used in previous carotid artery dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) studies varied. PURPOSE To investigate the effect of contrast injection protocol and optimize this protocol for carotid artery DCE-MRI. STUDY TYPE Prospective. SUBJECTS Digital phantom and seven patients with carotid atherosclerosis. FIELD STRENGTH/SEQUENCE 3 T, spoiled gradient recalled echo sequence. ASSESSMENT Different injection doses (0.01-0.3 mmol/kg) and effective injection rates (0.01-1 mmol/sec) were tested using a digital carotid plaque phantom considering the contrast pharmacokinetics, DCE-MRI imaging, contrast variation and flow-related imaging artifacts, random time delay between the contrast injection and image acquisition, and pharmacokinetic analysis process. For each injection protocol, combining the root mean square relative error (RMSRE) of the measured K trans and v P maps within the adventitial vasa vasorum from 10 tested time delays by the root mean square produced RMSREoverall-vv which was used to measure the overall accuracy of the pharmacokinetic parameters. In vivo validation was performed on seven patients with carotid atherosclerosis by imaging them twice using the traditional commonly used protocol and the recommended protocol found by simulation. STATISTICAL TEST Student's t-test, chi-square test, and paired t-test, P < 0.05 was considered statistically significant. RESULTS A low region of RMSREoverall-vv with the combination of medium injection dose and low effective injection rate was found. The protocol with injection dose of 0.07 mmol/kg and effective injection rate of 0.06 mmol/sec achieved the minimal RMSREoverall-vv (4.29%), thus was recommended, which showed more accurate arterial input function. Coinciding with the simulation results, this recommended protocol in in vivo experiments produced significantly fewer image artifacts, lower K trans and v P (P all <0.05) than traditional protocol which overestimated these parameters in simulation. DATA CONCLUSION The contrast injection protocol influenced the accuracy of the pharmacokinetics parameter estimation in carotid artery DCE-MRI. The injection protocol with injection dose of 0.07 mmol/kg and effective injection rate of 0.06 mmol/sec was recommended. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY STAGE: 1.
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Affiliation(s)
- Yajie Wang
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Xiaoming Liu
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.,Hubei Province Key Laboratory of Molecular Imaging, Wuhan, Hubei, China
| | | | - Haikun Qi
- School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
| | - Xian Liu
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Xiangchuang Kong
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.,Hubei Province Key Laboratory of Molecular Imaging, Wuhan, Hubei, China
| | - Qiang Zhang
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Jiaqi Dou
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Jing Wang
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.,Hubei Province Key Laboratory of Molecular Imaging, Wuhan, Hubei, China
| | - Huijun Chen
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
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12
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Safety of Carotid Artery Stenting in Elderly Patients by Treatment Selection Based on Plaque Characteristics. Indian J Surg 2022. [DOI: 10.1007/s12262-022-03585-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
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13
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In Vivo Intravascular Optical Coherence Tomography (IVOCT) Structural and Blood Flow Imaging Based Mechanical Simulation Analysis of a Blood Vessel. Cardiovasc Eng Technol 2022; 13:685-698. [PMID: 35112317 DOI: 10.1007/s13239-022-00608-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Accepted: 01/04/2022] [Indexed: 01/27/2023]
Abstract
INTRODUCTION Computer modelling of blood vessels based on biomedical imaging provides important hemodynamic and biomechanical information for vascular disease studies and diagnosis. However due to lacking well-defined physiological blood flow profiles, the accuracy of the simulation results is often not guaranteed. Flow velocity profiles of a specific cross section of a blood vessel were obtained by in vivo Doppler intravascular optical coherence tomography (IVOCT) lately. However due to the influence of the catheter, the velocity profile imaged by IVOCT can't be applied to simulation directly. METHODS A simulation-experiment combined method to determine the inlet flow boundary based on in vivo porcine carotid Doppler IVOCT imaging is proposed. A single conduit carotid model was created from the 3D IVOCT structural images using an image processing-computer aided design combined method. RESULTS With both high- resolution arterial model and near physiological blood flow profile, stress analysis by fluid-structure interaction and computational fluid dynamics were performed. The influence of the catheter to the wall shear stress, the hemodynamics and the stresses of the carotid wall under the measured inlet flow and various outlet pressure boundary conditions, are analyzed. CONCLUSION This study provides a solution to the difficulty of getting inlet flow boundary for numerical simulation of arteries. It paves the way for developing IVOCT based vascular stress analysis and imaging methods for the studies and diagnosis of vascular diseases.
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14
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Kaczynski J, Sellers S, Seidman MA, Syed M, Dennis M, Mcnaught G, Jansen M, Semple SI, Alcaide-Corral C, Tavares AAS, MacGillivray T, Debono S, Forsythe R, Tambyraja A, Slomka PJ, Leipsic J, Dweck MR, Whiteley W, Wardlaw J, van Beek EJR, Newby DE, Williams MC. 18F-NaF PET/MRI for Detection of Carotid Atheroma in Acute Neurovascular Syndrome. Radiology 2022; 305:137-148. [PMID: 35670715 PMCID: PMC9523682 DOI: 10.1148/radiol.212283] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 02/28/2022] [Accepted: 04/21/2022] [Indexed: 12/17/2022]
Abstract
Background MRI and fluorine 18-labeled sodium fluoride (18F-NaF) PET can be used to identify features of plaque instability, rupture, and disease activity, but large studies have not been performed. Purpose To evaluate the association between 18F-NaF activity and culprit carotid plaque in acute neurovascular syndrome. Materials and Methods In this prospective observational cohort study (October 2017 to January 2020), participants underwent 18F-NaF PET/MRI. An experienced clinician determined the culprit carotid artery based on symptoms and record review. 18F-NaF uptake was quantified using standardized uptake values and tissue-to-background ratios. Statistical significance was assessed with the Welch, χ2, Wilcoxon, or Fisher test. Multivariable models were used to evaluate the relationship between the imaging markers and the culprit versus nonculprit vessel. Results A total of 110 participants were evaluated (mean age, 68 years ± 10 [SD]; 70 men and 40 women). Of the 110, 34 (32%) had prior cerebrovascular disease, and 26 (24%) presented with amaurosis fugax, 54 (49%) with transient ischemic attack, and 30 (27%) with stroke. Compared with nonculprit carotids, culprit carotids had greater stenoses (≥50% stenosis: 30% vs 15% [P = .02]; ≥70% stenosis: 25% vs 4.5% [P < .001]) and had increased prevalence of MRI-derived adverse plaque features, including intraplaque hemorrhage (42% vs 23%; P = .004), necrotic core (36% vs 18%; P = .004), thrombus (7.3% vs 0%; P = .01), ulceration (18% vs 3.6%; P = .001), and higher 18F-NaF uptake (maximum tissue-to-background ratio, 1.38 [IQR, 1.12-1.82] vs 1.26 [IQR, 0.99-1.66], respectively; P = .04). Higher 18F-NaF uptake was positively associated with necrosis, intraplaque hemorrhage, ulceration, and calcification and inversely associated with fibrosis (P = .04 to P < .001). In multivariable analysis, carotid stenosis at or over 70% (odds ratio, 5.72 [95% CI: 2.2, 18]) and MRI-derived adverse plaque characteristics (odds ratio, 2.16 [95% CI: 1.2, 3.9]) were both associated with the culprit versus nonculprit carotid vessel. Conclusion Fluorine 18-labeled sodium fluoride PET/MRI characteristics were associated with the culprit carotid vessel in study participants with acute neurovascular syndrome. Clinical trial registration no. NCT03215550 and NCT03215563 © RSNA, 2022 Online supplemental material is available for this article.
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Affiliation(s)
- Jakub Kaczynski
- From the BHF Centre for Cardiovascular Science, University of
Edinburgh, The Chancellor’s Building, 49 Little France Crescent,
EH16 4SB, Edinburgh, Scotland (J.K., M.S., G.M., M.J., S.I.S., C.A.C.,
A.A.S.T., S.D., M.R.D., E.J.R.v.B., D.E.N., M.C.W.); Centre for Heart Lung
Innovation, St Paul’s Hospital and University of British Columbia,
Vancouver, Canada (S.S., J.L.); Laboratory Medicine Program, University Health
Network, General Hospital, Toronto, Canada (M.A.S.); Royal Infirmary of
Edinburgh, Edinburgh, Scotland (M.D., R.F., A.T., W.W., J.W.); Edinburgh
Imaging, Queen’s Medical Research Institute, Edinburgh, Scotland (G.M.,
S.I.S., T.M., E.J.R.v.B., D.E.N., M.C.W.); and Department of Medicine, Division
of Artificial Intelligence in Medicine, Cedars-Sinai Medical Center, Los
Angeles, Calif (P.J.S.)
| | - Stephanie Sellers
- From the BHF Centre for Cardiovascular Science, University of
Edinburgh, The Chancellor’s Building, 49 Little France Crescent,
EH16 4SB, Edinburgh, Scotland (J.K., M.S., G.M., M.J., S.I.S., C.A.C.,
A.A.S.T., S.D., M.R.D., E.J.R.v.B., D.E.N., M.C.W.); Centre for Heart Lung
Innovation, St Paul’s Hospital and University of British Columbia,
Vancouver, Canada (S.S., J.L.); Laboratory Medicine Program, University Health
Network, General Hospital, Toronto, Canada (M.A.S.); Royal Infirmary of
Edinburgh, Edinburgh, Scotland (M.D., R.F., A.T., W.W., J.W.); Edinburgh
Imaging, Queen’s Medical Research Institute, Edinburgh, Scotland (G.M.,
S.I.S., T.M., E.J.R.v.B., D.E.N., M.C.W.); and Department of Medicine, Division
of Artificial Intelligence in Medicine, Cedars-Sinai Medical Center, Los
Angeles, Calif (P.J.S.)
| | - Michael A. Seidman
- From the BHF Centre for Cardiovascular Science, University of
Edinburgh, The Chancellor’s Building, 49 Little France Crescent,
EH16 4SB, Edinburgh, Scotland (J.K., M.S., G.M., M.J., S.I.S., C.A.C.,
A.A.S.T., S.D., M.R.D., E.J.R.v.B., D.E.N., M.C.W.); Centre for Heart Lung
Innovation, St Paul’s Hospital and University of British Columbia,
Vancouver, Canada (S.S., J.L.); Laboratory Medicine Program, University Health
Network, General Hospital, Toronto, Canada (M.A.S.); Royal Infirmary of
Edinburgh, Edinburgh, Scotland (M.D., R.F., A.T., W.W., J.W.); Edinburgh
Imaging, Queen’s Medical Research Institute, Edinburgh, Scotland (G.M.,
S.I.S., T.M., E.J.R.v.B., D.E.N., M.C.W.); and Department of Medicine, Division
of Artificial Intelligence in Medicine, Cedars-Sinai Medical Center, Los
Angeles, Calif (P.J.S.)
| | - Maaz Syed
- From the BHF Centre for Cardiovascular Science, University of
Edinburgh, The Chancellor’s Building, 49 Little France Crescent,
EH16 4SB, Edinburgh, Scotland (J.K., M.S., G.M., M.J., S.I.S., C.A.C.,
A.A.S.T., S.D., M.R.D., E.J.R.v.B., D.E.N., M.C.W.); Centre for Heart Lung
Innovation, St Paul’s Hospital and University of British Columbia,
Vancouver, Canada (S.S., J.L.); Laboratory Medicine Program, University Health
Network, General Hospital, Toronto, Canada (M.A.S.); Royal Infirmary of
Edinburgh, Edinburgh, Scotland (M.D., R.F., A.T., W.W., J.W.); Edinburgh
Imaging, Queen’s Medical Research Institute, Edinburgh, Scotland (G.M.,
S.I.S., T.M., E.J.R.v.B., D.E.N., M.C.W.); and Department of Medicine, Division
of Artificial Intelligence in Medicine, Cedars-Sinai Medical Center, Los
Angeles, Calif (P.J.S.)
| | - Martin Dennis
- From the BHF Centre for Cardiovascular Science, University of
Edinburgh, The Chancellor’s Building, 49 Little France Crescent,
EH16 4SB, Edinburgh, Scotland (J.K., M.S., G.M., M.J., S.I.S., C.A.C.,
A.A.S.T., S.D., M.R.D., E.J.R.v.B., D.E.N., M.C.W.); Centre for Heart Lung
Innovation, St Paul’s Hospital and University of British Columbia,
Vancouver, Canada (S.S., J.L.); Laboratory Medicine Program, University Health
Network, General Hospital, Toronto, Canada (M.A.S.); Royal Infirmary of
Edinburgh, Edinburgh, Scotland (M.D., R.F., A.T., W.W., J.W.); Edinburgh
Imaging, Queen’s Medical Research Institute, Edinburgh, Scotland (G.M.,
S.I.S., T.M., E.J.R.v.B., D.E.N., M.C.W.); and Department of Medicine, Division
of Artificial Intelligence in Medicine, Cedars-Sinai Medical Center, Los
Angeles, Calif (P.J.S.)
| | - Gillian Mcnaught
- From the BHF Centre for Cardiovascular Science, University of
Edinburgh, The Chancellor’s Building, 49 Little France Crescent,
EH16 4SB, Edinburgh, Scotland (J.K., M.S., G.M., M.J., S.I.S., C.A.C.,
A.A.S.T., S.D., M.R.D., E.J.R.v.B., D.E.N., M.C.W.); Centre for Heart Lung
Innovation, St Paul’s Hospital and University of British Columbia,
Vancouver, Canada (S.S., J.L.); Laboratory Medicine Program, University Health
Network, General Hospital, Toronto, Canada (M.A.S.); Royal Infirmary of
Edinburgh, Edinburgh, Scotland (M.D., R.F., A.T., W.W., J.W.); Edinburgh
Imaging, Queen’s Medical Research Institute, Edinburgh, Scotland (G.M.,
S.I.S., T.M., E.J.R.v.B., D.E.N., M.C.W.); and Department of Medicine, Division
of Artificial Intelligence in Medicine, Cedars-Sinai Medical Center, Los
Angeles, Calif (P.J.S.)
| | - Maurits Jansen
- From the BHF Centre for Cardiovascular Science, University of
Edinburgh, The Chancellor’s Building, 49 Little France Crescent,
EH16 4SB, Edinburgh, Scotland (J.K., M.S., G.M., M.J., S.I.S., C.A.C.,
A.A.S.T., S.D., M.R.D., E.J.R.v.B., D.E.N., M.C.W.); Centre for Heart Lung
Innovation, St Paul’s Hospital and University of British Columbia,
Vancouver, Canada (S.S., J.L.); Laboratory Medicine Program, University Health
Network, General Hospital, Toronto, Canada (M.A.S.); Royal Infirmary of
Edinburgh, Edinburgh, Scotland (M.D., R.F., A.T., W.W., J.W.); Edinburgh
Imaging, Queen’s Medical Research Institute, Edinburgh, Scotland (G.M.,
S.I.S., T.M., E.J.R.v.B., D.E.N., M.C.W.); and Department of Medicine, Division
of Artificial Intelligence in Medicine, Cedars-Sinai Medical Center, Los
Angeles, Calif (P.J.S.)
| | - Scott I. Semple
- From the BHF Centre for Cardiovascular Science, University of
Edinburgh, The Chancellor’s Building, 49 Little France Crescent,
EH16 4SB, Edinburgh, Scotland (J.K., M.S., G.M., M.J., S.I.S., C.A.C.,
A.A.S.T., S.D., M.R.D., E.J.R.v.B., D.E.N., M.C.W.); Centre for Heart Lung
Innovation, St Paul’s Hospital and University of British Columbia,
Vancouver, Canada (S.S., J.L.); Laboratory Medicine Program, University Health
Network, General Hospital, Toronto, Canada (M.A.S.); Royal Infirmary of
Edinburgh, Edinburgh, Scotland (M.D., R.F., A.T., W.W., J.W.); Edinburgh
Imaging, Queen’s Medical Research Institute, Edinburgh, Scotland (G.M.,
S.I.S., T.M., E.J.R.v.B., D.E.N., M.C.W.); and Department of Medicine, Division
of Artificial Intelligence in Medicine, Cedars-Sinai Medical Center, Los
Angeles, Calif (P.J.S.)
| | - Carlos Alcaide-Corral
- From the BHF Centre for Cardiovascular Science, University of
Edinburgh, The Chancellor’s Building, 49 Little France Crescent,
EH16 4SB, Edinburgh, Scotland (J.K., M.S., G.M., M.J., S.I.S., C.A.C.,
A.A.S.T., S.D., M.R.D., E.J.R.v.B., D.E.N., M.C.W.); Centre for Heart Lung
Innovation, St Paul’s Hospital and University of British Columbia,
Vancouver, Canada (S.S., J.L.); Laboratory Medicine Program, University Health
Network, General Hospital, Toronto, Canada (M.A.S.); Royal Infirmary of
Edinburgh, Edinburgh, Scotland (M.D., R.F., A.T., W.W., J.W.); Edinburgh
Imaging, Queen’s Medical Research Institute, Edinburgh, Scotland (G.M.,
S.I.S., T.M., E.J.R.v.B., D.E.N., M.C.W.); and Department of Medicine, Division
of Artificial Intelligence in Medicine, Cedars-Sinai Medical Center, Los
Angeles, Calif (P.J.S.)
| | - Adriana A. S. Tavares
- From the BHF Centre for Cardiovascular Science, University of
Edinburgh, The Chancellor’s Building, 49 Little France Crescent,
EH16 4SB, Edinburgh, Scotland (J.K., M.S., G.M., M.J., S.I.S., C.A.C.,
A.A.S.T., S.D., M.R.D., E.J.R.v.B., D.E.N., M.C.W.); Centre for Heart Lung
Innovation, St Paul’s Hospital and University of British Columbia,
Vancouver, Canada (S.S., J.L.); Laboratory Medicine Program, University Health
Network, General Hospital, Toronto, Canada (M.A.S.); Royal Infirmary of
Edinburgh, Edinburgh, Scotland (M.D., R.F., A.T., W.W., J.W.); Edinburgh
Imaging, Queen’s Medical Research Institute, Edinburgh, Scotland (G.M.,
S.I.S., T.M., E.J.R.v.B., D.E.N., M.C.W.); and Department of Medicine, Division
of Artificial Intelligence in Medicine, Cedars-Sinai Medical Center, Los
Angeles, Calif (P.J.S.)
| | - Thomas MacGillivray
- From the BHF Centre for Cardiovascular Science, University of
Edinburgh, The Chancellor’s Building, 49 Little France Crescent,
EH16 4SB, Edinburgh, Scotland (J.K., M.S., G.M., M.J., S.I.S., C.A.C.,
A.A.S.T., S.D., M.R.D., E.J.R.v.B., D.E.N., M.C.W.); Centre for Heart Lung
Innovation, St Paul’s Hospital and University of British Columbia,
Vancouver, Canada (S.S., J.L.); Laboratory Medicine Program, University Health
Network, General Hospital, Toronto, Canada (M.A.S.); Royal Infirmary of
Edinburgh, Edinburgh, Scotland (M.D., R.F., A.T., W.W., J.W.); Edinburgh
Imaging, Queen’s Medical Research Institute, Edinburgh, Scotland (G.M.,
S.I.S., T.M., E.J.R.v.B., D.E.N., M.C.W.); and Department of Medicine, Division
of Artificial Intelligence in Medicine, Cedars-Sinai Medical Center, Los
Angeles, Calif (P.J.S.)
| | - Samuel Debono
- From the BHF Centre for Cardiovascular Science, University of
Edinburgh, The Chancellor’s Building, 49 Little France Crescent,
EH16 4SB, Edinburgh, Scotland (J.K., M.S., G.M., M.J., S.I.S., C.A.C.,
A.A.S.T., S.D., M.R.D., E.J.R.v.B., D.E.N., M.C.W.); Centre for Heart Lung
Innovation, St Paul’s Hospital and University of British Columbia,
Vancouver, Canada (S.S., J.L.); Laboratory Medicine Program, University Health
Network, General Hospital, Toronto, Canada (M.A.S.); Royal Infirmary of
Edinburgh, Edinburgh, Scotland (M.D., R.F., A.T., W.W., J.W.); Edinburgh
Imaging, Queen’s Medical Research Institute, Edinburgh, Scotland (G.M.,
S.I.S., T.M., E.J.R.v.B., D.E.N., M.C.W.); and Department of Medicine, Division
of Artificial Intelligence in Medicine, Cedars-Sinai Medical Center, Los
Angeles, Calif (P.J.S.)
| | - Rachael Forsythe
- From the BHF Centre for Cardiovascular Science, University of
Edinburgh, The Chancellor’s Building, 49 Little France Crescent,
EH16 4SB, Edinburgh, Scotland (J.K., M.S., G.M., M.J., S.I.S., C.A.C.,
A.A.S.T., S.D., M.R.D., E.J.R.v.B., D.E.N., M.C.W.); Centre for Heart Lung
Innovation, St Paul’s Hospital and University of British Columbia,
Vancouver, Canada (S.S., J.L.); Laboratory Medicine Program, University Health
Network, General Hospital, Toronto, Canada (M.A.S.); Royal Infirmary of
Edinburgh, Edinburgh, Scotland (M.D., R.F., A.T., W.W., J.W.); Edinburgh
Imaging, Queen’s Medical Research Institute, Edinburgh, Scotland (G.M.,
S.I.S., T.M., E.J.R.v.B., D.E.N., M.C.W.); and Department of Medicine, Division
of Artificial Intelligence in Medicine, Cedars-Sinai Medical Center, Los
Angeles, Calif (P.J.S.)
| | - Andrew Tambyraja
- From the BHF Centre for Cardiovascular Science, University of
Edinburgh, The Chancellor’s Building, 49 Little France Crescent,
EH16 4SB, Edinburgh, Scotland (J.K., M.S., G.M., M.J., S.I.S., C.A.C.,
A.A.S.T., S.D., M.R.D., E.J.R.v.B., D.E.N., M.C.W.); Centre for Heart Lung
Innovation, St Paul’s Hospital and University of British Columbia,
Vancouver, Canada (S.S., J.L.); Laboratory Medicine Program, University Health
Network, General Hospital, Toronto, Canada (M.A.S.); Royal Infirmary of
Edinburgh, Edinburgh, Scotland (M.D., R.F., A.T., W.W., J.W.); Edinburgh
Imaging, Queen’s Medical Research Institute, Edinburgh, Scotland (G.M.,
S.I.S., T.M., E.J.R.v.B., D.E.N., M.C.W.); and Department of Medicine, Division
of Artificial Intelligence in Medicine, Cedars-Sinai Medical Center, Los
Angeles, Calif (P.J.S.)
| | - Piotr J. Slomka
- From the BHF Centre for Cardiovascular Science, University of
Edinburgh, The Chancellor’s Building, 49 Little France Crescent,
EH16 4SB, Edinburgh, Scotland (J.K., M.S., G.M., M.J., S.I.S., C.A.C.,
A.A.S.T., S.D., M.R.D., E.J.R.v.B., D.E.N., M.C.W.); Centre for Heart Lung
Innovation, St Paul’s Hospital and University of British Columbia,
Vancouver, Canada (S.S., J.L.); Laboratory Medicine Program, University Health
Network, General Hospital, Toronto, Canada (M.A.S.); Royal Infirmary of
Edinburgh, Edinburgh, Scotland (M.D., R.F., A.T., W.W., J.W.); Edinburgh
Imaging, Queen’s Medical Research Institute, Edinburgh, Scotland (G.M.,
S.I.S., T.M., E.J.R.v.B., D.E.N., M.C.W.); and Department of Medicine, Division
of Artificial Intelligence in Medicine, Cedars-Sinai Medical Center, Los
Angeles, Calif (P.J.S.)
| | - Jonathon Leipsic
- From the BHF Centre for Cardiovascular Science, University of
Edinburgh, The Chancellor’s Building, 49 Little France Crescent,
EH16 4SB, Edinburgh, Scotland (J.K., M.S., G.M., M.J., S.I.S., C.A.C.,
A.A.S.T., S.D., M.R.D., E.J.R.v.B., D.E.N., M.C.W.); Centre for Heart Lung
Innovation, St Paul’s Hospital and University of British Columbia,
Vancouver, Canada (S.S., J.L.); Laboratory Medicine Program, University Health
Network, General Hospital, Toronto, Canada (M.A.S.); Royal Infirmary of
Edinburgh, Edinburgh, Scotland (M.D., R.F., A.T., W.W., J.W.); Edinburgh
Imaging, Queen’s Medical Research Institute, Edinburgh, Scotland (G.M.,
S.I.S., T.M., E.J.R.v.B., D.E.N., M.C.W.); and Department of Medicine, Division
of Artificial Intelligence in Medicine, Cedars-Sinai Medical Center, Los
Angeles, Calif (P.J.S.)
| | - Marc R. Dweck
- From the BHF Centre for Cardiovascular Science, University of
Edinburgh, The Chancellor’s Building, 49 Little France Crescent,
EH16 4SB, Edinburgh, Scotland (J.K., M.S., G.M., M.J., S.I.S., C.A.C.,
A.A.S.T., S.D., M.R.D., E.J.R.v.B., D.E.N., M.C.W.); Centre for Heart Lung
Innovation, St Paul’s Hospital and University of British Columbia,
Vancouver, Canada (S.S., J.L.); Laboratory Medicine Program, University Health
Network, General Hospital, Toronto, Canada (M.A.S.); Royal Infirmary of
Edinburgh, Edinburgh, Scotland (M.D., R.F., A.T., W.W., J.W.); Edinburgh
Imaging, Queen’s Medical Research Institute, Edinburgh, Scotland (G.M.,
S.I.S., T.M., E.J.R.v.B., D.E.N., M.C.W.); and Department of Medicine, Division
of Artificial Intelligence in Medicine, Cedars-Sinai Medical Center, Los
Angeles, Calif (P.J.S.)
| | - William Whiteley
- From the BHF Centre for Cardiovascular Science, University of
Edinburgh, The Chancellor’s Building, 49 Little France Crescent,
EH16 4SB, Edinburgh, Scotland (J.K., M.S., G.M., M.J., S.I.S., C.A.C.,
A.A.S.T., S.D., M.R.D., E.J.R.v.B., D.E.N., M.C.W.); Centre for Heart Lung
Innovation, St Paul’s Hospital and University of British Columbia,
Vancouver, Canada (S.S., J.L.); Laboratory Medicine Program, University Health
Network, General Hospital, Toronto, Canada (M.A.S.); Royal Infirmary of
Edinburgh, Edinburgh, Scotland (M.D., R.F., A.T., W.W., J.W.); Edinburgh
Imaging, Queen’s Medical Research Institute, Edinburgh, Scotland (G.M.,
S.I.S., T.M., E.J.R.v.B., D.E.N., M.C.W.); and Department of Medicine, Division
of Artificial Intelligence in Medicine, Cedars-Sinai Medical Center, Los
Angeles, Calif (P.J.S.)
| | - Joanna Wardlaw
- From the BHF Centre for Cardiovascular Science, University of
Edinburgh, The Chancellor’s Building, 49 Little France Crescent,
EH16 4SB, Edinburgh, Scotland (J.K., M.S., G.M., M.J., S.I.S., C.A.C.,
A.A.S.T., S.D., M.R.D., E.J.R.v.B., D.E.N., M.C.W.); Centre for Heart Lung
Innovation, St Paul’s Hospital and University of British Columbia,
Vancouver, Canada (S.S., J.L.); Laboratory Medicine Program, University Health
Network, General Hospital, Toronto, Canada (M.A.S.); Royal Infirmary of
Edinburgh, Edinburgh, Scotland (M.D., R.F., A.T., W.W., J.W.); Edinburgh
Imaging, Queen’s Medical Research Institute, Edinburgh, Scotland (G.M.,
S.I.S., T.M., E.J.R.v.B., D.E.N., M.C.W.); and Department of Medicine, Division
of Artificial Intelligence in Medicine, Cedars-Sinai Medical Center, Los
Angeles, Calif (P.J.S.)
| | - Edwin J. R. van Beek
- From the BHF Centre for Cardiovascular Science, University of
Edinburgh, The Chancellor’s Building, 49 Little France Crescent,
EH16 4SB, Edinburgh, Scotland (J.K., M.S., G.M., M.J., S.I.S., C.A.C.,
A.A.S.T., S.D., M.R.D., E.J.R.v.B., D.E.N., M.C.W.); Centre for Heart Lung
Innovation, St Paul’s Hospital and University of British Columbia,
Vancouver, Canada (S.S., J.L.); Laboratory Medicine Program, University Health
Network, General Hospital, Toronto, Canada (M.A.S.); Royal Infirmary of
Edinburgh, Edinburgh, Scotland (M.D., R.F., A.T., W.W., J.W.); Edinburgh
Imaging, Queen’s Medical Research Institute, Edinburgh, Scotland (G.M.,
S.I.S., T.M., E.J.R.v.B., D.E.N., M.C.W.); and Department of Medicine, Division
of Artificial Intelligence in Medicine, Cedars-Sinai Medical Center, Los
Angeles, Calif (P.J.S.)
| | - David E. Newby
- From the BHF Centre for Cardiovascular Science, University of
Edinburgh, The Chancellor’s Building, 49 Little France Crescent,
EH16 4SB, Edinburgh, Scotland (J.K., M.S., G.M., M.J., S.I.S., C.A.C.,
A.A.S.T., S.D., M.R.D., E.J.R.v.B., D.E.N., M.C.W.); Centre for Heart Lung
Innovation, St Paul’s Hospital and University of British Columbia,
Vancouver, Canada (S.S., J.L.); Laboratory Medicine Program, University Health
Network, General Hospital, Toronto, Canada (M.A.S.); Royal Infirmary of
Edinburgh, Edinburgh, Scotland (M.D., R.F., A.T., W.W., J.W.); Edinburgh
Imaging, Queen’s Medical Research Institute, Edinburgh, Scotland (G.M.,
S.I.S., T.M., E.J.R.v.B., D.E.N., M.C.W.); and Department of Medicine, Division
of Artificial Intelligence in Medicine, Cedars-Sinai Medical Center, Los
Angeles, Calif (P.J.S.)
| | - Michelle C. Williams
- From the BHF Centre for Cardiovascular Science, University of
Edinburgh, The Chancellor’s Building, 49 Little France Crescent,
EH16 4SB, Edinburgh, Scotland (J.K., M.S., G.M., M.J., S.I.S., C.A.C.,
A.A.S.T., S.D., M.R.D., E.J.R.v.B., D.E.N., M.C.W.); Centre for Heart Lung
Innovation, St Paul’s Hospital and University of British Columbia,
Vancouver, Canada (S.S., J.L.); Laboratory Medicine Program, University Health
Network, General Hospital, Toronto, Canada (M.A.S.); Royal Infirmary of
Edinburgh, Edinburgh, Scotland (M.D., R.F., A.T., W.W., J.W.); Edinburgh
Imaging, Queen’s Medical Research Institute, Edinburgh, Scotland (G.M.,
S.I.S., T.M., E.J.R.v.B., D.E.N., M.C.W.); and Department of Medicine, Division
of Artificial Intelligence in Medicine, Cedars-Sinai Medical Center, Los
Angeles, Calif (P.J.S.)
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Kurosaki Y, Kinosada M, Ikeda H, Yamashita H, Yoshida K, Chin M. Clinical features and long-term outcomes of symptomatic low-grade carotid stenosis. J Stroke Cerebrovasc Dis 2022; 31:106779. [PMID: 36179612 DOI: 10.1016/j.jstrokecerebrovasdis.2022.106779] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 09/07/2022] [Accepted: 09/08/2022] [Indexed: 11/17/2022] Open
Abstract
OBJECTIVE In symptomatic low-grade stenosis, most of the reports did not clarify the long-term outcome. This study aims to clarify the clinical features and long-term outcomes of symptomatic low-grade stenosis cases. MATERIALS AND METHODS We included 123 symptomatic patients with low-grade (<50%) carotid stenosis. The relative plaque signal intensity (rSI) and expansive remodeling rate (ERR) were measured using carotid magnetic resonance imaging (MRI). Antiplatelet therapy and treatment for atherosclerosis risk factors were administered in all cases. Carotid endarterectomy (CEA) was performed when ischemic symptoms appeared, or the percent stenosis progressed despite medical treatment. RESULTS The mean percent stenosis, rSI, and ERR on admission were 22.3, 1.70, and 2.01, respectively. The mean volume of the hyperintense plaque on carotid MRI was 641.4± 540 mm3. Sixty percent of cases involved intraplaque hemorrhage and expansive remodeling. During a mean follow-up of 52 months, recurrence of ischemic events was confirmed in 45 cases (36.6%). Of the 67 cases performed follow-up MRI, 34 cases (50%) had an increased volume of T1-hyperintense plaque. CEA or carotid artery stenting was performed in 49 cases. During a mean follow-up of 57.8 months after CEA, two cases of death (fatal intracerebral hemorrhage and asphyxia) and one case of brain stem lacunar infarction were observed, but ipsilateral ischemic events were not. CONCLUSION Most of the symptomatic patients with low-grade stenosis had both intraplaque hemorrhage and expansive remodeling and presented a high risk of recurrence and stenosis progression. CEA may have preventive effects against ischemic events in low-grade stenosis.
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Affiliation(s)
| | - Masanori Kinosada
- Department of Neurosurgery, Kurashiki Central Hospital, Okayama, Japan
| | - Hiroyuki Ikeda
- Department of Neurosurgery, Kurashiki Central Hospital, Okayama, Japan
| | - Haruki Yamashita
- Department of Neurosurgery, Kurashiki Central Hospital, Okayama, Japan
| | - Kazumichi Yoshida
- Department of Neurosurgery, Kyoto University School of Medicine, 54 Shogoin Kawahara-Cho Sakyo-ku, Kyoto 606-8507, Japan.
| | - Masaki Chin
- Department of Neurosurgery, Kurashiki Central Hospital, Okayama, Japan
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16
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Abstract
Vessel wall MR imaging (VW-MRI) has been introduced into clinical practice and applied to a variety of diseases, and its usefulness has been reported. High-resolution VW-MRI is essential in the diagnostic workup and provides more information than other routine MR imaging protocols. VW-MRI is useful in assessing lesion location, morphology, and severity. Additional information, such as vessel wall enhancement, which is useful in the differential diagnosis of atherosclerotic disease and vasculitis could be assessed by this special imaging technique. This review describes the VW-MRI technique and its clinical applications in arterial disease, venous disease, vasculitis, and leptomeningeal disease.
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17
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Mura M, Rivoire E, Dehina-Khenniche L, Weiss-Gayet M, Chazaud B, Faes C, Connes P, Long A, Rytz CL, Mury P, Delrieu L, Gouraud E, Bordet M, Schiava ND, Lermusiaux P, Arsicot M, Millon A, Pialoux V. Effectiveness of an individualized home-based physical activity program in surgery-free non-endarterectomized asymptomatic stroke patients: a study protocol for the PACAPh interventional randomized trial. Trials 2022; 23:145. [PMID: 35164816 PMCID: PMC8842739 DOI: 10.1186/s13063-022-06061-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 01/27/2022] [Indexed: 02/06/2023] Open
Abstract
Background Carotid atherosclerotic plaques remain silent until their rupture, which may lead to detrimental ischemic events such as strokes. This is due, in part, to intraplaque hemorrhages (IPH) and the resulting inflammatory processes, which may promote carotid plaque vulnerability. Currently, the benefits of carotid endarterectomy remain unclear for asymptomatic patients. Interestingly, the completion of physical activity (PA) may have beneficial effects; however, the paucity of current data warrants robust longitudinal interventions. We therefore aim to study the effects of a 6-month longitudinal personalized home-based PA program on IPH, biological, and inflammatory markers in asymptomatic stroke patients. Methods Eighty patients (≥ 18 years old) will be recruited for the Physical Activity and Carotid Atherosclerotic Plaque Hemorrhage (PACAPh) clinical trial from the Hospices Civils de Lyon. Patients will be eligible if they present with carotid stenosis ≥ 50% and are asymptomatic from any ischemic events for at least 6 months. Recruited patients will be randomized into either a PA or a control group, and assessed at baseline and after 6 months. At both time points, all patients will be assessed using magnetic resonance imaging to assess IPH, blood sampling to measure inflammatory markers and monocytic phenotyping, PA and sedentary behavior questionnaires, 6-min walking test, and maximal isometric quadricep contraction test. The randomized PA intervention will consist of reaching a daily walking step goal individually tailored to each patient. Steps will be collected using a wirelessly connected wristband. The number of steps completed by individuals in the PA group will be re-evaluated bimonthly to encourage walking habits. Discussion The PACAPh study is the first of its kind representing a feasible, easily accessible therapeutic strategy for asymptomatic stroke patients. We hypothesize that the personalized home-based PA program will reduce IPH and modulate inflammatory and biological parameters in patients presenting with carotid plaques. If the results of the PACAPh study prove to be beneficial on such health parameters, the implementation of such kind of intervention in the daily treatment of these patients would be an advantageous and cost-effective practice to adopt globally. Trial registration This study has been approved by the National Ethics Committee (IDRCB:2019-A01543-54/SI:19.06.21.40640). ClinicalTrials.gov NCT04053166
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18
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Baylam Geleri D, Watase H, Chu B, Chen L, Zhao H, Zhao X, Hatsukami TS, Yuan C. Detection of Advanced Lesions of Atherosclerosis in Carotid Arteries Using 3-Dimensional Motion-Sensitized Driven-Equilibrium Prepared Rapid Gradient Echo (3D-MERGE) Magnetic Resonance Imaging as a Screening Tool. Stroke 2021; 53:194-200. [PMID: 34587796 DOI: 10.1161/strokeaha.120.032505] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND AND PURPOSE Two-dimensional high-resolution multicontrast magnetic resonance imaging (2D-MC MRI) is currently the most reliable and reproducible noninvasive carotid vessel wall imaging technique. However, the long scan time required for 2D-MC MRI restricts its practical clinical application. Alternatively, 3-dimensional motion-sensitized driven-equilibrium prepared rapid gradient echo (3D-MERGE) vessel wall MRI can provide high isotropic resolution with extensive coverage in two minutes. In this study, we sought to prove that 3D-MERGE alone can serve as a screening tool to identify advanced carotid lesions. METHODS Two hundred twenty-seven subjects suspected of recent ischemic stroke or transient ischemic attack were imaged using 2D-MC MRI with an imaging time of 30 minutes, then with 3D-MERGE with an imaging time of 2 minutes, on 3T-MRI scanners. Two experienced reviewers interpreted plaque components using 2D-MC MRI as the reference standard and categorized plaques using a modified American Heart Association lesion classification for MRI. Plaques of American Heart Association type IV and above were classified as advanced. Arteries of American Heart Association types I to II and III were categorized as normal or with early lesions, respectively. One radiologist independently reviewed only 3D-MERGE and labeled the plaques as advanced if they had a wall thickness of >2 mm with high or low signal intensity compared with the adjacent sternocleidomastoid muscle. Sensitivity, specificity, and accuracy for 3D-MERGE were calculated. RESULTS Four hundred forty-nine arteries from 227 participants (mean age 61.2 years old, 64% male) were included in the analysis. Sensitivity, specificity, and accuracy for identification of advanced lesions on 3D-MERGE were 95.0% (95% CI, 91.8-97.2), 86.9% (95% CI, 81.4-92.0), 93.8% (95% CI, 91.1-95.8), respectively. CONCLUSIONS 3D-MERGE can accurately identify advanced carotid atherosclerotic plaques in patients suspected of stroke or transient ischemic attack. It has a more extensive coverage and higher sensitivity and specificity for advanced plaque detection with a much shorter acquisition time than 2D-MC MRI. REGISTRATION URL: https://www.clinicaltrials.gov; Unique identifier: NCT02017756.
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Affiliation(s)
- Duygu Baylam Geleri
- Department of Radiology, University of Washington, Seattle, WA. (D.B.G, B.C., C.Y.)
| | - Hiroko Watase
- Department of Surgery, University of Washington, Seattle, WA. (H.W., T.S.H.)
| | - Baocheng Chu
- Department of Radiology, University of Washington, Seattle, WA. (D.B.G, B.C., C.Y.).,BioMolecular Imaging Center, University of Washington, Seattle, WA. (B.C., C.Y.)
| | - Li Chen
- Department of Electrical and Computer Engineering, University of Washington, Seattle, WA. (L.C.)
| | - Huilin Zhao
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiaotong University Shanghai, China (H.Z.)
| | - Xihai Zhao
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China (X.Z.)
| | - Thomas S Hatsukami
- Department of Surgery, University of Washington, Seattle, WA. (H.W., T.S.H.)
| | - Chun Yuan
- Department of Radiology, University of Washington, Seattle, WA. (D.B.G, B.C., C.Y.).,BioMolecular Imaging Center, University of Washington, Seattle, WA. (B.C., C.Y.)
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19
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Saba L, Sanagala SS, Gupta SK, Koppula VK, Johri AM, Khanna NN, Mavrogeni S, Laird JR, Pareek G, Miner M, Sfikakis PP, Protogerou A, Misra DP, Agarwal V, Sharma AM, Viswanathan V, Rathore VS, Turk M, Kolluri R, Viskovic K, Cuadrado-Godia E, Kitas GD, Sharma N, Nicolaides A, Suri JS. Multimodality carotid plaque tissue characterization and classification in the artificial intelligence paradigm: a narrative review for stroke application. ANNALS OF TRANSLATIONAL MEDICINE 2021; 9:1206. [PMID: 34430647 PMCID: PMC8350643 DOI: 10.21037/atm-20-7676] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Accepted: 02/25/2021] [Indexed: 12/12/2022]
Abstract
Cardiovascular disease (CVD) is one of the leading causes of morbidity and mortality in the United States of America and globally. Carotid arterial plaque, a cause and also a marker of such CVD, can be detected by various non-invasive imaging modalities such as magnetic resonance imaging (MRI), computer tomography (CT), and ultrasound (US). Characterization and classification of carotid plaque-type in these imaging modalities, especially into symptomatic and asymptomatic plaque, helps in the planning of carotid endarterectomy or stenting. It can be challenging to characterize plaque components due to (I) partial volume effect in magnetic resonance imaging (MRI) or (II) varying Hausdorff values in plaque regions in CT, and (III) attenuation of echoes reflected by the plaque during US causing acoustic shadowing. Artificial intelligence (AI) methods have become an indispensable part of healthcare and their applications to the non-invasive imaging technologies such as MRI, CT, and the US. In this narrative review, three main types of AI models (machine learning, deep learning, and transfer learning) are analyzed when applied to MRI, CT, and the US. A link between carotid plaque characteristics and the risk of coronary artery disease is presented. With regard to characterization, we review tools and techniques that use AI models to distinguish carotid plaque types based on signal processing and feature strengths. We conclude that AI-based solutions offer an accurate and robust path for tissue characterization and classification for carotid artery plaque imaging in all three imaging modalities. Due to cost, user-friendliness, and clinical effectiveness, AI in the US has dominated the most.
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Affiliation(s)
- Luca Saba
- Department of Radiology, Azienda Ospedaliero Universitaria (AOU), Cagliari, Italy
| | - Skandha S Sanagala
- CSE Department, CMR College of Engineering & Technology, Hyderabad, India.,CSE Department, Bennett University, Greater Noida, UP, India
| | - Suneet K Gupta
- CSE Department, Bennett University, Greater Noida, UP, India
| | - Vijaya K Koppula
- CSE Department, CMR College of Engineering & Technology, Hyderabad, India
| | - Amer M Johri
- Department of Medicine, Division of Cardiology, Queen's University, Kingston, Ontario, Canada
| | - Narendra N Khanna
- Department of Cardiology, Indraprastha APOLLO Hospitals, New Delhi, India
| | - Sophie Mavrogeni
- Cardiology Clinic, Onassis Cardiac Surgery Center, Athens, Greece
| | - John R Laird
- Heart and Vascular Institute, Adventist Health St. Helena, St Helena, CA, USA
| | - Gyan Pareek
- Minimally Invasive Urology Institute, Brown University, Providence, Rhode Island, USA
| | - Martin Miner
- Men's Health Center, Miriam Hospital Providence, Rhode Island, USA
| | - Petros P Sfikakis
- Rheumatology Unit, National Kapodistrian University of Athens, Greece
| | - Athanasios Protogerou
- Department of Cardiovascular Prevention, National and Kapodistrian University of Athens, Athens, Greece
| | - Durga P Misra
- Department of Clinical Immunology and Rheumatology, SGPGIMS, Lucknow, India
| | - Vikas Agarwal
- Department of Clinical Immunology and Rheumatology, SGPGIMS, Lucknow, India
| | - Aditya M Sharma
- Division of Cardiovascular Medicine, University of Virginia, VA, USA
| | - Vijay Viswanathan
- MV Hospital for Diabetes & Professor M Viswanathan Diabetes Research Centre, Chennai, India
| | - Vijay S Rathore
- Nephrology Department, Kaiser Permanente, Sacramento, CA, USA
| | - Monika Turk
- The Hanse-Wissenschaftskolleg Institute for Advanced Study, Delmenhorst, Germany
| | | | | | | | - George D Kitas
- R & D Academic Affairs, Dudley Group NHS Foundation Trust, Dudley, UK
| | - Neeraj Sharma
- Department of Biomedical Engineering, IIT-BHU, Banaras, UP, India
| | - Andrew Nicolaides
- Vascular Screening and Diagnostic Centre, University of Nicosia, Nicosia, Cyprus
| | - Jasjit S Suri
- Stroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA, USA
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20
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Cao X, Tang Y, Pan L, Yang J, Wu Y, Geng D, Zhang J. Assessment of carotid atherosclerotic plaque using 3D motion-sensitized driven-equilibrium prepared rapid gradient echo: a comparative study. Quant Imaging Med Surg 2021; 11:2744-2755. [PMID: 34079738 DOI: 10.21037/qims-20-869] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Background 3D motion-sensitized driven-equilibrium prepared rapid gradient echo (MERGE) can characterize carotid atherosclerotic plaque morphology and composition. The present study aimed to evaluate its performance by comparing it with reference images and assessing the inter-reader agreement. Methods Eighty-four patients were prospectively recruited and scanned with 3D MERGE. Two trained magnetic resonance imaging (MRI) readers measured and calculated the maximum wall thickness (WT), maximum vessel diameter, total vessel area, lumen area, wall area, normalized wall index, plaque volume, intraplaque hemorrhage (IPH) volume, and calcification volume independently. IPH, calcification, mixed calcification, and ulceration were identified. The intraclass correlation coefficient (ICC) with 95% confidence interval (CI) was used to assess the inter-reader agreement. MERGE performance was assessed in terms of sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio, kappa value (κ), and the results of the Bland-Altman analysis and compared with reference images. Results MERGE showed excellent inter-reader agreement (All ICCs >0.90). MERGE and simultaneous non-contrast angiography and intraplaque hemorrhage (SNAP) showed excellent agreement in detecting IPH (κ=0.938) and measuring IPH volume (ICC =0.995; 95% CI: 0.991-0.997). MERGE and computed tomography angiography (CTA) showed strong consistency in detecting calcification (κ=0.814) and mixed calcification (κ=0.972), and in measuring calcification volume (ICC =0.996; 95% CI: 0.993-0.997). MERGE and digital subtraction angiography (DSA) showed relatively strong consistency in identifying ulceration (κ=0.737). Conclusions MERGE showed excellent performance in identifying and measuring IPH and calcification in carotid atherosclerotic plaques. Therefore, MERGE can be a promising imaging approach in atherosclerotic-vulnerable plaque.
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Affiliation(s)
- Xin Cao
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China.,Institute of Functional and Molecular Medical Imaging, Fudan University, Shanghai, China
| | - Ye Tang
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Lei Pan
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Jinming Yang
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Yifan Wu
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China.,Institute of Functional and Molecular Medical Imaging, Fudan University, Shanghai, China
| | - Daoying Geng
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China.,Institute of Functional and Molecular Medical Imaging, Fudan University, Shanghai, China
| | - Jun Zhang
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China.,Institute of Functional and Molecular Medical Imaging, Fudan University, Shanghai, China
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21
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Xin R, Yang D, Xu H, Han H, Li J, Miao Y, Du Z, Ding Q, Deng S, Ning Z, Shen R, Li R, Li C, Yuan C, Zhao X. Comparing Symptomatic and Asymptomatic Carotid Artery Atherosclerosis in Patients With Bilateral Carotid Vulnerable Plaques Using Magnetic Resonance Imaging. Angiology 2021; 73:104-111. [PMID: 34018407 DOI: 10.1177/00033197211012531] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
We compared plaque characteristics between symptomatic and asymptomatic sides in patients with bilateral carotid vulnerable plaques using magnetic resonance imaging (MRI). Participants (n = 67; mean age: 65.8 ± 7.7 years, 61 males) with bilateral carotid vulnerable plaques were included. Vulnerable plaques were characterized by intraplaque hemorrhage (IPH), large lipid-rich necrotic core (LRNC), or fibrous cap rupture (FCR) on MRI. Symptomatic vulnerable plaques showed greater plaque burden, LRNC volume (median: 221.4 vs 134.8 mm3, P = .003), IPH volume (median: 32.2 vs 22.5 mm3, P = .030), maximum percentage (Max%) LRNC (median: 51.3% vs 41.8%, P = .002), Max%IPH (median: 13.4% vs 9.5%, P = .022), cumulative slices of LRNC (median: 10 vs 8, P = .005), and more juxtaluminal IPH and/or thrombus (29.9% vs 6.0%, P = .001) and FCR (37.3% vs 16.4%, P = .007) than asymptomatic ones. After adjusting for plaque burden, differences in juxtaluminal IPH and/or thrombus (odds ratio [OR]: 5.49, 95% CI: 1.61-18.75, P = .007) and FCR (OR: 2.90, 95% CI: 1.16-7.24, P = .022) between bilateral sides remained statistically significant. For patients with bilateral carotid vulnerable plaques, symptomatic plaques had greater burden, more juxtaluminal IPH and/or thrombus, and FCR compared with asymptomatic ones. The differences in juxtaluminal IPH and/or thrombus and FCR between bilateral sides were independent of plaque burden.
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Affiliation(s)
- Ruijing Xin
- Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China
| | - Dandan Yang
- Center for Brain Disorders Research, Capital Medical University and Beijing Institute of Brain Disorders, Beijing, China
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, 118223Tsinghua University School of Medicine, Beijing, China
| | - Huimin Xu
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Hualu Han
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, 118223Tsinghua University School of Medicine, Beijing, China
| | - Jin Li
- Department of Radiology, The Affiliated BenQ Hospital of Nanjing Medical University, Nanjing, China
| | - Yingyu Miao
- Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China
| | - Ziwei Du
- Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China
| | - Qian Ding
- Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China
| | - Shasha Deng
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Zihan Ning
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, 118223Tsinghua University School of Medicine, Beijing, China
| | - Rui Shen
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, 118223Tsinghua University School of Medicine, Beijing, China
| | - Rui Li
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, 118223Tsinghua University School of Medicine, Beijing, China
| | - Cheng Li
- Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China
| | - Chun Yuan
- Department of Radiology, 7284University of Washington, Seattle, USA
| | - Xihai Zhao
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, 118223Tsinghua University School of Medicine, Beijing, China
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22
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Fujiwara Y, Mio M. Improvement in the contrast-to-noise ratio and quantitative measurement of T 1 and T 2* values for carotid atherosclerotic plaque using multi-echo phase-sensitive inversion recovery. Radiol Phys Technol 2021; 14:186-192. [PMID: 33942236 DOI: 10.1007/s12194-021-00619-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 04/04/2021] [Accepted: 04/26/2021] [Indexed: 10/21/2022]
Abstract
Quantitative magnetic resonance imaging is required to accurately evaluate carotid plaque vulnerability. We prospectively evaluated the potential for fast quantitative black-blood carotid vessel wall imaging using a three-dimensional (3D) multi-echo phase-sensitive inversion recovery (mPSIR) sequence. Forty-nine patients with carotid atherosclerotic plaques were examined. Two-dimensional (2D) turbo spin-echo (TSE), 3D volumetric isotropic turbo spin-echo, and 3D mPSIR imaging were performed. The contrast-to-noise ratios (CNRs) between the carotid plaque and adjacent muscle were compared for the three imaging methods. The T1 and T2* values of the carotid plaques were measured using 3D mPSIR images. These values were compared with those of symptomatic and asymptomatic plaques. For carotid plaques with a signal intensity ratio ≥ 1.55, between the carotid plaque and adjacent muscle in 2D TSE images, the CNR of the mPSIR images was significantly higher than that of the other sequences. T1 values for symptomatic and asymptomatic plaques were 544.0 ± 258.0 and 569.1 ± 301.7, respectively. T2* values for symptomatic and asymptomatic plaques were 34.0 ± 33.0 and 21.8 ± 20.3 ms, respectively. There were no significant differences in the T1 and T2* values between the symptomatic and asymptomatic plaques. 3D mPSIR improves the CNR of T1-weighted images for carotid plaques and the adjacent muscle while simultaneously providing the T1 and T2* values of the carotid plaque. This improved CNR may be useful for assessing the vulnerability of carotid plaques.
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Affiliation(s)
- Yasuhiro Fujiwara
- Department of Medical Image Sciences, Faculty of Life Sciences, Kumamoto University, 4-24-1 Kuhonji, Chuo-ku, Kumamoto, 862-0976, Japan.
| | - Motohira Mio
- Department of Radiology, Fukuoka Chikushi Hospital, Fukuoka, Japan
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23
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Normalized wall index, intraplaque hemorrhage and ulceration of carotid plaques correlate with the severity of ischemic stroke. Atherosclerosis 2020; 315:138-144. [PMID: 33183741 DOI: 10.1016/j.atherosclerosis.2020.10.896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Revised: 09/20/2020] [Accepted: 10/28/2020] [Indexed: 11/23/2022]
Abstract
BACKGROUND AND AIMS Carotid atherosclerosis is considered an important cause of ischemic stroke. Tthis study aimed to explore the relationship between plaque features and the severity of stroke, and to identify plaque risk factors for the assessment of the severity of ischemic stroke. METHODS Symptomatic patients with carotid atherosclerotic plaques were prospectively recruited and underwent high-resolution vessel wall magnetic resonance imaging (VW-MRI). Two trained MRI readers independently identified intraplaque hemorrhage (IPH), calcification (CA), surface CA, deep CA, and ulceration. They measured and calculated the maximum vessel diameter (Max VD), maximum wall thickness (Max WT), total vessel area, lumen area, normalized wall index (NWI), plaque volume, IPH volume, IPH proportion, CA volume, and CA proportion. Patients were divided into two groups according to their National Institutes of Health Stroke Scale (NIHSS) scores (NIHSS ≤1 vs. NIHSS >1). Clinical characteristics and carotid plaque features were compared using the Mann-Whitney U test or Chi-square test as appropriate. Odds ratio (OR) and corresponding 95% confidence interval (CI) of plaque features to distinguish patients with NIHSS >1 were calculated. Spearman's rank correlations or Pearson correlations were determined for plaque features and NIHSS scores. RESULTS Of the 97 included patients, 34 (35.05%) with NIHSS >1 had significantly greater NWI (p < 0.05), larger IPH volume (p < 0.01), and greater IPH proportion (p < 0.01), and higher prevalence of IPH (OR, 5.654; 95%CI, 2.272-14.070; p < 0.01) and ulceration (OR, 2.891; 95%CI, 1.090-7.667; p = 0.033) than patients with NIHSS ≤1. Max WT (r = 0.24, p = 0.018), NWI (r = 0.22, p = 0.032), IPH (r = 0.27, p = 0.007), IPH volume (r = 0.35, p < 0.01), IPH proportion (r = 0.28, p = 0.005), and ulceration (r = 0.35, p < 0.01) had positive correlations with NIHSS scores. CONCLUSIONS NWI, IPH, and ulceration of carotid atherosclerotic plaque based on high-resolution VW-MRI may be useful indicators for assessing the severity of ischemic stroke in patients with atherosclerosis. NIHSS score is related to max WT, NWI, IPH, IPH volume, IPH proportion, and ulceration.
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24
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Mura M, Della Schiava N, Long A, Chirico EN, Pialoux V, Millon A. Carotid intraplaque haemorrhage: pathogenesis, histological classification, imaging methods and clinical value. ANNALS OF TRANSLATIONAL MEDICINE 2020; 8:1273. [PMID: 33178805 PMCID: PMC7607119 DOI: 10.21037/atm-20-1974] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Vulnerable carotid atherosclerotic plaques are characterised by several risk factors, such as inflammation, neovascularization and intraplaque haemorrhage (IPH). Vulnerable plaques can lead to ischemic events such as stroke. Many studies reported a relationship between IPH, plaque rupture, and ischemic stroke. Histology is the gold standard to evaluate IPH, but it required carotid endarterectomy (CEA) surgery to collect the tissue sample. In this context, several imaging methods can be used as a non-invasive way to evaluate plaque vulnerability and detect IPH. Most imaging studies showed that IPH is associated with plaque vulnerability and stroke, with magnetic resonance imaging (MRI) being the most sensitive and specific to detect IPH as a predictor of ischemic events. These conclusions are however still debated because of the limited number of patients included in these studies; further studies are required to better assess risks associated with different IPH stages. Moreover, IPH is implicated in plaque vulnerability with other risk factors which need to be considered to predict ischemic risk. In addition, MRI sequences standardization is required to compare results from different studies and agree on biomarkers that need to be considered to predict plaque rupture. In these circumstances, IPH detection by MRI could be an efficient clinical method to predict stroke. The goal of this review article is to first describe the pathophysiological process responsible for IPH, its histological detection in carotid plaques and its correlation with plaque rupture. The second part will discuss the benefits and limitations of imaging the carotid plaque, and finally the clinical interest of imaging IPH to predict plaque rupture, focusing on MRI-IPH.
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Affiliation(s)
- Mathilde Mura
- Univ Lyon, University Claude Bernard Lyon 1, Interuniversity Laboratory of Human Movement Biology EA7424, Lyon, France
| | - Nellie Della Schiava
- Department of Vascular and Endovascular Surgery, Groupement Hospitalier Est, Louis Pradel Hospital, Hospices Civils de Lyon, Lyon, France.,Institut National des Sciences Appliquées Lyon, Laboratoire de Génie Electrique et Ferroélectricité EA 682, Villeurbanne, France
| | - Anne Long
- Univ Lyon, University Claude Bernard Lyon 1, Interuniversity Laboratory of Human Movement Biology EA7424, Lyon, France.,Departement of Internal Medicine and Vascular Medicine, Groupement Hospitalier Edouard Herriot, Hospices Civils de Lyon, Lyon, France
| | - Erica N Chirico
- Department of Biomedical Sciences, Cooper Medical School of Rowan University, Camden, NJ, USA
| | - Vincent Pialoux
- Univ Lyon, University Claude Bernard Lyon 1, Interuniversity Laboratory of Human Movement Biology EA7424, Lyon, France.,Institut Universitaire de France, Paris, France
| | - Antoine Millon
- Department of Vascular and Endovascular Surgery, Groupement Hospitalier Est, Louis Pradel Hospital, Hospices Civils de Lyon, Lyon, France.,Univ Lyon, University Claude Bernard Lyon 1, CarMeN Laboratory, INSERM U1060, Bron, France
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25
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Aizaz M, Moonen RPM, van der Pol JAJ, Prieto C, Botnar RM, Kooi ME. PET/MRI of atherosclerosis. Cardiovasc Diagn Ther 2020; 10:1120-1139. [PMID: 32968664 DOI: 10.21037/cdt.2020.02.09] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Myocardial infarction and stroke are the most prevalent global causes of death. Each year 15 million people worldwide die due to myocardial infarction or stroke. Rupture of a vulnerable atherosclerotic plaque is the main underlying cause of stroke and myocardial infarction. Key features of a vulnerable plaque are inflammation, a large lipid-rich necrotic core (LRNC) with a thin or ruptured overlying fibrous cap, and intraplaque hemorrhage (IPH). Noninvasive imaging of these features could have a role in risk stratification of myocardial infarction and stroke and can potentially be utilized for treatment guidance and monitoring. The recent development of hybrid PET/MRI combining the superior soft tissue contrast of MRI with the opportunity to visualize specific plaque features using various radioactive tracers, paves the way for comprehensive plaque imaging. In this review, the use of hybrid PET/MRI for atherosclerotic plaque imaging in carotid and coronary arteries is discussed. The pros and cons of different hybrid PET/MRI systems are reviewed. The challenges in the development of PET/MRI and potential solutions are described. An overview of PET and MRI acquisition techniques for imaging of atherosclerosis including motion correction is provided, followed by a summary of vessel wall imaging PET/MRI studies in patients with carotid and coronary artery disease. Finally, the future of imaging of atherosclerosis with PET/MRI is discussed.
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Affiliation(s)
- Mueez Aizaz
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, The Netherlands.,CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
| | - Rik P M Moonen
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, The Netherlands.,CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
| | - Jochem A J van der Pol
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.,Escuela de Ingenieria, Pontificia Universidad Catolica de Chile, Santiago, Chile
| | - René M Botnar
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.,Escuela de Ingenieria, Pontificia Universidad Catolica de Chile, Santiago, Chile
| | - M Eline Kooi
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, The Netherlands.,CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
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26
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Yang WJ, Abrigo J, Soo YOY, Wong S, Wong KS, Leung TWH, Chu WCW, Chen XY. Regression of Plaque Enhancement Within Symptomatic Middle Cerebral Artery Atherosclerosis: A High-Resolution MRI Study. Front Neurol 2020; 11:755. [PMID: 32849214 PMCID: PMC7399098 DOI: 10.3389/fneur.2020.00755] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Accepted: 06/18/2020] [Indexed: 01/10/2023] Open
Abstract
Objective: Contrast enhancement is a vital feature of the intracranial atherosclerotic plaque on high-resolution magnetic resonance imaging (HRMRI), but its clinical significance is still unclear. We aimed to quantitatively assess plaque enhancement patterns in the middle cerebral artery (MCA) atherosclerotic plaque. Methods: We conducted a cross-sectional study by prospectively recruiting stroke or transient ischemic attack patients with >30% of MCA stenosis of either side. All patients underwent contrast-enhanced HRMRI scans. Enrolled patients were classified into acute phase (<4 weeks), subacute phase (4-12 weeks) and chronic phase (>12 weeks) groups based on the time interval from stroke onset to imaging scan. Plaque enhancement index was calculated for each MCA lesion at the maximal narrowing site. Results: We identified a total of 89 MCA plaques [53 (60%) symptomatic and 36 (40%) asymptomatic; 57 (64%) acute, 18 (20%) subacute and 14 (16%) chronic] in 58 patients on HRMRI. Among the acute lesions, symptomatic plaques had a significantly stronger plaque enhancement than asymptomatic plaques (symptomatic vs. asymptomatic: 38.9 ± 18.2 vs. 18.2 ± 16.2, p < 0.001). Among the symptomatic lesions, plaque enhancement diminished with increasing time after stroke onset (38.9 ± 18.2, 22.0 ± 22.8, and 5.0 ± 10.1 for acute, subacute, and chronic phase, respectively; p = 0.001). Conclusion: Plaque enhancement in the acute atherosclerotic plaque is closely related to recent ischemic events. In symptomatic atherosclerosis, plaque enhancement regresses over time after ischemic stroke, which may offer the potential to monitor the plaque activity in intracranial atherosclerosis using HRMRI.
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Affiliation(s)
- Wen-Jie Yang
- The Russell H. Morgan Department of Radiology and Radiological Sciences, The Johns Hopkins University, Baltimore, MD, United States
| | - Jill Abrigo
- Department of Imaging and Interventional Radiology, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, China
| | - Yannie Oi-Yan Soo
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, China
| | - Simon Wong
- Department of Imaging and Interventional Radiology, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, China
| | - Ka-Sing Wong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, China
| | - Thomas Wai-Hong Leung
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, China
| | - Winnie Chiu-Wing Chu
- Department of Imaging and Interventional Radiology, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, China
| | - Xiang-Yan Chen
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Kowloon, China
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27
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Fu Q, Wang X, Wu T, Wang R, Wu X, Wang Y, Feng Z. Carotid atherosclerosis biomarkers in cardiovascular diseases prevention: A systematic review and bibliometric analysis. Eur J Radiol 2020; 129:109133. [PMID: 32610187 DOI: 10.1016/j.ejrad.2020.109133] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2019] [Revised: 02/09/2020] [Accepted: 06/12/2020] [Indexed: 10/24/2022]
Abstract
PURPOSE While carotid atherosclerosis (CA) biomarkers are valuable surrogates for cardiovascular events, their inadequate utility is highlighted by clinical practice. We performed an interdisciplinary systematic review and bibliometric analysis to identify the knowledge gaps and offer directions for future research. METHODS We applied a comprehensive search strategy to construct a representative dataset of the bibliographic records of CA from 1997 to 2018. A total of 31,793 retrieved articles and 407,473 cited references were included in the analysis. The co-word network and co-citation network were derived to describe the major disciplines and topics of CA research. Milestones detected by burst analysis were reviewed to delineate the evolutionary patterns and emerging trends of research on CA biomarkers. RESULTS CA is a multidisciplinary field of study which could be divided into 3 communities: the primary prevention of CVD, the secondary prevention of CVD and imaging techniques to characterize carotid atherosclerosis. The evolution of a CA biomarker may go through 3 stages: the conceptualization stage, the validation stage and the reclassification stage. Measurements that include different CA plaque features, rather than separately, have shown greater value for cardiovascular risk or clinical decision-making. CONCLUSIONS Although wide variability exists in the evolutionary stages of CA biomarkers, combined evaluation of CA plaque imaging features shows potential value to improve risk prediction and clinical decision-making for CVD prevention.
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Affiliation(s)
- Qian Fu
- School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan 430030, China
| | - Xiaojun Wang
- School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan 430030, China
| | - Tailai Wu
- School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan 430030, China
| | - Ruoxi Wang
- School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan 430030, China
| | - Xiang Wu
- School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan 430030, China
| | - Yang Wang
- School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan 430030, China
| | - Zhanchun Feng
- School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan 430030, China.
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28
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Wang Y, Liu X, Haraldsson H, Zhu C, Ballweber M, Gasper W, Hatsukami T, Saloner D. Quantitative measurement of atheroma burden: reproducibility in serial studies of atherosclerotic femoral arteries. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2020; 33:855-863. [PMID: 32297164 DOI: 10.1007/s10334-020-00843-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Revised: 03/18/2020] [Accepted: 04/03/2020] [Indexed: 11/30/2022]
Abstract
OBJECTIVES This study aims to evaluate the reproducibility of measures of plaque morphology in serially acquired black-blood MRI of untreated atherosclerotic femoral arteries. MATERIALS AND METHODS MR studies was obtained from 42 timepoints, on 12 patients with known femoral artery atherosclerosis. Images with a 3D isotropic FLASH with DANTE-prepared black blood contrast (DASH) at a 3-T scanner were acquired at baseline, within 1 week, and at 1 month. Six of the patients were scanned additionally at 6 months. Inter-scan and inter-observer variations of arterial area/volume measurements were evaluated. RESULTS Measurement of vessel area, lumen area, wall area and wall volume showed inter-scan intraclass correlation coefficients (ICC) ranging from 0.92 to 0.97 for 3 scans, 0.91-0.97 for 4 scans, and inter-observer ICCs of 0.89-0.96. Among 3 scans, the coefficients of variance (CV) for the vessel area, lumen area, wall area and wall volume were 4.1%, 6.5%, 7.5%, and 4.4%. CVs among 4 scans ranged from 4.4% to 7.9%, and interobserver CVs ranged from 6.1% to 11.8% for the different area/volume measurements. CONCLUSION DASH MRI is useful for quantifying atherosclerotic vessel area and volume of femoral arteries with low variability among serial repeated scans and between observers.
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Affiliation(s)
- Yuting Wang
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, No. 2006 Xiyuan Avenue, Chengdu, 611731, China. .,Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.
| | - Xinke Liu
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.,Department of Interventional Neuroradiology, Beijing Neurosurgical Institute and Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Henrik Haraldsson
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Chengcheng Zhu
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Megan Ballweber
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Warren Gasper
- Division of Vascular and Endovascular Surgery, University of California, San Francisco, CA, USA
| | - Thomas Hatsukami
- Department of Surgery, University of Washington, Seattle, WA, USA
| | - David Saloner
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
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29
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Evans NR, Tarkin JM, Le EP, Sriranjan RS, Corovic A, Warburton EA, Rudd JH. Integrated cardiovascular assessment of atherosclerosis using PET/MRI. Br J Radiol 2020; 93:20190921. [PMID: 32238077 DOI: 10.1259/bjr.20190921] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
Atherosclerosis is a systemic inflammatory disease typified by the development of lipid-rich atheroma (plaques), the rupture of which are a major cause of myocardial infarction and stroke. Anatomical evaluation of the plaque considering only the degree of luminal stenosis overlooks features associated with vulnerable plaques, such as high-risk morphological features or pathophysiology, and hence risks missing vulnerable or ruptured non-stenotic plaques. Consequently, there has been interest in identifying these markers of vulnerability using either MRI for morphology, or positron emission tomography (PET) for physiological processes involved in atherogenesis. The advent of hybrid PET/MRI scanners offers the potential to combine the strengths of PET and MRI to allow comprehensive assessment of the atherosclerotic plaque. This review will discuss the principles and technical aspects of hybrid PET/MRI assessment of atherosclerosis, and consider how combining the complementary modalities of PET and MRI has already furthered our understanding of atherogenesis, advanced drug development, and how it may hold potential for clinical application.
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Affiliation(s)
- Nicholas R Evans
- Department of Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Jason M Tarkin
- Division of Cardiovascular Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Elizabeth Pv Le
- Division of Cardiovascular Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Rouchelle S Sriranjan
- Division of Cardiovascular Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Andrej Corovic
- Division of Cardiovascular Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Elizabeth A Warburton
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
| | - James Hf Rudd
- Division of Cardiovascular Medicine, University of Cambridge, Cambridge, United Kingdom
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30
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Wüst RCI, Calcagno C, Daal MRR, Nederveen AJ, Coolen BF, Strijkers GJ. Emerging Magnetic Resonance Imaging Techniques for Atherosclerosis Imaging. Arterioscler Thromb Vasc Biol 2020; 39:841-849. [PMID: 30917678 DOI: 10.1161/atvbaha.118.311756] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Atherosclerosis is a prevalent disease affecting a large portion of the population at one point in their lives. There is an unmet need for noninvasive diagnostics to identify and characterize at-risk plaque phenotypes noninvasively and in vivo, to improve the stratification of patients with cardiovascular disease, and for treatment evaluation. Magnetic resonance imaging is uniquely positioned to address these diagnostic needs. However, currently available magnetic resonance imaging methods for vessel wall imaging lack sufficient discriminative and predictive power to guide the individual patient needs. To address this challenge, physicists are pushing the boundaries of magnetic resonance atherosclerosis imaging to increase image resolution, provide improved quantitative evaluation of plaque constituents, and obtain readouts of disease activity such as inflammation. Here, we review some of these important developments, with specific focus on emerging applications using high-field magnetic resonance imaging, the use of quantitative relaxation parameter mapping for improved plaque characterization, and novel 19F magnetic resonance imaging technology to image plaque inflammation.
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Affiliation(s)
- Rob C I Wüst
- From the Biomedical Engineering and Physics (R.C.I.W., M.R.R.D., B.F.C., G.J.S.), Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, the Netherlands
| | - Claudia Calcagno
- Department of Radiology, Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York (C.C., G.J.S.)
| | - Mariah R R Daal
- From the Biomedical Engineering and Physics (R.C.I.W., M.R.R.D., B.F.C., G.J.S.), Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, the Netherlands
| | - Aart J Nederveen
- Radiology and Nuclear Medicine (A.J.N.), Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, the Netherlands
| | - Bram F Coolen
- From the Biomedical Engineering and Physics (R.C.I.W., M.R.R.D., B.F.C., G.J.S.), Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, the Netherlands
| | - Gustav J Strijkers
- From the Biomedical Engineering and Physics (R.C.I.W., M.R.R.D., B.F.C., G.J.S.), Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, the Netherlands.,Department of Radiology, Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York (C.C., G.J.S.)
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31
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Murata K, Murata N, Chu B, Watase H, Hippe DS, Balu N, Sun J, Zhao X, Hatsukami TS, Yuan C. Characterization of Carotid Atherosclerotic Plaques Using 3-Dimensional MERGE Magnetic Resonance Imaging and Correlation With Stroke Risk Factors. Stroke 2020; 51:475-480. [PMID: 31902332 DOI: 10.1161/strokeaha.119.027779] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background and Purpose- High-resolution magnetic resonance imaging is capable of characterizing carotid atherosclerotic plaque morphology and composition. Most reported carotid plaque imaging techniques are 2-dimensional (2D) based with limited longitudinal coverage of ≈30 mm, which may be insufficient for complete visualization of extracranial carotid atheroma. A 3D black-blood imaging technique, motion-sensitized driven equilibrium prepared rapid gradient echo technique (3D-MERGE) can provide larger coverage. We sought to use 3D-MERGE to investigate carotid atherosclerosis plaque distribution and to analyze their correlation with clinical information and stroke risk factors. Methods- From 5 hospitals in China, 97 subjects suspected of recent stroke or transient ischemic attack were imaged with 3D-MERGE within 2 weeks of symptoms using 3T magnetic resonance imaging. Images were analyzed by 2 reviewers. Plaque length was calculated and categorized as plaques within, partially outside, or completely outside of typical 2D magnetic resonance imaging coverage. Associations between plaque features and clinical information, stroke risk factors were assessed. Results- Ninety-seven subjects with 194 carotid arteries (70 men and 27 women, mean age 60 years) were analyzed. Of the 136 plaques identified, 68 (50%) were within, 46 (33.8%) were partially outside, and 22 (16.2%) were completely outside of 2D magnetic resonance imaging coverage. Total plaque length was significantly positively associated with male sex (P<0.001), hypertension (P=0.011), and history of smoking (P<0.001). Hypertensive subjects were more likely to have at least one plaque completely outside the 2D magnetic resonance imaging coverage than nonhypertensive subjects (P=0.007). Conclusions- The 3D-MERGE allows for the identification of substantially more carotid plaques than 2D black-blood techniques. The extent and distribution of plaque, identified by the larger coverage afforded by 3D-MERGE, were found to correlate significantly with male sex and risk factors that are common among patients with stroke, including hypertension and history of cigarette smoking.
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Affiliation(s)
- Kiyoko Murata
- From the Department of Radiology (K.M., N.M., B.C., D.S.H., N.B., J.S., C.Y.), University of Washington, Seattle.,Department of Neurology, Toho University Omori Medical center, Tokyo, Japan (K.M.)
| | - Nozomu Murata
- From the Department of Radiology (K.M., N.M., B.C., D.S.H., N.B., J.S., C.Y.), University of Washington, Seattle.,Department of Radiology, Toho University Ohashi Medical Center, Tokyo, Japan (N.M.)
| | - Baocheng Chu
- From the Department of Radiology (K.M., N.M., B.C., D.S.H., N.B., J.S., C.Y.), University of Washington, Seattle
| | - Hiroko Watase
- Department of Surgery (H.W., T.S.H.), University of Washington, Seattle
| | - Daniel S Hippe
- From the Department of Radiology (K.M., N.M., B.C., D.S.H., N.B., J.S., C.Y.), University of Washington, Seattle
| | - Niranjan Balu
- From the Department of Radiology (K.M., N.M., B.C., D.S.H., N.B., J.S., C.Y.), University of Washington, Seattle
| | - Jie Sun
- From the Department of Radiology (K.M., N.M., B.C., D.S.H., N.B., J.S., C.Y.), University of Washington, Seattle
| | - Xihai Zhao
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China (X.Z.)
| | | | - Chun Yuan
- From the Department of Radiology (K.M., N.M., B.C., D.S.H., N.B., J.S., C.Y.), University of Washington, Seattle
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Wei H, Zhang M, Li Y, Zhao X, Canton G, Sun J, Xu D, Zhou Z, Chen S, Ferguson MS, Hatsukami TS, Li R, Yuan C. Evaluation of 3D multi-contrast carotid vessel wall MRI: a comparative study. Quant Imaging Med Surg 2020; 10:269-282. [PMID: 31956548 DOI: 10.21037/qims.2019.09.11] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
Background Conventional reference multi-contrast black-blood (BB) MRI can be used for measuring luminal stenosis severity and plaque components, and its performance has been validated by intra- and inter-reader reproducibility test and histology. Recently, a set of 3D multi-contrast BB sequences have been developed, but its accuracy and reliability have not been well investigated. In this study, we evaluated the performance of 3D multi-contrast MRI (3D-MERGE, T2-VISTA, and SNAP) by comparing it with reference multi-contrast vessel wall MRI and assessing the inter-reader reproducibility. Methods In total, 27 patients were recruited in this study. Twenty-six participants underwent reference and 3D multi-contrast imaging in a 3.0T MR scanner. One participant underwent carotid endarterectomy (CEA) after 3D MR imaging. Two trained reviewers interpreted reference and 3D datasets. Lumen area (LA), wall area (WA), normalized wall index (NWI), maximum wall thickness (MaxWT), and mean wall thickness (MWT) were measured, and the presence of lipid-rich necrotic core (LRNC), intra-plaque hemorrhage (IPH) and calcification (CA) were identified. Inter-reader reproducibility of 3D interpretation was assessed. Results 3D imaging provided comparable measurements with reference imaging in LA (43.81±25.74 vs. 43.35±24.66 mm2) and MaxWT (1.65±1.33 vs. 1.62±1.10 mm), with a lower NWI (0.40±0.15 vs. 0.43±0.11), WA (29.40±21.92 vs. 30.64±16.17 mm2) and MWT (1.09±0.69 vs. 1.14±0.47), and showed good agreement for identification of LRNC (κ=0.66, 95% CI: 0.30-1.00) and CA (κ=0.69, 95% CI: 0.42-0.97), and excellent agreement for IPH (κ=1.00, 95% CI: 1.00-1.00). Inter-reader agreement of 3D analysis was good (LRNC, κ=0.87, 95% CI: 0.61-1.00; CA, κ=0.66, 95% CI: 0.36-0.96; IPH, κ=1.00, 95% CI: 1.00-1.00). Conclusions 3D multi-contrast vessel wall imaging provides comparable performance in morphological measurements and identification of carotid plaque components as reference multi-contrast MRI, with good inter-reader reproducibility.
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Affiliation(s)
- Hanyu Wei
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China
| | - Miaoqi Zhang
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China
| | - Yunduo Li
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China
| | - Xihai Zhao
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China
| | - Gador Canton
- Department of Radiology, University of Washington, Seattle, WA, USA
| | - Jie Sun
- Department of Radiology, University of Washington, Seattle, WA, USA
| | - Dongxiang Xu
- Department of Radiology, University of Washington, Seattle, WA, USA
| | - Zechen Zhou
- Philips Research North America, Cambridge, MA, USA
| | - Shuo Chen
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China
| | | | | | - Rui Li
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China
| | - Chun Yuan
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China.,Department of Radiology, University of Washington, Seattle, WA, USA
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Gavrilova NE, Zhatkina MV, Metelskaya VA, Rudenko BA, Drapkina OM. Assessment methods and possibilities of instrumental diagnosis of subclinical atherosclerosis of coronary arteries. КАРДИОВАСКУЛЯРНАЯ ТЕРАПИЯ И ПРОФИЛАКТИКА 2019. [DOI: 10.15829/1728-8800-2019-6-136-141] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Affiliation(s)
| | - M. V. Zhatkina
- National Medical Research Center for Preventive Medicine
| | | | - B. A. Rudenko
- National Medical Research Center for Preventive Medicine
| | - O. M. Drapkina
- National Medical Research Center for Preventive Medicine
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34
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Wang Q, Tang D, Wang L, Canton G, Wu Z, Hatsukami TS, Billiar KL, Yuan C. Combining morphological and biomechanical factors for optimal carotid plaque progression prediction: An MRI-based follow-up study using 3D thin-layer models. Int J Cardiol 2019; 293:266-271. [PMID: 31301863 DOI: 10.1016/j.ijcard.2019.07.005] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2019] [Revised: 05/24/2019] [Accepted: 07/02/2019] [Indexed: 11/24/2022]
Abstract
Plaque progression prediction is of fundamental significance to cardiovascular research and disease diagnosis, prevention, and treatment. Magnetic resonance image (MRI) data of carotid atherosclerotic plaques were acquired from 20 patients with consent obtained. 3D thin-layer models were constructed to calculate plaque stress and strain. Data for ten morphological and biomechanical risk factors were extracted for analysis. Wall thickness increase (WTI), plaque burden increase (PBI) and plaque area increase (PAI) were chosen as three measures for plaque progression. Generalized linear mixed models (GLMM) with 5-fold cross-validation strategy were used to calculate prediction accuracy and identify optimal predictor. The optimal predictor for PBI was the combination of lumen area (LA), plaque area (PA), lipid percent (LP), wall thickness (WT), maximum plaque wall stress (MPWS) and maximum plaque wall strain (MPWSn) with prediction accuracy = 1.4146 (area under the receiver operating characteristic curve (AUC) value is 0.7158), while PA, plaque burden (PB), WT, LP, minimum cap thickness, MPWS and MPWSn was the best for WTI (accuracy = 1.3140, AUC = 0.6552), and a combination of PA, PB, WT, MPWS, MPWSn and average plaque wall strain (APWSn) was the best for PAI with prediction accuracy = 1.3025 (AUC = 0.6657). The combinational predictors improved prediction accuracy by 9.95%, 4.01% and 1.96% over the best single predictors for PAI, PBI and WTI (AUC values improved by 9.78%, 9.45%, and 2.14%), respectively. This suggests that combining both morphological and biomechanical risk factors could lead to better patient screening strategies.
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Affiliation(s)
- Qingyu Wang
- School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China
| | - Dalin Tang
- School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China; Mathematical Sciences Department, Worcester Polytechnic Institute, Worcester, MA 01609, USA.
| | - Liang Wang
- School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China.
| | - Gador Canton
- Department of Mechanical Engineering, University of Washington, Seattle, WA 98195, USA.
| | - Zheyang Wu
- Mathematical Sciences Department, Worcester Polytechnic Institute, Worcester, MA 01609, USA.
| | - Thomas S Hatsukami
- Division of Vascular Surgery, University of Washington, Seattle, WA 98195, USA.
| | - Kristen L Billiar
- Biomedical Engineering Department, Worcester Polytechnic Institute, Worcester, MA 01609, USA.
| | - Chun Yuan
- Department of Radiology, University of Washington, Seattle, WA 98195, USA.
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Liu Z, Bai Z, Huang C, Huang M, Huang L, Xu D, Zhang H, Yuan C, Luo J. Interoperator Reproducibility of Carotid Elastography for Identification of Vulnerable Atherosclerotic Plaques. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2019; 66:505-516. [PMID: 30575532 DOI: 10.1109/tuffc.2018.2888479] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Ultrasound-based carotid elastography has been developed to evaluate the vulnerability of carotid atherosclerotic plaques. The aim of this study was to investigate the in vivo interoperator reproducibility of carotid elastography for the identification of vulnerable plaques, with high-resolution magnetic resonance imaging (MRI) as reference. Ultrasound radio-frequency data of 45 carotid arteries (including 53 plaques) from 32 volunteers were acquired separately by two experienced operators in the longitudinal view and then were used to estimate the interframe axial strain rate (ASR) with a two-step optical flow method. The maximum 99th percentile of absolute ASR of all plaques in a carotid artery was used as the elastographic index. MRI scanning was also performed on each volunteer to identify the vulnerable plaque. The results showed no systematic bias in the Bland-Altman plot and an intraclass correlation coefficient of 0.66 between the two operators. In addition, no statistical significance was found between the receiver operating characteristic (ROC) curves from the two operators ( ), and their areas under the ROC curves were 0.83 and 0.77, respectively. Using the mean measurements of the two operators as the classification criterion, a sensitivity of 71.4%, a specificity of 87.1%, and an accuracy of 82.2% were obtained with a cutoff value of 1.37 [Formula: see text]. This study validates the interoperator reproducibility of ultrasound-based carotid elastography for identifying vulnerable carotid plaques.
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36
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Bonanno L, Marino S, Morabito R, Barbalace G, Sestito A, Testagrossa B, Acri G. Evaluation of US and MRI techniques for carotid stenosis: a novel phantom approach. Radiol Med 2018; 124:368-374. [PMID: 30542910 DOI: 10.1007/s11547-018-0971-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2017] [Accepted: 12/05/2018] [Indexed: 11/26/2022]
Abstract
Carotid atherosclerosis is very important in the pathogenesis of cerebral ischemia. Ultrasonography (US) and magnetic resonance imaging (MRI) are the predominant noninvasive techniques capable to identify the presence and stage of intra-plaque hemorrage. In this work, we propose a novel dedicated phantom that can be used for both US and MRI scanners to evaluate carotid atherosclerotic lesions. The phantom consists of a polymethyl metacrylate (PMMA) diagonally crossed by a PMMA hollow cylinder simulating a blood vessel. To simulate a stenosis, we inserted a plastic hollow tube inside the cylinder. Quantitative image analysis, based on accuracy measurements, was performed on two US and two MRI scanners. The accuracy measurements have highlighted the use of the 3.0 T MRI scanner to characterize the vessel stenosis. However, no significant difference between US and MRI techniques was found in Fisher exact test and inter-rater agreement. The concordance correlation coefficient showed a moderate agreement between some methods. Agreement between 3.0 T and other methods results poor, and this could be due to the fact that the 3.0 T has a better resolution compared to a US and MR 1.5 T. These methods seem to have similar efficacies for the evaluation of vessel stenosis, legitimizing the use of the developed phantom as a versatile and reproducible instrument that could be used during quality controls programs.
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Affiliation(s)
- Lilla Bonanno
- IRCCS Centro Neurolesi "Bonino-Pulejo", Messina, Italy
| | - Silvia Marino
- Department of BIOMORF, University of Messina, Messina, Italy
- IRCCS Centro Neurolesi "Bonino-Pulejo", Messina, Italy
| | - Rosa Morabito
- IRCCS Centro Neurolesi "Bonino-Pulejo", Messina, Italy
- Biomedical Department of Internal and Specialistic Medicine, University of Palermo, Palermo, Italy
| | | | | | | | - Giuseppe Acri
- Department of BIOMORF, University of Messina, Messina, Italy.
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Ota H, Tamura H, Itabashi R, Yazawa Y, Nakamura Y, Hisamatsu K, Takamatsu M, Endo H, Niizuma K, Enomoto Y, Nagasaka T, Kajita K, Watanabe M, Yoshimura S, Yuan C. Quantitative characterization of carotid plaque components using MR apparent diffusion coefficients and longitudinal relaxation rates at 3T: A comparison with histology. J Magn Reson Imaging 2018; 48:1657-1667. [DOI: 10.1002/jmri.26216] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2018] [Accepted: 05/22/2018] [Indexed: 11/11/2022] Open
Affiliation(s)
- Hideki Ota
- Department of Diagnostic Radiology; Tohoku University Hospital; Miyagi Japan
| | - Hajime Tamura
- Division of Medical Physics; Tohoku University Graduate School of Medicine; Miyagi Japan
| | - Ryo Itabashi
- Department of Stroke Neurology; Kohnan Hospital; Miyagi Japan
| | - Yukako Yazawa
- Department of Stroke Neurology; Kohnan Hospital; Miyagi Japan
| | - Yasuhiro Nakamura
- Division of Pathology, Faculty of Medicine; Tohoku Medical and Pharmaceutical University, Miyagi, Japan; Miyagi Japan
| | - Kenji Hisamatsu
- Pathology Division; Gifu University Hospital; Gifu Japan
- Department of Tumor Pathology; Gifu University Graduate School of Medicine; Gifu Japan
| | - Manabu Takamatsu
- Department of Pathology; The Cancer Institute Hospital, Japanese Foundation for Cancer Research; Tokyo Japan
| | - Hidenori Endo
- Department of Neurosurgery; Tohoku University Graduate School of Medicine; Miyagi Japan
| | - Kuniyasu Niizuma
- Department of Neurosurgery; Tohoku University Graduate School of Medicine; Miyagi Japan
| | - Yukiko Enomoto
- Department of Neurosurgery; Gifu University Graduate School of Medicine; Gifu Japan
| | - Tatsuo Nagasaka
- Department of Radiological Technology; Tohoku University Hospital; Miyagi Japan
| | - Kimihiro Kajita
- Department of Radiology service; Gifu University Hospital; Gifu Japan
| | - Mika Watanabe
- Department of Pathology; Tohoku University Hospital; Miyagi Japan
| | | | - Chun Yuan
- Department of Radiology; University of Washington; Seattle Washington USA
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Affiliation(s)
- Ying Wang
- Department of Nuclear Medicine, First Hospital of China Medical University, Shenyang, Liaoning, China.,Department of Radiology, Massachusetts General Hospital, Boston, MA
| | - Michael T Osborne
- Department of Radiology, Massachusetts General Hospital, Boston, MA.,Cardiology Division, Massachusetts General Hospital, Boston, MA
| | - Brian Tung
- Department of Radiology, Massachusetts General Hospital, Boston, MA
| | - Ming Li
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
| | - Yaming Li
- Department of Nuclear Medicine, First Hospital of China Medical University, Shenyang, Liaoning, China
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39
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Pereira T, Betriu A, Alves R. Non-invasive imaging techniques and assessment of carotid vasa vasorum neovascularization: Promises and pitfalls. Trends Cardiovasc Med 2018; 29:71-80. [PMID: 29970286 DOI: 10.1016/j.tcm.2018.06.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/24/2018] [Revised: 06/12/2018] [Accepted: 06/14/2018] [Indexed: 12/17/2022]
Abstract
Carotid adventitia vasa vasorum neovascularization (VVn) is associated with the initial stages of arteriosclerosis and with the formation of unstable plaque. However, techniques to accurately quantify that neovascularization in a standard, fast, non-invasive, and efficient way are still lacking. The development of such techniques holds the promise of enabling wide, inexpensive, and safe screening programs that could stratify patients and help in personalized preventive cardiovascular medicine. In this paper, we review the recent scientific literature pertaining to imaging techniques that could set the stage for the development of standard methods for quantitative assessment of atherosclerotic plaque and carotid VVn. We present and discuss the alternative imaging techniques being used in clinical practice and we review the computational developments that are contributing to speed up image analysis and interpretation. We conclude that one of the greatest upcoming challenges will be the use of machine learning techniques to develop automated methods that assist in the interpretation of images to stratify patients according to their risk.
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Affiliation(s)
- T Pereira
- Institute for Biomedical Research in Lleida Dr. Pifarré Foundation, Catalonia, Spain; Departament de Ciències Mèdiques Bàsiques, University of Lleida, Catalonia, Spain.
| | - A Betriu
- Unit for the Detection and Treatment of Atherothrombotic Diseases, Hospital Universitari Arnau de Vilanova de Lleida, Catalonia, Spain; Vascular and Renal Translational Research Group - IRBLleida, Catalonia, Spain
| | - R Alves
- Institute for Biomedical Research in Lleida Dr. Pifarré Foundation, Catalonia, Spain; Departament de Ciències Mèdiques Bàsiques, University of Lleida, Catalonia, Spain
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40
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Khosa F, Clough RE, Wang X, Madhuranthakam AJ, Greenman RL. The potential role of IDEAL MRI for identification of lipids and hemorrhage in carotid artery plaques. Magn Reson Imaging 2018; 49:25-31. [DOI: 10.1016/j.mri.2017.12.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2017] [Accepted: 12/03/2017] [Indexed: 02/06/2023]
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41
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Fujiwara Y, Maruyama H, Toyomaru K, Nishizaka Y, Fukamatsu M. Quantitative T 1 and T 2* carotid atherosclerotic plaque imaging using a three-dimensional multi-echo phase-sensitive inversion recovery sequence: a feasibility study. Radiol Phys Technol 2018; 11:156-164. [PMID: 29512056 DOI: 10.1007/s12194-018-0449-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2017] [Revised: 03/01/2018] [Accepted: 03/02/2018] [Indexed: 10/17/2022]
Abstract
Magnetic resonance imaging (MRI) is widely used to detect carotid atherosclerotic plaques. Although it is important to evaluate vulnerable carotid plaques containing lipids and intra-plaque hemorrhages (IPHs) using T1-weighted images, the image contrast changes depending on the imaging settings. Moreover, to distinguish between a thrombus and a hemorrhage, it is useful to evaluate the iron content of the plaque using both T1-weighted and T2*-weighted images. Therefore, a quantitative evaluation of carotid atherosclerotic plaques using T1 and T2* values may be necessary for the accurate evaluation of plaque components. The purpose of this study was to determine whether the multi-echo phase-sensitive inversion recovery (mPSIR) sequence can improve T1 contrast while simultaneously providing accurate T1 and T2* values of an IPH. T1 and T2* values measured using mPSIR were compared to values from conventional methods in phantom and in vivo studies. In the phantom study, the T1 and T2* values estimated using mPSIR were linearly correlated with those of conventional methods. In the in vivo study, mPSIR demonstrated higher T1 contrast between the IPH phantom and sternocleidomastoid muscle than the conventional method. Moreover, the T1 and T2* values of the blood vessel wall and sternocleidomastoid muscle estimated using mPSIR were correlated with values measured by conventional methods and with values reported previously. The mPSIR sequence improved T1 contrast while simultaneously providing accurate T1 and T2* values of the neck region. Although further study is required to evaluate the clinical utility, mPSIR may improve carotid atherosclerotic plaque detection and provide detailed information about plaque components.
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Affiliation(s)
- Yasuhiro Fujiwara
- Department of Medical Imaging, Faculty of Life Sciences, Kumamoto University, 4-24-1 Kuhonji, Chuo-ku, Kumamoto, 862-0976, Japan.
| | - Hirotoshi Maruyama
- Radiological Center, National Hospital Organization Kumamoto Saisyunsou Hospital, Kumamoto, Japan
| | - Kanako Toyomaru
- Course of Radiological Science, School of Health Sciences, Kumamoto University, Kumamoto, Japan
| | - Yuri Nishizaka
- Course of Radiological Science, School of Health Sciences, Kumamoto University, Kumamoto, Japan
| | - Masahiro Fukamatsu
- Radiological Center, National Hospital Organization Kumamoto Medical Center, Kumamoto, Japan
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42
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Watson JDB, Grasu B, Menon R, Pensy R, Crawford RS, Shin T. Novel, non-gadolinium-enhanced magnetic resonance imaging technique of pedal artery aneurysms. JOURNAL OF VASCULAR SURGERY CASES INNOVATIONS AND TECHNIQUES 2018; 3:87-89. [PMID: 29349385 PMCID: PMC5757774 DOI: 10.1016/j.jvscit.2016.12.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/22/2016] [Accepted: 12/05/2016] [Indexed: 11/16/2022]
Abstract
Non-gadolinium-enhanced magnetic resonance angiography (nMRA) is a noninvasive, contrast-free imaging modality used for visualizing pedal arterial anatomy. We report application of the nMRA technique for detailed arterial imaging in a patient with dorsalis pedis aneurysm. Compared with digital subtraction angiography, we demonstrate that nMRA provides sufficient arterial detail needed to develop a complex operative plan before vascular intervention without risk of contrast agent or ionizing radiation exposure.
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Affiliation(s)
- J Devin B Watson
- Division of Vascular Surgery, Department of Surgery, University of Maryland Medical Center, Baltimore, Md
| | - Beatrice Grasu
- Department of Orthopaedics, Union Memorial Hospital, Baltimore, Md
| | - Rajiv Menon
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland Medical Center, Baltimore, Md
| | - Raymond Pensy
- Division of Orthopaedic Traumatology, Department of Orthopaedics, University of Maryland Medical Center, Baltimore, Md
| | - Robert S Crawford
- Division of Vascular Surgery, Department of Surgery, University of Maryland Medical Center, Baltimore, Md
| | - Taehoon Shin
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland Medical Center, Baltimore, Md
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43
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Chinese specialist consensus on imaging diagnosis of intracranial arterial dissection. Chin Neurosurg J 2017. [DOI: 10.1186/s41016-017-0095-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
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44
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Coolen BF, Calcagno C, van Ooij P, Fayad ZA, Strijkers GJ, Nederveen AJ. Vessel wall characterization using quantitative MRI: what's in a number? MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2017; 31:201-222. [PMID: 28808823 PMCID: PMC5813061 DOI: 10.1007/s10334-017-0644-x] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/07/2017] [Revised: 07/04/2017] [Accepted: 07/18/2017] [Indexed: 12/15/2022]
Abstract
The past decade has witnessed the rapid development of new MRI technology for vessel wall imaging. Today, with advances in MRI hardware and pulse sequences, quantitative MRI of the vessel wall represents a real alternative to conventional qualitative imaging, which is hindered by significant intra- and inter-observer variability. Quantitative MRI can measure several important morphological and functional characteristics of the vessel wall. This review provides a detailed introduction to novel quantitative MRI methods for measuring vessel wall dimensions, plaque composition and permeability, endothelial shear stress and wall stiffness. Together, these methods show the versatility of non-invasive quantitative MRI for probing vascular disease at several stages. These quantitative MRI biomarkers can play an important role in the context of both treatment response monitoring and risk prediction. Given the rapid developments in scan acceleration techniques and novel image reconstruction, we foresee the possibility of integrating the acquisition of multiple quantitative vessel wall parameters within a single scan session.
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Affiliation(s)
- Bram F Coolen
- Department of Biomedical Engineering and Physics, Academic Medical Center, PO BOX 22660, 1100 DD, Amsterdam, The Netherlands. .,Department of Radiology, Academic Medical Center, Amsterdam, The Netherlands.
| | - Claudia Calcagno
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Pim van Ooij
- Department of Radiology, Academic Medical Center, Amsterdam, The Netherlands
| | - Zahi A Fayad
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Gustav J Strijkers
- Department of Biomedical Engineering and Physics, Academic Medical Center, PO BOX 22660, 1100 DD, Amsterdam, The Netherlands
| | - Aart J Nederveen
- Department of Radiology, Academic Medical Center, Amsterdam, The Netherlands
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45
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Li B, Li H, Kong H, Dong L, Zhang J, Fang J. Compressed sensing based simultaneous black- and gray-blood carotid vessel wall MR imaging. Magn Reson Imaging 2017; 38:214-223. [DOI: 10.1016/j.mri.2017.01.013] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2016] [Revised: 01/17/2017] [Accepted: 01/17/2017] [Indexed: 10/20/2022]
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46
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Huang C, He Q, Huang M, Huang L, Zhao X, Yuan C, Luo J. Non-Invasive Identification of Vulnerable Atherosclerotic Plaques Using Texture Analysis in Ultrasound Carotid Elastography: An In Vivo Feasibility Study Validated by Magnetic Resonance Imaging. ULTRASOUND IN MEDICINE & BIOLOGY 2017; 43:817-830. [PMID: 28153351 DOI: 10.1016/j.ultrasmedbio.2016.12.003] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2016] [Revised: 11/04/2016] [Accepted: 12/08/2016] [Indexed: 06/06/2023]
Abstract
The aims of this study were to quantify the textural information of strain rate images in ultrasound carotid elastography and evaluate the feasibility of using the textural features in discriminating stable and vulnerable plaques with magnetic resonance imaging as an in vivo reference. Ultrasound radiofrequency data were acquired in 80 carotid plaques from 52 patients, mainly in the longitudinal imaging view, and axial strain rate images were estimated with an ultrasound carotid elastography technique based on an optical flow algorithm. Four textural features of strain rate images-contrast, homogeneity, correlation and angular second moment-were derived based on the gray-level co-occurrence matrix in plaque regions to quantify the deformation distribution pattern. Conventional elastographic indices based on the magnitude of the absolute strain rate, such as the maximum, mean, median, standard deviation and 99th percentile of the axial strain rate, were also obtained for comparison. Composition measurement with magnetic resonance imaging identified 30 plaques as vulnerable and the other 50 as stable. The four textural features, as well as the magnitude of strain rate images, significantly differed between the two groups of plaques. The best performing features for plaque classification were found to be the contrast and 99th percentile of the absolute strain rate, with a comparative area under the receiver operating characteristic curve of 0.81; a slightly higher maximum accuracy of plaque classification can be achieved by the textural feature of contrast (83.8% vs. 81.3%). The results indicate that the use of texture analysis in plaque classification is feasible and that larger local deformations and higher level of complexity in deformation patterns (associated with the elastic or stiffness heterogeneity of plaque tissues) are more likely to occur in vulnerable plaques.
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Affiliation(s)
- Chengwu Huang
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China; Center for Biomedical Imaging Research, Tsinghua University, Beijing, China
| | - Qiong He
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China; Center for Biomedical Imaging Research, Tsinghua University, Beijing, China
| | - Manwei Huang
- Department of Sonography, China Meitan General Hospital, Beijing, China
| | - Lingyun Huang
- Clinical Sites Research Program, Philips Research China, Shanghai, China
| | - Xihai Zhao
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China; Center for Biomedical Imaging Research, Tsinghua University, Beijing, China
| | - Chun Yuan
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China; Center for Biomedical Imaging Research, Tsinghua University, Beijing, China; Department of Radiology, University of Washington, Seattle, Washington, USA
| | - Jianwen Luo
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China; Center for Biomedical Imaging Research, Tsinghua University, Beijing, China.
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Kurosaki Y, Yoshida K, Fukuda H, Handa A, Chin M, Yamagata S. Asymptomatic Carotid T1-High-Intense Plaque as a Risk Factor for a Subsequent Cerebrovascular Ischemic Event. Cerebrovasc Dis 2017; 43:250-256. [DOI: 10.1159/000455973] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2016] [Accepted: 01/10/2017] [Indexed: 01/06/2023] Open
Abstract
Background: Intraplaque hemorrhage, detected as a high-signal intensity on carotid MRI, is also strongly associated with ischemic events in symptomatic patients. However, in asymptomatic patients, the relationship of the T1-high intense plaque and the subsequent stroke is not clear. The aim of this study is to test the hypothesis that asymptomatic carotid T1-high intense plaque is a risk factor for a subsequent cerebrovascular ischemic event. Methods: Of the 1,353 consecutive patients, who underwent head and carotid MRI as part of their annual medical check-up, the imaging quality of 13 was poor and 150 did not present for follow-up examination, thus leaving 1,190 subjects for evaluation. Of the 1,190 patients, 96 patients had findings of high-signal intensity on carotid MRI and 1,094 patients did not. Cerebrovascular events were retrospectively evaluated. Results: During a mean follow-up period of 53 months, 4 patients with high-signal intensities on carotid MRI (4%) and 3 with no findings (0.3%) had a cerebrovascular ischemic event, with the occurrences significantly higher in the high-signal-intensity group. (p < 0.01) Cox regression analysis indicated that the presence of the high-intense plaque on carotid MRI (hazard ratio [HR] 4.2; 95% CI 1.0-17.1; p = 0.04), age (HR 1.1; 95% CI 1.0-1.2; p = 0.003), and diabetes mellitus (HR 7.2; 95% CI 1.8-27.4; p = 0.004) were associated with the occurrence of subsequent ischemic cerebrovascular events. Conclusions: Asymptomatic carotid T1-high-intense plaque might be a potential high-risk factor for a subsequent cerebrovascular ischemic event.
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Liem MI, Kennedy F, Bonati LH, van der Lugt A, Coolen BF, Nederveen AJ, Jager HR, Brown MM, Nederkoorn PJ. Investigations of Carotid Stenosis to Identify Vulnerable Atherosclerotic Plaque and Determine Individual Stroke Risk. Circ J 2017; 81:1246-1253. [DOI: 10.1253/circj.cj-16-1284] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
| | - Fiona Kennedy
- UCL Stroke Research Centre, Institute of Neurology, University College London
| | | | | | | | | | - Hans R. Jager
- UCL Stroke Research Centre, Institute of Neurology, University College London
| | - Martin M. Brown
- UCL Stroke Research Centre, Institute of Neurology, University College London
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49
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Hingwala DR, Chandrasekhakan K, Thomas B, Sylaja PN, Unnikrishnan M, Kapilamoorthy TR. Atherosclerotic Carotid Plaques: Multimodality Imaging with Contrast-enhanced Ultrasound, Computed Tomography, and Magnetic Resonance Imaging. Ann Indian Acad Neurol 2017; 20:378-386. [PMID: 29184341 PMCID: PMC5682742 DOI: 10.4103/aian.aian_122_17] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
Introduction The imaging of carotid plaques has undergone a paradigm shift increasing importance being given to plaque characterization. Patients with "vulnerable" plaques are more prone to develop future neurovascular events. Purpose The purpose of this study is to analyze the role of multimodality imaging techniques in the assessment of carotid atherosclerotic plaques. Materials and Methods Twenty-six patients were prospectively enrolled in the study. Patients underwent multidetector computed tomography (CT) angiography, ultrasound, contrast-enhanced ultrasound, and high-resolution magnetic resonance imaging (MRI) of the carotid arteries with special emphasis on the carotid bifurcation. Results The mean age of patients was 65.41 years. Twenty-one were males. Plaque neovascularization was seen in 10 of the 18 plaques studied (55.56%). Based on the predominant components of the plaque, plaques were characterized as lipid (3), lipid with recent hemorrhage (1), fibrous (7), fibrofatty (4), fibrofatty with some hemorrhagic components (3), and recent hemorrhage (2). Conclusions Together, contrast-enhanced ultrasound, CT, and MRI provide complete information about the plaque characteristics.
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Affiliation(s)
- Divyata R Hingwala
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India
| | - Kesavadas Chandrasekhakan
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India
| | - Bejoy Thomas
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India
| | - P N Sylaja
- Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India
| | - M Unnikrishnan
- Department of Cardiovascular and Thoracic Surgery, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India
| | - T R Kapilamoorthy
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India
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50
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Zhu J, Bornstedt A, Merkle N, Liu N, Rottbauer W, Ma G, Rasche V. T2-prepared segmented 3D-gradient-echo for fast T2-weighted high-resolution three-dimensional imaging of the carotid artery wall at 3T: a feasibility study. Biomed Eng Online 2016; 15:165. [PMID: 28155713 PMCID: PMC5259811 DOI: 10.1186/s12938-016-0276-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/29/2023] Open
Abstract
BACKGROUND The multi-contrast assessment of the carotid artery wall has become an important diagnostic tool for the characterization of atherosclerotic plaque and vessel wall thickening. For providing the required T1-, T2-, and proton density weighted contrast, multi-slice turbo spin echo (TSE) techniques are normally applied. The straightforward extension of the TSE techniques to volumetric imaging of large sections of the carotid arteries is limited by the resulting long acquisition times. Where the acquisition of a T1-weighted contrast can be accelerated by applying a T1-weighted fast gradient echo technique, acceleration of the T2-weighted contrast is not as straightforward. METHODS In this work, the combination of a T2 preparation and a conventional fast gradient echo technique (T2P-3DGE) was evaluated for rapid acquisition of a T2-weighted image contrast. Acquisition parameters were optimized in an initial in vitro study in direct comparison to the conventional T2-weighted TSE (T2W-3DTSE) technique. Subsequently, the T2P-3DGE technique was evaluated in vivo. RESULTS In direct comparison, the T2P-3DGE sequence provided similar T2 contrast as the respective T2W-3DTSE sequence. After correction of an observed intensity offset, most likely caused by the additional T1-weighting of the T2P-3DGE sequence, no significant difference between the two T2-weighted sequences were observed in phantom data. The good correlation of the image contrast between the two sequences was confirmed in the initial in-vivo study, proving a potential reduction of the scan time for T2P-3DGE to 25% of the respective T2W-3DTSE technique. CONCLUSION The in vitro as well as the in vivo results clearly indicate the potential of the T2P-3DGE technique for providing similar T2 image contrast as in the conventional techniques. Thereby, the acquisition times could be substantially reduced to about 25% of the respective 3D-TSE technique.
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Affiliation(s)
- Jian Zhu
- Department of Cardiology, Zhongda Hospital, Southeast University, Nanjing, China.,Department of Internal Medicine II, University Hospital of Ulm, Ulm, Germany
| | - Axel Bornstedt
- Department of Internal Medicine II, University Hospital of Ulm, Ulm, Germany
| | - Nico Merkle
- Department of Internal Medicine II, University Hospital of Ulm, Ulm, Germany
| | - Naifeng Liu
- Department of Cardiology, Zhongda Hospital, Southeast University, Nanjing, China
| | - Wolfgang Rottbauer
- Department of Internal Medicine II, University Hospital of Ulm, Ulm, Germany
| | - Genshan Ma
- Department of Cardiology, Zhongda Hospital, Southeast University, Nanjing, China.
| | - Volker Rasche
- Department of Internal Medicine II, University Hospital of Ulm, Ulm, Germany.
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