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Globa MV, Derkach BV. Modern approaches to ultrasonographic assessment of carotid plaque in terms of its potential instability. WIADOMOSCI LEKARSKIE (WARSAW, POLAND : 1960) 2024; 77:919-925. [PMID: 39008577 DOI: 10.36740/wlek202405106] [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: 07/17/2024]
Abstract
OBJECTIVE Aim: To identify potentially adverse characteristics of atherosclerotic carotid plaque in terms of stroke risk. PATIENTS AND METHODS Materials and Methods: The study is based on the analysis of US data obtained from 96 patients aged 47 to 84 years diagnosed with carotid stenosis. The patients were divided into 2 groups depending on the presence or absence of ischemic events. Examination methods: clinical, duplex US, brain MRI, statistical. In addition to the standard US criteria for the evaluation of carotid stenoses, superb microvascular imaging (SMI) and shear wave elastography (SWE) are used. RESULTS Results: Statistically significant association of the following characteristics of plaques with the presence of ipsilateral ischemia focus was established: maximum thickness (p = 0,04), presence of microvascularization according to SMI data (p = 0,02), degree of carotid stenosis (statistically significant in the right carotid circulation [p = 0,04]), stiffness of the plaque according to SWE data (significantly in the right carotid circulation [p = 0,001]), type of plaque echogenicity according to Gray-Weale-Geroulakos classification (on the right carotid artery; p = 0,04). CONCLUSION Conclusions: The presence of microvascularization according to SMI data and the low stiffness of the plaque according to SWE data can characterize the potential instability of the carotid plaque. These criteria should be added to the traditional US assessment of carotid plaques.
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Affiliation(s)
- Maryna V Globa
- SHUPYK NATIONAL HEALTHCARE UNIVERSITY OF UKRAINE, KYIV, UKRAINE
| | - Borys V Derkach
- SHUPYK NATIONAL HEALTHCARE UNIVERSITY OF UKRAINE, KYIV, UKRAINE
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Zeng P, Zhang Q, Liang X, Zhang M, Luo D, Chen Z. Progress of Ultrasound Techniques in the Evaluation of Carotid Vulnerable Plaque Neovascularization. Cerebrovasc Dis 2023; 53:479-487. [PMID: 37812915 DOI: 10.1159/000534372] [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: 04/29/2023] [Accepted: 09/25/2023] [Indexed: 10/11/2023] Open
Abstract
BACKGROUND The rupture and detachment of unstable plaques in the carotid artery can cause embolism in the cerebral artery, leading to acute cerebrovascular events. Intraplaque neovascularization (IPN) is a very important contributor to carotid plaque instability, and its evolution plays a key role in determining the outcome of vulnerable plaques. Ultrasound techniques, represented by contrast-enhanced ultrasound (CEUS) and superb microvascular imaging (SMI), are reported to be non-invasive, rapid, and effective techniques for the semi-quantitative or quantitative evaluation for IPN. Although ultrasound techniques have been widely applied in the detection of carotid plaque stability, it has been limited owing to the lack of unified IPN quantitative standards. SUMMARY This review summarizes the application and semi-quantitative/quantitative diagnostic standards of ultrasound techniques in evaluating IPN and looks forward to the prospects of the future research. With the development of novel techniques like artificial intelligence, ultrasound will offer appropriate selections for achieving more accuracy diagnosis. KEY MESSAGES A large number of studies have used CEUS and SMI to detect IPN and perform semi-quantitative grading to predict the occurrence of diseases such as stroke and to accurately assess drug efficacy based on rating changes. These studies have made great progress at this stage, but more accurate and intelligent quantitative imaging methods should become the future development goal.
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Affiliation(s)
- Penghui Zeng
- Institution of Medical Imaging, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, China
- Institution of Medical Imaging, University of South China, Hengyang, China
- Medical Imaging Centre, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, China
| | - Qing Zhang
- Institution of Medical Imaging, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, China
- Institution of Medical Imaging, University of South China, Hengyang, China
| | - Xiaowen Liang
- Institution of Medical Imaging, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, China
- Institution of Medical Imaging, University of South China, Hengyang, China
| | - Min Zhang
- Department of Ultrasound, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, China
| | - Dan Luo
- Department of Ultrasound, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, China
| | - Zhiyi Chen
- Institution of Medical Imaging, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, China
- Institution of Medical Imaging, University of South China, Hengyang, China
- Medical Imaging Centre, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, China
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Aghabaglou F, Ainechi A, Abramson H, Curry E, Kaovasia TP, Kamal S, Acord M, Mahapatra S, Pustavoitau A, Smith B, Azadi J, Son JK, Suk I, Theodore N, Tyler BM, Manbachi A. Ultrasound monitoring of microcirculation: An original study from the laboratory bench to the clinic. Microcirculation 2022; 29:e12770. [PMID: 35611457 PMCID: PMC9786257 DOI: 10.1111/micc.12770] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 04/08/2022] [Accepted: 05/20/2022] [Indexed: 12/30/2022]
Abstract
OBJECTIVE Monitoring microcirculation and visualizing microvasculature are critical for providing diagnosis to medical professionals and guiding clinical interventions. Ultrasound provides a medium for monitoring and visualization; however, there are challenges due to the complex microscale geometry of the vasculature and difficulties associated with quantifying perfusion. Here, we studied established and state-of-the-art ultrasonic modalities (using six probes) to compare their detection of slow flow in small microvasculature. METHODS Five ultrasonic modalities were studied: grayscale, color Doppler, power Doppler, superb microvascular imaging (SMI), and microflow imaging (MFI), using six linear probes across two ultrasound scanners. Image readability was blindly scored by radiologists and quantified for evaluation. Vasculature visualization was investigated both in vitro (resolution and flow characterization) and in vivo (fingertip microvasculature detection). RESULTS Superb Microvascular Imaging (SMI) and Micro Flow Imaging (MFI) modalities provided superior images when compared with conventional ultrasound imaging modalities both in vitro and in vivo. The choice of probe played a significant difference in detectability. The slowest flow detected (in the lab) was 0.1885 ml/s and small microvasculature of the fingertip were visualized. CONCLUSIONS Our data demonstrated that SMI and MFI used with vascular probes operating at higher frequencies provided resolutions acceptable for microvasculature visualization, paving the path for future development of ultrasound devices for microcirculation monitoring.
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Affiliation(s)
- Fariba Aghabaglou
- Department of Neurosurgery, School of MedicineJohns Hopkins UniversityBaltimoreMarylandUSA,Department of Biomedical EngineeringJohns Hopkins UniversityBaltimoreMarylandUSA,HEPIUS Innovation Laboratory, School of MedicineJohns Hopkins UniversityBaltimoreMarylandUSA
| | - Ana Ainechi
- Department of Neurosurgery, School of MedicineJohns Hopkins UniversityBaltimoreMarylandUSA,HEPIUS Innovation Laboratory, School of MedicineJohns Hopkins UniversityBaltimoreMarylandUSA
| | - Haley Abramson
- Department of Biomedical EngineeringJohns Hopkins UniversityBaltimoreMarylandUSA,HEPIUS Innovation Laboratory, School of MedicineJohns Hopkins UniversityBaltimoreMarylandUSA
| | - Eli Curry
- Department of Neurosurgery, School of MedicineJohns Hopkins UniversityBaltimoreMarylandUSA,Department of Biomedical EngineeringJohns Hopkins UniversityBaltimoreMarylandUSA,HEPIUS Innovation Laboratory, School of MedicineJohns Hopkins UniversityBaltimoreMarylandUSA
| | - Tarana Parvez Kaovasia
- Department of Biomedical EngineeringJohns Hopkins UniversityBaltimoreMarylandUSA,HEPIUS Innovation Laboratory, School of MedicineJohns Hopkins UniversityBaltimoreMarylandUSA
| | - Serene Kamal
- HEPIUS Innovation Laboratory, School of MedicineJohns Hopkins UniversityBaltimoreMarylandUSA,Department of Electrical and Computer EngineeringJohns Hopkins UniversityBaltimoreMarylandUSA
| | - Molly Acord
- Department of Biomedical EngineeringJohns Hopkins UniversityBaltimoreMarylandUSA,HEPIUS Innovation Laboratory, School of MedicineJohns Hopkins UniversityBaltimoreMarylandUSA
| | - Smruti Mahapatra
- Department of Biomedical EngineeringJohns Hopkins UniversityBaltimoreMarylandUSA,HEPIUS Innovation Laboratory, School of MedicineJohns Hopkins UniversityBaltimoreMarylandUSA
| | - Aliaksei Pustavoitau
- Department of Anesthesiology and Critical Care, School of MedicineJohns Hopkins UniversityBaltimoreMarylandUSA
| | - Beth Smith
- Department of Radiology and Radiological Science, School of MedicineJohns Hopkins UniversityBaltimoreMarylandUSA
| | - Javad Azadi
- Department of Radiology and Radiological Science, School of MedicineJohns Hopkins UniversityBaltimoreMarylandUSA
| | - Jennifer K. Son
- Department of Radiology and Radiological Science, School of MedicineJohns Hopkins UniversityBaltimoreMarylandUSA
| | - Ian Suk
- Department of Neurosurgery, School of MedicineJohns Hopkins UniversityBaltimoreMarylandUSA
| | - Nicholas Theodore
- Department of Neurosurgery, School of MedicineJohns Hopkins UniversityBaltimoreMarylandUSA,HEPIUS Innovation Laboratory, School of MedicineJohns Hopkins UniversityBaltimoreMarylandUSA
| | - Betty M. Tyler
- Department of Neurosurgery, School of MedicineJohns Hopkins UniversityBaltimoreMarylandUSA,HEPIUS Innovation Laboratory, School of MedicineJohns Hopkins UniversityBaltimoreMarylandUSA
| | - Amir Manbachi
- Department of Neurosurgery, School of MedicineJohns Hopkins UniversityBaltimoreMarylandUSA,Department of Biomedical EngineeringJohns Hopkins UniversityBaltimoreMarylandUSA,HEPIUS Innovation Laboratory, School of MedicineJohns Hopkins UniversityBaltimoreMarylandUSA,Department of Electrical and Computer EngineeringJohns Hopkins UniversityBaltimoreMarylandUSA,Department of Mechanical EngineeringJohns Hopkins UniversityBaltimoreMarylandUSA
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Song Y, Xing H, Zhang Z, Felix LO. Detection of Carotid Atherosclerotic Intraplaque Neovascularization Using Superb Microvascular Imaging: A Meta-Analysis. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2021; 40:2629-2638. [PMID: 33587302 DOI: 10.1002/jum.15652] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Revised: 12/31/2020] [Accepted: 01/20/2021] [Indexed: 06/12/2023]
Abstract
OBJECTIVES Although superb microvascular imaging (SMI) (Toshiba/Canon, Tokyo, Japan) has enabled routine characterization of intraplaque neovascularization (IPN) features in patients with carotid stenosis, no reports have been published on the multicenter and large sample size research in this aspect. The efficacy of SMI in detecting carotid IPN has not been concluded. This study aimed to assess the efficacy of SMI comparing with contrast-enhanced carotid ultrasonography (CEUS) in the detection of carotid IPN or pathologic evaluations of IPN correlated with a history of stroke or transient ischemic attack (TIA). METHODS Web of Science, Cochrane Library, PubMed, Embase, and Scopus were searched up to August 2020 to identify peer-reviewed human studies on the diagnostic accuracy of SMI in detecting IPN. For the selected study, the correlation coefficient R and Kappa index between SMI and CEUS in detecting IPN were calculated. The correlation coefficient R between SMI in identifying IPN and pathologic evaluations of IPN and the odds ratio of IPN detected by SMI and history of stroke or TIA were also extracted. The subgroup analysis was performed to indicate the source of heterogeneity. RESULTS Our search identified 11 reports enrolling a total of 605 carotid stenosis patients. Carotid IPN detected by SMI was significantly correlated with which detected by CEUS (R, 0.89; 95% CI, 0.80-0.94; P = .00, and Kappa index, 0.73; 95% CI, 0.67-0.80; P = .00). Notably, a significant correlation was observed in SMI in detecting IPN and pathologic evaluations of IPN (R, 0.52; 95% CI, 0.40-0.62; P = .00). The odds ratio of IPN detected by SMI and history of stroke or TIA was pooled summary with statistical significance (OR, 3.33; 95% CI, 1.78-6.23; P = .00). In subgroup analysis, lower heterogeneity was associated with the degree of carotid stenosis, patients from which country, and types of equipment. CONCLUSIONS SMI and CEUS display an excellent agreement in detecting carotid IPN. IPN detected by SMI shows high consistency with pathologic evaluations of IPN. Individuals with carotid IPN are more likely to develop stroke or TIA than those without carotid IPN.
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Affiliation(s)
- Yi Song
- Department of Ultrasound, First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China
| | - Hang Xing
- Division of Cardiothoracic Surgery, Warren Alpert Medical School of Brown University, Rhode Island Hospital, Providence, RI, 02903, USA
| | - Zhiqi Zhang
- Division of Cardiothoracic Surgery, Warren Alpert Medical School of Brown University, Rhode Island Hospital, Providence, RI, 02903, USA
| | - Lewis Oscar Felix
- Infectious Diseases Division, Warren Alpert Medical School of Brown University, Rhode Island Hospital, Providence, RI, 02903, USA
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Chiba T, Fujiwara S, Oura K, Oikawa K, Chida K, Kobayashi M, Yoshida K, Kubo Y, Maeda T, Itabashi R, Ogasawara K. Superb Microvascular Imaging Ultrasound for Cervical Carotid Artery Stenosis for Prediction of the Development of Microembolic Signals on Transcranial Doppler during Carotid Exposure in Endarterectomy. Cerebrovasc Dis Extra 2021; 11:61-68. [PMID: 34034253 PMCID: PMC8215948 DOI: 10.1159/000516426] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2021] [Accepted: 04/08/2021] [Indexed: 11/23/2022] Open
Abstract
Introduction During exposure of the carotid arteries, embolism from the surgical site is recognized as a primary cause of neurological deficits or new cerebral ischemic lesions following carotid endarterectomy (CEA), and associations have been reported between histological neovascularization in the carotid plaque and both plaque vulnerability and the development of artery-to-artery embolism. Superb microvascular imaging (SMI) enables accurate visualization of neovessels in the carotid plaque without the use of intravenous contrast. This study aimed to determine whether preoperative SMI ultrasound for cervical carotid artery stenosis predicts the development of microembolic signals (MES) on transcranial Doppler (TCD) during exposure of the carotid arteries in CEA. Methods Preoperative cervical carotid artery SMI ultrasound followed by CEA under TCD monitoring of MES in the ipsilateral middle cerebral artery was conducted in 70 patients previously diagnosed with internal carotid artery stenosis (defined as ≥70%). First, observers visually identified intraplaque microvascular flow (IMVF) signals as moving enhancements located near the surface of the carotid plaque within the plaque on SMI ultrasonograms. Next, regions of interest (ROI) were manually placed at the identified IMVF signals (or at arbitrary places within the plaque when no IMVF signals were identified within the carotid plaque) and the carotid lumen, and time-intensity curves of the IMVF signal and lumen ROI were generated. Ten heartbeat cycles of both time-intensity curves were segmented into each heartbeat cycle based on gated electrocardiogram findings and averaged with respect to the IMVF signal and lumen ROI. The difference between the maximum and minimum intensities (ID) was calculated based on the averaged IMVF signal (ID<sub>IMVF</sub>) and lumen (ID<sub>l</sub>) curves. Finally, the ratio of ID<sub>IMVF</sub> to ID<sub>l</sub> was calculated. Results MES during exposure of the carotid arteries were detected in 17 patients (24%). The incidence of identification of IMVF signals was significantly greater in patients with MES (94%) than in those without (57%; p = 0.0067). The ID<sub>IMVF</sub>/ID<sub>l</sub> ratio was significantly greater in patients with MES (0.108 ± 0.120) than in those without (0.017 ± 0.042; p < 0.0001). The specificity and positive predictive value for the ID<sub>IMVF</sub>/ID<sub>l</sub> ratio for prediction of the development of MES were significantly higher than those for the identification of IMVF signals. Logistic regression analysis revealed that only the ID<sub>IMVF</sub>/ID<sub>l</sub> ratio was significantly associated with the development of MES (95% CI 101.1–3,628.9; p = 0.0048). Conclusion Preoperative cervical carotid artery SMI ultrasound predicts the development of MES on TCD during exposure of the carotid arteries in CEA.
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Affiliation(s)
- Takayuki Chiba
- Department of Neurosurgery, Iwate Medical University School of Medicine, Yahaba, Japan
| | - Shunrou Fujiwara
- Department of Neurosurgery, Iwate Medical University School of Medicine, Yahaba, Japan
| | - Kazumasa Oura
- Department of Neurology and Gerontology, Iwate Medical University School of Medicine, Yahaba, Japan
| | - Kohki Oikawa
- Department of Neurosurgery, Iwate Medical University School of Medicine, Yahaba, Japan
| | - Kokei Chida
- Department of Neurosurgery, Iwate Medical University School of Medicine, Yahaba, Japan
| | - Masakazu Kobayashi
- Department of Neurosurgery, Iwate Medical University School of Medicine, Yahaba, Japan
| | - Kenji Yoshida
- Department of Neurosurgery, Iwate Medical University School of Medicine, Yahaba, Japan
| | - Yoshitaka Kubo
- Department of Neurosurgery, Iwate Medical University School of Medicine, Yahaba, Japan
| | - Tetsuya Maeda
- Department of Neurology and Gerontology, Iwate Medical University School of Medicine, Yahaba, Japan
| | - Ryo Itabashi
- Department of Neurology and Gerontology, Iwate Medical University School of Medicine, Yahaba, Japan
| | - Kuniaki Ogasawara
- Department of Neurosurgery, Iwate Medical University School of Medicine, Yahaba, Japan
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