Assessing carotid plaque neovascularity and calcifications in patients prior to endarterectomy

Comparison Between Clinically Available Low-Intensity Pulsed Ultrasound (LIPUS) and a Novel Bimodal Acoustic Signal System for Accelerating Fracture Healing

Low-intensity pulsed ultrasound (LIPUS) accelerates fracture healing by stimulating the production of bone callus and the mineralization process. This study compared a novel bimodal acoustic signal (BMAS) device for bone fracture healing to a clinical LIPUS system (EXOGEN; Bioventus, Durham, NC, USA). Thirty rabbits underwent a bilateral fibular osteotomy. Each rabbits' legs were randomized to receive 20-min treatment daily for 18 days with BMAS or LIPUS. The latter utilizes a longitudinal ultrasonic mode only, while the former employs ultrasound-induced shear stress to promote bone formation. Power Doppler imaging (PDI) was acquired days 0, 2, 4, 7, 11, 14, and 18 post-surgery to monitor treatment response and quantified off-line. X-rays were acquired to evaluate fractures on days 0, 14, 18, and 21. Seventeen rabbits completed the study and were euthanized day 21 post-surgery. The fibulae were analyzed to determine maximum torque, initial torsional stiffness, and angular displacement at failure. ANOVAs and paired t-tests were used to compare pair-wise outcome variables for the two treatment modes on a per rabbit basis. The BMAS system induced better fracture healing with greater stiffness (BMAS 0.21 ± 0.19 versus LIPUS 0.16 ± 0.19 [Formula: see text]cm/°, p = 0.050 ) and maximum torque (BMAS 7.84 ± 5.55 versus LIPUS 6.26 ± 3.46 [Formula: see text]cm, p = 0.022 ) than the LIPUS system. Quantitative PDI assessments showed a higher amount of vascularity with LIPUS than BMAS on days 4 and 18 ( ). In conclusion, the novel BMAS technique achieved better bone fracture healing response than the current Food and Drug Administration (FDA)-approved LIPUS system.

Detection of Carotid Atherosclerotic Intraplaque Neovascularization Using Superb Microvascular Imaging: A Meta-Analysis

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.

Deep learning-based carotid plaque vulnerability classification with multicentre contrast-enhanced ultrasound video: a comparative diagnostic study

OBJECTIVES

The aim of this study was to evaluate the performance of deep learning-based detection and classification of carotid plaque (DL-DCCP) in carotid plaque contrast-enhanced ultrasound (CEUS).

METHODS AND ANALYSIS

A prospective multicentre study was conducted to assess vulnerability in patients with carotid plaque. Data from 547 potentially eligible patients were prospectively enrolled from 10 hospitals, and 205 patients with CEUS video were finally enrolled for analysis. The area under the receiver operating characteristic curve (AUC) was used to evaluate the effectiveness of DL-DCCP and two experienced radiologists who manually examined the CEUS video (RA-CEUS) in diagnosing and classifying carotid plaque vulnerability. To evaluate the influence of dynamic video input on the performance of the algorithm, a state-of-the-art deep convolutional neural network (CNN) model for static images (Xception) was compared with DL-DCCP for both training and holdout validation cohorts.

RESULTS

The AUCs of DL-DCCP were significantly better than those of the experienced radiologists for both the training and holdout validation cohorts (training, DL-DCCP vs RA-CEUS, AUC: 0.85 vs 0.69, p<0.01; holdout validation, DL-DCCP vs RA-CEUS, AUC: 0.87 vs 0.66, p<0.01), that is, also better than the best deep CNN model Xception we had performed, for both the training and holdout validation cohorts (training, DL-DCCP vs Xception, AUC:0.85 vs 0.82, p<0.01; holdout validation, DL-DCCP vs Xception, AUC: 0.87 vs 0.77, p<0.01).

CONCLUSION

DL-DCCP shows better overall performance in assessing the vulnerability of carotid atherosclerotic plaques than RA-CEUS. Moreover, with a more powerful network structure and better utilisation of video information, DL-DCCP provided greater diagnostic accuracy than a state-of-the-art static CNN model.

TRIAL REGISTRATION NUMBER

ChiCTR1900021846.

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

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_IMVF) and lumen (ID_l) curves. Finally, the ratio of ID_IMVF to ID_l 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_IMVF/ID_l 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_IMVF/ID_l 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_IMVF/ID_l 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.

Vascular imaging of atherosclerosis: Strengths and weaknesses

Atherosclerosis is an inflammatory disease that can lead to several complications such as ischemic heart disease, stroke, and peripheral vascular disease. Therefore, researchers and clinicians rely heavily on the use of imaging modalities to identify, and more recently, quantify the burden of atherosclerosis in the aorta, carotid arteries, coronary arteries, and peripheral vasculature. These imaging techniques vary in invasiveness, cost, resolution, radiation exposure, and presence of artifacts. Consequently, a detailed understanding of the risks and benefits of each technique is crucial prior to their introduction into routine cardiovascular screening. Additionally, recent research in the field of microvascular imaging has proven to be important in the field of atherosclerosis. Using techniques such as contrast-enhanced ultrasound and superb microvascular imaging, researchers have been able to detect blood vessels within a plaque lesion that may contribute to vulnerability and rupture. This paper will review the strengths and weaknesses of the various imaging techniques used to measure atherosclerotic burden. Furthermore, it will discuss the future of advanced imaging modalities as potential biomarkers for atherosclerosis.

The ability of Micropure® ultrasound technique to identify microcalcifications in carotid plaques

OBJECTIVES

To study the ability of Micropure® ultrasound technique to identify microcalcifications in carotid plaques.

METHODS

Forty-four carotids in 22 patients were enrolled in this study and were detected by routine ultrasound examination and Micropure® examination at the same time to identify microcalcifications in plaques. The results were compared with the tissue-background ratio (TBR) in ¹⁸F-NaF PET-CT imaging, which was performed one or two days after the ultrasound examination.

RESULTS

In the 44 carotids, plaques were detected in 37 carotids. Microcalcifications were detected by the Micropure® technique in 32 carotids, which were located surrounded by macrocalcifications in 23 carotids, in the fibre cap in 12 carotids, and in the base of the plaque in 6 carotids. Microcalcifications were not detected in 12 carotids. In ¹⁸F-NaF PET-CT examination, TBR > 1.61 (range 1.62-3.99, mean 2.25 ± 0.58) was detected in 37 carotids, and TBR < 1.61 was detected in 7 carotids. There were no significant differences between the two methods in detecting microcalcifications (p = 0.180). The sensitivity of the Micropure® technique in detecting microcalcifications was 81.08 %, and the specificity was 71.43 %.

CONCLUSIONS

Microcalcifications in the carotid artery detected by the Micropure® technique were well in accordance with ¹⁸F-NaF PET-CT scanning, with better sensitivity and specificity.