Advances in Carotid Artery Imaging

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Medical Imaging and Theranostics".

Deadline for manuscript submissions: closed (30 June 2022) | Viewed by 12543

Special Issue Editors

Department of Radiology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
Interests: ultrasound imaging; flow imaging; neuroendovascular procedures
Department of Diagnostic Radiology, Copenhagen University Hospital, Rigshospitalet, 2100 Copenhagen, Denmark
Interests: vector flow imaging; super resolution imaging; dual energy computed tomography; cardiac flow; kidney perfusion; pulmonary embolism; GI perfusion
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Special Issue Information

Dear Colleagues,

Stroke is a leading cause of death in developed countries, and diseases in the carotid artery increase the risk of stroke. Several different imaging techniques such as ultrasound, DSA, CTA, and MRA permit the analysis of various diseases like stenoses, aneurysms, thromboses, and dissections caused by atherosclerosis or congenital abnormalities. New advanced techniques for imaging have recently been brought to light, enabling a better understanding of carotid artery disease.

The focus in this Special Issue will be on carotid imaging. Both clinical and preclinical papers dealing with in vivo examination using established and new techniques will be considered.

Dr. Andreas Hjelm Brandt
Dr. Kristoffer Lindskov Hansen
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Carotid artery imaging
  • Carotid artery disease
  • New imaging technique
  • Angiography
  • Ultrasound
  • Computed tomography
  • Magnetic resonance imaging

Published Papers (6 papers)

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15 pages, 3219 KiB  
Article
Volumetric Flow Assessment in Extracranial Arteries in Patients with 70–99% Internal Carotid Artery Stenosis
by Piotr Kaszczewski, Michał Elwertowski, Jerzy Leszczyński, Tomasz Ostrowski, Joanna Kaszczewska, Tomasz Brzeziński, Daniel Jarosz, Siavash Świeczkowski-Feiz and Zbigniew Gałązka
Diagnostics 2022, 12(9), 2216; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics12092216 - 13 Sep 2022
Cited by 2 | Viewed by 1171
Abstract
Background: Cerebral blood flow (CBF) can be related to the risk of occurrence of neurological symptoms. Well-developed collateral circulation is a good prognostic factor in patients with cerebrovascular disease. Understanding the mechanisms of collateral circulation may be important in the diagnosis, treatment, and [...] Read more.
Background: Cerebral blood flow (CBF) can be related to the risk of occurrence of neurological symptoms. Well-developed collateral circulation is a good prognostic factor in patients with cerebrovascular disease. Understanding the mechanisms of collateral circulation may be important in the diagnosis, treatment, and monitoring in this group of patients. The aim of this study covered the assessment of CBF in patients with 70–99% Internal carotid artery (ICA) stenosis, focusing on the circulation pathways and flow volume in extracranial arteries. Materials and methods: 53 patients with 70–99% ICA stenosis (mean age 73.4 ± 7 years old; 17 female, mean age 73.9 ± 7.5 years old; 36 male, mean age 73.2 ± 6.8 years old) were included in the study. In all patients a Doppler ultrasound (DUS) examination, measuring blood flow volume in the internal carotid artery (ICA), external carotid artery (ECA), and vertebral artery (VA), was performed. The cerebral blood flow (CBF) was compared to the previously reported CBF values in the healthy population > 65 years old. Results: Among the study groups three subgroups with flow differences were identified: patients with elevated CBF (significant volumetric flow compensation—26/53, 49%), patients with CBF similar to (mild compensation—17/53, 32%), and patients with CBF lower than (no compensation—10/53, 19%) the healthy, equally aged population. The percentage of patients with significant volumetric flow compensation was the highest in age groups 65–69 years old (62.5%) and >80 years old (60%). In the oldest age group (>80 years old) no patients without flow compensation (0%) were observed. The level of compensation depends on the number of the arteries with compensatory increased flow. In patients with significant volumetric flow compensation, the compensatory increased flow was observed, on average, in 3.31 arteries, in the mild compensation group—in 2.18 arteries, and in the no compensation group only in 1 artery. ICA plays the most important role in the volumetric flow compensation—the increase in the flow volume, in comparison to the reference values, was between 116.7 mL/min and 251.9 mL/min (in the ECA 57.6 mL/min–110.4 mL/min; in the VA 73.9 mL/min–104.9 mL/min). The relative flow increase was highest in the VA: 215–246%, then in the ECA: 163–206%, and finally in the ICA: 148.6–192%. The increased flow was most commonly observed in the VA—57 arteries, in second place in the ECA—42 arteries, and ICA—31 arteries. In patients with unilateral ICA stenosis, the volumetric flow increase was stated more frequently in the ipsilateral ECAs then in the contralateral ones (23 vs. 14). In the VA the opposite tendency was observed (29 contralateral vs. 23 ipsilateral). The ability of volumetric flow compensation decreased significantly with increasing age. Conclusions: Understanding the mechanisms of collateral circulation and their assessment in Doppler ultrasonography may provide a novel and easily accessible tool of identifying and monitoring patients with cerebrovascular disease. Full article
(This article belongs to the Special Issue Advances in Carotid Artery Imaging)
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18 pages, 3999 KiB  
Article
Intracranial Flow Volume Estimation in Patients with Internal Carotid Artery Occlusion
by Piotr Kaszczewski, Michał Elwertowski, Jerzy Leszczyński, Tomasz Ostrowski, Joanna Kaszczewska and Zbigniew Gałązka
Diagnostics 2022, 12(3), 766; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics12030766 - 21 Mar 2022
Cited by 4 | Viewed by 2201
Abstract
(1) Background: Carotid artery occlusion (CAO) in population studies has a reported prevalence of about 6 per 100,000 people; however, the data may be underestimated. CAO carries a significant risk of stroke. Up to 15% of large artery infractions may be secondary to [...] Read more.
(1) Background: Carotid artery occlusion (CAO) in population studies has a reported prevalence of about 6 per 100,000 people; however, the data may be underestimated. CAO carries a significant risk of stroke. Up to 15% of large artery infractions may be secondary to the CAO, and in 27–38% of patients, ischaemic stroke is a first presentation of the disease. The presence of sufficient and well-developed collateral circulation has a protective influence, being a good prognostic factor in patients with carotid artery disease, both chronic and acute. Understanding the mechanisms and role of collateral circulation may be very important in the risk stratification of such patients. (2) Materials and Methods: This study included 46 patients (mean age: 70.5 ± 6 years old; 15 female, mean age 68.5 ± 3.8 years old and 31 male, mean age 71.5 ± 6.7 years old) with unilateral or bilateral ICA occlusion. In all patients, a Doppler ultrasound (DUS) examination, measuring blood flow volume in the internal carotid artery (ICA), external carotid artery (ECA), and vertebral artery (VA), was performed. The cerebral blood flow (CBF) was compared to the previously reported CBF values in the healthy population >65 years old. (3) Results: In comparison with CBF values in the healthy population, three subgroups with CBF changes were identified among patients with ICA occlusion: patients with significant volumetric flow compensation (CBF higher than average + standard deviation for healthy population of the same age), patients with flow similar to the healthy population (average ± standard deviation), and patients without compensation (CBF lower than the average-standard deviation for healthy population). The percentage of patients with significant volumetric flow compensation tend to rise with increasing age, while a simultaneous decline was observed in the group without compensation. The percentage of patients with flow similar to the healthy population remained relatively unchanged. ICA played the most important role in volumetric flow compensation in patients with CAO; however, the relative increase in flow in the ICA was smaller than that in the ECA and VA. Compensatory increased flow was observed in about 50% of all patent extracranial arteries and was more frequently observed in ipsilateral vessels than in contralateral ones, in both the ECA and the VA. In patients with CAO, there was no decrease in CBF, ICA, ECA, and VA flow volume with increasing age. (4) Conclusions: Volumetric flow compensation may play an important predictive role in patients with CAO. Full article
(This article belongs to the Special Issue Advances in Carotid Artery Imaging)
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21 pages, 9770 KiB  
Article
Simulation of Ultrasound RF Signals Backscattered from a 3D Model of Pulsating Artery Surrounded by Tissue
by Monika Makūnaitė, Rytis Jurkonis, Arūnas Lukoševičius and Mindaugas Baranauskas
Diagnostics 2022, 12(2), 232; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics12020232 - 18 Jan 2022
Cited by 1 | Viewed by 1673
Abstract
Arterial stiffness is an independent predictor of cardiovascular events. The motion of arterial tissues during the cardiac cycle is important as a mechanical deformation representing vessel elasticity and is related to arterial stiffness. In addition, arterial pulsation is the main source of endogenous [...] Read more.
Arterial stiffness is an independent predictor of cardiovascular events. The motion of arterial tissues during the cardiac cycle is important as a mechanical deformation representing vessel elasticity and is related to arterial stiffness. In addition, arterial pulsation is the main source of endogenous tissue micro-motions currently being studied for tissue elastography. Methods based on artery motion detection are not applied in clinical practice these days, because they must be carefully investigated in silico and in vitro before wide usage in vivo. The purpose of this paper is to propose a dynamic 3D artery model capable of reproducing the biomechanical behavior of human blood vessels surrounded by elastic tissue for endogenous deformation elastography developments and feasibility studies. The framework is based on a 3D model of a pulsating artery surrounded by tissue and simulation of linear scanning by Field II software to generate realistic dynamic RF signals and B-mode ultrasound image sequential data. The model is defined by a spatial distribution of motions, having patient-specific slopes of radial and longitudinal motion components of the artery wall and surrounding tissues. It allows for simulating the quantified mechanical micro-motions in the volume of the model. Acceptable simulation errors calculated between modeled motion patterns and those estimated from simulated RF signals and B-scan images show that this approach is suitable for the development and validation of elastography algorithms based on motion detection. Full article
(This article belongs to the Special Issue Advances in Carotid Artery Imaging)
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20 pages, 4490 KiB  
Article
Unseen Artificial Intelligence—Deep Learning Paradigm for Segmentation of Low Atherosclerotic Plaque in Carotid Ultrasound: A Multicenter Cardiovascular Study
by Pankaj K. Jain, Neeraj Sharma, Luca Saba, Kosmas I. Paraskevas, Mandeep K. Kalra, Amer Johri, John R. Laird, Andrew N. Nicolaides and Jasjit S. Suri
Diagnostics 2021, 11(12), 2257; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics11122257 - 02 Dec 2021
Cited by 34 | Viewed by 2278
Abstract
Background: The early detection of carotid wall plaque is recommended in the prevention of cardiovascular disease (CVD) in moderate-risk patients. Previous techniques for B-mode carotid atherosclerotic wall plaque segmentation used artificial intelligence (AI) methods on monoethnic databases, where training and testing are from [...] Read more.
Background: The early detection of carotid wall plaque is recommended in the prevention of cardiovascular disease (CVD) in moderate-risk patients. Previous techniques for B-mode carotid atherosclerotic wall plaque segmentation used artificial intelligence (AI) methods on monoethnic databases, where training and testing are from the “same” ethnic group (“Seen AI”). Therefore, the versatility of the system is questionable. This is the first study of its kind that uses the “Unseen AI” paradigm where training and testing are from “different” ethnic groups. We hypothesized that deep learning (DL) models should perform in 10% proximity between “Unseen AI” and “Seen AI”. Methodology: Two cohorts from multi-ethnic groups (330 Japanese and 300 Hong Kong (HK)) were used for the validation of our hypothesis. We used a four-layered UNet architecture for the segmentation of the atherosclerotic wall with low plaque. “Unseen AI” (training: Japanese, testing: HK or vice versa) and “Seen AI” experiments (single ethnicity or mixed ethnicity) were performed. Evaluation was conducted by measuring the wall plaque area. Statistical tests were conducted for its stability and reliability. Results: When using the UNet DL architecture, the “Unseen AI” pair one (Training: 330 Japanese and Testing: 300 HK), the mean accuracy, dice-similarity, and correlation-coefficient were 98.55, 78.38, and 0.80 (p < 0.0001), respectively, while for “Unseen AI” pair two (Training: 300 HK and Testing: 330 Japanese), these were 98.67, 82.49, and 0.87 (p < 0.0001), respectively. Using “Seen AI”, the same parameters were 99.01, 86.89 and 0.92 (p < 0.0001), respectively. Conclusion: We demonstrated that “Unseen AI” was in close proximity (<10%) to “Seen AI”, validating our DL model for low atherosclerotic wall plaque segmentation. The online system runs < 1 s. Full article
(This article belongs to the Special Issue Advances in Carotid Artery Imaging)
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31 pages, 10028 KiB  
Article
Ten Fast Transfer Learning Models for Carotid Ultrasound Plaque Tissue Characterization in Augmentation Framework Embedded with Heatmaps for Stroke Risk Stratification
by Skandha S. Sanagala, Andrew Nicolaides, Suneet K. Gupta, Vijaya K. Koppula, Luca Saba, Sushant Agarwal, Amer M. Johri, Manudeep S. Kalra and Jasjit S. Suri
Diagnostics 2021, 11(11), 2109; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics11112109 - 15 Nov 2021
Cited by 31 | Viewed by 2579
Abstract
Background and Purpose: Only 1–2% of the internal carotid artery asymptomatic plaques are unstable as a result of >80% stenosis. Thus, unnecessary efforts can be saved if these plaques can be characterized and classified into symptomatic and asymptomatic using non-invasive B-mode ultrasound. Earlier [...] Read more.
Background and Purpose: Only 1–2% of the internal carotid artery asymptomatic plaques are unstable as a result of >80% stenosis. Thus, unnecessary efforts can be saved if these plaques can be characterized and classified into symptomatic and asymptomatic using non-invasive B-mode ultrasound. Earlier plaque tissue characterization (PTC) methods were machine learning (ML)-based, which used hand-crafted features that yielded lower accuracy and unreliability. The proposed study shows the role of transfer learning (TL)-based deep learning models for PTC. Methods: As pertained weights were used in the supercomputer framework, we hypothesize that transfer learning (TL) provides improved performance compared with deep learning. We applied 11 kinds of artificial intelligence (AI) models, 10 of them were augmented and optimized using TL approaches—a class of Atheromatic™ 2.0 TL (AtheroPoint™, Roseville, CA, USA) that consisted of (i–ii) Visual Geometric Group-16, 19 (VGG16, 19); (iii) Inception V3 (IV3); (iv–v) DenseNet121, 169; (vi) XceptionNet; (vii) ResNet50; (viii) MobileNet; (ix) AlexNet; (x) SqueezeNet; and one DL-based (xi) SuriNet-derived from UNet. We benchmark 11 AI models against our earlier deep convolutional neural network (DCNN) model. Results: The best performing TL was MobileNet, with accuracy and area-under-the-curve (AUC) pairs of 96.10 ± 3% and 0.961 (p < 0.0001), respectively. In DL, DCNN was comparable to SuriNet, with an accuracy of 95.66% and 92.7 ± 5.66%, and an AUC of 0.956 (p < 0.0001) and 0.927 (p < 0.0001), respectively. We validated the performance of the AI architectures with established biomarkers such as greyscale median (GSM), fractal dimension (FD), higher-order spectra (HOS), and visual heatmaps. We benchmarked against previously developed Atheromatic™ 1.0 ML and showed an improvement of 12.9%. Conclusions: TL is a powerful AI tool for PTC into symptomatic and asymptomatic plaques. Full article
(This article belongs to the Special Issue Advances in Carotid Artery Imaging)
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7 pages, 1452 KiB  
Case Report
Imaging Challenges in the Diagnosis of Anatomical Variations of the Supra-Aortic Vessels: A Case Report and Review of Literature
by Alexandra Dădârlat-Pop, Adrian Molnar, Alexandru Oprea, Raluca Tomoaia, Bianca Boros, Sorin Literat, Adela Serban and Simona Manole
Diagnostics 2022, 12(1), 169; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics12010169 - 12 Jan 2022
Cited by 1 | Viewed by 1707
Abstract
A 73-year-old woman was referred to our Cardiology Department due to recurrent headaches and dizziness. She had a history of hypertension of 10 years. In the territorial hospital, left internal carotid artery significant stenosis was suspected. Neurological examination and laboratory tests were normal. [...] Read more.
A 73-year-old woman was referred to our Cardiology Department due to recurrent headaches and dizziness. She had a history of hypertension of 10 years. In the territorial hospital, left internal carotid artery significant stenosis was suspected. Neurological examination and laboratory tests were normal. A neck vascular ultrasound was performed, showing a low bifurcation of the left common carotid artery (CCA) and a hypoplastic left internal carotid artery (ICA) with a sinuous path at the cervical level. Therefore, a computed tomographic (CT) angiography examination of the head and neck vessels was performed. The images confirmed the presence of a hypoplastic left ICA, anatomic variation in the left CCA, and also showed that the left vertebral artery (VA) was stemming directly from the aortic arch, exhibiting a kinking trajectory. Full article
(This article belongs to the Special Issue Advances in Carotid Artery Imaging)
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