Evaluation of a Dedicated Radiofrequency Carotid PET/MRI Coil

Carotid radiofrequency coils inside a PET/MRI system can result in PET quantification errors. We compared the performance of a dedicated PET/MRI carotid coil against a coil for MRI-only use. An 18F-fluorodeoxyglucose (18F-FDG) phantom was scanned without and with an MRI-only coil and with the PET/MRI coil. The decay-corrected normalized activity was compared for the different coil configurations. Eighteen patients were scanned with the three coil configurations. The maximal standardized uptake values (SUVmax) and signal-to-noise ratios (SNR) were calculated. Repeated measures ANOVA was performed to assess the differences in SUVmax and SNR between the coil configurations. In the phantom study, the PET/MRI coil demonstrated a slight decrease (<5%), while the MRI-only coil showed a substantial decrease (up to 10%) in normalized activity at the position of coil elements compared to no dedicated coil configuration. In the patient study, the SUVmax values for both no surface coil (3.59 ± 0.15) and PET/MRI coil (3.54 ± 0.15) were significantly higher (p = 0.03 and p = 0.04, respectively) as compared to the MRI-only coil (3.28 ± 0.16). No significant difference was observed between PET/MRI and no surface coil (p = 1.0). The SNR values for both PET/MRI (7.31 ± 0.44) and MRI-only (7.62 ± 0.42) configurations demonstrated significantly higher (p < 0.001) SNR values as compared to the no surface coil (3.78 ± 0.22), while no significant difference was observed in SNR between the PET/MRI and MRI-only coil (p = 1.0). This study demonstrated that the PET/MRI coil can be used for PET imaging without requiring attenuation correction while acquiring high-resolution MR images.

Multimodality carotid plaque tissue characterization and classification in the artificial intelligence paradigm: a narrative review for stroke application

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.

A flexible five-channel shielded-coaxial-cable (SCC) transceive neck coil for high-resolution carotid imaging at 7T

Purpose

Imaging the carotid arteries at 7T ideally requires a flexible multichannel array that allows B1‐shimming and conforms to different neck sizes. The major challenge is to minimize coupling between closely spaced coils and to make the coupling relatively insensitive to loading conditions.

Methods

We have designed a five‐channel flexible transceive array composed of shielded‐coaxial‐cable coils placed on the anterior part of the neck and conforming to the anatomy. In vivo imaging of the carotid arteries in three subjects has been performed.

Results

The measured noise correlation matrices show the decoupling level between the individual elements to be −12.5 dB and better. Anatomical localizer imaging of the carotids shows both carotids in every subject well visualized after B1‐shimming. In vivo black‐blood, carotid images were acquired with very high in‐plane spatial resolution (0.25 × 0.25 mm²) with clear depiction of the vessel walls.

Conclusions

The flexibility of the proposed coil has been demonstrated by imaging subjects with different neck circumferences. To the best of our knowledge, the in‐plane resolution of 0.25 × 0.25 mm² is the highest reported at 7T.

Diffusion-prepared stimulated-echo turbo spin echo (DPsti-TSE): An eddy current-insensitive sequence for three-dimensional high-resolution and undistorted diffusion-weighted imaging

In this study, we present a new three-dimensional (3D), diffusion-prepared turbo spin echo sequence based on a stimulated-echo read-out (DPsti-TSE) enabling high-resolution and undistorted diffusion-weighted imaging (DWI). A dephasing gradient in the diffusion preparation module and rephasing gradients in the turbo spin echo module create stimulated echoes, which prevent signal loss caused by eddy currents. Near to perfect agreement of apparent diffusion coefficient (ADC) values between DPsti-TSE and diffusion-weighted echo planar imaging (DW-EPI) was demonstrated in both phantom transient signal experiments and phantom imaging experiments. High-resolution and undistorted DPsti-TSE was demonstrated in vivo in prostate and carotid vessel wall. 3D whole-prostate DWI was achieved with four b values in only 6 min. Undistorted ADC maps of the prostate peripheral zone were obtained at low and high imaging resolutions with no change in mean ADC values [(1.60 ± 0.10) × 10^-3 versus (1.60 ± 0.02) × 10^-3  mm² /s]. High-resolution 3D DWI of the carotid vessel wall was achieved in 12 min, with consistent ADC values [(1.40 ± 0.23) × 10^-3  mm² /s] across different subjects, as well as slice locations through the imaging volume. This study shows that DPsti-TSE can serve as a robust 3D diffusion-weighted sequence and is an attractive alternative to the traditional two-dimensional DW-EPI approaches.

Stroke prevention in cardiac surgery

This article addresses the main risk factors for stroke in cardiac surgery and discusses the role of carotid artery intervention and peri-operative epi-aortic scanning in the prevention of stroke. In great Britain and Northern Ireland, there were ∼2789 new strokes following the 105,558 cases of cardiac surgery from 2004 to 2008 (an annual stroke rate of 2.6% complicating heart surgery in the UK). We argue that The National Health Service in the UK is set to spend £187,682 preventing each stroke in some 30 cardiac surgical patients while ignoring the remaining 528 strokes that complicate cardiac surgery in the UK each year. Caution must be taken in pricing the prevention of perioperative stroke as we must question our use of finite resources. Aortic atheroma has been demonstrated as the foremost cause of post-coronary artery bypass graft strokes. Epi-aortic scanning is effective in identifying aortic atheroma encouraging measures to reduce perioperative stroke with heart surgery, and it is cheap. Several studies have confirmed epi-aortic scanning at the time of heart surgery to be effective in reducing the incidence of perioperative brain damage. We suggest that it is time to adopt epi-aortic scanning in our routine cardiac surgical practice if only to confirm or refute its cost-effectiveness in brain protection during this surgery.