A Dual-Stream Centerline-Guided Network for Segmentation of the Common and Internal Carotid Arteries From 3D Ultrasound Images

Segmentation of the carotid section encompassing the common carotid artery (CCA), the bifurcation and the internal carotid artery (ICA) from three-dimensional ultrasound (3DUS) is required to measure the vessel wall volume (VWV) and localized vessel-wall-plus-plaque thickness (VWT), shown to be sensitive to treatment effect. We proposed an approach to combine a centerline extraction network (CHG-Net) and a dual-stream centerline-guided network (DSCG-Net) to segment the lumen-intima (LIB) and media-adventitia boundaries (MAB) from 3DUS images. Correct arterial location is essential for successful segmentation of the carotid section encompassing the bifurcation. We addressed this challenge by using the arterial centerline to enhance the localization accuracy of the segmentation network. The CHG-Net was developed to generate a heatmap indicating high probability regions for the centerline location, which was then integrated with the 3DUS image by the DSCG-Net to generate the MAB and LIB. The DSCG-Net includes a scale-based and a spatial attention mechanism to fuse multi-level features extracted by the encoder, and a centerline heatmap reconstruction side-branch connected to the end of the encoder to increase the generalization ability of the network. Experiments involving 224 3DUS volumes produce a Dice similarity coefficient (DSC) of 95.8±1.9% and 92.3±5.4% for CCA MAB and LIB, respectively, and 93.2±4.4% and 89.0±10.0% for ICA MAB and LIB, respectively. Our approach outperformed four state-of-the-art 3D CNN models, even after their performances were boosted by centerline guidance. The efficiency afforded by the framework would allow it to be incorporated into the clinical workflow for improved quantification of plaque change.

Three-dimensional ultrasound assessment of effects of therapies on carotid atherosclerosis using vessel wall thickness maps

We present a new method for assessing the effects of therapies on atherosclerosis, by measuring the weighted average of carotid vessel-wall-plus-plaque thickness change (ΔVWT¯_Weighted) in 120 patients randomized to pomegranate juice/extract versus placebo. Three-dimensional ultrasound images were acquired at baseline and one year after. Three-dimensional VWT maps were reconstructed and then projected onto a carotid template to obtain two-dimensional VWT maps. Anatomic correspondence on the two-dimensional VWT maps was optimized to reduce misalignment for the same subject and across subjects. A weight was computed at each point on the two-dimensional VWT map to highlight anatomic locations likely to exhibit plaque progression/regression, resulting in ΔVWT¯_Weighted for each subject. The weighted average of VWT-Change measured from the two-dimensional VWT maps with correspondence alignment (ΔVWT¯_Weighted,MDL) detected a significant difference between the pomegranate and placebo groups (P = 0.008). This method improves the cost-effectiveness of proof-of-concept studies involving new therapies for atherosclerosis.

Three-dimensional ultrasound imaging: An effective method to detect the effect of moderate intensity statin treatment in slowing carotid plaque progression

PURPOSE

We aimed to evaluate the feasibility of three-dimensional ultrasound imaging (3DUS) in assessing the therapeutic effect of moderate-intensity statin therapy on carotid atherosclerotic plaques.

METHODS

Patients with carotid plaques were recruited to the study from January 2016 to September 2018, and were divided into two groups based on whether or not they were taking statins. All participants underwent 3DUS of their carotid plaques at baseline, then 3 months and 2 years after initial examination. The changes of the carotid plaques were compared between the two groups.

RESULTS

Were included 97 patients (57 males and 40 females), 65.26 ± 9.53 year-old with 67 into the statin group and 30 in the control group. The baseline levels of total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) were lower in the statin group than in the control group (3.79 ± 0.78 mmol/L vs 4.50 ± 1.12 mmol/L; 2.01 ± 0.62 mmol/L vs 2.58 ± 0.91 mmol/L, P < .05). There was no significant difference in the change of total plaque volume (TPV) detected by 3D-US between the statin (median [interquartile range]: 0 [-30-20] mm³ ) and the control group (0 [-22.5-25] mm³ ) at 3 months. Over 2 years, the TPV increased faster in the control group (+70 [25-150] mm³ ), than in the statin group (15 [-57.5-90) mm³ , P < .05).

CONCLUSIONS

3DUS can be an effective tool to observe the development of carotid plaques and the effect of statin treatment.

Fully automatic plaque segmentation in 3-D carotid ultrasound images

Automatic segmentation of the carotid plaques from ultrasound images has been shown to be an important task for monitoring progression and regression of carotid atherosclerosis. Considering the complex structure and heterogeneity of plaques, a fully automatic segmentation method based on media-adventitia and lumen-intima boundary priors is proposed. This method combines image intensity with structure information in both initialization and a level-set evolution process. Algorithm accuracy was examined on the common carotid artery part of 26 3-D carotid ultrasound images (34 plaques ranging in volume from 2.5 to 456 mm(3)) by comparing the results of our algorithm with manual segmentations of two experts. Evaluation results indicated that the algorithm yielded total plaque volume (TPV) differences of -5.3 ± 12.7 and -8.5 ± 13.8 mm(3) and absolute TPV differences of 9.9 ± 9.5 and 11.8 ± 11.1 mm(3). Moreover, high correlation coefficients in generating TPV (0.993 and 0.992) between algorithm results and both sets of manual results were obtained. The automatic method provides a reliable way to segment carotid plaque in 3-D ultrasound images and can be used in clinical practice to estimate plaque measurements for management of carotid atherosclerosis.