Advanced Ultrasound in Diagnosis and Therapy ›› 2026, Vol. 10 ›› Issue (3): 193-202.doi: 10.26599/AUDT.2026.250087
• ORIGINAL RESEARCH • Previous Articles Next Articles
Huang Yunqiana,1, Shi Junnia,1, Chen Chuanjiana,1, Li Jiawenb, Yan Weia, Zheng Ruib,*(
), Chen Mana,*(
)
Received:2025-08-10
Revised:2025-11-09
Accepted:2026-01-04
Online:2026-09-30
Published:2026-10-12
Contact:
Zheng Rui, Chen Man,
E-mail:zhengrui@shanghaitech.edu.cn;maggiech1221@126.com
About author:First author contact:1Yunqian Huang, Junni Shi and Chuanjian Chen are contributed equally to this work.
Huang Yunqian, Shi Junni, Chen Chuanjian, Li Jiawen, Yan Wei, Zheng Rui, Chen Man. Semiautomated Portable Hand-held 3D Ultrasound Imaging System for Carotid Atherosclerotic Plaque Scanning. Advanced Ultrasound in Diagnosis and Therapy, 2026, 10(3): 193-202.
Figure 2
(A) The system consisted of a 2D linear probe, a host computer and a magnetic wireless/wired tracking system; (B) The overall network architecture. The architecture of the segmentation module is the U-Net, the channels are set to (64, 128, 256, 512, 512). The segmentation module is followed by the diagnosis module which consists of image information sub-module and morphology information sub-module; (C) Overall progress including data acquisition, segmentation, diagnosis and 3D reconstruction."
Table 1
Characteristics of Participants and Carotid plaques (Training set, Validation set and independent validation set)"
| Characteristic | Training set | Validation set | Independent validation set (n = 67) | P-value |
| (n = 25) | (n = 30) | |||
| Age (y) | 67.36 ± 8.96 | 62.8 ± 13.31 | 62.18 ± 11.28 | 0.173 |
| Sex | 0.618 | |||
| Female | 14 (56%) | 15 (50%) | 30 (44.78%) | |
| Male | 11 (44%) | 15 (50%) | 37 (55.22%) | |
| Body mass index (kg/m2) | 23.60 ± 3.47 | 23.07 ± 3.45 | 23.39 ± 3.83 | 0.878 |
| Smoking (Former + Current) | 4 (16%) | 10 (33.33%) | 22 (32.8%) | 0.251 |
| Diabetes | 5 (20%) | 4 (13.3%) | 13 (19.4%) | 0.73 |
| Hypertension | 13 (52%) | 16 (53.3%) | 32 (47.8%) | 0.857 |
| Carotid plaque | 17 (68%) | 20 (66.67%) | 32 (47.8%) | 0.096 |
| Thickness of plaque (mm) | 2.835 ± 0.97 | 2.88 ± 1.11 | 2.834 ± 1.05 | 0.986 |
| Echogenicity | 0.279 | |||
| Hypoechoic | 3 (17.64%) | 6 (30%) | 10 (31.25%) | |
| Heterogeneous echogenic | 10 (58.82%) | 7 (35%) | 12 (37.5%) | |
| Hyperechoic | 4 (23.53%) | 7 (35%) | 10 (31.25%) |
Table 2
The diagnostic result of 3D Ultrasound Imaging System of carotid plaque in validation set and independent validation set"
| Validation set (n = 30) | Independent validation set (n = 84) | |||||
| 3D Ultrasound diagnosis | 3D Ultrasound diagnosis | |||||
| Plaque | No plaque | Plaque | No plaque | |||
| Doctor diagnosis | Plaque | 15 | 5 | 26 | 6 | |
| No plaque | 3 | 7 | 5 | 47 | ||
| Sensitivity (%) | 83.3 (61.0 - 94.5) | 83.9 (65.7 - 90.8) | ||||
| Specificity (%) | 58.3 (32.3 - 80.3) | 88.7 (79.0 - 96.2) | ||||
| Accuracy (%) | 73.3 (54.1 - 87.7) | 86.9 (77.8 - 92.7) | ||||
Figure 4
Two incorrect cases of diagnosed are demonstrated. (A-C) show the segmentation results of frames 155, 160, and 165 for a false negative case, respectively, and it can be observed that the segmentation result of the 160th is wrong because the plaque is a hypoechoic plaque, which cannot be seen by the model in this frame; (D-F) show the segmentation results of frames 95, 100 and 105 for a false positive case, respectively. The segmentation results for 3 consecutive frames are wrong because the algorithm incorrectly identifies the artifacts as plaques."
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