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Zhang J, Chen X, Tian J, Sun B, Li X, Wang L, Zhang J, Zhao B, Guo Q, Wan J, Wu P, Zhou Y, Xu J, Ding S, Zhao X, Zhao H. Associations between atherosclerotic luminal stenosis in the distal internal carotid artery and diffuse wall thickening in its upstream segment. Eur Radiol 2024; 34:4831-4840. [PMID: 38172441 DOI: 10.1007/s00330-023-10539-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Revised: 11/01/2023] [Accepted: 11/23/2023] [Indexed: 01/05/2024]
Abstract
OBJECTIVES Significant atherosclerotic stenosis or occlusion in the distal internal carotid artery (ICA) may induce diffuse wall thickening (DWT) in the upstream arterial wall. This study aimed to assess the association of atherosclerotic steno-occlusive diseases in the distal ICA with DWT in the upstream ipsilateral ICA. METHODS Individuals with atherosclerotic stenosis in the distal ICA, detected by carotid MR vessel wall imaging using 3D pre- and post-contrast T1 volume isotropic turbo spin-echo acquisition (T1-VISTA) sequence, were enrolled. The associations of vessel wall thickening, the longitudinal extent of DWT, enhancement of the upstream ipsilateral ICA, and stenosis degree in the distal ICA were examined. RESULTS Totally 64 arteries in 55 patients with atherosclerotic steno-occlusive distal ICAs were included. Significant correlations were found between distal ICA stenosis and DWT in the petrous ICA (r = 0.422, p = 0.001), DWT severity (r = 0.474, p < 0.001), the longitudinal extent of DWT in the ICA (r = 0.671, p < 0.001), enhancement in the petrous ICA (r = 0.409, p = 0.001), and enhancement degree (r = 0.651, p < 0.001). In addition, high degree of enhancement was correlated with both increased wall thickness and increased prevalence of DWT in the petrous ICA (both p < 0.001). CONCLUSIONS DWT of the petrous ICA is commonly detected in patients with atherosclerotic steno-occlusive disease in the distal ICA. The degree of stenosis in the distal ICA is associated with wall thickening and its longitudinal extent in the upstream segments. CLINICAL RELEVANCE STATEMENT Diffuse wall thickening is a common secondary change in atherosclerotic steno-occlusive disease in the intracranial carotid. This phenomenon constitutes a confounding factor in the distinction between atherosclerosis and inflammatory vasculopathies, and could be reversed after alleviated atherosclerotic stenosis. KEY POINTS • Diffuse wall thickening of the petrous internal carotid artery is commonly detected in patients with atherosclerotic steno-occlusive disease in the distal internal carotid artery. • The phenomenon of diffuse wall thickening could be reversed after stenosis alleviation. • Carotid artery atherosclerosis with diffuse wall thickening should warrant a differential diagnosis from other steno-occlusive diseases, including moyamoya diseases and Takayasu aortitis.
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Affiliation(s)
- Jin Zhang
- Department of Radiology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiaoyi Chen
- Department of Radiology, Beijing Geriatric Hospital, Beijing, China
| | - Jiaqi Tian
- Department of Radiology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Beibei Sun
- Department of Radiology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiao Li
- Department of Radiology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lingling Wang
- Department of Radiology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jianjian Zhang
- Department of Radiology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Bing Zhao
- Department of Neurosurgery, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qinghua Guo
- Department of Neurosurgery, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jieqing Wan
- Department of Neurosurgery, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Peng Wu
- Philips Healthcare, Shanghai, China
| | - Yan Zhou
- Department of Radiology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jianrong Xu
- Department of Radiology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shenghao Ding
- Department of Neurosurgery, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Xihai Zhao
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University School of Medicine, Beijing, China.
| | - Huilin Zhao
- Department of Radiology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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Deep learning-based detection algorithm for brain metastases on black blood imaging. Sci Rep 2022; 12:19503. [PMID: 36376364 PMCID: PMC9663732 DOI: 10.1038/s41598-022-23687-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 11/03/2022] [Indexed: 11/16/2022] Open
Abstract
Brain metastases (BM) are the most common intracranial tumors, and their prevalence is increasing. High-resolution black-blood (BB) imaging was used to complement the conventional contrast-enhanced 3D gradient-echo imaging to detect BM. In this study, we propose an efficient deep learning algorithm (DLA) for BM detection in BB imaging with contrast enhancement scans, and assess the efficacy of an automatic detection algorithm for BM. A total of 113 BM participants with 585 metastases were included in the training cohort for five-fold cross-validation. The You Only Look Once (YOLO) V2 network was trained with 3D BB sampling perfection with application-optimized contrasts using different flip angle evolution (SPACE) images to investigate the BM detection. For the observer performance, two board-certified radiologists and two second-year radiology residents detected the BM and recorded the reading time. For the training cohort, the overall performance of the five-fold cross-validation was 87.95%, 24.82%, 19.35%, 14.48, and 18.40 for sensitivity, precision, F1-Score, the false positive average for the BM dataset, and the false positive average for the normal individual dataset, respectively. For the comparison of reading time with and without DLA, the average reading time was reduced by 20.86% in the range of 15.22-25.77%. The proposed method has the potential to detect BM with a high sensitivity and has a limited number of false positives using BB imaging.
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Sundermann B, Billebaut B, Bauer J, Iacoban CG, Alykova O, Schülke C, Gerdes M, Kugel H, Neduvakkattu S, Bösenberg H, Mathys C. Practical Aspects of novel MRI Techniques in Neuroradiology: Part 1-3D Acquisitions, Dixon Techniques and Artefact Reduction. ROFO-FORTSCHR RONTG 2022; 194:1100-1108. [PMID: 35545104 DOI: 10.1055/a-1800-8692] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
BACKGROUND Recently introduced MRI techniques offer improved image quality and facilitate examinations of patients even when artefacts are expected. They pave the way for novel diagnostic imaging strategies in neuroradiology. These methods include improved 3D imaging, movement and metal artefact reduction techniques as well as Dixon techniques. METHODS Narrative review with an educational focus based on current literature research and practical experiences of different professions involved (physicians, MRI technologists/radiographers, physics/biomedical engineering). Different hardware manufacturers are considered. RESULTS AND CONCLUSIONS 3D FLAIR is an example of a versatile 3D Turbo Spin Echo sequence with broad applicability in routine brain protocols. It facilitates detection of smaller lesions and more precise measurements for follow-up imaging. It also offers high sensitivity for extracerebral lesions. 3D techniques are increasingly adopted for imaging arterial vessel walls, cerebrospinal fluid spaces and peripheral nerves. Improved hybrid-radial acquisitions are available for movement artefact reduction in a broad application spectrum. Novel susceptibility artefact reduction techniques for targeted application supplement previously established metal artefact reduction sequences. Most of these techniques can be further adapted to achieve the desired diagnostic performances. Dixon techniques allow for homogeneous fat suppression in transition areas and calculation of different image contrasts based on a single acquisition. KEY POINTS · 3D FLAIR can replace 2 D FLAIR for most brain imaging applications and can be a cornerstone of more precise and more widely applicable protocols.. · Further 3D TSE sequences are increasingly replacing 2D TSE sequences for specific applications.. · Improvement of artefact reduction techniques increase the potential for effective diagnostic MRI exams despite movement or near metal implants.. · Dixon techniques facilitate homogeneous fat suppression and simultaneous acquisition of multiple contrasts.. CITATION FORMAT · Sundermann B, Billebaut B, Bauer J et al. Practical Aspects of novel MRI Techniques in Neuroradiology: Part 1-3D Acquisitions, Dixon Techniques and Artefact Reduction. Fortschr Röntgenstr 2022; DOI: 10.1055/a-1800-8692.
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Affiliation(s)
- Benedikt Sundermann
- Institute of Radiology and Neuroradiology, Evangelisches Krankenhaus, Medical Campus University of Oldenburg, Germany.,Research Center Neurosensory Science, University of Oldenburg, Germany.,Clinic for Radiology, University Hospital Münster, Germany
| | - Benoit Billebaut
- Clinic for Radiology, University Hospital Münster, Germany.,School for Radiologic Technologists, University Hospital Münster, Germany
| | - Jochen Bauer
- Clinic for Radiology, University Hospital Münster, Germany
| | - Catalin George Iacoban
- Institute of Radiology and Neuroradiology, Evangelisches Krankenhaus, Medical Campus University of Oldenburg, Germany
| | - Olga Alykova
- Institute of Radiology and Neuroradiology, Evangelisches Krankenhaus, Medical Campus University of Oldenburg, Germany
| | | | - Maike Gerdes
- Institute of Radiology and Neuroradiology, Evangelisches Krankenhaus, Medical Campus University of Oldenburg, Germany
| | - Harald Kugel
- Clinic for Radiology, University Hospital Münster, Germany
| | | | - Holger Bösenberg
- Institute of Radiology and Neuroradiology, Evangelisches Krankenhaus, Medical Campus University of Oldenburg, Germany
| | - Christian Mathys
- Institute of Radiology and Neuroradiology, Evangelisches Krankenhaus, Medical Campus University of Oldenburg, Germany.,Research Center Neurosensory Science, University of Oldenburg, Germany.,Department of Diagnostic and Interventional Radiology, University of Düsseldorf, Germany
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