1
|
Ma C, Liang S, Liang F, Lu L, Zhu H, Lv X, Yang X, Jiang C, Zhang Y. Predicting postinterventional rupture of intracranial aneurysms using arteriography-derived radiomic features after pipeline embolization. Front Neurol 2024; 15:1327127. [PMID: 38515449 PMCID: PMC10954779 DOI: 10.3389/fneur.2024.1327127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 02/26/2024] [Indexed: 03/23/2024] Open
Abstract
Background and purpose Postinterventional rupture of intracranial aneurysms (IAs) remains a severe complication after flow diverter treatment. However, potential hemodynamic mechanisms underlying independent predictors for postinterventional rupture of IAs remain unclear. In this study, we employed arteriography-derived radiomic features to predict this complication. Methods We included 64 patients who underwent pipeline flow diversion for intracranial aneurysms, distinguishing between 16 patients who experienced postinterventional rupture and 48 who did not. We performed propensity score matching based on clinical and morphological factors to match these patients with 48 patients with postinterventional unruptured IAs at a 1:3 ratio. Postinterventional digital subtraction angiography were used to create five arteriography-derived perfusion parameter maps and then radiomics features were obtained from each map. Informative features were selected through the least absolute shrinkage and selection operator method with five-fold cross-validation. Subsequently, radiomics scores were formulated to predict the occurrence of postinterventional IA ruptures. Prediction performance was evaluated with the training and test datasets using area under the curve (AUC) and confusion matrix-derived metrics. Results Overall, 1,459 radiomics features were obtained, and six were selected. The resulting radiomics scores had high efficacy in distinguishing the postinterventional rupture group. The AUC and Youden index were 0.912 (95% confidence interval: 0.767-1.000) and 0.847 for the training dataset, respectively, and 0.938 (95% confidence interval, 0.806-1.000) and 0.800 for the testing dataset, respectively. Conclusion Radiomics scores generated using arteriography-derived radiomic features effectively predicted postinterventional IA ruptures and may aid in differentiating IAs at high risk of postinterventional rupture.
Collapse
Affiliation(s)
- Chao Ma
- School of Clinical Medicine, Tsinghua University, Beijing, China
- Department of Neurosurgery, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China
| | - Shikai Liang
- School of Clinical Medicine, Tsinghua University, Beijing, China
- Department of Neurosurgery, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China
- Institute for Intelligent Healthcare, Tsinghua University, Beijing, China
| | - Fei Liang
- Department of Vascular Surgery and Interventional Radiology, Peking University Third Hospital, Beijing, China
| | - Ligong Lu
- Guangdong Provincial Key Laboratory of Tumor Interventional Diagnosis and Treatment, Zhuhai Interventional Medical Center, Zhuhai Hospital, Affiliated with Jinan University, Zhuhai, China
| | - Haoyu Zhu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xianli Lv
- Department of Neurosurgery, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China
| | - Xuejun Yang
- Department of Neurosurgery, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China
- Institute for Intelligent Healthcare, Tsinghua University, Beijing, China
| | - Chuhan Jiang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yupeng Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| |
Collapse
|
2
|
Relationship between Injection Rate and Contrast Enhancement on Three-dimensional Digital Subtraction Angiography of the Cerebral Arteries. J Belg Soc Radiol 2018; 102:76. [PMID: 30533599 PMCID: PMC6284140 DOI: 10.5334/jbsr.1619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Objective: Three-dimensional (3D) digital subtraction angiography (DSA) is becoming a common technique for the assessment of the cerebral arteries. Nevertheless, the injection parameters for each artery are not standardized among institutions. The objective of this study was to analyze the relationship between injection rate and contrast enhancement on 3D DSA of the common carotid artery. Materials and methods: Twenty-four patients who underwent 3D DSA of the common carotid artery from June 2013 to March 2015 were included in this retrospective study. Contrast enhancement of each patient was analyzed for four cerebral arteries segments (A1, A2, M1 and M2) by measuring the average pixel value on the source rotational two-dimensional DSA images. Linear regression analysis was used to investigate the correlation between injection rate and contrast enhancement. Results: All four regression lines showed that a higher injection rate led to higher contrast enhancement. There was a significant relationship for the A1, A2 and M1 segments (P = 0.008, 0.03 and < 0.001) but not for the M2 segment (P = 0.13). The goodness-of-fit of the regression lines was high for the M1 segment (R2 = 0.63). However, as the size of the vascular lumen became narrower, the value for the A1 (R2 = 0.28) and A2 (R2 = 0.19) segments became lower. Conclusion: In 3D DSA of the common carotid artery, contrast enhancement of a relatively wide lumen could be optimized by adjusting the injection rate. However, it is difficult to optimize the contrast enhancement of a relatively narrow lumen only by adjusting the injection rate.
Collapse
|
3
|
Duckworth EA, Chintalapani G, Camstra KM, Kan P. Optimizing contrast-enhanced cone-beam CT protocol to facilitate simultaneous visualization of neurovascular pathologies and surrounding structures of interest. Interv Neuroradiol 2018; 25:102-110. [PMID: 30231798 DOI: 10.1177/1591019918800216] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
OBJECTIVE Contrast-enhanced cone-beam computed tomography (CBCT) imaging is commonly used for evaluating neurovascular stents and their relationship to the parent artery or vascular pathologies such as arteriovenous malformations (AVMs) and dural arteriovenous fistulas (dAVFs) in the context of surrounding anatomical structures. The purpose of this study was to understand the effects of varying concentrations of contrast medium used in CBCT imaging for optimal visualization of various endovascular devices and anatomical pathologies. METHODS Thirty-five patients with various neurovascular pathologies were included in the study. Contrast-enhanced CBCT images (20 s DR, Siemens syngo DynaCT, Siemens AG, Forchheim, Germany) were acquired in all cases, with varying dilutions of contrast medium, from 1% to 30%. The injection rate was kept constant at 3 cc/sec with an X-ray delay of two sec, and a total volume of 66 cc of diluted contrast was administered. Results from visual and quantitative analysis were reported. RESULTS Ten percent dilution of contrast medium resulted in the best image differentiation between flow-diverter devices and the parent artery. Concentrations as low as 2.5% contrast medium also resulted in identifying AVMs in the context of the surrounding brain parenchyma, whereas 20% to 30% dilution provided the best visualization of residual AVMs with prior Onyx embolization and dAVFs in the presence of bony structures. CONCLUSIONS Simultaneous visualization of brain parenchyma, bony structures, devices, and pathological anatomy using contrast-enhanced CBCT imaging is feasible with appropriate doses of iodinated contrast, and should be tailored to the individual case based on the goals of CBCT.
Collapse
Affiliation(s)
| | | | - Kevin M Camstra
- 1 Department of Neurosurgery, Baylor College of Medicine, Houston, USA
| | - Peter Kan
- 1 Department of Neurosurgery, Baylor College of Medicine, Houston, USA
| |
Collapse
|