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  • Quantitative analysis of unruptured intracranial aneurysm wall thickness and enhancement using 7T high resolution, black blood magnetic resonance imaging

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Neuroimaging
Original research
Quantitative analysis of unruptured intracranial aneurysm wall thickness and enhancement using 7T high resolution, black blood magnetic resonance imaging
  1. Xinke Liu1,
  2. Junqiang Feng1,
  3. Zhixin Li2,3,
  4. Zihao Zhang2,3,
  5. Qiang Zhang4,
  6. Yuhua Jiang1,
  7. Xiaochuan Huo1,
  8. Xubin Chai2,3,
  9. Yue Wu2,3,
  10. Qingle Kong5,
  11. Peng Liu1,
  12. Huijian Ge1,
  13. Hengwei Jin1,
  14. Jing An6,
  15. Peng Jiang1,
  16. David A Saloner7,
  17. Youxiang Li1,
  18. Chengcheng Zhu8
  1. 1 Department of Interventional Neuroradiology, Beijing Neurosurgical Institute and Beijing Tiantan Hospital, Capital Medical University, Beijing, China
  2. 2 State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, 15 Datun Road, Beijing 100101, China
  3. 3 University of Chinese Academy of Sciences, Beijing 100049, China
  4. 4 Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
  5. 5 MR Collaboration, Siemens Healthcare China, Beijing, China
  6. 6 Siemens Shenzhen Magnetic Resonance Ltd, Siemens Healthcare China, Shenzhen, China
  7. 7 Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
  8. 8 Department of Radiology, University of Washington, Seattle, Washington, USA
  1. Correspondence to Dr Zihao Zhang, State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, 15 Datun Road, Beijing 100101, China; zhzhang{at}ibp.ac.cn; Professor Youxiang Li, Department of Interventional Neuroradiology, Beijing Neurosurgical Institute and Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; liyouxiang{at}263.net

Abstract

Background This study was performed to quantify intracranial aneurysm wall thickness (AWT) and enhancement using 7T MRI, and their relationship with aneurysm size and type.

Methods 27 patients with 29 intracranial aneurysms were included. Three-dimensional T1 weighted pre‐ and post-contrast fast spin echo with 0.4 mm isotropic resolution was used. AWT was defined as the full width at half maximum on profiles of signal intensity across the aneurysm wall on pre-contrast images. Enhancement ratio (ER) was defined as the signal intensity of the aneurysm wall over that of the brain parenchyma. The relationships between AWT, ER, and aneurysm size and type were investigated.

Results 7T MRI revealed large variations in AWT (range 0.11–1.24 mm). Large aneurysms (>7 mm) had thicker walls than small aneurysms (≤7 mm) (0.49±0.05 vs 0.41±0.05 mm, p<0.001). AWT was similar between saccular and fusiform aneurysms (p=0.546). Within each aneurysm, a thicker aneurysm wall was associated with increased enhancement in 28 of 29 aneurysms (average r=0.65, p<0.05). Thicker walls were observed in enhanced segments (ER >1) than in non-enhanced segments (0.53±0.09 vs 0.38±0.07 mm, p<0.001).

Conclusion Improved image quality at 7T allowed quantification of intracranial AWT and enhancement. A thicker aneurysm wall was observed in larger aneurysms and was associated with stronger enhancement.

  • aneurysm
  • MRI

Data availability statement

Data are available upon reasonable request. The data that support the findings of this study are available from the corresponding author upon reasonable request.

https://doi.org/10.1136/neurintsurg-2021-017688

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    Data availability statement

    Data are available upon reasonable request. The data that support the findings of this study are available from the corresponding author upon reasonable request.

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    Footnotes

    • XL and JF are joint first authors.

    • XL and JF contributed equally.

    • Contributors Protocol/project development: XL, ZZ, CZ, and YL. Data collection or management: JF, ZL, LP, XH, YJ, PJ, QK, XC, YW, HG, HJ, and JA. Data analysis: XL, JF, ZL, QZ, DAS, and CZ.

    • Funding This work was supported by the National Natural Science Foundation of China (82001804, 81901197 and 31730039); the Natural Science Foundation of Beijing Municipality (7191003); the Ministry of Science and Technology of China (2019YFA0707103); and the Chinese Academy of Sciences (XDB32010300). Chengcheng Zhu is supported by the US National Institutes of Health (NIH) grant R00HL136883.

    • Competing interests None declared.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.