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  • Using angiographic parametric imaging-derived radiomics features to predict complications and embolization outcomes of intracranial aneurysms treated by pipeline embolization devices

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New devices and techniques
Original research
Using angiographic parametric imaging-derived radiomics features to predict complications and embolization outcomes of intracranial aneurysms treated by pipeline embolization devices
  1. Fei Liang1,
  2. Chao Ma1,
  3. Haoyu Zhu1,
  4. Lian Liu1,
  5. Shikai Liang2,
  6. Peng Jiang1,
  7. Yupeng Zhang1,
  8. Chuhan Jiang1
  1. 1 Department of Interventional Neuroradiology, Beijing Neurosurgical Institute and Beijing Tiantan Hospital, Capital Medical University, Beijing, China
  2. 2 Department of Neurosurgery, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China
  1. Correspondence to Dr Chuhan Jiang, Department of Interventional Neuroradiology, Beijing Neurosurgical Institute and Beijing Tiantan Hospital, Capital Medical University, Beijing, China; jiangchuhan126{at}126.com; Dr Yupeng Zhang, Department of Interventional Neuroradiology, Beijing Neurosurgical Institute and Beijing Tiantan Hospital, Capital Medical University, Beijing, China; zhangyupeng1003{at}gmail.com

Abstract

Background Pipeline embolization devices (PEDs) have gained widespread popularity in the treatment of intracranial aneurysms (IAs). However, precise predictors of treatment outcomes are still lacking. This study aimed to use angiographic parametric imaging (API)-derived radiomics features to explore whether biomarkers extracted from immediate postprocedural digital subtraction angiography (DSA) were associated with complications and embolization outcomes of IAs treated with PED without adjunctive coils.

Methods Radiomic features were extracted from postprocedural DSA by API, and radiomics feature selection and radiomics score calculation were performed by the least absolute shrinkage and selection operator (LASSO) logistic regression. Angiographic findings and clinical characteristics were screened using stepwise multivariable logistic regression analysis to identify significant variables for predicting the complication endpoint. Radiomics feature selection and radiomics risk score (RadRS) calculations were performed by LASSO Cox regression. Univariate and multivariate Cox regression analyses were used to identify significant predictors for the occlusion endpoint.

Results We screened 281 observations for complications and 235 observations for embolization outcomes from IAs treated in our center using PED between June 2015 and July 2020. Multivariate regression analysis showed association of the radiomics score (p<0.01) and hypertension (p=0.04) with complications. RadRS (p<0.01), symptoms (p<0.01), and age (p=0.03) were predictors of embolization outcomes. Kaplan-Meier analysis revealed that symptomatic patients (p<0.01) and those with off-label IAs (p=0.03) had shorter intervals to complete occlusion.

Conclusions Biomarkers extracted from immediate postprocedural DSA by API could be potential indicators for assessing treatment outcomes of IAs treated by PED without adjunctive coils.

  • aneurysm
  • angiography
  • flow diverter
  • intervention

Data availability statement

Data are available upon reasonable request.

https://doi.org/10.1136/neurintsurg-2021-017832

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    Data availability statement

    Data are available upon reasonable request.

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    Footnotes

    • YZ and CJ contributed equally.

    • Contributors FL collected and analyzed the data and drafted and revised the paper. CM monitored data collection and analyzed the data. HZ monitored data collection. LL revised the paper and gave final approval of the version to be submitted. SL revised the paper and gave final approval of the version to be submitted. PJ gave final approval of the version to be submitted. YZ conceived and designed the article, wrote the statistical analysis plan, analyzed and interpreted the data, and revised the paper critically. CJ conceived and designed the article, revised the paper critically, and gave final approval of the version to be submitted.

    • Funding This work was supported by the Beijing Natural Science Foundation project (Grant No. 7212007).

    • 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.