Automatic flow analysis of digital subtraction angiography using independent component analysis in patients with carotid stenosis

Han-Jui Lee; Jia-Sheng Hong; Chung-Jung Lin; Yi-Hsuan Kao; Feng-Chi Chang; Chao-Bao Luo; Wei-Fa Chu

doi:10.1371/journal.pone.0185330

Automatic flow analysis of digital subtraction angiography using independent component analysis in patients with carotid stenosis

PLoS One. 2017 Sep 26;12(9):e0185330. doi: 10.1371/journal.pone.0185330. eCollection 2017.

Authors

Han-Jui Lee^{1

2}, Jia-Sheng Hong³, Chung-Jung Lin^{1

2}, Yi-Hsuan Kao³, Feng-Chi Chang^{1

2}, Chao-Bao Luo^{1

2}, Wei-Fa Chu^{1

2}

Affiliations

¹ Department of Radiology, Taipei Veterans General Hospital, Taipei, Taiwan.
² School of Medicine, National Yang-Ming University, Taipei, Taiwan.
³ Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, Taipei, Taiwan.

Abstract

Purpose: Current time-density curve analysis of digital subtraction angiography (DSA) provides intravascular flow information but requires manual vasculature selection. We developed an angiographic marker that represents cerebral perfusion by using automatic independent component analysis.

Materials and methods: We retrospectively analyzed the data of 44 patients with unilateral carotid stenosis higher than 70% according to North American Symptomatic Carotid Endarterectomy Trial criteria. For all patients, magnetic resonance perfusion (MRP) was performed one day before DSA. Fixed contrast injection protocols and DSA acquisition parameters were used before stenting. The cerebral circulation time (CCT) was defined as the difference in the time to peak between the parietal vein and cavernous internal carotid artery in a lateral angiogram. Both anterior-posterior and lateral DSA views were processed using independent component analysis, and the capillary angiogram was extracted automatically. The full width at half maximum of the time-density curve in the capillary phase in the anterior-posterior and lateral DSA views was defined as the angiographic mean transient time (aMTT; i.e., aMTTAP and aMTTLat). The correlations between the degree of stenosis, CCT, aMTTAP and aMTTLat, and MRP parameters were evaluated.

Results: The degree of stenosis showed no correlation with CCT, aMTTAP, aMTTLat, or any MRP parameter. CCT showed a strong correlation with aMTTAP (r = 0.67) and aMTTLat (r = 0.72). Among the MRP parameters, CCT showed only a moderate correlation with MTT (r = 0.67) and Tmax (r = 0.40). aMTTAP showed a moderate correlation with Tmax (r = 0.42) and a strong correlation with MTT (r = 0.77). aMTTLat also showed similar correlations with Tmax (r = 0.59) and MTT (r = 0.73).

Conclusion: Apart from vascular anatomy, aMTT estimates brain parenchyma hemodynamics from DSA and is concordant with MRP. This process is completely automatic and provides immediate measurement of quantitative peritherapeutic brain parenchyma changes during stenting.

MeSH terms

Aged
Aged, 80 and over
Angiography, Digital Subtraction / methods*
Carotid Stenosis / diagnostic imaging*
Carotid Stenosis / pathology
Female
Humans
Male
Middle Aged

Grants and funding

This work was supported by MOST 104-2314-B-010 -037 to CJL, https://www.most.gov.tw/), and Taipei Veterans General Hospital (V105-C-145 to CJL, https://rg.vghtpe.gov.tw/PR93APPLY/personal/intra.htm). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.