Elsevier

Magnetic Resonance Imaging

Volume 57, April 2019, Pages 293-302
Magnetic Resonance Imaging

Original contribution
Quantification of morphometry and intensity features of intracranial arteries from 3D TOF MRA using the intracranial artery feature extraction (iCafe): A reproducibility study

https://doi.org/10.1016/j.mri.2018.12.007Get rights and content

Abstract

Background

Accurate and reliable vascular features extracted from 3D time-of-flight (TOF) magnetic resonance angiography (MRA) can help evaluate cerebral vascular diseases and conditions. The goal of this study was to evaluate the reproducibility of an intracranial artery feature extraction (iCafe) algorithm for quantitative analysis of intracranial arteries from TOF MRA.

Methods

Twenty-four patients with known intracranial artery stenosis were recruited and underwent two separate MRA scans within 2 weeks of each other. Each dataset was blinded to associated imaging and clinical data and then processed independently using iCafe. Inter-scan reproducibility analysis was performed on the 24 pairs of scans while intra-/inter-operator reproducibility and stenosis detection were assessed on 8 individual MRA scans. After tracing the vessels visualized on TOF MRA, iCafe was used to automatically extract the locations with stenosis and eight other vascular features. The vascular features included the following six morphometry and two signal intensity features: artery length (total, distal, and proximal), volume, number of branches, average radius of the M1 segment of the middle cerebral artery, and average normalized intensity of all arteries and large vertical arteries. A neuroradiologist independently reviewed the images to identify locations of stenosis for the reference standard. Reproducibility of stenosis detection and vascular features was assessed using Cohen's kappa, the intra-class correlation coefficient (ICC), and within-subject coefficient of variation (CV).

Results

The segment-based sensitivity of iCafe for stenosis detection ranged from 83.3–91.7% while specificity was 97.4%. Kappa values for inter-scan and intra-operator reproducibility were 0.73 and 0.77, respectively. All vascular features demonstrated excellent inter-scan and intra-operator reproducibility (ICC = 0.91–1.00, and CV = 1.21–8.78% for all markers), and good to excellent inter-operator reproducibility (ICC = 0.76–0.99, and CV = 3.27–15.79% for all markers).

Conclusion

Intracranial artery features can be reliably quantified from TOF MRA using iCafe to provide both clinical diagnostic assistance and facilitate future investigative quantitative analyses.

Section snippets

Background

Atherosclerosis is a major cause of cardio- and cerebrovascular disease mortality and morbidity globally [[1], [2], [3]]. Plaque progression leads to arterial stenosis and/or occlusion, which may cause downstream ischemic events due to atherothrombosis or hypoperfusion [4]. As a subset of atherosclerosis, intracranial atherosclerosis accounts for about 30–50% and 10% of cerebrovascular ischemic events in Asian and Caucasian populations, respectively [5].

In current clinical practice, luminal

Patient studies

After institutional review board review and approval, 24 subjects with documented intracranial arterial stenosis were enrolled in the study after obtaining informed consent. Subjects were scanned during two different scan sessions on a 3T Philips Ingenia Scanner (Philips Healthcare, Best, the Netherlands) using a standard head coil. Imaging parameters for TOF MRA were as follows: TR/TE = 14.7/3.5 ms, flip angle = 18°, acquired in-plane resolution = 0.6 mm × 0.6 mm, interpolated in-plane

Results

Sixteen males and eight females were recruited for this study. Subjects included in this study had an age range from 45 to 81, and a mean age of 61.0 ± 9.6.

Intracranial artery structures of each subject were generated using iCafe with manual corrections applied after automated vessel segment, from which the vascular features were extracted. The processing time needed for each case was between 20 min to 1 h. An example of generated artery tracing and extracted features is shown in Fig. 2.

In the

Discussion

In this study assessing a novel, semi-automated method (iCafe) that provides quantitative measurements of intracranial vasculature on TOF-MRA, we found: 1) both stenosis detection and quantification of artery features agree well for inter-scan, intra-operator and inter-operator reproducibility analyses; 2) reproducibility for the lengths of proximal and distal arteries was similar; and 3) reproducibility of the average normalized intensity for the large artery subgroup was similar to the

Conclusion

iCafe is a highly reproducible image analysis tool that can reliably detect locations of stenosis and extract intracranial arterial morphometry and intensity features from TOF MRA to provide both clinical diagnostic assistance and facilitate future investigative quantitative analyses.

List of abbreviations

    TOF

    time-of-flight

    CoW

    circle of Willis

    MRA

    magnetic resonance angiography

    iCafe

    intracranial artery feature extraction

    ICC

    intra-class correlation coefficient

    CV

    coefficient of variation

    MCA

    middle cerebral artery

    ACA

    anterior cerebral artery

    PCA

    posterior cerebral artery

    ICA

    internal carotid artery

    BA

    basilar artery

    VA

    vertebral artery

    Pcomm

    posterior communicating artery

    Acomm

    anterior communicating artery

    OA

    ophthalmic artery

    PPV

    positive predictive values

Ethics approval and consent to participate

This study was approved by institutional review board, and all subjects gave written informed consent prior to enrollment in the study.

Consent for publication

Written informed consent was obtained from all participants for inclusion of their data in publications.

Availability of software

iCafe is available for other groups for non-commercial research under an academic license. Please contact Dr. Chun Yuan ([email protected]) to request an executable file.

Competing interests

The authors declare that they have no competing interests.

Funding

This research was supported by grants from the National Institutes of Health (R01-NS083503, R01-NS092207 and R01-HL103609) and Philips Healthcare.

Authors' contributions

LC developed the iCafe software and wrote the manuscript. LC and QY processed data. MM identified stenosis positions of 8 subjects for comparison. LC, JS, DH did statistical analysis. NB, KP and TH collected image data. MM, JH, CY conceived, directed and advised on the project. All authors read and approved the final manuscript.

Acknowledgements

We are grateful to the support of NVIDIA Corporation with donation of the Titan Xp GPU.

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