Automated Composition Analysis of Thrombus from Endovascular Treatment in Acute Ischemic Stroke Using Computer Vision

Article information

J Stroke. 2022;24(3):433-435

Publication date (electronic) : 2022 September 30

doi : https://doi.org/10.5853/jos.2022.02054

JoonNyung Heo^a, Young Seog^a, Hyungwoo Lee^a, Il Hyung Lee^a, Sungeun Kim^a, Jang-Hyun Baek^b, Hyungjong Park^c, Kwon-Duk Seo^d, Gyu Sik Kim^d, Han-Jin Cho^e, Minyoul Baik^f, Joonsang Yoo^f, Jinkwon Kim^f, Jun Lee^g, Yoon-Kyung Chang^h, Tae-Jin Songⁱ, Jung Hwa Seo^j, Seong Hwan Ahn^k, Heow Won Lee^a, Il Kwon^a,l, Eunjeong Park^l, Young Dae Kim^a,l, Hyo Suk Nam^,a,l

^aDepartment of Neurology, Yonsei University College of Medicine, Seoul, Korea

^bDepartment of Neurology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea

^cDepartment of Neurology, Brain Research Institute, Keimyung University School of Medicine, Daegu, Korea

^dDepartment of Neurology, National Health Insurance Service Ilsan Hospital, Goyang, Korea

^eDepartment of Neurology, Pusan National University School of Medicine, Busan, Korea

^fDepartment of Neurology, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin, Korea

^gDepartment of Neurology, Yeungnam University College of Medicine, Daegu, Korea

^hDepartment of Neurology, Ewha Womans University Mokdong Hospital, Ewha Womans University School of Medicine, Seoul, Korea

ⁱDepartment of Neurology, Ewha Womans University Seoul Hospital, Ewha Womans University School of Medicine, Seoul, Korea

^jDepartment of Neurology, Inje University Busan Paik Hospital, College of Medicine, Inje University, Busan, Korea

^kDepartment of Neurology, Chosun University Hospital, Chosun University College of Medicine, Gwangju, Korea

^lIntegrative Research Center for Cerebrovascular and Cardiovascular Diseases, Seoul, Korea

Correspondence: Hyo Suk Nam Department of Neurology, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea Tel: +82-2-2228-1617 Fax: +82-2-393-0705 E-mail: hsnam@yuhs.ac

Received 2022 June 22; Revised 2022 August 7; Accepted 2022 September 5.

Dear Sir:

Histological analysis of thrombi acquired from endovascular thrombectomy for ischemic stroke provides an unprecedented understanding of thrombus formation in stroke [1]. Composition analysis is currently the mainstream of research for stroke thrombi, and immunohistochemistry (IHC) staining is frequently used [2,3]. Most studies have used general purpose software, including ImageJ and Photoshop (Adobe, San Jose, CA, USA) [4,5]. However, for composition analysis, these tools require manual drawing for area measurement, which is labor-intensive and prone to bias, and the results are irreproducible. This study aimed to develop an open-sourced software named Automated Region-of-interest based Image Analysis (ARIA) for automated composition analysis of IHC-stained thrombi.

This was a retrospective study using a nationwide multicenter prospective registry. The Specialized Multi-center Attributed Registry of sTroke–Clot (SMART-Clot) is a prospective registry that enrolls consecutive patients with acute ischemic stroke from 10 centers in Korea who underwent endovascular thrombectomy. Forty stained slides from 10 randomly selected patients were included in this study. Detailed methodology is described in the Supplementary Methods and Supplementary Figure 1. Screen recordings using both ARIA and traditional method for thrombus image analysis are presented in the Supplementary Video. The accuracy and time needed for analysis were compared between the traditional analysis method and ARIA. Four analysts with varying experiences measured the same 40 slides using both the traditional method and ARIA. External validation was performed for two datasets: (1) anti-CD42b IHC stained slides of stroke thrombi from a previously published study [6] and (2) an open dataset of IHC slides from breast tissue [7]. This study was approved by the Institutional Review Board of Yonsei University College of Medicine (Approval number: 4-2017-0426), and informed consent was obtained from each patient. ARIA is publicly available as an open-sourced project and can be installed in all major operating systems (https://github.com/jnheo-md/aria).

The median age of the patients included in this study was 71.5 years (interquartile range [IQR], 66.2 to 79.8) and six (60.0%) were male (Supplementary Table 1). The results obtained using ARIA by all analysts showed highly accurate results compared to the results from the professional analyst using the traditional method. The Spearman’s correlation coefficient of the stained ratio, defined as the stained area divided by the total area, ranged between 0.913 and 0.916 (all P<0.001) (Table 1). The Bland-Altman analysis showed 95% limits of agreement between 0.11 and 0.14 (Supplementary Figure 2). Agreement of the results from each analyst were significantly higher using ARIA than the traditional method for thrombus area (P=0.005), stained area (P<0.001), and stained ratio (P<0.001) (Table 2 and Supplementary Figure 3). The focused and total times needed for analysis were significantly shorter when ARIA was used than when the traditional method was used (Figure 1 and Supplementary Table 2). The median focused time needed while using ARIA was 7 seconds (IQR, 3.0 to 11.0), whereas the traditional method required a median of 231 seconds (IQR, 182.0 to 286.0; P<0.001). There was disagreement on one sample with homogeneous staining pattern due to differences in thresholding algorithm. There was high correlation, except for that sample with tissue factor staining, and significant analysis time difference between the two methods across each staining method and composition (Supplementary Tables 3 and 4, Supplementary Figure 4). External validation showed high correlation for both stroke thrombi and breast tissue (Spearman’s correlation coefficient 0.929 and 0.875 respectively, both P<0.001) with significant focused time reduction (median 7.0 seconds [IQR, 7.0 to 10.0] vs. 198.0 seconds [IQR, 184.0 to 313.0] in stroke thrombi; and 11.0 seconds [IQR, 8.0 to 13.0] vs. 185.0 seconds [IQR, 165.5 to 217.5] in breast tissue, both P<0.001).

Table 1.

Comparison between stained ratio of each analyst using ARIA and those of the professional analyst using the traditional method

Table 2.

Differences between analysts for ARIA and traditional method

Figure 1.

Comparison of (A) focused time and (B) total time needed for analysis using Automated Region-of-interest based Image Analysis (ARIA) and traditional methodology

This study validated a custom-built software named ARIA developed with computer vision for automated stroke thrombus composition analysis. ARIA (1) was highly accurate; (2) provided consistent results even for analysts without previous experience; and (3) was 30 times faster than the traditional method. Additionally, ARIA produced the same results when the input image and analysis parameters were equal, which is impossible using traditional methods.

Traditional method of composition analysis requires manual demarcation of the thrombus border, which is strenuous and inevitably introduces potential error due to inconsistencies in freehand drawing. ARIA mainly uses the Canny Edge Detection algorithm to replace freehand drawing, which is a widely used technique [8]. Additionally, slide image processing and automatic thresholding have been used in ARIA to reduce unnecessarily burden on the researchers [9,10]. Furthermore, this study demonstrated that the four analysts with varying experiences produced more consistent results when they used ARIA. Considering that the reproducibility and consistency between analysts are critical factors for a research methodology, ARIA has advantages for thrombus analysis over traditional methodologies.

This study has several limitations. The number of samples included in this study was small and originated form a single laboratory. There is no gold standard in measuring the composition of thrombi and the assessment of the accuracy of the novel software is limited. The expert’s analysis result using traditional method does not necessarily represent the true composition of the thrombus. As seen in one sample with exceptional disagreement between methods, thresholding algorithm may have great effect on the results, especially in images with homogeneous texture.

In conclusion, ARIA may be used as an efficient and accurate tool that provides reproducible results in thrombus analysis.