
==== Front
Medicine (Baltimore)
Medicine (Baltimore)
MD
Medicine
0025-7974
1536-5964
Lippincott Williams & Wilkins Hagerstown, MD

39312348
MD-D-24-06369
00049
10.1097/MD.0000000000039787
3
3900
Research Article
Diagnostic Accuracy Study
Insights into multilevel tissue-level collateral status using ColorViz maps from dual data sources in acute ischemic cerebrovascular diseases: A STARD-compliant retrospective study
Zhang Xiaoxiao MD 13645035027@126.com
ab
Liu Qingyu MD 1092347334@qq.com
c
Guo Luxin MS 66936225@qq.com
a
Guo Xiaoxi MS 66936225@qq.com
a
Zhou Xinhua MS 125558121@qq.com
a
Lv Shaomao MD catch.mao@163.com
ab
https://orcid.org/0000-0003-1131-6839
Lin Yu MD abd*
Wang Jinan MD ab
a Department of Radiology, Zhongshan Hospital Affiliated to Xiamen University, School of Medicine, Xiamen University, Xiamen, China
b Xiamen Radiology Quality Control Center, Zhongshan Hospital Affiliated to Xiamen University, School of Medicine, Xiamen University, Xiamen, China
c Department of Ultrasound, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
d Department of Radiology, The First Affiliated Hospital of Fujian Medical University, The First Clinical Medical College of Fujian Medical University, Fuzhou, China.
* Correspondence: Yu Lin, Department of Radiology, Zhongshan Hospital Affiliated to Xiamen University, Xiamen 361004, China (e-mail: 420867402@qq.com).
20 9 2024
20 9 2024
103 38 e3978706 6 2024
22 8 2024
30 8 2024
Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal.

This study aims to explore the utility of ColorViz mapping from dual data sources for assessing arterial collateral circulation and predicting cerebral tissue-level collateral (TLC) in patients with acute ischemic cerebrovascular diseases. A retrospective study was conducted at a single center on a cohort of 79 patients diagnosed with acute ischemic cerebrovascular diseases between November 2021 and April 2022, who had undergone both multi-phase CT angiography (mCTA) and computed tomography perfusion (CTP). The quality of images and arterial collateral status depicted on ColorViz maps from dual data-sets (mCTA and CTP) were assessed using a “5-point scale” and a “10-point scale,” respectively. The status of TLC was evaluated by analyzing multilevel hypoperfusion volume and the hypoperfusion intensity ratio (HIR). The Spearman correlation coefficient was employed to examine the association between arterial collateral status derived from dual data sources and TLC. Receiver operating characteristic curve analysis was used to determine the diagnostic efficacy in detecting large vessel occlusive acute ischemic stroke (LVO-AIS). The ColorViz maps derived from dual data sources facilitated comparable image quality, with over 95% of cases meeting diagnostic criteria, for the evaluation of arterial level collateral circulation. Patients with robust arterial collateral circulation, as determined by dual data sources, were more likely to exhibit favorable TLC status, as evidenced by reductions in hypoperfusion volume (Tmax > 4 seconds, Tmax > 6 seconds, Tmax > 8 seconds, and Tmax > 10 seconds, P < .05) and HIR (Tmax > 6 seconds/4 seconds, Tmax > 8 seconds/4 seconds, Tmax > 10 seconds/4 seconds, and Tmax > 8 seconds/6 seconds, P < .05). The sensitivity and specificity in detecting LVO-AIS was 60.00% and 97.73% for mCTA source maps, while 74.29% and 72.73% for CTP source maps (P > .05 based on De-Long test). In conclusion, this study indicates that ColorViz maps derived from both data sources are equally important in evaluating arterial collateral circulation and enhancing diagnostic efficiency in patients with LVO-AIS, as well as offering insights into the TLC status based on hypoperfusion volume and HIR.

collateral circulation
computed tomography angiography
perfusion
stroke
Natural Science Foundation of Fujian Province 10.13039/501100003392 2022J011343 Yu LinScientific and Technological Planning Project of Xiamen3502Z20184029 Shaomao LvOPEN-ACCESSTRUE
SDCT
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pmc1. Introduction

Acute ischemic stroke (AIS) arises from acute cerebral hemodynamic disturbances, leading to localized ischemic and hypoxic necrosis of brain tissue, posing a significant threat to global human life and health. Notably, large vessel occlusive (LVO)-AIS is distinguished by its swift disease progression, elevated rates of disability and mortality, with occlusion of the middle cerebral artery (MCA) being the predominant manifestation.[1–3] On the contrary, minor ischemic stroke (MIS) and transient ischemic attack (TIA) typically present with less severe neurological impairment, yet may still result in diverse neurological impairments and cognitive deterioration, with a potential for future short-term stroke progression.[4] Hence, it is crucial to promptly and accurately diagnose and stratify the risk of various cerebrovascular diseases.

Arterial level collaterals play a vital role in providing compensatory blood flow for patients with LVO-AIS. Variations in demographic, genetic, and metabolic factors contribute to notable differences in arterial collateral circulation among these patients.[5–7] Prior research has indicated that patients with AIS who exhibit robust arterial collateral circulation tend to experience favorable outcomes following reperfusion therapies, characterized by reduced infarct size and enhanced neurological recovery.[8–11]

Multi-phase CT angiography (mCTA) is utilized for assessing baseline arterial collateralization in AIS patients and can provide insight into the “tissue window” by analyzing the dynamic changes in cerebral blood flow in AIS patients.[9,12–15] In comparison to single-phase CTA (sCTA), mCTA has demonstrated superior accuracy and reliability in assessing arterial collateral status and forecasting clinical outcomes in stroke patients.[7–11,16,17] Nevertheless, the reconstruction and interpretation processes of traditional mCTA are laborious and necessitate significant clinical expertise.[18,19] Currently, the utilization of color-coding in reconstruction aids in the visualization of temporal variations in blood flow characteristics across different mCTA phases of grayscale images.[20,21] The color-coded map, known as ColorViz maps, has been implemented in stroke imaging to display all 3 phases of vascular information into a single set of images.[22,23] In prior clinical settings, the utilization of ColorViz maps has been shown to facilitate rapid assessment of arterial level collateral, bolster diagnostic certainty, and expedite diagnostic efficacy in stroke imaging.[22,24–27]

Computed tomography perfusion (CTP) imaging is frequently utilized in stroke imaging to capture dynamic cerebral blood flow information through multi-phase scanning. The time-to-max (Tmax) maps have emerged as crucial multiparameter maps in CTP examinations, playing a significant role in evaluating perfusion abnormalities in acute, subacute, and chronic ischemic cerebrovascular diseases.[28,29] The most recent study conducted by Christian et al has affirmed that the quality of tissue level collaterals (TLC) appears to be influenced more significantly by the proportion of severe hypoperfusion volume, known as the hypoperfusion intensity ratio (HIR), rather than the total hypoperfusion volume as determined by Tmax.[30–32]

In addition, how to select suitable phases from CTP images for mCTA reconstruction is also a topic that scholars have increasingly focused on in recent years.[33–36] The utilization of CTP images in the reconstruction of mCTA images is anticipated to streamline the scanning procedure in clinical settings by eliminating the need for additional mCTA scans, reducing imaging examination duration, and minimizing radiation exposure and contrast agent administration. Wijngaard et al have validated that CTP images obtained within an 11 to 21 second time frame following the initial passage of contrast agent in the internal carotid artery are optimal for the peak artery phase of mCTA reconstruction.[35] While the selection of appropriate delay phases (peak venous phase and delay venous phase) from CTP images can aid in preventing underestimation of the true extent of arterial level collateral in conventional mCTA reconstruction and ColorViz map generation, the available evidence supporting this practice is scarce. Furthermore, additional research is required to confirm the image quality, clinical feasibility, diagnostic accuracy, and correlation with HIR of the CTP-based ColorViz map generation.

Therefore, this study seeks to examine the clinical viability of producing ColorViz maps from CTP data, assess the quality of ColorViz maps generated from dual data sources (mCTA and CTP), investigate the relationship between arterial collateral score on ColorViz maps and TLC parameters (hypoperfusion volume and HIR) on Tmax maps, and explore the potential diagnostic effectiveness of ColorViz maps derived from CTP in detecting LVO-AIS.

2. Methods

2.1. Clinical data

Patients who were suspected to have acute cerebrovascular disease between November 2021 and April 2022 of our university hospital were consecutively enrolled in this retrospective study, which was approved by the ethics committee of Zhongshan Hospital Affiliated to Xiamen University and followed the STARD guidelines for reporting of diagnostic accuracy. Informed consent was obtained from all participants or their close relative. Baseline demographic information, including gender, age, National Institutes of Health Stroke Scale (NIHSS) scores, and time from symptom onset to imaging was collected for all patients. Additionally, available follow-up digital subtraction angiography (DSA) images or diffusion-weighted images (DWI) were also retrospectively evaluated.

The study’s inclusion criteria comprised individuals aged 18 years or older who had undergone non-contrast-enhanced CT, mCTA and CTP examinations prior to treatment, had time from symptom onset to treatment of ≤72 hours, and had received a clinical diagnosis of AIS (including LVO-AIS and MIS) or TIA. Exclusion criteria included individuals with unclear diagnosis or hemorrhagic disease, as well as those with poor image quality or incomplete raw data. Subsequent DSA or DWI were utilized to confirm an accurate diagnosis.

2.2. CT examination

All patients who were enrolled in the study underwent CT scans using a 256 row CT scanner (Revolution CT, GE Healthcare, Chicago, IL). The detailed scanning protocols for mCTA and CTP can be found in Supplementary digital content, Supplemental Digital Content, http://links.lww.com/MD/N611.

2.3. Automated CTP image reconstruction

The CTP images, consisting of a total of 736 images across 23 phases, were analyzed using the “Digital Brain” platform (CerebralDoc, Shukun Technology, China). The platform automatically generated time density curves (TDC) for cerebral arteries and veins and Tmax maps.

Different levels of hypoperfusion volume areas were automatically defined, segmented, and calculated based on 4 distinct cutoff values of “Tmax > 4 seconds,” “Tmax > 6 seconds,” “Tmax > 8 seconds,” and “Tmax > 10 seconds.” Multilevel HIRs were calculated based on the ratio of 2 distinct hypoperfusion volumes.

2.4. Optimal CTP phase selection

To ascertain the appropriate CTP phase for further ColorViz map reconstruction, a retrospective analysis of 10 patients was undertaken. Various combinations of CTP phases were reconstructed and evaluated based on the TDC, leading to the sequential determination of the optimal phases for peak arterial phase, peak venous phase, and late venous phases for ColorViz map reconstruction. The detailed methodology is provided in Supplementary digital content, Supplemental digital content, http://links.lww.com/MD/N611.

2.5. Color-coded reconstruction of mCTA and CTP

The ColorViz mapping reconstruction methodology relies on images obtained from 3 distinct phases (arterial peak phase, peak venous phase, and late venous phase) acquired through mCTA and CTP using the a commercially available software package (FastStroke, GE Healthcare, Chicago, IL).

2.6. Image quality evaluation of ColorViz maps

In order to assess the viability and dependability of ColorViz maps derived from dual data sources (mCTA and CTP) for clinical utilization, 2 radiologists conducted an independent analysis utilizing a criteria-based “5-point scale” with a 2-week interval.[37] A consensus evaluation will be conducted in case of discordant ratings. This evaluation encompasses the assessment of proximal cerebral artery, distal cerebral artery, deep cerebral vein, superficial cerebral vein, and overall quality. Details regarding the evaluations of image quality were available in Supplementary digital content, Supplemental Digital Content, http://links.lww.com/MD/N611.

2.7. Collateral scoring of ColorViz maps

The arterial-level collateral scores of the affected side on ColorViz maps generated from dual data sources were analyzed independently. Two radiologists, who were blinded to the clinical information, assessed the collateral scores using a 10-point scale.[38] In cases where there were discrepancies in ratings, a consensus evaluation was performed. Additional detailed information can be found in Supplementary digital content, Supplemental Digital Content, http://links.lww.com/MD/N611.

2.8. Collateral scoring of DSA

For LVO-AIS patients, a collateral scoring of DSA images was performed by applying the American Society of Interventional and Therapeutic Neurology/Society of Interventional Radiology scoring system.

2.9. Subgroup analysis

In order to mitigate the effects of significant heterogeneity in the clinical characteristics of the enrolled patients, subsequent subgroup analyses were performed utilizing NIHSS scores (mild stroke: NIHSS score of 0 to 4; severe stroke: NIHSS score of 5 or higher), time from symptom onset to imaging (early time window: ≤24 hours; late time window: >24 hour), large vessel occlusion (LVO) status (LVO-AIS; none-LVO-AIS) as criteria for classification. The collateral scores derived from ColorViz maps from 2 distinct data sources were compared between patients within each subgroup. Additionally, correlations between ColorViz map scores and TLC status or NIHSSS score were examined within each subgroup.

2.10. Statistical analysis

Statistical analysis was conducted using SPSS Statistics software (v26.0, IBM, Armonk, NY). The inter-group correlation coefficient (ICC) were used to analyze the inter observer consistency of quantitative data. The comparison of 3 groups of quantitative data was conducted using one-way analysis of variance or Kruskal–Wallis H-test. The comparison of 2 groups of quantitative data was conducted using Student t test or Mann Whitney U-test. The Wilcoxon test was used to compare the quantitative data between 2 paired samples. Qualitative data were compared using Chi-square test or Fisher exact test. Spearman correlation coefficient was used to analyze the correlation between different quantitative data. The strength of correlation can be categorized as follows: 0.8 to 1.0 indicates a very strong correlation, 0.6 to 0.8 indicates a strong correlation, 0.4 to 0.6 indicates a moderate correlation, 0.2 to 0.4 indicates a weak correlation, and 0.0 to 0.2 indicates a very weak or no correlation. Receiver operating characteristic (ROC) curve and Hosmer–Lemeshow test was used to determine the diagnostic efficacy and calibration of the original ColorViz collateral scores and adjusted ColorViz collateral scores (adjusted by the patients’ NIHSS scores prior to treatment); Furthermore, De-Long test was used to compare the area under curve (AUC) of ROC curves for different diagnostic parameters. P < .05 indicates significant difference.

3. Results

3.1. Clinical information

Two hundred eight patients with available mCTA and CTP scans were eligible for the study. Seventy-nine patients (35 cases with LVO-AIS, 31 cases with MIA and 13 cases with TIA) ultimately included in our study (Table 1). The baseline NIHSS score showed significant differences among groups (P < .05) while LVO-AIS patients represented a most elevated scores.

Table 1 Demographic data and collateral score of the patients (n = 79).

Characteristic	AIS (n = 66)	TIA
(n = 13)	P value	
LVO (n = 35)	MIS (n = 31)	
Age (year, mean ± SD)	63.43 ± 14.96	69.45 ± 12.45	64.08 ± 13.77	.191	
Male gender (n, %)	26, 74.29	22, 70.97	10, 76.92	.909	
NIHSS score [median (IQR)]	8 (3, 12)	3 (1, 7)	0 (0, 1)	<.001*	
Time from symptom onset to imaging [median (IQR)]	15 (7, 45)	9 (5, 26)	47 (31, 50)	.033*	
Site of artery occlusion (n, %)					
 Internal carotid artery	8, 22.85	N/A	N/A	N/A	
 Anterior cerebral artery	2, 5.71	N/A	N/A	N/A	
 Middle cerebral artery†	19, 54.29	N/A	N/A	N/A	
 Posterior cerebral artery	1, 2.86	N/A	N/A	N/A	
 Vertebral-basilar artery	5, 14.29	N/A	N/A	N/A	
Arterial-level collateral score
[median (IQR)]					
 ColorViz maps from mCTA	7 (6, 9)	9 (9, 10)	10 (9, 10)	<.001*	
 ColorViz maps from CTP	8 (6, 9)	9 (8, 10)	9 (9, 10)	<.001*	
 DSA (ASITN/SIR)	3 (2, 4)	N/A	N/A	N/A	
AIS = acute ischemic stroke, ASITN/SIR = American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology, CTP = computed tomography perfusion, DSA = digital subtraction angiography, IQR = interquartile range, LVO = large vessel occlusion, mCTA = multi-phase computed tomography angiography, MIS = minor ischemic stroke, N/A = not applicable, NIHSS = National Institutes of Health Stroke Scale, SD = standard deviation, TIA = transient ischemic attack.

† If both the middle cerebral artery and the internal carotid artery are occluded simultaneously, the responsible vessel is recorded as the middle cerebral artery.

* Significant difference.

3.2. Optimal phase for CTP-based reconstruction

In the phase selection for peak artery phase of mCTA based on CTP images, 8 patients (8/10, 80%) obtained the best image quality based on “A-peak phase (CTP phase corresponding to the peak of arterial TDC),” and 2 patients (2/10, 20%) obtained the best image quality based on “A-peak-1 phase” (Fig. 1).

Figure 1. Firstly, select “A-peak” phase (corresponding to the peak of arterial time density curve), “A-peak-1” phase (the phase preceding “A-peak”) and “A-peak + 1” phase (the phase following “A-peak”) for the peak arterial phase determination. Subsequently, designate the “A-peak + 4” phases for peak venous phase and the “D-plateau” phase for late venous phase (corresponding to the point at which the arterial and venous time density curve begin to decline and approach a plateau) for late venous phase (A). ColorViz maps were reconstructed utilizing various combinations of “A-peak-1, A-peak + 4, D-plateau (B),” “A-peak, A-peak + 4, D-plateau (C),” and “A-peak + 1, A-peak + 4, D-plateau (D)” CT images. The 3 sets of images are capable of meeting the diagnostic criteria. Figure B exhibits a lack of detail in arterial anatomy compared to Figure C (orange arrows), while Figure D displays certain artifacts in the contralateral artery (yellow arrows).

In the phase selection for peak venous phase based on CTP images, 10 patients (10/10, 100%) obtained the best image quality based on “A-peak + 4 phase” reconstruction (Fig. 2).

Figure 2. Firstly, utilize “A-peak + 3” phase, “A-peak + 4” phase, and “A-peak + 5” phase for the peak venous phase determination. Subsequently, designate the “A-peak” phase for the peak arterial phase and the “D-plateau” phase for the late venous phase (A). ColorViz maps were reconstructed utilizing various combinations of “A-peak, A-peak + 3, D-plateau” (B), “A-peak, A-peak + 4, D-plateau” (C), “A-peak, A-peak + 5, D-plateau” (D). The 3 sets of images are capable of meeting the diagnostic criteria. Among them, with Figure C providing the most detailed depiction of vascular anatomy and delayed blood flow (orange arrows).

In the phase selection for late venous phase based on CTP images, 7 patients (7/10, 70%) obtained the best image quality based on “D-plateau + 1 phase,” and 3 patients (3/10, 30%) obtained the best image quality based on “D-plateau phase” (Fig. 3).

Figure 3. Firstly, choose the “D-plateau-1,” “D-plateau,” and “D-plateau + 1” phases for the late venous phase determination. Subsequently, designate the “A-peak” phase for the peak arterial phase and the “A-peak + 4” phase for the peak venous phase (A). ColorViz maps were reconstructed utilizing various combinations of “A-peak, A-peak + 4, D-plateau-1” (B), “A-peak, A-peak + 4, D-plateau” (C), “A-peak, A-peak + 4, D-plateau + 1” (D). The 3 sets of images are capable of meeting the diagnostic criteria, figure D demonstrating the most effective discrimination between arteries and veins (orange arrows).

3.3. Quality evaluation of ColorViz maps

The image quality score of 3 to 5 points (meeting diagnostic requirements) were discovered in over 95% cases for reconstructed ColorViz maps from dual data sources (mCTA data sources or CTP data sources, Figs. 4 and 5). The proportion of CTP-based ColorViz map with “excellent (5 points)” overall image quality (36 cases, 45.57 %) is slightly lower than that for mCTA-source map (45 cases, 56.96 %). After subgroup score comparison, the image quality of distal cerebral arteries and superficial cerebral veins is lower than that of proximal cerebral artery and deep cerebral vein on ColorViz map regardless of data sources (all P < .05, Table 2).

Table 2 Quality evaluation of ColorViz map reconstructed from mCTA and CTP.

Image quality of
ColorViz map	mCTA-based score
[median (IQR)]	CTP-based score
[median (IQR)]	P value	
Proximal cerebral artery	5 (5, 5)	5 (4, 5)	<.001*	
Distal cerebral artery	4 (4, 5)	4 (4, 4)	.032*	
Superficial cerebral vein	4 (3, 4)	4 (3, 4)	.881	
Deep cerebral vein	5 (4, 5)	5 (4, 5)	.079	
Overall quality	5 (4, 5)	4 (4, 5)	.078	
CTP = computed tomography perfusion, mCTA = multi-phase computed tomography angiography.

* Significant difference.

Figure 4. The image quality score of the ColorViz map was assessed using data from multi-phase CT angiography (A) and CT perfusion (B).

Figure 5. The volume rendering image (A) indicated occlusion of the left proximal middle cerebral artery, while the Tmax map (B) revealed varying degrees of hypoperfusion within the left middle cerebral artery territory (blue: Tmax > 4 seconds; green: Tmax > 6 seconds; yellow: Tmax > 8 seconds). Utilizing the ColorViz maps derived from multi-phase CT angiography data source (C) and CT perfusion data source (D), collateral vessels distal to the occluded artery were visualized, demonstrating correspondence with the hypoperfusion areas on Tmax map. Specific artifacts are present on the ColorViz map derived from CT perfusion data when visualizing the distal artery and superficial vein (orange arrows).

Strong inter-observer consistencies were discovered in ColorViz maps regardless of the data source (mCTA data sources: ICC = 0.972, 95% CI = 0.956–0.982; CTP data sources: ICC = 0.926, 95% CI = 0.885–0.953).

3.4. Correlations between ColorViz maps and DSA

For LVO-AIS patients, strong positive correlations were discovered between collateral scores of ColorViz maps and American Society of Interventional and Therapeutic Neurology/Society of Interventional Radiology scores of DSA images (mCTA data source: ρ = 0.728, P < .001; CTP data source: ρ = 0.673, P < .001, Fig. 6).

Figure 6. The ColorViz maps (A and B) generated from CT perfusion imaging effectively demonstrate the presence of collateral vessels distal to the occluded artery, as indicated by a collateral circulation score of 4 points. This finding aligns with the collateral flow observed in digital subtraction angiography images (C and D), which yielded an ASTIN/SIR score of 2 points. ASITN/SIR = American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology.

3.5. ColorViz collateral score in predicting TLC

There were strong negative correlations between the hypoperfusion volumes (Tmax > 4 seconds, Tmax > 6 seconds, and Tmax > 8 seconds) and arterial-level collateral scores of ColorViz maps reconstructed from mCTA and CTP (All P < .05, Fig. 5 and Table 3). The HIR ratios (Tmax > 6 seconds/4 seconds, Tmax > 8 seconds/4 seconds, Tmax > 10 seconds/4 seconds, and Tmax > 8 seconds/6 seconds) and collateral scores of ColorViz maps regardless of the data source also showed strong negative correlations (all P < .05, Table 4).

Table 3 Correlation between arterial-level collateral score and hypoperfusion volume.

Hypoperfusion volume	Arterial-level collateral score	
mCTA-based ColorViz maps	CTP-based ColorViz maps	
ρ value	P value	ρ value	P value	
Tmax > 4 seconds	‐0.674	<.001*	‐0.673	<.001*	
Tmax > 6 seconds	‐0.701	<.001*	‐0.658	<.001*	
Tmax > 8 seconds	‐0.695	<.001*	‐0.704	<.001*	
Tmax > 10 seconds	‐0.570	<.001*	‐0.573	<.001*	
CTP = computed tomography perfusion, mCTA = multi-phase computed tomography angiography, Tmax = time to maximum.

* Significant difference.

Table 4 Correlation between arterial-level collateral score and HIR.

HIR	Arterial-level collateral score	
mCTA-based ColorViz maps	CTP-based ColorViz maps	
ρ value	P value	ρ value	P value	
Tmax > 6 seconds/4 seconds	‐0.688	<.001*	‐0.598	<.001*	
Tmax > 8 seconds/4 seconds	‐0.685	<.001*	‐0.700	<.001*	
Tmax > 10 seconds/4 seconds	‐0.512	<.001*	‐0.544	<.001*	
Tmax > 8 seconds/6 seconds	‐0.634	<.001*	‐0.674	<.001*	
Tmax > 10 seconds/6 seconds	‐0.448	.003*	‐0.506	.001*	
Tmax > 10 seconds/8 seconds	‐0.232	.265	‐0.210	.313	
CTP = computed tomography perfusion, HIR = hypo-perfusion intensity ratio, mCTA = multi-phase computed tomography angiography, Tmax = time to maximum.

* Significant difference.

3.6. Diagnostic performance of ColorViz collateral score

Based on the ROC curve analysis, the sensitivity, specificity, and AUC for detecting LVO-AIS was 60.00%/80.00%, 97.73%/86.36%, and 0.857/0.887 for mCTA source ColorViz collateral scores before and after adjustment, while the sensitivity, specificity, and AUC were 74.29%/68.57%, 72.73%/93.18%, and 0.814/0.871 for CTP source scores before and after adjustment (Table 5). The diagnostic performance of ColorViz maps reconstructed from dual data sources in detecting LVO-AIS is similar based on the De-Long test (P = .255). The Hosmer–Lemeshow test showed a good fit for ColorViz collateral scores regardless of data sources (all P > .05).

Table 5 ROC curve analysis of arterial-level collateral score of ColorViz maps from dual data source for detecting LVO-AIS.

Parameters	AUC	95% CI	YI	Criterion	Sensitivity	Specificity	
Arterial-level collateral score							
 ColorViz maps from mCTA	0.857	0.761–0.926	0.470	≤8	60.00%	97.73%	
 ColorViz maps from CTP	0.814	0.710–0.892	0.470	≤8	74.29%	72.73%	
Adjusted collateral score*							
 ColorViz maps from mCTA	0.887	0.796–0.947	0.664	NA	80.00%	86.36%	
 ColorViz maps from CTP	0.871	0.777–0.936	0.618	NA	68.57%	93.18%	
95% CI = 95% confidence interval, AIS = acute ischemic stroke, AUC = area under the curve, CTP = computed tomography perfusion, mCTA = multi-phase computed tomography angiography, NA = not applicable, ROC = receiver operating characteristic, YI = You-den Index.

* Adjusted by the patients’ NIHSS scores prior to treatment.

3.7. Subgroup analysis

The collateral scores obtained from ColorViz maps using data from 2 distinct sources exhibited significant differences between groups with mild (n = 44) and severe (n = 35) strokes, and between groups with LVO-AIS (n = 35) and none-LVO-AIS (n = 44) (all P < .05). However, the arterial-level collateral scores obtained from dual data sources exhibited no significant differences between groups with early (n = 47) and late (n = 32) time window (both P > .05). Strong negative correlations were observed between the HIR parameters (including Tmax > 6 seconds/4 seconds, Tmax > 8 seconds/4 seconds, Tmax > 10 seconds/4 seconds, Tmax > 8 seconds/6 seconds, Tmax > 10 seconds/6 seconds, and Tmax > 10 seconds/8 seconds for patients with severe strokes; including Tmax > 8 seconds/4 seconds, Tmax > 10 seconds/4 seconds, Tmax > 8 seconds/6 seconds for patients with LVO-AIS) and the ColorViz collateral scores from dual data source (all P < .05). Strong negative correlations were observed between the NIHSS score and the ColorViz collateral scores from dual data source for patients with severe strokes or LVO-AIS (All P < .05). However, a very weak to moderate correlation was identified between HIR parameters (excluding Tmax > 6 seconds/4 seconds) and ColorViz collateral scores in patients with mild strokes or none-LVO-AIS. Furthermore, strong negative correlations were observed between the HIR parameters (including Tmax > 6 seconds/4 seconds, Tmax > 8 seconds/4 seconds, and Tmax > 8 seconds/6 seconds) and the ColorViz collateral scores, irrespective of the data source and time-window (all P < .05).

4. Discussion

The findings of the study suggest that utilizing color-coding reconstruction from both data sources (mCTA and CTP) can produce ColorViz maps that align with diagnostic standards. Additionally, the arterial collateral score determined from ColorViz images sourced from diverse data sets may be indicative of multi-level TLC characteristics in the impacted brain tissue. Furthermore, the arterial collateral circulation scores acquired from ColorViz maps originating from differing data sources can aid in the accurate identification of LVO-AIS lesions.

Phase selection played a crucial role in the ColorViz map reconstruction process utilizing CTP data in our study. The choice of peak artery phase primarily impacted the visualization of arterial structures, whereas the selection of peak venous phase and late venous phase primarily influenced the display of venous structures and delayed-enhanced collateral vessels. Optimal phase selection is essential for achieving adequate density contrast between vascular structures during peak arterial and venous phases, thereby minimizing the occurrence of color mixing associated with phase selection.

Although the image quality of both sets of ColorViz maps generated from dual data sources (mCTA and CTP) is deemed sufficient for clinical purposes, our analysis revealed disparities between the 2 sets. Specifically, the ColorViz maps derived from mCTA images exhibited higher overall image quality scores compared to those generated from CTP images. These discrepancies in image quality may be attributed to variations in CT scanning parameters and phase selection strategies employed for each data source.

Furthermore, it was observed that ColorViz maps, irrespective of the data source utilized (mCTA or CTP), exhibit deficiencies in accurately representing distal arterial branches or superficial veins. This limitation may be attributed to the comparable density of the enhanced blood vessels and adjacent skull bones, rendering them less distinguishable by the software. The assessment of distal arterial branches and superficial veins through imaging also holds particular significance in the context of diagnosing and prognosticating cerebrovascular diseases.[31,32,39,40] Therefore, it is imperative for FastStroke software or comparable software platforms to promptly undergo upgrades in order to enhance the visualization of vascular structures proximal to the skull.

Our research suggests that the arterial-level collateral score on ColorViz maps has potential utility in predicting downstream TLC characteristics. Our findings indicate that the variation in regional arterial collateral circulation may be a key factor in explaining the multi-level HIR derived from CTP within individuals, which is influenced by blood flow gradients. Besides, the formation and progression of edema are recognized to significantly influence regional collateral blood flow both prior to and following thrombectomy, thereby impacting microvascular blood transit through ischemic cerebral tissue, as illustrated by multi-level HIR in our study.[41,42] Additionally, specific thrombus characteristics, such as thrombus burden and perviousness, could be associated with arterial collateral status, consequently affecting the HIR level in patients of our cohort.[43]

Conventionally, HIR has been defined as a single ratio of Tmax > 10 seconds/Tmax > 6 seconds.[44] However, the clinical importance of other Tmax threshold-defined ischemic areas has been pointed out by scholars in recent years. For example, the volume of tissue with a perfusion delay of Tmax > 4 seconds is thought to represent benign oligemia and is dependent on the patient’s arterial-level collateral status.[45,46] In clinical practice, we noticed that some LVO-AIS patients may not even have a Tmax > 10 seconds region in the baseline examination, but these patients might still have severe clinical symptoms and require aggressive reperfusion therapy. Therefore, in order to achieve a comprehensive evaluation of the TLC status of ischemic brain tissue in patients with different severity levels, our study have assessed various Tmax thresholds and ratio combinations to facilitate multi-level HIR. The multi-level HIR constructed in this study is a useful supplement to the fixed HIR indicator (Tmax > 10 seconds/Tmax > 6 seconds), and is expected to provide more detailed evaluation of intracranial TLC in future studies.

In addition to the HIR parameters, indicators such as relative cerebral blood flow (rCBF)-based ischemic core volumes, the cerebral blood volume (CBV) index, and Tmax based compensation index (CI) have also been used in recent studies for the comprehensive evaluation of TLC in ischemic brain tissue.[46–49] Specifically, the rCBF map has emerged as a preferred tool for estimating the ischemic core at the threshold of rCBF < 30% and could be visualized and quantified by major automated CTP software package.[47] Ischemic core volumes based on rCBF thresholds have shown prognostic ability for functional outcome following mechanical thrombectomy.[48] Karamchandani et al recently introduced the CBV index as the average CBV in Tmax > 6 seconds region compared to the average CBV in contralateral normal brain.[46,49] Lakhani et al present CI as the volume of Tmax > 4 seconds divided by the volume of Tmax > 6 seconds as a novel quantitative pretreatment collateral biomarker.[46] Likewise, both the CBV index and CI parameters have each shown a correlation with final infarct core and with clinical outcomes. The intrinsic link between the aforementioned quantitative TLC indicators and the arterial level collateral score on ColorViz maps still needs further exploration.

Consistent with our results, Mohammed et al observed that the proportion of collateral vessels on both sCTA and mCTA images of AIS patients can also predict CTP parameters effectively.[50] Similarly, Almekhlafi et al[51] demonstrated that AIS patients who underwent screening with mCTA exhibited comparable clinical outcomes to those screened with CTP. Besides, the mCTA ColorViz maps displayed superior discriminatory ability and reduced information loss comparing to conventional sCTA.[20,21,25] Thus, it is plausible to suggest that ColorViz maps may encompass data pertaining to both arterial-level collateral circulation and TLC, thereby potentially serving as a valuable tool for guiding treatment decisions and evaluating prognosis in individuals with acute ischemic cerebrovascular disease.

The collateral scores on ColorViz maps from both data sources demonstrated a strong correlation with DSA collateral scores in LVO-AIS cases. The mCTA scanning offers images at 3 distinct time points, providing a temporal resolution comparable to that of DSA (arterial phase, capillary phase, and venous phase), enabling a comprehensive assessment of the hemodynamic properties of cerebral blood vessels at different anatomical levels. While DSA remains the preferred method for cerebrovascular assessment, it is important to acknowledge its limitations, including the complexity of intervention procedures and the potential for overlapping grayscale images in DSA imaging.[52] Hence, ColorViz maps generated from mCTA or CTP images could potentially be utilized as alternative modalities to DSA for assessing cerebral collateral circulation.

In this study, analysis of the ROC curve among all patients indicates that the ColorViz reconstruction and arterial collateral circulation score are valuable tools for detecting AIS of varying severity levels, including LVO-AIS and non-LVO-AIS. These methods demonstrate a high diagnostic efficiency, with an AUC exceeding 0.8 regardless of data source, suggesting their potential utility in emergency stroke imaging practices. Byrne et al have highlighted the significance of “delayed vessel signs” observed on conventional mCTA grayscale images. These signs not only facilitate the precise localization and determination of the extent of LVO-AIS, but they also have the potential to aid in the assessment of distal vascular abnormalities. This underscores the crucial clinical importance of both peak and delayed venous phases of mCTA in the comprehensive analysis of arterial-level collateral circulation.[53] ColorViz reconstruction, which is grounded in the principles of human vision, employs visually recognizable color images to intuitively depict the hemodynamic information encoded in mCTA. This approach significantly enhances the detection rate of “delayed vessel signs” in AIS patients, thereby playing a crucial role in the rapid and precise identification of severe LVO-AIS cases. This advancement holds immense significance for the risk stratification management of stroke patients, enabling more informed and targeted treatment decisions.[21,22,25] AIS cases involving distal MCA occlusion are often associated with a high misdiagnosis rate, necessitating the use of additional DWI scanning for accurate diagnosis in clinical practice. The limited number of cases analyzed in this study nonetheless indicates that the ColorViz map can assist in sensitively detecting “color delayed vessel signs” with high correlation with DWI performance in patients with distal MCA occlusion, as demonstrated in Figure 7.

Figure 7. The ColorViz map generated from CT perfusion imaging (A) provides a visual representation of distal middle cerebral artery occlusion through the observation of the “color delayed vessel sign” (orange circle). The Tmax image (B) illustrates hypoperfusion areas in the left frontal lobe, with varying colors indicating different levels of delay in perfusion (blue: Tmax > 4 seconds; green: Tmax > 6 seconds; yellow: Tmax > 8 seconds; red: Tmax > 10 seconds). Diffusion weighted imaging (C) confirms the presence of hyperintense areas in the left frontal lobe.

In the subgroup analysis stratified by patient severity or LVO status, individuals with lower NIHSS scores or without LVO exhibited significantly elevated ColorViz collateral scores, indicating that the visual assessment of arterial-level collateral characteristics through mCTA and CTP imaging modalities can effectively delineate the clinical severity of patients. Moreover, the ColorViz collateral scores are especially effective in determining the TLC status in patients with severe stroke or LVO-AIS, while their predictive accuracy is diminished in patients with mild symptoms. This discrepancy may be attributed to the overall heightened levels of arterial collateral circulation and TLC in mild cases with minimal hypoperfusion volume. Meanwhile, despite the inherent susceptibility of TLC to fluctuations or deterioration over time, strong negative correlations were consistently observed between TLC and ColorViz collateral scores, regardless of the time window considered. This finding suggests that, across patients with varying onset times, TLC and arterial collateral status may exhibit a synchronous trend and interact with each other during the progression of stroke.

Recent studies have extensively investigated both arterial-level collaterals, as indicated by the mCTA-based collateral score, and TLC, as indicated by the CTP-based metric. These parameters have been found to be associated with early infarct growth and long-term clinical recovery in stroke patients.[5,22,31,54–59] Consequently, the ColorViz collateral score, derived from dual data sources in our study, demonstrates the capability to predict TLC levels both swiftly and effectively, while also serving as a potential tool for evaluating treatment efficacy and clinical prognosis in stroke patients. Similarly, patients experiencing TIA frequently present with varying levels of chronic stenosis in the carotid and vertebral arteries, which is often mitigated by compensatory collateral flow.[60] Furthermore, the patency of collateral arteries is critically important for the progression of TIA, the risk of subsequent stroke, and overall clinical outcomes.[61] Therefore, evaluating arterial collateral circulation and TLC in TIA patients using the ColorViz map may hold significant clinical value. This warrants further investigation in future studies, particularly within specialized disease cohorts.

5. Limitations

There are still some limitations in this study: (1) This study is a retrospective single-center study, and the included cases may inevitably have selection bias. (2) This study included AIS and TIA patients with varying severity, resulted in confounding bias in clinical and imaging features. (3) Although the criteria-based scale and consensus assessment were applied, the evaluation of image quality or collateral score may be influenced by the subjected factors of the raters. (4) Due to TLC status can be fluctuating and strongly deteriorated over time, finer control of time variables is of great significance in correcting offsets and can ensure the accuracy and reliability of future research. (5) There exist other numerous influencing factors for the association between TLC and arterial collateral circulation, necessitating further investigation into the potential influence of venous outflow and various clinical indicators.

6. Conclusion

In conclusion, our study suggests that color-coded reconstructions utilizing dual data sources (mCTA and CTP) exhibit comparable efficacy and reliability in assessing arterial-level collateral, predicting TLC, and identifying patients with LVO-AIS in the realm of emergency stroke imaging. The implementation of CTP scans with ColorViz map reconstructions may aid in streamlining stroke imaging protocols and facilitating a thorough evaluation of collateral circulation status.

Acknowledgments

We sincerely thank Dr Suping Chen of GE Healthcare, Shanghai, China, for providing technical support.

Author contributions

Conceptualization: Yu Lin.

Data curation: Xiaoxiao Zhang, Qingyu Liu, Yu Lin.

Formal analysis: Qingyu Liu, Yu Lin.

Investigation: Qingyu Liu, Luxin Guo, Xinhua Zhou, Shaomao Lv.

Methodology: Xinhua Zhou, Shaomao Lv.

Software: Luxin Guo, Xinhua Zhou.

Supervision: Xinhua Zhou, Jinan Wang.

Visualization: Xiaoxi Guo, Shaomao Lv, Yu Lin.

Writing – original draft: Xiaoxiao Zhang, Yu Lin.

Writing – review & editing: Xiaoxiao Zhang, Xiaoxi Guo, Yu Lin, Jinan Wang.

Supplementary Material

Abbreviations:

AIS acute ischemic stroke

AUC area under curve

CBV cerebral blood volume

CI compensation index

CTP computed tomography perfusion

DSA subtraction angiography

DWI diffusion-weighted image

HIR hypoperfusion intensity ratio

ICC inter-group correlation coefficient

LVO large vessel occlusion

MCA middle cerebral artery

mCTA multi-phase computed tomography angiography

NIHSS National Institutes of Health Stroke Scale

rCBF relative cerebral blood flow

ROC receiver operating characteristic

sCTA single-phase computed tomography angiography

TDC time density curves

TIA transient ischemic attack

TLC tissue level collaterals

This study has received funding from the Natural Science Foundation of Fujian Province (grant number 2022J011343) to Dr. Yu Lin, and the Scientific and Technological Planning Project of Xiamen (grant number 3502Z20184029) to Dr. Shaomao Lv.

The authors have no conflicts of interest to disclose.

The datasets generated during and/or analyzed during the current study are not publicly available, but are available from the corresponding author on reasonable request.

Supplemental Digital Content is available for this article.

How to cite this article: Zhang X, Liu Q, Guo L, Guo X, Zhou X, Lv S, Lin Y, Wang J. Insights into multilevel tissue-level collateral status using ColorViz maps from dual data sources in acute ischemic cerebrovascular diseases: A STARD-compliant retrospective study. Medicine 2024;103:38(e39787).

XZ and QL contributed equally to this work.
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