Table 3.

Seven technologies are indicated to analyze CTP images. The majority of studies were retrospective. Algorithms are able to predict final infarct volume and/or assess the quality of collateral perfusion, and algorithm performance met or exceeded human performance in binary and multiclass classification. ICH location (e.g., under the calvaria) and anatomical variations (e.g., calcification of the falx) reduced algorithm performance. Human performance generally continues to be the gold standard for evaluating these algorithms. CBF: Cerebral Blood Flow; CBV: Cerebral Blood Volume; MTT: Mean Transit Time; SVD: Singular Value Decomposition.

Device	Author, Year	Level of Evidence	Dataset Characteristics	Sample Size (Scans)	AUC	PPV	NPV	Accuracy	Sensitivity	Specificity	Other Metrics/Comments
Vitrea CT Brain Perfusion	Rava et al., 2020 [47]	Retrospective	Proprietary, Single Center	105	-	-	-	-	-	-	In estimating infarct volume, Spearman correlation coefficient between Vitrea and DWI/FLAIR ranged from 0.71 to 0.77. Vitrea outperformed RAPID.
	Rava et al., 2020 [48]	Retrospective	Proprietary, Single Center	107	-	-	-	-	-	-	In estimating infarct volume, Spearman correlation coefficient between different algorithms within Vitrea (i.e., Bayesian and Singular Value Decomposition) and FLAIR MRI was 0.98 vs. 0.76-0.87 between RAPID and FLAIR MRI.
	Rava et al., 2021 [49]	Retrospective	Proprietary, Single Center	63	-	63–72%	-	-	-	-	-
	Rava et al., 2021 [59]	Retrospective	Proprietary, Single Center	108	-	-	-	96–98%	60–62%	98–99%	Vitrea overestimated infarct volume, but provided the most accurate penumbra assessment for patients treated conservatively.
	Ichikawa et al., 2021 [60]	Retrospective	Proprietary, Single Center	36	-	-	-	-	-	-	Vitrea’s Bayesian algorithm had better delineation of abnormal perfusion areas and estimation of infarct volume compared to the SVD implementation.
RAPID (CTP)	Hokkinen et al., 2021 [40]	Retrospective	Proprietary, Single Center	89	-	-	-	-	-	-	In patients presenting 6 to 24 hours from onset of symptoms, CTP-RAPID’s estimate of infarct volume correlated with follow-up imaging (r = 0.82). Correlation decreased (r = 0.58) in patients presenting 0 to 6 hours after symptom onset.
	Wouters et al., 2021 [42]	Randomized Controlled Trial	MR CLEAN trial & CRISP study, Multicenter	127	-	-	-	-	-	-	A new deep learning CNN model outperformed RAPID in predicting final infarct volume.
	Potreck et al., 2021 [43]	Retrospective	Simulation	53	-	-	-	-	-	-	Head motion during CT perfusion acquisition can impact infarct core estimates.
	Bouslama et al., 2021 [44]	Retrospective	Proprietary, Single Center	479	-	-	-	-	-	-	RAPID had moderate correlation with final infarct volumes (r = 0.42–0.44).
	Siegler et al., 2020 [61]	Retrospective	Multi-site registry, Multicenter	410	0.69	-	-	-	62%	72%	Stroke mimics can show abnormalities on RAPID CT analysis.
	Kim et al., 2019 [45]	Prospective	Proprietary, Single Center	296	-	-	-	89–100%	-	-	Interclass correlation between RAPID and manual measurements of infarct volume were 0.98, with RAPID underestimating volumes by ~2 mL on average.
FastStroke/CT Perfusion 4D	Verdolotti et al., 2020 [51]	Retrospective	Proprietary, Single Center	86	-	-	-	-	-	-	Algorithm is comparable in efficacy to the status quo in evaluating collateral circulation, but has simpler workflows and faster turnaround times, making use easier for radiologists.
	Ospel et al., 2021 [53]	Prospective	PRove-IT cohort study, Multicenter	285	0.63–0.76	-	-	-	-	-	Time-variant multiphase CTA (mCTA) maps produced by the software improved prediction of good outcomes and performed comparably to conventional mCTA in predicting infarct volume.
	Liu et al., 2021 [52]	Retrospective	Proprietary, Single Center	82	-	-	-	-	-	-	CT Perfusion 4D had ICC of 0.95 compared to RAPID in predicting core volumes. The algorithm also performed well for volumes ≤ 70 mL
Icobrain-CTP	de la Rosa et al., 2021 [54]	Retrospective	Public ISLES18 stroke database	156	-	-	-	-	-	-	Icobrain uses a CNN that does not need user input in the form of thresholding to assess perfusion. Estimations of penumbra volume using CBF, CBV, and MTT had strong correlation with assessments by radiologists.
	de la Rosa et al., 2021 [55]	Retrospective	Public ISLES18 stroke database	156	0.86	-	-	-	-	-	Icobrain performed comparably to expert estimates of cerebral blood flow based on 4D CTP scans.
Viz CTP	Pisani et al., 2021 [56]	Prospective	Proprietary database otherwise unspecified	242	-	-	-	-	-	-	Viz CTP performed well in predicting final infarct volume (r = 0.601).
Augmented Vascular Analysis
Neuro.Al Algorithm