Effect of prolonged acquisition intervals for CT-perfusion analysis methods in patients with ischemic stroke

Standardizing the estimation of ischemic regions can harmonize CT perfusion stroke imaging

OBJECTIVES

We aimed to evaluate the real-world variation in CT perfusion (CTP) imaging protocols among stroke centers and to explore the potential for standardizing vendor software to harmonize CTP images.

METHODS

Stroke centers participating in a nationwide multicenter healthcare evaluation were requested to share their CTP scan and processing protocol. The impact of these protocols on CTP imaging was assessed by analyzing data from an anthropomorphic phantom with center-specific vendor software with default settings from one of three vendors (A-C): IntelliSpace Portal, syngoVIA, and Vitrea. Additionally, standardized infarct maps were obtained using a logistic model.

RESULTS

Eighteen scan protocols were studied, all varying in acquisition settings. Of these protocols, seven, eight, and three were analyzed with center-specific vendor software A, B, and C respectively. The perfusion maps were visually dissimilar between the vendor software but were relatively unaffected by the acquisition settings. The median error [interquartile range] of the infarct core volumes (mL) estimated by the vendor software was - 2.5 [6.5] (A)/ - 18.2 [1.2] (B)/ - 8.0 [1.4] (C) when compared to the ground truth of the phantom (where a positive error indicates overestimation). Taken together, the median error [interquartile range] of the infarct core volumes (mL) was - 8.2 [14.6] before standardization and - 3.1 [2.5] after standardization.

CONCLUSIONS

CTP imaging protocols varied substantially across different stroke centers, with the perfusion software being the primary source of differences in CTP images. Standardizing the estimation of ischemic regions harmonized these CTP images to a degree.

CLINICAL RELEVANCE STATEMENT

The center that a stroke patient is admitted to can influence the patient's diagnosis extensively. Standardizing vendor software for CT perfusion imaging can improve the consistency and accuracy of results, enabling a more reliable diagnosis and treatment decision.

KEY POINTS

• CT perfusion imaging is widely used for stroke evaluation, but variation in the acquisition and processing protocols between centers could cause varying patient diagnoses. • Variation in CT perfusion imaging mainly arises from differences in vendor software rather than acquisition settings, but these differences can be reconciled by standardizing the estimation of ischemic regions. • Standardizing the estimation of ischemic regions can improve CT perfusion imaging for stroke evaluation by facilitating reliable evaluations independent of the admission center.

A retrospective study of non-equidistant interstitial brain CT perfusion scanning and prediction of time to peak

Background

Eexploring the limits of CT cranial perfusion scan acquisition intervals and predicting time to peak.

Methods

A retrospective analysis was conducted on 45 patients with suspected stroke who underwent brain CTP scans. Different sampling intervals were set based on the TDC. The patients were divided into four groups: Group 1 underwent continuous scanning with a uniform interval of 1.5 s; Group 2 had a uniform interval of 3 s; Group 3 had a 1.5-s interval between arterial and venous peak vertices with 1 point retained before and after the peak for 1.5 s and with a remaining acquisition interval of 4.5 s; and Group 4 had a uniform interval of 4.5 s. Statistical analysis was performed on the perfusion parameters of each group. Additionally, in 286 patients who underwent head and neck CTA examinations, the peak time of contrast medium was recorded, and the peak time was predicted based on factors such as age, height, weight, heart rate, systolic blood pressure, diastolic blood pressure, triglycerides, and total cholesterol. The results compared with Group 1 and Group 2, as well as Group 1 and Group 3, the P values of CBF, CBV, MTT, and Tmax in the left and right cerebral hemispheres of healthy subjects and in the infarct and noninfarct areas of patients were all >0.05. A comparison between Group 1 and Group 4 showed that right cerebral hemisphere CBF and CBV, left cerebral hemisphere CBF, CBV, and Tmax, infarct area CBV and Tmax, and noninfarct area CBF, CBV, and MTT had P values > 0.05, while other groups all had P values < 0.05. Bland‒Altman analysis showed that the perfusion parameters in Group 1 were consistent with those in Group 2, and those in Group 1 were consistent with those in Group 3. The radiation doses in the second and third groups were lower, and the dose in the third group was lower than that in the second group.

Conclusion

Continuous acquisition between the peak points of the arterial and venous phases, with 1 point reserved before and after the peak and a 4.5-s interval for the rest, represents the maximum time interval for CTP scanning and can effectively reduce the radiation dose. The formula Tmax (s) = 0.290 × height (cm) - 0.226 × heart rate (times/min) + 0.216 × age (years) - 1.901 × triglycerides (mmol/L) - 0.061 × systolic blood pressure (mmHg) - 7.216 (R2 = 0.449, F = 17.905, P < 0.01) was established for predicting time to peak enhancement.

Multiphase CT angiography perfusion maps for predicting target mismatch and ischemic lesion volumes

The complexity of CT perfusion (CTP) acquisition protocols may limit the availability of target mismatch assessment at resource-limited hospitals. We compared CTP mismatch with a mismatch surrogate generated from a simplified dynamic imaging sequence comprising widely available non-contrast CT (NCCT) and multiphase CT angiography (mCTA). Consecutive patients with anterior circulation acute ischemic stroke who received NCCT, mCTA, and CTP were retrospectively included in this study. An mCTA-perfusion (mCTA-P) dynamic series was formed by co-registering NCCT and mCTA. We simulated an ideal mCTA-P study by down-sampling CTP (dCTP) dynamic images according to mCTA timing. Ischemic core and penumbra volumes were estimated by cerebral blood flow and Tmax thresholding, respectively, on perfusion maps calculated independently for CTP, dCTP, and mCTA-P by deconvolution. Concordance in target mismatch (core < 70 ml, penumbra ≥ 15 ml, mismatch ratio ≥ 1.8) determination by dCTP and mCTA-P versus CTP was assessed. Of sixty-one included patients, forty-six had a CTP target mismatch. Concordance with CTP profiles was 90% and 82% for dCTP and mCTA-P, respectively. Lower mCTA-P concordance was likely from differences in collimation width between NCCT and mCTA, which worsened perfusion map quality due to a CT number shift at mCTA. Moderate diagnostic agreement between CTP and mCTA-P was found and may improve with optimal mCTA scan parameter selection as simulated by dCTP. mCTA-P may be a pragmatic alternative where CTP is unavailable or the risks of additional radiation dose, contrast injections, and treatment delays outweigh the potential benefit of a separate CTP scan.

Spatio-temporal physics-informed learning: A novel approach to CT perfusion analysis in acute ischemic stroke

CT perfusion imaging is important in the imaging workup of acute ischemic stroke for evaluating affected cerebral tissue. CT perfusion analysis software produces cerebral perfusion maps from commonly noisy spatio-temporal CT perfusion data. High levels of noise can influence the results of CT perfusion analysis, necessitating software tuning. This work proposes a novel approach for CT perfusion analysis that uses physics-informed learning, an optimization framework that is robust to noise. In particular, we propose SPPINN: Spatio-temporal Perfusion Physics-Informed Neural Network and research spatio-temporal physics-informed learning. SPPINN learns implicit neural representations of contrast attenuation in CT perfusion scans using the spatio-temporal coordinates of the data and employs these representations to estimate a continuous representation of the cerebral perfusion parameters. We validate the approach on simulated data to quantify perfusion parameter estimation performance. Furthermore, we apply the method to in-house patient data and the public Ischemic Stroke Lesion Segmentation 2018 benchmark data to assess the correspondence between the perfusion maps and reference standard infarct core segmentations. Our method achieves accurate perfusion parameter estimates even with high noise levels and differentiates healthy tissue from infarcted tissue. Moreover, SPPINN perfusion maps accurately correspond with reference standard infarct core segmentations. Hence, we show that using spatio-temporal physics-informed learning for cerebral perfusion estimation is accurate, even in noisy CT perfusion data. The code for this work is available at https://github.com/lucasdevries/SPPINN.

Basis and current state of computed tomography perfusion imaging: a review

Computed tomography perfusion (CTP) is a functional imaging that allows for providing capillary-level hemodynamics information of the desired tissue in clinics. In this paper, we aim to offer insight into CTP imaging which covers the basics and current state of CTP imaging, then summarize the technical applications in the CTP imaging as well as the future technological potential. At first, we focus on the fundamentals of CTP imaging including systematically summarized CTP image acquisition and hemodynamic parameter map estimation techniques. A short assessment is presented to outline the clinical applications with CTP imaging, and then a review of radiation dose effect of the CTP imaging on the different applications is presented. We present a categorized methodology review on known and potential solvable challenges of radiation dose reduction in CTP imaging. To evaluate the quality of CTP images, we list various standardized performance metrics. Moreover, we present a review on the determination of infarct and penumbra. Finally, we reveal the popularity and future trend of CTP imaging.

Probability maps classify ischemic stroke regions more accurately than CT perfusion summary maps

OBJECTIVES

To compare single parameter thresholding with multivariable probabilistic classification of ischemic stroke regions in the analysis of computed tomography perfusion (CTP) parameter maps.

METHODS

Patients were included from two multicenter trials and were divided into two groups based on their modified arterial occlusive lesion grade. CTP parameter maps were generated with three methods-a commercial method (ISP), block-circulant singular value decomposition (bSVD), and non-linear regression (NLR). Follow-up non-contrast CT defined the follow-up infarct region. Conventional thresholds for individual parameter maps were established with a receiver operating characteristic curve analysis. Probabilistic classification was carried out with a logistic regression model combining the available CTP parameters into a single probability.

RESULTS

A total of 225 CTP data sets were included, divided into a group of 166 patients with successful recanalization and 59 with persistent occlusion. The precision and recall of the CTP parameters were lower individually than when combined into a probability. The median difference [interquartile range] in mL between the estimated and follow-up infarct volume was 29/23/23 [52/50/52] (ISP/bSVD/NLR) for conventional thresholding and was 4/6/11 [31/25/30] (ISP/bSVD/NLR) for the probabilistic classification.

CONCLUSIONS

Multivariable probability maps outperform thresholded CTP parameter maps in estimating the infarct lesion as observed on follow-up non-contrast CT. A multivariable probabilistic approach may harmonize the classification of ischemic stroke regions.

KEY POINTS

• Combining CTP parameters with a logistic regression model increases the precision and recall in estimating ischemic stroke regions. • Volumes following from a probabilistic analysis predict follow-up infarct volumes better than volumes following from a threshold-based analysis. • A multivariable probabilistic approach may harmonize the classification of ischemic stroke regions.

CT liver perfusion in patients with hepatocellular carcinoma: can we modify acquisition protocol to reduce patient exposure?

OBJECTIVES

To investigate the potential of decreasing the number of scans and associated radiation exposure involved in CT liver perfusion (CTLP) dynamic studies for hepatocellular carcinoma (HCC) assessment.

METHODS

Twenty-four CTLP image datasets of patients with HCC were retrospectively analyzed. All examinations were performed on a modern CT system using a standard acquisition protocol involving 35 scans with 1.7 s interval. A deconvolution-based or a standard algorithm was employed to compute ten perfusion parametric maps. 3D ROIs were positioned on 33 confirmed HCCs and non-malignant parenchyma. Analysis was repeated for two subsampled datasets generated from the original dataset by including only the (a) 18 odd-numbered scans with 3.4 s interval and (b) 18 first scans with 1.7 s interval. Standard and modified datasets were compared regarding the (a) accuracy of calculated perfusion parameters, (b) power of parametric maps to discriminate HCCs from liver parenchyma, and (c) associated radiation exposure.

RESULTS

When the time interval between successive scans was doubled, perfusion parameters of HCCs were found unaffected (p > 0.05) and the discriminating efficiency of parametric maps was preserved (p < 0.05). In contrast, significant differences were found for all perfusion parameters of HCCs when acquisition duration was reduced to half (p < 0.05), while the discriminating efficiency of four parametric maps was significantly deteriorated (p < 0.05). Modified CTLP acquisition protocols were found to involve 48.5% less patient exposure.

CONCLUSIONS

Doubling the interscan time interval may considerably reduce radiation exposure from CTLP studies performed for HCC evaluation without affecting the diagnostic efficiency of perfusion maps generated with either standard or deconvolution-based mathematical model.

KEY POINTS

• CT liver perfusion for HCC diagnosis/assessment is not routinely used in clinical practice mainly due to the associated high radiation exposure. • Two alternative acquisition protocols involving 18 scans of the liver were compared with the standard 35-scan protocol. • Increasing the time interval between successive scans to 3.4 s was found to preserve the accuracy of computed perfusion parameters derived with a standard or a deconvolution-based model and to reduce radiation exposure by 48.5%.