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

Computed tomography perfusion (CTP) and computed tomography angiography (CTA) are valuable tools for diagnosing acute ischemic stroke (AIS). It is essential to obtain high-quality CTP and CTA images in short time. This study aimed to evaluate the image quality and diagnostic performance of brain CTP and CTA images generated from CTP reconstructed by a deep learning image reconstruction (DLIR) algorithm on patients with AIS. The study prospectively enrolled 54 patients with suspected AIS undergoing non-contrast CT and CTP within 24 hours. CTP datasets were reconstructed with three levels of adaptive statistical iterative reconstruction-Veo algorithm [ASIR-V 0% with filtered back projection (FBP), ASIR-V 40%, and ASIR-V 80%] and three levels of DLIR, including low (DLIR-L), medium (DLIR-M), and high (DLIR-H). CTA images were generated using the CTP datasets at the peak arterial phase. Objective parameters including signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and noise reduction rate. Subjective evaluation was assessed according to Abels scoring system. Perfusion parameters and detection accuracy for infarction core lesions were evaluated. The objective and subjective image quality of CTA images were also evaluated. All reconstructions produced similar CT values (P>0.05). With the increase of ASIR-V and DLIR reconstruction strength, image noise decreased, while SNR and CNR increased for CTP images, especially in white matter. DLIR-H, DLIR-M, and ASIR-V80% yielded higher subjective scores than did ASIR-V40% and FBP. DLIR-H provided the highest noise reduction rate and detection accuracy. No significant difference was found in conventional parameters, the volume of infarct core, or ischemic penumbra among the 6 groups (P>0.05). The objective evaluation of reconstructed CTA images was comparable in DLIR-H, DLIR-M, and ASIR-V80% (P>0.05). The subjective scores of the DLIR-H and DLIR-M images were higher than those of the other groups, especially ASIR-V40% and FBP (P<0.05). Compared with FBP and ASIR-V40%, DLIR-H, DLIR-M, and ASIR-V80% improved the overall image quality of CTP and CTA images to varying degrees. Furthermore, DLIR-H and DLIR-M showed the best performance. DLIR-H is the best choice in diagnosing AIS with improved detection accuracy for cerebral infarction. Reconstructing CTA images using CTP datasets could reduce contrast agent and radiation dose.

BackgroundComputed tomography is the most frequently used imaging modality in acute stroke imaging protocols. Detection of small volume infarcts in the brain and cardioembolic sources of stroke is difficult with current computed tomography protocols. Furthermore, the role of computed tomography findings to predict recurrent ischemic stroke is unclear. With ENCLOSE, we aim to improve (1) the detection of small volume infarcts with thin slice computed tomography perfusion (CTP) images and thromboembolic source with cardiac computed tomography techniques in the acute stage of ischemic stroke and (2) prediction of recurrent ischemic stroke with computed tomography-derived predictors.Methods/design: ENCLOSE is a prospective multicenter observational cohort study, which will be conducted in three Dutch stroke centers (ClinicalTrials.gov Identifier: NCT04019483). Patients (≥18 years) with suspected acute ischemic stroke who undergo computed tomography imaging within 9 h after symptom onset are eligible. Computed tomography imaging includes non-contrast CT, CTP, and computed tomography angiography (CTA) from base of the heart to the top of the brain. Dual-energy CT data will be acquired when possible, and thin-slice CTP reconstructions will be obtained in addition to standard 5 mm CTP data. CTP data will be processed with commercially available software and locally developed model-based methods. The post-processed thin-slice CTP images will be compared to the standard CTP images and to magnetic resonance diffusion-weighted imaging performed within 48 h after admission. Detection of cardioembolic sources of stroke will be evaluated on the CTA images. Recurrence will be evaluated 90 days and two years after the index event. The added value of imaging findings to prognostic models for recurrent ischemic stroke will be evaluated.ConclusionThe aim of ENCLOSE is to improve early detection of small volume stroke and thromboembolic sources and to improve prediction of recurrence in patients with acute ischemic stroke.

PurposeIntravenous alteplase (IVT) prior to endovascular treatment (EVT) is neither superior nor noninferior to EVT alone in acute ischemic stroke patients. We aim to assess whether the effect of IVT prior to EVT differs according to CT perfusion (CTP)–based imaging parameters.MethodsIn this retrospective post hoc analysis, we included patients from the MR CLEAN-NO IV with available CTP data. CTP data were processed using syngo.via (version VB40). We performed multivariable logistic regression to obtain the effect size estimates (adjusted common odds ratio a[c]OR) on 90-day functional outcome (modified Rankin Scale [mRS]) and functional independence (mRS 0-2) for CTP parameters with two-way multiplicative interaction terms between IVT administration and the studied parameters.ResultsIn 227 patients, median CTP-estimated core volume was 13 (IQR 5–35) mL. The treatment effect of IVT prior to EVT on outcome was not altered by CTP-estimated ischemic core volume, penumbral volume, mismatch ratio, and presence of a target mismatch profile. None of the CTP parameters was significantly associated with functional outcome after adjusting for confounders.ConclusionIn directly admitted patients with limited CTP-estimated ischemic core volumes who presented within 4.5 h after symptom onset, CTP parameters did not statistically significantly alter the treatment effect of IVT prior to EVT. Further studies are needed to confirm these results in patients with larger core volumes and more unfavorable baseline perfusion profiles on CTP imaging.

The role of CT perfusion (CT-P) imaging for the selection of patients with acute ischemic stroke who may benefit from endovascular treatment is not defined. The objective of this study was to determine whether CT-P-guided endovascular treatment improves clinical outcomes compared with standard endovascular treatment based on the time interval between symptom onset and presentation and noncontrast cranial CT imaging. A retrospective study was performed comparing the clinical characteristics, complications, and clinical outcomes of patients with acute ischemic stroke who were treated using endovascular modalities based on either CT-P imaging (CT-P-guided) or time interval between symptom onset and presentation and absence of intracerebral hemorrhage or extensive ischemic changes on noncontrast cranial CT scan (time-guided). The rates of partial and complete recanalization were similar between the CT-P- and time-guided treatment groups (n=61 [88%] versus n=103 [81%]; P=0.52) regardless of whether they received intravenous recombinant tissue plasminogen activator before endovascular treatment. Comparing the CT-P-guided with the time-guided patients, favorable discharge outcome (modified Rankin Scale 0 to 2) was observed in 23 (32%) versus 41 (33%) of the patients, respectively (P=0.9). In-hospital mortality was observed in 15 (21%) of CT-P- and 29 (23%) of time-guided patients (P=0.74). CT-P-guided endovascular treatment did not increase the rate of short-term favorable outcomes among patients with acute ischemic stroke. Prospective studies are required to validate the CT-P criteria and protocols currently in use before incorporating CT-P as a routine modality for patient selection for endovascular treatment.

CT perfusion imaging (CTP) plays an important role in decision making for the treatment of acute ischemic stroke with large vessel occlusion. Since the CT perfusion scan time is approximately one minute, the patient is exposed to a non-negligible dose of ionizing radiation. However, further dose reduction increases the level of noise in the data and the resulting perfusion maps. We present a method for reducing noise in perfusion data based on dimension reduction of time attenuation curves. For dimension reduction, we use either the fit of the first five terms of the trigonometric polynomial or the first five terms of the SVD decomposition of the time attenuation profiles. CTP data from four patients with large vessel occlusion and three control subjects were studied. To compare the noise level in the perfusion maps, we use the wavelet estimation of the noise standard deviation implemented in the scikit-image package. We show that both methods significantly reduce noise in the data while preserving important information about the perfusion deficits. These methods can be used to further reduce the dose in CT perfusion protocols or in perfusion studies using C-arm CT, which are burdened by high noise levels.

The role of CT perfusion (CTP) in the management of patients with acute ischemic stroke (AIS) remains a matter of debate. The primary aim of this study was to evaluate the correlation between the areas of infarction and penumbra on CTP scans and functional outcome in patients with AIS. This was a retrospective review of 100 consecutively treated patients with acute anterior circulation ischemic stroke who underwent CT angiography (CTA) and CTP at admission between February 2011 and October 2014. On CTP, the volume of ischemic core and penumbra was measured using the Alberta Stroke Program Early CT Score (ASPECTS). CTA findings were also noted, including the site of occlusion and regional leptomeningeal collateral (rLMC) score. Functional outcome was defined by modified Rankin Scale (mRS) score obtained at discharge. Associations of CTP and CTA parameters with mRS scores at discharge were assessed using multivariable proportional odds logistic regression models. The median age was 67 years (range 19-95 years), and the median NIH Stroke Scale score was 16 (range 2-35). In a multivariable analysis adjusting for potential confounding variables, having an infarct on CTP scans in the following regions was associated with a worse mRS score at discharge: insula ribbon (p = 0.043), perisylvian fissure (p < 0.001), motor strip (p = 0.007), M2 (p < 0.001), and M5 (p = 0.023). A worse mRS score at discharge was more common in patients with a greater volume of infarct core (p = 0.024) and less common in patients with a greater rLMC score (p = 0.004). The results of this study provide evidence that several CTP parameters are independent predictors of functional outcome in patients with AIS and have potential to identify those patients most likely to benefit from reperfusion therapy in the treatment of AIS.

Nowadays, PET and dynamic contrast enhanced CT or MRI are used to assess tumor blood perfusion. Although [(15)O]H2O PET is the gold standard, it is hardly available for routine clinical practice, due to the short half-life of (15)O. However, the lack of uniformity in scanning and analytic methods limits the use of CT perfusion (CTP) in clinical trials and practice. This study compares [(15)O]H2O PET with CT based perfusion in lung tumors and assesses the effects of various CTP postprocessing and analytical methods on the CTP results using [(15)O]H2O PET as the reference technique. Various CTP analysis and image postprocessing methods were assessed. Furthermore, parametric images were obtained using the Slope method. Volumes of interests were defined using several different segmentation methods including Hounsfield unit based contouring thresholds, both with and without framewise application of dynamic contouring thresholds to exclude lung tissue or intravascular contrast. A head-to-head comparison of tumor perfusion obtained by CTP and [(15)O]H2O PET was performed using linear regressions, Bland-Altman plots, and an intraclass correlation coefficient (ICC). In addition, the different postprocessing methods were compared reciprocally. In six lung cancer patients, perfusion assessed using CTP studies combined with the Slope method correlated best with [(15)O]H2O PET (ICC = 0.88; R(2) = 0.89; Y = 0.80). The Mullani-Gould method showed best correlation with the Slope method (ICC ≥ 0.71; R(2) ≥ 0.80; Y = 0.71-1.35). These correlations were obtained using dynamic contouring thresholds and show the influence of CTP postprocessing methods. Tumor perfusion assessed by CTP in combination with dynamic contouring thresholds using the Slope method correlates well with [(15)O]H2O PET. This suggests that CTP can be used as a method to evaluate tumor perfusion in lung cancer.

Objective: To compare the predictive capacity to detect established infarct in acute anterior circulation stroke between the Alberta Stroke Program Early Computed Tomography Score (ASPECTS) on non-contrast computed tomography (CT) and CT perfusion. Methods: Fifty-nine acute anterior circulation ischemic stroke patients received brain non-contrast CT, CT perfusion and hyperacute magnetic resonance imaging (MRI) within 100 minutes from CT imaging. ASPECTS scores were calculated by 4 independent vascular neurologists, blinded from CT perfusion and MRI data. CT perfusion infarct core volumes were calculated by MIStar software. The accuracy of commonly used ASPECTS cut-off scores and a CT perfusion core volume of ≥ 70 mL to detect a hyperacute MRI diffusion lesion of ≥ 70 ml was evaluated. Results: Median ASPECTS score was 9 (IQR 7-10). Median CT perfusion core volume was 22 ml (IQR 10.4-71.9). Median MRI diffusion lesion volume was 24,5 ml (IQR 10-63.9). ASPECTS score of &lt; 6 had a sensitivity of 0.37, specificity of 0.95 and c-statistic of 0.66 to predict an acute MRI lesion ≥ 70 ml. In comparison, a CT perfusion core lesion of ≥ 70 ml had a sensitivity of 0.76, specificity of 0.98 and c-statistic of 0.92. The CT perfusion core lesion covered a median of 100% of the acute MRI lesion volume (IQR 86-100%). Conclusions: CT perfusion is superior to ASPECTS to predict hyperacute MRI lesion volume in ischemic stroke.

X-ray computed tomographic perfusion (CTP) imaging, a rapid method for measuring cerebral blood flow (CBF), is an effective modality for assessment of the severity and extent of brain tissue ischemia. Low-dose scanning has been required for CTP imaging for reducing the radiation exposure to patients, because the same plane is scanned repeatedly. Low-dose CTP imaging, however, results in substantial statistical noise in the images, which may negatively impact the accuracy of CBF values. Because CBF values are calculated from the set of CTP images, it is important to reduce the statistical noise in raw CTP images to make the values reliable. Noise reduction must be performed without blurring of vessel structures, because such blurring will overestimate CBF values. For this purpose, two-dimensional nonlinear diffusion filtering (NLDF) was introduced. It was applied to CTP images of a CTP phantom for evaluating the accuracy of CBF values in low-dose CTP and to clinical low-dose CTP images for determining its effectiveness in actual CTP examinations. NLDF successfully reduced the statistical noise in the CTP images while preserving the sharp edges. This feature generated CBF values close to the reference value, producing reliable CBF maps from low-dose CT perfusion images. The CBF maps obtained with NLDF were comparable to or better than those obtained by other, commercial CTP software programs. The use of NLDF was thus effective for manipulation of low-dose CT perfusion images.

ObjectiveThe present study investigated the predictive value of each perfusion parameter of the Alberta Stroke Program Early Computed Tomography Score (ASPECTS) in CT perfusion (CTP) imaging for the prognosis of endovascular treatment at the time of admission in patients with acute ischemic stroke in the anterior circulation.Patients and MethodsThe imaging data of 62 patients with acute ischemic stroke in the anterior circulation with an onset time of 6 h or less were retrospectively analyzed. All patients underwent the one-stop whole-brain dynamic volume four-dimensional (4D) CT angiography (CTA)-CTP and cranial magnetic resonance imaging (MRI) within seven days after treatment. The patients were divided into better and worse prognosis groups according to their clinical symptoms, combined with an MRI-ASPECTS score of ≤ 6 within seven days after treatment. The observed perfusion parameters included cerebral blood flow (CBF)-ASPECTS, cerebral blood volume (CBV)-ASPECTS, mean transit time (MTT)-ASPECTS, and time to peak (TTP)-ASPECTS. The difference in ASPECTS scores involving the CTP parameter, as well as diagnostic power, was compared between the two groups of patients.ResultsAll CTP-ASPECTS scores negatively correlated with clinical prognosis. The higher the CTP-ASPECTS scores preceding treatment in patients with ischemic stroke in the anterior circulation, the better the prognosis. There were statistically significant differences in the scores of CBF-ASPECTS and CBV-ASPECTS between the two groups (P < 0.05). Receiver operating curve (ROC) analysis showed that the parameter with the largest area under the curve (AUC) was the CBF-ASPECTS score (P = 0.003), with a sensitivity of 90.9%, a specificity of 59.1%, and an AUC of 0.806, which was the most valuable prognostic predictor.ConclusionThe CBF-ASPECTS score presented significant value as a primary indicator for predicting the outcome of endovascular treatment in patients with acute ischemic stroke in the anterior circulation, and it had good application prospects in clinical practice.

d’Esterre, CD1, 3 Qazi, E1, 3 Patil, S1, 3 Almekhlafi, M3, 1 Lee, T2, 3 Demchuk, A1, 3 Goyal, M1, 3 Menon, B1, 3; 1. University of Calgary, Calgary, AB; 2. University of Western Ontario, London, ON; 3. Calgary Stroke Program, Calgary, AB Background : For ischemic stroke, CT Perfusion (CTP) may change thrombolytic/endovascular treatment decisions when compared to NCCT/CTA alone. Two distinct thresholds may be useful in this regard: separation of 1) non-salvageable tissue (infarct core) from salvageable electrically silent tissue (penumbra), and 2) penumbra from benign oligemia (hypoperfused, but will survive if clot persists). Methods : CTP (120s,8cm) was performed on 180 patients within 12hrs of ischemic stroke. Two patient cohorts were analyzed: (1) recanalization (TICI 2b,3) 6s. For group (2) CBF, CBV, and Tmax values were obtained from within the final infarct region, and total ipsilateral hemisphere, excluding infarction. CBF, CBV and Tmax were used in univariate regression models. Results : For group (1)[n=11], mean time from CTP to recanalization was 60±19min. CBF parameter (thresholds for gray and white matter 7.2 and 5.2 ml•min-1•(100g)-1) had the highest sensitivity (90.9%) and specificity (81.8%) for infarction. For group (2)[n=15], the Tmax parameter (thresholds for gray and white matter 11.3s and 11.8s) had the highest sensitivity (86.6%) and specificity (80.0%) for penumbra. Conclusion : Knowing the status of recanalization within 90mins of CTP allows for accurate delineation of infarct core, as …

Cerebral perfusion imaging predicts final infarct volume after basilar artery thrombectomy

Perfusion CT may improve the diagnostic performance of noncontrast CT in acute ischemic stroke. We assessed predictors of focal hypoperfusion in acute ischemic stroke and perfusion CT performance in predicting infarction on follow-up imaging. Patients from the Acute STroke Registry and Analysis of Lausanne data base with acute ischemic stroke and perfusion CT were included. Clinical and radiologic data were collected. We identified predictors of focal hypoperfusion using multivariate analyses. From the 2216 patients with perfusion CT, 38.2% had an acute ischemic lesion on NCCT and 73.3% had focal hypoperfusion on perfusion CT. After we analyzed 104 covariates, high-admission NIHSS, visual field defect, aphasia, hemineglect, sensory deficits, and impaired consciousness were positively associated with focal hypoperfusion. Negative associations were pure posterior circulation, lacunar strokes, and anticoagulation. After integrating radiologic variables into the multivariate analyses, we found that visual field defect, sensory deficits, hemineglect, early ischemic changes on NCCT, anterior circulation, cardioembolic etiology, and arterial occlusion were positively associated with focal hypoperfusion, whereas increasing onset-to-CT delay, chronic vascular lesions, and lacunar etiology showed negative association. Sensitivity, specificity, and positive and negative predictive values of focal hypoperfusion on perfusion CT for infarct detection on follow-up MR imaging were 66.5%, 79.4%, 96.2%, and 22.8%, respectively, with an overall accuracy of 76.8%. Compared with NCCT, perfusion CT doubles the sensitivity in detecting acute ischemic stroke. Focal hypoperfusion is independently predicted by stroke severity, cortical clinical deficits, nonlacunar supratentorial strokes, and shorter onset-to-imaging delays. A high proportion of patients with focal hypoperfusion developed infarction on subsequent imaging, as did some patients without focal hypoperfusion, indicating the complementarity of perfusion CT and MR imaging in acute ischemic stroke.

Objective. Computed tomography perfusion (CTP) imaging is widely used for assessing acute ischemic stroke. However, conventional methods for quantifying CTP images, such as singular value decomposition (SVD), often lead to oscillations in the estimated residue function and underestimation of tissue perfusion. In addition, the use of global arterial input function (AIF) potentially leads to erroneous parameter estimates. We aim to develop a method for accurately estimating physiological parameters from CTP images.Approach. We introduced a Transformer-based network to learn voxel-wise temporal features of CTP images. With global AIF and concentration time curve (CTC) of brain tissue as inputs, the network estimated local AIF and flow-scaled residue function. The derived parameters, including cerebral blood flow (CBF) and bolus arrival delay (BAD), were validated on both simulated and patient data (ISLES18 dataset), and were compared with multiple SVD-based methods, including standard SVD (sSVD), block-circulant SVD (cSVD) and oscillation-index SVD (oSVD).Main results.On data simulating multiple scenarios, local AIF estimated by the proposed method correlated with true AIF with a coefficient of 0.97 ± 0.04 (P < 0.001), estimated CBF with a mean error of 4.95 ml/100 g min-1, and estimated BAD with a mean error of 0.51 s; the latter two errors were significantly lower than those of the SVD-based methods (P < 0.001). The CBF estimated by the SVD-based methods were underestimated by 10%∼15%. For patient data, the CBF estimates of the proposed method were significantly higher than those of the sSVD method in both normally perfused and ischemic tissues, by 13.83 ml/100 g min-1or 39.33% and 8.55 ml/100 g min-1or 57.73% (P < 0.001), respectively, which was in agreement with the simulation results.Significance. The proposed method is capable of estimating local AIF and perfusion parameters from CTP images with high accuracy, potentially improving CTP's performance and efficiency in diagnosing and treating ischemic stroke.

Prediction of infarct extent among patients with acute ischemic stroke using computed tomography perfusion is defined by predefined discrete computed tomography perfusion thresholds. Our objective is to develop a threshold-free computed tomography perfusion-based machine learning (ML) model to predict follow-up infarct in patients with acute ischemic stroke. Sixty-eight patients from the PRoveIT study (Measuring Collaterals With Multi-Phase CT Angiography in Patients With Ischemic Stroke) were used to derive a ML model using random forest to predict follow-up infarction voxel by voxel, and 137 patients from the HERMES study (Highly Effective Reperfusion Evaluated in Multiple Endovascular Stroke Trials) were used to test the derived ML model. Average map, Tmax, cerebral blood flow, cerebral blood volume, and time variables including stroke onset-to-imaging and imaging-to-reperfusion time, were used as features to train the ML model. Spatial and volumetric agreement between the ML model predicted follow-up infarct and actual follow-up infarct were assessed. Relative cerebral blood flow <0.3 threshold using RAPID software and time-dependent Tmax thresholds were compared with the ML model. In the test cohort (137 patients), median follow-up infarct volume predicted by the ML model was 30.9 mL (interquartile range, 16.4-54.3 mL), compared with a median 29.6 mL (interquartile range, 11.1-70.9 mL) of actual follow-up infarct volume. The Pearson correlation coefficient between 2 measurements was 0.80 (95% CI, 0.74-0.86, P<0.001) while the volumetric difference was -3.2 mL (interquartile range, -16.7 to 6.1 mL). Volumetric difference with the ML model was smaller versus the relative cerebral blood flow <0.3 threshold and the time-dependent Tmax threshold (P<0.001). A ML using computed tomography perfusion data and time estimates follow-up infarction in patients with acute ischemic stroke better than current methods.