Overestimation of core infarct by computed tomography perfusion in the golden hour.
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ABSTRACT:
SUBMITTER: Mendez AA
PROVIDER: S-EPMC7646387 | biostudies-literature | 2020 Jul-Sep
REPOSITORIES: biostudies-literature
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Project description:PurposeComputed tomography perfusion (CTP) is used to diagnose ischemic strokes through contralateral hemisphere comparisons of various perfusion parameters. Various perfusion parameter thresholds have been utilized to segment infarct tissue due to differences in CTP software and patient baseline hemodynamics. This study utilized a convolutional neural network (CNN) to eliminate the need for non-universal parameter thresholds to segment infarct tissue.MethodsCTP data from 63 ischemic stroke patients was retrospectively collected and perfusion parameter maps were generated using Vitrea CTP software. Infarct ground truth labels were segmented from diffusion-weighted imaging (DWI) and CTP and DWI volumes were registered. A U-net based CNN was trained and tested five separate times using each CTP parameter (cerebral blood flow (CBF), cerebral blood volume (CBV), time-to-peak (TTP), mean-transit-time (MTT), delay time). 8,352 infarct slices were utilized with a 60:30:10 training:testing:validation split and Monte Carlo cross-validation was conducted using 20 iterations. Infarct volumes were reconstructed following segmentation from each CTP slice. Infarct spatial and volumetric agreement was compared between each CTP parameter and DWI.ResultsSpatial agreement metrics (Dice coefficient, positive predictive value) for each CTP parameter in predicting infarct volumes are: CBF=(0.67, 0.76), CBV=(0.44, 0.62), TTP=(0.60, 0.67), MTT=(0.58, 0.62), delay time=(0.57, 0.60). 95% confidence intervals for volume differences with DWI infarct are: CBF=14.3±11.5 mL, CBV=29.6±21.2 mL, TTP=7.7±15.2 mL, MTT=-10.7±18.6 mL, delay time=-5.7±23.6 mL.ConclusionsCBF is the most accurate CTP parameter in segmenting infarct tissue. Segmentation of infarct using a CNN has the potential to eliminate non-universal CTP contralateral hemisphere comparison thresholds.
| S-EPMC7946163 | biostudies-literature
Project description:Background and purposeThe ISLES challenge (Ischemic Stroke Lesion Segmentation) enables globally diverse teams to compete to develop advanced tools for stroke lesion analysis with machine learning. Detection of irreversibly damaged tissue on computed tomography perfusion (CTP) is often necessary to determine eligibility for late-time-window thrombectomy. Therefore, the aim of ISLES-2018 was to segment infarcted tissue on CTP based on diffusion-weighted imaging as a reference standard.MethodsThe data, from 4 centers, consisted of 103 cases of acute anterior circulation large artery occlusion stroke who underwent diffusion-weighted imaging rapidly after CTP. Diffusion-weighted imaging lesion segmentation was performed manually and acted as a reference standard. The data were separated into 63 cases for training and 40 for testing, upon which quality metrics (dice score coefficient, Hausdorff distance, absolute lesion volume difference, etc) were computed to rank methods based on their overall performance.ResultsTwenty-four different teams participated in the challenge. Median time to CTP was 185 minutes (interquartile range, 180-238), the time between CTP and magnetic resonance imaging was 36 minutes (interquartile range, 25-79), and the median infarct lesion size was 15.2 mL (interquartile range, 5.7-45). The best performance for Dice score coefficient and absolute volume difference were 0.51 and 10.1 mL, respectively, from different teams. Based on the ranking criteria, the top team's algorithm demonstrated for average Dice score coefficient and average absolute volume difference 0.51 and 10.2 mL, respectively, outperforming the conventional threshold-based method (dice score coefficient, 0.3; volume difference, 15.3). Diverse algorithms were used, almost all based on deep learning, with top-ranked approaches making use of the raw perfusion data as well as methods to synthetically generate complementary information to boost prediction performance.ConclusionsMachine learning methods may predict infarcted tissue from CTP with improved accuracy compared with threshold-based methods used in clinical routine. This dataset will remain public and can be used to test improvement in algorithms over time.
| S-EPMC8240494 | biostudies-literature
Project description:Infarct core can expand rapidly in acute stroke patients receiving intravenous tissue plasminogen activator (IV t-PA). We investigated changes in the extent of infarct core during IV t-PA treatment, and explored the associative factors of this infarct core expansion in patients with proximal artery occlusion.We included patients who were considered for sequential intra-arterial therapy (IAT) due to occlusion of intracranial proximal artery after IV t-PA. Patients who had a baseline Alberta Stroke Program Early Computed Tomography (CT) Score (ASPECTS) ?6 and who underwent two consecutive CT scans before and shortly after IV t-PA infusion were enrolled. Patients were classified into no, moderate, and marked expansion groups based on decreases in ASPECTS (0-1, 2-3, and ?4, respectively) on follow-up CT. Collateral status was graded using CT angiography.Of the 104 patients, 16 (15.4%) patients showed moderate and 13 (12.5%) patients showed marked infarct core expansion on follow-up CT scans obtained at 71.1±19.1 min after baseline CT scan. Sixteen (15.4%) patients had an ASPECTS value <6 on the follow-up CT. None of the patients with marked expansion were independent at 3 months. Univariate analysis and ordinal logistic regression analysis demonstrated that the infarct core expansion was significantly associated with collateral status (p<0.001).Among patients who were considered for IAT after IV t-PA treatment, one out of every seven patients exhibited marked expansion of infarct core on follow-up CT before IAT. These patients tend to have poor collaterals and poor outcomes despite rescue IAT.
| S-EPMC5823835 | biostudies-other
Project description:Background The diagnosis of ischemic cerebellar stroke is challenging because of nonspecific symptoms and very limited accuracy of commonly applied computed tomography (CT) imaging. Advances in CT perfusion imaging provide increasing value in the detection of posterior circulation stroke, but the prognostic value remains unclear. We aimed to identify imaging parameters that predict morphologic outcome in cerebellar stroke patients using advanced CT including whole-brain CT perfusion (WB-CTP). Methods and Results We selected all subjects with cerebellar WB-CTP perfusion deficits and follow-up-confirmed cerebellar infarction from a consecutive cohort with suspected stroke who underwent WB-CTP. Posterior-circulation-Acute-Stroke-Prognosis-Early-CT-Score (pc-ASPECTS) was determined on noncontrast CT, CT angiography source images, and on parametric WB-CTP maps. Cerebellar perfusion deficit volumes on all maps and the final infarction volume on follow-up imaging were quantified. Uni- and multivariate regression analyses were performed. Sixty patients fulfilled the inclusion criteria. pc-ASPECTS on CT angiography source images (ß, -9.239; 95% CI, -14.220 to -4.259; P<0.001) and cerebral blood flow deficit volume (ß, 0.886; 95% CI, 0.684 to 1.089; P<0.001) were significantly associated with final infarction volume in univariate linear regression analysis. The association of cerebral blood flow deficit volume (ß, 0.830; 95% CI, 0.605-1.055; P<0.001) was confirmed in a multivariate linear regression model adjusted for age, sex, pc-ASPECTS on noncontrast CT, and CT angiography source images and the National Institutes of Health Stroke Scale score on admission. No other clinical or imaging parameters were associated with cerebellar stroke final infarction volume (P>0.05). Conclusions In contrast to noncontrast CT and CT angiography, WB-CTP imaging contains prognostic information for morphologic outcome in patients with acute cerebellar stroke.
| S-EPMC6898835 | biostudies-literature
Project description:Differences in research methodology have hampered the optimization of Computer Tomography Perfusion (CTP) for identification of the ischemic core. We aim to optimize CTP core identification using a novel benchmarking tool. The benchmarking tool consists of an imaging library and a statistical analysis algorithm to evaluate the performance of CTP. The tool was used to optimize and evaluate an in-house developed CTP-software algorithm. Imaging data of 103 acute stroke patients were included in the benchmarking tool. Median time from stroke onset to CT was 185?min (IQR 180-238), and the median time between completion of CT and start of MRI was 36?min (IQR 25-79). Volumetric accuracy of the CTP-ROIs was optimal at an rCBF threshold of <38%; at this threshold, the mean difference was 0.3?ml (SD 19.8?ml), the mean absolute difference was 14.3 (SD 13.7) ml, and CTP was 67% sensitive and 87% specific for identification of DWI positive tissue voxels. The benchmarking tool can play an important role in optimizing CTP software as it provides investigators with a novel method to directly compare the performance of alternative CTP software packages.
| S-EPMC5076783 | biostudies-literature
Project description:Background and purposeThe Alberta Stroke Program Early Computed Tomography (CT) Score (ASPECTS) and CT perfusion (CTP) are commonly used to predict the ischemic core in acute ischemic strokes. CT angiography source images (CTA-SI) can also provide additional information to identify the extent of ischemia. Our objective was to investigate the correlation of noncontrast CT (NCCT) ASPECTS and CTA-SI ASPECTS with CTP core volumes.MethodsWe utilized a single institutional, retrospective registry of consecutive patients with acute ischemic stroke with large vessel occlusion between May 2016 and May 2018. We graded ASPECTS both on baseline NCCT and CTA-SI and measured CTP core using automated RAPID software (cerebral blood flow <30%). We used Spearman's correlation coefficients to evaluate the correlation between continuous variables.ResultsA total of 52 patients fit the inclusion criteria of large vessel occlusion in 6 to 24 hours and baseline imaging work up of NCCT, CTA, and CTP. The median age was 63 (interquartile range=53.5-75) and 38.46% were female. The median NCCT ASPECTS was 7 (interquartile range=6-9), CTA-SI ASPECTS was 5 (interquartile range=4-7), and CTP core was 14.5 mL (interquartile range=0-46 mL). There was a moderate correlation between NCCT ASPECTS and CTP core (rs=-0.55, P<0.0001) and between CTA-SI ASPECTS and CTP core (rs=-0.50, P=0.0002). The optimal NCCT ASPECTS cutoff score to detect CTP core ≤70 mL was ≥6 (sensitivity, 0.84; specificity, 0.57; positive predictive value, 0.93; negative predictive value, 0.36) and the optimal CTA-SI ASPECTS was ≥5 (sensitivity, 0.76; specificity, 0.71; positive predictive value, 0.94; negative predictive value, 0.31).ConclusionsThere was a moderate correlation between NCCT and CTA-SI ASPECTS in predicting CTP defined ischemic core in delayed time windows. Further studies are needed to determine if NCCT and CTA imaging could be used for image-based patient selection when CTP imaging is not available.
| S-EPMC8591482 | biostudies-literature
Project description:PurposeComputed tomography (CT)-derived ventilation methods compute respiratory induced volume changes as a surrogate for pulmonary ventilation. Currently, there are no known methods to derive perfusion information from noncontrast CT. We introduce a novel CT-Perfusion (CT-P) method for computing the magnitude mass changes apparent on dynamic noncontrast CT as a surrogate for pulmonary perfusion.MethodsCT-Perfusion is based on a mass conservation model which describes the unknown mass change as a linear combination of spatially corresponding inhale and exhale HU estimated voxel densities. CT-P requires a deformable image registration (DIR) between the inhale/exhale lung CT pair, a preprocessing lung volume segmentation, and an estimate for the Jacobian of the DIR transformation. Given this information, the CT-P image, which provides the magnitude mass change for each voxel within the lung volume, is formulated as the solution to a constrained linear least squares problem defined by a series of subregional mean magnitude mass change measurements. Similar to previous robust CT-ventilation methods, the amount of uncertainty in a subregional sample mean measurement is related to measurement resolution and can be characterized with respect to a tolerance parameter τ . Spatial Spearman correlation between single photon emission CT perfusion (SPECT-P) and the proposed CT-P method was assessed in two patient cohorts via a parameter sweep of τ . The first cohort was comprised of 15 patients diagnosed with pulmonary embolism (PE) who had SPECT-P and 4DCT imaging acquired within 24 h of PE diagnosis. The second cohort was comprised of 15 nonsmall cell lung cancer patients who had SPECT-P and 4DCT images acquired prior to radiotherapy. For each test case, CT-P images were computed for 30 different uncertainty parameter values, uniformly sampled from the range [0.01, 0.125], and the Spearman correlation between the SPECT-P and the resulting CT-P images were computed.ResultsThe median correlations between CT-P and SPECT-P taken over all 30 test cases ranged between 0.49 and 0.57 across the parameter sweep. For the optimal tolerance τ = 0.0385, the CT-P and SPECT-P correlations across all 30 test cases ranged between 0.02 and 0.82. A one-sample sign test was applied separately to the PE and lung cancer cohorts. A low Spearmen correlation of 15% was set as the null median value and two-sided alternative was tested. The PE patients showed a median correlation of 0.57 (IQR = 0.305). One-sample sign test was statistically significant with 96.5 % confidence interval: 0.20-0.63, P < 0.00001. Lung cancer patients had a median correlation of 0.57(IQR = 0.230). Again, a one-sample sign test for median was statistically significant with 96.5 percent confidence interval: 0.45-0.71, P < 0.00001.ConclusionCT-Perfusion is the first mechanistic model designed to quantify magnitude blood mass changes on noncontrast dynamic CT as a surrogate for pulmonary perfusion. While the reported correlations with SPECT-P are promising, further investigation is required to determine the optimal CT acquisition protocol and numerical method implementation for CT-P imaging.
| S-EPMC8252085 | biostudies-literature
Project description:PurposeFlat-panel computed tomography (FP-CT) is increasingly available in angiographic rooms and hybrid OR's. Considering its easy access, cerebral imaging using FP-CT is an appealing modality for intra-procedural applications. The purpose of this systematic review is to assess the diagnostic accuracy of FP-CT compared with perfusion computed tomography (CTP) and perfusion magnetic resonance (MRP) in cerebral perfusion imaging.MethodsWe performed a systematic literature search in the Cochrane Library, MEDLINE, Embase, and Web of Science up to June 2019 for studies directly comparing FP-CT with either CTP or MRP in vivo. Methodological quality was assessed using the QUADAS-2 tool. Data on diagnostic accuracy was extracted and pooled if possible.ResultsWe found 11 studies comparing FP-CT with CTP and 5 studies comparing FP-CT with MRP. Most articles were pilot or feasibility studies, focusing on scanning and contrast protocols. All patients studied showed signs of cerebrovascular disease. Half of the studies were animal trials. Quality assessment showed unclear to high risks of bias and low concerns regarding applicability. Five studies reported on diagnostic accuracy; FP-CT shows good sensitivity (range 0.84-1.00) and moderate specificity (range 0.63-0.88) in detecting cerebral blood volume (CBV) lesions.ConclusionsEven though FP-CT provides similar CBV values and reconstructed blood volume maps as CTP in cerebrovascular disease, additional studies are required in order to reliably compare its diagnostic accuracy with cerebral perfusion imaging.
| S-EPMC6848034 | biostudies-literature
Project description:See Saver (doi:10.1093/awx020) for a scientific commentary on this article.Stroke shortens an individual's disability-free life. We aimed to assess the relative prognostic influence of pre- and post-treatment perfusion computed tomography imaging variables (e.g. ischaemic core and penumbral volumes) compared to standard clinical predictors (such as onset-to-treatment time) on long-term stroke disability in patients undergoing thrombolysis. We used data from a prospectively collected international, multicentre, observational registry of acute ischaemic stroke patients who had perfusion computed tomography and computed tomography angiography before treatment with intravenous alteplase. Baseline perfusion computed tomography and follow-up magnetic resonance imaging were analysed to derive the baseline penumbra volume, baseline ischaemic core volume, and penumbra salvaged from infarction. The primary outcome measure was the effect of imaging and clinical variables on Disability-Adjusted Life Year. Clinical variables were age, sex, National Institutes of Health Stroke Scale score, and onset-to-treatment time. Age, sex, country, and 3-month modified Rankin Scale were extracted from the registry to calculate disability-adjusted life-year due to stroke, such that 1 year of disability-adjusted life-year equates to 1 year of healthy life lost due to stroke. There were 772 patients receiving alteplase therapy. The number of disability-adjusted life-year days lost per 1 ml of baseline ischaemic core volume was 17.5 (95% confidence interval, 13.2-21.9 days, P < 0.001). For every millilitre of penumbra salvaged, 7.2 days of disability-adjusted life-year days were saved (β = -7.2, 95% confidence interval, -10.4 to -4.1 days, P < 0.001). Each minute of earlier onset-to-treatment time resulted in a saving of 4.4 disability-free days after stroke (1.3-7.5 days, P = 0.006). However, after adjustment for imaging variables, onset-to-treatment time was not significantly associated with savings in disability-adjusted life-year days. Pretreatment perfusion computed tomography can (independently of clinical variables) predict significant gains, or loss, of disability-free life in patients undergoing reperfusion therapy for stroke. The effect of earlier treatment on disability-free life appears explained by salvage of penumbra, particularly when the ischaemic core is not too large.
| S-EPMC5382947 | biostudies-literature
Project description:AIMS:To evaluate the diagnostic power of integrating the results of computed tomography angiography (CTA) and CT myocardial perfusion (CTP) to identify coronary artery disease (CAD) defined as a flow limiting coronary artery stenosis causing a perfusion defect by single photon emission computed tomography (SPECT). METHODS AND RESULTS:We conducted a multicentre study to evaluate the accuracy of integrated CTA-CTP for the identification of patients with flow-limiting CAD defined by ?50% stenosis by invasive coronary angiography (ICA) with a corresponding perfusion deficit on stress single photon emission computed tomography (SPECT/MPI). Sixteen centres enroled 381 patients who underwent combined CTA-CTP and SPECT/MPI prior to conventional coronary angiography. All four image modalities were analysed in blinded independent core laboratories. The prevalence of obstructive CAD defined by combined ICA-SPECT/MPI and ICA alone was 38 and 59%, respectively. The patient-based diagnostic accuracy defined by the area under the receiver operating characteristic curve (AUC) of integrated CTA-CTP for detecting or excluding flow-limiting CAD was 0.87 [95% confidence interval (CI): 0.84-0.91]. In patients without prior myocardial infarction, the AUC was 0.90 (95% CI: 0.87-0.94) and in patients without prior CAD the AUC for combined CTA-CTP was 0.93 (95% CI: 0.89-0.97). For the combination of a CTA stenosis ?50% stenosis and a CTP perfusion deficit, the sensitivity, specificity, positive predictive, and negative predicative values (95% CI) were 80% (72-86), 74% (68-80), 65% (58-72), and 86% (80-90), respectively. For flow-limiting disease defined by ICA-SPECT/MPI, the accuracy of CTA was significantly increased by the addition of CTP at both the patient and vessel levels. CONCLUSIONS:The combination of CTA and perfusion correctly identifies patients with flow limiting CAD defined as ?50 stenosis by ICA causing a perfusion defect by SPECT/MPI.
| S-EPMC6693293 | biostudies-literature