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.

Reduction of scan duration and radiation dose in cerebral CT perfusion imaging of acute stroke using a recurrent neural network

Objective. Cerebral CT perfusion (CTP) imaging is most commonly used to diagnose acute ischaemic stroke and support treatment decisions. Shortening CTP scan duration is desirable to reduce the accumulated radiation dose and the risk of patient head movement. In this study, we present a novel application of a stochastic adversarial video prediction approach to reduce CTP imaging acquisition time.Approach. A variational autoencoder and generative adversarial network (VAE-GAN) were implemented in a recurrent framework in three scenarios: to predict the last 8 (24 s), 13 (31.5 s) and 18 (39 s) image frames of the CTP acquisition from the first 25 (36 s), 20 (28.5 s) and 15 (21 s) acquired frames, respectively. The model was trained using 65 stroke cases and tested on 10 unseen cases. Predicted frames were assessed against ground-truth in terms of image quality and haemodynamic maps, bolus shape characteristics and volumetric analysis of lesions.Main results. In all three prediction scenarios, the mean percentage error between the area, full-width-at-half-maximum and maximum enhancement of the predicted and ground-truth bolus curve was less than 4 ± 4%. The best peak signal-to-noise ratio and structural similarity of predicted haemodynamic maps was obtained for cerebral blood volume followed (in order) by cerebral blood flow, mean transit time and time to peak. For the 3 prediction scenarios, average volumetric error of the lesion was overestimated by 7%-15%, 11%-28% and 7%-22% for the infarct, penumbra and hypo-perfused regions, respectively, and the corresponding spatial agreement for these regions was 67%-76%, 76%-86% and 83%-92%.Significance. This study suggests that a recurrent VAE-GAN could potentially be used to predict a portion of CTP frames from truncated acquisitions, preserving the majority of clinical content in the images, and potentially reducing the scan duration and radiation dose simultaneously by 65% and 54.5%, respectively.

Low-dose CT Perfusion with Sparse-view Filtered Back Projection in Acute Ischemic Stroke

RATIONALE AND OBJECTIVES

Radiation dose associated with computed tomography (CT) perfusion (CTP) may discourage its use despite its added diagnostic benefit in quantifying ischemic lesion volume. Sparse-view CT reduces scan dose by acquiring fewer X-ray projections per gantry rotation but is contaminated by streaking artifacts using filtered back projection (FBP). We investigated the achievable dose reduction by sparse-view CTP with FBP without affecting CTP lesion volume estimations.

MATERIALS AND METHODS

Thirty-eight consecutive patients with acute ischemic stroke and CTP were included in this simulation study. CTP projection data was simulated by forward projecting original reconstructions with 984 views and adding Gaussian noise. Full-view (984 views) and sparse-view (492, 328, 246, and 164 views) CTP studies were simulated by FBP of simulated projection data. Cerebral blood flow (CBF) and time-to-maximum of the impulse residue function (Tmax) maps were generated by deconvolution for each simulated CTP study. Ischemic volumes were measured by CBF<30% relative to the contralateral hemisphere and Tmax > 6 s. Volume accuracy was evaluated with respect to the full-view CTP study by the Friedman test with post hoc multiplicity-adjusted pairwise tests and Bland-Altman analysis.

RESULTS

Friedman and multiplicity-adjusted pairwise tests indicated that 164-view CBF < 30%, 246- and 164-view Tmax > 6 s volumes were significantly different to full-view volumes (p < 0.001). Mean difference ± standard deviation (sparse minus full-view lesion volume) ranged from -1.0 ± 2.8 ml to -4.1 ± 11.7 ml for CBF < 30% and -2.9 ± 3.8 ml to -12.5 ± 19.9 ml for Tmax > 6 s from 492 to 164 views, respectively.

CONCLUSION

By ischemic volume accuracy, our study indicates that sparse-view CTP may allow dose reduction by up to a factor of 3.

Study on a new "One-stop-shop" scan protocol combining brain CT perfusion and head-and-neck CT angiography by using 256-detector CT for stroke patients

PURPOSE

We sought to evaluate the performance of a new "one-stop-shop" scan protocol combining brain computed tomography perfusion (CTP) and head-and-neck CT angiography (CTA) imaging for acute stroke patients using a 256-detector CT scanner.

METHOD

From March to August 2020, 60 patients (30 men and 30 women) aged 22-88 years with suspected acute stroke were enrolled and randomly divided into 2 groups to undergo brain CTP and head-and-neck CTA with a 256-detector CT system. Group A used traditional scan protocol with a separate brain CTP and head-and-neck CT examination that included non-contrast-enhanced and contrast-enhanced acquisitions; group B used the new "one-stop-shop" scan protocol with head-and-neck CTA data inserted into brain CTP scans at the peak time (PT) of the arterial phase. The insertion point of the head-and-neck CTA data was determined by a test bolus. The examination time, contrast dose, radiation dose, and image quality were compared between the groups.

RESULTS

The total contrast dose was reduced by 40% in group B compared to group A (60 mL vs. 100 mL). The imaging time was 52.5 ± 2.6 s in group B and 74.9 ± 3.3 s in group A, showing a reduction of approximately 43% in group B. There was no significant difference in image quality both quantitatively and qualitatively between the groups (all P > 0.05). Group B had a slight reduction in dose length product (1139.0 ± 45.3 vs. 1211.6 ± 31.9 mGy·cm, P < 0.001).

CONCLUSIONS

The proposed "one-stop-shop" scan protocol combining brain CTP and head-and-neck CTA on a 256-detector CT system can reduce imaging time and contrast dose, without affecting image quality or perfusion results, compared to the traditional protocol of separating the examinations.

A novel use of time separation technique to improve flat detector CT perfusion imaging in stroke patients

BACKGROUND

CT perfusion imaging (CTP) is used in the diagnostic workup of acute ischemic stroke (AIS). CTP may be performed within the angio suite using flat detector CT (FDCT) to help reduce patient management time.

PURPOSE

In order to significantly improve FDCT perfusion (FDCTP) imaging, data-processing algorithms need to be able to compensate for the higher levels of noise, slow rotation speed, and a lower frame rate of current FDCT devices.

METHODS

We performed a realistic simulation of FDCTP acquisition based on CTP data from seven subjects. We used the time separation technique (TST) as a model-based approach for FDCTP data processing. We propose a novel dimension reduction in which we approximate the time attenuation curves by a linear combination of trigonometric functions. Our goal was to show that the TST can be used even without prior assumptions on the shape of the attenuation profiles.

RESULTS

We first demonstrated that a trigonometric basis is suitable for dimension reduction of perfusion data. Using simulated FDCTP data, we have shown that a trigonometric basis in the TST provided better results than the classical straightforward processing even with additional noise. Average correlation coefficients of perfusion maps were improved for cerebral blood flow (CBF), cerebral blood volume, mean transit time (MTT) maps. In a moderate noise scenario, the average Pearson's coefficient for the CBF map was improved using the TST from 0.76 to 0.81. For the MTT map, it was improved from 0.37 to 0.45. Furthermore, we achieved a total processing time from the reconstruction of FDCTP data to the generation of perfusion maps of under 5 min.

CONCLUSIONS

In our study cohort, perfusion maps created from FDCTP data using the TST with a trigonometric basis showed equivalent perfusion deficits to classic CT perfusion maps. It follows, that this novel FDCTP technique has potential to provide fast and accurate FDCTP imaging for AIS patients.

Absolute cerebral blood flow: Assessment with a novel low-radiation-dose dynamic CT perfusion technique in a swine model

RATIONALE AND OBJECTIVES

To validate the accuracy of a novel low-dose dynamic CT perfusion technique in a swine model using fluorescent microsphere measurement as the reference standard.

MATERIALS AND METHODS

Contrast-enhanced dynamic CT perfusion was performed in five swine at baseline and following brain embolization. Reference microspheres and intravenous contrast (370 mg/ml iodine, 1 ml/kg) were injected (5 ml/s), followed by dynamic CT perfusion. Scan parameters were 320×0.5 mm, 100 kVp and 200 mA. On average, 47 contrast-enhanced volume scans were acquired per acquisition to capture the time attenuation curve. For each acquisition, only two systematically selected volume scans were used to quantify brain perfusion with first-pass analysis technique. The first volume scan was selected at the base, simulating bolus tracking, while the second volume at the peak of the time attenuation curve similar to a CT angiogram. Regional low-dose CT perfusion measurements were compared to the microsphere perfusion measurements with t-test, linear regression and Bland-Altman analysis. The radiation dose of the two-volume CT perfusion technique was determined.

RESULTS

Low-dose CT perfusion measurements (P_CT) showed excellent correlation with reference microsphere perfusion measurements (P_MICRO) by P_CT = 1.15 P_MICRO - 0.01 (r = 0.93, p ≤ 0.01). The CT dose index and dose-length product for the two-volume CT perfusion technique were 25.6 mGy and 409.6 mGy, respectively.

CONCLUSIONS

The accuracy and repeatability of a low-dose dynamic CT perfusion technique was validated in a swine model. This technique has the potential for accurate diagnosis and follow up of stroke and vasospasm.

Efficient radiation dose reduction in whole-brain CT perfusion imaging using a 3D GAN: Performance and clinical feasibility

Dose reduction in cerebral CT perfusion (CTP) imaging is desirable but is accompanied by an increase in noise that can compromise the image quality and the accuracy of image-based haemodynamic modelling used for clinical decision support in acute ischaemic stroke. The few reported methods aimed at denoising low-dose CTP images lack practicality by considering only small sections of the brain or being computationally expensive. Moreover, the prediction of infarct and penumbra size and location - the chief means of decision support for treatment options - from denoised data has not been explored using these approaches. In this work, we present the first application of a 3D generative adversarial network (3D GAN) for predicting normal-dose CTP data from low-dose CTP data. Feasibility of the approach was tested using real data from 30 acute ischaemic stroke patients in conjunction with low dose simulation. The 3D GAN model was applied to 64^3 voxel patches extracted from two different configurations of the CTP data- frame-based and stacked. The method led to whole-brain denoised data being generated for haemodynamic modelling within 90 seconds. Accuracy of the method was evaluated using standard image quality metrics and the extent to which the clinical content and lesion characteristics of the denoised CTP data were preserved. Results showed an average improvement of 5.15-5.32 dB PSNR and 0.025-0.033 SSIM for CTP images and 2.66-3.95 dB PSNR and 0.036-0.067 SSIM for functional maps at 50% and 25% of normal dose using GAN model in conjunction with a stacked data regime for image synthesis. Consequently, the average lesion volumetric error reduced significantly (p-value < 0.05) by 18-29% and dice coefficient improved significantly by 15-22%. We conclude that GAN-based denoising is a promising practical approach for reducing radiation dose in CTP studies and improving lesion characterisation.

Low Dose CT Perfusion With K-Space Weighted Image Average (KWIA)

CTP (Computed Tomography Perfusion) is widely used in clinical practice for the evaluation of cerebrovascular disorders. However, CTP involves high radiation dose (≥~200mGy) as the X-ray source remains continuously on during the passage of contrast media. The purpose of this study is to present a low dose CTP technique termed K-space Weighted Image Average (KWIA) using a novel projection view-shared averaging algorithm with reduced tube current. KWIA takes advantage of k-space signal property that the image contrast is primarily determined by the k-space center with low spatial frequencies and oversampled projections. KWIA divides each 2D Fourier transform (FT) or k-space CTP data into multiple rings. The outer rings are averaged with neighboring time frames to achieve adequate signal-to-noise ratio (SNR), while the center region of k-space remains unchanged to preserve high temporal resolution. Reduced dose sinogram data were simulated by adding Poisson distributed noise with zero mean on digital phantom and clinical CTP scans. A physical CTP phantom study was also performed with different X-ray tube currents. The sinogram data with simulated and real low doses were then reconstructed with KWIA, and compared with those reconstructed by standard filtered back projection (FBP) and simultaneous algebraic reconstruction with regularization of total variation (SART-TV). Evaluation of image quality and perfusion metrics using parameters including SNR, CNR (contrast-to-noise ratio), AUC (area-under-the-curve), and CBF (cerebral blood flow) demonstrated that KWIA is able to preserve the image quality, spatial and temporal resolution, as well as the accuracy of perfusion quantification of CTP scans with considerable (50-75%) dose-savings.

Contrast-Medium Anisotropy-Aware Tensor Total Variation Model for Robust Cerebral Perfusion CT Reconstruction with Low-Dose Scans

Perfusion computed tomography (PCT) is critical in detecting cerebral ischemic lesions. PCT examination with low-dose scans can effectively reduce radiation exposure to patients at the cost of degraded images with severe noise and artifacts. Tensor total variation (TTV) models are powerful tools that can encode the regional continuous structures underlying a PCT object. In a TTV model, the sparsity structures of the contrast-medium concentration (CMC) across PCT frames are assumed to be isotropic with identical and independent distribution. However, this assumption is inconsistent with practical PCT tasks wherein the sparsity has evident variations and correlations. Such modeling deviation hampers the performance of TTV-based PCT reconstructions. To address this issue, we developed a novel contrast-medium anisotropy-aware tensor total variation (CMAA-TTV) model to describe the intrinsic anisotropy sparsity of the CMC in PCT imaging tasks. Instead of directly on the difference matrices, the CMAA-TTV model characterizes sparsity on a low-rank subspace of the difference matrices which are calculated from the input data adaptively, thus naturally encoding the intrinsic variant and correlated anisotropy sparsity structures of the CMC. We further proposed a robust and efficient PCT reconstruction algorithm to improve low-dose PCT reconstruction performance using the CMAA-TTV model. Experimental studies using a digital brain perfusion phantom, patient data with low-dose simulation and clinical patient data were performed to validate the effectiveness of the presented algorithm. The results demonstrate that the CMAA-TTV algorithm can achieve noticeable improvements over state-of-the-art methods in low-dose PCT reconstruction tasks.

Stacked Bidirectional Convolutional LSTMs for Deriving 3D Non-Contrast CT From Spatiotemporal 4D CT

The imaging workup in acute stroke can be simplified by deriving non-contrast CT (NCCT) from CT perfusion (CTP) images. This results in reduced workup time and radiation dose. To achieve this, we present a stacked bidirectional convolutional LSTM (C-LSTM) network to predict 3D volumes from 4D spatiotemporal data. Several parameterizations of the C-LSTM network were trained on a set of 17 CTP-NCCT pairs to learn to derive a NCCT from CTP and were subsequently quantitatively evaluated on a separate cohort of 16 cases. The results show that the C-LSTM network clearly outperforms the baseline and competitive convolutional neural network methods. We show good scalability and performance of the method by continued training and testing on an independent dataset which includes pathology of 80 and 83 CTP-NCCT pairs, respectively. C-LSTM is, therefore, a promising general deep learning approach to learn from high-dimensional spatiotemporal medical images.

Patient dose in brain perfusion imaging using an 80-slice CT system

BACKGROUND AND PURPOSE

Brain CT Perfusion (CTP) is an X-ray imaging technique for the assessment of brain tissue perfusion, which can be used in several different entities. The aim of this study is the evaluation of the radiation dose to patients during a comprehensive brain CT prescription protocol (CPP) consisting of an unenhanced brain CT, a brain CT angiography and a CTP scan.

MATERIALS AND METHODS

Eighteen patients were studied using an 80-slice CT system, with an iterative reconstruction algorithm. The volume Computed Tomography Dose Index (CTDI_vol) and dose length product (DLP) were recorded from the dose report of the system. The calculation of effective dose (ED) was accomplished using the DLP values.

RESULTS

For the CTP examinations, the CTDI_vol ranged from 116.0 to 134.8mGy, with the mean value 119.5mGy. The DLP ranged from 463.9 to 539.2mGy·cm, with the mean value 478mGy·cm. For the CPP, the total ED ranged from 3.31 to 5.07mSv, with the mean value 4.37mSv.

CONCLUSIONS

These values are lower than the values reported in corresponding studies, including studies utilizing CT systems with more slices.

Diagnostic Accuracy of Simulated Low-Dose Perfusion CT to Detect Cerebral Perfusion Impairment after Aneurysmal Subarachnoid Hemorrhage: A Retrospective Analysis

Purpose To evaluate diagnostic accuracy of low-dose volume perfusion (VP) computed tomography (CT) compared with original VP CT regarding the detection of cerebral perfusion impairment after aneurysmal subarachnoid hemorrhage. Materials and Methods In this retrospective study, 85 patients (mean age, 59.6 years; 62 women) with aneurysmal subarachnoid hemorrhage and who were suspected of having cerebral vasospasm at unenhanced CT and VP CT (tube voltage, 80 kVp; tube current-time product, 180 mAs) were included, 37 of whom underwent digital subtraction angiography (DSA) within 6 hours. Low-dose VP CT data sets at tube current-time product of 72 mAs were retrospectively generated by validated realistic simulation. Perfusion maps were generated from both data sets and reviewed by two neuroradiologists for overall image quality, diagnostic confidence and presence and/or severity of perfusion impairment indicating vasospasm. An interventional neuroradiologist evaluated 16 vascular segments at DSA. Diagnostic accuracy of low-dose VP CT was calculated with original VP CT as reference standard. Agreement between findings of both data sets was assessed by using weighted Cohen κ and findings were correlated with DSA by using Spearman correlation. After quantitative volumetric analysis, lesion volumes were compared on both VP CT data sets. Results Low-dose VP CT yielded good ratings of image quality and diagnostic confidence and classified all patients correctly with high diagnostic accuracy (sensitivity, 99.0%; specificity, 99.5%) without significant differences regarding presence and/or severity of perfusion impairment between original and low-dose data sets (Z = -0.447; P = .655). Findings of both data sets correlated significantly with DSA (original, r = 0.671; low dose, r = 0.667). Lesion volume was comparable for both data sets (relative difference, 5.9% ± 5.1 [range, 0.2%-25.0%; median, 4.0%]) with strong correlation (r = 0.955). Conclusion The results suggest that radiation dose reduction to 40% of original dose levels (tube current-time product, 72 mAs) may be performed in VP CT imaging of patients with aneurysmal subarachnoid hemorrhage without compromising the diagnostic accuracy regarding detection of cerebral perfusion impairment indicating vasospasm. ^© RSNA, 2018 Online supplemental material is available for this article.

Robust Segmentation of the Full Cerebral Vasculature in 4D CT of Suspected Stroke Patients

A robust method is presented for the segmentation of the full cerebral vasculature in 4-dimensional (4D) computed tomography (CT). The method consists of candidate vessel selection, feature extraction, random forest classification and postprocessing. Image features include among others the weighted temporal variance image and parameters, including entropy, of an intensity histogram in a local region at different scales. These histogram parameters revealed to be a strong feature in the detection of vessels regardless of shape and size. The method was trained and tested on a large database of 264 patients with suspicion of acute ischemia who underwent 4D CT in our hospital in the period January 2014 to December 2015. Five subvolumes representing different regions of the cerebral vasculature were annotated in each image in the training set by medical assistants. The evaluation was done on 242 patients. A total of 16 (<8%) patients showed severe under or over segmentation and were reported as failures. One out of five subvolumes was randomly annotated in 159 patients and was used for quantitative evaluation. Quantitative evaluation showed a Dice coefficient of 0.91 ± 0.07 and a modified Hausdorff distance of 0.23 ± 0.22 mm. Therefore, robust vessel segmentation in 4D CT is feasible with good accuracy.

A 4D CT digital phantom of an individual human brain for perfusion analysis

Brain perfusion is of key importance to assess brain function. Modern CT scanners can acquire perfusion maps of the cerebral parenchyma in vivo at submillimeter resolution. These perfusion maps give insights into the hemodynamics of the cerebral parenchyma and are critical for example for treatment decisions in acute stroke. However, the relations between acquisition parameters, tissue attenuation curves, and perfusion values are still poorly understood and cannot be unraveled by studies involving humans because of ethical concerns. We present a 4D CT digital phantom specific for an individual human brain to analyze these relations in a bottom-up fashion. Validation of the signal and noise components was based on 1,000 phantom simulations of 20 patient imaging data. This framework was applied to quantitatively assess the relation between radiation dose and perfusion values, and to quantify the signal-to-noise ratios of penumbra regions with decreasing sizes in white and gray matter. This is the first 4D CT digital phantom that enables to address clinical questions without having to expose the patient to additional radiation dose.

Hyaluronic acid-modified manganese-chelated dendrimer-entrapped gold nanoparticles for the targeted CT/MR dual-mode imaging of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common malignant tumor of the liver. The early and effective diagnosis has always been desired. Herein, we present the preparation and characterization of hyaluronic acid (HA)-modified, multifunctional nanoparticles (NPs) targeting CD44 receptor-expressing cancer cells for computed tomography (CT)/magnetic resonance (MR) dual-mode imaging. We first modified amine-terminated generation 5 poly(amidoamine) dendrimers (G5.NH2) with an Mn chelator, 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA), fluorescein isothiocyanate (FI), and HA. Then, gold nanoparticles (AuNPs) were entrapped within the above raw product, denoted as G5.NH2-FI-DOTA-HA. The designed multifunctional NPs were formed after further Mn chelation and purification and were denoted as {(Au0)100G5.NH2-FI-DOTA(Mn)-HA}. These NPs were characterized via several different techniques. We found that the {(Au0)100G5.NH2-FI-DOTA(Mn)-HA} NPs exhibited good water dispersibility, stability under different conditions, and cytocompatibility within a given concentration range. Because both AuNPs and Mn were present in the product, {(Au0)100G5.NH2-FI-DOTA(Mn)-HA} displayed a high X-ray attenuation intensity and favorable r1 relaxivity, which are advantageous properties for targeted CT/MR dual-mode imaging. This approach was used to image HCC cells in vitro and orthotopically transplanted HCC tumors in a unique in vivo model through the CD44 receptor-mediated endocytosis pathway. This work introduces a novel strategy for preparing multifunctional NPs via dendrimer nanotechnology.

C-Arm Conebeam CT Perfusion Imaging in the Angiographic Suite: A Comparison with Multidetector CT Perfusion Imaging

BACKGROUND AND PURPOSE

Perfusion imaging in the angiography suite may provide a way to reduce time from stroke onset to endovascular revascularization of patients with large-vessel occlusion. Our purpose was to compare conebeam CT perfusion with multidetector CT perfusion.

MATERIALS AND METHODS

Data from 7 subjects with both multidetector CT perfusion and conebeam CT perfusion were retrospectively processed and analyzed. Two algorithms were used to enhance temporal resolution and temporal sampling density and reduce the noise of conebeam CT data before generating perfusion maps. Two readers performed qualitative image-quality evaluation on maps by using a 5-point scale. ROIs indicating CBF/CBV abnormalities were drawn. Quantitative analyses were performed by using the Sørensen-Dice coefficients to quantify the similarity of abnormalities. A noninferiority hypothesis was tested to compare conebeam CT perfusion against multidetector CT perfusion.

RESULTS

Average image-quality scores for multidetector CT perfusion and conebeam CT perfusion images were 2.4 and 2.3, respectively. The average confidence score in diagnosis was 1.4 for both multidetector CT and conebeam CT; the average confidence scores for the presence of a CBV/CBF mismatch were 1.7 (κ = 0.50) and 1.5 (κ = 0.64). For multidetector CT perfusion and conebeam CT perfusion maps, the average scores of confidence in making treatment decisions were 1.4 (κ = 0.79) and 1.3 (κ = 0.90). The area under the visual grading characteristic for the above 4 qualitative quality scores showed an average area under visual grading characteristic of 0.50, with 95% confidence level cover centered at the mean for both readers. The Sørensen-Dice coefficient for CBF maps was 0.81, and for CBV maps, 0.55.

CONCLUSIONS

After postprocessing methods were applied to enhance image quality for conebeam CT perfusion maps, the conebeam CT perfusion maps were not inferior to those generated from multidetector CT perfusion.