Automatic selection of arterial input function using cluster analysis

Cerebrovascular MRI: a review of state-of-the-art approaches, methods and techniques

Cerebrovascular imaging is of great interest in the understanding of neurological disease. MRI is a non-invasive technology that can visualize and provide information on: (i) the structure of major blood vessels; (ii) the blood flow velocity in these vessels; and (iii) the microcirculation, including the assessment of brain perfusion. Although other medical imaging modalities can also interrogate the cerebrovascular system, MR provides a comprehensive assessment, as it can acquire many different structural and functional image contrasts whilst maintaining a high level of patient comfort and acceptance. The extent of examination is limited only by the practicalities of patient tolerance or clinical scheduling limitations. Currently, MRI methods can provide a range of metrics related to the cerebral vasculature, including: (i) major vessel anatomy via time-of-flight and contrast-enhanced imaging; (ii) blood flow velocity via phase contrast imaging; (iii) major vessel anatomy and tissue perfusion via arterial spin labeling and dynamic bolus passage approaches; and (iv) venography via susceptibility-based imaging. When designing an MRI protocol for patients with suspected cerebral vascular abnormalities, it is appropriate to have a complete understanding of when to use each of the available techniques in the 'MR angiography toolkit'. In this review article, we: (i) overview the relevant anatomy, common pathologies and alternative imaging modalities; (ii) describe the physical principles and implementations of the above listed methods; (iii) provide guidance on the selection of acquisition parameters; and (iv) describe the existing and potential applications of MRI to the cerebral vasculature and diseases. The focus of this review is on obtaining an understanding through the application of advanced MRI methodology of both normal and abnormal blood flow in the cerebrovascular arteries, capillaries and veins.

Repeatability of Cerebral Perfusion Using Dynamic Susceptibility Contrast MRI in Glioblastoma Patients

OBJECTIVES

This study evaluates the repeatability of brain perfusion using dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) with a variety of post-processing methods.

METHODS

Thirty-two patients with newly diagnosed glioblastoma were recruited. On a 3-T MRI using a dual-echo, gradient-echo spin-echo DSC-MRI protocol, the patients were scanned twice 1 to 5 days apart. Perfusion maps including cerebral blood volume (CBV) and cerebral blood flow (CBF) were generated using two contrast agent leakage correction methods, along with testing normalization to reference tissue, and application of arterial input function (AIF). Repeatability of CBV and CBF within tumor regions and healthy tissues, identified by structural images, was assessed with intra-class correlation coefficients (ICCs) and repeatability coefficients (RCs). Coefficients of variation (CVs) were reported for selected methods.

RESULTS

CBV and CBF were highly repeatable within tumor with ICC values up to 0.97. However, both CBV and CBF showed lower ICCs for healthy cortical tissues (up to 0.83), healthy gray matter (up to 0.95), and healthy white matter (WM; up to 0.93). The values of CV ranged from 6% to 10% in tumor and 3% to 11% in healthy tissues. The values of RC relative to the mean value of measurement within healthy WM ranged from 22% to 42% in tumor and 7% to 43% in healthy tissues. These percentages show how much variation in perfusion parameter, relative to that in healthy WM, we expect to observe to consider it statistically significant. We also found that normalization improved repeatability, but AIF deconvolution did not.

CONCLUSIONS

DSC-MRI is highly repeatable in high-grade glioma patients.

Capillary dysfunction: its detection and causative role in dementias and stroke

In acute ischemic stroke, critical hypoperfusion is a frequent cause of hypoxic tissue injury: As cerebral blood flow (CBF) falls below the ischemic threshold of 20 mL/100 mL/min, neurological symptoms develop and hypoxic tissue injury evolves within minutes or hours unless the oxygen supply is restored. But is ischemia the only hemodynamic source of hypoxic tissue injury? Reanalyses of the equations we traditionally use to describe the relation between CBF and tissue oxygenation suggest that capillary flow patterns are crucial for the efficient extraction of oxygen: without close capillary flow control, "functional shunts" tend to form and some of the blood's oxygen content in effect becomes inaccessible to tissue. This phenomenon raises several questions: Are there in fact two hemodynamic causes of tissue hypoxia: Limited blood supply (ischemia) and limited oxygen extraction due to capillary dysfunction? If so, how do we distinguish the two, experimentally and in patients? Do flow-metabolism coupling mechanisms adjust CBF to optimize tissue oxygenation when capillary dysfunction impairs oxygen extraction downstream? Cardiovascular risk factors such as age, hypertension, diabetes, hypercholesterolemia, and smoking increase the risk of both stroke and dementia. The capillary dysfunction phenomenon therefore forces us to consider whether changes in capillary morphology or blood rheology may play a role in the etiology of some stroke subtypes and in Alzheimer's disease. Here, we discuss whether certain disease characteristics suggest capillary dysfunction rather than primary flow-limiting vascular pathology and how capillary dysfunction may be imaged and managed.

Perfusion MRI derived indices of microvascular shunting and flow control correlate with tumor grade and outcome in patients with cerebral glioma

Objectives

Deficient microvascular blood flow control is thought to cause tumor hypoxia and increase resistance to therapy. In glioma patients, we tested whether perfusion-weighted MRI (PWI) based indices of microvascular flow control provide more information on tumor grade and patient outcome than does the established PWI angiogenesis marker, cerebral blood volume (CBV).

Material and Methods

Seventy-two glioma patients (sixty high-grade, twelve low-grade gliomas) were included. Capillary transit time heterogeneity (CTH) and the coefficient of variation (COV), its ratio to blood mean transit time, provide indices of microvascular flow control and the extent to which oxygen can be extracted by tumor tissue. The ability of these parameters and CBV to differentiate tumor grade were assessed by receiver operating characteristic curves and logistic regression. Their ability to predict time to progression and overall survival was examined by the Cox proportional-hazards regression model, and by survival curves using log-rank tests.

Results

The best prediction of grade (AUC = 0.876; p < 0.05) was achieved by combining knowledge of CBV and CTH in the enhancing tumor and peri-focal edema, and patients with glioblastoma multiforme were identified best by CTH (AUC = 0.763; p<0.001). CTH outperformed CBV and COV in predicting time to progression and survival in all gliomas and in a subgroup consisting of only high-grade gliomas.

Conclusion

Our study confirms the importance of microvascular flow control in tumor growth by demonstrating that determining CTH improves tumor grading and outcome prediction in glioma patients compared to CBV alone.

Imaging Patterns and Management Algorithms in Acute Stroke: An Update for the Emergency Radiologist

Neuroimaging plays a key role in the initial work-up of patients with symptoms of acute stroke. Understanding the advantages and limitations of available CT and MR imaging techniques and how to use them optimally in the emergency setting is crucial for accurately making the diagnosis of acute stroke and for rapidly determining appropriate treatment.

Relative cerebral blood volume is a potential predictive imaging biomarker of bevacizumab efficacy in recurrent glioblastoma

BACKGROUND

To analyze the relevance of dynamic susceptibility-weighted contrast-enhanced MRI (DSC-MRI) derived relative cerebral blood volume (rCBV) analysis for predicting response to bevacizumab (BEV) in patients with recurrent glioblastoma (rGB).

METHODS

A total of 127 patients diagnosed with rGB receiving either bevacizumab (71 patients, BEV cohort) or alkylating chemotherapy (56 patients, non-BEV cohort) underwent conventional anatomic MRI and DSC-MRI at baseline and at first follow-up after treatment initiation. The mean rCBV of the contrast-enhancing tumor (cT1) as well as cT1 and fluid-attenuated inversion recovery (FLAIR) volumes at both time points were correlated with progression-free survival (PFS) and overall survival (OS) using Cox proportional hazard models, logistic regression, and the log-rank test.

RESULTS

Baseline rCBV was associated with both PFS (hazard ratio [HR] = 1.3; P < .01) and OS (HR = 1.3; P < .01) in the BEV cohort and predicted 6-month PFS in 82% and 12-month OS in 79% of patients, whereas it was not associated with PFS (HR = 1.0; P = .70) or OS (HR = 1.0; P = .47) in the non-BEV cohort. Corresponding median OS and PFS rates in the BEV cohort for patients with rCBV-values less than 3.92 (optimal threshold from receiver operating characteristic [ROC] analysis of 12-month OS data) were 14.2 and 6.0 months, as compared to 6.6 and 2.8 months for patients with rCBV-values greater than 3.92 (P < .01, respectively). cT1 and FLAIR volumes at first follow-up were significant predictors of 6-month PFS and 12-month OS in the BEV cohort but not in the non-BEV cohort. Corresponding volumes at baseline were not significant in any cohort.

CONCLUSIONS

Pretreatment rCBV is a potential predictive imaging biomarker in BEV-treated rGB but not alkylating chemotherapy-treated rGB, which is superior to volumetric analysis of conventional anatomic MRI and predicts 6-month PFS and 12-month OS in 80% of BEV-treated patients.

Automatic determination of the arterial input function in dynamic susceptibility contrast MRI: comparison of different reproducible clustering algorithms

Introduction

Arterial input function (AIF) plays an important role in the quantification of cerebral hemodynamics. The purpose of this study was to select the best reproducible clustering method for AIF detection by comparing three algorithms reported previously in terms of detection accuracy and computational complexity.

Methods

First, three reproducible clustering methods, normalized cut (Ncut), hierarchy (HIER), and fast affine propagation (FastAP), were applied independently to simulated data which contained the true AIF. Next, a clinical verification was performed where 42 subjects participated in dynamic susceptibility contrast MRI (DSC-MRI) scanning. The manual AIF and AIFs based on the different algorithms were obtained. The performance of each algorithm was evaluated based on shape parameters of the estimated AIFs and the true or manual AIF. Moreover, the execution time of each algorithm was recorded to determine the algorithm that operated more rapidly in clinical practice.

Results

In terms of the detection accuracy, Ncut and HIER method produced similar AIF detection results, which were closer to the expected AIF and more accurate than those obtained using FastAP method; in terms of the computational efficiency, the Ncut method required the shortest execution time.

Conclusion

Ncut clustering appears promising because it facilitates the automatic and robust determination of AIF with high accuracy and efficiency.

Dynamic contrast-enhanced perfusion processing for neuroradiologists: model-dependent analysis may not be necessary for determining recurrent high-grade glioma versus treatment effect

BACKGROUND AND PURPOSE

Dynamic contrast-enhanced perfusion MR imaging has proved useful in determining whether a contrast-enhancing lesion is secondary to recurrent glial tumor or is treatment-related. In this article, we explore the best method for dynamic contrast-enhanced data analysis.

MATERIALS AND METHODS

We retrospectively reviewed 24 patients who met the following conditions: 1) had at least an initial treatment of a glioma, 2) underwent a half-dose contrast agent (0.05-mmol/kg) diagnostic-quality dynamic contrast-enhanced perfusion study for an enhancing lesion, and 3) had a diagnosis by pathology within 30 days of imaging. The dynamic contrast-enhanced data were processed by using model-dependent analysis (nordicICE) using a 2-compartment model and model-independent signal intensity with time. Multiple methods of determining the vascular input function and numerous perfusion parameters were tested in comparison with a pathologic diagnosis.

RESULTS

The best accuracy (88%) with good correlation compared with pathology (P = .005) was obtained by using a novel, model-independent signal-intensity measurement derived from a brief integration beginning after the initial washout and by using the vascular input function from the superior sagittal sinus for normalization. Modeled parameters, such as mean endothelial transfer constant > 0.05 minutes(-1), correlated (P = .002) but did not reach a diagnostic accuracy equivalent to the model-independent parameter.

CONCLUSIONS

A novel model-independent dynamic contrast-enhanced analysis method showed diagnostic equivalency to more complex model-dependent methods. Having a brief integration after the first pass of contrast may diminish the effects of partial volume macroscopic vessels and slow progressive enhancement characteristic of necrosis. The simple modeling is technique- and observer-dependent but is less time-consuming.

Exposing hidden truncation-related errors in acute stroke perfusion imaging

BACKGROUND AND PURPOSE

The durations of acute ischemic stroke patients' CT or MR perfusion scans may be too short to fully sample the passage of the injected contrast agent through the brain. We tested the potential magnitude of hidden errors related to the truncation of data by short perfusion scans.

MATERIALS AND METHODS

Fifty-seven patients with acute ischemic stroke underwent perfusion MR imaging within 12 hours of symptom onset, using a relatively long scan duration (110 seconds). Shorter scan durations (39.5-108.5 seconds) were simulated by progressively deleting the last-acquired images. CBV, CBF, MTT, and time to response function maximum (Tmax) were measured within DWI-identified acute infarcts, with commonly used postprocessing algorithms. All measurements except Tmax were normalized by dividing by the contralateral hemisphere values. The effects of the scan duration on these hemodynamic measurements and on the volumes of lesions with Tmax of >6 seconds were tested using regression.

RESULTS

Decreasing scan duration from 110 seconds to 40 seconds falsely reduced perfusion estimates by 47.6%-64.2% of normal for CBV, 1.96%-4.10% for CBF, 133%-205% for MTT, and 6.2-8.0 seconds for Tmax, depending on the postprocessing method. This truncation falsely reduced estimated Tmax lesion volume by 71.5 or 93.8 mL, depending on the deconvolution method. "Lesion reversal" (ie, change from above-normal to apparently normal, or from >6 seconds to ≤6 seconds for the time to response function maximum) with increasing truncation occurred in 37%-46% of lesions for CBV, 2%-4% for CBF, 28%-54% for MTT, and 42%-44% for Tmax, depending on the postprocessing method.

CONCLUSIONS

Hidden truncation-related errors in perfusion images may be large enough to alter patient management or affect outcomes of clinical trials.

Bayesian estimation of cerebral perfusion using reduced-contrast-dose dynamic susceptibility contrast perfusion at 3T

BACKGROUND AND PURPOSE

DSC perfusion has been increasingly used in conjunction with other contrast-enhanced MR applications and therefore there is need for contrast-dose reduction when feasible. The purpose of this study was to establish the feasibility of reduced-contrast-dose brain DSC perfusion by using a probabilistic Bayesian method and to compare the results with the commonly used singular value decomposition technique.

MATERIALS AND METHODS

Half-dose (0.05-mmol/kg) and full-dose (0.1-mmol/kg) DSC perfusion studies were prospectively performed in 20 patients (12 men; 34-70 years of age) by using a 3T MR imaging scanner and a gradient-EPI sequence (TR/TE, 1450/22 ms; flip angle, 90°). All DSC scans were processed with block circulant singular value decomposition and Bayesian probabilistic methods. SNR analysis was performed in both half-dose and full-dose groups. The CBF, CBV, and MTT maps from both full-dose and half-dose scans were evaluated qualitatively and quantitatively in both WM and GM on coregistered perfusion maps. Statistical analysis was performed by using a t test, regression, and Bland-Altman analysis.

RESULTS

The SNR was significantly (P < .0001) lower in the half-dose group with 32% and 40% reduction in GM and WM, respectively. In the half-dose group, the image-quality scores were significantly higher in Bayesian-derived CBV (P = .02) and MTT (P = .004) maps in comparison with block circulant singular value decomposition. Quantitative values of CBF, CBV, and MTT in Bayesian-processed data were comparable and without a statistically significant difference between the half-dose and full-dose groups. The block circulant singular value decomposition-derived half-dose perfusion values were significantly different from those of the full-dose group both in GM (CBF, P < .001; CBV, P = .02; MTT, P = .02) and WM (CBF, P < .001; CBV, P = .003; MTT, P = .01).

CONCLUSIONS

Reduced-contrast-dose (0.05-mmol/kg) DSC perfusion of the brain is feasible at 3T by using the Bayesian probabilistic method with quantitative results comparable with those of the full-dose protocol.

Evaluation of dynamic contrast-enhanced MRI derived microvascular permeability in recurrent glioblastoma treated with bevacizumab

Bevacizumab, an antibody to vascular endothelial growth factor, is commonly used in the setting of recurrent glioblastoma (rGB). The aim of the present study was to evaluate whether dynamic-contrast-enhanced MRI (DCE-MRI) derived microvascular permeability is related to bevacizumab treatment outcome in rGB. Twenty-two patients with rGB underwent DCE-MRI at a median of 2.6 weeks prior initializing bevacizumab therapy. Follow-up MRI-scans (DCE-MRI available for 19/22 patients) were obtained after a median of 9.9 weeks. The volume transfer constant (K(trans))--an estimate related to microvascular permeability--at baseline and voxel-wise-reduction (VWR) in K(trans) at first follow-up were measured from the entire contrast-enhancing tumor (CET) and correlated with progression-free and overall survival (PFS, OS) using uni- and multivariate cox-regression (significance-level p < 0.05). Baseline K(trans) ranged from 0.050 to 0.205 min(-1) (median, 0.109 min(-1)). The VWR in K(trans) ranged from 19.9 to 97.2 % (median, 89.4 %). Patients with lower baseline K(trans) and higher VWR in K(trans) showed significantly longer PFS and OS. Given the strong correlation of VWR in K(trans) and CET-volume changes (Spearman's ρ = -0.73, p < 0.01) both variables were included in a multivariate model. Thereby, neither VWR in K(trans) nor CET-volume changes retained independent significance for PFS or OS. Pre-treatment K(trans) stratifies PFS and OS in patients with bevacizumab-treated rGB. Although early pharmacodynamics changes in K(trans) were not assessed, the VWR in K(trans) at first follow-up had no additional benefit over assessment of CET-volume changes. Further prospective trials are needed to confirm these findings and to elucidate the potential role of pre-treatment K(trans) as a predictive and/or prognostic biomarker.

Correcting for large vessel contamination in dynamic susceptibility contrast perfusion MRI by extension to a physiological model of the vasculature

PURPOSE

Dynamic susceptibility contrast (DSC) perfusion images are contaminated by contributions from macro vascular signal arising from contrast agent within the larger arteries that do not contribute directly to the local tissue perfusion.

METHODS

A vascular model of the DSC perfusion signal was extended by the inclusion of a macro vascular component based on the arterial input function. This was implemented within a Bayesian nonlinear model-fitting algorithm that included automatic model complexity reduction. Results were compared with existing methods that do not correct for the macro vascular contamination as well as an independent component analysis technique.

RESULTS

Macro vascular signal was identified in regions corresponding to larger arteries resulting in reductions by 62% within a region of interest identified with high contamination. Whereas visually similar results could be achieved with independent component analysis, it resulted in reductions in global tissue perfusion and was not robustly applicable to patient data.

CONCLUSION

A model-based strategy for correction of macro vascular contamination in DSC perfusion images is feasible, although the model may currently need extending to more accurately account for nonlinear effects of contrast agent in large arteries. Magn Reson Med 74:280-290, 2015. © 2014 Wiley Periodicals, Inc.

Evaluating the feasibility of an agglomerative hierarchy clustering algorithm for the automatic detection of the arterial input function using DSC-MRI

During dynamic susceptibility contrast-magnetic resonance imaging (DSC-MRI), it has been demonstrated that the arterial input function (AIF) can be obtained using fuzzy c-means (FCM) and k-means clustering methods. However, due to the dependence on the initial centers of clusters, both clustering methods have poor reproducibility between the calculation and recalculation steps. To address this problem, the present study developed an alternative clustering technique based on the agglomerative hierarchy (AH) method for AIF determination. The performance of AH method was evaluated using simulated data and clinical data based on comparisons with the two previously demonstrated clustering-based methods in terms of the detection accuracy, calculation reproducibility, and computational complexity. The statistical analysis demonstrated that, at the cost of a significantly longer execution time, AH method obtained AIFs more in line with the expected AIF, and it was perfectly reproducible at different time points. In our opinion, the disadvantage of AH method in terms of the execution time can be alleviated by introducing a professional high-performance workstation. The findings of this study support the feasibility of using AH clustering method for detecting the AIF automatically.

MRI before intraarterial therapy in ischemic stroke: feasibility, impact, and safety

Intraarterial therapy (IAT) in acute ischemic stroke is effective for opening occlusions of major extracranial or intracranial vessels. Clinical efficacy data are lacking pointing to a need for proper patient selection. We examined feasibility, clinical impact, and safety profile of magnetic resonance imaging (MRI) for patient selection before IAT. In this single-center study, we collected epidemiologic, imaging, and outcome data on all intraarterial-treated patients presenting with anterior circulation occlusions at our center from 2004 to 2011. Magnetic resonance imaging was the first imaging choice. Computer tomography (CT) was performed in the presence of a contraindication. We treated 138 patients. Mean age was 64 years and median National Institutes of Health Stroke Scale (NIHSS) was 17. Major reperfusion (thrombolysis in cerebral infarction (TICI) 2b+3) was achieved in 52% and good outcome defined as modified Rankin Scale (mRS) score 0 to 2 at 90 days was achieved in 41%. Mortality at 90 days was 10%. There was only one symptomatic hemorrhage. Recanalization, age, and stroke severity were associated with outcome. Preprocedure MRI was obtained in 83%. Good outcome was significantly associated with smaller diffusion-weighted imaging (DWI) lesion size at presentation and not with the size of the perfusion lesion. It is feasible to triage patients for IAT using MRI with acceptable rates of poor outcome and symptomatic hemorrhage.

Quantification of cerebral perfusion using dynamic quantitative susceptibility mapping

PURPOSE

The purpose of this study is to develop a dynamic quantitative susceptibility mapping (QSM) technique with sufficient temporal resolution to map contrast agent concentration in cerebral perfusion imaging.

METHODS

The dynamic QSM used a multiecho three-dimensional (3D) spoiled gradient echo golden angle interleaved spiral sequence during contrast bolus injection. Four-dimensional (4D) space-time resolved magnetic field reconstruction was performed using the temporal resolution acceleration with constrained evolution reconstruction method. Deconvolution of the gadolinium-induced field was performed at each time point with the morphology enabled dipole inversion method to generate a 4D gadolinium concentration map, from which three-dimensional spatial distributions of cerebral blood volume and cerebral blood flow were computed.

RESULTS

Initial in vivo brain imaging demonstrated the feasibility of using dynamic QSM for generating quantitative 4D contrast agent maps and imaging three-dimensional perfusion. The cerebral blood flow obtained with dynamic QSM agreed with that obtained using arterial spin labeling.

CONCLUSION

Dynamic QSM can be used to perform 4D mapping of contrast agent concentration in contrast-enhanced magnetic resonance imaging. The perfusion parameters derived from this 4D contrast agent concentration map were in good agreement with those obtained using arterial spin labeling.

Comparison of K-means and fuzzy c-means algorithm performance for automated determination of the arterial input function

The arterial input function (AIF) plays a crucial role in the quantification of cerebral perfusion parameters. The traditional method for AIF detection is based on manual operation, which is time-consuming and subjective. Two automatic methods have been reported that are based on two frequently used clustering algorithms: fuzzy c-means (FCM) and K-means. However, it is still not clear which is better for AIF detection. Hence, we compared the performance of these two clustering methods using both simulated and clinical data. The results demonstrate that K-means analysis can yield more accurate and robust AIF results, although it takes longer to execute than the FCM method. We consider that this longer execution time is trivial relative to the total time required for image manipulation in a PACS setting, and is acceptable if an ideal AIF is obtained. Therefore, the K-means method is preferable to FCM in AIF detection.

Modeling and correction of bolus dispersion effects in dynamic susceptibility contrast MRI

PURPOSE

Bolus dispersion in DSC-MRI can lead to errors in cerebral blood flow (CBF) estimation by up to 70% when using singular value decomposition analysis. However, it might be possible to correct for dispersion using two alternative methods: the vascular model (VM) and control point interpolation (CPI). Additionally, these approaches potentially provide a means to quantify the microvascular residue function.

METHODS

VM and CPI were extended to correct for dispersion by means of a vascular transport function. Simulations were performed at multiple dispersion levels and an in vivo analysis was performed on a healthy subject and two patients with carotid atherosclerotic disease.

RESULTS

Simulations showed that methods that could not address dispersion tended to underestimate CBF (ratio in CBF estimation, CBFratio = 0.57-0.77) in the presence of dispersion; whereas modified CPI showed the best performance at low-to-medium dispersion; CBFratio = 0.99 and 0.81, respectively. The in vivo data showed trends in CBF estimation and residue function that were consistent with the predictions from simulations.

CONCLUSION

In patients with atherosclerotic disease the estimated residue function showed considerable differences in the ipsilateral hemisphere. These differences could partly be attributed to dispersive effects arising from the stenosis when dispersion corrected CPI was used. It is thus beneficial to correct for dispersion in perfusion analysis using this method.

Remote ischemic perconditioning as an adjunct therapy to thrombolysis in patients with acute ischemic stroke: a randomized trial

BACKGROUND AND PURPOSE

Remote ischemic preconditioning is neuroprotective in models of acute cerebral ischemia. We tested the effect of prehospital rPerC as an adjunct to treatment with intravenous alteplase in patients with acute ischemic stroke.

METHODS

Open-label blinded outcome proof-of-concept study of prehospital, paramedic-administered rPerC at a 1:1 ratio in consecutive patients with suspected acute stroke. After neurological examination and MRI, patients with verified stroke receiving alteplase treatment were included and received MRI at 24 hours and 1 month and clinical re-examination after 3 months. The primary end point was penumbral salvage, defined as the volume of the perfusion-diffusion mismatch not progressing to infarction after 1 month.

RESULTS

Four hundred forty-three patients were randomized after provisional consent, 247 received rPerC and 196 received standard treatment. Patients with a nonstroke diagnosis (n=105) were excluded from further examinations. The remaining patients had transient ischemic attack (n=58), acute ischemic stroke (n=240), or hemorrhagic stroke (n=37). Transient ischemic attack was more frequent (P=0.006), and National Institutes of Health Stroke Scale score on admission was lower (P=0.016) in the intervention group compared with controls. Penumbral salvage, final infarct size at 1 month, infarct growth between baseline and 1 month, and clinical outcome after 3 months did not differ among groups. After adjustment for baseline perfusion and diffusion lesion severity, voxelwise analysis showed that rPerC reduced tissue risk of infarction (P=0.0003).

CONCLUSIONS

Although the overall results were neutral, a tissue survival analysis suggests that prehospital rPerC may have immediate neuroprotective effects. Future clinical trials should take such immediate effects, and their duration, into account.

CLINICAL TRIAL REGISTRATION

URL: http://www.clinicaltrials.gov. Unique identifier: NCT00975962.

Slice accelerated gradient-echo spin-echo dynamic susceptibility contrast imaging with blipped CAIPI for increased slice coverage

PURPOSE

To improve slice coverage of gradient echo spin echo (GESE) sequences for dynamic susceptibility contrast (DSC) MRI using a simultaneous-multiple-slice (SMS) method.

METHODS

Data were acquired on 3 Tesla (T) MR scanners with a 32-channel head coil. To evaluate use of SMS for DSC, an SMS GESE sequence with two-fold slice coverage and same temporal sampling was compared with a standard GESE sequence, both with 2× in-plane acceleration. A signal to noise ratio (SNR) comparison was performed on one healthy subject. Additionally, data with Gadolinium injection were collected on three patients with glioblastoma using both sequences, and perfusion analysis was performed on healthy tissues as well as on tumor.

RESULTS

Retained SNR of SMS DSC is 90% for a gradient echo (GE) and 99% for a spin echo (SE) acquisition, compared with a standard acquisition without slice acceleration. Comparing cerebral blood volume maps, it was observed that the results of standard and SMS acquisitions are comparable for both GE and SE images.

CONCLUSION

Two-fold slice accelerated DSC MRI achieves similar SNR and perfusion metrics as a standard acquisition, while allowing a significant increase in slice coverage of the brain. The results also point to a possibility to improve temporal sampling rate, while retaining the same slice coverage.

Automatic detection of arterial input function in dynamic contrast enhanced MRI based on affinity propagation clustering

PURPOSE

To automatically and robustly detect the arterial input function (AIF) with high detection accuracy and low computational cost in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).

MATERIALS AND METHODS

In this study, we developed an automatic AIF detection method using an accelerated version (Fast-AP) of affinity propagation (AP) clustering. The validity of this Fast-AP-based method was proved on two DCE-MRI datasets, i.e., rat kidney and human head and neck. The detailed AIF detection performance of this proposed method was assessed in comparison with other clustering-based methods, namely original AP and K-means, as well as the manual AIF detection method.

RESULTS

Both the automatic AP- and Fast-AP-based methods achieved satisfactory AIF detection accuracy, but the computational cost of Fast-AP could be reduced by 64.37-92.10% on rat dataset and 73.18-90.18% on human dataset compared with the cost of AP. The K-means yielded the lowest computational cost, but resulted in the lowest AIF detection accuracy. The experimental results demonstrated that both the AP- and Fast-AP-based methods were insensitive to the initialization of cluster centers, and had superior robustness compared with K-means method.

CONCLUSION

The Fast-AP-based method enables automatic AIF detection with high accuracy and efficiency.

Arterial input function in perfusion MRI: a comprehensive review

Cerebral perfusion, also referred to as cerebral blood flow (CBF), is one of the most important parameters related to brain physiology and function. The technique of dynamic-susceptibility contrast (DSC) MRI is currently the most commonly used MRI method to measure perfusion. It relies on the intravenous injection of a contrast agent and the rapid measurement of the transient signal changes during the passage of the bolus through the brain. Central to quantification of CBF using this technique is the so-called arterial input function (AIF), which describes the contrast agent input to the tissue of interest. Due to its fundamental role, there has been a lot of progress in recent years regarding how and where to measure the AIF, how it influences DSC-MRI quantification, what artefacts one should avoid, and the design of automatic methods to measure the AIF. The AIF is also directly linked to most of the major sources of artefacts in CBF quantification, including partial volume effect, bolus delay and dispersion, peak truncation effects, contrast agent non-linearity, etc. While there have been a number of good review articles on DSC-MRI over the years, these are often comprehensive but, by necessity, with limited in-depth discussion of the various topics covered. This review article covers in greater depth the issues associated with the AIF and their implications for perfusion quantification using DSC-MRI.

The 39 steps: evading error and deciphering the secrets for accurate dynamic susceptibility contrast MRI

Dynamic susceptibility contrast (DSC) MRI is the most commonly used MRI method to assess cerebral perfusion and other related haemodynamic parameters. Although the technique is well established and used routinely in clinical centres, there are still many problems that impede accurate perfusion quantification. In this review article, we present 39 steps which guide the reader through the theoretical principles, practical decisions, potential problems, current limitations and latest advances in DSC-MRI. The 39 steps span the collection, analysis and interpretation of DSC-MRI data, expounding issues and possibilities relating to the contrast agent, the acquisition of DSC-MRI data, data pre-processing, the contrast concentration-time course, the arterial input function, deconvolution, common perfusion parameters, post-processing possibilities, patient studies, absolute versus relative quantification and automated analysis methods.

Failure of collateral blood flow is associated with infarct growth in ischemic stroke

Changes in collateral blood flow, which sustains brain viability distal to arterial occlusion, may impact infarct evolution but have not previously been demonstrated in humans. We correlated leptomeningeal collateral flow, assessed using novel perfusion magnetic resonance imaging (MRI) processing at baseline and 3 to 5 days, with simultaneous assessment of perfusion parameters. Perfusion raw data were averaged across three consecutive slices to increase leptomeningeal collateral vessel continuity after subtraction of baseline signal analogous to digital subtraction angiography. Changes in collateral quality, Tmax hypoperfusion severity, and infarct growth were assessed between baseline and days 3 to 5 perfusion-diffusion MRI. Acute MRI was analysed for 88 patients imaged 3 to 6 hours after ischemic stroke onset. Better collateral flow at baseline was associated with larger perfusion-diffusion mismatch (Spearman's Rho 0.51, P<0.001) and smaller baseline diffusion lesion volume (Rho -0.70, P<0.001). In 30 patients without reperfusion at day 3 to 5, deterioration in collateral quality between baseline and subacute imaging was strongly associated with absolute (P=0.02) and relative (P<0.001) infarct growth. The deterioration in collateral grade correlated with increased mean Tmax hypoperfusion severity (Rho -0.68, P<0.001). Deterioration in Tmax hypoperfusion severity was also significantly associated with absolute (P=0.003) and relative (P=0.002) infarct growth. Collateral flow is dynamic and failure is associated with infarct growth.

Comparison of three-dimensional pseudo-continuous arterial spin labeling perfusion imaging with gradient-echo and spin-echo dynamic susceptibility contrast MRI

PURPOSE

To compare the relative cerebral blood flow (CBF) obtained by pseudo-continuous arterial spin labeling sequence incorporated with volumetric fast spin-echo readout (3D-PCASL) with those by gradient-echo (GE) and spin-echo (SE) dynamic susceptibility contrast (DSC) MRI.

MATERIALS AND METHODS

Thirty patients with various neurological diseases participated in this study. In addition to 3D-PCASL, 15 patients received GE-DSC and the others received SE-DSC imaging on a 3 Tesla scanner. A cortical gray matter (GM) to white matter (WM) and a thalamus (TM) to WM CBF ratio were determined from each perfusion scan. In addition, histograms of relative CBF distributions were obtained from each method for comparison.

RESULTS

Significant correlations of CBF ratios were found between 3D-PCASL and the two DSC methods (P < 0.05). The 3D-PCASL resulted in GM/WM CBF ratios similar to SE-DSC but significantly smaller than GE-DSC (P = 2.3 × 10(-7) ). TM/WM CBF ratio obtained by 3D-PCASL was significantly smaller than those by GE- and SE-DSC (P = 4.1 × 10(-7) and 1.2 × 10(-6) , respectively). The histogram of relative CBF maps obtained from SE-DSC, after applied spatial smoothing, agreed well with that from 3D-PCASL.

CONCLUSION

This study suggested that perfusion images obtained from 3D-PCASL exhibited significant correlations with DSC-MRI, with greater microvascular weighting like SE-DSC.

Heterogeneity of cortical lesions in multiple sclerosis: an MRI perfusion study

In this study, dynamic susceptibility contrast-magnetic resonance imaging (DSC-MRI) was used to quantify the cerebral blood flow (CBF), the cerebral blood volume (CBV), and the mean transit time (MTT) and to analyze the changes in cerebral perfusion associated with the cortical lesions in 44 patients with relapsing-remitting multiple sclerosis. The cortical lesions showed a statistically significant reduction in CBF and CBV compared with the normal-appearing gray matter, whereas there were no significant changes in the MTT. The reduced perfusion suggests a reduction of metabolism because of the loss of cortical neurons. A small population of outliers showing an increased CBF and/or CBV has also been detected. The presence of hyperperfused outliers may imply that perfusion could evolve during inflammation. These findings show that perfusion is altered in cortical lesions and that DSC-MRI can be a useful tool to investigate more deeply the evolution of cortical lesions in multiple sclerosis.

Perfusion-weighted imaging-derived collateral flow index is a predictor of MCA M1 recanalization after i.v. thrombolysis

BACKGROUND AND PURPOSE

Recent studies highlight the role of CC in preserving ischemic penumbra. Some authors suggested the quality of CC could also impact recanalization. The purpose of this study is to test this hypothesis in patients who were treated with i.v. thrombolysis for MCA-M1 occlusion.

MATERIALS AND METHODS

A normalized index derived from Tmax maps (MR-PWI) was defined to quantify the CC deficit (nCCD) in 64 patients with stroke who underwent i.v. thrombolysis. Correlations between nCCD and parameters that may be altered by CC quality were tested (baseline NIHSS, volume of diffusion abnormalities, modified Rankin Scale at 3 months). The correlation between baseline nCCD and MCA-M1 recanalization rate at 24 hours was tested.

RESULTS

The nCCD is significantly correlated with NIHSS and with lesional volume (Pearson correlation test, positive correlations, respectively, 0.40, 0.57; P = .00089, P = 8.7e-07). The nCCD also has a significant predictive value on the full recanalization at 24 hours that decreases as TTT increases (logistic regression, P = .021). Furthermore, among patients who were treated within 3 hours, nCCD and recanalization are significantly correlated (correlation ratio test, eta2 = 0.23, P = .0023): Patients who did not achieve full recanalization have significantly higher nCCD than fully recanalized patients (Mann-Whitney U test, P = .007). In addition, the probability of full recanalization decreases as the nCCD increases (P = .021). nCCD (OR 0.988, 95% CI 0.977-0.999, P = .042) and full recanalization at 24 hours (OR 4.539, 95% CI 1.252-16.456, P = .021) are independent predictors of functional independence at 3 months.

CONCLUSIONS

The nCCD index is a predictor of full MCA-M1 recanalization in patients treated with i.v. thrombolysis.

Comparison of computed tomography perfusion and magnetic resonance imaging perfusion-diffusion mismatch in ischemic stroke

BACKGROUND AND PURPOSE

Perfusion imaging has the potential to select patients most likely to respond to thrombolysis. We tested the correspondence of computed tomography perfusion (CTP)-derived mismatch with contemporaneous perfusion-diffusion magnetic resonance imaging (MRI).

METHODS

Acute ischemic stroke patients 3 to 6 hours after onset had CTP and perfusion-diffusion MRI within 1 hour, before thrombolysis. Relative cerebral blood flow (relCBF) and time to peak of the deconvolved tissue residue function (Tmax) were calculated. The diffusion lesion (diffusion-weighted imaging) was registered to the CTP slabs and manually outlined to its maximal visual extent. Volumetric accuracy of CT-relCBF infarct core (compared with diffusion-weighted imaging) was tested. To reduce false-positive low CBF regions, relCBF core was restricted to voxels within a relative time-to-peak (relTTP) >4 seconds for lesion region of interest. The MR-Tmax >6 seconds perfusion lesion was automatically segmented and registered to CTP. Receiver-operating characteristic analysis determined the optimal CT-Tmax threshold to match MR-Tmax >6 seconds. Agreement of these CT parameters with MR perfusion-diffusion mismatch in coregistered slabs was assessed (mismatch ratio >1.2, absolute mismatch >10 mL, infarct core <70 mL).

RESULTS

In analysis of 49 patients (mean onset to CT, 213 minutes; mean CT to MR, 31 minutes), constraining relCBF <31% within the automated relTTP perfusion lesion region of interest reduced the median magnitude of volumetric error (vs diffusion-weighted imaging) from 47.5 mL to 15.8 mL (P<0.001). The optimal CT-Tmax threshold to match MR-Tmax >6 seconds was 6.2 seconds (95% confidence interval, 5.6-7.3 seconds; sensitivity, 91%; specificity, 70%; area under the curve, 0.87). Using CT-Tmax >6 seconds "penumbra" and relTTP-constrained relCBF "core," CT-based and MRI-based mismatch status was concordant in 90% (kappa=0.80).

CONCLUSIONS

Quantitative CTP mismatch classification using relCBF and Tmax is similar to perfusion-diffusion MRI. The greater accessibility of CTP may facilitate generalizability of mismatch-based selection in clinical practice and trials.

Quantitative dynamic contrast-enhanced MRI for mouse models using automatic detection of the arterial input function

Dynamic contrast-enhanced MRI (DCE-MRI) is widely accepted for the evaluation of cancer. DCE-MRI, a noninvasive measurement of microvessel permeability, blood volume and blood flow, is extremely useful for understanding disease mechanisms and monitoring therapeutic responses in preclinical research. For the accurate quantification of pharmacokinetic parameters using DCE-MRI, determination of the arterial input function (AIF) from a large arterial vessel near the tumor is required. However, a manual determination of AIF in mouse MR images is often difficult because of the small spatial dimensions or the location of the tumor. In this study, we propose an algorithm for the automatic detection of AIF from mouse DCE-MR images using Kendall's coefficient of concordance. The proposed method was tested with computer simulations and then applied to tumor-bearing mice (n = 8). Results from computer simulations showed that the proposed algorithm is capable of categorizing simulated AIF signals according to their noise levels. We found that the resulting pharmacokinetic parameters computed from our method were comparable with those from the manual determination of AIF, with acceptable differences in K(trans) (5.14 ± 3.60%), v(e) (6.02 ± 3.22%), v(p) (5.10 ± 7.05%) and k(ep) (5.38 ± 4.72%). The results of the current study suggest the usefulness of an automatically defined AIF using Kendall's coefficient of concordance for quantitative DCE-MRI in mouse models for cancer evaluation.

Evaluating effects of normobaric oxygen therapy in acute stroke with MRI-based predictive models

Background

Voxel-based algorithms using acute multiparametric-MRI data have been shown to accurately predict tissue outcome after stroke. We explored the potential of MRI-based predictive algorithms to objectively assess the effects of normobaric oxygen therapy (NBO), an investigational stroke treatment, using data from a pilot study of NBO in acute stroke.

Methods

The pilot study of NBO enrolled 11 patients randomized to NBO administered for 8 hours, and 8 Control patients who received room-air. Serial MRIs were obtained at admission, during gas therapy, post-therapy, and pre-discharge. Diffusion/perfusion MRI data acquired at admission (pre-therapy) was used in generalized linear models to predict the risk of lesion growth at subsequent time points for both treatment scenarios: NBO or Control.

Results

Lesion volume sizes 'during NBO therapy' predicted by Control-models were significantly larger (P = 0.007) than those predicted by NBO models, suggesting that ischemic lesion growth is attenuated during NBO treatment. No significant difference was found between the predicted lesion volumes at later time-points. NBO-treated patients, despite showing larger lesion volumes on Control-models than NBO-models, tended to have reduced lesion growth.

Conclusions

This study shows that NBO has therapeutic potential in acute ischemic stroke, and demonstrates the feasibility of using MRI-based algorithms to evaluate novel treatments in early-phase clinical trials.

MR perfusion imaging in acute ischemic stroke

Magnetic resonance (MR) perfusion imaging offers the potential for measuring brain perfusion in acute stroke patients, at a time when treatment decisions based on these measurements may affect outcomes dramatically. Rapid advancements in both acute stroke therapy and perfusion imaging techniques have resulted in continuing redefinition of the role that perfusion imaging should play in patient management. This review discusses the basic pathophysiology of acute stroke, the utility of different kinds of perfusion images, and research on the continually evolving role of MR perfusion imaging in acute stroke care.

Automatic selection of arterial input function on dynamic contrast-enhanced MR images

Dynamic susceptibility contrast-magnetic resonance imaging (DSC-MRI) data analysis requires the knowledge of the arterial input function (AIF) to quantify the cerebral blood flow (CBF), volume (CBV) and the mean transit time (MTT). AIF can be obtained either manually or using automatic algorithms. We present a method to derive the AIF on the middle cerebral artery (MCA). The algorithm draws a region of interest (ROI) where the MCA is located. Then, it uses a recursive cluster analysis on the ROI to select the arterial voxels. The algorithm had been compared on simulated data to literature state of art automatic algorithms and on clinical data to the manual procedure. On in silico data, our method allows to reconstruct the true AIF and it is less affected by partial volume effect bias than the other methods. In clinical data, automatic AIF provides CBF and MTT maps with a greater contrast level compared to manual AIF ones. Therefore, AIF obtained with the proposed method improves the estimate reliability and provides a quantitatively reliable physiological picture.

Validating a local Arterial Input Function method for improved perfusion quantification in stroke

In bolus-tracking perfusion magnetic resonance imaging (MRI), temporal dispersion of the contrast bolus due to stenosis or collateral supply presents a significant problem for accurate perfusion quantification in stroke. One means to reduce the associated perfusion errors is to deconvolve the bolus concentration time-course data with local Arterial Input Functions (AIFs) measured close to the capillary bed and downstream of the arterial abnormalities causing dispersion. Because the MRI voxel resolution precludes direct local AIF measurements, they must be extrapolated from the surrounding data. To date, there have been no published studies directly validating these local AIFs. We assess the effectiveness of local AIFs in reducing dispersion-induced perfusion error by measuring the residual dispersion remaining in the local AIF deconvolved perfusion maps. Two approaches to locating the local AIF voxels are assessed and compared with a global AIF deconvolution across 19 bolus-tracking data sets from patients with stroke. The local AIF methods reduced dispersion in the majority of data sets, suggesting more accurate perfusion quantification. Importantly, the validation inherently identifies potential areas for perfusion underestimation. This is valuable information for the identification of at-risk tissue and management of stroke patients.

Cerebral blood flow is the optimal CT perfusion parameter for assessing infarct core

BACKGROUND AND PURPOSE

CT perfusion (CTP) is widely and rapidly accessible for imaging acute ischemic stroke but has limited validation. Cerebral blood volume (CBV) has been proposed as the best predictor of infarct core. We tested CBV against other common CTP parameters using contemporaneous diffusion MRI.

METHODS

Patients with acute ischemic stroke<6 hours after onset had CTP and diffusion MRI<1 hour apart, before any reperfusion therapies. CTP maps of time to peak (TTP), absolute and relative CBV, cerebral blood flow (CBF), mean transit time (MTT), and time to peak of the deconvolved tissue residue function (Tmax) were generated. The diffusion lesion was manually outlined to its maximal visual extent. Receiver operating characteristic (ROC) analysis area under the curve (AUC) was used to quantify the correspondence of each perfusion parameter to the coregistered diffusion-weighted imaging lesion. Optimal thresholds were determined (Youden index).

RESULTS

In analysis of 98 CTP slabs (54 patients, median onset to CT 190 minutes, median CT to MR 30 minutes), relative CBF performed best (AUC, 0.79; 95% CI, 0.77-81), significantly better than absolute CBV (AUC, 0.74; 95% CI, 0.73-0.76). The optimal threshold was <31% of mean contralateral CBF. Specificity was reduced by low CBF/CBV in noninfarcted white matter in cases with reduced contrast bolus intensity and leukoaraiosis.

CONCLUSIONS

In contrast to previous reports, CBF corresponded with the acute diffusion-weighted imaging lesion better than CBV, although no single threshold avoids detection of false-positive regions in unaffected white matter. This relates to low signal-to-noise ratio in CTP maps and emphasizes the need for optimized acquisition and postprocessing.

T1- and T2*-dominant extravasation correction in DSC-MRI: part I--theoretical considerations and implications for assessment of tumor hemodynamic properties

We present a novel contrast agent (CA) extravasation-correction method based on analysis of the tissue residue function for assessment of multiple hemodynamic parameters. The method enables semiquantitative determination of the transfer constant and can be used to distinguish between T(1)- and T(2)(*)-dominant extravasation effects, while being insensitive to variations in tissue mean transit time (MTT). Results in 101 patients with confirmed glioma suggest that leakage-corrected absolute cerebral blood volume (CBV) values obtained with the proposed method provide improved overall survival prediction compared with normalized CBV values combined with an established leakage-correction method. Using a standard gradient-echo echo-planar imaging sequence, ∼60% and 10% of tumors with detectable CA extravasation mainly exhibited T(1)- and T(2)(*)-dominant leakage effects, respectively. The remaining 30% of leaky tumors had mixed T(1)- and T(2)(*)-dominant effects. Using an MTT-sensitive correction method, our results show that CBV is underestimated when tumor MTT is significantly longer than MTT in the reference tissue. Furthermore, results from our simulations suggest that the relative contribution of T(1)- versus T(2)(*)-dominant extravasation effects is strongly dependent on the effective transverse relaxivity in the extravascular space and may thus be a potential marker for cellular integrity and tissue structure.

Perfusion MRI using dynamic-susceptibility contrast MRI: quantification issues in patient studies

OBJECTIVES

Measurement of perfusion accurately, noninvasively, and with good spatial resolution offers the chance to characterize abnormal tissue in many clinical conditions. Dynamic-susceptibility contrast (DSC) MRI, also known as bolus-tracking MRI, is a dynamic MRI method to measure perfusion and other related hemodynamic parameters. This review article describes the principles involved in perfusion quantification using DSC-MRI as well as discusses the main issues affecting its quantification in patient studies.

CONCLUSIONS

It is shown that DSC-MRI is a very powerful technique that provides important information regarding cerebral hemodynamics. The relatively high contrast-to-noise ratio, fast acquisition, and wealth of information available have made DSC-MRI the most commonly used MRI technique for the rapid assessment of the brain hemodynamics in clinical investigations. While very important advances have been achieved in the last 2 decades, there are still some remaining limitations that users should be aware of to avoid misinterpretation of the findings and to make the most of the invaluable information provided by perfusion MRI.

Deconvolution-Based CT and MR Brain Perfusion Measurement: Theoretical Model Revisited and Practical Implementation Details

Deconvolution-based analysis of CT and MR brain perfusion data is widely used in clinical practice and it is still a topic of ongoing research activities. In this paper, we present a comprehensive derivation and explanation of the underlying physiological model for intravascular tracer systems. We also discuss practical details that are needed to properly implement algorithms for perfusion analysis. Our description of the practical computer implementation is focused on the most frequently employed algebraic deconvolution methods based on the singular value decomposition. In particular, we further discuss the need for regularization in order to obtain physiologically reasonable results. We include an overview of relevant preprocessing steps and provide numerous references to the literature. We cover both CT and MR brain perfusion imaging in this paper because they share many common aspects. The combination of both the theoretical as well as the practical aspects of perfusion analysis explicitly emphasizes the simplifications to the underlying physiological model that are necessary in order to apply it to measured data acquired with current CT and MR scanners.

Evaluation of signal formation in local arterial input function measurements of dynamic susceptibility contrast MRI

Correct arterial input function (AIF) measurements in dynamic susceptibility contrast-MRI are crucial for quantification of the hemodynamic parameters. Often a single global AIF is selected near a large brain-feeding artery. Alternatively, local AIF measurements aim for voxel-specific AIFs from smaller arteries. Because local AIFs are measured higher in the arterial-tree, it is assumed that these will reflect the true input of the microvasculature much better. However, do the measured local AIFs reflect the true concentration-time curves of small arteries? To answer this question, in vivo data were used to evaluate local AIF candidates selected based on two different types of angiograms. For interpretation purposes, a 3D numerical model that simulated partial-volume effects in local AIF measurements was created and the simulated local AIFs were compared to the ground truth. The findings are 2-fold. First, the in vivo data showed that the shape-characteristics of local AIFs are similar to the shape-characteristics of gray matter concentration-time curves. Second, these findings are supported by the simulations showing broadening of the measured local AIFs compared to the ground truth. These findings are suggesting that local AIF measurements do not necessarily reflect the true concentration-time curve in small arteries.

A novel AIF tracking method and comparison of DCE-MRI parameters using individual and population-based AIFs in human breast cancer

Quantitative analysis of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) data requires the accurate determination of the arterial input function (AIF). A novel method for obtaining the AIF is presented here and pharmacokinetic parameters derived from individual and population-based AIFs are then compared. A Philips 3.0 T Achieva MR scanner was used to obtain 20 DCE-MRI data sets from ten breast cancer patients prior to and after one cycle of chemotherapy. Using a semi-automated method to estimate the AIF from the axillary artery, we obtain the AIF for each patient, AIF(ind), and compute a population-averaged AIF, AIF(pop). The extended standard model is used to estimate the physiological parameters using the two types of AIFs. The mean concordance correlation coefficient (CCC) for the AIFs segmented manually and by the proposed AIF tracking approach is 0.96, indicating accurate and automatic tracking of an AIF in DCE-MRI data of the breast is possible. Regarding the kinetic parameters, the CCC values for K(trans), v(p) and v(e) as estimated by AIF(ind) and AIF(pop) are 0.65, 0.74 and 0.31, respectively, based on the region of interest analysis. The average CCC values for the voxel-by-voxel analysis are 0.76, 0.84 and 0.68 for K(trans), v(p) and v(e), respectively. This work indicates that K(trans) and v(p) show good agreement between AIF(pop) and AIF(ind) while there is a weak agreement on v(e).

Quantitative effects of using compressed sensing in dynamic contrast enhanced MRI

Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) involves the acquisition of images before, during and after the injection of a contrast agent. In order to perform quantitative modeling on the resulting signal intensity time course, data must be acquired rapidly, which compromises spatial resolution, signal to noise and/or field of view. One approach that may allow for gains in temporal or spatial resolution or signal to noise of an individual image is to use compressed sensing (CS) MRI. In this study, we demonstrate the accuracy of extracted pharmacokinetic parameters from DCE-MRI data obtained as part of pre-clinical and clinical studies in which fully sampled acquisitions have been retrospectively undersampled by factors of 2, 3 and 4 in Fourier space and then reconstructed with CS. The mean voxel-level concordance correlation coefficient for K(trans) (i.e. the volume transfer constant) obtained from the 2× accelerated and the fully sampled data is 0.92 and 0.90 for mouse and human data, respectively; for 3×, the results are 0.79 and 0.79, respectively; for 4×, the results are 0.64 and 0.70, respectively. The mean error in the tumor mean K(trans) for the mouse and human data at 2× acceleration is 1.8% and -4.2%, respectively; at 3×, 3.6% and -10%, respectively; at 4×, 7.8% and -12%, respectively. These results suggest that CS combined with appropriate reduced acquisitions may be an effective approach to improving image quality in DCE-MRI.

Real-time diffusion-perfusion mismatch analysis in acute stroke

Diffusion-perfusion mismatch can be used to identify acute stroke patients that could benefit from reperfusion therapies. Early assessment of the mismatch facilitates necessary diagnosis and treatment decisions in acute stroke. We developed the RApid processing of PerfusIon and Diffusion (RAPID) for unsupervised, fully automated processing of perfusion and diffusion data for the purpose of expedited routine clinical assessment. The RAPID system computes quantitative perfusion maps (cerebral blood volume, CBV; cerebral blood flow, CBF; mean transit time, MTT; and the time until the residue function reaches its peak, T(max)) using deconvolution of tissue and arterial signals. Diffusion-weighted imaging/perfusion-weighted imaging (DWI/PWI) mismatch is automatically determined using infarct core segmentation of ADC maps and perfusion deficits segmented from T(max) maps. The performance of RAPID was evaluated on 63 acute stroke cases, in which diffusion and perfusion lesion volumes were outlined by both a human reader and the RAPID system. The correlation of outlined lesion volumes obtained from both methods was r(2) = 0.99 for DWI and r(2) = 0.96 for PWI. For mismatch identification, RAPID showed 100% sensitivity and 91% specificity. The mismatch information is made available on the hospital's PACS within 5-7 min. Results indicate that the automated system is sufficiently accurate and fast enough to be used for routine care as well as in clinical trials.