Whole brain quantitative CBF, CBV, and MTT measurements using MRI bolus tracking: implementation and application to data acquired from hyperacute stroke patients

Pre-operative spinal cord perfusion quantified by DSC MRI as a predictor of post-operative prognosis in patients with cervical spondylotic myelopathy

OBJECTIVE

This study aims to investigate the potential of preoperative blood supply condition measured by dynamic susceptibility contract (DSC) MRI in prediction of postoperative outcomes for patients with cervical spondylotic myelopathy (CSM).

MATERIALS AND METHOD

Thirty-nine patients (Age: 61 ± 7, male: 23, female: 16) with CSM who underwent laminoplasty were enrolled. All patients received DSC MRI before the operation. Five parameters include Enhance, rEnhance, full width at half maxima (FWHM), Slope1 and Slope2 in DSC MRI, were calculated at all the compressed spinal cord segments. Clinical outcomes were evaluated by modified Japanese Orthopaedic Association (mJOA) scores. Patients were divided into two groups based on mJOA recovery rate of 5 years: good recovery (> 50%) or poor recovery (≤ 50%). The difference between two groups were compared. The value of DSC MRI to CSM was evaluated by logistic and receiver operating characteristic (ROC) curve analysis.

RESULTS

There were 26 patients in good recovery group and 13 patients in poor recovery group. The baseline characteristics, including age, gender, preoperative mJOA score, and smoking status showed no significant difference between the two groups (all p > 0.05). The FWHM was significantly higher in the poor recovery group (9.77 ± 2.78) compared to the good recovery group (6.64 ± 1.65) (p = 0.002). Logistic regression analysis indicated that an increased FWHM was a significant risk factor for poor prognosis recovery (p = 0.013, OR = 0.392, 95%CI: 0.187-0.822). The AUC of FWHM for ROC was 0.843 (95% CI: 0.710-0.975) with a p value of 0.001. In addition, an FWHM greater than 5.87, with a sensitivity of 92.3% and specificity of 69.2%, was found to be an independent risk factor for poor postoperative recovery in patients with CSM.

CONCLUSION

In this study, we successfully quantified the spinal cord blood supply condition by DSC MRI technique. We found that an increase in FWHM was an independent risk factor for poor postoperative recovery in CSM patients. Specifically, patients with FWHM > 5.87 have a poor postoperative recovery.

Spinal cord perfusion is associated with microstructural damage in cervical spondylotic myelopathy patients who underwent cervical laminoplasty

OBJECTIVES

To investigate the association between spinal cord perfusion and microstructural damage in CSM patients who underwent cervical laminoplasty using MR dynamic susceptibility contrast (DSC), diffusion tensor imaging (DTI), and neurite orientation dispersion and density imaging (NODDI) techniques.

METHODS

A follow-up cohort study was conducted with 53 consecutively recruited CSM patients who had undergone cervical laminoplasty 12-14 months after the surgery from April 2016 to December 2016. Twenty-one aged-matched healthy volunteers were recruited as controls. For each patient, decompressed spinal cord levels were imaged on a 3.0-T MRI scanner by diffusion and DSC sequences to quantify the degrees of microstructural damage and perfusion conditions, respectively. The diffusion data were analyzed by DTI and NODDI models to produce diffusion metrics. Classic indicator dilution model was used to quantify the DSC metrics. Mann-Whitney U test was performed for comparison of diffusion metrics between patients and healthy controls. Pearson correlation was used to explore the associations between the metrics of spinal cord perfusion and microstructural damage.

RESULTS

DTI metrics, neurite density, and isotropic volume fraction had significant differences between postoperative patients and healthy controls. Pearson correlation test showed that SCBV was significantly positively correlated with RD, MD, and ODI, and negatively correlated with FA and NDI. SCBF was found to be significantly positively correlated with RD and MD, and negatively correlated with FA.

CONCLUSIONS

Increased spinal cord perfusion quantified by DSC is associated with microstructural damage assessed by diffusion MRI in CSM patients who underwent cervical laminoplasty.

CLINICAL RELEVANCE STATEMENT

This study found that the spinal cord perfusion is associated with microstructural damage in postoperative cervical spondylotic myelopathy patients, indicating that high perfusion may play a role in the pathophysiological process of cervical spondylotic myelopathy and deserves more attention.

KEY POINTS

• Spinal cord microstructural damage can be persistent despite the compression had been relieved 12-14 months after the cervical laminoplasty in cervical spondylotic myelopathy (CSM) patients. • Spinal cord perfusion is associated with microstructural damage in CSM patients after the cervical laminoplasty. • Inflammation in the decompressed spinal cord may be a cause of increased perfusion and is associated with microstructural damage during the recovery period of CSM.

Differentiation of Glioblastoma and Brain Metastases by MRI-Based Oxygen Metabolomic Radiomics and Deep Learning

Glioblastoma (GB) and brain metastasis (BM) are the most frequent types of brain tumors in adults. Their therapeutic management is quite different and a quick and reliable initial characterization has a significant impact on clinical outcomes. However, the differentiation of GB and BM remains a major challenge in today's clinical neurooncology due to their very similar appearance in conventional magnetic resonance imaging (MRI). Novel metabolic neuroimaging has proven useful for improving diagnostic performance but requires artificial intelligence for implementation in clinical routines. Here; we investigated whether the combination of radiomic features from MR-based oxygen metabolism ("oxygen metabolic radiomics") and deep convolutional neural networks (CNNs) can support reliably pre-therapeutic differentiation of GB and BM in a clinical setting. A self-developed one-dimensional CNN combined with radiomic features from the cerebral metabolic rate of oxygen (CMRO₂) was clearly superior to human reading in all parameters for classification performance. The radiomic features for tissue oxygen saturation (mitoPO₂; i.e., tissue hypoxia) also showed better diagnostic performance compared to the radiologists. Interestingly, both the mean and median values for quantitative CMRO₂ and mitoPO₂ values did not differ significantly between GB and BM. This demonstrates that the combination of radiomic features and DL algorithms is more efficient for class differentiation than the comparison of mean or median values. Oxygen metabolic radiomics and deep neural networks provide insights into brain tumor phenotype that may have important diagnostic implications and helpful in clinical routine diagnosis.

Radiophysiomics: Brain Tumors Classification by Machine Learning and Physiological MRI Data

The precise initial characterization of contrast-enhancing brain tumors has significant consequences for clinical outcomes. Various novel neuroimaging methods have been developed to increase the specificity of conventional magnetic resonance imaging (cMRI) but also the increased complexity of data analysis. Artificial intelligence offers new options to manage this challenge in clinical settings. Here, we investigated whether multiclass machine learning (ML) algorithms applied to a high-dimensional panel of radiomic features from advanced MRI (advMRI) and physiological MRI (phyMRI; thus, radiophysiomics) could reliably classify contrast-enhancing brain tumors. The recently developed phyMRI technique enables the quantitative assessment of microvascular architecture, neovascularization, oxygen metabolism, and tissue hypoxia. A training cohort of 167 patients suffering from one of the five most common brain tumor entities (glioblastoma, anaplastic glioma, meningioma, primary CNS lymphoma, or brain metastasis), combined with nine common ML algorithms, was used to develop overall 135 classifiers. Multiclass classification performance was investigated using tenfold cross-validation and an independent test cohort. Adaptive boosting and random forest in combination with advMRI and phyMRI data were superior to human reading in accuracy (0.875 vs. 0.850), precision (0.862 vs. 0.798), F-score (0.774 vs. 0.740), AUROC (0.886 vs. 0.813), and classification error (5 vs. 6). The radiologists, however, showed a higher sensitivity (0.767 vs. 0.750) and specificity (0.925 vs. 0.902). We demonstrated that ML-based radiophysiomics could be helpful in the clinical routine diagnosis of contrast-enhancing brain tumors; however, a high expenditure of time and work for data preprocessing requires the inclusion of deep neural networks.

Metabolic Tumor Microenvironment Characterization of Contrast Enhancing Brain Tumors Using Physiologic MRI

The tumor microenvironment is a critical regulator of cancer development and progression as well as treatment response and resistance in brain neoplasms. The available techniques for investigation, however, are not well suited for noninvasive in vivo characterization in humans. A total of 120 patients (59 females; 61 males) with newly diagnosed contrast-enhancing brain tumors (64 glioblastoma, 20 brain metastases, 15 primary central nervous system (CNS) lymphomas (PCNSLs), and 21 meningiomas) were examined with a previously established physiological MRI protocol including quantitative blood-oxygen-level-dependent imaging and vascular architecture mapping. Six MRI biomarker maps for oxygen metabolism and neovascularization were fused for classification of five different tumor microenvironments: glycolysis, oxidative phosphorylation (OxPhos), hypoxia with/without neovascularization, and necrosis. Glioblastoma showed the highest metabolic heterogeneity followed by brain metastasis with a glycolysis-to-OxPhos ratio of approximately 2:1 in both tumor entities. In addition, glioblastoma revealed a significant higher percentage of hypoxia (24%) compared to all three other brain tumor entities: brain metastasis (7%; p < 0.001), PCNSL (8%; p = 0.001), and meningioma (8%; p = 0.003). A more aggressive biological brain tumor behavior was associated with a higher percentage of hypoxia and necrosis and a lower percentage of remaining vital tumor tissue and aerobic glycolysis. The proportion of oxidative phosphorylation, however, was rather similar (17–26%) for all four brain tumor entities. Tumor microenvironment (TME) mapping provides insights into neurobiological differences of contrast-enhancing brain tumors and deserves further clinical cancer research attention. Although there is a long roadmap ahead, TME mapping may become useful in order to develop new diagnostic and therapeutic approaches.

Hypoxia and Microvascular Alterations Are Early Predictors of IDH-Mutated Anaplastic Glioma Recurrence

Simple Summary

Anaplastic gliomas (AGs) are considered the most common and aggressive primary brain tumors of young adults with inevitable recurrence and treatment failure. The aim of this study was to investigate whether the imaging biomarkers of hypoxia, microvascular architecture and neovascularization activity can be of assistance to detect pathophysiological changes in the early developmental stages of isocitrate-dehydrogenase (IDH) mutated AG recurrence. We evaluated 142 physiological magnetic resonance imaging follow-up examinations as a part of the conventional magnetic resonance imaging (MRI) protocol in 60 AG patients after standard therapy. Physiological MRI biomarkers showed intensifying local tissue hypoxia 250 days prior to radiological recurrence with following upregulation of neovascularization activity 50 to 70 days later. Integration of physiological MRI in the monitoring of AG patients may be of clinical significance to make personalized decision of early tumor recurrence without an additional delay for multimodal therapy.

Abstract

Anaplastic gliomas (AG) represents aggressive brain tumors that often affect young adults. Although isocitrate-dehydrogenase (IDH) gene mutation has been identified as a more favorable prognostic factor, most IDH-mutated AG patients are confronted with tumor recurrence. Hence, increased knowledge about pathophysiological precursors of AG recurrence is urgently needed in order to develop precise diagnostic monitoring and tailored therapeutic approaches. In this study, 142 physiological magnetic resonance imaging (phyMRI) follow-up examinations in 60 AG patients after standard therapy were evaluated and magnetic resonance imaging (MRI) biomarker maps for microvascular architecture and perfusion, neovascularization activity, oxygen metabolism, and hypoxia calculated. From these 60 patients, 34 patients developed recurrence of the AG, and 26 patients showed no signs for AG recurrence during the study period. The time courses of MRI biomarker changes were analyzed regarding early pathophysiological alterations over a one-year period before radiological AG recurrence or a one-year period of stable disease for patients without recurrence, respectively. We detected intensifying local tissue hypoxia 250 days prior to radiological recurrence which initiated upregulation of neovascularization activity 50 to 70 days later. These changes were associated with a switch from an avascular infiltrative to a vascularized proliferative phenotype of the tumor cells another 30 days later. The dynamic changes of blood perfusion, microvessel density, neovascularization activity, and oxygen metabolism showed a close physiological interplay in the one-year period prior to radiological recurrence of IDH-mutated AG. These findings may path the wave for implementing both new MR-based imaging modalities for routine follow-up monitoring of AG patients after standard therapy and furthermore may support the development of novel, tailored therapy options in recurrent AG.

Measuring global impairment of cerebral perfusion using dynamic susceptibility contrast perfusion-weighted imaging in out-of-hospital cardiac arrest survivors: A prospective preliminary study

BACKGROUND AND PURPOSE

This study aimed to assess the global impairment and prognostic performance of cerebral perfusions (CP) measured by dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) in out-of-hospital cardiac arrest (OHCA) patients after sustained restoration of spontaneous circulation (ROSC).

MATERIALS AND METHODS

This is a single-centre, prospective observational study. OHCA patients performed DSC-PWI within 8 h after ROSC were enrolled. We quantified the CP parameters, such as cerebral blood volume (CBV), cerebral blood flow (CBF), mean transit time (MTT), time to peak (TTP), and time to maximum of the residue function (Tmax) either by normalization or arterial input function (AIF). The primary and secondary outcomes were survival to discharge and comparison of prognostic performance between CP parameters and serum neuron-specific enolase (NSE) using area under the receiver operating characteristic (AUROC) and sensitivity values.

RESULTS

Thirty-one patients were included in this study. CBV and TTP quantified by normalization, and MTT and Tmax quantified by AIF showed significantly higher CP values in the non-survival group (p = 0.02, 0.03, 0.02, and <0.01, respectively). Their AUROCs and 100% specific sensitivities were 0.74/25.0%, 0.60/33.3%, 0.75/56.3%, and 0.79/43.8%, respectively. MTT quantified by AIF showed sensitivity in predicting mortality at an early stage of PCA care, comparable with NSE.

CONCLUSION

Hyperaemia and delayed CP were generally observed in OHCA patients regardless of outcomes. MTT and Tmax quantified by AIF have prognostic performance in predicting mortality, comparable with NSE. Further prospective multicentre studies are required to confirm our results.

Predicting Glioblastoma Response to Bevacizumab Through MRI Biomarkers of the Tumor Microenvironment

PURPOSE

Glioblastoma (GB) is one of the most vascularized of all solid tumors and, therefore, represents an attractive target for antiangiogenic therapies. Many lesions, however, quickly develop escape mechanisms associated with changes in the tumor microenvironment (TME) resulting in rapid treatment failure. To prevent patients from adverse effects of ineffective therapy, there is a strong need to better predict and monitor antiangiogenic treatment response.

PROCEDURES

We utilized a novel physiological magnetic resonance imaging (MRI) method combining the visualization of oxygen metabolism and neovascularization for classification of five different TME compartments: necrosis, hypoxia with/without neovascularization, oxidative phosphorylation, and aerobic glycolysis. This approach, termed TME mapping, was used to monitor changes in tumor biology and pathophysiology within the TME in response to bevacizumab treatment in 18 patients with recurrent GB.

RESULTS

We detected dramatic changes in the TME by rearrangement of its compartments after the onset of bevacizumab treatment. All patients showed a decrease in active tumor volume and neovascularization as well as an increase in hypoxia and necrosis in the first follow-up after 3 months. We found that recurrent GB with a high percentage of neovascularization and active tumor before bevacizumab onset showed a poor or no treatment response.

CONCLUSIONS

TME mapping might be useful to develop strategies for patient stratification and response prediction before bevacizumab onset.

Vascular architecture mapping for early detection of glioblastoma recurrence

OBJECTIVE

Treatment failure and inevitable tumor recurrence are the main reasons for the poor prognosis of glioblastoma (GB). Gross-total resection at repeat craniotomy for GB recurrence improves patient overall survival but requires early and reliable detection. It is known, however, that even advanced MRI approaches have limited diagnostic performance for distinguishing tumor progression from pseudoprogression. The novel MRI technique of vascular architectural mapping (VAM) provides deeper insight into tumor microvascularity and neovascularization. In this study the authors evaluated the usefulness of VAM for the monitoring of GB patients and quantitatively analyzed the features of neovascularization of early- and progressed-stage GB recurrence.

METHODS

In total, a group of 115 GB patients who received overall 374 follow-up MRI examinations after standard treatment were retrospectively evaluated in this study. The clinical routine MRI (cMRI) protocol at 3 Tesla was extended with the authors’ experimental VAM approach, requiring 2 minutes of extra time for data acquisition. Custom-made MATLAB software was used for calculation of imaging biomarker maps of macrovascular perfusion from perfusion cMRI as well as of microvascular perfusion and architecture from VAM data. Additionally, cMRI data were analyzed by two board-certified radiologists in consensus. Statistical procedures included receiver operating characteristic (ROC) analysis to determine diagnostic performances for GB recurrence detection.

RESULTS

Overall, cMRI showed GB recurrence in 89 patients, and in 28 of these patients recurrence was detected earlier with VAM data, by 1 (20 patients) or 2 (8 patients) follow-up examinations, than with cMRI data. The mean time difference between recurrence detection with VAM and cMRI data was 147 days. During this time period the mean tumor volume increased significantly (p < 0.001) from 9.7 to 26.8 cm3. Quantitative analysis of imaging biomarkers demonstrated microvascular but no macrovascular hyperperfusion in early GB recurrence. Therefore, ROC analysis revealed superior diagnostic performance for VAM compared with cMRI.

CONCLUSIONS

This study demonstrated that the targeted assessment of microvascular features using the VAM technique provided valuable information about early neovascularization activity in recurrent GB that is complementary to perfusion cMRI and may be helpful for earlier and more precise monitoring of patients suffering from GB. This VAM approach is compatible with existing cMRI protocols. Prospective clinical trials are necessary to investigate the clinical usefulness and potential benefit of increased overall survival with the use of VAM in patients with recurrent GB.

Intratumoral heterogeneity of oxygen metabolism and neovascularization uncovers 2 survival-relevant subgroups of IDH1 wild-type glioblastoma

Background

The intratumoral heterogeneity of oxygen metabolism in combination with variable patterns of neovascularization (NV) as well as reprogramming of energy metabolism affects the landscape of tumor microenvironments (TMEs) in glioblastoma. Knowledge of the hypoxic and perivascular niches within the TME is essential for understanding treatment failure.

Methods

Fifty-two patients with untreated glioblastoma (isocitrate dehydrogenase 1 wild type [IDH1wt]) were examined with a physiological MRI protocol including a multiparametric quantitative blood oxygen level dependent (qBOLD) approach and vascular architecture mapping (VAM). Imaging biomarker information about oxygen metabolism (mitochondrial oxygen tension) and neovascularization (microvascular density and type) were fused for classification of 6 different TMEs: necrosis, hypoxia with/without neovascularization, oxidative phosphorylation (OxPhos), and glycolysis with/without neovascularization. Association of the different TME volume fractions with progression-free survival (PFS) was assessed using Kaplan-Meier analysis and Cox proportional hazards models.

Results

A common spatial structure of TMEs was detected: central necrosis surrounded by tumor hypoxia (with defective and functional neovasculature) and different TMEs with a predominance of OxPhos and glycolysis for energy production, respectively. The percentage of the different TMEs on the total tumor volume uncovered 2 clearly different subtypes of glioblastoma IDH1wt: a glycolytic dominated phenotype with predominantly functional neovasculature and a necrotic/hypoxic dominated phenotype with approximately 50% of defective neovasculature. Patients with a necrotic/hypoxic dominated phenotype showed significantly shorter PFS (P = 0.035).

Conclusions

Our non-invasive mapping approach allows for classification of the TME and detection of tumor-supportive niches in glioblastoma which may be helpful for both clinical patient management and research.

Estimating the discretization dependent accuracy of perfusion in coupled capillary flow measurements

One-compartment models are widely used to quantify hemodynamic parameters such as perfusion, blood volume and mean transit time. These parameters are routinely used for clinical diagnosis and monitoring of disease development and are thus of high relevance. However, it is known that common estimation techniques are discretization dependent and values can be erroneous. In this paper we present a new model that enables systematic quantification of discretization errors. Specifically, we introduce a continuous flow model for tracer propagation within the capillary tissue, used to evaluate state-of-the-art one-compartment models. We demonstrate that one-compartment models are capable of recovering perfusion accurately when applied to only one compartment, i.e. the whole region of interest. However, substantial overestimation of perfusion occurs when applied to fractions of a compartment. We further provide values of the estimated overestimation for various discretization levels, and also show that overestimation can be observed in real-life applications. Common practice of using compartment models for fractions of tissue violates model assumptions and careful interpretation is needed when using the computed values for diagnosis and treatment planning.

Detection of severity in Alzheimer's disease (AD) using computational modeling

The prevalent cause of dementia - Alzheimer's disease (AD) is characterized by an early cholinergic deficit that is in part responsible for the cognitive deficits (especially memory and attention defects). Prolonged AD leads to moderate-to-severe AD, which is one of the leading causes of death. Placebo-controlled, randomized clinical trials have shown significant effects of Acetyl cholin esterase inhibitors (ChEIs) on function, cognition, activities of daily living (ADL) and behavioral symptoms in patients. Studies have shown comparable effects for ChEIs in patients with moderate-to-severe or mild AD. Setting a fixed measurement (e.g. a Mini-Mental State Examination score, as a 'when to stop treatment limit) for the disease is not clinically rational. Detection of changed regional cerebral blood flow in mild cognitive impairment and early AD by perfusion-weighted magnetic resonance imaging has been a challenge. The utility of perfusion-weighted magnetic resonance imaging (PW-MRI) for detecting changes in regional cerebral blood flow (rCBF) in patients with mild cognitive impairment (MCI) and early AD was evaluated. We describe a computer aided prediction model to determine the severity of AD using known data in literature. We designed an automated system for the determination of AD severity. It is used to predict the clinical cases and conditions with disagreements from specialist. The model described is useful in clinical practice to validate diagnosis.

Recurrence of glioblastoma is associated with elevated microvascular transit time heterogeneity and increased hypoxia

Dynamic susceptibility contrast (DSC) perfusion MRI provide information about differences in macro- and microvasculature when executed with gradient-echo (GE; sensitive to macrovasculature) and spin-echo (SE; sensitive to microvasculature) contrast. This study investigated whether there are differences between macro- and microvascular transit time heterogeneity (MVTH and µVTH) and tissue oxygen tension (PO2_mit) in newly-diagnosed and recurrent glioblastoma. Fifty-seven patients with glioblastoma (25 newly-diagnosed/32 recurrent) were examined with GE- and SE-DSC perfusion sequences, and a quantitative blood-oxygen-level-dependent (qBOLD) approach. Maps of MVTH, µVTH and coefficient of variation (MCOV and µCOV) were calculated from GE- and SE-DSC data, respectively, using an extended flow-diffusion equation. PO2_mit maps were calculated from qBOLD data. Newly-diagnosed and recurrent glioblastoma showed significantly lower ( P ≤ 0.001) µCOV values compared to both normal brain and macrovasculature (MCOV) of the lesions. Recurrent glioblastoma had significantly higher µVTH ( P = 0.014) and µCOV ( P = 0.039) as well as significantly lower PO2_mit values ( P = 0.008) compared to newly-diagnosed glioblastoma. The macrovasculature, however, showed no significant differences. Our findings provide evidence of microvascular adaption in the disorganized tumor vasculature for retaining the metabolic demands in stress response of therapeutically-uncontrolled glioblastomas. Thus, µVTH and PO2_mit mapping gives insight into the tumor microenvironment (vascular and hypoxic niches) responsible for therapy resistance.

MR Imaging-derived Oxygen Metabolism and Neovascularization Characterization for Grading and IDH Gene Mutation Detection of Gliomas

Purpose To explore the diagnostic performance of physiological magnetic resonance (MR) imaging of oxygen metabolism and neovascularization activity for grading and characterization of isocitrate dehydrogenase (IDH) gene mutation status of gliomas. Materials and Methods This retrospective study had institutional review board approval; written informed consent was obtained from all patients. Eighty-three patients with histopathologically proven glioma (World Health Organization [WHO] grade II-IV) were examined with quantitative blood oxygen level-dependent imaging and vascular architecture mapping. Biomarker maps of neovascularization activity (microvessel radius, microvessel density, and microvessel type indicator [MTI]) and oxygen metabolism (oxygen extraction fraction [OEF] and cerebral metabolic rate of oxygen [CMRO₂]) were calculated. Receiver operating characteristic analysis was used to determine diagnostic performance for grading and detection of IDH gene mutation status. Results Low-grade (WHO grade II) glioma showed areas with increased OEF (+18%, P < .001, n = 20), whereas anaplastic glioma (WHO grade III) and glioblastoma (WHO grade IV) showed decreased OEF when compared with normal brain tissue (-54% [P < .001, n = 21] and -49% [P < .001, n = 41], respectively). This allowed clear differentiation between low- and high-grade glioma (area under the receiver operating characteristic curve [AUC], 1) for the patient cohort. MTI had the highest diagnostic performance (AUC, 0.782) for differentiation between gliomas of grades III and IV among all biomarkers. CMRO₂ was decreased (P = .037) in low-grade glioma with a mutated IDH gene, and MTI was significantly increased in glioma grade III with IDH mutation (P = .013) when compared with the IDH wild-type counterparts. CMRO₂ showed the highest diagnostic performance for IDH gene mutation detection in low-grade glioma (AUC, 0.818) and MTI in high-grade glioma (AUC, 0.854) and for all WHO grades (AUC, 0.899) among all biomarkers. Conclusion MR imaging-derived oxygen metabolism and neovascularization characterization may be useful for grading and IDH mutation detection of gliomas and requires only 7 minutes of extra imaging time. ^© RSNA, 2016 Online supplemental material is available for this article.

Quantification of serial changes in cerebral blood volume and metabolism in patients with recurrent glioblastoma undergoing antiangiogenic therapy

OBJECTIVES

To evaluate the usefulness of quantitative advanced magnetic resonance imaging (MRI) methods for assessment of antiangiogenic therapy (AAT) response in recurrent glioblastoma multiforme (GBM).

METHODS

Eighteen patients with recurrent GBM received bevacizumab and 18 patients served as control group. Baseline MRI and two follow-up examinations were acquired every 3-5 months using dynamic susceptibility-weighted contrast (DSC) perfusion MRI and (1)H-MR spectroscopic imaging ((1)H-MRSI). Maps of absolute cerebral blood volume (aCBV) were coregistered with choline (Cho) and N-acetyl-aspartate (NAA) concentrations and compared to usually used relative parameters as well as controls.

RESULTS

Perfusion significantly decreased in responding and pseudoresponding GBMs but also in normal appearing brain after AAT onset. Cho and NAA concentrations were superior to Cr-ratios in lesion differentiation and showed a clear gap between responding and pseudoresponding lesions. Responders to AAT exceptionally frequently (6 out of 8 patients) showed remote GBM progression.

CONCLUSIONS

Quantification of CBV reveals changes in normal brain perfusion due to AAT, which were not described so far. DSC perfusion MRI seems not to be suitable for differentiation between response and pseudoresponse to AAT. However, absolute quantification of brain metabolites may allow for distinction due to a clear gap at 6-9 months after therapy onset.

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.

Development and validation of an open source quantification tool for DSC-MRI studies

MOTIVATION

This work presents the development of an open source tool for the quantification of dynamic susceptibility-weighted contrast-enhanced (DSC) perfusion studies. The development of this tool is motivated by the lack of open source tools implemented on open platforms to allow external developers to implement their own quantification methods easily and without the need of paying for a development license.

MATERIALS AND METHODS

This quantification tool was developed as a plugin for the ImageJ image analysis platform using the Java programming language. A modular approach was used in the implementation of the components, in such a way that the addition of new methods can be done without breaking any of the existing functionalities. For the validation process, images from seven patients with brain tumors were acquired and quantified with the presented tool and with a widely used clinical software package. The resulting perfusion parameters were then compared.

RESULTS

Perfusion parameters and the corresponding parametric images were obtained. When no gamma-fitting is used, an excellent agreement with the tool used as a gold-standard was obtained (R(2)>0.8 and values are within 95% CI limits in Bland-Altman plots).

CONCLUSION

An open source tool that performs quantification of perfusion studies using magnetic resonance imaging has been developed and validated using a clinical software package. It works as an ImageJ plugin and the source code has been published with an open source license.

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.

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.

High-resolution steady-state cerebral blood volume maps in patients with central nervous system neoplasms using ferumoxytol, a superparamagnetic iron oxide nanoparticle

Cerebral blood volume (CBV) measurement complements conventional magnetic resonance imaging (MRI) to indicate pathologies in the central nervous system (CNS). Dynamic susceptibility contrast (DSC) perfusion imaging is limited by low resolution and distortion. Steady-state (SS) imaging may provide higher resolution CBV maps but was not previously possible in patients. We tested the feasibility of clinical SS-CBV measurement using ferumoxytol, a nanoparticle blood pool contrast agent. SS-CBV measurement was analyzed at various ferumoxytol doses and compared with DSC-CBV using gadoteridol. Ninety nine two-day MRI studies were acquired in 65 patients with CNS pathologies. The SS-CBV maps showed improved contrast to noise ratios, decreased motion artifacts at increasing ferumoxytol doses. Relative CBV (rCBV) values obtained in the thalamus and tumor regions indicated good consistency between the DSC and SS techniques when the higher dose (510 mg) ferumoxytol was used. The SS-CBV maps are feasible using ferumoxytol in a clinical dose of 510 mg, providing higher resolution images with comparable rCBV values to the DSC technique. Physiologic imaging using nanoparticles will be beneficial in visualizing CNS pathologies with high vascularity that may or may not correspond with blood-brain barrier abnormalities.

Advanced techniques using contrast media in neuroimaging

This article presents an overview of advanced magnetic resonance (MR) imaging techniques using contrast media in neuroimaging, focusing on T2*-weighted dynamic susceptibility contrast MR imaging and T1-weighted dynamic contrast-enhanced MR imaging. Image acquisition and data processing methods and their clinical application in brain tumors, stroke, dementia, and multiple sclerosis are discussed.

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.

Feasibility of semiquantitative liver perfusion assessment by ferucarbotran bolus injection in double-contrast hepatic MRI

PURPOSE

To evaluate the feasibility of semiquantitative measurement of liver perfusion from analysis of ferucarbotran induced signal-dynamics in double-contrast liver MR-imaging (DC-MRI).

MATERIALS AND METHODS

In total 31 patients (21 men; 58 ± 10 years) including 18 patients with biopsy proven liver cirrhosis prospectively underwent clinically indicated DC-MRI at 1.5 Tesla (T) with dynamic T2-weighted gradient-echo imaging after ferucarbotran bolus injection. Breathing artefacts in tissue and input time curves were reduced by Savitzky-Golay-filtering and semiquantitative perfusion maps were calculated using a model free approach. Hepatic blood flow index (HBFI) and splenic blood flow index (SBFI) were determined by normalization of arbitrary perfusion values to the perfusion of the erector spinae muscle resulting in a semiquantitative perfusion measure.

RESULTS

In 30 of 31 patients the evaluated protocol could successfully be applied. Mean HBF was 7.7 ± 2.46 (range, 4.6-12.8) and mean SBF was 13.20 ± 2.57 (range, 8.5-17.8). A significantly lower total HBF was seen in patients with cirrhotic livers as compared to patients with noncirrhotic livers (P < 0.05). In contrast, similar SBF was observed in cirrhotic and noncirrhotic patients (P = 0.11).

CONCLUSION

Capturing the signal dynamics during bolus injection of ferucarbotran in DC-MRI of the liver allows for semiquantitative assessment of hepatic perfusion that may be helpful for a more precise characterisation of liver cirrhosis and focal liver lesions.

Hepatocellular nodules in liver cirrhosis: state of the art CT evaluation (perfusion CT/volume helical shuttle scan/dual-energy CT, etc.)

The purpose of this article is to explain the role of advanced liver CT imaging, including perfusion CT, dual-energy CT, and volume helical shuttle (VHS) scanning, with regard to its clinical applications. Perfusion CT is a promising method for calculating hepatic blood flow and portal blood flow, including microcirculation, using a color-encoded display of parameters obtained from the liver time-density curve, with iodine contrast agent. Tumor angiogenesis and assessment of the response to antiangiogenesis treatment (e.g., Sorafenib) can be analyzed by perfusion CT of the liver. VHS scan has very high temporal resolution due to the reciprocating movement employed during scanning, enabling the acquisition of 24 scans of the whole liver in the arterial dominant phase during a 40-s breath hold, and a reduction in radiation dose. Dual-energy CT enables differentiation of materials and tissues based on their CT density values, using two different energy spectra. This method includes a low tube voltage CT technique that increases the contrast enhancement of vascular structures while simultaneously reducing radiation dose. Images obtained at the preferred settings of low tube voltage and high tube current, with dose reduction in the hepatic arterial phase, are useful for detecting hypervascular hepatocellular carcinoma.

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.

Automated macrovessel artifact correction in dynamic susceptibility contrast magnetic resonance imaging using independent component analysis

Dynamic susceptibility contrast-MRI is the most commonly used functional MRI-based method for studying changes in cerebral perfusion. However, several studies indicated a systematic overestimation of perfusion parameters compared with other imaging modalities related to the high sensitivity of dynamic susceptibility contrast-MRI for blood flow in large vessels. In this study, we therefore suggest an improved, automated, robust, and efficient method allowing for generating hemodynamic parameter maps where signal influence from large vessels is minimized. Based on independent component analysis, this fully automated approach corrects dynamic susceptibility contrast-MRI data without any user interaction, thus making a clinical applicability possible. The accuracy of the proposed method was tested in 10 patients with cerebrovascular disease. Application of our correction algorithm resulted in a significant reduction of the effect of macrovessel signal on hemodynamic parameters like the cerebral blood flow and the cerebral blood volume compared with uncorrected data. As desired, our method specifically corrected for macrovessel artifacts in cortical grey matter tissue, leaving white matter tissue parameters largely unaffected. This may increase sensitivity and reliability of detecting perfusion abnormalities in patient groups, in particular with regard to stroke and other cerebrovascular disorders.

A generic bioheat transfer thermal model for a perfused tissue

A thermal model was needed to predict temperatures in a perfused tissue, which satisfied the following three criteria. One, the model satisfied conservation of energy. Two, the heat transfer rate from blood vessels to tissue was modeled without following a vessel path. Three, the model applied to any unheated and heated tissue. To meet these criteria, a generic bioheat transfer model (BHTM) was derived here by conserving thermal energy in a heated vascularized finite tissue and by making a few simplifying assumptions. Two linear coupled differential equations were obtained with the following two variables: tissue volume averaged temperature and blood volume averaged temperature. The generic model was compared with the widely employed empirical Pennes' BHTM. The comparison showed that the Pennes' perfusion term wC(p)(1-epsilon) should be interpreted as a local vasculature dependent heat transfer coefficient term. Suggestions are presented for further adaptations of the general BHTM for specific tissues using imaging techniques and numerical simulations.

The performance of MRI-based cerebral blood flow measurements in acute and subacute stroke compared with 15O-water positron emission tomography: identification of penumbral flow

BACKGROUND AND PURPOSE

Perfusion-weighted MRI-based maps of cerebral blood flow (CBF(MRI)) are considered a good MRI measure of penumbral flow in acute ischemic stroke but are seldom used in clinical routine due to methodical issues. We validated CBF(MRI) on quantitative CBF measurement by 15O-water positron emission tomography (CBF(PET)).

MATERIAL AND METHODS

Comparative CBF(MRI) and CBF(PET) were performed in patients with acute and subacute stroke. In a voxel-based seed-growing technique, predefined CBF(MRI) thresholds (<40, <30, <20, <10 mL/100 g/min) were applied and the resulting volumes were compared with the hypoperfusion volume detected by the penumbral threshold (<20 mL/100 g/min) on CBF(PET). The volumetric comparison was expressed as the C-ratio (volume CBF(MRI)/volume CBF(PET)) to identify the best MRI threshold. The influence of vessel pathology, hypoperfusion size, and time point of imaging was described. The proportion of voxels correctly classified as hypoperfused and the proportion of voxel correctly classified as nonhypoperfused of the best CBF(MRI) threshold was calculated and a Bland-Altman plot illustrated the method-specific differences.

RESULTS

In 24 patients (median time MRI to PET: 68 minutes; 16 patients imaged within 24 hours after stroke), the median volume of hypoperfusion <20 mL/100 g/min (CBF(PET)) was 78.5 cm(3). Median hypoperfusion volume on CBF(MRI) ranged from 245.9 cm(3) (<40 mL/100 g/min) to 35.5 cm(3) (<10 mL/10 g/min). On visual inspection, an excellent qualitative congruence was found. The quantitative congruence was best for the MRI-CBF threshold <20 mL/100 g/min (median C-ratio: 1.0), reaching a proportion of voxels correctly classified as hypoperfused of 76% and a proportion of voxel correctly classified as nonhypoperfused of 96%, but a wide interindividual range (C-ratio 0.3 to 3.5) was found. Ipsilateral vessel pathology, time point of imaging, and size of hypoperfusion did not significantly influence the C-ratio. The Bland-Altman analysis for the volumetric difference of CBF(MRI) and CBF(PET) found a good overall agreement but a large SD.

CONCLUSIONS

Hypoperfusion areas below the CBF(PET) penumbral threshold can be well identified by the CBF(MRI) threshold <20 mL/10 g/min at a group level, but a large individual variance (exceeding 20% of volume in nearly half of the patients) could not be explained. Our results support a prudent use of MRI-based quantitative CBF measurement in clinical routine.

Contrast agent dose effects in cerebral dynamic susceptibility contrast magnetic resonance perfusion imaging

PURPOSE

To study the contrast agent dose sensitivity of hemodynamic parameters derived from brain dynamic susceptibility contrast MRI (DSC-MRI).

MATERIALS AND METHODS

Sequential DSC-MRI (1.5T gradient-echo echo-planar imaging using an echo time of 61-64 msec) was performed using contrast agent doses of 0.1 and 0.2 mmol/kg delivered at a fixed rate of 5.0 mL/second in 12 normal subjects and 12 stroke patients.

RESULTS

1) Arterial signal showed the expected doubling in relaxation response (DeltaR2*) to dose doubling. 2) The brain signal showed a less than doubled DeltaR2* response to dose doubling. 3) The 0.2 mmol/kg dose studies subtly underestimated cerebral blood volume (CBV) and cerebral blood flow (CBF) relative to the 0.1 mmol/kg studies. 4) In the range of low CBV and CBF, the 0.2 mmol/kg studies overestimated the CBV and CBF compared with the 0.1 mmol/kg studies. 5) The 0.1 mmol/kg studies reported larger ischemic volumes in stroke.

CONCLUSION

Subtle but statistically significant dose sensitivities were found. Therefore, it is advisable to carefully control the contrast agent dose when DSC-MRI is used in clinical trials. The study also suggests that a 0.1 mmol/kg dose is adequate for hemodynamic measurements.

Absolute quantification of cerebral blood flow in normal volunteers: correlation between Xe-133 SPECT and dynamic susceptibility contrast MRI

PURPOSE

To compare absolute cerebral blood flow (CBF) estimates obtained by dynamic susceptibility contrast MRI (DSC-MRI) and Xe-133 SPECT.

MATERIALS AND METHODS

CBF was measured in 20 healthy volunteers using DSC-MRI at 3T and Xe-133 SPECT. DSC-MRI was accomplished by gradient-echo EPI and CBF was calculated using a time-shift-insensitive deconvolution algorithm and regional arterial input functions (AIFs). To improve the reproducibility of AIF registration the time integral was rescaled by use of a venous output function. In the Xe-133 SPECT experiment, Xe-133 gas was inhaled over 8 minutes and CBF was calculated using a biexponential analysis.

RESULTS

The average whole-brain CBF estimates obtained by DSC-MRI and Xe-133 SPECT were 85 +/- 23 mL/(min 100 g) and 40 +/- 8 mL/(min 100 g), respectively (mean +/- SD, n = 20). The linear CBF relationship between the two modalities showed a correlation coefficient of r = 0.76 and was described by the equation CBF(MRI) = 2.4 . CBF(Xe)-7.9 (CBF in units of mL/(min 100 g)).

CONCLUSION

A reasonable positive linear correlation between MRI-based and SPECT-based CBF estimates was observed after AIF time-integral correction. The use of DSC-MRI typically results in overestimated absolute perfusion estimates and the present study indicates that this trend is further enhanced by the use of high magnetic field strength (3T).

Hemodynamic studies on brain CT perfusion imaging with varied injection rates

OBJECTIVE

This study aimed to determine a contrast medium injection rate that ensures both accuracy for data and safety for operation by comparing hemodynamic parameters of brain CT perfusion imaging with varied injection rates.

METHODS

Twenty-four healthy volunteers were divided into three groups based on contrast medium injection rates (4.5, 6.0, and 7.5 ml/s). For all subjects, CT perfusion scanning was started at 4 s after antecubital venous bolus of contrast media injection. A perfusion-analyzing software package was used to produce a time-density curve in the anterior cerebral artery and the superior sagittal sinus and calculate the regional cerebral blood flow (rCBF) in the gray matter and the white matter. The hemodynamic indices were compared among the three groups, and statistical analysis was carried out using the F test.

RESULTS

The time for the arterial rise to reach the peak value for the 7.5-ml/s group was only 0.2 s ahead of the initiation time for the rise of the superior sagittal sinus. The differences of rCBF in the gray matter and the white matter among the three groups were statistically significant. rCBF in the gray matter and the white matter for the 7.5-ml/s group was 52.8 ml x min(-1) 100 g(-1) . (+/-3.1) and 21.9 ml x min(-1) . 100 g(-1) (+/-2.4), respectively.

CONCLUSIONS

The use of the 7.5-ml/s injection rate can meet the prerequisite of the maximum slope model, and the resulting rCBF can be very close to that measured by positron emission tomography. Therefore, 7.5 ml/s was an ideal contrast medium injection rate.

Technical aspects of perfusion-weighted imaging

There is increasing interest in using diffusion-weighted (DWI) MR imaging and perfusion-weighted MR imaging (PWI) to assist clinical decision-making in the management of acute stroke patients. Larger PWI than DWI lesions have been speculated to represent potentially salvageable tissue that is at risk of infarction unless nutritive flow is restored and presence of these mismatches have been proposed as inclusion criteria for identifying patients most likely to benefit from therapeutic intervention. Understanding the technical aspects of PWI may improve comprehension of the capabilities and limitations of this technique.

Principles of cerebral perfusion imaging by bolus tracking

The principles of cerebral perfusion imaging by the method of dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) (bolus tracking) are described. The MRI signals underlying DSC-MRI are discussed. Tracer kinetics procedures are defined to calculate images of cerebral blood volume (CBV), cerebral blood flow (CBF), and mean transit time (MTT). Two general categories of numerical procedures are reviewed for deriving CBF from the residue function. Procedures that involve deconvolution, such as Fourier deconvolution or singular value decomposition (SVD), are classified as model-independent methods because they do not require a model of the microvascular hemodynamics. Those methods in principle also yield a measure of the tissue impulse response function and the residue function, from which microvascular hemodynamics can be characterized. The second category of methods is the model-dependent methods, which use models of tracer transport and retention in the microvasculature. These methods do not yield independent measures of the residue function and may introduce bias when the physiology does not follow the model. Statistical methods are sometimes used, which involve treating the residue function as a deconvolution kernel and optimizing (fitting) the kernel from the experimental data using procedures such as maximum likelihood. Finally, other hemodynamic indices that can be measured from DSC-MRI data are described.

The application of diffusion- and perfusion-weighted magnetic resonance imaging in the diagnosis and therapy of acute cerebral infarction

Diffusion- and perfusion-weighted magnetic resonance imaging (DWI and PWI) was applied for stroke diagnose in 120 acute (< 48 h) ischemic stroke patients. At hyperacute (< 6 h) stage, it is difficult to find out the infarction zone in conventional T1 or T2 image, but it is easy in DWI, apparent diffusion coefficient (ADC) map; when at 3–6-hour stage it is also easy in PWI, cerebral blood flow (CBF) map, cerebral blood volume (CBV) map, and mean transit time (MTT) map; at acute (6–48 h) stage, DWI or PWI is more sensitive than conventional T1 or T2 image too. Combining DWI with ADC, acute and chronic infarction can be distinguished. Besides, penumbra which should be developed in meaning was used as an indication or to evaluate the therapeutic efficacy. There were two cases (< 1.5 h) that broke the model of penumbra because abnormity was found in DWI but not that in PWI, finally they recovered without any sequela.