Perfusion parameter map generation from TOF-MRA in stroke using generative adversarial networks.

PURPOSE: To generate perfusion parameter maps from Time-of-flight magnetic resonance angiography (TOF-MRA) images using artificial intelligence to provide an alternative to traditional perfusion imaging techniques. MATERIALS AND METHODS: This retrospective study included a total of 272 patients with cerebrovascular diseases; 200 with acute stroke (from 2010 to 2018), and 72 with steno-occlusive disease (from 2011 to 2014). For each patient the TOF MRA image and the corresponding Dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) were retrieved from the datasets. The authors propose an adapted generative adversarial network (GAN) architecture, 3D pix2pix GAN, that generates common perfusion maps (CBF, CBV, MTT, TTP, Tmax) from TOF-MRA images. The performance was evaluated by the structural similarity index measure (SSIM). For a subset of 20 patients from the acute stroke dataset, the Dice coefficient was calculated to measure the overlap between the generated and real hypoperfused lesions with a time-to-maximum (Tmax) > 6 s. RESULTS: The GAN model exhibited high visual overlap and performance for all perfusion maps in both datasets: acute stroke (mean SSIM 0.88-0.92, mean PSNR 28.48-30.89, mean MAE 0.02-0.04 and mean NRMSE 0.14-0.37) and steno-occlusive disease patients (mean SSIM 0.83-0.98, mean PSNR 23.62-38.21, mean MAE 0.01-0.05 and mean NRMSE 0.03-0.15). For the overlap analysis for lesions with Tmax>6 s, the median Dice coefficient was 0.49. CONCLUSION: Our AI model can successfully generate perfusion parameter maps from TOF-MRA images, paving the way for a non-invasive alternative for assessing cerebral hemodynamics in cerebrovascular disease patients. This method could impact the stratification of patients with cerebrovascular diseases. Our results warrant more extensive refinement and validation of the method.

Diffusion-/perfusion-weighted imaging fusion to automatically identify stroke within 4.5 h.

OBJECTIVES: We aimed to develop machine learning (ML) models based on diffusion- and perfusion-weighted imaging fusion (DP fusion) for identifying stroke within 4.5 h, to compare them with DWI- and/or PWI-based ML models, and to construct an automatic segmentation-classification model and compare with manual labeling methods. METHODS: ML models were developed from multimodal MRI datasets of acute stroke patients within 24 h of clear symptom onset from two centers. The processes included manual segmentation, registration, DP fusion, feature extraction, and model establishment (logistic regression (LR) and support vector machine (SVM)). A segmentation-classification model (X-Net) was proposed for automatically identifying stroke within 4.5 h. The area under the receiver operating characteristic curve (AUC), sensitivity, Dice coefficients, decision curve analysis, and calibration curves were used to evaluate model performance. RESULTS: A total of 418 patients (≤ 4.5 h: 214; > 4.5 h: 204) were evaluated. The DP fusion model achieved the highest AUC in identifying the onset time in the training (LR: 0.95; SVM: 0.92) and test sets (LR: 0.91; SVM: 0.90). The DP fusion-LR model displayed consistent positive and greater net benefits than other models across a broad range of risk thresholds. The calibration curve demonstrated the good calibration of the DP fusion-LR model (average absolute error: 0.049). The X-Net model obtained the highest Dice coefficients (DWI: 0.81; Tmax: 0.83) and achieved similar performance to manual labeling (AUC: 0.84). CONCLUSIONS: The automatic segmentation-classification models based on DWI and PWI fusion images had high performance in identifying stroke within 4.5 h. CLINICAL RELEVANCE STATEMENT: Perfusion-weighted imaging (PWI) fusion images had high performance in identifying stroke within 4.5 h. The automatic segmentation-classification models based on DWI and PWI fusion images could provide clinicians with decision-making guidance for acute stroke patients with unknown onset time. KEY POINTS: • The diffusion/perfusion-weighted imaging fusion model had the best performance in identifying stroke within 4.5 h. • The X-Net model had the highest Dice and achieved performance close to manual labeling in segmenting lesions of acute stroke. • The automatic segmentation-classification model based on DP fusion images performed well in identifying stroke within 4.5 h.

The Impact of MRI-Based Advanced Neuroimaging on Neurooncologists' Clinical Decision-Making in Patients With Posttreatment High-Grade Glioma: A Prospective Survey-Based Study.

Background: Advanced MRI-based neuroimaging techniques, such as perfusion and spectroscopy, have been increasingly incorporated into routine follow-up protocols in patients treated for high-grade glioma (HGG), to help differentiate tumor progression from treatment effect. However, these techniques' influence on clinical management remains poorly understood. Objective: To evaluate the impact of MRI-based advanced neuroimaging on clinical decision-making in patients with HGG in the posttreatment setting. Methods: This prospective study, performed at a comprehensive cancer center from March 1, 2017, to October 31, 2020, included adult patients treated by chemoradiation for WHO grade 4 diffuse glioma who underwent MRIbased advanced neuroimaging (comprising multiple perfusion imaging sequences and spectroscopy) to further evaluate findings on conventional MRI equivocal for tumor progression versus treatment effect. The ordering neuro-oncologists completed surveys before and after each advanced neuroimaging session. The percent of care episodes with a change between the intended and actual management plan on the surveys conducted before and after advanced neuroimaging, respectively, was computed and compared with a previously published percent using the Wald test for independent samples proportions. Results: The study included 63 patients (mean age, 55±13 years; 36 women, 27 men) who underwent 70 advanced neuroimaging sessions. Ordering neuro-oncologists' intended and actual management plans on the surveys completed before and after advanced neuroimaging, respectively, differed in 44% (31/70, [95% CI: 33-56%]) of episodes, which differed from the previously published frequency of 8.5% (5/59) (p<.001). These management plan changes included selection of a different plan for 6/8 episodes with an intended plan to enroll patients in a clinical trial, 12/19 episodes with an intended plan to change chemotherapeutic agents, 4/8 episodes with an intended plan of surgical intervention, and 1/2 episodes with an intended plan of re-irradiation. The ordering neuro-oncologists found advanced neuroimaging to be helpful in 93% (95% CI: 87%-99%) (65/70) of episodes. Conclusion: Neuro-oncologists' management plans changed in a substantial fraction of adult patients with HGG who underwent advanced neuroimaging to further evaluate conventional MRI findings equivocal for tumor progression versus treatment effect. Clinical Impact: The findings support incorporation of advanced neuroimaging into HGG posttreatment monitoring protocols.

Zygomatic Anterolateral Temporal Approach for P1/P2 segment complex posterior cerebral aneurysm: a single-center retrospective study.

Treating complex posterior cerebral artery (PCA) aneurysms, such as fusiform, giant, and dissecting aneurysms, poses significant challenges. Parent artery occlusion carries a risk of ischemic stroke and fails to alleviate mass effects. This study aims to analyze the technical nuances and patient outcomes of treating complex PCA aneurysms, ranging from the P1 to P2P segments, using a Zygomatic Anterolateral Temporal Approach(ZATA) combined with flow reconstruction. This study was a retrospective study. Surgical treatment was performed on twelve patients with complex PCA aneurysms located in the P1 to P2P segments. Ten patients underwent flow reconstruction including Superficial Temporal Artery(STA)-Middle Cerebral Artery(MCA),Internal Maxillary Artery(IMA)-Radial Artery(RA)-MCA,STA-PCA(P2), and IMA-RA-PCA(P2). The aneurysm occlusion rate, surgical complications, and patient prognosis, including stroke occurrence/ modified Rankin Scale(mRS), were recorded and analyzed. Using the ZATA, all twelve complex PCA aneurysms were successfully clipped/resected/trapped. This included two high-position aneurysms (> 3 mm above the posterior clinoid process) at the P1/P2 junction and three P2P aneurysms. The mass effects of six large or giant aneurysms were resolved or alleviated. Postoperative and follow-up CTA/DSA confirmed the patency of the bypass vessels. Four patients experienced strokes in the perioperative period, with three ischemic and one hemorrhagic. The median follow-up period was 28.5 months. At the last follow-up, the good prognosis rate (mRS ≤ 2) was 83.3%, and one patient had died. Clipping/resection/trapping of aneurysms via the ZATA, combined with flow reconstruction, is a feasible option for treating complex PCA aneurysms from the P1 to P2P segments. This approach helps maintain or improve cerebral perfusion in the affected vascular territory.

Diffusion- and Perfusion-Weighted Imaging to Detect Neurological Deficits in Acute Focal Cerebral Ischemia in Rabbits.

PURPOSE: To investigate the relationship of diffusion-weighted imaging (DWI) and perfusion-weighted imaging (PWI) parameters with dysfunction in acute focal cerebral ischemia (ACI) rabbits. METHODS: The model of ACI in the middle cerebral artery was made using 30 adult male New Zealand rabbits. The dysfunction severities of the ACI rabbits were assessed using Purdy's score. A paired-sample rank sum test was adopted to compare the abnormal signal zone (ASZ) volumes from T2 weighted imaging (T2WI), dynamic susceptibility contrast-enhanced (DSC) imaging, and DWI with a relative cerebral blood flow (rCBF) map; correlations were analyzed between the volume of each ASZ and Purdy's score by Spearman's rank correlation coefficient. The degree of necrotic and apoptotic cells was evaluated in the ASZ from DWI and DSC PWI-DWI mismatch (PDM) zone. Correlations were analyzed between the index of cellular damage and Purdy's score, the volume of ASZs by Spearman's rank correlation coefficient. RESULTS: The ASZ volumes from DSC-PWI and the rCBF maps were larger than those from DWI (p < 0.001 and p < 0.001, respectively); those from the rCBF map (Z = 0.959, p < 0.001) and DSC-PWI (Z = 0.970, p < 0.001) were positively correlated with DWI; a positive correlation was found between Purdy's score and the ASZ volumes from DSC-PWI (Z = 0.889, p < 0.001), DWI (Z = 0.921, p < 0.001), and rCBF (Z = 0.891, p < 0.001). A significant difference was observed between the ASZ from DWI and the PDM zone in terms of the degree of necrotic (p < 0.001) and apoptotic cells (p < 0.001). The degree of cellular damage in the ASZ of DWI and PDM zone had no relationship with Purdy's score and the volumes of ASZs. CONCLUSION: The ASZ volumes from DSC-PWI, rCBF, and particularly DWI reflected the level of dysfunction in rabbits with ACI.

High-resolution dynamic susceptibility contrast perfusion imaging using higher-order temporal smoothness regularization.

PURPOSE: To improve image quality and resolution of dynamic susceptibility contrast perfusion weighted imaging (DSC-PWI) by developing acquisition and reconstruction methods exploiting the temporal regularity property of DSC-PWI signal. THEORY AND METHODS: A novel regularized reconstruction is proposed that recovers DSC-PWI series from interleaved segmented spiral k-space acquisition using higher order temporal smoothness (HOTS) properties of the DSC-PWI signal. The HOTS regularization is designed to tackle representational insufficiency of the standard first-order temporal regularizations for supporting higher accelerations. The higher accelerations allow for k-space coverage with shorter spiral interleaves resulting in improved acquisition point spread function, and acquisition of images at multiple TEs for more accurate DSC-PWI analysis. RESULTS: The methods were evaluated in simulated and in-vivo studies. HOTS regularization provided increasingly more accurate models for DSC-PWI than the standard first-order methods with either quadratic or robust norms at the expense of increased noise. HOTS DSC-PWI optimized for noise and accuracy demonstrated significant advantages over both spiral DSC-PWI without temporal regularization and traditional echo-planar DSC-PWI, improving resolution and mitigating image artifacts associated with long readout, including blurring and geometric distortions. In context of multi-echo DSC-PWI, the novel methods allowed ∼4.3× decrease of voxel volume, providing 2× number of TEs compared to the previously published results. CONCLUSIONS: Proposed HOTS reconstruction combined with dynamic spiral sampling represents a valid mechanism for improving image quality and resolution of DSC-PWI significantly beyond those available with established fast imaging techniques.

Dynamic contrast-enhanced MRI radiomics model predicts epidermal growth factor receptor amplification in glioblastoma, IDH-wildtype.

PURPOSE: To develop and validate a dynamic contrast-enhanced (DCE) MRI-based radiomics model to predict epidermal growth factor receptor (EGFR) amplification in patients with glioblastoma, isocitrate dehydrogenase (IDH) wildtype. METHODS: Patients with pathologically confirmed glioblastoma, IDH wildtype, from January 2015 to December 2020, with an EGFR amplification status, were included. Patients who did not undergo DCE or conventional brain MRI were excluded. Patients were categorized into training and test sets by a ratio of 7:3. DCE MRI data were used to generate volume transfer constant (Ktrans) and extracellular volume fraction (Ve) maps. Ktrans, Ve, and conventional MRI were then used to extract the radiomics features, from which the prediction models for EGFR amplification status were developed and validated. RESULTS: A total of 190 patients (mean age, 59.9; male, 55.3%), divided into training (n = 133) and test (n = 57) sets, were enrolled. In the test set, the radiomics model using the Ktrans map exhibited the highest area under the receiver operating characteristic curve (AUROC), 0.80 (95% confidence interval [CI], 0.65-0.95). The AUROC for the Ve map-based and conventional MRI-based models were 0.74 (95% CI, 0.58-0.90) and 0.76 (95% CI, 0.61-0.91). CONCLUSION: The DCE MRI-based radiomics model that predicts EGFR amplification in glioblastoma, IDH wildtype, was developed and validated. The MRI-based radiomics model using the Ktrans map has higher AUROC than conventional MRI.

Whole-tumor histogram analysis of diffusion and perfusion metrics for noninvasive pediatric glioma grading.

PURPOSE: An accurate assessment of the World Health Organization grade is vital for patients with pediatric gliomas to direct treatment planning. We aim to evaluate the diagnostic performance of whole-tumor histogram analysis of diffusion-weighted imaging (DWI) and dynamic susceptibility contrast-enhanced perfusion-weighted imaging (DSC-PWI) for differentiating pediatric high-grade gliomas from pediatric low-grade gliomas. METHODS: Sixty-eight pediatric patients (mean age, 10.47 ± 4.37 years; 42 boys) with histologically confirmed gliomas underwent preoperative MR examination. The conventional MRI features and whole-tumor histogram features extracted from apparent diffusion coefficient (ADC) and cerebral blood volume (CBV) maps were analyzed, respectively. Receiver operating characteristic curves and the binary logistic regression analysis were performed to determine the diagnostic performance of parameters. RESULTS: For conventional MRI features, location, hemorrhage and tumor margin showed significant difference between pediatric high- and low-grade gliomas (all, P < .05). For advanced MRI parameters, ten histogram features of ADC and CBV showed significant differences between pediatric high- and low-grade gliomas (all, P < .05). The diagnostic performance of the combination of DSC-PWI and DWI (AUC = 0.976, sensitivity = 100%, NPV = 100%) is superior to conventional MRI or DWI model, respectively (AUCcMRI = 0.700, AUCDWI = 0.830; both, P < .05). CONCLUSION: The whole-tumor histogram analysis of DWI and DSC-PWI is a promising method for grading pediatric gliomas.

Efficacy of three-dimensional arterial spin labeling and how it compares against that of contrast enhanced magnetic resonance imaging in preoperative grading of brain gliomas.

PURPOSE: To evaluate the efficacy of three-dimensional arterial spin labeling (3D-ASL) imaging in preoperative grading of brain gliomas, and compare the discrepancy between images obtained from 3D-ASL and contrast enhanced magnetic resonance imaging (CE-MRI) in grading of gliomas. METHODS: Fifty-one patients with brain gliomas received plain MRI, CE-MRI and 3D-ASL scanning before surgery. In 3D-ASL images, the maximum tumor blood flow (TBF) of tumor parenchyma was measured, relative TBF-M and rTBF-WM were calculated. The cases were categorized into "ASL dominant" and "CE dominant" to compare the discrepancy between 3D-ASL and CE-MRI results. Independent samples t test, Mann-Whitney and U test and one-way analysis of variance (ANOVA) were performed to test the differences of TBF, rTBF-M and rTBF-WM values among brain gliomas with different grades. Spearman rank correlation analysis was performed to assess the correlation between TBF, rTBF-M, rTBF-WM and glioma grades respectively. To compare the discrepancy between 3D-ASL and CE-MRI results. RESULTS: In high-grade gliomas (HGG) group, TBF, rTBF-M and rTBF-WM values were higher than those in low-grade gliomas (LGG) group (p < .05). Multiple comparison showed TBF and rTBF-WM values were different between grade I and IV gliomas, grade II and IV gliomas (both p < .05), the rTBF-M value was different between grade I and IV gliomas (p < .05). The values of all 3D-ASL derived parameters were positively correlated with gliomas grading (all p < .001). TBF showed highest specificity (89.3%) and rTBF-WM showed highest sensitivity (96.4%) when discriminating LGG and HGG using ROC curve. There were 29 CE dominant cases (23 cases were HGG), 9 ASL dominant cases (4 cases were HGG). CONCLUSION: 3D-ASL is of significance to preoperative grading of brain gliomas and might be more sensitive than CE-MRI in detection of tumor perfusion.

The new insights into human brain imaging after stroke.

Over the last two decades, developments of human brain stroke imaging have raised several questions about the place of new MRI biomarkers in the acute management of stroke and the prediction of poststroke outcome. Recent studies have demonstrated the main role of perfusion-weighted imaging in the identification of the best cerebral perfusion profile for a better response after reperfusion therapies in acute ischemic stroke. A major issue remains the early prediction of stroke outcome. While voxel-based lesion-symptom mapping emphasized the influence of stroke location, the analysis of the brain parenchyma underpinning the stroke lesion showed the relevance of prestroke cerebral status, including cortical atrophy, white matter integrity, or presence of chronic cortical cerebral microinfarcts. Moreover, besides the evaluation of the visually abnormal brain tissue, the analysis of normal-appearing brain parenchyma using diffusion tensor imaging and magnetization transfer imaging or spectroscopy offered new biomarkers to improve the prediction of the prognosis and new targets to follow in therapeutic trials. The aim of this review was to depict the main new radiological biomarkers reported in the last two decades that will provide a more thorough prediction of functional, motor, and neuropsychological outcome following the stroke. These new developments in neuroimaging might be a cornerstone in the emerging personalized medicine for stroke patients.

Sudden unilateral hearing loss and vertigo following isolated cerebellar hypoperfusion without infarction due to vertebral artery dissection.

BACKGROUND: The definition of sudden sensorineural hearing loss (SSNHL) is broadly accepted as acute sensorineural hearing loss of more than 30 dB over at least three consecutive frequencies in a pure-tone audiogram (PTA). Acute audiovestibular loss is common with ischaemic stroke in the territory of the anterior inferior cerebellar artery (AICA). However, cases in which SSNHL and vertigo occur with hypoperfusion alone are very rare. We describe a patient who developed unilateral SSNHL and vertigo as initial symptoms caused by cerebellar hypoperfusion by vertebral artery (VA) dissection without the occurrence of infarction. CASE PRESENTATION: A 51-year-old man suddenly developed acute hearing loss (AHL) in his left ear and vertigo. On neurological examination, he had vibration-induced right-beating nystagmus and left-beating nystagmus after a head-shaking test. Additionally, he had apogeotropic nystagmus during head turns to either side. The head impulse test (HIT) was normal. PTA showed mild unilateral SSNHL in the left ear. Diffusion-weighted imaging (DWI) and perfusion-weighted imaging (PWI) showed territorial perfusion deficits in the left posterior inferior cerebellar artery (PICA) and anterior inferior cerebellar artery (AICA) without infarction. Two months later, the patient had no vertigo but still had hearing impairment in his left ear. A follow-up PTA documented persistent unilateral SSNHL in the left ear. Additionally, perfusion computed tomography (CT) showed that perfusion deficits remained in the left cerebellum along the PICA and AICA territories. CONCLUSIONS: Our case highlights a case of AHL and vertigo presented by isolated cerebellar hypoperfusion without infarction. It is necessary to consider the possibility of a central cause in patients with AHL and vertigo, and it is important to confirm this possibility through brain magnetic resonance imaging (MRI), including PWI, and magnetic resonance angiography (MRA).

Dynamic susceptibility MR perfusion imaging of the brain: not a question of contrast agent molarity.

PURPOSE: Dynamic susceptibility contrast (DSC) perfusion-weighted MR imaging (PWI) is increasingly used in clinical neuroimaging for a range of conditions. More highly concentrated GBCAs (e.g., gadobutrol) are often preferred for DSC imaging because it is thought that more Gd is present in the volume of interest during first pass for a given equivalent injection rate. However, faster injection of a less viscous GBCA (e.g., gadoteridol) might generate a more compact and narrower contrast bolus thus obviating any perceived benefit of higher Gd concentration. This preliminary study aimed to analyze and compare DSC examinations in the healthy brain hemisphere of patients with brain tumors using gadobutrol and gadoteridol administered at injection rates of 4 and 6 mL/s. METHODS: Thirty-nine brain tumor patients studied with DSC-PWI were evaluated. A simplified gamma-variate model function was applied to calculate the mean peak, area under the curve (AUC), and full-width at half-maximum (FHWM) of concentration-time curves derived from ΔR2* signals at four different regions-of-interest (ROIs). Qualitative assessment of the derived CBV maps was also performed independently by 2 neuroradiologists. RESULTS: No qualitative or quantitative differences between the two GBCAs were observed when administered at a flow rate of 4 mL/s. At a flow rate of 6 mL/s, gadoteridol showed lower FWHM values. CONCLUSION: Gadobutrol and gadoteridol are equivalent for clinical assessment of qualitative CBV maps and quantitative perfusion parameters (FHWM) at a flow rate of 4 mL/s. At 6 mL/s, gadoteridol produces a narrower bolus shape and potentially improves quantitative assessment of perfusion parameters.

Early diagnosis of spinal tuberculosis by magnetic resonance: perfusion weighted imaging in a rabbit model.

BACKGROUND: This study aimed to analyze the application value of magnetic resonance (MR)-perfusion weighted imaging (PWI) in the early imaging diagnosis of rabbit spinal tuberculosis. METHODS: Spinal tuberculosis model was established using ATCC25177 Mycobacterium tuberculosis strain in the lumbar spine of rabbits. Forty rabbits were divided into 2 groups: rabbits in the experiment group were injected with 0.2 ml of 5.0 mg/ml tuberculosis suspension (n = 30) and those in the control group were injected with 0.2 ml of normal saline (n = 10) after vertebrae drilling surgery. Routine MRI and MR-PWI were performed at 4, 6, and 8 weeks after surgery. The statistical difference in terms of perfusion parameter values in the early MR-PWI scan of spinal tuberculosis between two groups was analyzed. The receiver operating characteristic (ROC) curve analysis was conducted for the accuracy of MR-PWI parameters in the early diagnosis of spinal tuberculosis. RESULTS: Except time to peak, the other perfusion parameters in the experiment group were all increased with time. In addition, the difference between the two groups, as well as the differences at each time point was statistically significant (all P < 0.05). First-pass enhancement rate (Efirst), early enhancement rate (Ee), peak height (PH), maximum slope of increase (MSI), maximum signal enhancement rate (Emax) and signal enhancement rate (SER) showed high values in early diagnosing spinal tuberculosis. CONCLUSION: The parameters including Efirst, Ee, PH, MSI, Emax and SER may provide valuable imaging evidence for the early diagnosis of spinal tuberculosis in clinical application.

Non-invasive assessment of heterogeneity of gliomas using diffusion and perfusion MRI: correlation with spatially co-registered PET.

BACKGROUND: Heterogeneity of gliomas challenges the neuronavigated biopsy and oncological therapy. Diffusion and perfusion magnetic resonance imaging (MRI) can reveal the cellular and hemodynamic heterogeneity of tumors. Integrated positron emission tomography (PET)/MRI is expected to be a non-invasive imaging approach to characterizing glioma. PURPOSE: To evaluate the value of apparent diffusion coefficient (ADC), cerebral blood volume (CBV), and spatially co-registered maximal standard uptake value (SUVmax) for tissue characterization and glioma grading. MATERIAL AND METHODS: Thirty-seven consecutive patients with pathologically confirmed gliomas were retrospectively investigated. The relative minimum ADC (rADCmin), relative maximal ADC (rADCmax), relative maximal rCBV (rCBVmax), the relative minimum rCBV (rCBVmin), and the corresponding relative SUVmax (rSUVmax) were measured. The paired t-test was used to compare the quantitative parameters between different regions to clarify tumor heterogeneity. Imaging parameters between WHO grade IV and grade II/III gliomas were compared by t-test. The diagnostic efficiency of multiparametric PET/MRI was analyzed by receiver operating characteristic (ROC) curve. RESULTS: The values of rSUVmax were significantly different between maximal diffusion/perfusion area and minimum diffusion/perfusion area (P < 0.001/P < 0.001) within tumor. The values of rADCmin (P < 0.001), rCBVmax (P = 0.002), and corresponding rSUVmax (P = 0.001/P < 0.001) could be used for grading gliomas. The areas under the ROC curves of rSUVmax defined by rADCmin and rCBVmax were 0.89 and 0.91, respectively. CONCLUSION: Diffusion and perfusion MRI can detect glioma heterogeneity with excellent molecular imaging correlations. Regions with rCBVmax suggest tissues with the highest metabolism and malignancy for guiding glioma grading and tissue sampling.

Differentiation between supratentorial pilocytic astrocytoma and extraventricular ependymoma using multiparametric MRI.

BACKGROUND: The differentiation of supratentorial pilocytic astrocytomas (STPAs) and supratentorial extraventricular ependymomas (STEEs) is clinically pivotal because of distinct therapeutic management and prognosis, which is sometimes challenging to both neuroradiologists and pathologists. PURPOSE: To explore and compare the conventional and advanced magnetic resonance imaging (MRI) features between STPA and STEE. MATERIAL AND METHODS: A total of 23 patients with STPAs and 23 patients with STEEs were reviewed in this study. All patients performed conventional MRI, susceptibility-weighted imaging (SWI), and diffusion-weighted imaging (DWI), and 34 patients (17 with STPAs and 17 with STEEs) examined dynamic susceptibility contrast-enhanced perfusion-weighted imaging (DSC-PWI) in addition. Clinical data, conventional MRI features, minimum relative apparent diffusion coefficient ratio (rADCmin), and maximum relative cerebral blood volume ratio (rCBVmax) were compared between the two groups and subgroups. The optimal cutoff values of rADCmin and rCBVmax with sensitivity and specificity were calculated. RESULTS: STPA manifested similar to STEE as a solid-cystic mass but more frequently presented with a marked enhancing deep nodule (P = 0.02), no peritumoral edema (P = 0.036), higher rADCmin value (2.0 ± 0.5 vs. 0.9 ± 0.2; P < 0.001), and lower rCBVmax value (2.1 ± 0.4 vs. 14.4 ± 5.5; P < 0.001). The cutoff value of >1.39 for rADCmin and ≤ 2.81 for rCBVmax produced a high sensitivity of 95.65% and 100.0%, respectively, and all produced a specificity of 100.0% in differentiating STPAs from STEEs. CONCLUSION: Multiparametric MRI techniques including conventional MRI, DWI, and DSC-PWI contribute to the differential diagnosis of STPA and STEE.

Assessment of brain tumors by magnetic resonance dynamic susceptibility contrast perfusion-weighted imaging and computed tomography perfusion: a comparison study.

PURPOSE: To investigate the association and agreement between magnetic resonance dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) and computed tomography perfusion (CTP) in determining vascularity and permeability of primary and secondary brain tumors. MATERIAL AND METHODS: DSC-PWI and CTP studies from 97 patients with high-grade glioma, low-grade glioma and solitary brain metastasis were retrospectively reviewed. Normalized cerebral blood flow (nCBF), cerebral blood volume (nCBV), capillary transfer constant (nK2) and permeability surface area product (nPS) values were obtained. Variables among groups were compared, and correlation and agreement between DSC-PWI and CTP were tested. RESULTS: All DSC-PWI and CTP parameters were higher in high-grade than in low-grade gliomas (p < 0.01 and p < 0.001). Metastases had greater DSC-PWI nCBV (p < 0.05), nCTP-CBF (p < 0.05), nCTP-CBV (p < 0.01) and nCTP-PS (p < 0.0001) than low-grade gliomas and more elevated nCTP-PS (p < 0.01) than high-grade gliomas. The correlation was strong between DSC-PWI nCBF and CTP nCBF (r = 0.79; p < 0.00001) and between DSC-PWI nCBV and CTP nCBV (r = 0.83; p < 0.00001), weaker between DSC-PWI nK2 and CTP nPS (r = 0.29; p < 0.01). Bland-Altman plots indicated that the agreement was strong between DSC-PWI nCBF and CTP nCBF, good between DSC-PWI nCBV and CTP nCBV and poorer between DSC-PWI nK2 and CTP nPS. CONCLUSION: DSC-PWI and CTP CBF and CBV maps were comparable and interchangeable in the assessment of tumor vascularity, unlike DSC-PWI K2 and CTP PS maps that were more discordant in the analysis of tumor permeability. CTP could be an alternative method to quantify tumor neoangiogenesis when MRI is not available or when the patient does not tolerate it.

Combining 18F-DOPA PET and MRI with perfusion-weighted imaging improves delineation of high-grade subregions in enhancing and non-enhancing gliomas prior treatment: a biopsy-controlled study.

PURPOSE: We aimed to compare spatial extent of high-grade subregions detected with combined [18F]-dihydroxyphenylalanine (18F-DOPA) PET and MRI to the one provided by advanced multimodal MRI alone including Contrast-enhanced (CE) and Perfusion weighted imaging (PWI). Then, we compared the accuracy between imaging modalities, in a per biopsy analysis. METHODS: Participants with suspected diffuse glioma were prospectively included between June 2018 and September 2019. Volumes of high-grade subregions were delineated respectively on 18F-DOPA PET and MRI (CE and PWI). Up to three per-surgical neuronavigation-guided biopsies were performed per patient. RESULTS: Thirty-eight biopsy samples from sixteen participants were analyzed. Six participants (38%) had grade IV IDH wild-type glioblastoma, six (38%) had grade III IDH-mutated astrocytoma and four (24%) had grade II IDH-mutated gliomas. Three patients had intratumoral heterogeneity with coexisting high- and low-grade tumor subregions. High-grade volumes determined with combined 18F-DOPA PET/MRI (median of 1.7 [interquartile range (IQR) 0.0, 19.1] mL) were larger than with multimodal MRI alone (median 1.3 [IQR 0.0, 12.8] mL) with low overlap (median Dice's coefficient 0.24 [IQR 0.08, 0.59]). Delineation volumes were substantially increased in five (31%) patients. In a per biopsy analysis, combined 18F-DOPA PET/MRI detected high-grade subregions with an accuracy of 58% compared to 42% (p = 0.03) with CE MRI alone and 50% (p = 0.25) using multimodal MRI (CE + PWI). CONCLUSIONS: The addition of 18F-DOPA PET to multimodal MRI (CE and PWI) enlarged the delineation volumes and enhanced overall accuracy for detection of high-grade subregions. Thus, combining 18F-DOPA with advanced MRI may improve treatment planning in newly diagnosed gliomas.

Advanced imaging techniques for neuro-oncologic tumor diagnosis, with an emphasis on PET-MRI imaging of malignant brain tumors.

PURPOSE OF REVIEW: This review will explore the latest in advanced imaging techniques, with a focus on the complementary nature of multiparametric, multimodality imaging using magnetic resonance imaging (MRI) and positron emission tomography (PET). RECENT FINDINGS: Advanced MRI techniques including perfusion-weighted imaging (PWI), MR spectroscopy (MRS), diffusion-weighted imaging (DWI), and MR chemical exchange saturation transfer (CEST) offer significant advantages over conventional MR imaging when evaluating tumor extent, predicting grade, and assessing treatment response. PET performed in addition to advanced MRI provides complementary information regarding tumor metabolic properties, particularly when performed simultaneously. 18F-fluoroethyltyrosine (FET) PET improves the specificity of tumor diagnosis and evaluation of post-treatment changes. Incorporation of radiogenomics and machine learning methods further improve advanced imaging. The complementary nature of combining advanced imaging techniques across modalities for brain tumor imaging and incorporating technologies such as radiogenomics has the potential to reshape the landscape in neuro-oncology.

Perfusion-weighted techniques in MRI grading of pediatric cerebral tumors: efficiency of dynamic susceptibility contrast and arterial spin labeling.

PURPOSE: Dynamic susceptibility contrast (DSC) and arterial spin labeling (ASL) perfusion MRI are applied in pediatric brain tumor grading, but their value for clinical daily practice remains unclear. We explored the ability of ASL and DSC to distinguish low- and high-grade lesions, in an unselected cohort of pediatric cerebral tumors. METHODS: We retrospectively compared standard perfusion outcomes including blood volume, blood flow, and time parameters from DSC and ASL at 1.5T or 3T MRI scanners of 46 treatment-naive patients by drawing ROI via consensus by two neuroradiologists on the solid portions of every tumor. The discriminant abilities of perfusion parameters were evaluated by receiver operating characteristic (ROC) over the entire cohort and depending on the tumor location and the magnetic field. RESULTS: ASL and DSC parameters showed overall low to moderate performances to distinguish low- and high-grade tumors (area under the curve: between 0.548 and 0.697). Discriminant abilities were better for tumors located supratentorially (AUC between 0.777 and 0.810) than infratentorially, where none of the metrics reached significance. We observed a better differentiation between low- and high-grade cancers at 3T than at 1.5-T. For infratentorial tumors, time parameters from DSC performed better than the commonly used metrics (AUC ≥ 0.8). CONCLUSION: DSC and ASL show moderate abilities to distinguish low- and high-grade brain tumors in an unselected cohort. Absolute value of K2, TMAX, tMIP, and normalized value of TMAX of the DSC appear as an alternative to conventional parameters for infratentorial tumors. Three Tesla evaluation should be favored over 1.5-Tesla.

Predicting 1p/19q codeletion status using diffusion-, susceptibility-, perfusion-weighted, and conventional MRI in IDH-mutant lower-grade gliomas.

BACKGROUND: Isocitrate dehydrogenase (IDH)-mutant lower-grade gliomas (LGGs) are further classified into two classes: with and without 1p/19q codeletion. IDH-mutant and 1p/19q codeleted LGGs have better prognosis compared with IDH-mutant and 1p/19q non-codeleted LGGs. PURPOSE: To evaluate conventional magnetic resonance imaging (cMRI), diffusion-weighted imaging (DWI), susceptibility-weighted imaging (SWI), and dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) for predicting 1p/19q codeletion status of IDH-mutant LGGs. MATERIAL AND METHODS: We retrospectively reviewed cMRI, DWI, SWI, and DSC-PWI in 142 cases of IDH mutant LGGs with known 1p/19q codeletion status. Features of cMRI, relative ADC (rADC), intratumoral susceptibility signals (ITSSs), and the value of relative cerebral blood volume (rCBV) were compared between IDH-mutant LGGs with and without 1p/19q codeletion. Receiver operating characteristic curve and logistic regression were used to determine diagnostic performances. RESULTS: IDH-mutant and 1p/19q non-codeleted LGGs tended to present with the T2/FLAIR mismatch sign and distinct borders (P < 0.001 and P = 0.038, respectively). Parameters of rADC, ITSSs, and rCBVmax were significantly different between the 1p/19q codeleted and 1p/19q non-codeleted groups (P < 0.001, P = 0.017, and P < 0.001, respectively). A combination of cMRI, SWI, DWI, and DSC-PWI for predicting 1p/19q codeletion status in IDH-mutant LGGs resulted in a sensitivity, specificity, positive predictive value, negative predictive value, and an AUC of 80.36%, 78.57%, 83.30%, 75.00%, and 0.88, respectively. CONCLUSION: 1p/19q codeletion status of IDH-mutant LGGs can be stratified using cMRI and advanced MRI techniques, including DWI, SWI, and DSC-PWI. A combination of cMRI, rADC, ITSSs, and rCBVmax may improve the diagnostic performance for predicting 1p/19q codeletion status.