Cerebral Blood Volume Maps Research Articles

Prospective Longitudinal Analysis of Physiologic MRI-based Tumor Habitat Predicts Short-term Patient Outcomes in IDH-wildtype Glioblastoma.

This study validates MRI-based tumor habitats in predicting time-to-progression (TTP), overall survival (OS), and progression site in isocitrate dehydrogenase (IDH)-wildtype glioblastoma patients. Seventy-nine patients were prospectively enrolled between January 2020 and June 2022. MRI, including diffusion-weighted and dynamic susceptibility contrast imaging, were obtained immediately post-operation and at three serial timepoints. Voxels from cerebral blood volume and apparent diffusion coefficient maps were grouped into three habitats (hypervascular cellular, hypovascular cellular, and nonviable tissue) using k-means clustering. Pre-defined cutoffs for increases in hypervascular and hypovascular cellular habitat were applied to calculate the habitat risk score. Associations between spatiotemporal habitats, habitat risk score, TTP, and OS were investigated using Cox proportional hazards modeling. Habitat risk score was compared to tumor volume using time-dependent receiver operating characteristics analysis. Progression sites were matched with spatial habitats. Increases in hypervascular and hypovascular cellular habitats and habitat risk scores were associated with shorter TTP and OS (all p < .05). Hypovascular cellular habitat and habitat risk scores 1 and 2 independently predicted TTP (hazard ratio [HR], 4.14; p=.03, HR, 4.51; p=.001 and HR, 10.02; p<.001, respectively). Hypovascular cellular habitat and habitat risk score 2 independently predicted OS (HR, 4.01, p=.003; and HR, 3.27, p<.001, respectively). Habitat risk score outperformed tumor volume in predicting TTP (12-month AUC, 0.762 vs. 0.646, p=.048). Hypovascular cellular habitat predicted progression sites (mean Dice index: 0.31). Multiparametric physiologic MRI-based spatiotemporal tumor habitats and habitat risk scores are useful biomarkers for early tumor progression and outcomes in IDH-wildtype glioblastoma patients.

Multi-Site Benchmark Study for Standardized Relative Cerebral Blood Volume in Untreated Brain Metastases Using the DSC-MRI Consensus Acquisition Protocol.

A national consensus recommendation for the collection of DSC (dynamic susceptibility contrast) MRI perfusion data, used to create maps of relative cerebral blood volume (rCBV), has been recently established for primary and metastatic brain tumors. The goal was to reduce inter-site variability and improve ease of comparison across time and sites, fostering widespread use of this informative measure. To translate this goal into practice the prospective collection of consensus DSC-MRI data and characterization of derived rCBV maps in brain metastases is needed. The purpose of this multi-site study was to determine rCBV in untreated brain metastases in comparison to glioblastoma and normal appearing brain using the national consensus protocol. Subjects from three sites with untreated enhancing brain metastases underwent DSC-MRI according to a recommended option that uses a mid-range flip angle, GRE-EPI acquisition and the administration of both a pre-load and 2nd DSC-MRI dose of 0.1 mmol/kg GBCA. Quantitative maps of standardized rCBV (sRCBV) were generated and enhancing lesion ROIs determined from post-contrast T1-weighted images alone or calibrated difference maps, termed delta T1 (dT1) maps. Mean sRCBV for metastases were compared to normal appearing white matter (NAWM) and glioblastoma (GBM) from a previous study. Comparisons were performed using either the Wilcoxon signed-rank test for paired comparisons or the Mann-Whitney nonparametric test for unpaired comparisons. 49 patients with a primary histology of lung (n=25), breast (n=6), squamous cell carcinoma (SCC) (n=1), melanoma (n=5), gastrointestinal (GI) (n=3) and genitourinary (GU) (n=9) were included in comparison to GBM (n=31). The mean sRCBV of all metastases (1.83+/-1.05) were significantly lower (p=0.0009) than mean sRCBV for GBM (2.67±1.34) with both statistically greater (p<0.0001) than NAWM (0.68 +/- 0.18). Histologically distinct metastases are each statistically greater than NAWM (p<0.0001) with lung (p=0.0002) and GU (p=.02) sRCBV being significantly different than GBM sRCBV. 49 patients with a primary histology of lung (n=25), breast (n=6), squamous cell carcinoma (SCC) (n=1), melanoma (n=5), gastrointestinal (GI) (n=3) and genitourinary (GU) (n=9) were included in comparison to GBM (n=31). The mean sRCBV of all metastases (1.83+/-1.05) were significantly lower (p=0.0009) than mean sRCBV for GBM (2.67+1.34) with both statistically greater (p<0.0001) than NAWM (0.68 +/- 0.18). Histologically distinct metastases are each statistically greater than NAWM (p<0.0001) with lung (p=0.0002) and GU (p=.02) sRCBV being significantly different than GBM sRCBV. dT1=delta T1; GBCA=gadolinium-based contrast agent; NAWM=normal appearing white matter; normalized relative cerebral blood volume=nRCBV; relative cerebral blood volume=rCBV; standardized relative cerebral blood volume=sRCBV.

Cerebral perfusion metrics calculated directly from a hypoxia-induced step change in deoxyhemoglobin

Resting cerebral perfusion metrics can be calculated from the MRI ΔR2* signal during the first passage of an intravascular bolus of a Gadolinium-based contrast agent (GBCA), or more recently, a transient hypoxia-induced change in the concentration of deoxyhemoglobin ([dOHb]). Conventional analysis follows a proxy process that includes deconvolution of an arterial input function (AIF) in a tracer kinetic model. We hypothesized that the step reduction in magnetic susceptibility accompanying a step decrease in [dOHb] that occurs when a single breath of oxygen terminates a brief episode of lung hypoxia permits direct calculation of relative perfusion metrics. The time course of the ΔR2* signal response enables both the discrimination of blood arrival times and the time course of voxel filling. We calculated the perfusion metrics implied by this step signal change in seven healthy volunteers and compared them to those from conventional analyses of GBCA and dOHb using their AIF and indicator dilution theory. Voxel-wise maps of relative cerebral blood flow and relative cerebral blood volume had a high spatial and magnitude congruence for all three analyses (r > 0.9) and were similar in appearance to published maps. The mean (SD) transit times (s) in grey and white matter respectively for the step response (7.4 (1.1), 8.05 (1.71)) were greater than those for GBCA (2.6 (0.45), 3.54 (0.83)) attributable to the nature of their respective calculation models. In conclusion we believe these calculations of perfusion metrics derived directly from ΔR2* have superior merit to calculations via AIF by virtue of being calculated from a direct signal rather than through a proxy model which encompasses errors inherent in designating an AIF and performing deconvolution calculations.

Fractional tumor burden maps increase the confidence of reading brain MR perfusion

Rationale and objectivesVarious methods exist to perform and post-process perfusion weighted MR imaging in the post-treatment imaging of glioma patients to differentiate tumor progression from tumor-related abnormalities. One of these post-processing methods produces ‘fractional tumor burden’ maps. This multi-reader study investigated the clinical feasibility of fractional tumor burden maps on real world data from radiological follow-up of high-grade astrocytoma patients. MethodsFive readers with background in radiology and varying levels of experience were tasked with assessing 30 astrocytoma and glioblastoma patients during one reader session. First, they were provided with a dataset of conventional MRI sequences, including perfusion MRI with regional cerebral blood volume maps. Then the dataset was expanded with a corresponding fractional tumor burden maps. Diagnostic accuracy, duration of post-processing, duration of the assessment of the fractional tumor burden maps, the diagnostic confidence reported by the readers and their diagnoses were recorded. Final diagnosis was determined by clinical and radiological follow-up and/or histopathological data used as gold standard. ResultsA mean sensitivity of 83.3 % and mean specificity of 55.1 % was obtained without the use of fractional tumor burden maps, whereas their additional of fractional tumor burden maps resulted in a mean sensitivity and specificity of 79.5 % and 54.2 %, respectively. Diagnostic accuracies with and without fractional tumor burden maps were not significantly different (Z = 0.76, p = 0.450). The median time spent post-processing was 313 s, while the median duration of the assessment of the FTB maps was 19 s. Interestingly, reader confidence increased significantly after adding the fractional tumor burden-maps to the assessment (Z = 454, p < 0.01). ConclusionsWhile the use of fractional tumor burden maps does not carry additional value in the radiological follow-up of post-operative high-grade astrocytoma and glioblastoma patients, it does give readers more confidence in their diagnosis.

Assessment of imaging risks for recurrence after stereotactic radiosurgery for brain metastases (IRRaS-BM)

BackgroundThe identification of viable tumors and radiation necrosis after stereotactic radiosurgery (SRS) is crucial for patient management. Tumor habitat analysis involving the grouping of similar voxels can identify subregions that share common biology and enable the depiction of areas of tumor recurrence and treatment-induced change. This study aims to validate an imaging biomarker for tumor recurrence after SRS for brain metastasis by conducting tumor habitat analysis using multi-parametric MRI.MethodsIn this prospective study (NCT05868928), patients with brain metastases will undergo multi-parametric MRI before SRS, and then follow-up MRIs will be conducted every 3 months until 24 months after SRS. The multi-parametric MRI protocol will include T2-weighted and contrast-enhanced T1-weighted imaging, diffusion-weighted imaging, and dynamic susceptibility contrast imaging. Using k-means voxel-wise clustering, this study will define three structural MRI habitats (enhancing, solid low-enhancing, and nonviable) on T1- and T2-weighted images and three physiologic MRI habitats (hypervascular cellular, hypovascular cellular, and nonviable) on apparent diffusion coefficient maps and cerebral blood volume maps. Using RANO-BM criteria as the reference standard, via Cox proportional hazards analysis, the study will prospectively evaluate associations between parameters of the tumor habitats and the time to recurrence. The DICE similarity coefficients between the recurrence site and tumor habitats will be calculated.DiscussionThe tumor habitat analysis will provide an objective and reliable measure for assessing tumor recurrence from brain metastasis following SRS. By identifying subregions for local recurrence, our study could guide the next therapeutic targets for patients after SRS.Trial registrationThis study is registered at ClinicalTrials.gov (NCT05868928).

E.2 Proof of concept for liquid biopsy: positive correlation between extracellular vesicles shed by high grade gliomas and volume of hypervascular tumour tissue on MRI

Background: High grade gliomas (HGGs) shed extracellular vesicles (EVs) into the bloodstream. EV-derived RNA (EV-RNA) can be detected in plasma, making it a potential biomarker for HGG recurrence after treatment. We sought to establish a baseline relationship between EV-RNA in plasma and hypervascular HGG tissue on MRI. Methods: Eight patients with a new diagnosis of HGG had measurements of plasma EV-RNA and contemporaneous dynamic susceptibility contrast (DSC) MRI. Patient-specific median signal intensity of corpus callosum (mSI-CC) was determined from 10 measurements on the relative cerebral blood volume (rCBV) map. Tumour tissue with signal intensity &gt; mSI-CC and &gt; 2x, &gt; 3x, &gt; 4x and &gt; 5x mSI-CC was segmented on the rCBV map. EV-RNA plasma concentration was correlated with tissue volumes. Results: Pearson correlation showed a significant positive relationship between EV-RNA plasma concentration and tissue volume with signal intensity &gt; mSI-CC (r(6) = 0.899, p = 0.002). No significant relationship could be detected for progressively smaller tissue volumes with signal intensity &gt; 2x, &gt; 3x, &gt; 4x and &gt; 5x mSI-CC. Conclusions: EV-RNA plasma concentration correlates strongly with the total volume of hypervascular HGG tissue on DSC MRI at baseline and merits further evaluation as a biomarker of tumour behaviour in longitudinal imaging studies.

Correlation between rCBV Delineation Similarity and Overall Survival in a Prospective Cohort of High-Grade Gliomas Patients: The Hidden Value of Multimodal MRI?

The accuracy of target delineation in radiation treatment planning of high-grade gliomas (HGGs) is crucial to achieve high tumor control, while minimizing treatment-related toxicity. Magnetic resonance imaging (MRI) represents the standard imaging modality for delineation of gliomas with inherent limitations in accurately determining the microscopic extent of tumors. The purpose of this study was to assess the survival impact of multi-observer delineation variability of multiparametric MRI (mpMRI) and [18F]-FET PET/CT. Thirty prospectively included patients with histologically confirmed HGGs underwent a PET/CT and mpMRI including diffusion-weighted imaging (DWI: b0, b1000, ADC), contrast-enhanced T1-weighted imaging (T1-Gado), T2-weighted fluid-attenuated inversion recovery (T2Flair), and perfusion-weighted imaging with computation of relative cerebral blood volume (rCBV) and K2 maps. Nine radiation oncologists delineated the PET/CT and MRI sequences. Spatial similarity (Dice similarity coefficient: DSC) was calculated between the readers for each sequence. Impact of the DSC on progression-free survival (PFS) and overall survival (OS) was assessed using Kaplan-Meier curves and the log-rank test. The highest DSC mean values were reached for morphological sequences, ranging from 0.71 +/- 0.18 to 0.84 +/- 0.09 for T2Flair and T1Gado, respectively, while metabolic volumes defined by PET/CT achieved a mean DSC of 0.75 +/- 0.11. rCBV variability (mean DSC0.32 +/- 0.20) significantly impacted PFS (p = 0.02) and OS (p = 0.002). Our data suggest that the T1-Gado and T2Flair sequences were the most reproducible sequences, followed by PET/CT. Reproducibility for functional sequences was low, but rCBV inter-reader similarity significantly impacted PFS and OS.

Probing the glioma microvasculature: a case series of the comparison between perfusion MRI and intraoperative high-frame-rate ultrafast Doppler ultrasound

BackgroundWe aimed to describe the microvascular features of three types of adult-type diffuse glioma by comparing dynamic susceptibility contrast (DSC) perfusion magnetic resonance imaging (MRI) with intraoperative high-frame-rate ultrafast Doppler ultrasound.MethodsCase series of seven patients with primary brain tumours underwent both DSC perfusion MRI and intra-operative high-frame-rate ultrafast Doppler ultrasound. From the ultrasound images, three-dimensional vessel segmentation was obtained of the tumour vascular bed. Relative cerebral blood volume (rCBV) maps were generated with leakage correction and normalised to the contralateral normal-appearing white matter. From tumour histograms, median, mean, and maximum rCBV ratios were extracted.ResultsLow-grade gliomas (LGGs) showed lower perfusion than high-grade gliomas (HGGs), as expected. Within the LGG subgroup, oligodendroglioma showed higher perfusion than astrocytoma. In HGG, the median rCBV ratio for glioblastoma was 3.1 while astrocytoma grade 4 showed low perfusion with a median rCBV of 1.2. On the high-frame-rate ultrafast Doppler ultrasound images, all tumours showed a range of rich and organised vascular networks with visually apparent abnormal vessels, even in LGG.ConclusionsThis unique case series revealed in vivo insights about the microvascular architecture in both LGGs and HGGs. Ultrafast Doppler ultrasound revealed rich vascularisation, also in tumours with low perfusion at DSC MRI. These findings warrant further investigations using advanced MRI postprocessing, in particular for characterising adult-type diffuse glioma.Relevance statementOur findings challenge the current assumption behind the estimation of relative cerebral blood volume that the distribution of blood vessels in a voxel is random.Key points• Ultrafast Doppler ultrasound revealed rich vascularity irrespective of perfusion dynamic susceptibility contrast MRI state.• Rich and organised vascularisation was also observed even in low-grade glioma.• These findings challenge the assumptions for cerebral blood volume estimation with MRI.Graphical

Diffusion- and Perfusion-Weighted MRI Radiomics for Survival Prediction in Patients with Lower-Grade Gliomas.

Lower-grade gliomas of histologic grades 2 and 3 follow heterogenous clinical outcomes, which necessitates risk stratification. This study aimed to evaluate whether diffusion-weighted and perfusion-weighted MRI radiomics allow overall survival (OS) prediction in patients with lower-grade gliomas and investigate its prognostic value. In this retrospective study, radiomic features were extracted from apparent diffusion coefficient, relative cerebral blood volume map, and Ktrans map in patients with pathologically confirmed lower-grade gliomas (January 2012-February 2019). The radiomics risk score (RRS) calculated from selected features constituted a radiomics model. Multivariable Cox regression analysis, including clinical features and RRS, was performed. The models' integrated area under the receiver operating characteristic curves (iAUCs) were compared. The radiomics model combined with clinical features was presented as a nomogram. The study included 129 patients (median age, 44 years; interquartile range, 37-57 years; 63 female): 90 patients for training set and 39 patients for test set. The RRS was an independent risk factor for OS with a hazard ratio of 6.01. The combined clinical and radiomics model achieved superior performance for OS prediction compared to the clinical model in both training (iAUC, 0.82 vs. 0.72, p=0.002) and test sets (0.88 vs. 0.76, p=0.04). The radiomics nomogram combined with clinical features exhibited good agreement between the actual and predicted OS with C-index of 0.83 and 0.87 in the training and test sets, respectively. Adding diffusion- and perfusion-weighted MRI radiomics to clinical features improved survival prediction in lower-grade glioma.

Assessment of Brain Tumour Perfusion Using Early-Phase 18F-FET PET: Comparison with Perfusion-Weighted MRI

PurposeMorphological imaging using MRI is essential for brain tumour diagnostics. Dynamic susceptibility contrast (DSC) perfusion-weighted MRI (PWI), as well as amino acid PET, may provide additional information in ambiguous cases. Since PWI is often unavailable in patients referred for amino acid PET, we explored whether maps of relative cerebral blood volume (rCBV) in brain tumours can be extracted from the early phase of PET using O-(2-18F-fluoroethyl)-L-tyrosine (18F-FET).ProcedureUsing a hybrid brain PET/MRI scanner, PWI and dynamic 18F-FET PET were performed in 33 patients with cerebral glioma and four patients with highly vascularized meningioma. The time interval from 0 to 2 min p.i. was selected to best reflect the blood pool phase in 18F-FET PET. For each patient, maps of MR-rCBV, early 18F-FET PET (0–2 min p.i.) and late 18F-FET PET (20–40 min p.i.) were generated and coregistered. Volumes of interest were placed on the tumour (VOI-TU) and normal-appearing brain (VOI-REF). The correlation between tumour-to-brain ratios (TBR) of the different parameters was analysed. In addition, three independent observers evaluated MR-rCBV and early 18F-FET maps (18F-FET-rCBV) for concordance in signal intensity, tumour extent and intratumoural distribution.ResultsTBRs calculated from MR-rCBV and 18F-FET-rCBV showed a significant correlation (r = 0.89, p < 0.001), while there was no correlation between late 18F-FET PET and MR-rCBV (r = 0.24, p = 0.16) and 18F-FET-rCBV (r = 0.27, p = 0.11). Visual rating yielded widely agreeing findings or only minor differences between MR-rCBV maps and 18F-FET-rCBV maps in 93 % of the tumours (range of three independent raters 91–94%, kappa among raters 0.78–1.0).ConclusionEarly 18F-FET maps (0–2 min p.i.) in gliomas provide similar information to MR-rCBV maps and may be helpful when PWI is not possible or available. Further studies in gliomas are needed to evaluate whether 18F-FET-rCBV provides the same clinical information as MR-rCBV.

Minimally Invasive Intracerebral Hemorrhage Evacuation Improves Pericavity Cerebral Blood Volume.

Cerebral blood volume mapping can characterize hemodynamic changes within brain tissue, particularly after stroke. This study aims to quantify blood volume changes in the perihematomal parenchyma and pericavity parenchyma after minimally invasive intracerebral hemorrhage evacuation (MIS for ICH). Thirty-two patients underwent MIS for ICH with pre- and post-operative CT imaging and intraoperative perfusion imaging (DynaCT PBV Neuro, Artis Q, Siemens). The pre-operative and post-operative CT scans were segmented using ITK-SNAP software to calculate hematoma volumes and to delineate the pericavity tissue. Helical CT segmentations were registered to cone beam CT data using elastix software. Mean blood volumes were computed inside subvolumes by dilating the segmentations at increasing distances from the lesion. Pre-operative perihematomal blood volumes and post-operative pericavity blood volumes (PBV) were compared. In 27 patients with complete imaging, post-operative PBV significantly increased within the 6-mm pericavity region after MIS for ICH. The mean relative PBV increased by 21.6 and 9.1% at 3 mm and 6 mm, respectively (P = 0.001 and 0.016, respectively). At the 9-mm pericavity region, there was a 2.83% increase in mean relative PBV, though no longer statistically significant. PBV analysis demonstrated a significant increase in pericavity cerebral blood volume after minimally invasive ICH evacuation to a distance of 6 mm from the border of the lesion.

Evaluation of 3D stack-of-spiral turbo FLASH acquisitions for pseudo-continuous and velocity-selective ASL-derived brain perfusion mapping.

The most-used 3D acquisitions for ASL are gradient and spin echo (GRASE)- and stack-of-spiral (SOS)-based fast spin echo, which require multiple shots. Alternatively, turbo FLASH (TFL) allows longer echo trains, and SOS-TFL has the potential to reduce the number of shots to even single-shot, thus improving the temporal resolution. Here we compare the performance of 3D SOS-TFL and 3D GRASE for ASL at 3T. The 3D SOS-TFL readout was optimized with respect to fat suppression and excitation flip angles for pseudo-continuous ASL- and velocity-selective (VS)ASL-derived cerebral blood flow (CBF) mapping as well as for VSASL-derived cerebral blood volume (CBV) mapping. Results were compared with 3D GRASE readout on healthy volunteers in terms of perfusion quantification and temporal SNR (tSNR) efficiency. CBF and CBV mapping derived from 3D SOS-TFL-based ASL was demonstrated on one stroke patient, and the potential for single-shot acquisitions was exemplified. SOS-TFL with a 15° flip angle resulted in adequate tSNR efficiency with negligible image blurring. Selective water excitation was necessary to eliminate fat-induced artifacts. For pseudo-continuous ASL- and VSASL-based CBF and CBV mapping, compared to the employed four-shot 3D GRASE with an acceleration factor of 2, the fully sampled 3D SOS-TFL delivered comparable performance (with a similar scan time) using three shots, which could be further undersampled to achieve single-shot acquisition with higher tSNR efficiency. SOS-TFL had reduced CSF contamination for VSASL-CBF. 3D SOS-TFL acquisition was found to be a viable substitute for 3D GRASE for ASL with sufficient tSNR efficiency, minimal relaxation-induced blurring, reduced CSF contamination, and the potential of single-shot, especially for VSASL.

Microvasculature Features Derived from Hybrid EPI MRI in Non-Enhancing Adult-Type Diffuse Glioma Subtypes

In this study, we used the vessel size imaging (VSI) MRI technique to characterize the microvasculature features of three subtypes of adult-type diffuse glioma lacking enhancement. Thirty-eight patients with confirmed non-enhancing glioma were categorized into three subtypes: Oligo (IDH-mut&1p/19q-codeleted), Astro (IDH-mut), and GBM (IDH-wt). The VSI technique provided quantitative maps of cerebral blood volume (CBV), microvasculature (µCBV), and vessel size for each patient. Additionally, tissue samples of 21 patients were histopathologically analyzed, and microvasculature features were quantified. Both MRI- and histology-derived features were compared across the three glioma subtypes with ANOVA or Kruskal-Wallis tests. Group averages of CBV, μCBV, and vessel size were significantly different between the three glioma subtypes (p < 0.01). Astro (IDH-mut) had a significantly lower CBV and µCBV compared to Oligo (IDH-mut&1p/19q-codeleted) (p = 0.004 and p = 0.001, respectively), and a higher average vessel size compared to GBM (IDH-wt) (p = 0.01). The histopathological analysis showed that GBM (IDH-wt) possessed vessels with more irregular shapes than the two other subtypes (p < 0.05). VSI provides a good insight into the microvasculature characteristics of the three adult-type glioma subtypes even when lacking enhancement. Further investigations into the specificity of VSI to differentiate glioma subtypes are thus warranted.

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

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. Sixty-eight pediatric patients (mean age, 10.47 ± 4.37years; 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. 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). The whole-tumor histogram analysis of DWI and DSC-PWI is a promising method for grading pediatric gliomas.

Pseudoprogression in GBM versus true progression in patients with glioblastoma: A multiapproach analysis

Background and purposeTo investigate the feasibility of using a multiapproach analysis combining clinical data, diffusion- and perfusion-weighted imaging, and 3D magnetic resonance spectroscopic imaging to distinguish true tumor progression (TP) from pseudoprogression (PSP) in patients with glioblastoma. Materials and methodsProgression was suspected within 6 months of radiotherapy in 46 of the 180 patients included in the Phase-III SpectroGlio trial (NCT01507506). Choline/creatine (Cho/Cr), choline/N-acetyl aspartate (Cho/NAA) and lactate/N-acetyl aspartate (Lac/NAA) ratios were extracted. Apparent diffusion coefficient (ADC) and cerebral blood volume (CBV) maps were calculated. ADC, relative CBV values and tumor volume (TV) were collected at relapse. Differences between TP and PSP were evaluated using Mann–Whitney tests, and p values were adjusted with Bonferroni correction. ResultsPatients with suspected progression underwent a new MRI scan 1 month after the first one. Of these, 28 were classified as PSP, and 18 as TP. After a median follow-up of 41 months, median overall survival was higher in PSP than in TP (25.2 vs 20.3 months; p = 0.0092). Lac/NAA and Cho/Cr ratios were higher in TP than in PSP (1.2 vs 0.5; p = 0.006; and 3 vs 2.2; p = 0.021). After multivariate regression analysis, TV was the most significant predictor of TP vs PSP, and the only one retained in the model (p = 0.028). ConclusionThree spectroscopic ratios could be used to differentiate PSP from TP. TV at relapse was the most predictive factor in the multivariate analysis, and overall survival was higher in PSP than in TP.

Effect of Temporal Sampling Rate on Estimates of the Perfusion Parameters for Patients with Moyamoya Disease Assessed with Simultaneous Multislice Dynamic Susceptibility Contrast-enhanced MR Imaging.

The effect of temporal sampling rate (TSR) on perfusion parameters has not been fully investigated in Moyamoya disease (MMD); therefore, this study evaluated the influence of different TSRs on perfusion parameters quantitatively and qualitatively by applying simultaneous multi-slice (SMS) dynamic susceptibility contrast-enhanced MR imaging (DSC-MRI). DSC-MRI datasets were acquired from 28 patients with MMD with a TSR of 0.5 s. Cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), time to peak (TTP), and time to maximum tissue residue function (Tmax) were calculated for eight TSRs ranging from 0.5 to 4.0 s in 0.5-s increments that were subsampled from a TSR of 0.5 s datasets. Perfusion measurements and volume for chronic ischemic (Tmax ≥ 2 s) and non-ischemic (Tmax < 2 s) areas for each TSR were compared to measurements with a TSR of 0.5 s, as was visual perfusion map analysis. CBF, CBV, and Tmax values tended to be underestimated, whereas MTT and TTP values were less influenced, with a longer TSR. Although Tmax values were overestimated in the TSR of 1.0 s in non-ischemic areas, differences in perfusion measurements between the TSRs of 0.5 and 1.0 s were generally minimal. The volumes of the chronic ischemic areas with a TSR ≥ 3.0 s were significantly underestimated. In CBF and CBV maps, no significant deterioration was noted in image quality up to 3.0 and 2.5 s, respectively. The image quality of MTT, TTP, and Tmax maps for the TSR of 1.0 s was similar to that for the TSR of 0.5 s but was significantly deteriorated for the TSRs of ≥ 1.5 s. In the assessment of MMD by SMS DSC-MRI, application of TSRs of ≥ 1.5 s may lead to deterioration of the perfusion measurements; however, that was less influenced in TSRs of ≤ 1.0 s.

Assessing the added value of apparent diffusion coefficient, cerebral blood volume, and radiomic magnetic resonance features for differentiation of pseudoprogression versus true tumor progression in patients with glioblastoma.

Pseudoprogression (PsPD) is a major diagnostic challenge in the follow-up of patients with glioblastoma (GB) after chemoradiotherapy (CRT). Conventional imaging signs and parameters derived from diffusion and perfusion-MRI have yet to prove their reliability in clinical practice for an accurate differential diagnosis. Here, we tested these parameters and combined them with radiomic features (RFs), clinical data, and MGMT promoter methylation status using machine- and deep-learning (DL) models to distinguish PsPD from Progressive disease. In a single-center analysis, 105 patients with GB who developed a suspected imaging PsPD in the first 7 months after standard CRT were identified retrospectively. Imaging data included standard MRI anatomical sequences, apparent diffusion coefficient (ADC), and normalized relative cerebral blood volume (nrCBV) maps. Median values (ADC, nrCBV) and RFs (all sequences) were calculated from DL-based tumor segmentations. Generalized linear models with LASSO feature-selection and DL models were built integrating clinical data, MGMT methylation status, median ADC and nrCBV values and RFs. A model based on clinical data and MGMT methylation status yielded an areas under the receiver operating characteristic curve (AUC) = 0.69 (95% CI 0.55-0.83) for detecting PsPD, and the addition of median ADC and nrCBV values resulted in a nonsignificant increase in performance (AUC = 0.71, 95% CI 0.57-0.85, P = .416). Combining clinical/MGMT information with RFs derived from ADC, nrCBV, and from all available sequences both resulted in significantly (both P < .005) lower model performances, with AUC = 0.52 (0.38-0.66) and AUC = 0.54 (0.40-0.68), respectively. DL imaging models resulted in AUCs ≤ 0.56. Currently available imaging biomarkers could not reliably differentiate PsPD from true tumor progression in patients with glioblastoma; larger collaborative efforts are needed to build more reliable models.

Telomerase reverse transcriptase promoter mutation and histologic grade in IDH wild-type histological lower-grade gliomas: The value of perfusion-weighted image, diffusion-weighted image, and 18F-FDG-PET

PurposeThe telomerase reverse transcriptase promoter (TERTp) mutation is an unfavorable prognostic factor in isocitrate dehydrogenase-wildtype (IDHwt) histologically lower-grade astrocytoma (LGA), which was incorporated as a key component in the WHO 2021 classification of IDHwt LGA, replacing histologic grades in the WHO 2016 classification. The purpose of this study was to identify the imaging characteristics predictive of TERTp mutations in IDHwt LGA. MethodsThis retrospective study was approved by our institutional review board. This single-center study retrospectively included 59 patients with pathologically confirmed IDHwt LGA with known TERTp mutation status. In addition to clinical information and morphological characteristics, semi-quantitative imaging biomarkers such as the tumor-to-normal ratio (T/N ratio) on 18F-FDG-PET, normalized apparent diffusion coefficient (nADC), and histogram parameters from normalized relative cerebral blood volume (nrCBV) maps were compared between (a) TERTp-wildtype and TERTp-mutant tumors or (b) grade II and grade III astrocytoma. A p value < 0.05 was considered significant. ResultsThere were no significant differences in the conventional imaging findings, T/N ratio on FDG-PET, nrCBV or ADC histogram metrics between IDHwt LGA with TERTp mutations and those without. Grade III IDHwt astrocytomas exhibited significantly higher nrCBV values, T/N ratio and lower ADC parameters than grade II IDHwt astrocytoma. ConclusionsIn patients with IDHwt LGA, T/N ratio, nrCBV values and nADC may be surrogate markers for predicting histologic grade, but are not useful for predicting TERTp mutations.

Can angiographic Flat Detector Computed Tomography blood volume measurement be used to predict final infarct size in acute ischemic stroke?

Introduction and purposeFlat detector computed tomography (FD-CT) technology is becoming more widely available in the angiography suites of comprehensive stroke centers. In patients with acute ischemic stroke (AIS), who are referred for endovascular therapy (EVT), FD-CT generates cerebral pooled blood volume (PBV) maps, which might help in predicting the final infarct area. We retrospectively analyzed pre- and post-recanalization therapy quantitative PBV measurements in both the infarcted and hypoperfused brain areas of AIS patients referred for EVT. Materials and methodsWe included AIS patients with large vessel occlusion in the anterior circulation referred for EVT from primary stroke centers to our comprehensive stroke center. The pre- and post-recanalization FD-CT regional relative PBV (rPBV) values were measured between ipsilateral lesional and contralateral non-lesional areas based on final infarct area on post EVT follow-up cross-sectional imaging. Statistical analysis was performed to identify differences in PBV values between infarcted and non-infarcted, recanalized brain areas. ResultsWe included 20 AIS patients. Mean age was 63 years (ranging from 36 to 86 years). The mean pre- EVT rPBV value was 0.57 (±0.40) for infarcted areas and 0.75 (±0.43) for hypoperfusion areas. The mean differences (Δ) between pre- and post-EVT rPBV values for infarcted and hypoperfused areas were respectively 0.69 (±0.59) and 0.69 (±0.90). We found no significant differences (p > 0.05) between pre-EVT rPBV and ΔrPBV values of infarct areas and hypoperfusion areas. ConclusionAngiographic PBV mapping is useful for the detection of cerebral perfusion deficits, especially in combination with the fill run images. However, we were not able to distinguish irreversibly infarcted tissue from potentially salvageable, hypoperfused brain tissue based on quantitative PBV measurement in AIS patients.

NIMG-12. DSC-MRI PERFUSION IMAGING IN UNTREATED BRAIN METASTASES USING THE CONSENSUS ACQUISITION PROTOCOL: A MULTI-SITE BENCHMARK STUDY

Abstract INTRODUCTION DSC-MRI perfusion methods are commonly used to evaluate both primary and metastatic brain cancer with the creation of maps of relative cerebral blood volume (rCBV). Recently, guidelines were established to ensure a standard DSC-MRI acquisition protocol that reduces inter-site variability. The purpose of this study was to initiate the determination of rCBV benchmark values using the DSC-MRI consensus protocol in treatment-naïve brain metastases. METHODS Patients from three sites with treatment-naïve, contrast-enhancing brain metastases on MRI were considered for inclusion in this retrospective study. The MRIs included pre- and post-contrast T1w(T1+C) images obtained after administration of gadolinium-based contrast agent (GBCA) (0.1 mmol/kg), which serves as the recommended preload for the DSC-MRI data collection. A 2nd GBCA dose (0.1 mmol/kg) was administered 40-60sec after the collection of baseline GRE-EPI images using recommended settings (FA=60o, TE/TR=30ms/1100-1250ms) for 120s. Calibrated pre/post T1w difference maps (dT1) were used for delineation of enhancing lesion, and standardized (calibrated) rCBV (sRCBV) created. Mean sRCBV for metastases were compared to normal appearing white matter (NAWM) and treatment-naive glioblastoma (GBM) from a previous study. Pairwise comparisons were performed using the Mann-Whitney nonparametric test. RESULTS N=52 patients with primary histology of lung (n=27); breast (n=6); skin (n=7); gastrointestinal (GI: n=3) and genitourinary (GU: n=9) cancers were included in comparison to GBM (n=31). The mean sRCBV for all metastases (1.77+/-1.05) is significantly lower (p=0.0003) than for GBM (2.67+/-1.34) but with both statistically greater (p&amp;lt; 0.0001) than NAWM (0.706+/-0.163). Individually, lung (1.47+/- 0.61), breast (2.275+/-0.87), skin (2.10+/-1.22), GI (1.91+/- 0.64) and GU (2.01+/-0.63) mean sRCBV are statistically greater than for NAWM. CONCLUSION Using the consensus DSC-MRI acquisition protocol confirms use of sRCBV to identify biologically active, treatment-naive brain metastases setting benchmark values for future applications.