Susceptibility Contrast Perfusion MR Imaging Research Articles

Correlation between dynamic susceptibility contrast perfusion MRI and genomic alterations in glioblastoma

To determine if dynamic susceptibility contrast perfusion MR imaging (DSC-pMRI) can predict significant genomic alterations in glioblastoma (GB). A total of 47 patients with treatment-naive GB (M/F: 23/24, mean age: 54years, age range: 20-90years) having DSC-pMRI with leakage correction and genomic analysis were reviewed. Mean relative cerebral blood volume (rCBV), maximum rCBV, relative percent signal recovery (rPSR), and relative peak height (rPH) were derived from T2* signal intensity-time curves by ROI analysis. Major genomic alterations of IDH1-132H, MGMT, p53, EGFR, ATRX, and PTEN status were correlated with DSC-pMRI-derived GB parameters. Statistical analysis was performed utilizing the independent-samples t-test, ROC (receiver operating characteristic) curve analysis, and multivariable stepwise regression model. rCBVmean and rCBVmax were significantly different in relation to the IDH1, MGMT, p53, and PTEN mutation status (all p < 0.05). The rPH of the p53 mutation-positive GBs (mean 5.8 ± 2.8) was significantly higher than those of the p53 mutation-negative GBs (mean 4.0 ± 1.5) (p = 0.022). Multivariable stepwise regression analysis revealed that the presence of IDH-1 mutation (B = - 2.81, p = 0.005) was associated with decreased rCBVmean; PTEN mutation (B = - 1.21, p = 0.003) and MGMT methylation (B = - 1.47, p = 0.038) were associated with decreased rCBVmax; and ATRX loss (B = - 1.05, p = 0.008) was associated with decreased rPH. Significant associations were identified between DSC-pMRI-derived parameters and major genomic alterations, including IDH-1 mutation, MGMT methylation, ATRX loss, and PTEN mutation status in GB.

Prediction of IDH genotype in gliomas with dynamic susceptibility contrast perfusion MR imaging using an explainable recurrent neural network.

The aim of this study was to predict isocitrate dehydrogenase (IDH) genotypes of gliomas using an interpretable deep learning application for dynamic susceptibility contrast (DSC) perfusion MRI. Four hundred sixty-three patients with gliomas who underwent preoperative MRI were enrolled in the study. All the patients had immunohistopathologic diagnoses of either IDH-wildtype or IDH-mutant gliomas. Tumor subregions were segmented using a convolutional neural network followed by manual correction. DSC perfusion MRI was performed to obtain T2* susceptibility signal intensity-time curves from each subregion of the tumors: enhancing tumor, non-enhancing tumor, peritumoral edema, and whole tumor. These, with arterial input functions, were fed into a neural network as multidimensional inputs. A convolutional long short-term memory model with an attention mechanism was developed to predict IDH genotypes. Receiver operating characteristics analysis was performed to evaluate the model. The IDH genotype predictions had an accuracy, sensitivity, and specificity of 92.8%, 92.6%, and 93.1%, respectively, in the validation set (area under the curve [AUC], 0.98; 95% confidence interval [CI], 0.969-0.991) and 91.7%, 92.1%, and 91.5%, respectively, in the test set (AUC, 0.95; 95% CI, 0.898-0.982). In temporal feature analysis, T2* susceptibility signal intensity-time curves obtained from DSC perfusion MRI with attention weights demonstrated high attention on the combination of the end of the pre-contrast baseline, up/downslopes of signal drops, and/or post-bolus plateaus for the curves used to predict IDH genotype. We developed an explainable recurrent neural network model based on DSC perfusion MRI to predict IDH genotypes in gliomas.

Dynamic contrast-enhanced and dynamic susceptibility contrast perfusion MR imaging for glioma grading: Preliminary comparison of vessel compartment and permeability parameters using hotspot and histogram analysis

IntroductionDynamic susceptibility contrast (DSC)-MRI is a perfusion technique with high diagnostic accuracy for glioma grading, despite limitations due to inherent susceptibility effects. Dynamic contrast-enhanced (DCE)-MRI has been proposed as an alternative technique able to overcome the DSC-MRI shortcomings.This pilot study aimed at comparing the diagnostic accuracy of DSC and DCE-MRI for glioma grading by evaluating two estimates of blood volume, the DCE-derived plasma volume (Vp) and the DSC-derived relative cerebral blood volume (rCBV), and a measure of vessel permeability, the DCE-derived volume transfer constant Ktrans. MethodsTwenty-six newly diagnosed glioma patients underwent 3T-MR DCE and DSC imaging. Parametric maps of CBV, Vp and Ktrans were calculated and the region of highest value (hotspot) was measured on each map. Histograms of rCBV, Vp and Ktrans values were calculated for the tumor volume. Statistical differences according to WHO grade were assessed. The diagnostic accuracy for tumor grading of the two techniques was determined by ROC analysis. ResultsrCBV, Vp and Ktrans measures differed significantly between high and low-grade gliomas. Hotspot analysis showed the highest correlation with grading. Ktrans hotspots co-localized with Vp hotspots only in 56% of enhancing gliomas. For differentiating high from low-grade gliomas the AUC was 0.987 for rCBVmax, and 1.000 for Vpmax and Ktransmax. Combination of DCE-derived Vp and Ktrans parameters improved the diagnostic performance of the histogram method. ConclusionThis initial experience of DCE-derived Vp evaluation shows that this parameter is as accurate as the well-established DSC-derived rCBV for glioma grading. DCE-derived Ktrans is equally useful for grading, providing different informations with respect to Vp.

Pseudoprogression in patients with glioblastoma: added value of arterial spin labeling to dynamic susceptibility contrast perfusion MR imaging

Pseudoprogression is a treatment-related reaction with an increase in contrast-enhancing lesion size, followed by subsequent improvement. Differentiating tumor recurrence from pseudoprogression remains a problem in neuro-oncology. To validate the added value of arterial spin labeling (ASL), compared with dynamic susceptibility contrast (DSC) perfusion magnetic resonance imaging (MRI) alone, in distinguishing early tumor progression from pseudoprogression in patients with newly diagnosed glioblastoma multiforme (GBM). We retrospectively evaluated 117 consecutive patients with newly diagnosed GBM who underwent surgical resection and concurrent chemoradiotherapy (CCRT) as standard treatment modality. Sixty-two patients who developed contrast-enhancing lesions were assessed by both ASL and DSC perfusion MRI and classified into groups of early tumor recurrence (n = 34) or pseudoprogression (n = 28) based on pathologic analysis or clinical-radiologic follow-up. We used a qualitative analysis and semi-quantitative grade system on the basis of the tumor perfusion signal intensity into those equal to white matter (grade I), gray matter (grade II), and blood vessels (grade III) on ASL imaging. ASL grade was correlated with histogram parameters derived from DSC perfusion MRI. Pseudoprogression was observed in 15 (53.6%) patients with ASL grade I, 13 (46.4%) with grade II, and 0 (0%) with grade III, with early tumor progression observed in seven (20.6%) patients with ASL grade I, 11 (32.3%) with grade II, and 16 (47.1%) with grade III (P = 0.0022). DSC perfusion histogram parameters differed significantly among ASL grades. ASL grade was an independent predictor differentiating pseudoprogression from early tumor progression (odds ratio, 4.73; P = 0.0017). On qualitative review, adjunctive ASL produced eight (12.9%) more accurate results than DSC perfusion MRI alone. ASL improves the diagnostic accuracy of DSC perfusion MRI in differentiating pseudoprogression from early tumor progression.

Dynamic susceptibility contrast perfusion MR imaging in distinguishing malignant from benign head and neck tumors: A pilot study

To preliminarily investigate the utility of dynamic susceptibility contrast perfusion MR imaging in distinguishing malignant from benign head and neck tumors. Seventy eight patients with head and neck masses underwent single shot dynamic susceptibility contrast T2*-weighted perfusion weighted MR imaging after bolus infusion of gadolinium-DTPA was administrated. The signal intensity time curve of the lesion was created. Dynamic susceptibility contrast percentage (DSC%) was calculated and correlated with pathological findings. The mean DSC% of malignant tumor (n=40) was 39.3±9.6% and of benign lesions (n=38) was 24.3±10.3%. There was a statistically significant difference of the DSC% between benign and malignant tumors (P=0.001) and within benign tumors (P=0.001). When DSC% of 30.7% was used as a threshold for differentiating malignant from benign tumors, the best results were obtained: accuracy of 84.6%, sensitivity of 80% and specificity of 89.2%. Dynamic susceptibility contrast perfusion weighted MR imaging is a non-invasive imaging technique that can play a role in differentiation between malignant and benign head and neck tumors.

Perfusion MR imaging for differentiation of benign and malignant meningiomas

IntroductionOur purpose was to determine whether perfusion MR imaging can be used to differentiate benign and malignant meningiomas on the basis of the differences in perfusion of tumor parenchyma and/or peritumoral edema.MethodsA total of 33 patients with preoperative meningiomas (25 benign and 8 malignant) underwent conventional and dynamic susceptibility contrast perfusion MR imaging. Maximal relative cerebral blood volume (rCBV) and the corresponding relative mean time to enhance (rMTE) (relative to the contralateral normal white matter) in both tumor parenchyma and peritumoral edema were measured. The independent samples t-test was used to determine whether there was a statistically significant difference in the mean rCBV and rMTE ratios between benign and malignant meningiomas.ResultsThe mean maximal rCBV values of benign and malignant meningiomas were 7.16±4.08 (mean±SD) and 5.89±3.86, respectively, in the parenchyma, and 1.05±0.96 and 3.82±1.39, respectively, in the peritumoral edema. The mean rMTE values were 1.16±0.24 and 1.30±0.32, respectively, in the parenchyma, and 0.91±0.25 and 1.24±0.35, respectively, in the peritumoral edema. The differences in rCBV and rMTE values between benign and malignant meningiomas were not statistically significant (P>0.05) in the parenchyma, but both were statistically significant (P<0.05) in the peritumoral edema.ConclusionPerfusion MR imaging can provide useful information on meningioma vascularity which is not available from conventional MRI. Measurement of maximal rCBV and corresponding rMTE values in the peritumoral edema is useful in the preoperative differentiation between benign and malignant meningiomas.

Pattern of hemodynamic impairment in multiple sclerosis: Dynamic susceptibility contrast perfusion MR imaging at 3.0 T

This study aimed to determine regional pattern of tissue perfusion in the normal-appearing white matter (NAWM) of patients with primary-progressive (PP), relapsing-remitting (RR) multiple sclerosis (MS) and healthy controls, and to investigate the association between perfusion abnormalities and clinical disability. Using dynamic susceptibility contrast (DSC) perfusion MRI at 3 T, we studied 22 patients with clinically definite MS, 11 with PP-MS and 11 with RR-MS and 11 age- and gender-matched healthy volunteers. The MRI protocol included axial dual-echo, dynamic susceptibility contrast enhanced (DSC) T2*-weighted and post-contrast T1-weighted images. Absolute cerebral blood flow (CBF), cerebral blood volume (CBV) and mean transit time (MTT) were measured in the periventricular, frontal, occipital NAWM and in the splenium of the corpus callosum. Compared to controls, CBF and CBV were significantly lower in all NAWM regions in both PP-MS patients (p values from <0.0001 to 0.001) and RR-MS (p values from <0.0001 to 0.020). Compared to RR-MS, PP-MS patients showed significantly lower CBF in the periventricular NAWM (p=0.002) and lower CBV in the periventricular and frontal NAWM (p values: 0.0029 and 0.022). EDSS was significantly correlated with the periventricular CBF (r=−0.48, p=0.0016) and with the periventricular and frontal CBV (r=−0.42, p=0.015; r=−0.35, p=0.038, respectively). This study suggests that the hemodynamic abnormalities of NAWM have clinical relevance in patients with MS. DSC perfusion MRI might provide a relevant objective measure of disease activity and treatment efficacy.

Feasibility of dynamic susceptibility contrast perfusion MR imaging at 3T using a standard quadrature head coil and eight‐channel phased‐array coil with and without SENSE reconstruction

To investigate changes in image and dynamic signal-to-noise ratios (SNRs) of the DeltaR2* curve, as well as magnetic susceptibility-induced artifacts between a standard quadrature head coil and an eight-channel phased-array coil with and without sensitivity-encoding (SENSE) at 3T, compared to the current clinical standard head coil acquisition at 1.5T. Dynamic susceptibility contrast (DSC) perfusion MRI was performed on 80 brain tumor patients using a gradient-echo, echo-planar imaging (EPI) sequence. Image and dynamic SNR were compared between 1.5T and 3T field strengths, a quadrature and eight-channel phased-array coil, and a conventional vs. partially parallel EPI acquisition with SENSE reconstruction. The amount of geometric distortion and signal dropout was quantified and compared between conventional and SENSE EPI acquisitions within the same exam at 3T. An initial 2.6-fold elevation in dynamic SNR was observed in normal-appearing white matter when doubling the field strength (P < 0.001), with an additional 1.7-fold increase found when employing an eight-channel phased-array coil (P < 0.002). Compared to the standard 3T eight-channel coil acquisition, the implementation of SENSE reduced the number of voxels experiencing large anterior shifts in the phase-encode direction, lowered the volume of signal dropout by 2.0-11.5%, and allowed a 1.4-fold increase in slice coverage, while only decreasing the dynamic SNR by 22%. SENSE EPI at 3T yielded a significant improvement in dynamic SNR over the 1.5T acquisitions. A significant reduction in magnetic susceptibility-induced artifacts was achieved with SENSE EPI compared to the standard EPI eight-channel coil acquisition at 3T.

Cerebral perfusion MR imaging using FAIR-HASTE in chronic carotid occlusive disease: comparison with dynamic susceptibility contrast-perfusion MR imaging.

To determine the efficacy of flow-sensitive alternating inversion recovery using half-Fourier single-shot turbo spin-echo (FAIR-HASTE) in detecting cerebral hypoperfusion in chronic carotid occlusive disease, we subjected 12 patients with various degrees of cervical internal carotid artery stenoses and/or occlusion (Stenosis group) and 24 volunteers (Normal group) to FAIR-HASTE. In addition, 10 out of 12 patients in the Stenosis group underwent dynamic susceptibility contrast-perfusion magnetic resonance imaging (DSC-pMRI) before and after revascularization in the dominantly affected side. The absolute asymmetry indexes (AIs) of both cerebral hemispheres in the Normal and Stenosis groups were compared in FAIR-HASTE. In addition, the AIs were compared with those in the Stenosis group before and after revascularization in both FAIR-HASTE and regional cerebral blood flow (rCBF), calculated with DSC-pMRI. A statistically significant difference was recognized between the AIs in the Normal and Stenosis groups (AI = 2.25 +- 1.92, 8.09 +- 4.60, respectively ; p < 0.0001). Furthermore, in the Stenosis group the AIs on both FAIR-HASTE (8.88 +- 4.93, 2.22 +- 1.79, respectively ; p = 0.0003) and rCBF (7.13 +- 3.57, 1.25 +- 1.33, respectively ; p = 0.0003) significantly decreased after revascularization. In the Stenosis group, before revascularization, signal intensity on both FAIR-HASTE and rCBF had a tendency to be lower in the dominantly affected side. FAIR-HASTE imaging was useful in the detection and evaluation of cerebral hypoperfusion in chronic occlusive carotid disease.