Ho Sung Kim

Percent change of perfusion skewness and kurtosis: a potential imaging biomarker for early treatment response in patients with newly diagnosed glioblastomas.

PURPOSE To test the predictive value of skewness and kurtosis changes of normalized cerebral blood volume (nCBV) during the early treatment period for differentiating early tumor progression from pseudoprogression in patients with newly diagnosed glioblastomas. MATERIALS AND METHODS The institutional review board approved this retrospective study. The authors assessed 135 patients with newly diagnosed glioblastomas who underwent concurrent chemotherapy and radiation therapy (CCRT) after surgical resection. Patients who developed new or enlarged contrast material-enhanced lesions after CCRT were assessed by means of conventional and perfusion magnetic resonance (MR) imaging. The percent change of skewness and kurtosis on nCBV histograms between the first and second post-CCRT follow-up were classified into four categories. Independent predictors of early tumor progression were determined by means of logistic regression analysis. RESULTS Of 135 patients, 79 had new or enlarged contrast-enhanced lesions after CCRT, subsequently classified as early tumor progression (n = 42, 53.2%) and pseudoprogression (n = 37, 46.8%). Pseudoprogression was observed in 23 of 24 (95.8%) patients in category 1, 10 of 15 (66.7%) in category 2, four of 20 (20.0%) in category 3, and 0 of 20 (0%) in category 4 (χ(2) test, P < .0001). The histographic pattern of nCBV was the best independent predictor (odds ratio, 3.51; P = .0032) for early tumor progression, rather than each percent change of skewness or kurtosis; the histographic pattern of nCBV represented the largest area under the receiver operating characteristic curve (0.934; 95% confidence interval: 0.855, 0.977), with a sensitivity of 85.7% and a specificity of 89.2%. CONCLUSION The percent change of skewness and kurtosis of nCBV may be a potential imaging biomarker for early treatment response in patients with newly diagnosed glioblastomas.

Alterations of mean diffusivity in brain white matter and deep gray matter in Parkinson's disease.

Although Parkinsons disease is a neurodegenerative disease primarily involving basal ganglia and midbrain, the deficit of white matter is also involved during the disease progression. As the diffusion tensor imaging method is sensitive to the microstructural changes, we investigated the microstructural alterations in white matter and deep gray matter in patients with Parkinsons disease. Brain images of 64 patients and sex- and age-matched 64 healthy controls were obtained from a 3T MRI scanner. Tract-based spatial statistics were used to compare the mean diffusivity of the white matter tract between the groups. Voxel-based analysis was used to compare the mean diffusivity of the subcortical gray matter between the groups. There were white matter deficits in the corticofugal tract, cingulum, uncinate fasciculus, crus of fornix or stria terminalis, corpus callosum, external capsule, superior longitudinal fasciculus, posterior thalamic radiation including optic radiation, and the tracts adjacent to the precuneus and supramarginal gyrus, as indicated by higher mean diffusivity in Parkinsons disease patients than in controls. There were also deficits in the left putamen, pallidum, thalamus, and caudate as indicated by higher mean diffusivity in Parkinsons disease patients than in controls. Using diffusion tensor imaging and multi-methods of image analysis, we successfully characterized and visualized brain white matter and deep gray matter areas with microstructural deficits in Parkinsons disease patients.

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

Background 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. Purpose 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). Material and Methods 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. Results 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. Conclusion ASL improves the diagnostic accuracy of DSC perfusion MRI in differentiating pseudoprogression from early tumor progression.

Multiple Cerebral Microbleeds in Hyperacute Ischemic Stroke: Impact on Prevalence and Severity of Early Hemorrhagic Transformation After Thrombolytic Treatment

OBJECTIVE The purpose of our study was to assess whether cerebral microbleeds are related to early hemorrhagic transformation after thrombolytic therapy for hyperacute ischemic stroke. MATERIALS AND METHODS The cases of 279 patients with suspected ischemic stroke who underwent MRI including T2*-weighted images were retrospectively evaluated. The inclusion criteria were as follows: imaging performed within 6 hr after symptom onset, presence of territorial infarct of anterior circulation, no history of intracerebral hemorrhage, thrombolytic treatment, and available follow-up MR images. Microbleeds were classified according to number as follows: absent (grade 1, 0 bleeds), mild (grade 2, 1-2 bleeds), moderate (grade 3, 3-10 bleeds), and severe (grade 4, > 10 bleeds). The prevalence and severity of early hemorrhagic transformation after thrombolysis were assessed on follow-up images. RESULTS Among 279 patients, 65 patients (37 men, 28 women; mean age, 67 years) met the inclusion criteria. Microbleeds were found in 25 patients. Early hemorrhagic transformation occurred in nine of 40 patients without microbleeds (grade 1) and in eight of 25 patients with microbleeds: two of 12 patients with grade 2, three of eight patients with grade 3, and three of five patients with grade 4 microbleeds. The presence of symptomatic hemorrhage did not correlate with the number of microbleeds. Results of multivariate logistic regression analysis showed that the presence of microbleeds was not associated with hemorrhagic transformation after thrombolytic treatment. CONCLUSION Small and large numbers of microbleeds are not independent risk factors for early hemorrhagic transformation and symptomatic hemorrhage after thrombolytic therapy for hyperacute ischemic stroke. Additional studies with large groups of subjects are needed to confirm our conclusion.

Recurrent Glioblastoma: Optimum Area under the Curve Method Derived from Dynamic Contrast-enhanced T1-weighted Perfusion MR Imaging

PURPOSE To determine whether the ratio of the initial area under the time-signal intensity curve (AUC) (IAUC) to the final AUC--or AUCR--derived from dynamic contrast material-enhanced magnetic resonance (MR) imaging can be an imaging biomarker for distinguishing recurrent glioblastoma multiforme (GBM) from radiation necrosis and to compare the diagnostic accuracy of the AUCR with commonly used model-free dynamic contrast-enhanced MR imaging parameters. MATERIALS AND METHODS The institutional review board approved this retrospective study and waived the informed consent requirement. Fifty-seven consecutive patients with pathologically confirmed recurrent GBM (n = 32) or radiation necrosis (n = 25) underwent dynamic contrast-enhanced MR imaging. Histogram parameters of the IAUC at 30, 60, and 120 seconds and the AUCR, which included the mean value at the higher curve of the bimodal histogram (mAUCR(H)), as well as 90th percentile cumulative histogram cutoffs, were calculated and were correlated with final pathologic findings. The best predictor for differentiating recurrent GBM from radiation necrosis was determined by means of receiver operating characteristic (ROC) curve analysis. RESULTS The demographic data were not significantly different between the two patient groups. There were statistically significant differences in all of the IAUC and AUCR parameters between the recurrent GBM and the radiation necrosis patient groups (P < .05 for each). ROC curve analyses showed mAUCR(H) to be the best single predictor of recurrent GBM (mAUCR(H) for recurrent GBM = 0.35 ± 0.11 [standard deviation], vs 0.19 ± 0.17 for radiation necrosis; P < .0001; optimum cutoff, 0.23), with a sensitivity of 93.8% and a specificity of 88.0%. CONCLUSION A bimodal histogram analysis of AUCR derived from dynamic contrast-enhanced MR imaging can be a potential noninvasive imaging biomarker for differentiating recurrent GBM from radiation necrosis. SUPPLEMENTAL MATERIAL http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.13130016/-/DC1.

Which Combination of MR Imaging Modalities Is Best for Predicting Recurrent Glioblastoma? Study of Diagnostic Accuracy and Reproducibility

PURPOSE To compare the added value of dynamic contrast material-enhanced ( CE contrast enhanced ) ( DCE dynamic CE ) magnetic resonance (MR) imaging with that of dynamic susceptibility CE contrast enhanced ( DSC dynamic susceptibility CE ) MR imaging with the combination of CE contrast enhanced T1-weighted imaging and diffusion-weighted ( DW diffusion weighted ) imaging for predicting recurrent glioblastoma. MATERIALS AND METHODS This retrospective study was approved by the institutional review board, with the requirement for informed patient consent waived. CE contrast enhanced T1-weighted images, DW diffusion weighted images, DSC dynamic susceptibility CE MR images, and DCE dynamic CE MR images in 169 patients with pathologically or clinicoradiologically diagnosed recurrent glioblastoma (n = 87) or radiation necrosis (n = 82) were retrospectively reviewed. Histogram cutoffs of quantitative parametric values were calculated from DW diffusion weighted images, DSC dynamic susceptibility CE MR images, and DCE dynamic CE MR images. Area under the receiver operating characteristic curve ( Az area under the ROC curve ) and interreader agreement were assessed. RESULTS For predicting recurrent glioblastoma, adding DCE dynamic CE MR imaging to the combination of CE contrast enhanced T1-weighted imaging and DW diffusion weighted imaging significantly improved Az area under the ROC curve from 0.84 to 0.96 for reader 1 and from 0.81 to 0.97 for reader 2, respectively. Adding DSC dynamic susceptibility CE MR imaging also significantly improved Az area under the ROC curve (0.95 for reader 1 and 0.93 for reader 2). However, there was no significant difference in Az between the combination of CE contrast enhanced T1-weighted imaging, DW diffusion weighted imaging, and DSC dynamic susceptibility CE MR imaging and the combination of CE contrast enhanced T1-weighted imaging, DW diffusion weighted imaging, and DCE dynamic CE MR imaging for both readers. The interreader agreement was highest for the combination of CE contrast enhanced T1-weighted imaging, DW diffusion weighted imaging, and DCE dynamic CE MR imaging (κ = 0.78) and lowest for CE contrast enhanced T1-weighted imaging and DW diffusion weighted imaging (κ = 0.65). CONCLUSION Adding perfusion MR imaging to the combination of CE contrast enhanced T1-weighted imaging and DW diffusion weighted imaging significantly improves the prediction of recurrent glioblastoma; however, selection of perfusion MR method does not affect the diagnostic performance.

Atypical Imaging Features of Primary Central Nervous System Lymphoma That Mimics Glioblastoma: Utility of Intravoxel Incoherent Motion MR Imaging

PURPOSE To determine the utility of intravoxel incoherent motion (IVIM)-derived perfusion and diffusion parameters for differentiation of atypical primary central nervous system lymphoma (PCNSL) from glioblastoma in patients who do not have acquired immunodeficiency syndrome. MATERIALS AND METHODS The institutional review board approved this retrospective study and waived the informed consent requirement. Sixty patients with either pathologic analysis-confirmed atypical PCNSLs (n = 19) or glioblastomas (n = 41) were assessed by using maximum IVIM-derived perfusion fraction (f) and minimum true IVIM diffusion parameter (D). Two readers independently calculated IVIM parameters and maximum normalized cerebral blood volume (nCBV) and minimum apparent diffusion coefficient. Leave-one-out cross-validation and intraclass correlation coefficients were assessed to determine reliability and reproducibility of the parameters, respectively. RESULTS Mean maximum f was significantly higher in the glioblastoma group than in the atypical PCNSL group (reader 1, 0.101 ± 0.016 [standard deviation] vs 0.021 ± 0.010; P < .001; reader 2: 0.107 ± 0.024 vs 0.027 ± 0.015; P < .001). Mean minimum D did not significantly differ between the two groups (reader 1, P = .202; reader 2, P = .091). By using maximum f as a discriminative index, respective sensitivity and specificity were 89.5% and 95.1% for reader 1 and 84.2% and 95.1% for reader 2. There was a significant positive correlation between maximum f and the corresponding nCBV (r = 0.68; P < .001). The intraclass correlation coefficient between readers was highest for measurement of maximum f (intraclass correlation coefficient, 0.92). CONCLUSION IVIM imaging can be used as a noninvasive imaging method to differentiate malignant brain tumors that show similar conventional MR imaging features.

The Fate of High-Density Lesions on the Non-contrast CT Obtained Immediately After Intra-arterial Thrombolysis in Ischemic Stroke Patients

Objective Hyperdense lesions can frequently be observed on the CT obtained immediately after intra-arterial (IA) thrombolysis, and it is sometimes difficult to differentiate contrast extravasation from the hemorrhagic lesions. The purposes of this study are to classify the hyperdense lesions according to their morphologic features and to track the outcome of those lesions. Materials and Methods Among the 94 patients who suffered with anterior circulation ischemic stroke and who were treated with IA thrombolysis, 31 patients revealed hyperdense lesions on the CT obtained immediately after the procedure. The lesions were categorized into four types according to their volume, shape, location and density: cortical high density (HD), soft HD, metallic HD and diffuse HD. The follow-up images were obtained 3-5 days later in order to visualize the morphologic changes and hemorrhagic transformation of the lesions. Results Among the 31 patients with HD lesions, 18 (58%) showed hemorrhagic transformation of their lesion, and six of them were significant. All the cortical HD lesions (n = 4) revealed spontaneous resolution. Seven of the soft HD lesions (n = 13) showed spontaneous resolution, while the rest of the group showed hemorrhagic transformation. Among them the hemorrhage was significant in only two patients (2/6) who did not achieve successful recanalization. All the metallic HD lesions (n = 10) resulted in hemorrhagic transformation; among them, three cases (30%) with a maximum CT value more than 150 HU (Hounsfield unit) subsequently showed significant hemorrhagic transformation on the follow-up CT. There were four diffuse HD lesions, and two of them showed hemorrhagic transformation. Conclusion The parenchymal hyperdense lesions observed on the CT obtained immediately after IA thrombolysis in ischemic stroke patients exhibited varying features and they were not always hemorrhagic. Most of the soft HD lesions were benign, and although all of the metallic HD lesions were hemorrhagic, some of them were ultimately found to be benign.

Cerebral Fat Embolism: Diffusion-weighted Magnetic Resonance Imaging Findings

Purpose: To demonstrate the diffusion-weighted (DWI) magnetic resonance imaging (MRI) findings, and the follow-up MRI findings, of cerebral fat embolism in the acute stage. Material and Methods: The initial DWI and clinical findings of six patients with cerebral fat embolism were retrospectively evaluated. The finding of DWI with a b-value of 1000 s/mm2 (b = 1000) was compared with that of DWI with a b-value of 0 s/mm2 (b = 0). In three patients who underwent follow-up MRI, the interval change of the lesion on T2-weighted images was investigated. Results: The characteristic DWI finding of cerebral fat embolism in the acute stage was multiple, hyperintense, dot-like lesions disseminated in the brain. These lesions were distributed dominantly in the bilateral border-zone areas. Some lesions had an ancillary location including the cortex, deep white matter, basal ganglia, and cerebellum. The lesions were more intense and numerous in DWI (b = 1000) than in DWI (b = 0). The findings on the follow-up T2-weighted images were multiple confluent hyperintense lesions in the white matter with progression since the initial MRI. Conclusion: DWI could be a sensitive tool for detecting cerebral fat embolism in the acute phase. It is recommended that DWI be included in the initial evaluation of cerebral fat embolism with MRI.

Pseudoprogression in Patients with Glioblastoma: Assessment by Using Volume-weighted Voxel-based Multiparametric Clustering of MR Imaging Data in an Independent Test Set

PURPOSE To validate a volume-weighted voxel-based multiparametric clustering (VVMC) method for magnetic resonance imaging data that is designed to differentiate between pseudoprogression and early tumor progression (ETP) in patients with glioblastoma in an independent test set. MATERIALS AND METHODS This retrospective study was approved by the local institutional review board, with waiver of the need to obtain informed consent. The study patients were grouped chronologically into a training set (108 patients) and a test set (54 patients). The reference standard was pathologic findings or subsequent clinical-radiologic study results. By using the optimal cutoff determined in the training set, the diagnostic performance of VVMC was subsequently tested in the test set and was compared with that of single-parameter measurements (apparent diffusion coefficient [ADC], normalized cerebral blood volume [nCBV], and initial area under the time-signal intensity curve). RESULTS Interreader agreement was highest for VVMC (intraclass correlation coefficient, 0.87-0.89). Receiver operating characteristic curve analysis revealed that VVMC performed the best as a classifier, although statistical significance was not demonstrated with respect to the nCBV in the training set. In the test set, the diagnostic accuracy of VVMC was higher than that of any single-parameter measurements, but this trend reached significance only for the ADC. When the entire population was considered, VVMC had significantly better diagnostic accuracy than did any single parameter (P = .003-.046 for reader 1; P = .002-.016 for reader 2). Results of fivefold cross validation confirmed the trends in both the training set and the test set. CONCLUSION VVMC is a superior and more reproducible imaging biomarker than single-parameter measurements for differentiating between pseudoprogression and ETP in patients with glioblastoma. Online supplemental material is available for this article.