Yoon Seong Choi

The Added Prognostic Value of Preoperative Dynamic Contrast-Enhanced MRI Histogram Analysis in Patients with Glioblastoma: Analysis of Overall and Progression-Free Survival

BACKGROUND AND PURPOSE: The prognostic value of dynamic contrast-enhanced MR imaging in patients with glioblastoma is controversial. We investigated the added prognostic value of dynamic contrast-enhanced MR imaging to clinical parameters and molecular biomarkers in patients with glioblastoma by using histogram analysis. MATERIALS AND METHODS: This retrospective study consisted of 61 patients who underwent preoperative dynamic contrast-enhanced MR imaging for glioblastoma. The histogram parameters of dynamic contrast-enhanced MR imaging, including volume transfer constant, extravascular extracellular volume fraction, and plasma volume fraction, were calculated from entire enhancing tumors. Univariate analyses for overall survival and progression-free survival were performed with preoperative clinical and dynamic contrast-enhanced MR imaging parameters and postoperative molecular biomarkers. Multivariate Cox regression was performed to build pre- and postoperative models for overall survival and progression-free survival. The performance of models was assessed by calculating the Harrell concordance index. RESULTS: In univariate analysis, patients with higher volume transfer constant and extravascular extracellular volume fraction values showed worse overall survival and progression-free survival, whereas plasma volume fraction showed no significant correlation. In multivariate analyses for overall survival, the fifth percentile value of volume transfer constant and kurtosis of extravascular extracellular volume fraction were independently prognostic in the preoperative model, and kurtosis of volume transfer constant and extravascular extracellular volume fraction were independently prognostic in the postoperative model. For progression-free survival, independent prognostic factors were minimum and fifth percentile values of volume transfer constant and kurtosis of extravascular extracellular volume fraction in the preoperative model and kurtosis of extravascular extracellular volume fraction in the postoperative model. The performance of preoperative models for progression-free survival was significantly improved when minimum or fifth percentile values of volume transfer constant and kurtosis of extravascular extracellular volume fraction were added. CONCLUSIONS: Higher volume transfer constant and extravascular extracellular volume fraction values are associated with worse prognosis, and dynamic contrast-enhanced MR imaging may have added prognostic value in combination with preoperative clinical parameters, especially in predicting progression-free survival.

Histological characteristics of small hepatocellular carcinomas showing atypical enhancement patterns on gadoxetic acid-enhanced MR imaging

To define the histological characteristics of hepatocellular carcinomas (HCCs) showing atypical dynamic enhancement patterns on gadoxetic acid‐enhanced dynamic magnetic resonance imaging (EOB‐MRI).

Amide proton transfer imaging to discriminate between low- and high-grade gliomas: added value to apparent diffusion coefficient and relative cerebral blood volume

AbstractObjectivesTo evaluate the added value of amide proton transfer (APT) imaging to the apparent diffusion coefficient (ADC) from diffusion tensor imaging (DTI) and the relative cerebral blood volume (rCBV) from perfusion magnetic resonance imaging (MRI) for discriminating between high- and low-grade gliomas.MethodsForty-six consecutive adult patients with diffuse gliomas who underwent preoperative APT imaging, DTI and perfusion MRI were enrolled. APT signals were compared according to the World Health Organization grade. The diagnostic ability and added value of the APT signal to the ADC and rCBV for discriminating between low- and high-grade gliomas were evaluated using receiver operating characteristic (ROC) analyses and integrated discrimination improvement.ResultsThe APT signal increased as the glioma grade increased. The discrimination abilities of the APT, ADC and rCBV values were not significantly different. Using both the APT signal and ADC significantly improved discrimination vs. the ADC alone (area under the ROC curve [AUC], 0.888 vs. 0.910; P = 0.007), whereas using both the APT signal and rCBV did not improve discrimination vs. the rCBV alone (AUC, 0.927 vs. 0.923; P = 0.222).ConclusionsAPT imaging may be a useful imaging biomarker that adds value to the ADC for discriminating between low- and high-grade gliomas.Key points• Higher APT values were correlated with higher glioma grades. • Adding the APT signal to the ADC improved glioma grading. • Adding the APT signal to rCBV did not improve glioma grading. • APT is a useful adjunct to the ADC for glioma grading.

Gadolinium deposition in the brain: association with various GBCAs using a generalized additive model

AbstractObjectivesTo determine the relationship between the number of administrations of various gadolinium-based contrast agents (GBCAs) and increased T1 signal intensity in the globus pallidus (GP) and dentate nucleus (DN).MethodsThis retrospective study included 122 patients who underwent double-dose GBCA-enhanced magnetic resonance imaging. Two radiologists calculated GP-to-thalamus (TH) signal intensity ratio, DN-to-pons signal intensity ratio and relative change (Rchange) between the baseline and final examinations. Interobserver agreement was evaluated. The relationships between Rchange and several factors, including number of each GBCA administrations, were analysed using a generalized additive model.ResultsSix patients (4.9%) received linear GBCAs (mean 20.8 number of administration; range 15–30), 44 patients (36.1%) received macrocyclic GBCAs (mean 26.1; range 14–51) and 72 patients (59.0%) received both types of GBCAs (mean 31.5; range 12–65). Interobserver agreement was almost perfect (0.99; 95% CI: 0.99–0.99). Rchange (DN:pons) was associated with gadodiamide (p = 0.006) and gadopentetate dimeglumine (p < 0.001), but not with other GBCAs. Rchange (GP:TH) was not associated with GBCA administration.ConclusionsPrevious administration of linear agents gadoiamide and gadopentetate dimeglumine is associated with increased T1 signal intensity in the DN, whereas macrocyclic GBCAs do not show an association.Key points• Certain linear GBCAs are associated with T1 signal change in the dentate nucleus. • The signal change is related to the administration number of certain linear GBCAs. • Difference in signal change may reflect differences in stability of agents.

Four-dimensional real-time cine images of wrist joint kinematics using dual source CT with minimal time increment scanning

Purpose To validate the feasibility of real time kinematography with four-dimensional (4D) dynamic functional wrist joint imaging using dual source CT. Materials and Methods Two healthy volunteers performed radioulnar deviation and pronation-supination wrist motions for 10 s and 4 s per cycle in a dual source CT scanner. Scan and reconstruction protocols were set to optimize temporal resolution. Cine images of the reconstructed carpal bone of the moving wrist were recorded. The quality of the images and radiation dosage were evaluated. Results The 4D cine images obtained during 4 s and 10 s of radioulnar motion showed a smooth stream of movement with good quality and little noise or artifact. Images from the pronation-supination motion showed noise with a masked surface contour. The temporal resolution was optimized at 0.28 s. Conclusion Using dual source CT, 4D cine images of in vivo kinematics of wrist joint movement were obtained and found to have a shorter scan time, improved temporal resolution and lower radiation dosages compared with those previously reported.

Incremental Prognostic Value of ADC Histogram Analysis over MGMT Promoter Methylation Status in Patients with Glioblastoma

Purpose To investigate the incremental prognostic value of apparent diffusion coefficient (ADC) histogram analysis over oxygen 6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status in patients with glioblastoma and the correlation between ADC parameters and MGMT status. Materials and Methods This retrospective study was approved by institutional review board, and informed consent was waived. A total of 112 patients with glioblastoma were divided into training (74 patients) and test (38 patients) sets. Overall survival (OS) and progression-free survival (PFS) was analyzed with ADC parameters, MGMT status, and other clinical factors. Multivariate Cox regression models with and without ADC parameters were constructed. Model performance was assessed with c index and receiver operating characteristic curve analyses for 12- and 16-month OS and 12-month PFS in the training set and validated in the test set. ADC parameters were compared according to MGMT status for the entire cohort. Results By using ADC parameters, the c indices and diagnostic accuracies for 12- and 16-month OS and 12-month PFS in the models showed significant improvement, with the exception of c indices in the models for PFS (P < .05 for all) in the training set. In the test set, the diagnostic accuracy was improved by using ADC parameters and was significant, with the 25th and 50th percentiles of ADC for 16-month OS (P = .040 and P = .047) and the 25th percentile of ADC for 12-month PFS (P = .026). No significant correlation was found between ADC parameters and MGMT status. Conclusion ADC histogram analysis had incremental prognostic value over MGMT promoter methylation status in patients with glioblastoma. (©) RSNA, 2016 Online supplemental material is available for this article.

Application of Dynamic Contrast-Enhanced MRI Parameters for Differentiating Squamous Cell Carcinoma and Malignant Lymphoma of the Oropharynx

OBJECTIVE The purpose of this study was to investigate the usefulness of histogram analysis of dynamic contrast-enhanced MRI (DCE-MRI) parameters for the differentiation of squamous cell carcinoma (SCC) and malignant lymphoma of the oropharynx. MATERIALS AND METHODS Pretreatment DCE-MRI was performed in 21 patients with pathologically confirmed oropharyngeal SCC and six patients with malignant lymphoma. DCE-MRI parameter maps including the volume transfer constant (K(trans)), flux rate constant (kep), and extravascular extracellular volume fraction (ve) based on the Tofts model were obtained. Enhancing tumors were manually segmented on each slice of the parameter maps, and the data were collected to obtain a histogram for the entire tumor volume. The Wilcoxon rank sum test was used to compare the histogram parameters of each DCE-MRI-derived variable of oropharyngeal SCC and lymphoma. RESULTS Histogram analysis of K(trans) and ve maps revealed that the median and mode of K(trans) were significantly higher in SCC than in lymphoma (p = 0.039 and 0.032, respectively), and the mode, skewness, and kurtosis of ve were significantly different in SCC than in lymphoma (p = 0.046, 0.039, and 0.032, respectively). On ROC analysis, the kurtosis of ve had the best discriminative value for distinguishing between oropharyngeal SCC and lymphoma (AUC, 0.865; cutoff value, 2.60; sensitivity, 83.3%; specificity, 90.5%). CONCLUSION Our preliminary evidence using histogram analysis of DCE-MRI parameters based on the whole tumor volume suggests that it might be useful for differentiating SCC from malignant lymphoma of the oropharynx.

Retinal vessel structure measurement using spectral-domain optical coherence tomography.

PurposeTo assess the reliability and validity of spectral-domain optical coherence tomography (SD-OCT) measurements of retinal vessel lumen diameters and wall thicknesses.MethodsSD-OCT was used to characterize the circular region around the optic disc of 40 eyes (20 subjects). The inner and outer sides (vitreal and choroidal sides) of the vessel wall and the luminal diameter were measured using intensity graphs.ResultsMean arterial and venous luminal diameters were 95.1±16.1 and 132.6±17.8 μm, respectively. The wall thicknesses of inner and outer sides of the artery were 23.9±4.9 and 21.2±3.5 μm, respectively. The wall thicknesses of the inner and outer sides of the vein were 20.7±4.2 and 16.3±4.3 μm, respectively. There were significant differences between the inner and outer wall thicknesses in both the artery and vein (P<0.01). Intra- and interobserver intraclass correlation coefficients (ICCs) for lumen measurements were >0.95, and for wall thicknesses were >0.85, except for the outer wall thickness measurements. The mean value of outer and inner wall thicknesses showed good reproducibility, with ICCs of >0.85.ConclusionIntensity graph-assisted measurements using SD-OCT provided more objective information in finding boundaries of vessels. Luminal diameters and wall thicknesses obtained with OCT showed good overall reproducibility, with inner wall thicknesses being thicker, and with better reproducibility compared with outer wall thicknesses, where ICC values were the lowest among the inner wall thicknesses, mean thicknesses of inner and outer walls, and luminal diameters. When using SD-OCT measurements, caution is therefore advised when using only the outer wall as representative of the wall thicknesses.

The Initial Area Under the Curve Derived from Dynamic Contrast-Enhanced MRI Improves Prognosis Prediction in Glioblastoma with Unmethylated MGMT Promoter

BACKGROUND AND PURPOSE: Although perfusion and permeability MR parameters have known to have prognostic value, they have reproducibility issues. Our aim was to evaluate whether the initial area under the time-to-signal intensity curve (IAUC) derived from dynamic contrast-enhanced MR imaging can improve prognosis prediction in patients with glioblastoma with known MGMT status. MATERIALS AND METHODS: We retrospectively examined 88 patients with glioblastoma who underwent preoperative dynamic contrast-enhanced MR imaging. The means of IAUC values at 30 and 60 seconds (IAUC30mean and IAUC60mean) were extracted from enhancing tumors. The prognostic values of IAUC parameters for overall survival and progression-free survival were assessed with log-rank tests, according to the MGMT status. Multivariate overall survival and progression-free survival models before and after adding the IAUC parameters as covariates were explored by net reclassification improvement after receiver operating characteristic analysis for 1.5-year overall survival and 1-year progression-free survival and by random survival forest. RESULTS: High IAUC parameters were associated with worse overall survival and progression-free survival in the unmethylated MGMT group, but not in the methylated group. In the unmethylated MGMT group, 1.5-year overall survival and 1-year progression-free survival prediction improved significantly after adding IAUC parameters (overall survival area under the receiver operating characteristic curve, 0.86; progression-free survival area under the receiver operating characteristic curve, 0.74–0.76) to the model with other prognostic factors (overall survival area under the receiver operating characteristic curve, 0.81; progression-free survival area under the receiver operating characteristic curve, 0.69; P < .05 for all) except in the case of IAUC60mean for 1-year progression-free survival prediction (P = .059). Random survival forest models indicated that the IAUC parameters were the second or most important predictors in the unmethylated MGMT group, except in the case of the IAUC60mean for progression-free survival. CONCLUSIONS: IAUC can be a useful prognostic imaging biomarker in patients with glioblastoma with known MGMT status, improving prediction of glioblastoma prognosis with the unmethylated MGMT promoter status.

Primary central nervous system lymphoma and atypical glioblastoma: Differentiation using radiomics approach

ObjectivesTo evaluate the diagnostic performance of magnetic resonance (MR) radiomics-based machine-learning algorithms in differentiating primary central nervous system lymphoma (PCNSL) from non-necrotic atypical glioblastoma (GBM).MethodsSeventy-seven patients (54 individuals with PCNSL and 23 with non-necrotic atypical GBM), diagnosed from January 2009 to April 2017, were enrolled in this retrospective study. A total of 6,366 radiomics features, including shape, volume, first-order, texture, and wavelet-transformed features, were extracted from multi-parametric (post-contrast T1- and T2-weighted, and fluid attenuation inversion recovery images) and multiregional (enhanced and non-enhanced) tumour volumes. These features were subjected to recursive feature elimination and random forest (RF) analysis with nested cross-validation. The diagnostic abilities of a radiomics machine-learning classifier, apparent diffusion coefficient (ADC), and three readers, who independently classified the tumours based on conventional MR sequences, were evaluated using receiver operating characteristic (ROC) analysis. Areas under the ROC curves (AUC) of the radiomics classifier, ADC value, and the radiologists were compared.ResultsThe mean AUC of the radiomics classifier was 0.921 (95 % CI 0.825–0.990). The AUCs of the three readers and ADC were 0.707 (95 % CI 0.622–0.793), 0.759 (95 %CI 0.656–0.861), 0.695 (95 % CI 0.590–0.800) and 0.684 (95 % CI0.560–0.809), respectively. The AUC of the radiomics-based classifier was significantly higher than those of the three readers and ADC (p< 0.001 for all).ConclusionsLarge-scale radiomics with a machine-learning algorithm can be useful for differentiating PCNSL from atypical GBM, and yields a better diagnostic performance than human radiologists and ADC values.Key Points• Machine-learning algorithm radiomics can help to differentiate primary central PCNSL from GBM.• This approach yields a higher diagnostic accuracy than visual analysis by radiologists.• Radiomics can strengthen radiologists’ diagnostic decisions whenever conventional MRI sequences are available.