Oscillating Gradient Diffusion-Weighted MRI for Risk Stratification of Uterine Endometrial Cancer.

BACKGROUND: Oscillating gradient diffusion-weighted imaging (DWI) enables elucidation of microstructural characteristics in cancers; however, there are limited data to evaluate its utility in patients with endometrial cancer. PURPOSE: To investigate the utility of oscillating gradient DWI for risk stratification in patients with uterine endometrial cancer compared with conventional pulsed gradient DWI. STUDY TYPE: Retrospective. SUBJECTS: Sixty-three women (mean age: 58 [range: 32-85] years) with endometrial cancer. FIELD STRENGTH/SEQUENCE: 3 T MRI including DWI using oscillating gradient spin-echo (OGSE) and pulsed gradient spin-echo (PGSE) research sequences. ASSESSMENT: Mean value of the apparent diffusion coefficient (ADC) values for OGSE (ADCOGSE ) and PGSE (ADCPGSE ) as well as the ADC ratio (ADCOGSE /ADCPGSE ) within endometrial cancer were measured using regions of interest. Prognostic factors (histological grade, deep myometrial invasion, lymphovascular invasion, International Federation of Gynecology and Obstetrics [FIGO] stage, and prognostic risk classification) were tabulated. STATISTICAL TESTS: Interobserver agreement was analyzed by calculating the intraclass correlation coefficient. The associations of ADCOGSE , ADCPGSE , and ADCOGSE /ADCPGSE with prognostic factors were examined using the Kendall rank correlation coefficient, Mann-Whitney U test, and receiver operating characteristic (ROC) curve. A P value of <0.05 was statistically significant. RESULTS: Compared with ADCOGSE and ADCPGSE , ADCOGSE /ADCPGSE was significantly and strongly correlated with histological grade (observer 1, τ = 0.563; observer 2, τ = 0.456), FIGO stage (observer 1, τ = 0.354; observer 2, τ = 0.324), and prognostic risk classification (observer 1, τ = 0.456; observer 2, τ = 0.385). The area under the ROC curves of ADCOGSE /ADCPGSE for histological grade (observer 1, 0.92, 95% confidence intervals [CIs]: 0.83-0.98; observer 2, 0.84, 95% CI: 0.73-0.92) and prognostic risk (observer 1, 0.80, 95% CI: 0.68-0.89; observer 2, 0.76, 95% CI: 0.63-0.86) were significantly higher than that of ADCOGSE and ADCPGSE . DATA CONCLUSION: The ADC ratio obtained via oscillating gradient and pulsed gradient DWIs might be useful imaging biomarkers for risk stratification in patients with endometrial cancer. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Adding Delayed Phase Images to Dual-Phase Contrast-Enhanced CT Increases Sensitivity for Small Pancreatic Ductal Adenocarcinoma.

BACKGROUND. Contrast-enhanced CT performed for pancreatic ductal adeno-carcinoma (PDAC) detection traditionally uses a dual-phase (pancreatic and portal venous) protocol. However, PDAC may exhibit isoattenuation in these phases, hindering detection. OBJECTIVE. The purpose of this study was to assess the impact on diagnostic performance in detection of small PDAC when a delayed phase is added to dual-phase contrast-enhanced CT. METHODS. A database of 571 patients who underwent triple-phase (pancreatic, portal venous, and delayed) contrast-enhanced MDCT between January 2017 and March 2020 for suspected pancreatic tumor was retrospectively reviewed. A total of 97 patients had pathologically confirmed small PDAC (mean size, 22 mm; range, 7-30 mm). Twenty control patients had no pancreatic tumor suspected on CT, on initial MRI and follow-up CT, or on MRI after 12 months or longer. Three radiologists independently reviewed dual-phase and triple-phase images. Two additional radiologists assessed tumors' visual attenuation on each phase, reaching consensus for differences. Performance of dual- and triple-phase images were compared using ROC analysis, McNemar test, and Fisher exact test. RESULTS. AUC was higher (p < .05) for triple-phase than dual-phase images for all observers (observer 1, 0.97 vs 0.94; observer 2, 0.97 vs 0.94; observer 3, 0.97 vs 0.95). Sensitivity was higher (p < .001) for triple-phase than dual-phase images for all observers (observer 1, 74.2% [72/97] vs 59.8% [58/97]; observer 2, 88.7% [86/97] vs 71.1% [69/97]; observer 3, 86.6% [84/97] vs 72.2% [70/97]). Specificity, PPV, and NPV did not differ between image sets for any reader (p ≥ .05). Seventeen tumors showed pancreatic phase visual isoattenuation, of which nine showed isoattenuation and eight hyperattenuation in the delayed phase. Of these 17 tumors, 16 were not detected by any observer on dual-phase images; of these 16, six were detected by at least two observers and five by at least one observer on triple-phase images. Visual attenuation showed excellent interob-server agreement (κ = 0.89-0.96). CONCLUSION. Addition of a delayed phase to pancreatic and portal venous phase CT increases sensitivity for small PDAC without loss of specificity, partly related to delayed phase hyperattenuation of some small PDACs showing pancreatic phase isoattenuation. CLINICAL IMPACT. Addition of a delayed phase may facilitate earlier PDAC detection and thus improved prognosis.

Visual enhancement pattern during the delayed phase of enhanced CT as an independent prognostic factor in stage IV pancreatic ductal adenocarcinoma.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) has substantial heterogeneity in biophysical features and in outcomes of patients. Identifying reliable pretreatment imaging biomarkers for PDAC with distant metastases (stage IV) is a key imperative. Our objective was to determine whether visual tumor enhancement pattern on enhanced computed tomography (CT) can be used as a prognostic factor in stage IV PDAC treated with chemotherapy. METHODS: This is a retrospective cohort study of 133 patients with stage IV PDAC who underwent multiphasic enhanced CT before systemic chemotherapy. The enhancement pattern of PDAC was qualitatively categorized as hypoattenuation, isoattenuation, or hyperattenuation on each of the pancreatic, portal venous, and delayed phases. The effects of clinical prognostic factors and the visual tumor enhancement pattern on progression-free survival (PFS) and overall survival (OS) were assessed in univariate and multivariate analyses using Cox proportional hazards models. RESULTS: On univariate analysis, the number of metastatic organs and the visual tumor enhancement pattern during the delayed phase were significantly associated with PFS (p = 0.003 and < 0.001, respectively) and OS (p = 0.005 and < 0.001, respectively). Multivariate analysis identified the number of metastatic organs (PFS, p = 0.021; OS, p = 0.041) and visual tumor enhancement pattern during the delayed phase (PFS, p < 0.001; OS, p < 0.001) as independent predictors of PFS and OS. CONCLUSION: Visual enhancement pattern of PDAC on delayed phase enhanced CT appears to be associated with outcomes and could be a useful prognostic factor in stage IV PDAC, despite the need to add the delayed phase to CT protocol for pancreatic disease.

Assessment of microvessel perfusion of pituitary adenomas: a feasibility study using turbo spin-echo-based intravoxel incoherent motion imaging.

OBJECTIVES: To evaluate the feasibility of assessment of microvessel perfusion of pituitary adenomas with intravoxel incoherent motion (IVIM) imaging using single-shot turbo spin-echo-based diffusion-weighted imaging (SS-TSE-DWI). METHODS: We examined 51 consecutive patients with pituitary adenomas (35 non-functioning and 16 functioning) and 32 patients with normal pituitary glands using SS-TSE-DWI IVIM. The diffusion coefficient (D), the perfusion fraction (f), and the pseudo-diffusion coefficient (D*) were calculated pixel-by-pixel for each adenoma and normal pituitary gland. We also obtained the pathological microvessel area (MVA) of each adenoma. The IVIM parameters in adenomas were compared with those in normal pituitary glands using the Mann-Whitney U test. The correlation between the MVA and IVIM f of adenomas was analyzed using Spearman's rank correlation coefficient. RESULTS: The mean D (× 10-3 mm2/s) in adenomas was 0.723 ± 0.253, which was significantly lower than that in normal pituitary glands (0.862 ± 0.128; p < 0.0001). The mean f (%) in adenomas was 10.74 ± 4.51, which was significantly lower than that in normal pituitary glands (13.26 ± 4.32, p = 0.0251). No significant difference was found in the mean D*. We found a significant positive correlation between MVA and f in non-functioning adenomas (ρ = 0.634, p < 0.0001) as well as in all adenomas (ρ = 0.451, p = 0.0009). CONCLUSIONS: Assessment of microvessel perfusion of pituitary adenomas based on SS-TSE-DWI IVIM is feasible. Compared to normal pituitary glands, pituitary adenomas were characterized by lower D and f. KEY POINTS: • Assessment of microvessel perfusion of pituitary adenomas based on SS-TSE-IVIM is feasible. • SS-TSE-IVIM helps with evaluation of the vascularity of pituitary lesions. • Pituitary adenomas were characterized by lower D and f than normal pituitary glands.

Extracellular volume fraction determined by equilibrium contrast-enhanced multidetector computed tomography as a prognostic factor in unresectable pancreatic adenocarcinoma treated with chemotherapy.

OBJECTIVES: To assess whether extracellular volume (ECV) fraction with equilibrium contrast-enhanced multidetector computed tomography (MDCT) predicts outcomes for unresectable pancreatic adenocarcinoma patients treated with chemotherapy METHODS: Sixty-seven patients (42 men, 25 women; mean age, 67.5 years; range, 45-83 years) with histologically confirmed surgically unresectable pancreatic adenocarcinoma underwent contrast-enhanced MDCT before systemic chemotherapy. Tumour contrast enhancement (CE) and ECV fraction were calculated using region-of-interest measurement within the pancreatic adenocarcinoma and aorta on unenhanced and equilibrium phase-enhanced CT. The effect on survival variables including age, sex, tumour location, tumour size, TNM stage, carbohydrate antigen (CA) 19-9, carcinoembryonic antigen (CEA), tumour CE and tumour ECV fraction was determined on univariate and multivariate analyses using Cox proportional hazards regression model. RESULTS: Median overall survival was 10.5 months. On univariate analysis, elevated serum CA19-9 (hazard ratio (HR), 1.00; p = 0.006) and CEA (HR, 1.02; p = 0.011) levels were found to be associated with a negative effect on overall survival. Increasing tumour CE (HR, 0.98; p < 0.001) and ECV fraction (HR, 0.97; p = 0.001) were associated with a positive effect. Multivariate analysis revealed that only tumour ECV fraction was an independent predictor of overall survival (HR, 0.97; p = 0.012). CONCLUSIONS: ECV fraction with equilibrium contrast-enhanced MDCT could be a useful imaging biomarker for predicting patient survival after chemotherapy for unresectable pancreatic adenocarcinoma. KEY POINTS: • Tumour aggressiveness and response to therapy are influenced by the extravascular extracellular space. • Extracellular volume (ECV) fraction can be quantified with equilibrium contrast-enhanced CT. • Patients with higher tumour ECV fraction had better prognosis after chemotherapy.

Histogram analysis of amide proton transfer-weighted imaging: comparison of glioblastoma and solitary brain metastasis in enhancing tumors and peritumoral regions.

OBJECTIVES: Differentiation of glioblastomas (GBMs) and solitary brain metastases (SBMs) is an important clinical problem. The aim of this study was to determine whether amide proton transfer-weighted (APTW) imaging is useful for distinguishing GBMs from SBMs. METHODS: We examined 31 patients with GBM and 17 with SBM. For each tumor, enhancing areas (EAs) and surrounding non-enhancing areas with T2-prolongation (peritumoral high signal intensity areas, PHAs) were manually segmented using fusion images of the post-contrast T1-weighted and T2-weighted images. The mean amide proton transfer signal intensities (APTSIs) were compared among the EAs, PHAs, and contralateral normal appearing white matter (NAWM) within each tumor type. Furthermore, we analyzed APTSI histograms to compare the EAs and PHAs of GBMs and SBMs. RESULTS: In GBMs, the mean APTSI in EAs (2.92 ± 0.74%) was the highest, followed by that in PHAs (1.64 ± 0.83%, p < 0.001) and NAWM (0.43 ± 0.83%, p < 0.001). In SBMs, the mean APTSI in EAs (1.85 ± 0.99%) and PHAs (1.42 ± 0.45%) were significantly higher than that in NAWM (0.42 ± 0.30%, p < 0.001), whereas no significant difference was found between EAs and PHAs. The mean and 10th, 25th, 50th, 75th, and 90th percentiles for APT in EAs of GBMs were significantly higher than those of SBMs. However, no significant difference was found between GBMs and SBMs in any histogram parameters for PHA. CONCLUSIONS: APTSI in EAs, but not PHAs, is useful for differentiation between GBMs and SBMs. KEY POINTS: • Amide proton transfer-weighted imaging and histogram analysis in the enhancing tumor can provide useful information for differentiation between glioblastomas and solitary brain metastasis. • Amide proton transfer signal intensity histogram parameters from peritumoral areas showed no significant difference between glioblastomas and solitary brain metastasis. • Vasogenic edema alone can substantially increase amide proton transfer signal intensity which may mimic tumor invasion.

Whole-tumor apparent diffusion coefficient (ADC) histogram analysis to differentiate benign peripheral neurogenic tumors from soft tissue sarcomas.

BACKGROUND: Apparent diffusion coefficient (ADC) histogram analyses have been used to differentiate tumor grades and predict therapeutic responses in various anatomic sites with moderate success. PURPOSE: To determine the ability of diffusion-weighted imaging (DWI) with a whole-tumor ADC histogram analysis to differentiate benign peripheral neurogenic tumors (BPNTs) from soft tissue sarcomas (STSs). STUDY TYPE: Retrospective study, single institution. SUBJECTS: In all, 25 BPNTs and 31 STSs. FIELD STRENGTH/SEQUENCE: Two-b value DWI (b-values = 0, 1000s/mm2 ) was at 3.0T. ASSESSMENT: The histogram parameters of whole-tumor for ADC were calculated by two radiologists and compared between BPNTs and STSs. STATISTICAL TESTS: Nonparametric tests were performed for comparisons between BPNTs and STSs. P < 0.05 was considered statistically significant. The ability of each parameter to differentiate STSs from BPNTs was evaluated using area under the curve (AUC) values derived from a receiver operating characteristic curve analysis. RESULTS: The mean ADC and all percentile parameters were significantly lower in STSs than in BPNTs (P < 0.001-0.009), with AUCs of 0.703-0.773. However, the coefficient of variation (P = 0.020 and AUC = 0.682) and skewness (P = 0.012 and AUC = 0.697) were significantly higher in STSs than in BPNTs. Kurtosis (P = 0.295) and entropy (P = 0.604) did not differ significantly between BPNTs and STSs. DATA CONCLUSION: Whole-tumor ADC histogram parameters except kurtosis and entropy differed significantly between BPNTs and STSs. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

Diagnostic performances of FDG-PET/CT and diffusion-weighted imaging indices for differentiating benign pheochromocytoma from other benign adrenal tumors.

PURPOSE: The purpose of this study is to compare diagnostic performances of (18)F-fluorodeoxyglucose (FDG) visual score, maximum standardized uptake value (SUVmax), ratio of adrenal SUVmax to liver SUVmax (A/L SUVmax), apparent diffusion coefficient (ADC) from diffusion-weighted imaging, and SUVmax/ADC ratio to differentiate adrenal pheochromocytoma from other benign tumors. METHODS: Eleven pheochromocytomas and 22 other benign tumors in 30 patients were included. FDG-based indices, ADC, and SUVmax/ADC ratio were compared between groups using the Mann-Whitney U test, and sensitivity, specificity, accuracy, and area under the curve (AUC) for diagnosing pheochromocytoma by receiver operating characteristic analyses. The correlation between SUVmax and ADC was analyzed using the Spearman's rank test. RESULTS: Pheochromocytoma showed significantly higher visual score (2.8 ± 0.4 vs. 1.3 ± 0.9), SUVmax (11.0 ± 8.9 vs. 3.2 ± 1.4), A/L SUVmax ratio (3.96 ± 3.48 vs. 0.96 ± 0.51), and SUVmax/ADC ratio (10.6 ± 8.09 vs. 2.28 ± 0.98) (each P < 0.001) and significantly lower ADC (1.08 ± 0.23 × 10(-3) mm(2)/s vs. 1.43 ± 0.29 × 10(-3) mm(2)/s, P = 0.003) than other benign tumors. Sensitivity, specificity, and accuracy for diagnosing pheochromocytoma were 100, 73, and 82% for visual score, 100, 86, and 91% for both SUVmax and A/L SUVmax ratio, and 64, 100, and 88% for ADC and 82, 95, and 91% for SUVmax/ADC ratio. No significant differences in AUC were found between FDG-based indices, ADC, and SUVmax/ADC ratio. A significant negative correlation was noted between SUVmax and ADC (ρ = -0.36, P = 0.039). CONCLUSION: FDG-based indices and ADC appear comparably useful for differentiating pheochromocytoma from other benign adrenal tumors.

Quantitative evaluation of liver function with T1 relaxation time index on Gd-EOB-DTPA-enhanced MRI: comparison with signal intensity-based indices.

PURPOSE: To evaluate whether the reduction rate of T1 relaxation time of the liver (T1 relaxation time index) before and 20 minutes after gadolinium-ethoxybenzyl-diethylenetriaminepentaacetic acid (Gd-EOB-DTPA) injection has the potential to serve as an magnetic resonance imaging (MRI)-based liver function test in comparison with signal intensity-based indices. MATERIALS AND METHODS: Ninety-nine patients with suspected liver lesions underwent Gd-EOB-DTPA-enhanced MRI. T1 maps using 3D T1-weighted gradient-echo volumetric interpolated examination with two different flip angles were also performed before and 20 minutes after Gd-EOB-DTPA administration. T1 relaxation time index was compared with four signal intensity-based indices in terms of the ability to discriminate Child-Pugh A (CPA) and Child-Pugh B (CPB) from normal liver function (NLF), and in terms of its correlation with indocyanine green (ICG) clearance. RESULTS: Twenty-four patients were classified as NLF, 64 patients were classified as CPA, and 11 were classified as CPB group. The T1 relaxation time index was significantly lower for CPA (0.62 ± 0.08 vs. 0.68 ± 0.07, P = 0.021) and CPB (0.55 ± 0.15 vs. 0.68 ± 0.07, P < 0.001) than for NLF. All signal intensity-based indices showed significant differences only when comparing NLF and CPB. The correlation coefficient with ICG clearance was the highest for T1 relaxation time index (r = -0.605, P < 0.001). CONCLUSION: The T1 relaxation time index has the potential to serve as an MRI-based liver function test, and is most strongly correlated with ICG clearance among the Gd-EOB-DTPA MRI-based indices investigated.

Efficacy of liver parenchymal enhancement and liver volume to standard liver volume ratio on Gd-EOB-DTPA-enhanced MRI for estimation of liver function.

OBJECTIVE: We aimed to develop and assess the efficacy of a liver function index that combines liver enhancement and liver volume to standard liver volume (LV/SLV) ratio on gadolinium ethoxybenzyl diethylenetriaminepentaacetic acid (Gd-EOB-DTPA)-enhanced MRI. METHODS: In all, 111 patients underwent a Gd-EOB-DTPA-enhanced MRI, including T1 mapping, before and 20 min after Gd-EOB-DTPA administration. We calculated the following Gd-EOB-DTPA-enhanced MRI-based liver function indices: relative enhancement of the liver, corrected enhancement of the liver-to-spleen ratio, LSC_N20, increase rate of the liver-to-muscle ratio, reduction rate of T1 relaxation time of the liver, ΔR1 of the liver and K Hep; the indices were multiplied by the LV/SLV ratio. We calculated the correlations between an indocyanine green (ICG) clearance and the Gd-EOB-DTPA-enhanced MRI-based liver function indices multiplied by the LV/SLV ratio, by using Pearson correlation analysis. RESULTS: There were significant correlations between all Gd-EOB-DTPA-enhanced MRI-based liver function indices and ICG clearance (r = -0.354 to -0.574, P < 0.001). All Gd-EOB-DTPA-enhanced MRI-based liver function indices multiplied by the LV/SLV ratio (r = -0.394 to -0.700, P < 0.001) were more strongly correlated with the ICG clearance than those without multiplication by the LV/SLV ratio. CONCLUSIONS: Gd-EOB-DTPA-enhanced MRI-based liver function indices that combine liver enhancement and the LV/SLV ratio may more reliably estimate liver function. KEY POINTS: • Gd-EOB-DTPA-enhanced MRI is useful for assessing liver function. • Liver enhancement on Gd-EOB-DTPA-enhanced MRI correlates with indocyanine green (ICG) clearance. • Liver volume to standard liver volume (LV/SLV) ratio correlates with ICG clearance. • Liver enhancement and LV/SLV ratio help to estimate liver function.

Machine learning approach using 18F-FDG-PET-radiomic features and the visibility of right ventricle 18F-FDG uptake for predicting clinical events in patients with cardiac sarcoidosis.

OBJECTIVES: To investigate the usefulness of machine learning (ML) models using pretreatment 18F-FDG-PET-based radiomic features for predicting adverse clinical events (ACEs) in patients with cardiac sarcoidosis (CS). MATERIALS AND METHODS: This retrospective study included 47 patients with CS who underwent 18F-FDG-PET/CT scan before treatment. The lesions were assigned to the training (n = 38) and testing (n = 9) cohorts. In total, 49 18F-FDG-PET-based radiomic features and the visibility of right ventricle 18F-FDG uptake were used to predict ACEs using seven different ML algorithms (namely, decision tree, random forest [RF], neural network, k-nearest neighbors, Naïve Bayes, logistic regression, and support vector machine [SVM]) with tenfold cross-validation and the synthetic minority over-sampling technique. The ML models were constructed using the top four features ranked by the decrease in Gini impurity. The AUCs and accuracies were used to compare predictive performances. RESULTS: Patients who developed ACEs presented with a significantly higher surface area and gray level run length matrix run length non-uniformity (GLRLM_RLNU), and lower neighborhood gray-tone difference matrix_coarseness and sphericity than those without ACEs (each, p < 0.05). In the training cohort, all seven ML algorithms had a good classification performance with AUC values of > 0.80 (range: 0.841-0.944). In the testing cohort, the RF algorithm had the highest AUC and accuracy (88.9% [8/9]) with a similar classification performance between training and testing cohorts (AUC: 0.945 vs 0.889). GLRLM_RLNU was the most important feature of the modeling process of this RF algorithm. CONCLUSION: ML analyses using 18F-FDG-PET-based radiomic features may be useful for predicting ACEs in patients with CS.

Multiparametric approach with synthetic MR imaging for diagnosing salivary gland lesions.

PURPOSE: To determine whether synthetic MR imaging can distinguish between benign and malignant salivary gland lesions. METHODS: The study population included 44 patients with 33 benign and 11 malignant salivary gland lesions. All MR imaging was obtained using a 3 Tesla system. The QRAPMASTER pulse sequence was used to acquire images with four TI values and two TE values, from which quantitative images of T1 and T2 relaxation times and proton density (PD) were generated. The Mann-Whitney U test was used to compare T1, T2, PD, and ADC values among the subtypes of salivary gland lesions. ROC analysis was used to evaluate diagnostic capability between malignant tumors (MTs) and either pleomorphic adenomas (PAs) or Warthin tumors (WTs). We further calculated diagnostic accuracy for distinguishing malignant from benign lesions when combining these parameters. RESULTS: PAs demonstrated significantly higher T1, T2, PD, and ADC values than WTs (all p < 0.001). Compared to MTs, PAs had significantly higher T1, T2, and ADC values (all p < 0.001), whereas WTs had significantly lower T1, T2, and PD values (p < 0.001, p = 0.008, and p = 0.003, respectively). T2 and ADC were most effective in differentiating between MTs and PAs (AUC = 0.928 and 0.939, respectively), and T1 and PD values for differentiating between MTs and WTs (AUC = 0.915 and 0.833, respectively). Combining T1 with T2 or ADC achieved accuracy of 86.4% in distinguishing between malignant and benign tumors. Similarly, combining PD with T2 or ADC reached accuracy of 86.4% for differentiating between malignant and benign tumors. CONCLUSIONS: Utilizing a combination of synthetic MRI parameters may assist in differentiating malignant from benign salivary gland lesions.

A case of glioblastoma harboring non-amplified epidermal growth factor receptor variant III: Critical molecular detection using RNA-based panel analysis.

Amplification of the epidermal growth factor receptor gene (EGFR) and its variants are the most commonly detected pathogenic gene alterations in glioblastoma. Herein, we report a case of molecularly defined glioblastoma harboring an EGFR variant III (EGFRvIII) without EGFR amplification. The initial histological diagnosis was isocitrate dehydrogenase (IDH)-wildtype low-grade glioma, due to an absence of anaplasia, necrosis, and microvascular proliferation, and a low Ki-67 labeling index. DNA-based next-generation sequencing (NGS) panel analysis revealed a TERTp promoter mutation but no EGFR mutation or amplification, supporting the diagnosis of "molecular glioblastoma." However, RNA-based NGS panel analysis revealed mRNA expression of EGFRvIII. Therefore, the final integrative diagnosis was glioblastoma with non-amplified EGFRvIII. Our report suggests that non-amplified EGFRvIII might be an early molecular event in glioblastoma tumorigenesis. In addition to the usual DNA-based analysis, RNA-based analysis is required to identify exon-skipping EGFR variants without EGFR amplification.

Extracellular volume fraction derived from equilibrium contrast-enhanced CT as a diagnostic parameter in anterior mediastinal tumors.

PURPOSE: To assess the usefulness of extracellular volume (ECV) fraction derived from equilibrium contrast-enhanced CT (CECT) for diagnosing anterior mediastinal tumors. METHOD: This study included 161 histologically confirmed anterior mediastinal tumors (55 low-risk thymomas, 57 high-risk thymomas, 32 thymic carcinomas, and 17 malignant lymphomas) that were assessed by pretreatment CECT. ECV fraction was calculated using measurements obtained within the lesion and the aorta on unenhanced and equilibrium phase CECT. ECV fraction was compared among anterior mediastinal tumors using one-way ANOVA or t-test. Receiver-operating characteristic (ROC) curve analysis was performed to evaluate the ability of ECV fraction to differentiate thymic carcinomas/lymphomas from thymomas. RESULTS: ECV fraction differed significantly among the anterior mediastinal tumors (p < 0.001). ECV fraction of thymic carcinomas was significantly higher than those of low-risk thymomas, high-risk thymomas, and lymphomas (p < 0.001, p < 0.001, and p = 0.006, respectively). ECV fraction of lymphomas was significantly higher than that of low-risk thymomas (p < 0.001). ECV fraction was significantly higher in thymic carcinomas/lymphomas than in thymomas (40.1 % vs. 27.7 %, p < 0.001). The optimal cutoff value to differentiate thymic carcinomas/lymphomas from thymomas was 38.5 % (AUC, 0.805; 95 %CI, 0.736-0.863). CONCLUSIONS: ECV fraction derived from equilibrium CECT is helpful in diagnosing anterior mediastinal tumors. High ECV fraction is indicative of thymic carcinomas/lymphomas, particularly thymic carcinomas.

Alterations in EGFR and PDGFRA are associated with the localization of contrast-enhancing lesions in glioblastoma.

Background: Glioblastoma (GBM) is a malignant brain tumor, with radiological and genetic heterogeneity. We examined the association between radiological characteristics and driver gene alterations. Methods: We analyzed the driver genes of 124 patients with IDH wild-type GBM with contrast enhancement using magnetic resonance imaging. We used a next-generation sequencing panel to identify mutations in driver genes and matched them with radiological information. Contrast-enhancing lesion localization of GBMs was classified into 4 groups based on their relationship with the subventricular zone (SVZ) and cortex (Ctx). Results: The cohort included 69 men (55.6%) and 55 women (44.4%) with a mean age of 66.4 ±â€…13.3 years. EGFR and PDGFRA alterations were detected in 28.2% and 22.6% of the patients, respectively. Contrast-enhancing lesion touching both the SVZ and Ctx was excluded because it was difficult to determine whether it originated from the SVZ or Ctx. Contrast-enhancing lesions touching the SVZ but not the Ctx had significantly worse overall survival than non-SVZ lesions (441 days vs. 897 days, P = .002). GBM touching only the Ctx had a better prognosis (901 days vs. 473 days, P < .001) than non-Ctx lesions and was associated with EGFR alteration (39.4% vs. 13.2%, P = .015). Multiple contrast lesions were predominant in PDGFRA alteration and RB1-wild type (P = .036 and P = .031, respectively). Conclusions: EGFR alteration was associated with cortical lesions. And PDGFRA alteration correlated with multiple lesions. Our results suggest that clarifying the association between driver genes and tumor localization may be useful in clinical practice, including prognosis prediction.

Differentiating brain metastasis from glioblastoma by time-dependent diffusion MRI.

BACKGROUND: This study was designed to investigate the use of time-dependent diffusion magnetic resonance imaging (MRI) parameters in distinguishing between glioblastomas and brain metastases. METHODS: A retrospective study was conducted involving 65 patients with glioblastomas and 27 patients with metastases using a diffusion-weighted imaging sequence with oscillating gradient spin-echo (OGSE, 50 Hz) and a conventional pulsed gradient spin-echo (PGSE, 0 Hz) sequence. In addition to apparent diffusion coefficient (ADC) maps from two sequences (ADC50Hz and ADC0Hz), we generated maps of the ADC change (cADC): ADC50Hz - ADC0Hz and the relative ADC change (rcADC): (ADC50Hz - ADC0Hz)/ ADC0Hz × 100 (%). RESULTS: The mean and the fifth and 95th percentile values of each parameter in enhancing and peritumoral regions were compared between glioblastomas and metastases. The area under the receiver operating characteristic curve (AUC) values of the best discriminating indices were compared. In enhancing regions, none of the indices of ADC0Hz and ADC50Hz showed significant differences between metastases and glioblastomas. The mean cADC and rcADC values of metastases were significantly higher than those of glioblastomas (0.24 ± 0.12 × 10-3mm2/s vs. 0.14 ± 0.03 × 10-3mm2/s and 23.3 ± 9.4% vs. 14.0 ± 4.7%; all p < 0.01). In peritumoral regions, no significant difference in all ADC indices was observed between metastases and glioblastomas. The AUC values for the mean cADC (0.877) and rcADC (0.819) values in enhancing regions were significantly higher than those for ADC0Hz5th (0.595; all p < 0.001). CONCLUSIONS: The time-dependent diffusion MRI parameters may be useful for differentiating brain metastases from glioblastomas.

Differentiating primary central nervous system lymphoma from glioblastoma by time-dependent diffusion using oscillating gradient.

BACKGROUND: This study aimed to elucidate the impact of effective diffusion time setting on apparent diffusion coefficient (ADC)-based differentiation between primary central nervous system lymphomas (PCNSLs) and glioblastomas (GBMs) and to investigate the usage of time-dependent diffusion magnetic resonance imaging (MRI) parameters. METHODS: A retrospective study was conducted involving 21 patients with PCNSLs and 66 patients with GBMs using diffusion weighted imaging (DWI) sequences with oscillating gradient spin-echo (Δeff = 7.1 ms) and conventional pulsed gradient (Δeff = 44.5 ms). In addition to ADC maps at the two diffusion times (ADC7.1 ms and ADC44.5 ms), we generated maps of the ADC changes (cADC) and the relative ADC changes (rcADC) between the two diffusion times. Regions of interest were placed on enhancing regions and non-enhancing peritumoral regions. The mean and the fifth and 95th percentile values of each parameter were compared between PCNSLs and GBMs. The area under the receiver operating characteristic curve (AUC) values were used to compare the discriminating performances among the indices. RESULTS: In enhancing regions, the mean and fifth and 95th percentile values of ADC44.5 ms and ADC7.1 ms in PCNSLs were significantly lower than those in GBMs (p = 0.02 for 95th percentile of ADC44.5 ms, p = 0.04 for ADC7.1 ms, and p < 0.01 for others). Furthermore, the mean and fifth and 95th percentile values of cADC and rcADC were significantly higher in PCNSLs than in GBMs (each p < 0.01). The AUC of the best-performing index for ADC7.1 ms was significantly lower than that for ADC44.5 ms (p < 0.001). The mean rcADC showed the highest discriminating performance (AUC = 0.920) among all indices. In peritumoral regions, no significant difference in any of the three indices of ADC44.5 ms, ADC7.1 ms, cADC, and rcADC was observed between PCNSLs and GBMs. CONCLUSIONS: Effective diffusion time setting can have a crucial impact on the performance of ADC in differentiating between PCNSLs and GBMs. The time-dependent diffusion MRI parameters may be useful in the differentiation of these lesions.

Pancreatic adenocarcinoma: variability of diffusion-weighted MR imaging findings.

PURPOSE: To compare the apparent diffusion coefficients (ADCs) of pancreatic adenocarcinomas that appear hyperintense with clearly defined borders (clear hyperintense) with those that do not show clear hyperintense borders on diffusion-weighted magnetic resonance (MR) images. MATERIALS AND METHODS: Institutional review board approval was obtained and informed consent was waived. Eighty patients with histologically confirmed pancreatic adenocarcinoma (mean tumor size, 32 mm) underwent fat-suppressed single-shot echo-planar 3.0-T diffusion-weighted MR imaging with diffusion gradients (b = 1000 sec/mm(2)). ADC values of the pancreatic adenocarcinomas (n = 80) and proximal (n = 51) and distal (n = 70) pancreas were compared by using the Friedman test, followed by the Wilcoxon signed-rank test, and the difference in serum amylase levels between pancreatic adenocarcinomas with and without clear hyperintensity was evaluated by using the x(2) test. RESULTS: In 38 of 80 patients, pancreatic adenocarcinomas showed clear hyperintensity relative to the surrounding pancreas; 26 were hyperintense with unclear distal borders; 12, isointense; and four, hypointense. In all patients, the mean ADC (± standard deviation) of the tumors (1.16 × 10(-3) mm(2)/sec ± 0.22) was significantly lower than those of the proximal pancreas (1.33 × 10(-3) mm(2)/sec ± 0.16, P < .001) and the distal pancreatic parenchyma (1.24 × 10(-3) mm(2)/sec ± 0.23, P = .004). No significant difference in ADC was seen between the pancreatic adenocarcinomas without clear hyperintensity and the distal pancreas. The frequency of serum amylase levels greater than 120 U/L (2.00 µkat/L) was significantly higher than in those with clear hyperintense pancreatic adenocarcinomas (P < .001). CONCLUSION: Diffusion-weighted MR imaging was not useful for delineating 47% of pancreatic adenocarcinomas, because of hyperintensity of the pancreatic parenchyma distal to the cancer.

Differentiation of hemangioblastoma from brain metastasis using MR amide proton transfer imaging.

BACKGROUND AND PURPOSE: Differentiation between hemangioblastoma and brain metastasis remains a challenge in neuroradiology using conventional MRI. Amide proton transfer (APT) imaging can provide unique molecular information. This study aimed to evaluate the usefulness of APT imaging in differentiating hemangioblastomas from brain metastases and compare APT imaging with diffusion-weighted imaging and dynamic susceptibility contrast perfusion-weighted imaging. METHODS: This retrospective study included 11 patients with hemangioblastoma and 20 patients with brain metastases. Region-of-interest analyses were employed to obtain the mean, minimum, and maximum values of APT signal intensity, apparent diffusion coefficient (ADC), and relative cerebral blood volume (rCBV), and these indices were compared between hemangioblastomas and brain metastases using the unpaired t-test and Mann-Whitney U test. Their diagnostic performances were evaluated using receiver operating characteristic (ROC) analysis and area under the ROC curve (AUC). AUCs were compared using DeLong's method. RESULTS: All MRI-derived indices were significantly higher in hemangioblastoma than in brain metastasis. ROC analysis revealed the best performance with APT-related indices (AUC = 1.000), although pairwise comparisons showed no significant difference between the mean ADC and mean rCBV. CONCLUSIONS: APT imaging is a useful and robust imaging tool for differentiating hemangioblastoma from metastasis.

Correlation between amide proton transfer-related signal intensity and diffusion and perfusion magnetic resonance imaging parameters in high-grade glioma.

Amide proton transfer (APT) imaging is a magnetic resonance (MR) molecular imaging technique that is sensitive to mobile proteins and peptides in living tissue. Studies have shown that APT-related signal intensity (APTSI) parallels with the malignancy grade of gliomas, allowing the preoperative assessment of tumor grades. An increased APTSI in malignant gliomas has been attributed to cytosolic proteins and peptides in proliferating tumor cells; however, the exact underlying mechanism is poorly understood. To get an insight into the mechanism of high APTSI in malignant gliomas, we investigated the correlations between APTSI and several MR imaging parameters including apparent diffusion coefficient (ADC), relative cerebral blood volume and pharmacokinetic parameters obtained in the same regions-of-interest in 22 high-grade gliomas. We found a significant positive correlation between APTSI and ADC (ρ = 0.625 and 0.490 for observers 1 and 2, respectively; p < 0.001 for both), which is known to be inversely correlated with cell density. Multiple regression analysis revealed that ADC was significantly associated with APTSI (p < 0.001 for both observers). Our results suggest possible roles of extracellular proteins and peptides in high APTSI in malignant gliomas.