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.

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.

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.

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.

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.

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.

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.

Consistency of Pituitary Adenoma: Prediction by Pharmacokinetic Dynamic Contrast-Enhanced MRI and Comparison with Histologic Collagen Content.

Prediction of tumor consistency is valuable for planning transsphenoidal surgery for pituitary adenoma. A prospective study was conducted involving 49 participants with pituitary adenoma to determine whether quantitative pharmacokinetic analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is useful for predicting consistency of adenomas. Pharmacokinetic parameters in the adenomas including volume of extravascular extracellular space (EES) per unit volume of tissue (ve), blood plasma volume per unit volume of tissue (vp), volume transfer constant between blood plasma and EES (Ktrans), and rate constant between EES and blood plasma (kep) were obtained. The pharmacokinetic parameters and the histologic percentage of collagen content (PCC) were compared between soft and hard adenomas using Mann-Whitney U test. Pearson's correlation coefficient was used to correlate pharmacokinetic parameters with PCC. Hard adenomas showed significantly higher PCC (44.08 ± 15.14% vs. 6.62 ± 3.47%, p < 0.01), ve (0.332 ± 0.124% vs. 0.221 ± 0.104%, p < 0.01), and Ktrans (0.775 ± 0.401/min vs. 0.601 ± 0.612/min, p = 0.02) than soft adenomas. Moreover, a significant positive correlation was found between ve and PCC (r = 0.601, p < 0.01). The ve derived using DCE-MRI may have predictive value for consistency of pituitary adenoma.

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.

Visualization of incidentally imaged pituitary gland on three-dimensional arterial spin labeling of the brain.

OBJECTIVE: To evaluate the visualization of incidentally imaged normal pituitary gland on three-dimensional (3D) pseudo continuous arterial spin labeling (PCASL) perfusion imaging of the brain. METHODS: Ninety-three patients with a normal pituitary gland who underwent 3D PCASL for suspected brain diseases were retrospectively included. Visualization of the pituitary gland on PCASL cerebral blood flow (CBF) maps was assessed independently by two observers using a three-point grading system: Grade 1, pituitary CBF ≤ CBF of the cerebral white matter (WM); Grade 2, CBF of WM < pituitary CBF ≤ CBF of the cortical gray matter (GM); and Grade 3, CBF of GM < pituitary CBF. The interobserver agreement of visual grading was determined using weighted κ statistic. The associations of visual grades with age, sex, and pituitary volume were assessed using multivariate logistic regression. Pituitary glands were divided equally into three groups (small, medium, and large) according to their volume for categorization. RESULTS: The interobserver agreement for visual rating was excellent (weighted κ = 0.823). Of the 93 cases, Grades 1, 2, and 3 included 17 (18.3%), 41 (44.1%), and 35 cases (37.6%), respectively. Medium and large pituitary volume were significantly associated with Grade 3 visualization (p = 0.0153, OR = 4.8323; 95% CI: 1.3525, 17.2649 and p = 0.0009; OR = 9.0299; 95% CI: 2.4663, 33.0614, respectively), whereas there was no significant association for age or sex. CONCLUSION: The normal pituitary gland is often visualized with higher CBF than cortical GM on 3D PCASL, especially in individuals with larger pituitary volume. ADVANCES IN KNOWLEDGE: Appearance of the normal pituitary gland on 3D PCASL has been documented for the first time.

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.

Histopathological variation in the demyelinating sentinel lesion of primary central nervous system lymphoma.

BACKGROUND: Primary central nervous system lymphoma (PCNSL) is one of the least common malignant brain tumors. It is usually diagnosed initially as diffuse large B cell lymphoma (DLBCL). In rare cases, however, a demyelinating lesion referred to as a "sentinel lesion" precedes the actual diagnosis, which usually depicts two distinct patterns of inflammatory cells during histological analysis. This case report describes a unique histological finding and describes the recognized variations in sentinel lesion histopathology. CASE DESCRIPTION: A 78-year-old female patient was found to have multiple white matter lesions of various degrees of enhancement on post-contrast T1-weighted magnetic resonance imaging. A stereotactic biopsy of a heterogeneous lesion in the left occipital lobe was performed, which revealed demyelination along with lymphocytic infiltration, reactive astrocytosis, abundant T cells, and foamy macrophages. There was no evidence of monoclonality, rapid regression of all lesions occurred, and the patient was thus treated for tumefactive demyelination. Three months later, all of the residual lesions had enlarged and were homogeneously enhancing. An endoscopic-guided biopsy of the right periventricular lesion showed diffuse atypical lymphoid cells. CONCLUSION: The sentinel lesion of PCNSL expresses a variable histological pattern of inflammatory cells. This case demonstrates a unique and rare picture of mixed perivascular and parenchymal infiltration of inflammatory cells, highlighting the importance of repeated biopsies and/or radiological examinations to obtain an accurate diagnosis.

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.

Precision of preoperative diagnosis in patients with brain tumor - A prospective study based on "top three list" of differential diagnosis for 1061 patients.

BACKGROUND: Accurate diagnosis of brain tumor is crucial for adequate surgical strategy. Our institution follows a comprehensive preoperative evaluation based on clinical and imaging information. METHODS: To assess the precision of preoperative diagnosis, we compared the "top three list" of differential diagnosis (the first, second, and third diagnoses according to the WHO 2007 classification including grading) of 1061 brain tumors, prospectively and consecutively registered in preoperative case conferences from 2010 to the end of 2017, with postoperative pathology reports. RESULTS: The correct diagnosis rate (sensitivity) of the first diagnosis was 75.8% in total. The sensitivity of the first diagnosis was high (84-94%) in hypothalamic-pituitary and extra-axial tumors, 67-75% in intra-axial tumors, and relatively low (29-42%) in intraventricular and pineal region tumors. Among major three intra-axial tumors, the sensitivity was highest in brain metastasis: 83.8% followed by malignant lymphoma: 81.4% and glioblastoma multiforme: 73.1%. Sensitivity was generally low (≦60%) in other gliomas. These sensitivities generally improved when the second and third diagnoses were included; 86.3% in total. Positive predictive value (PPV) was 76.9% in total. All the three preoperative diagnoses were incorrect in 3.4% (36/1061) of cases even when broader brain tumor classification was applied. CONCLUSION: Our institutional experience on precision of preoperative diagnosis appeared around 75% of sensitivity and PPV for brain tumor. Sensitivity improved by 10% when the second and third diagnoses were included. Neurosurgeons should be aware of these features of precision in preoperative differential diagnosis of a brain tumor for better surgical strategy and to adequately inform the patients.

Quantitative pharmacokinetic analysis of high-temporal-resolution dynamic contrast-enhanced MRI to differentiate the normal-appearing pituitary gland from pituitary macroadenoma.

PURPOSE: To evaluate the usefulness of high-temporal-resolution dynamic contrast-enhanced (DCE) MRI and quantitative pharmacokinetic analysis to differentiate the normal-appearing pituitary gland from a pituitary macroadenoma. MATERIALS AND METHODS: Twenty-seven patients with macroadenomas underwent preoperative DCE-MRI with a temporal resolution of 5 s using compressed sensing to obtain pharmacokinetic parameters. Two independent observers localized the normal-appearing pituitary gland on post-contrast T1-weighted images before and after referring to the corresponding Ktrans maps. Agreements between the localizations and intraoperative findings were evaluated using the kappa statistics. The Mann-Whitney U test was used to compare the pharmacokinetic parameters of the normal-appearing pituitary gland and adenoma. RESULTS: For both observers, the agreement between the MRI-based localization and the intraoperative findings increased after referring to the Ktrans maps (observer 1, 0.930-1; observer 2, 0.636-0.855). The normal-appearing pituitary gland had significantly higher Ktrans [/min] (1.50 ± 0.80 vs 0.58 ± 0.49, P < 0.0001), kep [/min] (3.19 ± 1.29 vs 2.15 ± 1.18, P = 0.0049), and ve (0.43 ± 0.15 vs 0.25 ± 0.17, P = 0.0003) than adenoma. CONCLUSION: High-temporal-resolution DCE-MRI and quantitative pharmacokinetic analysis help accurately localize the normal-appearing pituitary gland in patients with macroadenomas. The normal-appearing pituitary gland was characterized by higher Ktrans, kep, and ve than macroadenoma. Dynamic contrast-enhanced MRI with high-temporal-resolution using compressed sensing was used for quantitative pharmacokinetic analysis of pituitary macroadenomas. An observer study, the use of Ktrans maps improved accuracy in localizing the normal-appearing pituitary gland. As compared to an adenoma, the normal-appearing pituitary gland had significantly higher Ktrans, kep, and ve values.

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.

Histological Grade of Meningioma: Prediction by Intravoxel Incoherent Motion Histogram Parameters.

RATIONALE AND OBJECTIVES: To evaluate the usefulness of intravoxel incoherent motion (IVIM) histogram analysis for differentiating low-grade meningiomas (LGMs) and high-grade meningiomas (HGMs). MATERIALS AND METHODS: Fifty-nine patients with pathologically confirmed meningiomas (45 LGMs and 14 HGMs) underwent IVIM MR imaging. Maps of IVIM parameters (perfusion fraction, f; true diffusion coefficient, D; and pseudo diffusion coefficient, D*), as well as of the apparent diffusion coefficient (ADC), were generated. Histogram analysis was performed using parametric values from all voxels in regions-of-interest manually drawn to encompass the whole tumor. The histogram results of ADC and IVIM parameters were compared using the Mann-Whitney U test. Area under the receiver operating characteristic curve (AUC) values were generated to evaluate how well each parameter could differentiate LGMs from HGMs. Spearman's rank correlation coefficients were used to evaluate correlations between histogram parameters and Ki-67 expression. RESULTS: Compared to LGM, HGM showed significantly higher standard deviation (SD), variance, and coefficient of variation (CV) of ADC (p< 0.006-0.028; AUC, 0.693-0.748), D (p< 0.004-0.032; AUC, 0.670-0.752), and significantly higher CV of f (p< 0.005-0.024; AUC = 0.737). Means and percentiles of ADC and IVIM parameters did not differ significantly between LGM and HGM. Significant positive correlations were identified between Ki-67 and histogram parameters of ADC (SD, variance, kurtosis, skewness, and CV) and D (SD, variance, kurtosis, and CV), whereas no significant correlation with Ki-67 was shown for mean or percentiles of ADC and IVIM parameters. CONCLUSION: Heterogeneity histogram parameters of ADC, D, and f may be useful for differentiating LGMs from HGMs.

Large Intraosseous Schwannoma in Petrous Apex Presenting with Intratumoral Hemorrhage.

BACKGROUND: Intracranial schwannomas are rarely confined to the skull. We here report a large schwannoma localized in the petrous apex that presented with intratumoral hemorrhage. CASE DESCRIPTION: A 35-year-old woman with mild hearing disturbance and ear fullness underwent computed tomography scan and magnetic resonance imaging, which demonstrated a tumor accompanied with intratumoral hematoma in the right petrous apex. Bone marrow was totally destroyed, but the bone cortex was relatively preserved. Pathologic specimen showed that the tumor was composed of proliferation of elongated neoplastic cells and positive for S-100 protein. It showed a nuclear palisading pattern, compatible with schwannoma. The lack of any cranial nerve signs and relative preservation of canals through which cranial nerves pass suggested the neurilemma cells surrounded vessels or mismigrated fetal neurilemma cells in the petrous apex as origin of the tumor. Benign nature of the tumor and total disappearance of the symptoms, supposedly due to the spontaneous absorption of the hematoma, made the patient choose a wait-and-watch approach. Magnetic resonance imaging studied 7 years after the diagnosis showed significant decrease of the tumor volume and disappearance of the hematoma. CONCLUSIONS: Although it is a large intraosseous schwannoma in the petrous apex, it has a benign nature, its size is reduced due to the hematoma absorption, and the patient is asymptomatic. We observed the patients for 7 years after the diagnosis.