The utility of arterial spin labeling imaging for predicting prognosis after a recurrence of high-grade glioma in patients under bevacizumab treatment.

BACKGROUND AND PURPOSE: Currently, the antiangiogenic agent bevacizumab (BVZ) is used as a treatment option for high-grade glioma (HGG) patients. However, BVZ restores disruptions of the blood-brain barrier, which leads to the disappearance of contrast enhancement during radiological examinations and therefore complicates evaluations of treatment efficacy. This study aimed to investigate the radio-morphological features of recurrent lesions that newly appeared under BVZ therapy, as well as the utility of arterial spin labeling (ASL) perfusion imaging for evaluating treatment response and prognosis in HGG patients receiving BVZ. METHODS: Thirty-two patients (20 males, 12 females; age range, 35-84 years) with HGG who experienced a recurrence under BVZ therapy were enrolled. We measured the relative cerebral blood flow (rCBF) values of each recurrent lesion using ASL, and retrospectively investigated the correlation between rCBF values and prognosis. RESULTS: The optimal rCBF cut-off value for predicting prognosis was defined as 1.67 using receiver operating characteristic curve analysis. The patients in the rCBF < 1.67 group had significantly longer overall survival (OS) and post-progression survival (PPS) than those in the rCBF ≥ 1.67 group (OS: 34.0 months vs. 13.0 months, p = 0.03 and PPS: 13.0 months vs. 6.0 months, p < 0.001, respectively). CONCLUSION: The ASL-derived rCBF values of recurrent lesions may serve as an effective imaging biomarker for prognosis in HGG patients undergoing BVZ therapy. Low rCBF values may indicate that BVZ efficacy is sustainable, which will influence BVZ treatment strategies in HGG patients.

Amide proton transfer imaging in differentiation of type II and type I endometrial carcinoma: a pilot study.

PURPOSE: This study aimed at evaluating the efficacy of amide proton transfer (APT) imaging in differentiation of type II and type I uterine endometrial carcinoma. MATERIALS AND METHODS: Thirty-three patients diagnosed with uterine endometrial carcinoma, including 24 with type I and 9 with type II carcinomas, underwent APT imaging. Two readers evaluated the magnetization transfer ratio at 3.5 ppm [MTRasym (3.5 ppm)] in each type of carcinoma. The average MTRasym (APTmean) and the maximum MTRasym (APTmax) were analyzed. The receiver operating characteristic (ROC) curve analysis was performed. RESULTS: The APTmax was significantly higher in type II carcinomas than in type I carcinomas (reader1, p = 0.004; reader 2, p = 0.014; respectively). However, APTmean showed no significant difference between type I and II carcinomas. Based on the results reported by reader 1, the area under the curve (AUC) pertaining to the APTmax for distinguishing type I from type II carcinomas was 0.826, with a cut-off, sensitivity, and specificity of 9.90%, 66.7%, and 91.3%, respectively. Moreover, based on the results reported by reader 2, the AUC was 0.750, with a cut-off, sensitivity, and specificity of 9.80%, 62.5%, and 87.5%, respectively. CONCLUSION: APT imaging has the potential to determine the type of endometrial cancer.

CT and MR imaging findings of bilateral ovarian metastasis from renal cell carcinoma: a case report.

Secondary ovarian involvement by renal cell carcinoma rarely occurs. Here, we describe the computed tomography and magnetic resonance imaging findings of bilateral ovarian metastases from renal cell carcinoma that demonstrated heterogeneous strong contrast enhancing tumors with flow voids around and within the tumors. In addition, the apparent diffusion coefficients of the malignant tumors were high. These findings were similar to those of renal cell carcinomas at primary and other metastatic sites.

Effect of energy difference in the evaluation of calcification size and luminal diameter in calcified coronary artery plaque using spectral CT.

PURPOSE: This study evaluated the calcium blooming-reducing effect and the differences of luminal diameter among various-energy virtual monochromatic images (VMIs) using rapid kilovolt-switching dual-energy computed tomography (DECT). MATERIALS AND METHODS: Forty-five calcified segments in 31 patients were analyzed. For the analysis, 40- to 140-keV VMIs on both non-contrast CT and coronary CT angiography were generated at 10-keV steps, and calcification size and luminal diameter were measured using CT number profile curve and full-width at half-maximum method. We compared calcification size and luminal diameter on each keV VMIs with those on 70-keV VMI. RESULTS: There was no significant differences among the 40- to 140-keV VMIs regarding calcification size or luminal diameter. CONCLUSION: The 40- to 140-keV VMIs produced by single-source DECT had no effect on the calcification size or luminal diameter in the coronary artery.

Investigation of myocardial extracellular volume fraction in heart failure patients using iodine map with rapid-kV switching dual-energy CT: Segmental comparison with MRI T1 mapping.

PURPOSE: To measure myocardial extracellular volume fraction (ECV) for each region or segment using iodine density image (IDI) with single-source dual-energy computed tomography (DECT) and compare the results with an MRI T1 mapping approach. MATERIALS AND METHODS: For this prospective study, 79 consecutive heart failure patients referred for MRI were included and 23 patients (14 men, 63 ± 14 years) who underwent both MRI and late contrast enhancement DECT following coronary CT angiography were evaluated. CT-ECV was computed from IDI using late acquisition projection data. MR-ECV was computed from native and post-contrast T1 maps using non-rigid image registration for segments with evaluable image quality from 3.0-T MRI. Regional CT-ECV and MR-ECV were measured based on 16-segment models. CT-ECV and MR-ECV were compared using Pearson correlations. Agreement among methods was assessed using Bland-Altman comparisons. RESULTS: In the 368 segments, although all segments were evaluable on IDI, 37 segments were rated as non-evaluable on T1 maps. Overall, 331 segments were analyzed. Mean CT-ECV and MR-ECV were 31.6 ± 9.1 and 33.2 ± 9.1, respectively. Strong correlations were seen between CT-ECV and MR-ECV for each region, as follows: all segments, r = 0.837; septal, r = 0.871; mid-septal, r = 0.895; anterior, r = 0.869; inferior, r = 0.793; and lateral, 0.864 (all p < 0.001). Differences between CT-ECV and MR-ECV were as follows: all segments, 1.13 ± 4.98; septal, -1.51 ± 4.37; mid-septal, -1.85 ± 4.22; anterior, 2.54 ± 4.89; inferior, 1.2 ± 5.78; and lateral, 2.65 ± 3.98. CONCLUSION: ECV using DECT and from cardiac MRI showed a strong correlation on regional and segmental evaluations. DECT is useful for characterizing myocardial ECV changes as well as MRI.

Detection and Classification of Myocardial Delayed Enhancement Patterns on MR Images with Deep Neural Networks: A Feasibility Study.

PURPOSE: To evaluate whether deep neural networks trained on a similar number of images to that required during physician training in the American College of Cardiology Core Cardiovascular Training Statement can acquire the capability to detect and classify myocardial delayed enhancement (MDE) patterns. MATERIALS AND METHODS: The authors retrospectively evaluated 1995 MDE images for training and validation of a deep neural network. Images were from 200 consecutive patients who underwent cardiovascular MRI and were obtained from the institutional database. Experienced cardiac MR image readers classified the images as showing the following MDE patterns: no pattern, epicardial enhancement, subendocardial enhancement, midwall enhancement, focal enhancement, transmural enhancement, and nondiagnostic. Data were divided into training and validation datasets by using a fourfold cross-validation method. Three untrained deep neural network architectures using the convolutional neural network (CNN) technique were trained with the training dataset images. The detection and classification accuracies of the trained CNNs were calculated with validation data. RESULTS: The 1995 MDE images were classified by human readers as follows: no pattern, 926; epicardial enhancement, 91; subendocardial enhancement, 458; midwall enhancement, 118; focal enhancement, 141; transmural enhancement, 190; and nondiagnostic, 71. GoogLeNet, AlexNet, and ResNet-152 CNNs demonstrated accuracies of 79.5% (1592 of 1995 images), 78.9% (1574 of 1995 images), and 82.1% (1637 of 1995 images), respectively. CONCLUSION: Deep learning with CNNs using a limited amount of training data, less than that required during physician training, achieved high diagnostic performance in the detection of MDE on MR images.© RSNA, 2019Supplemental material is available for this article.

Quantitative evaluation of non-ischemic dilated cardiomyopathy by late iodine enhancement using rapid kV switching dual-energy computed tomography: A feasibility study.

OBJECTIVES: The aim of this study was to evaluate the feasibility of myocardial iodine density and extracellular volume fraction (ECV) from delayed iodine density images using dual-energy computed tomography (DECT) for differentiation between non-ischemic dilated cardiomyopathy (NIDCM) patients and normal subjects. METHODS: Forty-six subjects were imaged, including 35 normal subjects and 11 patients with NIDCM. All subjects underwent myocardial delayed enhancement (MDE) imaging on rapid-kVp switching DECT. Global and segmental iodine density and ECV were calculated from MDE images. Histogram analysis was also performed. Receiver-operator characteristic (ROC) analysis was used to determine the cut-off value and diagnostic performances in differentiating NIDCM patients from normal subjects. RESULTS: Global iodine density and ECV were significantly higher in NIDCM compared with normal controls (iodine: 14.19 ±â€¯3.90 vs. 10.69 ±â€¯1.88 in 100 µg/cm3, p = 0.015; ECV: 31.35 ±â€¯2.53% vs. 26.62 ±â€¯2.69%, p < 0.001). In histogram analyses, kurtosis was higher in NIDCM than in controls (0.47 ±â€¯0.46 vs. 1.26 ±â€¯0.88, p < 0.001). On segmental analysis, ECV showed higher values in NIDCM than in controls for all segments. ECV could differentiate between normal myocardium and NIDCM with 91.0% sensitivity and 86.0% specificity at a cut-off of 28.82% (area under the curve of ROC, 0.906). Iodine density could differentiate between normal myocardium and NIDCM with 91% sensitivity and 60% specificity at a cut-off of 11.18 (area under the curve of ROC, 0.812). CONCLUSIONS: Iodine density and ECV values from DECT may provide indices offering high diagnostic accuracy for discriminating between NIDCM and normal myocardium.

Role of Neuroimaging on Differentiation of Parkinson's Disease and Its Related Diseases.

An accurate diagnosis of Parkinson's disease (PD) is a prerequisite for therapeutic management. In spite of recent advances in the diagnosis of parkinsonian disorders, PD is misdiagnosed in between 6 and 25% of patients, even in specialized movement disorder centers. Although the gold standard for the diagnosis of PD is a neuropathological assessment, neuroimaging has been playing an important role in the differential diagnosis of PD and is used for clinical diagnostic criteria. In clinical practice, differential diagnoses of PD include atypical parkinsonian syndromes such as dementia with Lewy bodies, multiple system atrophy, progressive supranuclear palsy, corticobasal degeneration, caused by a striatal dopamine deficiency following nigrostrial degeneration. PD may also be mimicked by syndromes not associated with a striatal dopamine deficiency such as essential tremor, drug-induced parkinsonism, and vascular parkinsonism. Moreover, difficulties are associated with the clinical differentiation of patients with parkinsonism from those with Alzheimer's disease. In this review, we summarize the typical imaging findings of PD and its related diseases described above using morphological imaging modalities (conventional MR imaging and neuromelanin MR imaging) and functional imaging modalities (99mTc-ethyl cysteinate dimer perfusion single photon emission computed tomography, 123I-metaiodobenzylguanidine myocardial scintigraphy, and 123I-FP-CIT dopamine transporter single photon emission computed tomography) that are clinically available in most hospitals. We also attempt to provide a diagnostic approach for the differential diagnosis of PD and its related diseases in clinical practice.

Myocardial Delayed Enhancement CT for the Evaluation of Heart Failure: Comparison to MRI.

Purpose To assess the diagnostic performance of dual-energy CT with myocardial delayed enhancement (MDE) in the detection and classification of myocardial scar in patients with heart failure, with late gadolinium enhancement (LGE) MRI as the standard of reference. Materials and Methods MDE CT and LGE MRI were performed in 44 patients with heart failure (30 men; mean patient age, 66 years ± 14) between 2013 and 2016, and images were retrospectively analyzed. The presence and patterns of MDE on iodine-density and virtual monochromatic (VM) images were assessed by two independent readers. Contrast-to-noise ratio (CNR) and percentage signal intensity increase relative to normal myocardium were measured. Diagnostic performance and area under the receiver operating characteristic curve for MDE CT and kappa values for reader agreement were determined. Results Thirty-five of the 44 patients (80%) demonstrated a focal area of LGE, with a nonischemic pattern in 22 of the 44 patients (50%) and an ischemic pattern in 13 (30%). Iodine-density images demonstrated the highest CNR and percentage signal intensity increase on CT images (P < .05), resulting in the highest diagnostic performance in the detection of any MDE CT abnormality (92% sensitivity [195 of 213 segments] and 98% specificity [481 of 491 segments]). The areas under the receiver operating characteristic curve for iodine-density images and 40-keV VM images in the detection of MDE were 0.97 and 0.95, respectively (P < .001). Kappa values for reader agreement were 0.82 for iodine-density images and 0.72 for 40-keV VM images. Conclusion Myocardial delayed enhancement CT enables accurate detection and localization of scar in patients with heart failure when compared with late gadolinium enhancement MRI, the reference standard.

Image quality improvements using adaptive statistical iterative reconstruction for evaluating chronic myocardial infarction using iodine density images with spectral CT.

Single-source dual-energy CT (ssDECT) allows the reconstruction of iodine density images (IDIs) from projection based computing. We hypothesized that adding adaptive statistical iterative reconstruction (ASiR) could improve image quality. The aim of our study was to evaluate the effect and determine the optimal blend percentages of ASiR for IDI of myocardial late iodine enhancement (LIE) in the evaluation of chronic myocardial infarction using ssDECT. A total of 28 patients underwent cardiac LIE using a ssDECT scanner. IDIs between 0 and 100% of ASiR contributions in 10% increments were reconstructed. The signal-to-noise ratio (SNR) of remote myocardia and the contrast-to-noise ratio (CNR) of infarcted myocardia were measured. Transmural extent of infarction was graded using a 5-point scale. The SNR, CNR, and transmural extent were assessed for each ASiR contribution ratio. The transmural extents were compared with MRI as a reference standard. Compared to 0% ASiR, the use of 20-100% ASiR resulted in a reduction of image noise (p < 0.01) without significant differences in the signal. Compared with 0% ASiR images, reconstruction with 100% ASiR image showed the highest improvement in SNR (229%; p < 0.001) and CNR (199%; p < 0.001). ASiR above 80% showed the highest ratio (73.7%) of accurate transmural extent classification. In conclusion, ASiR intensity of 80-100% in IDIs can improve image quality without changes in signal and maximizes the accuracy of transmural extent in infarcted myocardium.

Measurement of Myocardial Extracellular Volume Fraction From Iodine Density Images Using Single-Source, Dual-Energy Computed Tomography: A Feasibility Study.

OBJECTIVE: The aims of this study were to develop and validate an iodine density method for the quantification of myocardial extracellular volume (ECV) fraction using single-source, dual-energy computed tomography. METHODS: Extracellular volume measurements were carried out in 40 subjects (20 patients with heart failure, 20 control subjects) using single-source, dual-energy computed tomography. Subtraction-derived ECVs (subECVs) were computed by subtracting precontrast from delayed images. Iodine density-derived ECVs (iECVs) were calculated from iodine density images obtained from delayed images. Iodine density-derived ECVs were compared with reference subECVs. RESULTS: A strong correlation (r = 0.896, P < 0.0001) and a small bias (-0.06%) were determined between subECV and iECV with high interobserver concordances (0.915 and 0.906, respectively). Extracellular volume measurements in patients with heart failure were higher in both subECV and iECV compared with control subjects (34.6% [SD, 5.0%] vs 29.5% [SD, 3.6%], P = 0.001, for subECV; 34.9% [SD, 4.5%] vs 29.2% [SD, 2.6%], P < 0.0001, for iECV). CONCLUSIONS: Extracellular volume analysis using iodine density is a useful tool for the noninvasive quantification of ECV in myocardial diseases.

Evaluation of image quality of coronary artery plaque with rapid kVp-switching dual-energy CT.

We evaluated the virtual monochromatic imaging (VMI) energy levels that maximize image quality of each coronary plaque component in dual-energy computed tomography angiography in 495 coronary segments (45 for each energy level). Maximal signal-to-noise ratios were different for plaque, lumen, fat, and surrounding tissue (p<0.05). Maximal contrast-to-noise ratios were observed at 70keV for calcified plaque (CP), non-calcified plaque (NCP), and fat in comparison with the lumen (p<0.05), and 70keV and 120keV for NCP in comparison with fat (p=0.144). VMI demonstrated maximal image quality at different energy levels for each component of coronary artery plaque.

Diagnostic performance of calcification-suppressed coronary CT angiography using rapid kilovolt-switching dual-energy CT.

OBJECTIVES: Multi-detector-row computed tomography angiography (MDCTA) plays an important role in the assessment of patients with suspected coronary artery disease. However, MDCTA tends to overestimate stenosis in calcified coronary artery lesions. The aim of our study was to evaluate the diagnostic performance of calcification-suppressed material density (MD) images produced by using a single-detector single-source dual-energy computed tomography (ssDECT). METHODS: We enrolled 67 patients with suspected or known coronary artery disease who underwent ssDECT with rapid kilovolt-switching (80 and 140 kVp). Coronary artery stenosis was evaluated on the basis of MD images and virtual monochromatic (VM) images. The diagnostic performance of the two methods for detecting coronary artery disease was compared with that of invasive coronary angiography as a reference standard. RESULTS: We evaluated 239 calcified segments. In all the segments, the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy for detecting significant stenosis were respectively 88%, 88%, 75%, 95% and 88% for the MD images, 91%, 71%, 56%, 95% and 77% for the VM images. PPV was significantly higher on the MD images than on the VM images (P < 0.0001). CONCLUSIONS: Calcification-suppressed MD images improved PPV and diagnostic performance for calcified coronary artery lesions. KEY POINTS: • Computed tomography angiography tends to overestimate stenosis in calcified coronary artery. • Dual-energy CT enables us to suppress calcification of coronary artery lesions. • Calcification-suppressed material density imaging reduces false-positive diagnosis of calcified lesion.

[A case of tuberculous myeloradiculitis with abdominal lymphadenitis presenting with symptoms of radiculomyelopathy].

A 30-year old man was admitted with right hip pain and gait disturbances. Neurological findings revealed muscular weakness in the lower limbs, hyporeflexia, dysesthesia in the sacral region, and bowel and bladder disturbances. Cerebrospinal fluid (CSF) examination indicated a white blood cell count of 371/µl (lymphocyte:polymorphonuclear leukocyte = 97:3), protein levels of 463 mg/dl and sugar of 20 mg/dl. Although CSF culture was negative, tuberculous infection was presumed. Magnetic resonance imaging revealed areas of enhancement in the intramedullary region surrounding the spinal cord and cauda equina. Enhanced computed tomography (CT) of the abdomen revealed lymph node swelling around the head of the pancreas. Biopsy of the lymph node swelling was culture-positive for Mycobacterium tuberculosis. Hence, assuming a diagnosis of tuberculous lymphadenitis of the abdomen, antitubercular drugs were started. Since antitubercular therapy had beneficial effects on the neurological symptoms and CSF findings, we diagnosed the patient with tuberculous myeloradiculitis. Systematic examinations including lymph node biopsy and cultures were useful for the diagnosis of tuberculous myeloradiculitis.

High incidence of asymptomatic cerebral microbleeds in patients with hemorrhagic onset-type moyamoya disease: a phase-sensitive MRI study and meta-analysis.

BACKGROUND: Moyamoya disease is a relatively rare cerebrovascular occlusive disorder. Several studies have reported cerebral microbleeds (CMBs) in moyamoya disease patients using T2*-weighted imaging (T2*WI) and/or susceptibility-weighted imaging (SWI). PURPOSE: To investigate the incidence, distribution patterns, and influencing factors of asymptomatic CMBs in patients with moyamoya disease. MATERIAL AND METHODS: Phase-sensitive imaging (PSI) was used to investigate 27 consecutive moyamoya disease patients with a 3-T magnetic resonance imaging system, then a meta-analysis of 245 patients (asymptomatic moyamoya disease, n = 23; ischemic moyamoya disease, n = 161; hemorrhagic moyamoya disease, n = 61) from four previous individual studies and our PSI study was performed. The meta-analysis was performed in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. Based on the clinical and radiological data, we divided the studies into different model groups to calculate the incidence of CMBs and discuss the distribution patterns of CMBs. RESULTS: Thirty-five asymptomatic CMBs were demonstrated in 14 moyamoya disease patients (51.9%) in our PSI study. Of these, 45.7% were located in the periventricular white matter. In the meta-analysis, the pooled incidence of asymptomatic CMBs in moyamoya disease was 46% (95% confidence interval [CI], 28.2-63.8%) on SWI or PSI and 29.6% (95% CI, 17.4-41.7%) on T2*WI. Statistical analysis showed that PSI or SWI offered better detection of CMBs in moyamoya disease than T2*WI, and 3-T T2*WI offered better detection than 1.5-T T2*WI. Furthermore, hemorrhagic onset-type moyamoya disease correlated with a high incidence of asymptomatic CMBs. CONCLUSION: PSI or SWI can detect CMBs better than T2*WI, and 3-T T2*WI. Hemorrhagic onset-type moyamoya disease seems to correlate with a high incidence of asymptomatic CMBs. The meta-analysis indicates that asymptomatic CMBs may be an important factor for hemorrhagic stroke risk. Long-term evaluation of CMBs using PSI or SWI may contribute to the management of moyamoya disease.

Correlation between pathology and neuromelanin MR imaging in Parkinson's disease and dementia with Lewy bodies.

INTRODUCTION: Direct correlation between neuropathological findings and postmortem neuromelanin MR imaging (NmMRI) was performed in the substantia nigra pars compacta (SNc) to clarify the pathological background of the signal changes in normal, Parkinson's disease (PD), and dementia with Lewy bodies (DLB) cases. METHODS: NmMRI of 10 % formalin-fixed autopsied midbrains was performed in three cases (normal control, DLB, and PD) with a 3T imaging system, using a 3D gradient echo T1-weighted sequence with a magnetization transfer contrast pulse. Neuropathological examinations of the midbrains were performed, and the density of neuromelanin-positive neurons (number per square millimeter) was determined. The extent of iron deposition in the midbrain was also evaluated using ferritin immunohistochemistry. Furthermore, we directly correlated the contrast signal ratio in the SNc and the density of neuromelanin-containing neurons. RESULTS: Diffuse hyperintense areas in the SNc reflected well-preserved neuromelanin-containing neurons in the normal control case, whereas an iso-intense area in the SNc showed severe loss of neuromelanin-containing neurons in the DLB and PD cases. Increased signal intensity in the SNc was apparently not influenced by iron deposition. Furthermore, a significant positive correlation between signal intensity and the density of neuromelanin-containing neurons was seen in the SNc. CONCLUSION: Based on the direct correlation between postportem NmMRI and neuropathological findings, signal intensity in the SNc is closely related to the quantity of neuromelanin-containing neurons but is not influenced by iron deposition.