Purpose: To develop a 3D magnetic resonance fingerprinting (MRF) method for application in high resolution knee cartilage PD, T₁, T₂ mapping. Materials and Methods: A novel 3D acquisition trajectory with golden-angle rotating radial in k_xy direction and interleaved echo planar imaging (EPI) acquisition in the k_z direction was implemented in the MRF framework. A centric order was applied to the interleaved EPI acquisition to reduce Nyquist ghosting artifact due to field inhomogeneity. For the reconstruction, singular value decomposition (SVD) compression method was used to accelerate reconstruction time and conjugate gradient sensitivity-encoding (CG-SENSE) was performed to overcome low SNR of the high resolution data. Phantom experiments were performed to verify the proposed method. In vivo experiments were performed on 6 healthy volunteers and 2 early osteoarthritis (OA) patients. Results: In the phantom experiments, the T₁ and T₂ values of the proposed method were in good agreement with the spin-echo references. The results from the in vivo scans showed high quality proton density (PD), T₁, T₂ map with EPI echo train length (N_ETL = 4), acceleration factor in through plane (R_z = 5), and number of radial spokes (N_spk = 4). In patients, high T₂ values (50-60 ms) were seen in all transverse, sagittal, and coronal views and the damaged cartilage regions were in agreement with the hyper-intensity regions shown on conventional turbo spin-echo (TSE) images. Conclusion: The proposed 3D MRF method can acquire high resolution (0.5 mm³) quantitative maps in practical scan time (~ 7 min and 10 sec) with full coverage of the knee (FOV: 160 × 160 × 120 mm³).

Recently, neuromelanin and nigrosome imaging techniques have been developed to evaluate the substantia nigra in Parkinson's disease. Previous studies have shown potential benefits of quantitative analysis of neuromelanin and nigrosome images in the substantia nigra, although visual assessments have been performed to evaluate structures in most studies. In this study, we investigate the potential of using deep learning based automatic region segmentation techniques for quantitative analysis of the substantia nigra. The deep convolutional neural network was trained to automatically segment substantia nigra regions on 3D nigrosome and neuromelanin sensitive MR images obtained from 30 subjects. With a 5-fold cross-validation, the mean calculated dice similarity coefficient between manual and deep learning was 0.70 ± 0.11. Although calculated dice similarity coefficients were relatively low due to empirically drawn margins, selected slices were overlapped for more than two slices of all subjects. Our results demonstrate that deep convolutional neural network-based method could provide reliable localization of substantia nigra regions on neuromelanin and nigrosome sensitive MR images.

Purpose: Mild cognitive impairment (MCI) is a prodromal stage of Alzheimer's disease (AD). Brain atrophy in this disease spectrum begins in the medial temporal lobe structure, which can be recognized by magnetic resonance imaging. To overcome the unsatisfactory inter-observer reliability of visual evaluation, quantitative brain volumetry has been developed and widely investigated for the diagnosis of MCI and AD. The aim of this study was to assess the prediction accuracy of quantitative brain volumetry using a fully automated segmentation software package, NeuroQuant^®, for the diagnosis of MCI. Materials and Methods: A total of 418 subjects from the Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer's Disease cohort were included in our study. Each participant was allocated to either a cognitively normal old group (n = 285) or an MCI group (n = 133). Brain volumetric data were obtained from T1-weighted images using the NeuroQuant software package. Logistic regression and receiver operating characteristic (ROC) curve analyses were performed to investigate relevant brain regions and their prediction accuracies. Results: Multivariate logistic regression analysis revealed that normative percentiles of the hippocampus (P < 0.001), amygdala (P = 0.003), frontal lobe (P = 0.049), medial parietal lobe (P = 0.023), and third ventricle (P = 0.012) were independent predictive factors for MCI. In ROC analysis, normative percentiles of the hippocampus and amygdala showed fair accuracies in the diagnosis of MCI (area under the curve: 0.739 and 0.727, respectively). Conclusion: Normative percentiles of the hippocampus and amygdala provided by the fully automated segmentation software could be used for screening MCI with a reasonable post-processing time. This information might help us interpret structural MRI in patients with cognitive impairment.

Purpose: We evaluated the diagnostic performance of LI-RADS version 2018 using gadoxetic acid enhanced MRI for recurrent but untreated HCC in patients with prior history of HCC. Materials and Methods: We enrolled 50 consecutive patients who 1) prior history of treatment of HCC, 2) underwent liver surgery for radiological/clinical diagnosis of new HCC between 2013 to 2018, 3) had gadoxetic acid enhanced MRI within one month before surgery, and 4) did not have more than five HCCs or infiltrative tumors only. Two radiologists reviewed MRI and determined the presence of LR3, LR4 and LR5 observations except previously treated tumors based on LI-RADS version 2018 in consensus. We sub-classified LR4 into LR4m (LR4 with major features only) and LR4u (LR4 upgraded from LR3 by ancillary features). LR4u were further sub-classified into LR4ua (with arterial phase hyperenhancement) and LR4un (without arterial phase hyperenhancement). Results: PPV for LR5, LR4 and LR3 observations for recurrent HCC were 100%, 61.5% and 25.0%, respectively. 100% (3/3) of LR4m were HCC. However, PPV of LR4u was 56.5%. PPV of LR4ua and LR4un were 73.3% and 25.0%, respectively. Sensitivity of LR5 and LR5+LR4 observations as a diagnostic threshold were 32.1% and 89.3%, respectively. Sensitivity for LR5+LR4m+LR4ua observations for diagnosis of HCC were 83.7% and significantly superior to that of LR5 without significant deterioration of specificity (75.0%). Conclusion: In patients with prior history of HCC, LR4 observations by major features or with APHE may be regarded as recurrent HCCs given high sensitivity and comparable specificity/PPV to LR5 observations.

Tumors that metastasize to the pituitary gland are unusual and metastasis of neuroendocrine neoplasm to the sellar region is extremely rare. We report a 59-year-old man with pituitary metastasis from pulmonary carcinoid tumor who presented with left progressive deterioration of visual field. Sellar dynamic magnetic resonance imaging revealed an enhancing sellar mass invading the left cavernous sinus. We report this unusual case with a review of the relevant literature.

Anti-myelin oligodendrocyte glycoprotein (anti-MOG) syndrome is an immune-mediated inflammatory condition of the central nervous system, which usually involves spinal cord and optic nerves. Herein, we studied the case of a 57-year-old female patient who presented with acute/subacute symptoms of sphincter dysfunction, paraparesis, and ocular pain. The patient was diagnosed with anti-MOG syndrome with findings resembling snake-eye appearance (SEA), characterized by nearly symmetrical round high signal intensity lesions located at anterior horns (gray matter) on T2-weighted image.

Congenital absence of the bilateral internal carotid arteries (ICA) is a very rare occurrence. Recognition of this rare anomaly is important, when considering intracranial endovascular interventions in the event of thromboembolic events with revascularization, transsphenoidal surgery, and the surveillance and detection of associated cerebral aneurysms. We report a case of a 25-year-old man who presented with headache since 2 years ago, and was incidentally discovered to have a congenital bilateral absence of ICAs.

Ramsay Hunt syndrome (RHS) is a disease caused by varicella-zoster virus (VZV) infection that can be diagnosed through clinical symptoms with or without imaging evaluations. The typical features of RHS on imaging evaluation include signal changes and enhancement in the internal auditory canal (IAC) nerves, and the labyrinthine segment of cranial nerve VII (CN VII) and cranial nerve VIII (CN VIII). In some patients, inner ear structure (cochlear and vestibular apparatus) is involved in RHS. Neurologic complications, such as encephalitis and meningitis, are rare in RHS, but are known to occur. Therefore, magnetic resonance imaging (MRI) is necessary to detect both abnormal signal intensity in the IAC, CN VII, CN VIII, inner and ear structure, and CNS complications. We report an RHS patient with CN VII, VIII, and leptomeningeal enhancement within the cerebellar folia on 10-min delayed, contrast-enhanced (CE), three-dimensional fluid-attenuated inversion recovery (3D-FLAIR) imaging.

Pleomorphic adenoma is the most common benign neoplasm of the salivary glands. Its three malignant variants include carcinoma ex pleomorphic adenoma, carcinosarcoma, and metastasizing pleomorphic adenoma. Among the subtypes of carcinoma ex pleomorphic adenoma, high-grade mucoepidermoid carcinoma has rarely been reported. Additionally, metastasizing pleomorphic adenoma is rare. We report the imaging findings of a high-grade mucoepidermoid carcinoma ex metastasizing pleomorphic adenoma of the parotid gland and parapharyngeal space in a 42-year-old man.