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The importance of fetal magnetic resonance imaging (MRI) in the prenatal diagnosis of central nervous system (CNS) anomalies is rapidly increasing. Fetal MRI represents a third level examination usually performed, as early as 18–20 weeks of gestational age, when a second level (expert) neuro-ultrasonography (US) evaluation raises the suspicion of a CNS anomaly or when a genetic disorder is known. Compared to the US, MRI has the advantage to allow a better visualization and characterization of brain structures so to detect anomalies not visible in the US, thus resulting in relevant implications for parent counselling and pregnancy management. Moreover, the improvement of MRI technologies permits to obtain ultrafast sequences, which minimize the drawback of movement artifacts, and to perform advanced studies. This review aims at providing a practical guide for trainees and fellows who are approaching fetal MRI. In the first part, we provide information about indications, safety and protocols based on the state-of-the-art sequences, with a mention on the innovations related to the use of a 3T scanner. The second part is focused on the normal development of the human fetal brain related to its MR appearance, whose knowledge is essential to detect possible abnormalities. The last section briefly describes the most frequent abnormalities in the fetal brain and spine as depicted by MRI.

PURPOSEThe authors purpose was to evaluate ADC and rCBV values in the enhanced lesion, in the peritumoral area and in distal oedema using a Volume of Interest (VOI) based method and to analysed hemodynamic curves obtained from DSC perfusion MRI, in order to create a valid multiparametric MRI model for the differential diagnosis between Glioblastoma and solitary Brain Metastasis.MATERIALS AND METHODSForty-one patients (twenty glioblastomas and twenty-one single brain metastases) were retrospectively evaluated. MRI images were acquired before surgery, radiotherapy and chemotherapy. MRIs were analysed with Olea Sphere® 3.0 (Olea Medical, La Ciotat, France), in particular with diffusion, perfusion and volume of interest segmentation plug-ins. FLAIR, 3D T1 MP-RAGE images after gadolinium, ADC and rCBV maps for each patient were co-registered by the OleaSphere software; this was followed by visual inspection to ensure adequate alignment. Volumes of interest (VOIs) of the lesions were drawn on enhanced 3D T1 MP-RAGE avoiding cyst or necrotic degeneration, and then projected on ADC and rCBV co-registered maps. Another 2 VOIs were drawn in the region of hyperintense cerebral oedema, surrounding the lesion (GB or BM) visible on FLAIR images. The first VOI was drawn into perilesional oedema within 5mm around the enhancing tumor. The second VOI was drawn into residual oedema. Both VOIs were projected on ADC and rCBV maps. Perfusion curves were obtained for each lesion and the value of signal recovery (SR) was reported. A Two sample T-Test was obtained to compare all parameters of GB and BM groups. Receiver operating characteristics (ROC) analysis was performed to determine the optimal parameter in distinguishing GB from BM. RESULTSComparing all parameters evaluated for patients with GB and BM, the cerebral lesions were distinguishable with the mean ADC VOI- values of solid component, the PSR values and the mean and max rCBV values in the perilesional edema within 5mm around the enhancing tumor. According to ROC analysis, the area under the curve was 88%, 78% and 74% respectively for mean ADC VOI-values of the solid component, the mean and max rCBV values in the perilesional edema and the PSR. The cumulative ROC curve of these parameters reached an area under the curve of 95% .Using perilesional max rCBV>1,37, PSR>75% and mean lesional ADC-3 mm2 s-1 GB could be differentiated from solitary BM with sensitivity and specificity of 95% and 86%. CONCLUSIONWe can conclude that lower values of ADC in the enhancing tumor volume and a higher percentage of signal recovery in perfusion curves, associated with higher values of rCBV in the peritumoral edema closed to the lesion, are strongly indicative of GB than solitary BM.

Isocitrate dehydrogenase (IDH) mutant and wildtype glioblastoma multiforme (GBM) often show overlapping features on magnetic resonance imaging (MRI), representing a diagnostic challenge. Deep learning showed promising results for IDH identification in mixed low/high grade glioma populations, however, a GBM-specific model is still lacking in the literature. Our aim was to develop a GBM-tailored deep-learning model for IDH prediction by applying convoluted neural networks (CNN) on multiparametric MRI. We selected 100 adult patients with pathologically demonstrated WHO grade IV gliomas and IDH testing. MRI sequences included: MPRAGE, T1, T2, FLAIR, rCBV and ADC. The model consisted of a 4-block 2D CNN, applied to each MRI sequence. Probability of IDH mutation was obtained from the last dense layer of a softmax activation function. Model performance was evaluated in the test cohort considering categorical cross-entropy loss (CCEL) and accuracy. Calculated performance was: rCBV (accuracy 83%, CCEL 0.64), T1 (accuracy 77%, CCEL 1.4), FLAIR (accuracy 77%, CCEL 1.98), T2 (accuracy 67%, CCEL 2.41), MPRAGE (accuracy 66%, CCEL 2.55). Lower performance was achieved on ADC maps. We present a GBM-specific deep-learning model for IDH mutation prediction, with a maximal accuracy of 83% on rCBV maps. Highest predictivity achieved on perfusion images possibly reflects the known link between IDH and neoangiogenesis through the hypoxia inducible factor.

Hemorrhage into a juxtafacet cyst is rare and cyst rupture with hemorrhagic extension into the epidural space is even less commonly seen. We describe the case of a patient with a hemorrhagic synovial cyst with rupture associated to abundant bleeding in the epidural space. A 61-year-old man had a 5-month history of worsening low back pain radiating into the right leg with associated weakness and numbness. A magnetic resonance imaging scan showed the presence of a mild anterior spondylolisthesis of L5 on S1 with increased synovial fluid into both facet joints. A suspected synovial cyst of the right facet joint at level L5-S1, with signal characteristics consistent with hemorrhage was seen. Caudally, epidural blood was evident from S1 to S2 that involved spinal canal and right S1 and S2 foramens. These findings were confirmed at surgery.

Non-congenital viral infections of the central nervous system in children can represent a severe clinical condition that needs a prompt diagnosis and management. However, the aetiological diagnosis can be challenging because symptoms are often nonspecific and cerebrospinal fluid analysis is not always diagnostic. In this context, neuroimaging represents a helpful tool, even though radiologic patterns sometimes overlap. The purpose of this pictorial essay is to suggest a schematic representation of different radiologic patterns of non-congenital viral encephalomyelitis based on the predominant viral tropism and vulnerability of specific regions: cortical grey matter, deep grey matter, white matter, brainstem, cerebellum and spine.