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.

This study investigates the hypothesis that there is, during childhood, a disproportionate age-related expansion of the origin of temporalis muscle compared to the growth of the underlying skull. Lateral projections of 50 randomly selected 3D reformatted computerized tomographic (CT) scans (yielding 100 temporalis muscles) of children aged >0.6 to 15 years scanned for conditions that did not affect the shape of their head or face were windowed to provide the optimum delineation of temporalis muscle against the underlying bone. Vertical and anterior-posterior measurements of the muscle made independently by two observers were compared with those of the skull along the same planes. The development of the anterior temporal crest was also assessed. The intraclass correlation coefficient for differences in the measurements made by each observer ranged from good to excellent. The muscle and skull measurements were used to produce a ratio of muscle-to-skull lengths in both vertical and horizontal planes. Analysis of these ratios showed a statistically significant increase in the vertical reach of temporalis with age (Pearson correlation coefficient (R) =0.7826; p < 0.05) compared to the growth of the skull along the planes chosen for the study-but less so for its horizontal reach (R = 0.5073. p < .001). There were no significant differences between right/left or male/female measurements. There was also a substantial level of agreement between both observers in their assessment of the development of the temporal crest. The mean age of children in whom a fully formed temporal crest could be identified (10.6 years) was significantly greater (p < 0.001) than that of the 38 remaining subjects (6.0 years). These results confirm that there is, in response to increased masticatory/dietary demands during childhood, a disproportionate increase in the vertical and (to a lesser extent) horizontal reach of temporalis muscle over its origin from the temporal, frontal, sphenoid, and parietal bones compared the growth of the skull. It is proposed that surgical interference with this normal process is responsible for the soft tissue component of late-developing deformity that can occur following early (at 6-18 months of age) operations for the correction of trigonocephalic head shape associated with metopic synostosis.

Purpose The authors’ purpose was to create a valid multiparametric MRI model for the differential diagnosis between glioblastoma and solitary brain metastasis. Materials and methods Forty-one patients (twenty glioblastomas and twenty-one brain metastases) were retrospectively evaluated. MRIs were analyzed with Olea Sphere® 3.0. Lesions’ volumes of interest (VOIs) were drawn on enhanced 3D T1 MP-RAGE and projected on ADC and rCBV co-registered maps. Another two VOIs were drawn in the region of hyperintense cerebral edema, surrounding the lesion, respectively, within 5 mm around the enhancing tumor and into residual edema. Perfusion curves were obtained, 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. Results 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 < 1 × 10−3 mm2 s−1 GB could be differentiated from solitary BM (sensitivity and specificity of 95% and 86%). Conclusion Lower values of ADC in the enhancing tumor, a higher percentage of SR in perfusion curves and higher values of rCBV in the peritumoral edema closed to the lesion are strongly indicative of GB than solitary BM.

Background Patient body size represents the main determinant of parenchymal enhancement and by adjusting the contrast media (CM) dose to patient weight may be a more appropriate approach to avoid a patient over dosage of CM. To compare the performance of fixed-dose and lean body weight (LBW)-adapted contrast media dosing protocols, in terms of image quality and parenchymal enhancement. Results One-hundred cancer patients undergoing multiphasic abdominal CT were prospectively enrolled in this multicentric study and randomly divided in two groups: patients in fixed-dose group (n = 50) received 120 mL of CM while in LBW group (n = 50) the amount of CM was computed according to the patient’s LBW. LBW protocol group received a significantly lower amount of CM (103.47 ± 17.65 mL vs. 120.00 ± 0.00 mL, p < 0.001). Arterial kidney signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) and pancreatic CNR were significantly higher in LBW group (all p ≤ 0.004). LBW group provided significantly higher arterial liver, kidney, and pancreatic contrast enhancement index (CEI) and portal venous phase kidney CEI (all p ≤ 0.002). Significantly lower portal vein SNR and CNR were observed in LBW-Group (all p ≤ 0.020). Conclusions LBW-adapted CM administration for abdominal CT reduces the volume of injected CM and improves both image quality and parenchymal enhancement.

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Congenital infections represent a challenging and varied clinical scenario in which the brain is frequently involved. Therefore, fetal and neonatal neuro-imaging plays a pivotal role in reaching an accurate diagnosis and in predicting the clinical outcome. Congenital brain infections are characterized by various clinical manifestations, ranging from nearly asymptomatic diseases to syndromic disorders, often associated with severe neurological symptoms. Brain damage results from the complex interaction among the infectious agent, its specific cellular tropism, and the stage of development of the central nervous system at the time of the maternal infection. Therefore, neuroradiological findings vary widely and are the result of complex events. An early detection is essential to establishing a proper diagnosis and prognosis, and to guarantee an optimal and prompt therapeutic perinatal management. Recently, emerging infective agents (i.e., Zika virus and SARS-CoV2) have been related to possible pre- and perinatal brain damage, thus expanding the spectrum of congenital brain infections. The purpose of this pictorial review is to provide an overview of the current knowledge on fetal and neonatal brain neuroimaging patterns in congenital brain infections used in clinical practice.

In utero MRI of the CNS is a third level examination that is indicated exclusively after a second level (expert) neuro-US

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<1x10-3 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.