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Proton magnetic resonance spectroscopy (1H MRS), which can demonstrate neuronal loss and gliosis, may be used as a sensitive tool for lateralization of temporal lobe epilepsy (TLE). Although the correlation between the memory functions and 1H MRS has been investigated, its predictive value after surgery has not been studied previously. This study evaluated memory and 1H MRS values of medically intractable patients with mesial TLE and hippocampal sclerosis (MTLE-HS) before and after selective amygdalohippocampectomy (SAH). Twenty-two patients underwent memory tests and 1H MRS investigation before and 6 months after SAH and were compared with nine control subjects. The 1H MRS scores were found to be significantly low on the pathological side of the patients. Both right-sided 1H MRS of right TLE and left-sided 1H MRS values of left TLE patients were correlated only with verbal memory scores. Statistical analysis did not reveal any significance for nonverbal memory scores for both TLE groups on either side, which showed no significant correlation between material specificity and 1H MRS findings. Conversely, regression analyses demonstrated that high right- and low left-sided 1H MRS values obtained before surgery may predict a decline in verbal learning scores after surgery. 1H MRS can be considered as a useful tool to determine the lateralization in patients with MTLE-HS before the surgery. Although only a weak relation exists between the MRS values and memory scores, presurgical MRS scores may be predictive for a possible deterioration in verbal memory after surgery. However, further studies with higher numbers of cases are needed for confirmation of the results.

Tuberous sclerosis complex is an autosomal dominant disorder that often causes refractory seizures. The presence of multiple lesions makes it difficult to identify a single lesion responsible for the epilepsy. Our purpose is to assess the single-voxel proton spectroscopic findings of the tubers in 11 children with tuberous sclerosis complex. Prior to age 4 years, all of the patients had presented with epileptic seizures and multiple bilateral tubers in magnetic resonance images. Single-voxel proton spectroscopy was performed from the tubers especially showing epileptogenic activity using both the long and short echo time and in 14 controls. The results were analyzed using the Mann-Whitney U-test. Compared with the control group, the spectroscopic findings of tubers were characterized by decreased N-acetylaspartate to creatine ratios (1.43 ± 0.33; P < .001) in both the long and short echo time spectra, increased choline to creatine ratios (0.91 ± 0.082; P < .05), and myo-inositol to creatine ratios (0.97 ± 0.19; P < .01) in the short echo time spectra. A lactate peak was detected in the regions corresponding to an epileptic focus on electroencephalography in six patients. Single-voxel proton spectroscopy could be a useful noninvasive method to evaluate epileptogenic tubers. ( J Child Neurol 2005;20:517—522).

S100 protein expression levels and neurofibromatosis type 2 (NF-2) mutations result in different disease courses in meningiomas. This study aimed to investigate non-invasive biomarkers of NF-2 copy number loss and S100 protein expression in meningiomas using morphological, radiomics, and deep learning-based features of susceptibility-weighted MRI (SWI). This retrospective study included 99 patients with S100 protein expression data and 92 patients with NF-2 copy number loss information. Preoperative cranial MRI was conducted using a 3T clinical MR scanner. Tumor volumes were segmented on fluid-attenuated inversion recovery (FLAIR) and subsequent registration of FLAIR to high-resolution SWI was performed. First-order textural features of SWI were extracted and assessed using Pyradiomics. Morphological features, including the tumor growth pattern, peritumoral edema, sinus invasion, hyperostosis, bone destruction, and intratumoral calcification, were semi-quantitatively assessed. Mann–Whitney U tests were utilized to assess the differences in the SWI features of meningiomas with and without S100 protein expression or NF-2 copy number loss. A logistic regression analysis was used to examine the relationship between these features and the respective subgroups. Additionally, a convolutional neural network (CNN) was used to extract hierarchical features of SWI, which were subsequently employed in a light gradient boosting machine classifier to predict the NF-2 copy number loss and S100 protein expression. NF-2 copy number loss was associated with a higher risk of developing high-grade tumors. Additionally, elevated signal intensity and a decrease in entropy within the tumoral region on SWI were observed in meningiomas with S100 protein expression. On the other hand, NF-2 copy number loss was associated with lower SWI signal intensity, a growth pattern described as “en plaque”, and the presence of calcification within the tumor. The logistic regression model achieved an accuracy of 0.59 for predicting NF-2 copy number loss and an accuracy of 0.70 for identifying S100 protein expression. Deep learning features demonstrated a strong predictive capability for S100 protein expression (AUC = 0.85 ± 0.06) and had reasonable success in identifying NF-2 copy number loss (AUC = 0.74 ± 0.05). In conclusion, SWI showed promise in identifying NF-2 copy number loss and S100 protein expression by revealing neovascularization and microcalcification characteristics in meningiomas.

A reliable and practical renal-lipid quantification and imaging method is needed. Here, the feasibility of an accelerated MRSI method to map renal fat fractions (FF) at 3T and its repeatability were investigated. A 2D density-weighted concentric-ring-trajectory MRSI was used for accelerating the acquisition of 48 × 48 voxels (each of 0.25 mL spatial resolution) without respiratory navigation implementations. The data were collected over 512 complex-FID timepoints with a 1250 Hz spectral bandwidth. The MRSI sequence was designed with a metabolite-cycling technique for lipid–water separation. The in vivo repeatability performance of the sequence was assessed by conducting a test–reposition–retest study within healthy subjects. The coefficient of variation (CV) in the estimated FF from the test–retest measurements showed a high degree of repeatability of MRSI-FF (CV = 4.3 ± 2.5%). Additionally, the matching level of the spectral signature within the same anatomical region was also investigated, and their intrasubject repeatability was also high, with a small standard deviation (8.1 ± 6.4%). The MRSI acquisition duration was ~3 min only. The proposed MRSI technique can be a reliable technique to quantify and map renal metabolites within a clinically acceptable scan time at 3T that supports the future application of this technique for the non-invasive characterization of heterogeneous renal diseases and tumors.

The reliability and reproducibility of T2-weighted imaging/fluid-attenuated inversion recovery (T2/FLAIR) mismatch were investigated in the diagnosis of isocitrate dehydrogenase (IDH) mutant astrocytoma between WHO grade II and III diffuse hemispheric gliomas. WHO grade II and grade III diffuse hemispheric gliomas (n=133) treated in our institute were included in the study. Pathological findings and molecular markers of the cases were reviewed with the criteria of WHO 2016. The finding of mismatch between T2-weighted and FLAIR images in preoperative magnetic resonance imaging (MRI) of the cases was evaluated by two different radiologists. The readers reviewed MRIs independently, blinded to the histopathologic diagnosis or molecular subset of tumors. The cases were classified as IDH-mutant astrocytoma, oligodendroglioma and IDH-wildtype (IDH-wt) astrocytoma according to molecular and genetic features. T2/FLAIR mismatch positivity was observed in 46 patients (34.6%). T2/FLAIR mismatch positivity was observed in 42 of 75 IDH-mutant astrocytomas (56%) and 4 of 43 oligodendrogliomas (9.30%), while it was not seen among IDH-wt astrocytomas (0/15, 0%). The T2/FLAIR mismatch ratio was significantly different between IDH-mutant astrocytomas (WHO grade II and grade III) and oligodendrogliomas (chi-square, p <0.05). The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of T2/FLAIR mismatch in predicting IDH-mutant astrocytomas were 58.7%, 90.7%, 91.7%, 61.4%, and 70.3% respectively. Radiologist 1 diagnosed T2/FLAIR mismatch in 48 of 133 cases (36.1%) and Radiologist 2 in 66 of 133 cases (49.6%). The interrater agreement for the T2/FLAIR mismatch sign was 0.61 (p <0.05), 95% CI (0.55, 0.67). T2/FLAIR mismatch appears to be an important MRI finding in distinguishing IDH-mutant astrocytomas from other diffuse hemispheric gliomas. However, it should be kept in mind that T2/FLAIR mismatch sign can be seen in a minority of oligodendrogliomas besides IDH-mutant astrocytomas.