Alp Dinçer

Gliomas exhibit aberrant angiogenesis that drives tumor progression and therapeutic resistance. Susceptibility‐weighted imaging (SWI) enables noncontrast visualization of intratumoral vasculature, but current approaches rely on summary metrics that overlook vascular topology. We developed a graph‐based framework to model vascular networks from SWI and predict glioma survival. Between 2005 and 2020, 228 adults with histologically confirmed diffuse glioma (World Health Organization [WHO] Grades 2–4) who had undergone preoperative MRI were retrospectively screened. MRI was performed on 1.5‐ and 3‐T scanners (Siemens Healthineers, Erlangen, Germany) including T2‐weighted imaging (TR/TE 4000–6000/80–120 ms, FOV 220–256 mm, slice thickness 2–3 mm) and SWI (TR/TE 25–35/15–25 ms, FOV 200–240 mm, slice thickness 1.5–2 mm). Tumors were manually delineated on T2‐weighted images and coregistered to SWI using advanced normalization tools (ANTs). Intratumoral vessels were extracted from SWI using the Frangi vesselness filtering and represented as graphs with nodes at branch points and endpoints and edges along vessel segments. Node‐level, edge‐level, and graph‐level vascular features were processed by a GraphSAGE encoder to generate patient‐specific embeddings, which were compared to a learnable population template within the connectional vessel template (CVT) framework to quantify individual vascular atypicality. A Cox proportional hazards head integrated graph embeddings, template deviation, and demographic features to output risk scores. Model performance was evaluated using 10‐fold stratified cross‐validation for progression‐free survival (PFS) and overall survival (OS), with multivariable Cox regression and subgroup analyses across isocitrate dehydrogenase (IDH) mutation status and histological subtypes. A total of 193 patients were included (mean age 43.4 ± 14.0 years; 57.5% male). OS analysis included 182 patients (61 deaths), and PFS analysis included 170 patients (102 progression events). The CVT model achieved C‐indices of 0.812 for PFS and 0.839 for OS with significant risk stratification (PFS log‐rank p = 5.82 × 10 ⁻⁷ ; OS log‐rank p = 1.17 × 10 ⁻⁶ ). The CVT risk score independently predicted PFS (HR 1.77, p < 0.001) and OS (HR 1.44, p < 0.001) beyond age and sex. Subgroup analyses demonstrated consistent PFS discrimination in IDH‐wildtype tumors and glioblastoma (C‐index 0.677) and strong OS prediction in IDH‐mutant tumors (C‐index 0.850). Graph‐based modeling of SWI‐derived vascular topology provides robust, independent prognostic information for glioma survival using a single noncontrast MRI sequence.

Introduction: Acute encephalitis is a severe neurological complication whose association with SARS-CoV-2 infection is increasingly recognized. However, the precise pathophysiological mechanisms remain incompletely understood. Understanding the factors contributing to central nervous system involvement in COVID-19 is crucial for guiding clinical management and improving patient outcomes. Methods: This single-center, retrospective cohort study analyzed data from 450 adult critically ill patients with RT-qPCR-confirmed SARS-CoV-2 infection admitted to our ICU between May 2021 and March 2023. All SARS-CoV-2-positive patients with suspected CNS involvement were included and categorized into encephalitis-positive (E+, n = 38) and encephalitis-negative (E−, n = 58) groups according to neurological examination, imaging, and lumbar puncture findings during ventilator weaning. Key patient characteristics, laboratory parameters at ICU admission (including SARS-CoV-2 Ct values and D-dimer levels), and clinical outcomes were analyzed with appropriate statistical methods, including ROC curve analysis and Cox regression. Results: Patients in the E+ group, compared with the E− group, were significantly older (mean 69 ± 15 vs. 61 ± 12 years, p = 0.006) and exhibited significantly lower median SARS-CoV-2 Ct values (23.7 vs. 27.0, p < 0.001) indicative of higher viral loads. The median D-dimer levels were also significantly elevated in the E+ group (4.6 vs. 1.1, p < 0.001). Other baseline characteristics and inflammatory markers were comparable between groups. Patients with encephalitis experienced significantly longer mechanical ventilation durations (median 19 vs. 14 days, p = 0.006) and ICU stays (median 21 vs. 15 days, p = 0.009) compared to those without encephalitis. No significant difference was observed in overall mortality between the groups (50.0% vs. 56.9%, p = 0.507). Multivariate analysis identified lower Ct values (HR: 1.9, p = 0.032) and higher D-dimer levels (HR: 2.9, p < 0.010) at ICU admission as independent risk factors for encephalitis development. Conclusions: Our findings indicated that higher SARS-CoV-2 viral loads (lower Ct values), older age, and higher D-dimer levels were significantly associated with a greater risk of COVID-19-associated encephalitis in critically ill patients. These markers might aid in identifying patients at high risk of neurological complications, thereby facilitating earlier monitoring and potentially improving patient management. Further prospective studies are warranted to fully elucidate the pathophysiological mechanisms underlying this association.

Functional Near-Infrared Spectroscopy is (fNIRS) a non-invasive neuroimaging technique that monitors cerebral hemodynamic responses by measuring near-infrared (NIR) light absorption caused by changes in oxygenated and deoxygenated hemoglobin concentrations. While fNIRS has been widely used in cognitive and clinical neuroscience, a key challenge persists: the lack of practical tools required for calibrating source-detector separation (SDS) to maximize sensitivity at depth (SAD) for monitoring specific cortical regions of interest to neuroscience and neuroimaging studies. This study presents DrSVision version 1.0, a standalone software developed to address this limitation. Monte Carlo (MC) simulations were performed using segmented magnetic resonance imaging (MRI) data from eight cadaveric heads to realistically model light attenuation across anatomical layers. SAD of 10–20 mm with SDS of 19–39 mm was computed. The dataset was used to train a Gaussian Process Regression (GPR)-based machine learning (ML) model that recommends optimal SDS for achieving maximal sensitivity at targeted depths. The software operates independently of any third-party platforms and provides users with region-specific calibration outputs tailored for experimental goals, supporting more precise application of fNIRS. Future developments aim to incorporate subject-specific calibration using anatomical data and broaden support for diverse and personalized experimental setups. DrSVision represents a step forward in fNIRS experimentation.

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.

Background: Diffuse leptomeningeal glioneuronal tumors (DL-GNT) are rare glioneuronal neoplasms with oligodendroglioma-like cells. These tumors can present as a dominant intracranial mass or as a solitary spinal cord mass without leptomeningeal involvement. In this study, we aimed to determine the magnetic resonance imaging and histopathological features, treatment modalities, and clinical outcomes of the parenchymal forms of DL-GNTs. Methods: This is a retrospective three-center case series study of 5 patients with a confirmed parenchymal form of DLGTs, out of which 4 patients were adults. Brain and spinal cord MR imaging were performed in all patients at either 1.5 or 3T. The patients' age ranged from 5 years to 50 years with a mean age of 27.6 years at presentation. Results: Four of the tumors were located in the frontal lobe, and one in the tectum. They were usually solid-cystic enhancing tumors as the other mixed neuronal-glial tumors. All of the tumors had an extension to the superficial surface of a cerebral hemisphere. One had systemic bone metastases. The clinical signs and symptoms of the parenchymal form varied based on the location of the mass, in contrast to the leptomeningeal form associated with hydrocephalus. In one case, the tumor’s initial grade was defined as intermediate. The initial histopathology of the two cases was low-grade and no upgrade occurred in the follow-up period. In two cases, although the tumors were low grade initially, they progressed to an anaplastic form in the follow-up period. Conclusion: The parenchymal form of DL-GNTs is common in adults. Extension to the superficial surface of a cerebral hemisphere is a distinctive imaging feature. Systemic osseous metastasis may occur. Due to the presence of common histopathological features, including the biphasic composition of glial and neuronal cell elements and oligodendroglioma-like cells, a proposed classification approach might be more beneficial for the histopathological and imaging description, and management of the glioneuronal tumors with oligodendroglioma-like features.

BACKGROUND AND PURPOSE: IDH and TERT mutations might infiltratively manifest within normal-appearing white matter with specific phenotypes such as microstructural changes undetectable by standard MR imaging contrasts but potentially associable with DTI variables. The aim of this retrospective glioma study was to statistically investigate IDH and TERT associations and classifications with DTI reported microstructure in normal-appearing white matter. MATERIALS AND METHODS: Retrospective data from patients imaged between March 2012 and February 2016 were analyzed by grouping them as IDH–TERT subgroups and by IDH and TERT mutation status. DTI variables in the IDH-TERT subgroups were first identified by the Kruskal-Wallis test, followed by Dunn-Šidák multiple comparisons with Bonferroni correction. IDH and TERT mutations were compared with the Mann-Whitney U test. Classification by thresholding was tested using receiver operating characteristic analysis. RESULTS: Of 170 patients, 70 patients (mean age, 43.73 [SD, 15.32] years; 40 men) were included. Whole-brain normal-appearing white matter fractional anisotropy (FA) and relative anisotropy (RA) (P = .002) were significantly higher and the contralateral-ipsilateral hemispheric differences, ΔFA and ΔRA, (P < .001) were significantly lower in IDHonly patients compared with TERTonly, with a higher whole-brain normal-appearing white matter FA and RA (P = .01) and ΔFA and ΔRA (P = .002) compared to double positive patients. Whole-brain normal-appearing white matter ADC (P = .02), RD (P = .001), λ₂ (P = .001), and λ₃ (P = .001) were higher in IDH wild-type. Whole-brain normal-appearing white matter λ₁ (AD) (P = .003), FA (P < .001), and RA (P = .003) were higher, but Δλ₁ (P = .002), ΔFA, and ΔRA (P < .001) were lower in IDH mutant versus IDH wild-type. ΔFA (P = .01) and ΔRA (P = .02) were significantly higher in TERT mutant versus TERT wild-type. CONCLUSIONS: Axial and nonaxial diffusivities, anisotropy indices in the normal-appearing white matter and their interhemispheric differences demonstrated microstructural differences between IDH and TERT mutations, with the potential for classification methods.

Solitary necrotic nodule of the liver (SNNL) is a rare benign lesion with uncertain etiology characterized by a “completely necrotic core” and a hyalinized capsule containing elastin fibers (Journal of Clinical Pathology 36:1181–1183, 1983). We report herein a 26-year-old woman with a previous diagnosis of rheumatoid arthritis, systemic lupus erythematosus, and Sjögren’s syndrome and no history of malignancy who presented with a complaint of diarrhea of 1-year duration. In the abdominal ultrasound, multiple paraaortic, portocaval, and ileal lymphadenopathies (LAPs) have been found with the largest one being 2 cm in size. The biopsy of the iliac LAP showed reactive nodular hyperplasia. An abdominal CT disclosed an incidental hypoechoic, heterogenous mass sized 27 × 27 mm close to segment VI of the liver. A trucut biopsy of this lesion was made, and clinicopathologic features of the specimen were compatible with a solitary necrotic nodule of the liver. Here, we discuss the diagnosis and the clinical course of this rare entity in light of current literature.

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.

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 to accelerate acquiring 48×48 voxels (each of 0.25 ml spatial-resolution) without respiratory navigation implementations. The data was 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 the MRSI-FF (CV= 4.3 ±2.5%). Additionally, the matching level of 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 minutes 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.