大場 茂生

Neuronal activity is known to promote glioma growth, yet whether inhibitory circuits can oppose this effect has remained unclear. Here, we show that adult gliomas receive functional γ-aminobutyric acid (GABAergic) synaptic input from local inhibitory interneurons and that this input acts as a tumor-suppressive circuit signal. Enhancing inhibitory tone, genetically or pharmacologically, restrains tumor proliferation and prolongs survival, whereas disrupting inhibitory synaptic output accelerates tumor growth. Mechanistically, inhibitory circuit activation suppresses tumor calcium dynamics, and calcium gain- and loss-of-function experiments establish these dynamics as causal regulators of proliferation and survival. Yes-associated protein 1 (YAP1) and mechanistic target of rapamycin (mTOR) emerge as calcium-coupled oncogenic programs attenuated by inhibitory activation. Thus, adult glioma progression is governed not simply by neuronal activity but by a balance between growth-promoting and growth-restraining circuit influences. These findings define inhibitory input as a suppressive component of the glioma ecosystem and suggest that strengthening inhibitory tone may offer a therapeutic strategy.

Medulloblastoma (MB) is a biologically and clinically heterogeneous pediatric brain tumor. However, large-scale molecular subgrouping studies have mainly been conducted in Western populations, and comprehensive data from Asia are limited. To address this gap, we analyzed 242 MB cases collected from 39 institutions through the Japan Pediatric Molecular Neuro-Oncology Group, performing centralized molecular classification using NanoString-based gene expression profiling, DNA methylation arrays, and multiplex ligation-dependent probe amplification (MLPA)-based copy number profiling, supplemented by targeted sequencing. The subgroup distribution was 16.1% WNT, 24.8% SHH, 17.4% Group 3, and 41.7% Group 4. CTNNB1 mutations and monosomy 6 characterized all WNT cases, whereas MYCN amplification and TP53 mutations were independent adverse markers in SHH MB. Group 3 showed the worst survival, with MYC amplification and metastasis as poor prognostic factors. In Group 4, large cell/anaplastic histology predicted poor outcomes, whereas chromosome 11 loss was correlated with a favorable prognosis. Whole chromosomal aberration-defined favorable-risk patterns consistently indicate improved outcomes in non-WNT/non-SHH MBs. We also developed a simplified MLPA-based classifier targeting six loci on chromosomes 7, 8, and 11 (SEE-6-CNA), which enabled robust and clinically feasible prognostic stratification. Overall, our findings confirm that the molecular subgroup-specific features of Japanese MBs are largely concordant with global observations and that SEE-6-CNA provides a cost-effective tool to support individualized treatment planning, particularly in resource-limited settings.

PURPOSE: This study aimed to establish and evaluate two evidence-based reconstruction protocols for [18F]fluciclovine PET on a high-resolution dedicated head PET system: a time-efficient protocol for routine clinical use, and a high-quality protocol designed to maximize small-lesion detectability. METHODS: A brain-tumor phantom (target-to-background ratio, 5:1) was scanned on a dedicated head PET scanner (BresTome, Shimadzu). Using a 60-min list-mode acquisition, parameters were optimized for two visually defined pathways (10-min clinical-efficiency; 30-min high-quality). The optimization sequence involved optimizing the relaxation factor (β) using mean percent contrast (%contrastmean), followed by a comparison of post-reconstruction filters (non-local means [NLM] and Gaussian) by maximizing a local contrast-to-noise ratio (CNR), guided by the Rose criterion. The final protocols were evaluated against Japanese brain-tumor phantom criteria for key performance metrics, including maximum percent contrast (%contrastmax), relative recovery coefficient (RC), quantitative accuracy (SUVTOT), and uniformity (SDΔSUVmean). RESULTS: Two distinct protocols were established. The 10-min clinical-efficiency protocol was optimized with β = 60 and an NLM filter (intensity 1.5), which provided the best CNR for the 7.5-mm sphere. The 30-min high-quality protocol was optimized with β = 70 and an NLM filter (intensity 1.0), which yielded the highest CNR for the 5-mm sphere. The 30-min protocol was required for enhanced visibility of the 5-mm sphere. Both protocols met the Japanese criteria for %contrastmax, relative RC, and SUVTOT, whereas SDΔSUVmean did not meet the criterion. Supplementary reconstructions of the full 60-min dataset met the SDΔSUVmean criterion. In two representative clinical cases, application of the optimized protocols yielded clinically interpretable images with clear visualization of tumor uptake. CONCLUSION: This study establishes a dual-pathway framework for [18F]fluciclovine PET. We recommend the 30-min high-quality protocol (β = 70, NLM intensity = 1.0) as the preferred option when feasible to maximize small-lesion detectability. The 10-min clinical-efficiency protocol (β = 60, NLM intensity = 1.5) serves as a practical, time-saving alternative for patients with limited tolerance. This approach provides a foundation for personalizing clinical protocols based on specific imaging needs and highlights the importance of standardizing uniformity assessment using an appropriate longer-duration reference acquisition for modern high-resolution PET systems.

Research on foundation models is actively progressing. The segment anything model (SAM) and MedSAM are representative foundation models for image segmentation. Recently, low-rank adaptation (LoRA) has been developed, allowing parameter updates without retraining the entire model, thus solving the problem with large data and time required for task-specific fine-tuning. Although many studies have used public databases, few have focused on local data. Moreover, to our knowledge, no studies have fine-tuned MedSAM using LoRA. We aimed to evaluate SAM, MedSAM, and their LoRA-tuned variants (SAM-LoRA and MedSAM-LoRA) using brain magnetic resonance images of gliomas from five centers in Japan and to compare their performance. We used 2D-based fluid-attenuated inversion recovery axial images and conducted parameter optimization based on four-fold cross-validation (189 cases) and external test evaluation (75 cases) using cases collected retrospectively. Dice coefficients, intersection over union (IoU), and the 95% Hausdorff distance (HD95) were used to evaluate the performance of SAM, MedSAM, SAM-LoRA, and MedSAM-LoRA. Additionally, subgroup evaluations were performed according to scanner manufacturer, glioma location, and calcification status. In the external test at the case level using SAM-LoRA and MedSAM-LoRA, the Dice coefficients/IoU/HD95 were 0.9166/0.8506/1.3517 and 0.9051/0.8342/1.8061, respectively. Both SAM-LoRA and MedSAM-LoRA demonstrated significantly higher Dice coefficients and IoU, as well as significantly lower HD95 values, compared with SAM and MedSAM. Subgroup evaluations also showed highly accurate extraction across different scanner manufacturers, glioma locations, and calcification statuses. SAM-LoRA and MedSAM-LoRA achieved high accuracy on an externally evaluated dataset, suggesting potential utility.

Ependymoma-like tumor with mesenchymal differentiation (ELTMD) is a recently proposed, but not yet formally defined, entity that is not recognized in the 2021 World Health Organization (WHO) classification of central nervous system tumors. Although it shares molecular features, such as ZFTA fusion, with ependymomas, it exhibits distinct histopathological and epigenetic profiles. Herein, we report the case of a 5-year-old girl with a supratentorial tumor harboring the ZFTA::NCOA2 fusion. Histopathology revealed atypical features including mesenchymal and undifferentiated components, which overlapped with those of ependymomas. DNA methylation profiling using two independent classifiers (DKFZ and NIH) yielded no matches, indicating that the tumor did not belong to any recognized CNS class. The failure of subclass assignment by both classifiers suggests that ELTMD represents a potentially epigenetically distinct subgroup. Despite being unclassifiable by the current WHO criteria, the tumor shared features with previously reported ELTMDs, supporting its recognition as an emerging tumor. This highlights the need for additional cases to refine the diagnosis, classification, and future therapeutic strategies.