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The glioma boundary is difficult to identify during surgery due to the infiltrative characteristics of tumor cells. In order to ensure a full resection rate and increase the postoperative survival of patients, it is often necessary to make an expansion range resection, which may have harmful effects on the quality of the patient's survival. A full-Stokes laser-induced breakdown spectroscopy (FSLIBS) theory with a corresponding system is proposed to combine the elemental composition information and polarization information for glioma boundary detection. To verify the elemental content of brain tissues and provide an analytical basis, inductively coupled plasma mass spectrometry (ICP-MS) and LIBS are also applied to analyze the healthy, boundary, and glioma tissues. Totally, 42 fresh tissue samples are analyzed, and the Ca, Na, K elemental lines and CN, C molecular fragmental bands are proved to take an important role in the different tissue identification. The FSLIBS provides complete polarization information and elemental information than conventional LIBS elemental analysis. The Stokes parameter spectra can significantly reduce the under-fitting phenomenon of artificial intelligence identification models. Meanwhile, the FSLIBS spectral features within glioma samples are relatively more stable than boundary and healthy tissues. Other tissues may be affected obviously by individual differences in lesion positions and patients. In the future, the FSLIBS may be used for the precise identification of glioma boundaries based on polarization and elemental characterizing ability.
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http://dx.doi.org/10.1364/BOE.492983 | DOI Listing |
J Imaging Inform Med
September 2025
A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA.
High-resolution magnetic resonance spectroscopic imaging (MRSI) plays a crucial role in characterizing tumor metabolism and guiding clinical decisions for glioma patients. However, due to inherently low metabolite concentrations and signal-to-noise ratio (SNR) limitations, MRSI data are often acquired at low spatial resolution, hindering accurate visualization of tumor heterogeneity and margins. In this study, we propose a novel deep learning framework based on conditional denoising diffusion probabilistic models for super-resolution reconstruction of MRSI, with a particular focus on mutant isocitrate dehydrogenase (IDH) gliomas.
View Article and Find Full Text PDFBioengineering (Basel)
August 2025
School of Mechanical Engineering, Hubei University of Technology, Wuhan 430068, China.
Cell confluence and number are critical indicators for assessing cellular growth status, contributing to disease diagnosis and the development of targeted therapies. Accurate and efficient cell segmentation is essential for quantifying these indicators. However, current segmentation methodologies still encounter significant challenges in addressing multi-scale heterogeneity, poorly delineated boundaries under limited annotation, and the inherent trade-off between computational efficiency and segmentation accuracy.
View Article and Find Full Text PDFNeuro Oncol
August 2025
Department of Neurosurgery, Graduate School of Medicine, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan.
Background: The 5th edition of the World Health Organization Classification of Tumors of the Central Nervous System introduced a subclassification of tumors based on key molecular markers. In adult-type diffuse gliomas, isocitrate dehydrogenase (IDH) and telomerase reverse transcriptase (TERT) promoter mutations play pivotal roles in the molecular classification. This study developed a rapid genotyping system using GeneSoC®, a real-time polymerase chain reaction (PCR) platform with microfluidic thermal cycling capable of completing 50 cycles of PCR within 20 min.
View Article and Find Full Text PDFNeurooncol Pract
August 2025
The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Background: The Response Assessment in Pediatric Neuro-Oncology (RAPNO) working group for diffuse intrinsic pontine glioma (DIPG) recently published its recommendations. We aim to test the operative performance of the RAPNO DIPG criteria imaging component by retrospectively applying it to a patient sample from the International DIPG/DMG Registry (IDIPGR).
Methods: Longitudinal MRIs for 46 patients were independently reviewed by 2 pediatric neuro-radiologists.
BMC Med Imaging
July 2025
Neurosurgery Department, Medicine Faculty, University of Szeged, Szeged, Hungary.
Background: Glioblastoma is the most aggressive and rapidly growing type of central nervous system tumor. Despite advancements in imaging, no objective measurement for predicting the true extent of glioblastoma has been established. Compared with contrast-enhanced magnetic resonance imaging (MRI), fluid-attenuated inversion recovery (FLAIR) imaging is believed to be more sensitive for detecting infiltrated tumor cells.
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