World Neurosurg
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Tumors that take up and metabolize 5-aminolevulinic acid emit bright pink fluorescence when illuminated with blue light, aiding surgeons in identifying the margin of resection. The adoption of this method is hindered by the blue light illumination, which is too dim to safely operate under and therefore necessitates switching back and forth from white-light mode. The aim of this study was to examine the addition of an optimized secondary illuminant adapter to improve usability of blue-light mode without degrading tumor contrast. ⋯ Addition of a secondary illuminant may mitigate surgeon complaints that the operative field is too dark under the blue light illumination required for 5-aminolevulinic acid fluorescence guidance by providing improved color rendering index without completely sacrificing tumor-to-background color contrast.
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The T2-FLAIR mismatch sign is a useful imaging sign in clinical magnetic resonance imaging studies for detecting isocitrate dehydrogenase (IDH)-mutant 1p/19q non-codeleted astrocytomas. However, the association between the mismatch sign and pathologic findings is poorly understood. Therefore, the aim of this study was to elucidate the relationship of histopathologic and radiologic features with the mismatch sign in IDH-mutant 1p/19q non-codeleted astrocytomas. ⋯ This study provides evidence that a region-dependent microstructural difference could reflect the mismatch sign in IDH-mutant 1p/19q non-codeleted astrocytomas. Core of the mismatch sign characteristically had microcystic changes accompanied by higher ADC values, whereas Rim had abundant neuroglial fibrils and cellularity accompanied by lower ADC values.
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This study describes a distinct magnetic resonance imaging (MRI) feature, placing emphasis on fluid-attenuation inversion recovery (FLAIR) and contrast-enhanced T1-weighted (T1C) images for the preoperative differentiation of glioblastoma (GBM) from primary central nervous system lymphoma (PCNSL). ⋯ The SNEPGF sign is effective in identifying GBM from PCNSL, especially with high specificity.
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Ability to thrive after invasive and intensive treatment is an important parameter to assess in patients with glioblastoma multiforme (GBM). Karnofsky Performance Status (KPS) is used to identify those patients suitable for postoperative radiochemotherapy. The aim of the present study is to investigate whether machine learning (ML)-based models can reliably predict patients' KPS 6 months after surgery. ⋯ Two robust ML-based prediction models were successfully trained and internally validated. Considerable effort remains to improve the interpretation of the results when these predictions are used in a patient-centered care context.
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This paper uses head and neck magnetic resonance angiography (MRA) images in the diagnosis of acute ischemic stroke (AIS), as well as the neurologic rehabilitation and the effect of rehabilitation treatment in patients with acute stroke. ⋯ Examination can effectively assess cerebral hemodynamic changes, the severity of ischemia, and accurately distinguish between infarct area and penumbra. MRA images of the head and neck can accurately detect the location and degree of cerebral artery stenosis. The combination of the two methods can not only accurately diagnose AIS, but also evaluate the condition and efficacy of the disease, and provide an imaging basis for the clinical choice of reasonable treatment options. Comprehensive rehabilitation care can significantly improve the neurologic function and quality of life of prospective patients.