Spinal Diffuse Midline Glioma H3 K27M-Altered: Report of a Rare Tumor with Extracranial Skeletal Metastases and Review of Literature.

Diffuse midline glioma, H3 K27-altered is a rare and aggressive pediatric brain tumor with a grim prognosis. Diffuse midline glioma is characterized by specific molecular alterations, including H3 K27 mutations, and involves deep midline structures such as the brainstem, cerebellum, spinal cord, and thalamus. These tumors present with a classic triad of symptoms and have limited surgical options due to their challenging locations. Extra-neural metastases are an unusual occurrence in diffuse midline glioma and have been rarely described. Here we report a 17-year-old girl with spinal diffuse midline glioma, H3 K27M-mutant, who presented with multiple metastatic osseous lesions confirmed on biopsy of the thoracic vertebral lesion. Due to the rapid disease progression, the patient was recommended palliative therapy. Extra-neural metastases in diffuse midline glioma are rare, with only 16 reported patients, and no standard therapy exists. An accurate and early diagnosis is necessary to develop a personalized plan of treatment. Further research is needed to gain insights into the molecular pathology of diffuse midline glioma, H3 K27-altered, and improve the quality of life and the outcome of patients with this deadly disease.

Implications of use of different intraoperative ultrasound modalities during glioma surgery - A comparative study of factors affecting outcomes.

BACKGROUND: The main goal of glioma surgery is to remove the maximum amount of tumor without worsening the patient's neurological condition. Intraoperative ultrasound (US) imaging technologies (2D and 3D) are available to assist surgeons, providing real-time updates. Considering additional time, personnel, and cost, we investigate if comparable outcomes can be achieved using basic (2D) and advanced (3D) technology. OBJECTIVE: We propose predictive models for (i) glioma tumor resectability (ii) surgical outcome, and (iii) a model to predict the outcome of surgery aided with a particular ultrasound and compare outcomes between 2D and 3D US. METHODOLOGY: We used real-world surgery data from a tertiary cancer centre. Three groups of cases were analyzed (2D US used, 3D US used, and no US used during resection). The data analysis uses hypothesis testing, bootstrap sampling, and logistic regression. RESULTS: The preoperatively anticipated extent of tumor removal correlated with the postoperative MRI measurement of tumor removal for US-supported surgery (p=0.01) but not for no US-supported surgeries (p = 0.13). A combination of delineation, eloquence, and the multifocal/multicentric nature of the tumor effectively predicted resectability. The eventual outcome of surgery (actual extent of resection achieved) can be predicted by prior treatment status, delineation, eloquence, and satellite nodules. Based on our prediction model (training set of 350 cases and test of 40 cases of US-guided surgeries), we identify some cases where 3D US seems to offer superior EORs. CONCLUSION: The resectability of glioma tumors is crucial in determining surgical objectives, and the type of ultrasound used as support impacts tumor removal. The findings in this study aid informed decision-making and optimize imaging technology usage, providing a decision flow for selecting ultrasound based on tumor characteristics.

Imaging of central nervous system emergencies in oncology.

Central nervous system (CNS) may be predisposed to devastating complications in cancer patients which may add to morbidity and mortality in this group. Majority of the complications are vascular in nature due to the altered coagulation profile and pro-inflammatory state in these patients. However, there are a host of other conditions which may affect the clinical course of these patients including metabolic and toxic encephalopathies, infections, and paraneoplastic syndromes. Moreover, multimodality management of these patients, which is often used in majority of the cancers, exposes them to treatment related complications. This pictorial review aims to enlighten the reader regarding the various complications affecting the CNS as seen at our tertiary cancer care institute. We aim to highlight the emergent nature of these complications and the need to identify them quickly and accurately on imaging which helps to institute early appropriate management and prevents further morbidity and mortality.

Multiparametric Magnetic Resonance Imaging Correlates of Isocitrate Dehydrogenase Mutation in WHO high-Grade Astrocytomas.

Purpose and background: Isocitrate dehydrogenase (IDH) mutation and O-6 methyl guanine methyl transferase (MGMT) methylation are surrogate biomarkers of improved survival in gliomas. This study aims at studying the ability of semantic magnetic resonance imaging (MRI) features to predict the IDH mutation status confirmed by the gold standard molecular tests. Methods: The MRI of 148 patients were reviewed for various imaging parameters based on the Visually AcceSAble Rembrandt Images (VASARI) study. Their IDH status was determined using immunohistochemistry (IHC). Fisher's exact or chi-square tests for univariate and logistic regression for multivariate analysis were used. Results: Parameters such as mild and patchy enhancement, minimal edema, necrosis < 25%, presence of cysts, and less rCBV (relative cerebral blood volume) correlated with IDH mutation. The median age of IDH-mutant and IDH-wild patients were 34 years (IQR: 29−43) and 52 years (IQR: 45−59), respectively. Mild to moderate enhancement was observed in 15/19 IDH-mutant patients (79%), while 99/129 IDH-wildtype (77%) had severe enhancement (p-value <0.001). The volume of edema with respect to tumor volume distinguished IDH-mutants from wild phenotypes (peritumoral edema volume < tumor volume was associated with higher IDH-mutant phenotypes; p-value < 0.025). IDH-mutant patients had a median rCBV value of 1.8 (IQR: 1.4−2.0), while for IDH-wild phenotypes, it was 2.6 (IQR: 1.9−3.5) {p-value = 0.001}. On multivariate analysis, a cut-off of 25% necrosis was able to differentiate IDH-mutant from IDH-wildtype (p-value < 0.001), and a cut-off rCBV of 2.0 could differentiate IDH-mutant from IDH-wild phenotypes (p-value < 0.007). Conclusion: Semantic imaging features could reliably predict the IDH mutation status in high-grade gliomas. Presurgical prediction of IDH mutation status could help the treating oncologist to tailor the adjuvant therapy or use novel IDH inhibitors.