Classification of brain lesions using a machine learning approach with cross-sectional ADC value dynamics.

Diffusion-weighted imaging (DWI) and its numerical expression via apparent diffusion coefficient (ADC) values are commonly utilized in non-invasive assessment of various brain pathologies. Although numerous studies have confirmed that ADC values could be pathognomic for various ring-enhancing lesions (RELs), their true potential is yet to be exploited in full. The article was designed to introduce an image analysis method allowing REL recognition independently of either absolute ADC values or specifically defined regions of interest within the evaluated image. For this purpose, the line of interest (LOI) was marked on each ADC map to cross all of the RELs' compartments. Using a machine learning approach, we analyzed the LOI between two representatives of the RELs, namely, brain abscess and glioblastoma (GBM). The diagnostic ability of the selected parameters as predictors for the machine learning algorithms was assessed using two models, the k-NN model and the SVM model with a Gaussian kernel. With the k-NN machine learning method, 80% of the abscesses and 100% of the GBM were classified correctly at high accuracy. Similar results were obtained via the SVM method. The proposed assessment of the LOI offers a new approach for evaluating ADC maps obtained from different RELs and contributing to the standardization of the ADC map assessment.

Spinal Metastasis in a Patient with Supratentorial Glioblastoma with Primitive Neuronal Component: A Case Report with Clinical and Molecular Evaluation.

Glioblastoma (GBM) is regarded as an aggressive brain tumor that rarely develops extracranial metastases. Despite well-investigated molecular alterations in GBM, there is a limited understanding of these associated with the metastatic potential. We herein present a case report of a 43-year-old woman with frontal GBM with primitive neuronal component who underwent gross total resection followed by chemoradiation. Five months after surgery, the patient was diagnosed with an intraspinal GBM metastasis. Next-generation sequencing analysis of both the primary and metastatic GBM tissues was performed using the Illumina TruSight Tumor 170 assay. The number of single nucleotide variants observed in the metastatic sample was more than two times higher. Mutations in TP53, PTEN, and RB1 found in the primary and metastatic tissue samples indicated the mesenchymal molecular GBM subtype. Among others, there were two inactivating mutations (Arg1026Ile, Trp1831Ter) detected in the NF1 gene, two novel NOTCH3 variants of unknown significance predicted to be damaging (Pro1505Thr, Cys1099Tyr), one novel ARID1A variant of unknown significance (Arg1046Ser), and one gene fusion of unknown significance, EIF2B5-KIF5B, in the metastatic sample. Based on the literature evidence, the alterations of NF1, NOTCH3, and ARID1A could explain, at least in part, the acquired invasiveness and metastatic potential in this particular GBM case.

Small RNA Sequencing Identifies a Six-MicroRNA Signature Enabling Classification of Brain Metastases According to their Origin.

BACKGROUND/AIM: Brain metastases (BMs) are the most frequent intracranial tumors in adults and one of the greatest challenges for modern oncology. Most are derived from lung, breast, renal cell, and colorectal carcinomas and melanomas. Up to 14% of patients are diagnosed with BMs of unknown primary, which are commonly characterized by an early and aggressive metastatic spread. It is important to discover novel biomarkers for early identification of BM origin, allowing better management of patients with this disease. Our study focused on microRNAs (miRNAs), which are very stable in frozen native and FFPE tissues and have been shown to be sensitive and specific diagnostic biomarkers of cancer. We aimed to identify miRNAs with significantly different expression in the five most frequent groups of BMs and develop a diagnostic classifier capable of sensitive and specific classification of BMs. MATERIALS AND METHODS: Total RNA enriched for miRNAs was isolated using the mirVana miRNA Isolation Kit from 71 fresh-frozen histopathologically confirmed BM tissues originating in 5 cancer types. Sequencing libraries were prepared using the QIAseq miRNA Library Kit and sequenced on the NextSeq 500 platform. MiRNA expression was further validated by RT-qPCR. RESULTS: Differential analysis identified 373 miRNAs with significantly different expression between 5 BM groups (p<0.001). A classifier model was developed based on the expression of 6 miRNAs (hsa-miR-141-3p, hsa-miR-141-5p, hsa-miR-146a-5p, hsa-miR-194-5p, hsa-miR-200b-3p and hsa-miR-365b-5p) with the ability to correctly classify 91.5% of samples. Subsequent validation confirmed both significantly different expression of selected miRNAs in 5 BM groups as well as their diagnostic potential. CONCLUSION: To date, our study is the first to analyze miRNA expression in various types of BMs using small RNA sequencing to develop a diagnostic classifier and, thus, to help stratify BMs of unknown primary. The presented results confirm the importance of studying the dysregulated expression of miRNAs in BMs and the diagnostic potential of the validated 6-miRNA signature.

Blood-Brain Barrier Alterations and Edema Formation in Different Brain Mass Lesions.

Differential diagnosis of brain lesion pathologies is complex, but it is nevertheless crucial for appropriate clinical management. Advanced imaging methods, including diffusion-weighted imaging and apparent diffusion coefficient, can help discriminate between brain mass lesions such as glioblastoma, brain metastasis, brain abscesses as well as brain lymphomas. These pathologies are characterized by blood-brain barrier alterations and have been extensively studied. However, the changes in the blood-brain barrier that are observed around brain pathologies and that contribute to the development of vasogenic brain edema are not well described. Some infiltrative brain pathologies such as glioblastoma are characterized by glioma cell infiltration in the brain tissue around the tumor mass and thus affect the nature of the vasogenic edema. Interestingly, a common feature of primary and secondary brain tumors or tumor-like brain lesions characterized by vasogenic brain edema is the formation of various molecules that lead to alterations of tight junctions and result in blood-brain barrier damage. The resulting vasogenic edema, especially blood-brain barrier disruption, can be visualized using advanced magnetic resonance imaging techniques, such as diffusion-weighted imaging and apparent diffusion coefficient. This review presents a comprehensive overview of blood-brain barrier changes contributing to the development of vasogenic brain edema around glioblastoma, brain metastases, lymphomas, and abscesses.

Prolonged survival in patients with local chronic infection after high-grade glioma treatment: Two case reports.

High-grade gliomas are primary brain tumors with poor prognosis, despite surgical treatment followed by radiotherapy and concomitant chemotherapy. We present two cases of long-term survival in patients treated for high-grade glioma and concomitant prolonged bacterial wound infection. The first patient treated for glioblastoma IDH-wildtype had been without disease progression for 61 months from the first resected recurrence. Despite incomplete chemotherapy-induced myelosuppression in the second patient with anaplastic astrocytoma IDH-mutant, she died without disease relapse after 14 years from the diagnosis due to other comorbidities. We assume that the documented prolonged survival could be related to the bacterial infection.