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New Approaches in Machine-based Image Analysis for Medical Oncology
Published in K. Gayathri Devi, Kishore Balasubramanian, Le Anh Ngoc, Machine Learning and Deep Learning Techniques for Medical Science, 2022
E. Francy Irudaya Rani, T. Lurthu Pushparaj, E. Fantin Irudaya Raj, M. Appadurai
In another report, Deepak et al., [24] concentrated on the classifications of different brain cancers, primary tumor, malignant tumors, and pituitary. The suggested model employed a preexisting GoogleNet with changes at the frequency maximum for various sorts of tumor categorization. The GoogleNet deep neural network based on CNN achieves an increase in the precision of 92.25% which also improved the multiclass SVM to 97.82%. A supervised technique to identify brain malformation in MRI was present in three main steps. The first objective is a formulation of the CNN model. The second is to divide the image set by the k-mean algorithm. The third is the classification of brain components as normal or abnormal classes as per a developed CNN model [25]. A deep-learning model is adopted by Ren and his co-workers [26]. The author constructs a histogram equalization for the relevant data in earlier studies. The hybrid approach was adopted by combining Weighed fuzzy kernel clustering (WKFCOM) and the Fuzzy Cmean kernel method (KFRCOM). The research showed that with 2,36% lower error rates, WKFCOM performs better than KFCOM. A novel method using Template-based K-mean clustering, as opposed to C-mean algorithms from FUZZY [27]. This procedure divides the MRI pictures into three separate clusters: White Matter, Gray Matter, and brain fluid. The technology claims that the Fuzzy C-mean method is quantitatively and qualitatively better.
Hybrid Nanosystems
Published in Carla Vitorino, Andreia Jorge, Alberto Pais, Nanoparticles for Brain Drug Delivery, 2021
Pablo Vicente Torres-Ortega, Laura Saludas, Jon Eneko Idoyaga, Carlos Rodríguez-Nogales, Elisa Garbayo, María José Blanco-Prieto
Brain cancers are neoplasms located in the central nervous system (CNS) characterised by high mortality and poor prognosis. Glioblastoma multiforme (GBM) is the most common and aggressive type among all brain tumours, representing almost 30% of these and 80% of all the malignant ones [5]. Current treatment options are limited in their effectiveness, requiring the development of advanced tumour imaging techniques as well as more effective and less toxic therapeutic strategies [6]. In this regard, HNs may bring new opportunities to improve brain cancer management, overcoming the shortcomings associated with current diagnostic and therapeutic approaches. As shown in Fig. 2A, HNs hold potential for improving the sensitivity and resolution of tumour-imaging agents as well as for increasing chemotherapy efficacy. In fact, there are already Food and Drug Administration (FDA)-approved nanoparticulate systems available for clinical use, such as Feridex (nanosized iron oxide crystals coated with dextran) [7, 8].
The Power of Patient Advocacy in Pediatric Neuro-Oncology
Published in David A. Walker, Giorgio Perilongo, Roger E. Taylor, Ian F. Pollack, Brain and Spinal Tumors of Childhood, 2020
Kathy Oliver, Susan Awrey, Mark Brougham, Gloria Garcia Castellvi, Anita Granero, Rakesh Jalali, Sacha Langton-Gilks, Yuko Moue, Kathy Riley, Bonita Suckling, Hisato Tagawa, Mohammed Raees Tonse
Brain cancer is considered a rare cancer, even though brain and spinal tumors (central nervous system [CNS] tumors) represent the most common solid tumor in children. It is also considered amongst the deadliest of cancers. For example, in the UK, while there are approximately 400 new cases of pediatric brain and CNS tumors annually,5 they are the biggest childhood cancer killer.6
Advances in therapeutic targeting of immune checkpoints receptors within the CD96-TIGIT axis: clinical implications and future perspectives
Published in Expert Review of Clinical Immunology, 2022
Pooya Farhangnia, Mahzad Akbarpour, Mahboubeh Yazdanifar, Amir Reza Aref, Ali-Akbar Delbandi, Nima Rezaei
Brain cancer is the first leading cause of cancer death among men younger than 40 years and women younger than 20 years [2]. Recently, CD96, TIGIT, and their ligand CD155, as a target for cancer immunotherapy in glioma, have been considered [83,95–97]. Findings have shown CD96 up-regulated expression in grade IV and isocitrate dehydrogenase (IDH)-wild type glioma, CD96 higher expression mesenchymal-molecular subtype glioma, positive correlation between CD96 expression and immune functions, CD96 negative relationship with IgG and interferon levels, and worse prognosis in association with CD96 higher expression [95,96]. There was a strong direct correlation between CD96 expression and glioma infiltrating-immune cells, including CD8+ T cells, Tregs, macrophages, neutrophils, and dendritic cells (DCs) [95,96]. TIGIT and PD-1 co-expression have been demonstrated in glioma tumor-infiltrating lymphocytes. Using a dual treatment regimen including anti-TIGIT and anti-PD-1 led to better survival than anti-PD-1 or anti-TIGIT monotherapy, increased IFN-γ producing CD8+ T cells, and promoted immune cell tumor-infiltration, and reduced tumor-infiltrating dendritic cells [97]. U87MG glioblastoma cell line and expressed membrane-bound and soluble CD155 [98]. CD155-mediated tumor cell invasion and migration in glioblastoma have been demonstrated [55,99]. There is a significant correlation between CD155 expression and poor prognosis in low-grade glioma patients [97]. Reduced migration of U87MG cells was shown following knockdown of CD155 [55].
A Meta-Analysis of Calcium Intake and Risk of Glioma
Published in Nutrition and Cancer, 2022
Glioma and meningioma are the two most prevalent forms of primary central nervous system tumors, accounting for more than 80% of all cases (1). Glioma is a tumor that originates from brain glial cells and is the most common in primary brain tumors (2). Gliomas have a reasonably high incidence of 4–5/100,000 persons each year, with the highest occurrence in the sixth decade of life (3, 4). Aside from ionizing radiation and some genetic abnormalities, the risk factors for brain cancer remain unknown. Furthermore, other potential risk factors include exposure to chemical carcinogens in the environment and exposure to n-nitroso compounds in dietary factors (5–7). Despite the low frequency of adult brain cancer, the prognosis for brain cancer (particularly glioma) is dismal (8). Therefore, preventing the progression of glioma has become an important strategy to prevent and treat glioma.
Recent advances in iron oxide nanoparticles for brain cancer theranostics: from in vitro to clinical applications
Published in Expert Opinion on Drug Delivery, 2021
Roghayeh Sheervalilou, Milad Shirvaliloo, Saman Sargazi, Habib Ghaznavi
Despite years of research, diagnosis and treatment of tumors confined to the neurocranium is still an unclear path that might lead to vanity [1]. In some instances, the tumor occurs adjacent to critical functional structures within the brain, making the diagnosis a much more demanding task [4]. The current conventional diagnostic methods for brain cancer include noninvasive imaging techniques and more invasive tests like tissue biopsy. In most of the cases, a biopsy is merely used to confirm the soundness of imaging results. A rather invasive method, biopsy may also be useful in the treatment of certain malignancies [1,4]. Techniques such as CT, PET, MRI, and ultrasound stand among the most frequently used methods for detecting tumors [46–49]. Several confounding factors might actually have a negative impact on the efficiency of imaging methods. Edema or retention of fluid in the tumor environment is one such factor that often impairs the exact discrimination of tumor margins. There is also the resolute BBB in action that can cause a torrent of problems in the proper delivery of contrast agents toward the tumors [4].