Abdullah Mohammad Al Fareed has graduated from College of Medicine from University- Imam Abdulrahman Bin Faisal University. He is currently pursuing his Pediatrics Hemato- Oncology Fellowship in King Fahad Specialist Hospital.
Embryonal tumors constitute approximately 15% of all primary CNS tumors occurring in patient less than 18 years old. The most common embryonal tumors are: Medulloblastoma (MB) (62%), Atypical Teratoid Rhabdoid Tumors (ATRT) (15%), CNS Primitive Neuroectodermal Tumors (PNET) (14.9%), other embryonal tumors (8%). MB The most common malignant brain tumor of childhood occurs in the posterior fossa, like other embryonal tumors may metastasize either early or late in the disease course. The aim is to study the treatment outcome of medulloblastoma in children and adolescents treated at King Fahad Specialist Hospital Dammam from 2012 to 2016. The objective is to study the clinical symptoms and signs of medulloblastoma in our cohort, histopathological subtypes, evaluate approach to therapy (surgery, chemotherapy, and radiation therapy), to evaluate all the complications related to the disease and/or to the treatment, distribution and incidence of MB by sex, age and histologic types, calculate the relapse rate, correlation between the above points and the outcome, identify inherited syndromes associated with medulloblastoma in our cohort study. It’s a retrospective chart review for all children’s less than 16 years of age diagnosed with MB from January 2012 till December 2016. Survival curves were generated using Kaplan-Meier method. Overall Survival (OS) is defining as time from diagnosis until death from any cause. Event Free Survival (EFS) is defining as time from diagnosis until the occurrence of event. Events are failure to achieve remission, relapse, or death from any cause.
Hyeong Cheol Moon is currently working as a Medical Physicist at Chungbuk National University Hospital. He has published more than 10 papers in reputed journals. He is interested in ultra-high field 7T MRI, quality assurance for gammaknife radiosurgery and artificial neural network.
Predictions of patient outcomes after radiotherapy are essential to medical practice with the neurosurgeon, oncologist and medical physicist. Stereotactic Radiosurgery (SRS) is commonly used for brain metastases that are 3 cm or smaller in maximum diameter. Fractionation was introduced that the total dose of radiation is divided into small doses over a period of several days; there are fewer toxic effects on healthy cells. However, LINAC-based SRS have reported some studies, but Gammaknife Radiosurgery (GKRS) based has been rarely reported. We employed neural network approach towards predicting the outcomes after hypo fractionated GKRS to large brain metastatic brain tumors (>3 cm). Features engineering in this database included standard clinical and GKRS treatments parameters. A neural network consists of feed-forward which is the most well-known many applications in the functional approximation and back-propagation network is used for training. Our training process was performed Keras tools of categorical cross-entropy in lost function and Stochastic Gradient Descent (SGD) for optimization. A learning rate of 1.0x10 -6 . The best accuracy had around 95% and error under 0.05 in multi-layer neural networks. And single neural networks showed around 90% accuracy. This neural network approach was able to provide the best prediction of large brain tumor outcomes under hypo fractionated treatment. Furthermore, we could demonstrate a paradigm for personalized treatments for further development tools in medical care.