simplification of care pathways for patients with rare brain tumors through artificial intelligence

Conditions: Brain Tumors

Summary: this study focuses on rare brain tumors, which are heterogeneous entities with different morphological, biological, and clinical characteristics. due to their rarity, many of these tumors fall under the rarecare definition of rare tumors. the main objective of the study is to standardize care models and pathways for patients with rare brain tumors, using artificial intelligence (ai) and machine learning (ml) techniques to identify specific predictors of postoperative outcomes. the study includes both retrospective and prospective phases, with the collection of clinical, cognitive, and psychological data at various time points. patients will undergo an early neuro-cognitive rehabilitation program using the rehacom software, which will be conducted at home. the goal is to improve the quality of life and care for patients through a multidisciplinary and innovative approach.

participants will be adults with rare brain tumors and will be enrolled at two neurosurgery centers in italy. the study aims to create a network of professionals specialized in predicting surgical outcomes, thereby improving the overall quality of care and the quality of life for patients. this study aims to improve the care and outcomes for patients with rare brain tumors (rbt) by standardizing clinical pathways and utilizing advanced technologies such as artificial intelligence (ai) and machine learning (ml). rare brain tumors, including astrocytomas, oligodendrogliomas, neuronal tumors, malignant meningiomas, and embryonal tumors, are defined as rare due to their low incidence (\<6 cases per 100,000 people/year). the study will be conducted in two phases: a retrospective phase and a prospective phase. the retrospective phase will involve the use of existing neurosurgical databases to implement ml algorithms. the prospective phase will include the collection of clinical, cognitive, and psychological data at multiple time points (pre-surgery, discharge, 3 months post-surgery, and 12 months post-surgery). patients will participate in an early neuro-cognitive rehabilitation program using the rehacom software, designed to enhance cognitive functions potentially affected by surgery. the rehabilitation will be conducted at the patient's home. the primary objective is to develop a common evaluation protocol that includes clinical, cognitive, psychological, and sociodemographic measures. secondary objectives include identifying predictors of surgical outcomes through retrospective and prospective studies and developing predictive models for rare brain tumors. the study will enroll approximately 200 adult patients from two neurosurgery centers in italy. inclusion criteria include adults (≥18 years) undergoing craniotomy for rare brain tumors, while exclusion criteria include patients undergoing stereotactic biopsy, those with psychiatric disorders, or those lacking the necessary technology for home-based rehabilitation. the ultimate goal is to create a multidisciplinary network of professionals specialized in predicting surgical outcomes, thereby improving the overall quality of care and the quality of life for patients with rare brain tumors.

Eligibility criteria:
inclusion criteria: * adults (age ≥18 years) * both sexes * patients with rare brain tumors (incidence \<6 cases per 100,000 people/year) * candidates for craniotomy for rare brain tumors * native italian speakers for cognitive and psychological evaluation and neuro-cognitive rehabilitation exclusion criteria: * patients undergoing stereotactic/frameless biopsy * patients with psychiatric disorders or on psychotropic medications * patients with known cognitive decline (not due to the lesion) * patients admitted on the same day as the surgery * patients with severe impairments referred to rehabilitation centers * patients without a windows pc or laptop with internet connection for neuro-cognitive rehabilitation

Keywords: rare brain tumors neurosurgery outcomes predictions machine learning artificial intelligence neurocognitive rehabilitation innovative models health care pathways astrocytic tumors of cns oligodendroglial tumors of cns ependymal tumors of cns neuronal and mixed neuronal-glial tumors choroid plexus carcinoma of cns malignant meningiomas embryonal tumors of cns