Neurosurgical medical image processing & innovations for imaging intracranial tumors

Abstract

Meningiomas make up about 20% of all intracranial tumors in men and 38% in women. Its prevalence is estimated at 97.5/100,000 with 2 and 5 year survival rates at 81% and 69%. Meningiomas make up 37.6% of all primary CNS tumors and 53.3% of all benign CNS tumors. Meningiomas are also the most common central nervous system tumors. The majority of meningiomas are benign in nature, their slow growth results in very gradual symptoms that remain unnoticed until tumors grow much larger in size . These usually come to the attention of patients when they experience cranial neuropathies (i.e. vision loss), seizures and hemiparesis which can sometimes stem from the pressure being exerted on regions of the brain. Diagnostic imaging of meningiomas is conducted through MR imaging before embolization and resection. Additional MR and histological imaging is conducted after resection. Surgical resection remains the golden clinical standard for treating large, symptomatic, and highly vascularized meningiomas, with radiosurgery used as an alternative for small, recurrent, or residual tumors. Preoperative embolization is a neoadjuvant therapy that constitutes a minimally invasive procedure in which embolic agents are delivered via a catheter to occlude arterial supply to tumors. The rationale for preoperative embolization has traditionally been to minimize intraoperative blood loss during surgical resection of highly vascular tumors. Systematic reviews have demonstrated that intraoperative blood loss is an unreliable metric as access to tumors and inaccurate measurements make this an erroneous measure. There is currently no tool to intraoperatively quantify the percent of the tumor that has been embolized, forcing surgeons to visually assess angiography data to determine success. This subjective endpoint results in poor reproducibility and limits the ability to automate future tools to optimize the technique. There is a clear need for the creation of an intraoperative image-processing tool to rapidly and accurately assess tumor embolization percentages. This is a report of work that aims to introduce quantitative image analysis tools to assess the extensiveness of endovascular embolization of meningiomas as well as the direct physiological effects. These image analysis tools applied in: MR data, angiography data, and histology data.