Skull base tumors pose some of the greatest challenges in neurosurgery due to their complex anatomical location and frequent intricate involvement of adjacent neurovascular and optic structures. Endoscopic endonasal surgery (EES) is the most effective, minimally invasive approach to skull base tumor removal. However, the safety and applicability of the procedure is highly dependent on accurate and detailed delineation of tumor anatomy and adjacent or encased vessels and cranial nerves. There is a critical need to bridge the gap between advanced imaging techniques and image guidance in the modern operating room. The overall objective in this application is to demonstrate that optimized high resolution 7T magnetic resonance imaging (MRI) is the precise tool required to provide critical preoperative information to enable improved planning and more confident intraoperative decision-making for EES of skull base lesions. Our central hypothesis is that the information added by 7T scans will enhance surgical planning, shorten operative time, and increase confidence of intraoperative decision making when compared to the gold standard preoperative imaging. Specifically, the aims of this proposal are: 1) To develop a comprehensive 7T imaging protocol for pre- and intra-operative guidance for EES of skull base tumors and 2) to apply the developed 7T imaging protocol to surgical planning and guidance for a set of 40 patients. Under the first specific aim, we will integrate novel adiabatic RF pulses int anatomical imaging sequences to improve image quality, maximize SNR and anatomical coverage. We will combine the newly developed anatomical and diffusion MRI sequences with the existing robust TOF sequence to generate a 7T protocol targeted at visualization of cranial nerves (especially optic structures), tumor anatomy and vasculature and to validate the performance of this protocol in healthy volunteers.
Under Specific Aim 2, the optimized 7T imaging protocol will be used to scan 40 patients with skull-base tumors, and the results will be compared with gold-standard 3T MRI images in 40 control patients with tumors matched by type, size, and location. The 7T images will be utilized for neurosurgical planning and will be imported into the image guidance platform to aid with intraoperative decision making and compared to controls. The innovation of this approach lies in the first application of a comprehensive 7T imaging protocol for accurate and safe neurosurgical planning, thereby bridging the gap between advanced MRI and modern surgical techniques. Our optimized techniques will utilize novel adiabatic RF pulses in 7T MRI sequences with significantly improved performance and reliability. This work is significant because the proposed 7T imaging techniques are addressing the critical need of providing precise and detailed anatomical imaging to the surgeon preoperatively, allowing for better patient selection, planning of approach, and intraoperative decision making, all of which have a high impact on patient safety and clinical outcome. This will ultimately improve the quality of neurosurgical procedures, improving management and treatment of a wide range of neurological diseases.

Public Health Relevance

The proposed research is relevant to public health because the application of novel ultrahigh field magnetic resonance imaging techniques to neurosurgical planning and guidance will improve the safety and efficacy of surgical treatment of skull base tumors as well as other neurological diseases. This impacts patient outcome by reducing morbidity and mortality. The development of new biomedical imaging techniques to fundamentally improve the detection and treatment of disease is directly relevant to one of the key missions of the NIH.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA202911-04
Application #
9669013
Study Section
Medical Imaging Study Section (MEDI)
Program Officer
Farahani, Keyvan
Project Start
2016-04-13
Project End
2021-03-31
Budget Start
2019-04-01
Budget End
2020-03-31
Support Year
4
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Icahn School of Medicine at Mount Sinai
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
078861598
City
New York
State
NY
Country
United States
Zip Code
10029
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