Skip to Content

Intracranial Ultrasound: Implantable ultrasound for early brain tumor detection

Team Members:
  • Shreya Narayan
  • William Robinson
  • Daniel Borders
  • Benjamin Treutler
  • Siddharth Krishnan
  • Rida Chowdhury
  • Elaina Regier
  • Jaden Maloney
  • Chad Gordon, DO
  • Elizabeth Logsdon, PhD
  • Hernando M. Lopez-Bertoni, PhD
  • Andrea Judit Machnitz, MD
  • Netanel Ben-Shalom, MD
  • Amir Manbachi, MSc, PhD
  • Jon Weingart, MD
  • Ignacio Albert


Occurring in 3.19 out of every 100,000 Americains, glioblastomas are the most common intracranial brain tumor and almost always recur with a high patient mortality rate.1 In the current standard of care, recurrent glioblastomas are detected through MRI scans conducted every 3 months.2 The frequency of these scans is problematic because glioblastomas progress rapidly in high grade tumor patients. In the three months between scans, a tumor can develop and grow to a stage that is significantly more difficult to treat. In low grade tumor patients, recurrent tumors can appear several years after the first diagnosis and resection, so obtaining four MRI scans a year poses high, unnecessary costs. Therefore, neurosurgeons need a cost effective way to detect rapidly-growing recurrent tumors before they reach a critical grade in order to prevent irreversible brain damage. Our solution provides a cost effective, efficient, and clinically superior way to detect these recurrent brain tumors, in both low grade and high grade (glioblastoma) patients. We are creating an implantable ultrasound device that will be placed in the skull space to image the resection site daily in order to detect the recurrence of glioblastomas as soon as they form. With our solution, patients will benefit from early diagnosis which will improve prognosis at a much lower cost, neurosurgeons will be better able to track patient health and provide more flexible treatment options, and hospitals will cut costs associated with unnecessary and frequent MRI scans, easing the strain on limited hospital resources.

Read the Johns Hopkins University privacy statement here.