A sensor to improve the accuracy of stereotactic brain biopsies for the diagnosis of brain tumours


Brain cancer has a significant impact on society, disproportionate to its prevalence in comparison to other more well-known cancers. It is also the deadliest. It is the leading cause of life-years lost in men and second leading life years lost in women (1). The most common primary brain cancer in humans’ glioblastoma (GBM) is also the most common primary brain cancer and has an abysmal median survival of 15 months despite surgery and chemo-radiation (2). Despite decades of research there has been no significant changes to this sad statistic.

Histologically GBM is defined by the presence of anaplastic cells surrounded by necrotic tissue with microvascular proliferation. This reflects the aggressive nature of the tumour. Accurate diagnosis depends on achieving a representative biopsy of the tumour with both necrotic and anaplastic tissue. Stereotactic biopsy may be desirable for patients with lesions which may represent non-neoplastic lesions such as inflammatory, infectious or demyelinating lesions. Other differentials for lesions which appear similar to GBM on MRI imaging include lymphoma and brain abscess. Previous case series has shown that in 60% of cases lower grade anaplastic glioma was upgraded to GBM when open surgical resection was performed following stereotactic biopsy (3).

Diagnosing GBM requires samples of tissues to be taken either with an open craniotomy or with closed stereotactic needle-based techniques. If the location of the tumour is a deep or eloquent part of the brain stereotactic biopsy under image guidance is sometimes the only surgical procedure that can be performed. A patient’s pre-operative MRI images is used to guide the biopsy target. On T1-weighted imaging the centre of the lesion is dark and presumed to be necrotic tissue with a ring of contrast-enhancement around this area termed the contrast enhancing region (CER).

The Team

Yizhou Wan
Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, 

Agavi Stavropoulou Tatla
Department of Engineering, University of Cambridge

Project Outputs

Project Report.png

Project Report

Project report and documentation on Github


Project Proposal

Original proposal and application


Project Resources

Hardware Schematics

Bill of Materials

Software Code