Intra-operative Hyperspectral Imaging in Neurosurgery

Recruiting

• Conditions: Neurosurgery; Neuro-Oncology; Neurovascular

• Registration Number: NCT05294185
• Lead Sponsor: King's College London

Brief Summary

Brain surgery operations include brain tumour removal and blood vessel procedures. Each year in the UK, approximately 70,500 patients are diagnosed with a brain tumour, 5,000 of whom undergo surgery. Approximately 1,000 patients undergo blood vessel brain surgery.

Brain tumour surgery involves removing as much of the tumour as safely as possible. If all tumour is removed, patients have significantly better outcomes and live longer. However, even with the best hands and the most modern technology currently available, it is often not possible to reliably identify tumour during surgery. Moreover, nerves and blood vessels cannot be reliably identified either during surgery. Yet, they need to be preserved to avoid brain damage. Due to this uncertainty and the need to balance risks, tumour is often left behind. Today, close to 30% of brain tumour patients require repeat surgery owing to tumour left behind during their first surgery. Further surgeries are more difficult, pose additional patient risks and lead to increased healthcare costs with often poor patient outcomes.

Newly developed camera systems have the potential to enhance the surgeon's vision to reliably identify tumour and healthy brain structures. Hyperspectral imaging (HSI) is one of the most promising of such technologies. Its core ability is to provide very detailed and rich information that is invisible to the human eye. HSI has demonstrated the potential to provide crucial, but currently unavailable, information about tumour and critical brain structures during surgery. However, HSI data is very complex and requires advanced computer-processing for its interpretation.

In this project, we will use a HSI imaging system to record data in 81 patient undergoing brain including 63 patients with brain tumours and 18 patients suffering from brain vessel abnormalities. Using this data we will develop key computer-processing features to enable real-time image interpretation.

Detailed Description

Not available

Study Timeline

• Study First Submitted: 2022-03-11
• Study First Submitted QC: 2022-03-15
• Study First Posted: 2022-03-24
• Study Start: 2022-05-17
• Status Verified: 2023-11
• Last Update Submitted: 2023-11-30
• Last Update Posted: 2023-12-01
• Primary Completion: 2024-08
• Study Completion: 2024-08

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 81

Inclusion Criteria

• Adult patients aged 18 years and over
• Patients with a diagnosis of a brain tumour (any type), AVM or aneurysm who are scheduled for elective surgery
• Patients able to provide written informed consent

Exclusion Criteria

• Patients under 18 years of age
• Patients who have previously had brain surgery

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Correlation of HSI data with histological analysis of the corresponding biopsied pathological tissue	4-6 months	To correlate HSI data with histological analysis of the corresponding biopsied pathological tissue and to correlate tissue perfusion and tissue oxygenation maps generated from the HSI data with the surgical timeline in patients undergoing neurovascular surgery.

Secondary Outcome Measures

Name	Time	Method
AI algorithm specificity	36 months	Specificity of the AI algorithm to determine the histological nature of imaged tissue
Safety of iHSI in Neurosurgery	36 months	Record of adverse events
Tissue perfusion and tissue oxygenation	36 months	Correlation of tissue perfusion and tissue oxygenation maps generated from the HSI data with the surgical timeline in patients undergoing neurovascular surgery
Qualitative assessment	36 months	The impact that using the system has on surgical workflow (qualitative assessment)

Trial Locations

Locations (1)

King's College NHS Foundation Trust; 🇬🇧 London, United Kingdom