Gliomas are tumors that occur in all ages; they include the most common malign primary central nervous system tumors in developed countries. Gliomas are often aggressive, and their recommended treatment is surgical resection and chemoradiation. Complete tumor removal is challenging because of diffuse cell growth and the proximity of functionally critical tissues. Surgeons use 5-aminolevulinic acid (5-ALA) drug-induced fluorescence to visually detect tumor cells, which improves resection rates and delays tumor progression. Tumor cells are often left unnoticed because of visual obstacles or weak fluorescence, which may lead to local recurrence and reoperations. Surgical suction devices are used to remove cancerous tissues, but so far the suction aspirate tissues have not been routinely used in tissue detection. This multicenter controlled clinical trial investigates the clinical performance and outcomes of a new method for detecting tumor from the suction aspirates in near-real time based on 5-ALA induced fluorescence. The feedback from the aspirate tissue monitor (ATM) is expected to improve the identification of tumors, leading to fewer reoperations and better treatment outcomes.

During glioma surgery, the diffuse boundary between healthy tissue and tumor is localized using 5-ALA drug-enhanced fluorescence of cancer cells. Visual fluorescence-based tissue recognition technique using 5-ALA has been shown to improve the rate of tumor removal and slow disease progression. To see the fluorescence typical of cancer, a special light source is needed in the operating microscope. In typical blue light, the fluorescence is visible, but it is more difficult detect anatomical landmarks, such as cerebral blood vessels and cranial nerves, which makes them vulnerable to injuries. Tumor cells can also be unnoticed because of visual obstacles or weak fluorescence, which may lead to local recurrence and reoperations. Unintended tumor remnants are frequent even though many other auxiliary techniques such as MRI guidance, neuronavigation, ultrasound and neurophysiological monitoring are used.

This multicenter controlled clinical trial investigates the clinical performance and outcomes from using an aspirate tissue monitor (ATM, Marginum Ltd HIVEN™) that detects cancerous tissue from the suction waste during the surgical treatment of suspected high-grade gliomas. The ATM provides near real-time audible feedback to the surgeon when tumor-related fluorescence is detected in the aspirated tissues. The trial investigates if the use of ATM to detect 5-ALA induced fluorescence contributes to faster tumor removal, less blood loss, less unintended residual tumor, less morbidity, longer survival and the frequency of local reoperations.

In total fifty (n=50) patients referred for resection surgery for suspected high-grade glioma or its recurrence at the Kuopio University Hospital, Tampere University Hospital and Oslo University Hospital, and potential other trial sites, will be recruited to the study. The patients are prescribed oral 5-ALA preoperatively according to the institution's practices. The cases are compared with controls (n=50) from applicable local clinical site registers (matched controls). The cases are operated with the help of aspirate tissue monitoring and the controls without. Other preferred adjunct techniques are used in both groups.

Informed written consent will be obtained from patients to participate in the study on the new surgical device. The clinical trial is approved by the local research ethics committees and approved by the Finnish Medicines Agency (Fimea) and Norwegian Medicines Agency (NoMA). Patients are asked for permission to pool unidentified study data from surgical patients collected at different research institutions. The investigated device is a CE equivalent or CE marked.

Inclusion Criteria:

• Patient admitted to neurosurgery department for surgical resection of a suspected high-grade glioma
• Patients aged 18 years old or older
• Informed consent obtained

Exclusion Criteria:

• Patient belongs to the following vulnerable groups: children, pregnant, prisoners or intellectually disabled

GDPR limitations.