Augmented visualisation of tumour boundaries and functioning brain during neurosurgery
File(s)
Author(s)
Anichini, Giulio
Type
Thesis
Abstract
Introduction. Surgery for brain tumours represents a major and multidisciplinary challenge. An extensive body of literature suggests a non-linear correlation between the extent of resection and survival. However, resection is often limited by the difficulty of exactly identifying the degree of brain invasion and the presence of functionally active areas.
Hypothesis. The project examines the hypothesis of advancing the current technological setup in neurosurgery, specifically attempting to visually improve the identification of tumour margins and eloquent brain activation.
Aims. To investigate:
• to evaluate the role and optimization of IntraOperative UltraSound (IOUS) in brain
tumour resection;
• to assess how Hyperspectral Imaging (HSI) can enhance the visualization of tumour margins
and detect haemodynamic changes in real-time.
Methods. The present thesis expands on the candidate’s experience with IOUS, reporting a published analysis of the advantages. The results of performance and technical limitations are also discussed. Regarding the HSI application, the thesis details the results from a pilot study applying these technologies intra-operatively. Hyperspectral data (hypercube images) were processed using various computational techniques, and brain haemodynamics were analyzed through an adapted Beer-Lambert model. Results. The IOUS series included 391 cases, and the data showed a resection and survival advantage in glioblastomas. Cases operated using IOUS showed an improved resection and a possible survival advantage. Regarding MSI/HSI, 47 patients have been recruited. The following findings were recorded: all the algorithms for intra-patient classifications showed excellent performance on all metrics; the inter-patent classification methods showed a better performance with meningiomas but more heterogeneous results with gliomas; the perfusion maps showed statistically significant changes in brain perfusion, although
the clinical significance of these findings is unclear.
Conclusions. The results reported in the present project are promising for the further technological
development of both iOUS and HSI.
Hypothesis. The project examines the hypothesis of advancing the current technological setup in neurosurgery, specifically attempting to visually improve the identification of tumour margins and eloquent brain activation.
Aims. To investigate:
• to evaluate the role and optimization of IntraOperative UltraSound (IOUS) in brain
tumour resection;
• to assess how Hyperspectral Imaging (HSI) can enhance the visualization of tumour margins
and detect haemodynamic changes in real-time.
Methods. The present thesis expands on the candidate’s experience with IOUS, reporting a published analysis of the advantages. The results of performance and technical limitations are also discussed. Regarding the HSI application, the thesis details the results from a pilot study applying these technologies intra-operatively. Hyperspectral data (hypercube images) were processed using various computational techniques, and brain haemodynamics were analyzed through an adapted Beer-Lambert model. Results. The IOUS series included 391 cases, and the data showed a resection and survival advantage in glioblastomas. Cases operated using IOUS showed an improved resection and a possible survival advantage. Regarding MSI/HSI, 47 patients have been recruited. The following findings were recorded: all the algorithms for intra-patient classifications showed excellent performance on all metrics; the inter-patent classification methods showed a better performance with meningiomas but more heterogeneous results with gliomas; the perfusion maps showed statistically significant changes in brain perfusion, although
the clinical significance of these findings is unclear.
Conclusions. The results reported in the present project are promising for the further technological
development of both iOUS and HSI.
Version
Open Access
Date Issued
2023-12-01
Date Awarded
01/12/2024
License URL
Advisor
O'Neill, Kevin
Syed, Nelofer
Elson, Daniel
Sponsor
Brain Tumour Research Campaign
Grant Number
P68941
Publisher Department
Brain Sciences
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)