Feasibility of [F-18]fluoropivalate hybrid PET/MRI for imaging lower and higher grade glioma: a prospective first-in-patient pilot study

Purpose: MRI and PET are used in neuro-oncology for the detection and characterisation of lesions for malignancy to target surgical biopsy and to plan surgical resections or stereotactic radiosurgery. The critical role of short-chain fatty acids (SCFAs) in brain tumour biology has come to the forefront. The non-metabolised SCFA radiotracer, [18F]fluoropivalate (FPIA), shows low background signal in most tissues except eliminating organs and has appropriate human dosimetry. Tumour uptake of the radiotracer is, however, unknown. We investigated the uptake characteristics of FPIA in this pilot PET/MRI study. Methods: Ten adult glioma subjects were identified based on radiological features using standard-of-care MRI prior to any surgical intervention, with subsequent histopathological confirmation of glioma subtype and grade (lower-grade – LGG – and higher-grade – HGG – patients). FPIA was injected as an intravenous bolus injection (range 342–368 MBq), and dynamic PET and MRI data were acquired simultaneously over 66 min. Results: All patients tolerated the PET/MRI protocol. Three patients were reclassified following resection and histology. Tumour maximum standardised uptake value (SUVmax,60) increased in the order LGG (WHO grade 2) < HGG (WHO grade 3) < HGG (WHO grade 4). The net irreversible solute transfer, Ki, and influx rate constant, K1, were significantly higher in HGG (p < 0.05). Of the MRI variables studied, DCE-MRI-derived extravascular-and-extracellular volume fraction (ve) was high in tumours of WHO grade 4 compared with other grades (p < 0.05). SLC25A20 protein expression was higher in HGG compared with LGG. Conclusion: Tumoural FPIA PET uptake is higher in HGG compared to LGG. This study supports further investigation of FPIA PET/MRI for brain tumour imaging in a larger patient population. Clinical trial registration: Clinicaltrials.gov, NCT04097535

Feasibility of magnetic resonance imaging-based radiation therapy for brain tumour treatment

Purpose : The increasing use of MRI alongside CT images has brought about growing interest in trying to determine radiation attenuation information based on MR images only. The primary aim of this thesis is, therefore, to determine what head tissue compartments need to have separate HU values in order to obtain sufficient RT planning accuracy. This can serve as input for an MR-based classification thus enabling pseudo-CT generation in an MR-only RT workflow. Methods: To achieve this target, flattened (stratified) CT images (fCT) were generated and compared to the original CT images. Mean (ME) and mean absolute (MAE) errors were used for the fCT quality assessment, as was dose comparisons. 70 CT-based RT plans were generated and the dose distributions compared to those obtained when using the different fCT versions in place of the original CT images. The dose agreement was assessed using DVH and 1%/1mm gamma analysis. Results: The lowest MAE of 59.63 HU was calculated for an fCT8 version. DVH analysis showed low differences in the range between 3% (water-filled fCT) and 0.05% depending on the tissue stratification of the fCT version. 1%/1mm gamma analysis correctly identified plans where insufficiently fine-grained tissue classification was the main reason for dose discrepancy. The best RT planning accuracy was obtained for the fCT5 with segmented air cavities, fat, water-rich tissue, spongy, and compact bone, and for the fCT8 where also the brain tissue was stratified. Conclusions: The small differences in dose accuracy between CT and fCT images shows the feasibility of using MR-only RT planning for the brain. Nonetheless, other aspects of the MR-only workflow, such as patient positioning, as well as the impact of e.g. the surgical incisions in the skull should be subject to further research

Microscope Embedded Neurosurgical Training and Intraoperative System

In the recent years, neurosurgery has been strongly influenced by new technologies. Computer Aided Surgery (CAS) offers several benefits for patients\u27 safety but fine techniques targeted to obtain minimally invasive and traumatic treatments are required, since intra-operative false movements can be devastating, resulting in patients deaths. The precision of the surgical gesture is related both to accuracy of the available technological instruments and surgeon\u27s experience. In this frame, medical training is particularly important. From a technological point of view, the use of Virtual Reality (VR) for surgeon training and Augmented Reality (AR) for intra-operative treatments offer the best results. In addition, traditional techniques for training in surgery include the use of animals, phantoms and cadavers. The main limitation of these approaches is that live tissue has different properties from dead tissue and that animal anatomy is significantly different from the human. From the medical point of view, Low-Grade Gliomas (LGGs) are intrinsic brain tumours that typically occur in younger adults. The objective of related treatment is to remove as much of the tumour as possible while minimizing damage to the healthy brain. Pathological tissue may closely resemble normal brain parenchyma when looked at through the neurosurgical microscope. The tactile appreciation of the different consistency of the tumour compared to normal brain requires considerable experience on the part of the neurosurgeon and it is a vital point. The first part of this PhD thesis presents a system for realistic simulation (visual and haptic) of the spatula palpation of the LGG. This is the first prototype of a training system using VR, haptics and a real microscope for neurosurgery. This architecture can be also adapted for intra-operative purposes. In this instance, a surgeon needs the basic setup for the Image Guided Therapy (IGT) interventions: microscope, monitors and navigated surgical instruments. The same virtual environment can be AR rendered onto the microscope optics. The objective is to enhance the surgeon\u27s ability for a better intra-operative orientation by giving him a three-dimensional view and other information necessary for a safe navigation inside the patient. The last considerations have served as motivation for the second part of this work which has been devoted to improving a prototype of an AR stereoscopic microscope for neurosurgical interventions, developed in our institute in a previous work. A completely new software has been developed in order to reuse the microscope hardware, enhancing both rendering performances and usability. Since both AR and VR share the same platform, the system can be referred to as Mixed Reality System for neurosurgery. All the components are open source or at least based on a GPL license

Central Nervous System Tumors

Though the treatment of central nervous system (CNS) tumors has been challenging, new advances have helped us better understand the molecular and genetic makeup of many tumor types, and new chemotherapies and immunotherapies have extended survival in patients with aggressive primary CNS tumors. This book discusses pediatric and adult tumors of the CNS, the classification schemes used to categorize them, advances in surgical techniques, and several important genetic alterations found in these tumors. We hope this book contributes to the reader’s understanding of these tumors and provides the most up-to-date and cutting-edge discoveries in this exciting field

Integrated navigation and visualisation for skull base surgery

Skull base surgery involves the management of tumours located on the underside of the brain and the base of the skull. Skull base tumours are intricately associated with several critical neurovascular structures making surgery challenging and high risk. Vestibular schwannoma (VS) is a benign nerve sheath tumour arising from one of the vestibular nerves and is the commonest pathology encountered in skull base surgery. The goal of modern VS surgery is maximal tumour removal whilst preserving neurological function and maintaining quality of life but despite advanced neurosurgical techniques, facial nerve paralysis remains a potentially devastating complication of this surgery. This thesis describes the development and integration of various advanced navigation and visualisation techniques to increase the precision and accuracy of skull base surgery. A novel Diffusion Magnetic Resonance Imaging (dMRI) acquisition and processing protocol for imaging the facial nerve in patients with VS was developed to improve delineation of facial nerve preoperatively. An automated Artificial Intelligence (AI)-based framework was developed to segment VS from MRI scans. A user-friendly navigation system capable of integrating dMRI and tractography of the facial nerve, 3D tumour segmentation and intraoperative 3D ultrasound was developed and validated using an anatomically-realistic acoustic phantom model of a head including the skull, brain and VS. The optical properties of five types of human brain tumour (meningioma, pituitary adenoma, schwannoma, low- and high-grade glioma) and nine different types of healthy brain tissue were examined across a wavelength spectrum of 400 nm to 800 nm in order to inform the development of an Intraoperative Hypserpectral Imaging (iHSI) system. Finally, functional and technical requirements of an iHSI were established and a prototype system was developed and tested in a first-in-patient study

Development and evaluation of image-guided neuroendoscopy, with investigation of post-imaging brain distortion and accuracy of frameless stereotaxy

Neuroendoscopy enables a surgeon to operate deep within the brain whilst limiting morbidity through a minimally invasive approach. Technical advances in illumination, instrumentation and camera design, along with evidence for improved clinical outcome, have increased the indications for this technique and have ensured widespread popularity. However, broader application of neuroendoscopy is restricted by the necessity for direct vision of targets and by spatial disorientation. The aim of this investigation was to overcome these limitations by combining neuronavigation with neuroendoscopy to develop Image-Guided Neuroendoscopy (IGN). The strategy adopted for this was firstly to select, assess and validate a neuronavigation system, secondly to develop methods of endoscope tracking and frameless stereotactic implantation. Thirdly, to assess the impact of post-imaging brain distortion upon neuronavigation, fourthly to correct distortion of the endoscope image and finally to assess the use of graphics overlay in IGN. Laboratory phantom accuracy assessments revealed a mean point localisation error for the navigation system pointers of0.8mm (SD 0.4mm) with CT imaging, for the tracked endoscope of 1.5mm (SD 0.8mm) and for frameless stereotaxy of 1.3mm (SD 0.6mm). An in vivo study revealed a mean Euclidean error of 4.8mm (SD 2.0mm) for frame less stereotactic biopsy. The navigation system was evaluated through a clinical series of 100 cases, the frameless stereotactic technique was employed in 21 brain biopsy procedures and IGN evaluated in 5 procedures. The magnitude of post-imaging brain distortion was determined and correlations discovered with pre-operative image characteristics. The conclusions of this thesis are that IGN can be accomplished with acceptable accuracy, including frameless stereotactic implantation, and that the impact of postimaging brain distortion will not negate the value of IGN in most cases. Thus, the method developed for IGN has overcome both major constraints of neuroendoscopy, enabling endoscopic surgery to pass through and beyond the ventricular wall, to be undertaken safely in cases with distorted anatomy and opening the potential for wider application of these minimally invasive techniques

Brain tumour genetic network signatures of survival

Tumour heterogeneity is increasingly recognized as a major obstacle to therapeutic success across neuro-oncology. Gliomas are characterised by distinct combinations of genetic and epigenetic alterations, resulting in complex interactions across multiple molecular pathways. Predicting disease evolution and prescribing individually optimal treatment requires statistical models complex enough to capture the intricate (epi)genetic structure underpinning oncogenesis. Here, we formalize this task as the inference of distinct patterns of connectivity within hierarchical latent representations of genetic networks. Evaluating multi-institutional clinical, genetic, and outcome data from 4023 glioma patients over 14 years, across 12 countries, we employ Bayesian generative stochastic block modelling to reveal a hierarchical network structure of tumour genetics spanning molecularly confirmed glioblastoma, IDH- wildtype; oligodendroglioma, IDH-mutant and 1p/19q codeleted; and astrocytoma, IDH- mutant. Our findings illuminate the complex dependence between features across the genetic landscape of brain tumours, and show that generative network models reveal distinct signatures of survival with better prognostic fidelity than current gold standard diagnostic categories.Comment: Main article: 52 pages, 1 table, 7 figures. Supplementary material: 13 pages, 11 supplementary figure

Clinical Management and Evolving Novel Therapeutic Strategies for Patients with Brain Tumors

A dramatic increase in knowledge regarding the molecular biology of brain tumors has been established over the past few years, and this has lead to the development of novel therapeutic strategies for these patients. In this book a review of the options available for the clinical management of patients with these tumors are outlined. In addition advances in radiology both for pre-operative diagnostic purposes along with surgical planning are described. Furthermore a review of newer developments in chemotherapy along with the evolving field of photodynamic therapy both for intra-operative management and subsequent therapy is provided. A discussion of certain surgical management issues along with tumor induced epilepsy is included. Finally a discussion of the management of certain unique problems including brain metastases, brainstem glioma, central nervous system lymphoma along with issues involving patients with a brain tumor and pregnancy is provided