Abstract
Aims
The co-existence of non-epileptic attacks (NEAD) in patients with brain tumour related epilepsy (BTRE) is poorly described. Non epileptic attacks (NEAD) co-occur in up to 30% of ...patients with epilepsy PWE. Adverse life events are associated with development of NEAD; their co-occurrence in those with BTRE is potentially un-surprising.
We sought to characterise the evolution of symptoms in this cohort.
Method
Clinical trajectories of patients with BTRE and co-existing NEAD were characterised. The diagnosis of NEAD was based on the epilepsy specialist’s observation of attacks and /or capture of attacks on video. Some patients had additional video EEG correlate.
Patients had been referred because of persisting symptoms in spite of escalating antiepileptic therapy.
Results
Of eight patients, six were initially misdiagnosed with escalating seizures. One patient developed NEAD de novo following tumour biopsy, the remaining patients developed NEAD following onset of BTRE. Onset of NEAD was not temporally linked with the diagnosis of a brain tumour. In five patients, NEAD onset occurred when seizures were controlled (< 1 seizure/ month). All patients reported fear of developing uncontrolled seizures as being associated with their symptoms and identified their NEAD as more disabling than their epilepsy.
Patients were eventually managed with polytherapy -two found adjunctive clobazam helpful and four were offered antidepressant/ anxiolytic medication. Behavourial strategies including mindfulness were also discussed. At time of last follow up, seven patients had on-going NEAD symptoms in spite of good seizure control.
Conclusion
NEAD can co-occur with BTRE and should be considered in those with rapidly escalating symptoms in spite of antiepileptic therapy and radiologically stable lesions. Both making the diagnosis of NEAD and providing ongoing support is challenging. These patients require a multidisciplinary approach with support from allied specialties including neuropsychiatry and neuropsychology.
Abstract
Aims
Treatment response assessment in glioblastoma is challenging. Patients routinely undergo conventional magnetic resonance imaging (MRI), but it has a low diagnostic accuracy for ...distinguishing between true progression (tPD) and pseudoprogression (psPD) in the early post-chemoradiotherapy time period due to similar imaging appearances. The aim of this study was to use artificial intelligence (AI) on imaging data, clinical characteristics and molecular information within machine learning models, to distinguish between and predict early tPD from psPD in patients with glioblastoma.
Method
The study involved retrospective analysis of patients with newly-diagnosed glioblastoma over a 3.5 year period (n=340), undergoing surgery and standard chemoradiotherapy treatment, with an increase in contrast-enhancing disease on the baseline MRI study 4-6 weeks post-chemoradiotherapy. Studies had contrast-enhanced T1-weighted imaging (CE-T1WI), T2-weighted imaging (T2WI) and apparent diffusion coefficient (ADC) sequences, acquired at 1.5 Tesla with 6-months follow-up to determine the reference standard outcome. 76 patients (mean age 55 years, range 18-76 years, 39% female, 46 tPD, 30 psPD) were included. Machine learning models utilised information from clinical characteristics (age, gender, resection extent, performance status), O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status and 307 quantitative imaging features; extracted from baseline study CE-T1WI/ADC and T2WI sequences using semi-automatically segmented enhancing disease and perilesional oedema masks respectively. Feature selection was performed within bootstrapped cross-validated recursive feature elimination with a random forest algorithm and Naïve Bayes five-fold cross-validation to validate the final model.
Results
Treatment response assessment based on the standard-of-care reports by clinical neuroradiologists showed an accuracy of 33% (sensitivity/specificity 52%/3%) to distinguish between tPD and psPD from the early post-treatment MRI study at 4-6 weeks. Machine learning-based models based on clinical and molecular features alone demonstrated an AUC of 0.66 and models using radiomic features alone from the early post-treatment MRI demonstrated an AUC of 0.46-0.69 depending on the feature and mask subset. A combined clinico-radiomic model utilising top common features demonstrated an AUC of 0.80 and an accuracy of 74% (sensitivity/specificity 78%/67%). The features in the final model were age, MGMT promoter methylation status, two shape-based features from the enhancing disease mask (elongation and sphericity), three radiomic features from the enhancing disease mask on ADC (kurtosis, correlation, contrast) and one radiomic feature from the perilesional oedema mask on T2WI (dependence entropy).
Conclusion
Current standard-of-care glioblastoma treatment response assessment imaging has limitations. In this study, the use of AI through a machine learning-based approach incorporating clinical characteristics and MGMT promoter methylation status with quantitative radiomic features from standard MRI sequences at early 4-6 weeks post-treatment imaging showed the best model performance and a higher accuracy to distinguish between tPD and psPD for early prediction of glioblastoma treatment response.
Abstract
Aims
Previous work has shown that increased numbers of macrophages are associated with more rapid schwannoma tumour growth and we are interested in signals that control entry of macrophages ...and other immune cells into these tumours. Activation of the Raf-kinase domain and the Raf/MEK/ERK pathway within Schwann cells has been observed to induce an inflammatory response in peripheral nerves in the absence of injury. Activation of an inducible Raf-kinase transgene in Schwann cells allows modelling of acute demyelination of peripheral nerves without nerve injury. This Raf-oestrogen receptor fusion protein (Raf-TR) is activated by the oestrogen analogue Tamoxifen and so allows targeted, controlled activation of the Raf/MEK/ERK pathway within the Schwann cells.
Here, in order to understand drivers of tumour formation, we assess the effect of MAPK activation in Merlin-null Schwann cells upon immune cell infiltration within the PNS.
Method
RafTR-P0CRE-NF2fl/fl mice of 4-6 weeks age were injected daily (IP) with 2mg of 4-hydroxy-tamoxifen or vehicle (corn oil) control for 5 consecutive days. RafTR was activated on either a Merlin (NF2) wild-type (NF2 fl/fl, P0-CRE-) or NF2 null (NF2 fl/fl, P0-CRE+) background and effects on immune cell infiltration studied in each condition.
Immunofluorescence was performed in the dorsal root ganglia (DRGs) and sciatic nerves of mice to identify various immune cell infiltrates at various timepoints. These will include neutrophils, mast cells, T-Cells and macrophages using the cell markers Csf3r, C-kit, CD3 and IBA1 respectively.
Results
At 21 days post treatment, a significantly increased infiltration of macrophages within the sciatic nerve and dorsal root ganglia was observed in mice treated with Tamoxifen when compared to vehicle controls. Loss of NF2 led to a massive increase in the number of macrophages recruited to peripheral nerves in tamoxifen-treated mice compared to Cre- mice and Cre+ treated with vehicle alone. Further assessment of other immune cell infiltration including neutrophils, mast cells and T cells are ongoing.
Conclusion
Raf/MEK/ERK signalling, in the absence of tumour suppressor Merlin, significantly increases the infiltration of inflammatory cells such as macrophages into peripheral nerves even in the absence of injury. As this effect is enhanced in NF2 null mice, this suggests that Merlin plays an important role in inhibiting the inflammatory response in peripheral nerves. It also suggests that Merlin could be involved in maintaining the blood nerve barrier (BNB), as in its absence the greater influx of immune cells into the nerves and DRGs suggests a more complete loss of BNB function than just activation of the Raf/MEK/ERK cascade alone.
Abstract
Aims
Despite improved understanding of effector T-cell trafficking into the central nervous system, initial trials with anti-PD1/PD-L1 immune checkpoint inhibitors (ICIs) have failed to meet ...their primary endpoints. PTEN loss of function is frequent in GBM and has been correlated with not only poor overall prognosis, but also impaired antitumour responses, including reduced T cell infiltration into tumour and reduced efficacy of ICIs.
Ipatasertib is a novel, potent, selective, small-molecule inhibitor of Akt. We have shown that Ipatasertib efficiently depletes FOXP3+ regulatory T cells from the tumour microenvironment (TME) resulting in increased infiltration of effector T cells in solid tumours (Lopez 2020, AACR).
We hypothesize that the use of AKT inhibition in PTEN glioblastomas may deplete the TME of suppressive immune cells, and render malignant brain tumours more responsive to ICIs. We present updated data for the combination of Ipat+ATZ in patients with glioblastoma.
Method
Patients with relapsed WHO grade IV GBM with stable neurological symptoms ≥5 days prior to enrolment, requiring <3mg Dexamethasone were recruited into two cohorts of this early phase, open-label, single-centre trial studying the combination of Ipatasertib (Ipat) and Atezolizumab (ATZ): a dose finding cohort (A2; n=9) and an expansion cohort (B3; n=7, recruitment ongoing).
The Ice-CAP A2 cohort assessed safety, pharmacodynamic, and preliminary clinical activity of Ipat (200mg or 400mg OD) + ATZ (1200mg Q3W) in pts with potentially resectable relapsed WHO Grade IV GBM. Pts had a 14-21-day run-in phase of Ipat then surgical tumour resection. Combination Ipat+ATZ commenced post surgery. Patients who declined surgery or who were deemed high risk for surgery proceeded directly to combination.
Patients in the expansion cohort B3 commenced directly on Ipat+ATZ at the RP2D of 400mg Ipat with ATZ.
Results
16 evaluable recurrent GBM pts were enrolled across two cohorts. Median age 56 yrs (25-71 yrs). Median ECOG PS 1. Median lines of prior therapy 1 (range 1-4). 10 pts had PTEN loss by IHC (H<30) and/or PTEN mutations on next generation sequencing.
No DLTs, treatment-related (TR) serious adverse events (AEs), or immune-related AEs were observed. Most common TR AEs were G1 diarrhoea (44%), mucositis (17%), rash (28%).
Clinical benefit rate (CR, PR and SD> 6 cycles) at clinical cutoff date (23/02/21) in patients with PTEN aberration was 30% (3/10). A 58-year-old man with PTEN loss had MRI at Cycle 5 showing worsening enhancement suggestive of disease progression. Resection of the lesion showed intense lymphocyte infiltration and pathological CR. He is currently on Cycle 22 with no evidence of disease. Two other patients with PTEN loss with radiological stable disease per RANO criteria remain well on study for >6 cycles.
Conclusion
Combination Ipat+ATZ appears safe and tolerable in GBM pts, with 400mg Ipatasertib OD + 1200mg ATZ Q3W declared as RP2D. Early efficacy signals were detected with PTEN loss being a promising predictive biomarker for response to combination. An expansion cohort enriched with pts with PTEN loss is ongoing.
Abstract
Aims
Circulating tumour DNA (ctDNA), shed from solid cancers in to the plasma, represents an exciting analyte for diagnosis and monitoring of disease in cancer patients. However, its use in ...glioma brain cancer patients represents a challenge, due to reduced permeability of the blood brain barrier.
This pilot study sought to investigate the practical aspects and clinical utility of using cell-free DNA (cfDNA) in glioma tests in a NHS diagnostic laboratory. Firstly, we investigated the potential of ctDNA as a proxy for the brain cancer biopsy; where cfDNA analysis was compared to the paired FFPE brain specimen for relevant glioma genetic biomarkers. Secondly, ctDNA constitutes a portion of the overall cfDNA and there is evidence cfDNA metrics per se may also be of value as prognostic tools and surrogates of tumour burden. Additionally, we investigated a potential role for cfDNA metrics in prognostic impact; linking cfDNA concentrations to clinical outcome measures.
Method
10ml peripheral blood was collected in specialist preservative tubes and cfDNA isolated using an extraction kit (Qiagen MinElute ccfDNA kit). cfDNA concentration and purity was assessed using chip-based automated electrophoresis.
Where relevant (12/39 cases), cfDNA samples were run though laboratory tests of IDH variant detection, 1p19q co-deletion assessment and MGMT promoter methylation analysis. Results were compared with ‘standard of care’ brain biopsy tests.
A potential correlate of cfDNA concentration and clinical outcomes data were assessed in a sub-cohort of glioblastoma patients (n=32). The cohort was divided in to 2 groups – high cfDNA vs. low cfDNA - based on whether a subject’s extracted sample cfDNA concentration fell above or below the mean. Comparison of overall survival in months between subjects was checked for normal distribution using the Shapiro-Wilk t-test. The test of equity of survival distributions for the high cfDNA vs. low cfDNA was then analysed as a Kaplan-Meier curve.
Results
The protocol delivered cfDNA of high purity, averaging 91%, within the plasma nucleic acid fraction, however the cfDNA concentrations (mean ≈1ng µl-1) fell below the conventional limit of detection of the laboratory tests. In spite of the low concentration, cfDNA samples did generate test PCR amplicon; however results reflected the germline DNA profile rather than the new somatic changes of the tumour. The cfDNA analysis did not pick up the tumour biomarkers seen in the paired tumour biopsy sample.
In a second part of the study, cfDNA concentrations for the glioblastoma cohort were assessed in the context of their clinical outcomes data. The data showed a correlate where high cfDNA concentration in the extracted sample was independently associated with inferior outcome in terms of overall survival, with Log Rank significance p=0.014 (Figure 1).
Conclusion
The cfDNA yields from a 10ml blood sample were consistently too low to meet the limit of detection requirements of the standard laboratory neuropathology genetic tests and glioma tumour profile could not be picked up against the germline background. Thus, in spite of the considerable advantages to glioma plasma molecular testing, using cfDNA as a proxy for a brain biopsy would currently not be possible in our routine diagnostic environment.
However, within the limitations of the pilot project testing strategy, the data showed an interesting correlate where high cfDNA concentration was independently associated with inferior outcome in terms of overall survival for glioblastoma patients. Given the simplicity of obtaining this quantifiable metric, there are grounds for further investigations as to its utility; not only with survival outcomes, but also potential correlation with the clinical assessment of tumour burden, blood brain barrier integrity and disease pseudoprogression.
Abstract
Aims
Survival has been poor in several multi-center/national trials since the 1980s, either delaying, avoiding or minimizing brain irradiation in young children with medulloblastoma. The ...introduction of German regimens supplementing “standard” chemotherapy with both intravenous high-dose (HD-MTX) and intraventricular (IVENT-MTX) methotrexate, and North American regimens incorporating marrow-ablative chemotherapy with autologous hematopoietic cell rescue (HDCx+AuHCR), have reported encouraging outcomes. We performed a comparative outcomes analysis of these differing strategies for young children with desmoplastic/extensive nodular medulloblastoma.
Method
Data from 12 trials reported between 2005 and 2020 for children <six-years-old with desmoplastic/extensive nodular medulloblastoma were reviewed; event-free (EFS) survival+/-standard errors were compared.
Results
The German HIT-SKK’92 and HIT-SKK’00 trials incorporating HD-MTX and IVENT-MTX reported 85+/-8% and 95+/-5% 5-10-year EFS respectively; a third trial (ACNS1221) incorporating HIT-SKK therapy but without IVENT-MTX reported only 49+/-10% EFS. Three trials (Head Start I and II combined and CCG-99703) employing induction chemotherapy without HD-MTX, followed by one or three HDCx+AuHCR cycles, reported 3-5-year EFS of 67+/-16% and 79+/-11%. Two trials employing HD-MTX-containing induction chemotherapy (Head Start III and ACNS0334), followed by one or three HDCx+AuHCR cycles, reported 3-5-year EFS of 89+/-6% and 100%, respectively. Finally, four trials utilizing neither IVENT-MTX nor HDCx+AuHCR (UK-CNS-9204, CCG-9921, COG-P9934 and SJYC07) reported 2-5 year EFS of 35+/-11%, 77+/-9%, 58+/-8% and 53+/-9% respectively.
Conclusion
A trend towards better EFS for young children with desmoplastic/extensive nodular medulloblastoma is observed in trials including eitherHD-MTX and IVENT-MTX or including HD-MTX-containing induction chemotherapy and HDCx+AuHCR. Trials excluding HD-MTX, IVENT-MTX and HDCx+AuHCR have poorer outcomes.
Abstract
Aims
Meningioma is the most common primary intracranial tumour. Although ~80% are benign WHO grade I and show high rates of recurrence. Surgery is the main therapeutic approach, yet location ...can hamper complete resection and chemotherapies are ineffective. Moreover, accurate biomarkers for clinical management are lacking. Approximately 60% sporadic meningiomas harbour mutations in the NF2gene, while mutations in genes including TRAF7, KLF4, AKT1, SMO and PIK3CAhave been identified majority in the NF2-positive low grade-tumours. Moreover, mutations in TRAF7 mostly co-occur with a KLF4K409Q or with AKT1E17K mutation. The mutations and their molecular manifestations consequently affect the signalling pathways at the protein level. The molecular mechanisms behind meningioma tumourigenesis are still obscure and the identification of specific biomarker is necessary to enable their implementation in routine diagnostics and therapeutics. Therefore, we aim to identify novel biomarkers and therapeutic targets of genetically stratified low-grade meningioma by characterising the proteomic landscape.
Method
Frozen tumour samples have already been analysed for NF2-/- by next generation sequencing and genotyped for common mutational hotspots in non-NF2 meningioma such as TRAF7, KLF4 and AKT1 and grouped in to three different mutational groups: AKT1E17K/TRAF7, KLF4K409Q/TRAF7and NF2-/- and all these mutations will be compared to normal healthy meninges. For global proteomics, proteins were separated by SDS-PAGE followed by in-gel tryptic digestion and sample preparation for LC-MS/MS analysis. Raw mass spectrometry data files were processed by MaxQuant (1.6.2.10) and Perseus software (1.6.1.3). Quantitative phospho-proteomics was performed using TMT 10plex labelling approach followed by motif analysis using motif-X algorithm. GO enrichment analyses were performed using (DAVID) v6.8 against all human proteins. Potential candidates from expression data analysis will be validated via Western Blot and immunohistochemistry.
Results
We have quantified 4162 proteins across all mutational meningioma subgroups and normal meninges (n=31). Hierarchical clustering analysis showed distinct proteomic profiles of mutational subgroups revealing clusters of differentially expressed proteins. Comparative analysis showed 10 proteins were commonly significantly upregulated (log2 fold-change≥1; p<0.05) among all mutational subtypes vs. normal meninges, indicating proteomic landscapes of mutational subtypes to be highly variable. In contrast, 257 proteins were commonly significantly downregulated (log2 fold-change≤-1; p<0.05) and enriched with molecular functions including aldehyde dehydrogenase and oxido-reductase. Mutational subtype-specific analysis identified 162 proteins significantly upregulated in AKT1E17K/TRAF7 vs. remaining sample groups to be enriched in the oxidative phosphorylation pathway. However, only 14 and 7 proteins were commonly significantly upregulated in KLF4K409Q/TRAF7 and NF2-/- mutant meningioma subtypes respectively. Several of these up-regulated proteins including ANNEXIN-3, CRABP2, CLIC3 and Endoglin were already verified via WB. Lastly, analyses of 6600 phospho-sites (n=8) predicted regulatory kinases including CHEK1, CHEK2 and LCK.
Conclusion
Global proteomic and phos-phoproteomics analysis has led to the identification of proteins differentially expressed in mutant subtypes. Results of this study to date suggest that a proteomic approach is an effective tool to identify distinct patterns in genetically distinct meningioma subgroups. Further validation and functional verification (with inhibitory or knockdown approaches) of potential candidates will allow us to identify potential drug targets/biomarkers for meningiomas.
Abstract
Aims
Ependymomas (tumours arising from ependymal cells) are rare in the adult population and therefore there is limited class 1 evidence on the treatment and management of these patients. We ...present our experience from a large single center. We address whether management should be undertaken by sub-specialised surgeons with high volume experience.
Method
Retrospective comparative study.
Results
High volume surgeons operated on larger volume (16.14 mm3, 8.31mm3, p=0.10) and more complex tumours (multi-centric cases p=0.10). We find a non-significant improvement in complication rate (p=0.77), extent of gross total resection (70.8% against 65.7%) and a positive change in performance status for high volume surgeons (p=0.84). Length of hospital stay is significantly prolonged when complications occur (14.2 and 48.4 days, p<0.05).
Conclusion
Surgeons who have higher case load of ependymomas operate on more complex tumours. In addition, our results indicate there is a technical advantage of high volume surgeons compared to low volume surgeons, which translates into improved clinical outcomes for patients. We show that this has a significant impact on length of hospital stay, as well as the associated economical implications. For rare tumours such as ependymomas, super-specialisation and referral to surgeons with higher case volume will likely improve patient outcomes.
We call for a multi-centre, prospective studies to combine data in demonstrating statistical significance (power calculation for complication rate, N=150, p=0.05).
Abstract
Aims
Glioblastoma multiforme (GBM) is an aggressive brain malignancy. Performance status is an important prognostic factor but is subjectively evaluated, resulting in inaccuracy. Objective ...markers of frailty/physical condition, such as measures of skeletal muscle mass can be evaluated on cross-sectional imaging and is associated with cancer survival. In GBM, temporalis muscle has been identified as a skeletal muscle mass surrogate and a prognostic factor. However, current manual muscle quantification is time consuming, limiting clinical adoption. We previously developed a deep learning system for automated temporalis muscle quantification, with high accuracy (Dice coefficient 0.912), and showed muscle cross-sectional area is independently significantly associated with survival in GBM (HR 0.380). However, it required manual selection of the temporalis muscle-containing MRI slice. Thus, in this work we aimed to develop a fully automatic deep-learning system, using the eyeball as an anatomic landmark for automatic slice selection, to quantify temporalis and validate on independent datasets.
Method
3D brain MRI scans were obtained from four datasets: our in-house glioblastoma patient dataset, TCGA-GBM, IVY-GAP and REMBRANDT. Manual eyeball and temporalis segmentations were performed on 2D MRI images by two experienced readers. Two neural networks (2D U-Nets) were trained, one to automatically segment the eyeball and the other to segment the temporalis muscle on 2D MRI images using Dice loss function. The cross sectional area of eyeball segmentations were quantified and thresholded, to select the superior orbital MRI slice from each scan. This slice underwent temporalis segmentation, whose cross sectional area was then quantified. Accuracy of automatically predicted eyeball and temporalis segmentations were compared to manual ground truth segmentations on metrics of Dice coefficient, precision, recall and Hausdorff distance. Accuracy of MRI slice selection (by the eyeball segmentation model) for temporalis segmentation was determined by comparing automatically selected slices to slices selected manually by a trained neuro-oncologist.
Results
398 images from 185 patients and 366 images from 145 patients were used for the eyeball and temporalis segmentation models, respectively. 61 independent TCGA-GBM scans formed a validation cohort to assess the performance of the full pipeline. The model achieved high accuracy in eyeball segmentation, with test set Dice coefficient of 0.9029 ± 0.0894, precision of 0.8842 ± 0.0992, recall of 0.9297 ± 0.6020 and Hausdorff distance of 2.8847 ± 0.6020. High segmentation accuracy was also achieved by the temporalis segmentation model, with Dice coefficient of 0.8968 ± 0.0375, precision of 0.8877 ± 0.0679, recall of 0.9118 ± 0.0505 and Hausdorff distance of 1.8232 ± 0.3263 in the test set. 96.1% of automatically selected slices for temporalis segmentation were within 2 slices of the manually selected slice.
Conclusion
Temporalis muscle cross-sectional area can be rapidly and accurately assessed from 3D MRI brain scans using a deep learning-based system in a fully automated pipeline. Combined with our and others’ previous results that demonstrate the prognostic significance of temporalis cross-sectional area and muscle width, our findings suggest a role for deep learning in muscle mass and sarcopenia screening in GBM, with the potential to add significant value to routine imaging. Possible clinical applications include risk profiling, treatment stratification and informing interventions for muscle preservation. Further work will be to validate the prognostic value of temporalis muscle cross sectional area measurements generated by our fully automatic deep learning system in the multiple in-house and external datasets.
Abstract
Aims
Extent of resection is associated with better survival in patients with glioblastoma. Numerous surgical adjuncts can be used to achieve maximal safe resection - including ...fluorescence-guidance with 5-aminolevulinic acid (5-ALA), neuronavigation, intraoperative ultrasound (IoUS), intra-operative MRI (iMRI), tractography, electrophysiological monitoring and awake surgery. We evaluated the availability, use and operative aim and success associated with these adjuncts.
Method
This is a prospective cohort study of 27 of 31 neurosurgical centres in the UK and Ireland from 6 January to 19 March 2020. Consecutive cases were identified through neuro-oncology multidisciplinary meetings. Eligible cases included adults with a supratentorial histopathologically confirmed glioblastoma with pre/post-operative reported T1-weighted MRI with contrast deemed suitable for resection. Outcomes included the availability and usage of surgical adjuncts, and the percentage of operations that achieved their aim of complete resection, defined as complete resection of enhancing tumour (CRET) on post-operative T1-MRI. We present the initial descriptive statistics from this national study.
Results
232 patients with glioblastoma were included. In 142 patients (61.2%) the surgical aim was CRET. 5-ALA and neuronavigation were available in all centres (Figure 1). The most commonly used neurosurgical adjunct was neuronavigation (88.2%) (Figure 2). The proportion of patients receiving 5-ALA in CRET and debulking-only groups was 65.0% and 48.9%, respectively. 35 different combinations of adjuncts were found in total, with 13 unique combinations only used in one instance (Figures 1 & 2). CRET was achieved in 69/142 (45.8%) patients in which was the aim. 9/90 (10%) patients in the debulking-only group achieved CRET, of which 7/9 (77.8%) had received 5-ALA. Of the three most frequently used combination of adjuncts for patients deemed feasible for CRET, the most successful in terms of achieving CRET was the combined use of neuronavigation, 5-ALA and IoUS, with post-operative CRET at 47.4% (Figure 3).
Conclusion
ELISAR-GB has collated prospective data to demonstrate the current use of intraoperative adjuncts in the UK and Ireland. There is marked heterogeneity with regards to combinations of adjuncts used. A CRET of 47% is lower than would be expected compared to previously published literature, possibly due to a more stringent definition of complete resection in this study. Based on these early descriptive results, there is no clear combination of adjuncts that shows superiority and use of 5-ALA does not always result in CRET when it is the surgical aim. Of interest, 5-ALA is being used for operations that do not aim for complete resection, a change in indication. The FUTURE GB trial will provide more conclusive evidence on the efficacy of surgical adjuncts to maximise extent of resection.
PDF