During 2006–2021, Canada had 55 laboratory-confirmed outbreaks of foodborne botulism, involving 67 cases. The mean annual incidence was 0.01 case/100,000 population. Foodborne botulism in Indigenous ...communities accounted for 46% of all cases, which is down from 85% of all cases during 1990–2005. Among all cases, 52% were caused by botulinum neurotoxin type E, but types A (24%), B (16%), F (3%), and AB (1%) also occurred; 3% were caused by undetermined serotypes. Four outbreaks resulted from commercial products, including a 2006 international outbreak caused by carrot juice. Hospital data indicated that 78% of patients were transferred to special care units and 70% required mechanical ventilation; 7 deaths were reported. Botulinum neurotoxin type A was associated with much longer hospital stays and more time spent in special care than types B or E. Foodborne botulism often is misdiagnosed. Increased clinician awareness can improve diagnosis, which can aid epidemiologic investigations and patient treatment.
Abstract
Aims
Glioblastoma multiforme (GBM) is a devastating disease with notoriously poor survival. Studies examining survival in patients given best supportive care (BSC) are few and far between. ...All patients harbouring brain tumours referred to the Neuro-oncology service at the Queen Elizabeth Hospital in Birmingham are recorded in the Somerset Cancer Registry. We set out to analyse survival times and identify patient and tumour-related factors significantly affecting prognosis.
Method
We identified 126 patients from 2015 to 2019 in our Somerset Cancer Registry with radiological diagnoses of glioblastoma for whom the Neuro-oncology MDT recommended BSC. We performed a retrospective analysis of clinical records and radiological images. 11 patients were excluded (8 due to insufficient imaging data, 2 who underwent subsequent surgery, 1 patient with brain metastases). Survival was measured in completed weeks since the index MDT decision. Associations between survival time and both patient- and tumour-related factors were assessed using Kaplan-Meier curves and log-rank tests. All analyses were performed using IBM SPSS 22 (IBM Corp. Armonk, NY), with p<0.05 deemed to be indicative of statistical significance throughout.
Results
Data were available for N=115 patients (69 males, 46 females), with a mean age of 79 ± 8 years. All patients died within 32 weeks of diagnosis, with a median survival time of 8 weeks. Only 8 patients survived for more than 20 weeks. Survival was significantly shorter in those with a greater number of main cerebral structures affected (p=0.044), with a median of 6 vs. 10 weeks for 3 or more vs. 1 structures affected (hazard ratio: 1.61, 95% CI: 0.99-2.62). Bilateral tumours involving the corpus callosum were also associated with shorter survival (p=0.039). None of the other factors considered were found to be significantly associated with survival, including age (p=0.193), gender (p=0.371), performance status (p=0.300) and tumour size (p=0.331).
Conclusion
With the exception of the number of main cerebral structures affected (frontal, parietal, temporal and occipital lobes, corpus callosum, insula, basal ganglia and brain stem), patient- and tumour-factors traditionally used by the MDT to prognosticate do not correlate with survival time in patients receiving BSC for radiological diagnoses of GBM. With 50% of the cohort dying within 8 weeks it is clear that we must reconsider the timing of referrals to palliative and hospice care. Finally, the fact that some patients survived for more than half a year with no surgical or oncological treatment suggests that the process of selecting patients for BSC vs aggressive treatments needs refinement.
Abstract
Aims
Since 2016, the University Hospital Southampton NHS Foundation Trust (UHSFT) has been commissioned by NHS England to deliver SRST to brain metastases. At UHSFT, all referrals are ...discussed at the Wessex Neurosciences multidisciplinary team meeting. Referrals that satisfy the criteria set by NHS England (estimated prognosis greater than 6 months, absence or controlled extracranial disease or potentially controllable extracranial disease with a Karnofsky Performance Status >70%) will be offered SRST. This retrospective study was performed to assess overall survival rates of patients with brain metastases treated with SRST with further tumour subtype analysis. We also benchmarked our results with other SRST centres.
Method
Retrospective data collection was performed for all the patients who have been treated with SRST. Patients who received SRST to a single metastasis, multiple metastases and/or to the resection cavity between 01/01/2017 to 30/09/2019 were included in this study. All treatment was delivered using a LINAC based SRST platform. Prescription doses ranged from 13.5 Gy to 21 Gy in a single fraction, 21 to 24 Gy in 3 fractions and 25 Gy in 5 fractions. Patients are treated using a stereotactic thermoplastic immobilisation shell and dynamic conformal arc therapy with ExacTrac TM and Cone Beam CT imaging. Dates of death were obtained from the NHS Digital Spine and survival analysis using median overall survival was performed using the Kaplan Meier Method.
Results
277 patients were treated between 01/01/17 and 30/9/2019. The median overall survival from the Kaplan Meier Method was shown to be 14.7 months and the 6-month overall survival was 71% for all patients.
Sub-group analysis of individual tumour sites showed: lung (n=110) median OS 12.1 months, melanoma (n=58) median OS 26.4 months, breast (n=46) median OS not reached (67% still alive) but 18 months survival was 70%, renal (n=22) median OS 15.4 months and colorectal (n=19) median OS 6 months. “Other” tumour sites (n=22) included patients with ovarian, neuroendocrine, sarcoma, testis, oesophagus, unknown primary and gallbladder which were grouped together due to small patient numbers. 41% of patients treated were alive at the time of analysis.
Conclusion
Patients with brain metastases treated with SRST at UHFST have similar outcomes compared to other SRST centres. These patients have a median overall survival of 14.7 months. However, 29% of patients analysed did not survive more than 6 months. Further collection and analysis of the data might improve patient selection and their outcomes.
Abstract
Aims
Low-grade gliomas (LGG) slowly grow and infiltrate the brain's network architecture (the connectome). Unlike strokes that acutely damage the connectome, LGGs intricately remodel it, ...leading to varying deficits in executive function (i.e. attention, concentration, working memory). By longitudinally mapping the “mesoscale” architecture of the connectome, we may begin to systematically accelerate domain-general cognitive rehabilitation in LGG patients. In this study, we pursued the following aims: 1) track cognitive and connectome trajectories following LGG surgery, 2) determine optimal time period for cognitive rehabilitation, and 3) distinguish patients with perioperative predictors of long-term cognitive deficits (>1 year).
Method
With MRI and cognitive data from n=629 individuals across the lifespan, we first validated the structural, functional, and topological relevance of the multiple demand (MD) system for higher-order cognition. Next, in n=17 patients undergoing glioma surgery, we longitudinally acquired connectome and cognitive data: pre-surgery, post-surgery Day 1, Month 3, & 12. We assessed how glioma infiltration, surgery, and rehabilitation affected MD system trajectories at the single-subject level. Deploying transcriptomic and graph theoretical analyses, we tested if perioperative connectome modularity can accurately distinguish long-term cognitive trajectories.
Results
Controlling for age and sex, the MD system’s multi-scale architecture in health was positively associated with higher-order cognition (Catell’s fluid intelligence). Pre-operative glioma infiltration into the MD system was negatively associated with the number of long-term cognitive deficits (OCS-Bridge cognitive battery), suggesting its functional reorganisation. Mixed-effects modelling demonstrated the resilience of the MD system to infiltration and resection, while the early post-operative period was critical for effective neurorehabilitation. Graph analyses revealed perioperative modularity can distinguish patients with long-term cognitive deficits at one-year follow-up. Transcriptomic analyses of inter-module connector hubs revealed increased gene expression for mitochondrial metabolism and synaptic plasticity.
Conclusion
This is the first serial functional mapping of LGG patient trajectories for domain-general cognition. By assessing the mesoscale architecture, we demonstrate how connectomics can help overcome the intrinsic heterogeneity in LGG patients and predict long-term rehabilitation trajectories. We discuss how to identify neurobiologically-grounded personalised targets for 'interventional neurorehabilitation' following LGG surgery.
Abstract
Aims
Morbidity and mortality following resection of malignant primary brain tumours is high. The benefits of reoperation for recurrent tumours are uncertain and it is not known how ...frequently patients in England undergo further tumour resections. The aim of this study was to describe 30-day and one-year readmission rates, the clinical reasons for readmission and the rate of resections for recurrent tumours.
Method
Patient data was extracted from Hospital Episode Statistics (the hospital administrative data for NHS hospitals in England) for all supratentorial, malignant, primary brain tumour resections performed from April 2013 to March 2017. All subsequent non-elective readmissions to any NHS hospital and all readmissions for further tumour resection within 30 days and one year were analysed for the primary clinical diagnosis and primary procedure performed.
Results
A total of 6,982 patients were identified and the 30-day and one-year readmission rates were 18.6% (n=1,298) and 57.4% (n=4,007), respectively. The rates of reoperation for tumour resection were 0.5% (n=33) and 6.2% (n=432), respectively. The commonest reasons for 30-day readmission were post-operative complications (17.9% of admissions), general medical complications (17.3%) and surgical site infection (9.6%). The most frequently performed neurosurgical procedures were for treatment of surgical site infection (37.6% of procedures). The commonest reasons for readmission within one year were general medical complications (17.4%), seizures (14%), systemic infections (11.4%) and post-operative complications (11%). Almost half of all neurosurgical procedures performed within one year were reoperation for tumour resection (45.6%), while treatment of surgical site infection (17.9%) and CSF shunt insertions and revisions (9.1%) were also common.
Conclusion
This study provides a descriptive analysis of the rates of readmission, diagnosis on readmission, and the need for further neurosurgical procedures. The rate of non-elective readmissions within one year is high and these data may be useful for service planning and for counselling patients about their treatment. Additionally, these data contribute to the development of quality indicators, for benchmarking and comparing quality of care provision between neurosurgical units. Further research, with linkage to histology data and performance status, would support an analysis of the role of resection of recurrent, malignant, primary brain tumours.
Abstract
Aims
Cerebellar mutism syndrome occurs in 25% of children following resection of posterior fossa tumours. Characterised by mutism, emotional lability and cerebellar motor signs, the syndrome ...is usually reversible over weeks to months. Its pathophysiology remains unclear, but evidence from diffusion MRI studies has implicated damage to the superior cerebellar peduncles in the development of this condition. The objective of this study was to describe the application of automated tractography of the cerebellar peduncles to provide a high-resolution spatiotemporal profile of diffusion MRI changes in cerebellar mutism syndrome.
Method
A retrospective case-control study was performed at Lucille Packard Children’s Hospital, Stanford University. Thirty children with midline medulloblastoma (mean age ± standard deviation 8.8 ± 3.8 years) underwent volumetric T1-weighted and diffusion MRI at four timepoints over one year. Forty-nine healthy children (9.0 ± 4.2 years), scanned at a single timepoint, were included as age- and sex-matched controls. Cerebellar mutism syndrome status was determined by contemporaneous casenote review. Automated Fibre Quantification was used to segment each subject’s cerebellar peduncles (Figure 1), and fractional anisotropy was computed at 30 nodes along each tract. A non-parametric permutation-based method was used to generate a critical cluster size and p-value for by-node ANOVA group comparisons. Z-scores for patients’ fractional anisotropy at each node were calculated based on values from controls’ corresponding nodes; these were analysed using mixed ANOVA with post-hoc false discovery rate-corrected pairwise t-tests.
Results
13 patients developed cerebellar mutism syndrome. Automated fibre segmentation successfully identified the cerebellar peduncles in the majority of participants, but was more robust at follow-up timepoints (78.7% vs. 44.7% pre-operatively). Fractional anisotropy was significantly lower in the distal regions of the left superior cerebellar peduncle pre-operatively (p=0.0137) in patients compared to controls, although patients could not be distinguished pre-operatively with respect to cerebellar mutism syndrome status (Figure 2). Post-operative reductions in fractional anisotropy in children with cerebellar mutism syndrome were highly specific to the distal left superior cerebellar peduncle, and were most pronounced at follow-up timepoints (p=0.006; Figure 3). There were no significant differences in other cerebellar peduncles, either in along-tract fractional anisotropy or Z-scores, with respect to cerebellar mutism syndrome status.
Conclusion
A novel application of an automated tool to extract diffusion MRI data along the length of the cerebellar peduncles is described in a longitudinal retrospective cohort of paediatric medulloblastoma. Changes in fractional anisotropy in the cerebellar peduncles following tumour resection are described in a heretofore unprecedented level of spatiotemporal detail. In particular, children with post-operative cerebellar mutism syndrome show changes in the distal regions of the left superior cerebellar peduncle, and these changes persist up to a year post-operatively. These findings will have direct clinical implications for neurosurgeons performing resection of midline paediatric posterior fossa tumours.
Abstract
Aims
Data on the treatment and outcomes of patients with primary brain tumours in England is sparse. The GlioCova project uses linked national data from England to explore the incidence, ...treatment, outcomes, and treatment costs of all adult brain tumour patients in all 50,000 patients in England from 2013 – 2018. Here we present initial results from patients with glioblastoma (GBM).
Method
We used a linked dataset from the national cancer registration system in England including all adult patients diagnosed with a malignant or benign brain tumour between 2013 and 2018 (51,775 patients in total).
Glioblastoma patients were selected based on ICD-10 codes (C70, C71, C72), morphology codes (9440, 9441, 9442), and grade (G4, G3, GX and NA) from the national cancer registry. We extracted data on treatment (radiotherapy, chemotherapy, brain surgery or biopsy) and measured how many patients who had adjuvant Temozolomide completed 6 cycles.
Results
We identified 15,294 glioblastoma patients. Most had glioblastoma morphology (14,924), followed by gliosarcoma (264) and giant cell glioblastoma (106). Almost all had a cranial tumour (C71) while 17 had a tumour originating in the spinal cord, cranial nerves or other part of central nervous system (C72). Median age was 66 (IQR=17) and 60% were male. 51.9% (7,935) underwent surgery; an additional 18.2% (2,784) had a biopsy; 3,701 (24.2%) out of 15,294 patients received radiotherapy (only) and 316 (2.1%) received chemotherapy (only). 5,520 (36.1%) received both radiotherapy and chemo. Out of 4,101 GBM patients receiving temozolomide after radiotherapy, only 1,535 (37.4%) completed 6 cycles. The 7,935 GBM patients who had surgery had a median length of stay in hospital of 5 days (IQR=6) while those that had a biopsy had a median of 3 days (IQR=6).
Conclusion
We have presented a description of treatment of all GBM patients in England over a five-year period. This is the first time we have been able to understand detailed treatment patterns at a national scale, and significantly extends previous analyses. Further work will look at patient safety indicators, variation across centres and costs of treatment.
Acknowledgements
We would like to thank the GlioCova Expert Advisory Group for their input and discussion.
This work uses data provided by patients and collected by the NHS as part of their care and support.
Abstract
Aims
Glioblastoma (GBM) is currently an incurable malignancy with a very poor prognosis for the majority of patients. Many patients undergo debulking surgery, radiotherapy and chemotherapy ...however therapeutic options are limited, and this can lead to patients sourcing their own treatments. There is some evidence that cannabinoids have the effect of inhibiting GBM tumour growth through a variety of pathways, some of which include CB2 cannabinoid receptor pathway activation. We undertook a patient questionnaire to understand what alternative therapies patients are accessing and why, with a focus on cannabinoid use.
Method
We undertook a prospective observational questionnaire based qualitative study of 50 … consecutive patients undergoing treatment for glioblastoma at our centre.
Results
43 patients responded to our questionnaire. 33% of patients were taking some kind of supplementary therapy with 25% taking cannabis derivatives, mainly CBD oil. There were no clear discriminators amongst our cohort including age or sex when considering the likelihood of taking cannabis derivatives. 6 out of 11 (55%) patients taking cannabis derivatives reported some positive effects with improved sleep and general wellbeing being most commonly reported. Patients reported spending between £10-£300 per month with an average of £42 per month. Cannabis products were obtained via the internet or from friends.
Conclusion
This small cohort of patients indicates that a significant proportion of glioblastoma patients investigate and use alternative therapies, in particular cannabis oil. NICE guidance for clinicians simply notes there is insufficient evidence to support the use of cannabis oil in the treatment of this disease. Given the publicity and interest in the utility of cannabis oil to treat cancers this leaves patients to research the use of these agents without access to robust clinical data to guide their use or indeed to conclude they are not beneficial. The accessing of these compounds, potentially by a sizeable number of patients, leaves them vulnerable to unregulated perhaps unscrupulous drug sources. This small study has further highlighted the unmet need for information and guidance on supplementary treatments for glioma patients and this poses a challenge to all those treating this group of patients to answer a question our patients are clearly wanting answered.
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.
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