Post-operative pediatric cerebellar mutism syndrome and its association with hypertrophic olivary degeneration

Background: The dentato-thalamo-cortical (DTC) pathway is recognized as the anatomical substrate for postoperative pediatric cerebellar mutism (POPCMS), a well-recognized complication affecting up to 31% of children undergoing posterior fossa brain tumour resection. The proximal structures of the DTC pathway also form a segment of the Guillain and Mollaret triangle, a neural network which when disrupted causes hypertrophic olivary degeneration (HOD) of the inferior olivary nucleus (ION). We hypothesize that there is an association between the occurrence of POPCMS and HOD and aim to evaluate this on MR imaging using qualitative and quantitative analysis of the ION in children with and without POPCMS. Methods: In this retrospective study we qualitatively analysed the follow up MR imaging in 48 children who underwent posterior fossa tumour resection for presence of HOD. Quantitative analysis of the ION was possible in 28 children and was performed using semi-automated segmentation followed by feature extraction and feature selection techniques and relevance of the features to POPCMS were evaluated. The diagnosis of POPCMS was made independently based on clinical and nursing assessment notes. Results: There was significant association between POPCMS and bilateral HOD (P=0.002) but not unilateral HOD. Quantitative analysis showed that hyperintensity in the left ION was the most relevant feature in children with POPCMS. Conclusions: Bilateral HOD can serve as a reliable radiological indicator in establishing the diagnosis of POPCMS particularly in equivocal cases. The strong association of signal change due to HOD in the left ION suggests that injury to the right proximal efferent cerebellar pathway plays an important role in the causation of POPCMS. Keywords: Cerebellar mutism syndrome (CMS); hypertrophic olivary degeneration; posterior fossa syndrome (PFS); postoperative pediatric cerebellar mutism syndrom

Skeletal Shape Correspondence Through Entropy

We present a novel approach for improving the shape statistics of medical image objects by generating correspondence of skeletal points. Each object's interior is modeled by an s-rep, i.e., by a sampled, folded, two-sided skeletal sheet with spoke vectors proceeding from the skeletal sheet to the boundary. The skeleton is divided into three parts: the up side, the down side, and the fold curve. The spokes on each part are treated separately and, using spoke interpolation, are shifted along that skeleton in each training sample so as to tighten the probability distribution on those spokes' geometric properties while sampling the object interior regularly. As with the surface/boundary-based correspondence method of Cates et al., entropy is used to measure both the probability distribution tightness and the sampling regularity, here of the spokes' geometric properties. Evaluation on synthetic and real world lateral ventricle and hippocampus data sets demonstrate improvement in the performance of statistics using the resulting probability distributions. This improvement is greater than that achieved by an entropy-based correspondence method on the boundary points

The molecular landscape and associated clinical experience in infant medulloblastoma: prognostic significance of second-generation subtypes

Aims: Biomarker‐driven therapies have not been developed for infant medulloblastoma (iMB). We sought to robustly sub‐classify iMB, and proffer strategies for personalized, risk‐adapted therapies. Methods: We characterized the iMB molecular landscape, including second‐generation subtyping, and the associated retrospective clinical experience, using large independent discovery/validation cohorts (n = 387). Results: iMBGrp3 (42%) and iMBSHH (40%) subgroups predominated. iMBGrp3 harboured second‐generation subtypes II/III/IV. Subtype II strongly associated with large‐cell/anaplastic pathology (LCA; 23%) and MYC amplification (19%), defining a very‐high‐risk group (0% 10yr overall survival (OS)), which progressed rapidly on all therapies; novel approaches are urgently required. Subtype VII (predominant within iMBGrp4) and subtype IV tumours were standard risk (80% OS) using upfront CSI‐based therapies; randomized‐controlled trials of upfront radiation‐sparing and/or second‐line radiotherapy should be considered. Seventy‐five per cent of iMBSHH showed DN/MBEN histopathology in discovery and validation cohorts (P < 0.0001); central pathology review determined diagnosis of histological variants to WHO standards. In multivariable models, non‐DN/MBEN pathology was associated significantly with worse outcomes within iMBSHH. iMBSHH harboured two distinct subtypes (iMBSHH‐I/II). Within the discriminated favourable‐risk iMBSHH DN/MBEN patient group, iMBSHH‐II had significantly better progression‐free survival than iMBSHH‐I, offering opportunities for risk‐adapted stratification of upfront therapies. Both iMBSHH‐I and iMBSHH‐II showed notable rescue rates (56% combined post‐relapse survival), further supporting delay of irradiation. Survival models and risk factors described were reproducible in independent cohorts, strongly supporting their further investigation and development. Conclusions: Investigations of large, retrospective cohorts have enabled the comprehensive and robust characterization of molecular heterogeneity within iMB. Novel subtypes are clinically significant and subgroup‐dependent survival models highlight opportunities for biomarker‐directed therapies

Metabolite profiles of medulloblastoma for rapid and non-invasive detection of molecular disease groups

\ua9 2024 The AuthorsBackground: The malignant childhood brain tumour, medulloblastoma, is classified clinically into molecular groups which guide therapy. DNA-methylation profiling is the current classification ‘gold-standard’, typically delivered 3–4 weeks post-surgery. Pre-surgery non-invasive diagnostics thus offer significant potential to improve early diagnosis and clinical management. Here, we determine tumour metabolite profiles of the four medulloblastoma groups, assess their diagnostic utility using tumour tissue and potential for non-invasive diagnosis using in vivo magnetic resonance spectroscopy (MRS). Methods: Metabolite profiles were acquired by high-resolution magic-angle spinning NMR spectroscopy (MAS) from 86 medulloblastomas (from 59 male and 27 female patients), previously classified by DNA-methylation array (WNT (n = 9), SHH (n = 22), Group3 (n = 21), Group4 (n = 34)); RNA-seq data was available for sixty. Unsupervised class-discovery was performed and a support vector machine (SVM) constructed to assess diagnostic performance. The SVM classifier was adapted to use only metabolites (n = 10) routinely quantified from in vivo MRS data, and re-tested. Glutamate was assessed as a predictor of overall survival. Findings: Group-specific metabolite profiles were identified; tumours clustered with good concordance to their reference molecular group (93%). GABA was only detected in WNT, taurine was low in SHH and lipids were high in Group3. The tissue-based metabolite SVM classifier had a cross-validated accuracy of 89% (100% for WNT) and, adapted to use metabolites routinely quantified in vivo, gave a combined classification accuracy of 90% for SHH, Group3 and Group4. Glutamate predicted survival after incorporating known risk-factors (HR = 3.39, 95% CI 1.4–8.1, p = 0.025). Interpretation: Tissue metabolite profiles characterise medulloblastoma molecular groups. Their combination with machine learning can aid rapid diagnosis from tissue and potentially in vivo. Specific metabolites provide important information; GABA identifying WNT and glutamate conferring poor prognosis. Funding: Children with Cancer UK, Cancer Research UK, Children\u27s Cancer North and a Newcastle University PhD studentship

Priority for the Worse Off and the Social Cost of Carbon

The social cost of carbon (SCC) is a monetary measure of the harms from carbon emission. Specifically, it is the reduction in current consumption that produces a loss in social welfare equivalent to that caused by the emission of a ton of CO2. The standard approach is to calculate the SCC using a discounted-utilitarian social welfare function (SWF)—one that simply adds up the well-being numbers (utilities) of individuals, as discounted by a weighting factor that decreases with time. The discounted-utilitarian SWF has been criticized both for ignoring the distribution of well-being, and for including an arbitrary preference for earlier generations. Here, we use a prioritarian SWF, with no time-discount factor, to calculate the SCC in the integrated assessment model RICE. Prioritarianism is a well-developed concept in ethics and theoretical welfare economics, but has been, thus far, little used in climate scholarship. The core idea is to give greater weight to well-being changes affecting worse off individuals. We find substantial differences between the discounted-utilitarian and non-discounted prioritarian SCC

Emergence and maintenance of actionable genetic drivers at medulloblastoma relapse

BACKGROUND: 90% of tumors) and established genetic drivers (e.g. SHH/WNT/P53 mutations; 60% of rMB events) were maintained from diagnosis. Critically, acquired and maintained rMB events converged on targetable pathways which were significantly enriched at relapse (e.g. DNA damage-signaling) and specific events (e.g. 3p loss) predicted survival post-relapse. CONCLUSIONS: rMB is defined by the emergence of novel events and pathways, in concert with selective maintenance of established genetic drivers. Together, these define the actionable genetic landscape of rMB and provide a basis for improved clinical management and development of stratified therapeutics, across disease-course

Development and clinical acceptability of a pre-operative risk stratification tool of cerebellar mutism syndrome in children with posterior fossa tumour

Aims: Despite identification of numerous pre-operative cerebellar mutism syndrome (CMS) clinical and radiological predictors, a unifying pre-operative risk stratification model for use during surgical consent is currently lacking. The aims of the project are (1) to develop a simple, easy to implemented risk scoring scheme to flag patients at higher risk of post-operative CMS; and (2) to assess its clinical acceptability amongst medical professionals. Methods: The combined cohort consists of 89 patients from two major treatment centres (age: 2-23yrs, gender 28M,61F, MRI pathology estimate 36 medulloblastoma, 40 pilocytic astrocytoma, 12 ependymoma, 1 non-committal); 26 (29%) of whom developed post-operative CMS. Post-operative CMS status was ascertained from clinical notes and pre-operative MRI scans, blinded to CMS status, underwent structured evaluation for 21 tightly-defined candidate imaging risk markers based on prior literature. All variables were first screened based upon results from univariate analysis and C4.5 decision tree. Stepwise logistic regression was then used to develop the optimal model, and multiple logistic regression coefficients for the predictors were converted into risk scores. Results: Univariate analysis identified five significant risks and C4.5 decision tree identified six predictors. The final model (Table 1) has an accuracy of 88.8% (79/89), with a sensitivity of 96.2% (25/26) and specificity of 85.7% (54/63). Using risk score cut-offs 203 and 238 permit discrimination into low (38/89, predicted probability < 3%), intermediate (17/89, predicted probability 3–52%) and high-risk (34/89, predicted probability 52%), respectively (Figure 1). Three illustrative cases from these categories will be used to collect clinicians’ opinion on surgical treatment decision and the acceptability of using this risk stratification for decision making and surgical consenting process. A web-based voting app will be used. Conclusions: A risk stratification model for post-operative CMS could flag patients at increased risk pre-operatively and may influence strategies for surgical treatment of cerebellar tumours. Following future testing and prospective validation, this risk scoring scheme may be utilised during the surgical consenting process