Background and aims:Assessment of ischemic lesions on computed tomography or MRI diffusion-weighted imaging (DWI) using the Alberta Stroke Program Early Computed Tomography Score (ASPECTS) is widely used to guide acute stroke treatment. However, it has never been defined how many voxels need to be affected to label a DWI-ASPECTS region ischemic. We aimed to assess the effect of various lesion load thresholds on DWI-ASPECTS and compare this automated analysis with visual rating. Materials and methods:We analyzed overlap of individual DWI lesions of 315 patients from the previously published predictive value of fluid-attenuated inversion recovery study with a probabilistic ASPECTS template derived from 221 CT images. We applied multiple lesion load thresholds per DWI-ASPECTS region (>0, >1, >10, and >20% in each DWI-ASPECTS region) to compute DWI-ASPECTS for each patient and compared the results to visual reading by an experienced stroke neurologist. Results:By visual rating, median ASPECTS was 9, 84 patients had a DWI-ASPECTS score ≤7. Mean DWI lesion volume was 22.1 (±35) ml. In contrast, by use of >0, >1-, >10-, and >20%-thresholds, median DWI-ASPECTS was 1, 5, 8, and 10; 97.1% (306), 72.7% (229), 41% (129), and 25.7% (81) had DWI-ASPECTS ≤7, respectively. Overall agreement between automated assessment and visual rating was low for every threshold used (>0%: κw = 0.020 1%: κw = 0.151; 10%: κw = 0.386; 20% κw = 0.381). Agreement for dichotomized DWI-ASPECTS ranged from fair to substantial (≤7: >10% κ = 0.48; >20% κ = 0.45; ≤5: >10% κ = 0.528; and >20% κ = 0.695). Conclusion:Overall agreement between automated and the standard used visual scoring is low regardless of the lesion load threshold used. However, dichotomized scoring achieved more comparable results. Varying lesion load thresholds had a critical impact on patient selection by ASPECTS. Of note, the relatively low lesion volume and lack of patients with large artery occlusion in our cohort may limit generalizability of these findings.

Background and purpose

Alberta Stroke Program Early Computed Tomographic Score (ASPECTS) has been used to estimate diffusion-weighted imaging (DWI) lesion volume in acute stroke. We aimed to assess correlations of DWI-ASPECTS with lesion volume in different middle cerebral artery (MCA) subregions and reproduce existing ASPECTS thresholds of a malignant profile defined by lesion volume ≥100 mL.

Methods

We analyzed data of patients with MCA stroke from a prospective observational study of DWI and fluid-attenuated inversion recovery in acute stroke. DWI-ASPECTS and lesion volume were calculated. The population was divided into subgroups based on lesion localization (superficial MCA territory, deep MCA territory, or both). Correlation of ASPECTS and infarct volume was calculated, and receiver-operating characteristics curve analysis was performed to identify the optimal ASPECTS threshold for ≥100-mL lesion volume.

Results

A total of 496 patients were included. There was a significant negative correlation between ASPECTS and DWI lesion volume (r=-0.78; P<0.0001). With regards to lesion localization, correlation was weaker in deep MCA region (r=-0.19; P=0.038) when compared with superficial (r=-0.72; P<0.001) or combined superficial and deep MCA lesions (r=-0.72; P<0.001). Receiver-operating characteristics analysis revealed ASPECTS≤6 as best cutoff to identify ≥100-mL DWI lesion volume; however, positive predictive value was low (0.35).

Conclusions

ASPECTS has limitations when lesion location is not considered. Identification of patients with malignant profile by DWI-ASPECTS may be unreliable. ASPECTS may be a useful tool for the evaluation of noncontrast computed tomography. However, if MRI is used, ASPECTS seems dispensable because lesion volume can easily be quantified on DWI maps.

Primitive neuroectodermal tumors of the central nervous system (CNS-PNETs) are highly aggressive, poorly differentiated embryonal tumors occurring predominantly in young children but also affecting adolescents and adults. Herein, we demonstrate that a significant proportion of institutionally diagnosed CNS-PNETs display molecular profiles indistinguishable from those of various other well-defined CNS tumor entities, facilitating diagnosis and appropriate therapy for patients with these tumors. From the remaining fraction of CNS-PNETs, we identify four new CNS tumor entities, each associated with a recurrent genetic alteration and distinct histopathological and clinical features. These new molecular entities, designated "CNS neuroblastoma with FOXR2 activation (CNS NB-FOXR2)," "CNS Ewing sarcoma family tumor with CIC alteration (CNS EFT-CIC)," "CNS high-grade neuroepithelial tumor with MN1 alteration (CNS HGNET-MN1)," and "CNS high-grade neuroepithelial tumor with BCOR alteration (CNS HGNET-BCOR)," will enable meaningful clinical trials and the development of therapeutic strategies for patients affected by poorly differentiated CNS tumors.

Current therapies for medulloblastoma, a highly malignant childhood brain tumour, impose debilitating effects on the developing child, and highlight the need for molecularly targeted treatments with reduced toxicity. Previous studies have been unable to identify the full spectrum of driver genes and molecular processes that operate in medulloblastoma subgroups. Here we analyse the somatic landscape across 491 sequenced medulloblastoma samples and the molecular heterogeneity among 1,256 epigenetically analysed cases, and identify subgroup-specific driver alterations that include previously undiscovered actionable targets. Driver mutations were confidently assigned to most patients belonging to Group 3 and Group 4 medulloblastoma subgroups, greatly enhancing previous knowledge. New molecular subtypes were differentially enriched for specific driver events, including hotspot in-frame insertions that target KBTBD4 and 'enhancer hijacking' events that activate PRDM6. Thus, the application of integrative genomics to an extensive cohort of clinical samples derived from a single childhood cancer entity revealed a series of cancer genes and biologically relevant subtype diversity that represent attractive therapeutic targets for the treatment of patients with medulloblastoma.