GoKawiilPatient cohorts
This study was approved by the institutional review board of GOSH NHS Foundation Trust (24/HRA/4335) with informed consent waived for retrospective analyses. Primary data collection was also approved by the institutional review boards of each participating study site before study commencement in accordance with the Declaration of Helsinki as amended61. Three independent cohorts of children diagnosed with primary pontine DMG/DIPG or thalamic DMG were identified and analysed retrospectively: (1) a discovery cohort from GOSH, UK; (2) an independent, multicentre external validation cohort from the Children’s Hospital Colorado (CHCO), USA; University of São Paulo, Brazil; Institute of Neurosurgery Dr. Alfonso Asenjo, Chile; and the HERBY clinical trial (NCT01390948)24; (3) a second, independent cohort of children with biopsied pontine DMG, H3K27-altered, enrolled on PNOC clinical trials. Participating centres are major international institutions with recognized subspecialty expertise in paediatric neuro-oncology. PNOC trial inclusion criteria have been previously reported. Inclusion criteria were identical across cohorts 1 and 2, with children reported between January 2000 and January 2024 inclusive:
(1) Consensus clinical–radiological diagnosis of DIPG, defined as the rapid (<3 month) onset of cranial nerve palsies, long-tract signs or cerebellar signs accompanied by MRI identification of an expansile, diffusely infiltrative mass arising from and involving ≥50% of the pons and which is T1-hypo- or iso-intense, T2-hyperintense and lacks or has minimal contrast enhancement20,21,22. or (2) Neuropathological (tissue biopsy) diagnosis of a primary pontine or thalamic DMG, H3K27-altered, consistent with World Health Organization 2021 criteria1. and (3) Child (aged under 18 years). (4) Treatment-naive brain MRI to include a three-dimensional volumetric T1-weighted sequence with high spatial resolution and two-dimensional T2-weighted or T2-weighted fluid-attenuated inversion recovery (FLAIR) sequences, both with a slice thickness of ≤5 mm. (5) Complete clinical data available for analysis, defined as treatment covariates and time to last follow-up or death, as appropriate.
Neuropathological diagnosis was required for the inclusion of long-term survivors of DMG (defined a priori as an overall survival ≥18 months from diagnosis), irrespective of tumour primary pontine or thalamic location23. Individuals with brain MRI of insufficient quality for analysis (for example, partial brain coverage or severe artefact(s) due to metal or motion) were excluded. Individuals lost to follow-up within 18 months (before the threshold for long-term survivorship) were excluded due to indeterminate outcome. Inclusion was based exclusively on the availability of the above data with no exclusions based on race, ethnicity, sex or other characteristics.
Clinical definitions
Age at diagnosis was defined as age at first brain MRI. Extent of resection was categorically stratified as unoperated, biopsy only, subtotal or gross-total by a board-certified paediatric neuroradiologist on postoperative brain MRI performed within 48 h of surgical resection. Gross-total resection was defined as the removal of all contrast-enhancing tumour volume while subtotal resection was defined as a greater than 10% but less than 90% reduction in tumour volume62,63. Further data were also collected for treatment modality, including but not limited to adjuvant radiotherapy and chemotherapy. Overall survival was defined as the time from diagnosis to death. Surviving patients were censored at the date of database closure (20 September 2024). Long-term survivors who did not participate in follow-up were censored at the date of last clinical follow-up. The time to last clinical follow-up was defined as the time from diagnosis to last clinical encounter.
Neuroimaging acquisition, segmentation and preprocessing
All individuals in the discovery cohort underwent brain MRI on the Siemens MAGNETOM Avanto (1.5 T) or Prisma (3 T) scanner. Given the retrospective multicentre nature of the study, there was significant heterogeneity in terms of scanner manufacturer and magnet field strength across the external validation cohorts. Patient brain MRI data were downloaded from institutional picture archiving and communications systems as digital communications in medicine (DICOM) files. Tumours were manually segmented in three planes (axial, coronal and sagittal), with reference to all available MRI sequences acquired at diagnosis, by researchers with expertise in neuroimaging (J.S., V.L., F.S., B.S.P. and R.S.O.) using ITK-SNAP (v.4.2.0)64. This yielded a binary tumour mask which was reviewed and, if necessary, corrected in consensus review with three board-certified paediatric neuroradiologists (K.M., A.B. and S.S.) consistent with a standardized, pan-institutional protocol for neuro-oncology MRI segmentation. After segmentation, the DICOM files were converted to Neuroimaging Informatics Technology Initiative (NIfTI) format using the nifti2dicom Python library (v.1.2.6). Brains were skull-stripped and extracted using SynthStrip and then registered to the Montreal Neurological Institute (MNI) MINC1 60MB paediatric template in MNI space (1.0 × 1.0 × 1.0 mm) using ANTs symmetric image normalization (SyN) registration65,66,67. Cost-function masking was applied to tumour masks to remove them from computations68. Tumours were then transformed to MNI space using forward SyN transforms and nearest-neighbour interpolation69. All registered tumours were manually compared to original, patient-specific neuroimaging and reviewed for neuroanatomic accuracy in MNI space by a board-certified paediatric neuroradiologist (K.M.). All segmentations were performed blinded to patient identity and clinical outcome.
Human connectome data acquisition and pre-processing
Integrative analyses of fMRI and dMRI data were performed to clinically translate the previously reported neural integration of DMG through tumour-specific whole-brain connectivity. High-resolution normative structural (three-dimensional T1-weighted) and resting-state fMRI were obtained for 1,000 healthy children aged 9.0 ± 0.2 years from the Adolescent Brain Cognitive Development Study (ABCD1000)35. High-resolution normative structural (three-dimensional T1-weighted) and advanced dMRI (multiple b values and directions) were obtained for 497 healthy children aged 13.0 ± 2.9 years from the Human Connectome Project (HCP) Lifespan Development dataset36,37. Cohort demographics and imaging parameters for both normative connectomes have been previously reported35,36,37. fMRI data preprocessing was performed using the Computational Brain Imaging Group preprocessing pipeline (https://github.com/bchcohenlab/BIDS_to_CBIG_fMRI_Preproc2016)70,71. dMRI data were preprocessed in line with the HCP minimal processing pipelines (https://github.com/Washington-University/HCPpipelines.git)72,73 and the resulting distortion-corrected b = 0 image was registered to MINC1 60MB through ANTs SyN registration74,75.
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