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Facial dysostosis syndromes (FDS) are rare congenital conditions that significantly impact facial function and appearance. At the time of this writing, standardised monitoring protocols for FDS are lacking, hampering research, and evidence-based care. Thus, a comprehensive dataset was developed within the European Reference Network for Rare and Complex Craniofacial Anomalies (ERN CRANIO). Candidate data elements were identified through a systematic literature review (1985–2024) and supplemented with elements from existing ERN CRANIO datasets and expert panel suggestions. A Delphi survey was then conducted among 61 clinicians and 3 patient representatives to assess each element’s relevance and reliability using a 9-point Likert scale. A subsequent hybrid consensus meeting with the expert panel shaped the final dataset, ensuring comprehensive coverage, avoiding overlap, and determining the appropriate timing for data collection. Of 200 data elements that entered the Delphi voting, 98 were strongly recommended, 102 scored neutral, and none were strongly discouraged. Ultimately, 110 elements were included, organised into 2 levels: Level 1, comprising exclusively patient-reported and parent-reported outcome measures; and Level 2, encompassing patient characteristics, treatment information, clinical outcomes, and imaging/diagnostics. This newly developed dataset marks the first international registry for FDS, offering considerable potential for collaborative research, cross-centre comparisons, and substantial improvements in care for patients with FDS worldwide. Real-world implementation will be essential to evaluate its feasibility and guide further refinements.

Background: Grade 2-3 diffuse gliomas (DGs) show extensive infiltration through white matter (WM) tracts. Along-tract analysis of WM tracts based on diffusion tensor tractography (DTI) can been performed to assess the microstructural integrity of WM tracts. The clinical implication of these DTI-related findings is still under debate, especially in tumor patients. The aim of this study was to analyze and compare diffusion-based parameters along WM tracts and variables specific to WM -tumor interactions in DGs and correlate them with preoperative neuropsychological assessment.

Methods: Fourteen patients with IDH-mutated grade 2-3 DGs were included. Tumor volumes were manually segmented on 3D-FLAIR images after spatial normalisation to MNI space. DTI was acquired using a single-shot echo-planar sequence on a 3T with 48 sampling directions. DTI data were reconstructed within the MNI space using q-space diffeomorphic reconstruction (QSDR) in DSI studio. Five bilateral sets of WM tracts were reconstructed based on the HCP-1065 template. All WM tracts were stretched to the same length of 100 indices, and for each index diffusion-based parameters fractional anisotropy (FA), radial diffusivity (RD), axial diffusivity (AD), mean diffusivity (MD) and quantitative anisotropy (QA) were sampled. Tumor-related parameters (TRP); tumor volume (Tv), maximum tumor presence (MTP) and the number of sequential indices in which a tumor is present (Te) were derived based on the along-tract analysis. Normal data were constructed by calculating the average and standard deviations of contralateral and not-affected WM tracts for each diffusion-based parameter, respectively. Affected WM tracts were individually compared to normal data using a z-test. Preoperative neuropsychological assessment was performed in all subjects and correlated to results from the along-tract analysis using correlation and logistic regression models.

Results: Abnormalities in diffusion-based parameters were detected in WM tracts. Topographical and quantitative information were presented within the same graph. AD and MD displayed the highest linear correlation with the TRPs. Abnormal QA showed a linear correlation with Tv per WM tract. Neuropsychological impairment was correlated with all the TRPs and with abnormal FA (p < 0.05) and abnormal QA (p < 0.01). Abnormal QA was the only independent variable able to predict the presence of neuropsychological impairment in the patients based on the linear regression analysis.

Conclusions: Graphical presentation of the along-tract analysis presented in this study shows that it may be a sensitive and robust method to acquire and display topographical and qualitative information regarding WM tracts in close proximity to DGs. Further studies and refinements to the methods presented herein may advance current clinical methods for evaluating displacement and infiltrations and further aid the efforts of pre-planning surgical interventions with the goal to maximise EOR and tailor oncological treatment.