Impact of trametinib on the neuropsychological profile of NF1 patients.

PURPOSE: The use of trametinib in the treatment of pediatric low-grade gliomas (PLGG) and plexiform neurofibroma (PN) is being investigated in an ongoing multicenter phase II trial (NCT03363217). Preliminary data shows potential benefits with significant response in the majority of PLGG and PN and an overall good tolerance. Moreover, possible benefits of MEK inhibitor therapy on cognitive functioning in neurofibromatosis type 1 (NF1) were recently shown which supports the need for further evaluation. METHODS: Thirty-six patients with NF1 (age range 3-19 years) enrolled in the phase II study of trametinib underwent a neurocognitive assessment at inclusion and at completion of the 72-week treatment. Age-appropriate Wechsler Intelligence Scales and the Trail Making Test (for children over 8 years old) were administered at each assessment. Paired t-tests and Reliable Change Index (RCI) analyses were performed to investigate change in neurocognitive outcomes. Regression analyses were used to investigate the contribution of age and baseline score in the prediction of change. RESULTS: Stable performance on neurocognitive tests was revealed at a group-level using paired t-tests. Clinically significant improvements were however found on specific indexes of the Wechsler intelligence scales and Trail Making Test, using RCI analyses. No significant impact of age on cognitive change was evidenced. However, lower initial cognitive performance was associated with increased odds of presenting clinically significant improvements on neurocognitive outcomes. CONCLUSION: These preliminary results show a potential positive effect of trametinib on cognition in patients with NF1. We observed significant improvements in processing speed, visuo-motor and verbal abilities. This study demonstrates the importance of including neuropsychological evaluations into clinical trial when using MEK inhibitors for patients with NF1.

Development of a semi-automatic segmentation technique based on mean magnetic resonance imaging intensity thresholding for volumetric quantification of plexiform neurofibromas.

Rationale and objectives: Plexiform neurofibromas (PNs) are peripheral nerve tumors that occur in 25-50 % of patients with neurofibromatosis type 1. PNs may have complex, diffused, and irregular shapes. The objective of this work was to develop a volumetric quantification method for PNs as clinical assessment is currently based on unidimensional measurement. Materials and methods: A semi-automatic segmentation technique based on mean magnetic resonance imaging (MRI) intensity thresholding (SSTMean) was developed and compared to a similar and previously published technique based on minimum image intensity thresholding (SSTMini). The performance (volume and computation time) of the two techniques was compared to manual tracings of 15 tumors of different locations, shapes, and sizes. Performance was also assessed using different MRI sequences. Reproducibility was assessed by inter-observer analysis. Results: When compared to manual tracing, quantification performed with SSTMean was not significantly different (mean difference: 1.2 %), while volumes computed by SSTMini were significantly different (p < .0001, mean difference: 13.4 %). Volumes quantified by SSTMean were also significantly different than the ones assessed by SSTMini (p < .0001). Using SSTMean, volumes quantified with short TI inversion recovery, T1-, and T2-weighted imaging were not significantly different. Computation times used by SSTMean and SSTMini were significantly lower than for manual segmentation (p < .0001). The highest difference measured by two users was 8 cm3. Conclusion: Our method showed accuracy compared to a current gold standard (manual tracing) and reproducibility between users. The refined segmentation threshold and the possibility to define multiple regions-of-interest to initiate segmentation may have contributed to its performance. The versatility and speed of our method may prove useful to better monitor volumetric changes in lesions of patients enrolled in clinical trials to assessing response to therapy.