Correlation between NF1 genotype and imaging phenotype on whole-body MRI: NF1 radiogenomics. (16th June 2020)

• Record Type: Journal Article
• Authors: Liu, Yunpeng; Jordan, Justin T.; Bredella, Miriam A.; Erdin, Serkan; Walker, James A.; Vangel, Mark; Harris, Gordon J.; Plotkin, Scott R.; Cai, Wenli
• Is Part Of: Neurology. Volume 94:Number 24(2020)
• Publication Date: 2020-06-16
• Subjects: Neurology -- Periodicals; Neurology -- Periodicals; Neurologie -- Périodiques; 616.8
• DOI: 10.1212/WNL.0000000000009490
• Languages: English
• ISSNs: 0028-3878

Abstract

Abstract : Objective: To investigate the genotype–phenotype correlation between neurofibromatosis 1 (NF1) germline mutations and imaging features of neurofibromas on whole-body MRI (WBMRI) by using radiomics image analysis techniques. Materials and methods: Twenty-nine patients with NF1 who had known germline mutations determined by targeted next-generation sequencing were selected from a previous WBMRI study using coronal short tau inversion recovery sequence. Each tumor was segmented in WBMRI and a set of 59 imaging features was calculated using our in-house volumetric image analysis platform, 3DQI. A radiomics heatmap of 59 imaging features was analyzed to investigate the per-tumor and per-patient associations between the imaging features and mutation domains and mutation types. Linear mixed-effect models and one-way analysis of variance tests were performed to assess the similarity of tumor imaging features within mutation groups, between mutation groups, and between randomly selected groups. Results: A total of 218 neurofibromas (97 discrete neurofibromas and 121 plexiform neurofibromas) were identified in 19 of the 29 patients. The unsupervised hierarchical clustering in heatmap analysis revealed 6 major image feature patterns that were significantly correlated with gene mutation domains and types with strong to very strong associations of genotype–phenotype correlations in both per-tumor and per-patient studies ( p < 0.05, Cramer V > 0.5), whereas tumor size and locations showed no correlations with imaging features ( p = 0.79 and p = 0.42, respectively). The statistical analyses revealed that the number of significantly different features (SDFs) within mutation groups were significantly lower than those between mutation groups (mutation domains: 10.9 ± 9.5% vs 31.9 ± 23.8% and mutation types: 31.8 ± 30.7% vs 52.6 ± 29.3%). The first and second quartile p values of within-patient groups were more than 2 times higher than those between-patient groups. However, the numbers of SDFs between randomly selected groups were much lower (approximately 5.2%). Conclusion: This preliminary study identified the NF1 radiogenomics linkage between NF1 causative mutations and MRI radiomic features, i.e., the correlation between NF1 genotype and imaging phenotype on WBMRI.