MRI radiomics-based long-term evaluation and identification of imaging biomarkers for growth prediction of distinct nodular lesions in plexiform neurofibromas in NF1

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Neurofibromatosis type 1 (NF1) is a rare autosomal-dominantly inherited tumor predisposition syndrome caused by defects in the neurofibromin gene. Affected patients have a high risk to develop peripheral nerve sheath tumors, of which plexiform neurofibromas (PNF) and distinct nodular lesions (DNL) are of particular clinical relevance. PNF can grow to large sizes (>20% of body weight) and can cause severe morbidity of patients. DNL can grow inside of PNF or as singular lesions. Growth of DNL raises concern for transformation into a pre-malignant atypical neurofibroma (ANF). Unlike malignant tumors, ANFs as precursors to malignant nerve sheath tumors do not show local recurrence after previous resection nor the ability to metastasize. Early detection of such a transformation process is crucial for the outcome of these patients and therefore essential for risk-adapted patient care of NF1 patients. Image-based features have been reported to be promising to indicate the malignant transformation, but it is difficult to extract and quantify such imaging biomarkers in a consistent and objective manner by human observers. This limitation can be addressed by automated standardized extraction of imaging features, that is, by a radiomics analysis, in longitudinal image data of NF1 patients. However, previous radiomics NF1 studies were only performed as cross-sectional studies using single time-point data in small NF1 patient cohorts (N<79). Therefore, the purpose of the project is to identify imaging biomarkers for the development and growth prediction of DNL in PNF in NF1 patients using the first long-term radiomics-based MRI approach in this rare disease using a unique longitudinal whole-body (WB)-MRI data set. Inclusion criteria for the project are diagnosis of NF1 according to the NIH criteria and availability of ≥ 2 WB MRI examinations. WB MRIs of 249 patients covering an observation period of 18 years (2003 - 2021) are available for the long-term radiomics study. The total number of WB MRI examinations is about 1.300 (corresponding to a mean of 5.2 per patient). The project aims to answer the following questions: (1) Do radiomics signatures of DNL and PNF in NF1 patients differ and can be automatically classified? (2) Do radiomics feature expressions of DNL and PNF with different growth patterns (linear vs. non-linear volume growth, high / low growth rates) differ? (3) Can radiomics predict the growth of PNF and DNL as a prognostic imaging parameter? (4) Do radiomics signatures of NF1 patients with whole gene defects differ from those without major deletions (genotype-phenotype correlation)? (5) Can radiomics and genetic information be combined to further improve PNF and DNL development or growth prediction? Ideally, the investigated radiomics approach will enable the identification of non-invasive prognostic imaging biomarkers towards an individualized risk stratification of NF1 patients.