Objective: The aim of this study was to systematically review the literature to synthesize and investigate repeatability and reproducibility of radiomic features, considered in building prognostic and prediction modelling with respect to NSCLC. Methods: The PubMed database was searched using combinations of the broad Haines and Ingui filters along with a set of text words specific to cancer, radiomics, reproducibility and repeatability. This systematic review was performed by two reviewers working entirely independently, and has been reported in compliance with PRISMA guidelines. Results: Out of 624 unique records, 41 full text articles were subjected to review. The studies were primarily in NSCLC. The imaging modalities were CT, PET and cone-beam CT – no studies addressed MR. Only 7 studies addressed in detail every methodological aspect related to image acquisition, pre-processing and feature extraction. Only few studies have made either the image set or software, or both, openly accessible. Due to heterogeneity in statistical metrics, a meta-analysis of pooled data was not possible. Conclusions: The repeatability and reproducibility of radiomic features are sensitive in varying degrees to processing details such as image acquisition settings, image reconstruction algorithm, image pre-processing and software used to extract radiomic features. Advances in Knowledge: Intra-class and concordance correlations were the most widely used statistical metrics, but arbitrarily selected cut-offs were variable. First-order features were overall more reproducible than shape metrics and textural features. Entropy was consistently reported as one of the most stable first-order features. There was no emergent consensus regarding either shape metrics or textural features.

Introduction : Extent of neck dissection is determined by the neck nodal positivity and indirectly has a bearing on neck dissection related morbidity. The current study prospectively compares the accuracy of these imaging techniques and FNAC to final histopathology. 31 patients of Oral cavity squamous cell carcinoma with no palpable lymphadenopathy were prospectively included in the study. Methodology : Thirty-one patients of oral cavity SCC who did not have any clinical lymphadenopathy treated at our centre from January 2018 to July 2018 were recruited for the study. All these patients underwent a whole body PET with contrast enhanced CT followed by a high-resolution ultrasound of the neck. Patients then underwent a US guided FNAC of the most suspicious lymph node. Results: 14 of the 31 patients had pathologically positive neck node. PET CT had 100 % negative predictive value. USG Neck diagnosed 22 patients to have suspicious lymph node with a negative predicitve value of 66.7% and positive predictive value of 50%. The combined yield of PET CT and USG Neck could produce a PPV of 100% and NPV of 68%. Conclusion : None of the test individually could predict the neck nodal positivity with absolute accuracy in our study. The best accuracy was when a combination of these tests were done.