Borrowing strength from adults: Transferability of AI algorithms for paediatric brain and tumour segmentation.

PURPOSE: AI brain tumour segmentation and brain extraction algorithms promise better diagnostic and follow-up of brain tumours in adults. The development of such tools for paediatric populations is restricted by limited training data but careful adaption of adult algorithms to paediatric population might be a solution. Here, we aim exploring the transferability of algorithms for brain (HD-BET) and tumour segmentation (HD-GLIOMA) in adults to paediatric imaging studies. METHOD: In a retrospective cohort, we compared automated segmentation with expert masks. We used the dice coefficient for evaluating the similarity and multivariate regressions for the influence of covariates. We explored the feasibility of automatic tumor classification based on diffusion data. RESULTS: In 42 patients (mean age 7 years, 9 below 2 years, 26 males), segmentation was excellent for brain extraction (mean dice 0.99, range 0.85-1), moderate for segmentation of contrast-enhancing tumours (mean dice 0.67, range 0-1), and weak for non-enhancing T2-signal abnormalities (mean dice 0.41). Precision was better for enhancing tumour parts (p < 0.001) and for malignant histology (p = 0.006 and p = 0.012) but independent from myelinisation as indicated by the age (p = 0.472). Automated tumour grading based on mean diffusivity (MD) values from automated masks was good (AUC = 0.86) but tended to be less accurate than MD values from expert masks (AUC = 1, p = 0.208). CONCLUSION: HD-BET provides a reliable extraction of the paediatric brain. HD-GLIOMA works moderately for contrast-enhancing tumours parts. Without optimization, brain tumor AI algorithms trained on adults and used on paediatric patients may yield acceptable results depending on the clinical scenario.

Computed tomography-guided microwave ablation of perivascular liver metastases from colorectal cancer: a study of the ablation zone, feasibility, and safety.

OBJECTIVES: To compare the ablation margins and safety of microwave ablation (MWA) of perivascular versus non-perivascular liver metastases from colorectal cancer (CRC) and to determine the risk factors for local tumor progression (LTP) after perivascular MWA. METHODS: Between June 2017 and June 2019, 84 metastases were treated: 39 perivascular (<5 mm from a vessel >3 mm), and 46 non-perivascular. Perivascular metastases were treated with either conventional or optimized protocols (maximum power and/or several heating cycles after repositioning the needle regardless of the initial tumor dimensions). The mean diameter of metastases was 15.4 mm (SD: 7.56). RESULTS: Vascular proximity did not result in a significant difference in ablation margins. The technical success rate, primary efficacy, and secondary efficacy were 90%, 66%, and 83%, respectively. Perivascular location was not a risk factor for time to LTP (p = 0.49), RFS (p = 0.52), or OS (p = 0.54). LTP was statistically related to the presence of a colonic obstruction (p < 0.05), number of metastases at the time of diagnosis (p < 0.05), type of protocol (p < 0.05), ablation margins (p < 0.001) and LTP was proportional to the number of liver resections before MWA (p < 0.05). There was no LTP in tumors ablated with margins over 10 mm. Two grade 4 complications occurred. CONCLUSION: MWA is an effective and safe treatment for perivascular liver metastases from CRC, provided that satisfactory margins are achieved. A maximalist attitude could be related to better local control.