(1) Background: Radiomics analysis of spontaneous intracerebral hemorrhages on computed tomography (CT) images has been proven effective in predicting hematoma expansion and poor neurologic outcome. In contrast, there is limited evidence on its predictive abilities for traumatic intraparenchymal hemorrhage (IPH). (2) Methods: A retrospective analysis of 107 traumatic IPH patients was conducted. Among them, 45 patients (42.1%) showed hemorrhagic progression of contusion (HPC) and 51 patients (47.7%) had poor neurological outcome. The IPH on the initial CT was manually segmented for radiomics analysis. After feature extraction, selection and repeatability evaluation, several machine learning algorithms were used to derive radiomics scores (R-scores) for the prediction of HPC and poor neurologic outcome. (3) Results: The AUCs for R-scores alone to predict HPC and poor neurologic outcome were 0.76 and 0.81, respectively. Clinical parameters were used to build comparison models. For HPC prediction, variables including age, multiple IPH, subdural hemorrhage, Injury Severity Score (ISS), international normalized ratio (INR) and IPH volume taken together yielded an AUC of 0.74, which was significantly (p = 0.022) increased to 0.83 after incorporation of the R-score in a combined model. For poor neurologic outcome prediction, clinical variables of age, Glasgow Coma Scale, ISS, INR and IPH volume showed high predictability with an AUC of 0.92, and further incorporation of the R-score did not improve the AUC. (4) Conclusion: The results suggest that radiomics analysis of IPH lesions on initial CT images has the potential to predict HPC and poor neurologic outcome in traumatic IPH patients. The clinical and R-score combined model further improves the performance of HPC prediction.

Background

The molecular profile of early-onset colonic cancer is undefined. This study evaluated clinicopathological features and oncological outcomes of young patients with colonic cancer according to microsatellite status.

Methods

Anonymized data from an international collaboration were analysed. Criteria for inclusion were patients younger than 50 years diagnosed with stage I-III colonic cancer that was surgically resected. Clinicopathological features, microsatellite status, and disease-specific outcomes were evaluated.

Results

A total of 650 patients fulfilled the criteria for inclusion. Microsatellite instability (MSI) was identified in 170 (26.2 per cent), whereas 480 had microsatellite-stable (MSS) tumours (relative risk of MSI 2.5 compared with older patients). MSI was associated with a family history of colorectal cancer and lesions in the proximal colon. The proportions with pathological node-positive disease (45.9 versus 45.6 per cent; P = 1.000) and tumour budding (20.3 versus 20.5 per cent; P = 1.000) were similar in the two groups. Patients with MSI tumours were more likely to have BRAF (22.5 versus 6.9 per cent; P < 0.001) and KRAS (40.0 versus 24.2 per cent; P = 0.006) mutations, and a hereditary cancer syndrome (30.0 versus 5.0 per cent; P < 0.001; relative risk 6). Five-year disease-free survival rates in the MSI group were 95.0, 92.0, and 80.0 per cent for patients with stage I, II, and III tumours, compared with 88.0, 88.0, and 65.0 per cent in the MSS group (P = 0.753, P = 0.487, and P = 0.105 respectively).

Conclusion

Patients with early-onset colonic cancer have a high risk of MSI and defined genetic conditions. Those with MSI tumours have more adverse pathology (budding, KRAS/BRAF mutations, and nodal metastases) than older patients with MSI cancers.