RESUMEN
BACKGROUND: Oesophageal, gastroesophageal, and gastric malignancies are often diagnosed at locally advanced stage and multimodal therapy is recommended to increase the chances of survival. However, given the significant variation in treatment response, there is a clear imperative to refine patient stratification. The aim of this narrative review was to explore the existing evidence and the potential of radiomics to improve staging and prediction of treatment response of oesogastric cancers. METHODS: The references for this review article were identified via MEDLINE (PubMed) and Scopus searches with the terms "radiomics", "texture analysis", "oesophageal cancer", "gastroesophageal junction cancer", "oesophagogastric junction cancer", "gastric cancer", "stomach cancer", "staging", and "treatment response" until May 2024. RESULTS: Radiomics proved to be effective in improving disease staging and prediction of treatment response for both oesophageal and gastric cancer with all imaging modalities (TC, MRI, and 18F-FDG PET/CT). The literature data on the application of radiomics to gastroesophageal junction cancer are very scarce. Radiomics models perform better when integrating different imaging modalities compared to a single radiology method and when combining clinical to radiomics features compared to only a radiomics signature. CONCLUSIONS: Radiomics shows potential in noninvasive staging and predicting response to preoperative therapy among patients with locally advanced oesogastric cancer. As a future perspective, the incorporation of molecular subgroup analysis to clinical and radiomic features may even increase the effectiveness of these predictive and prognostic models.
RESUMEN
BACKGROUND: We aimed to validate Imamura nomogram for prediction of stone free rate in patients undergoing ureterolithotripsy (ULT). METHODS: From January 2013 to June 2016, patients undergoing laser semi-rigid ULT were prospectively enrolled at our center. All patients were preoperatively assessed with clinical history, blood samples, uranalysis and non-contrast enhanced computed tomography (CT). Treatment efficacy was assessed 1 month later by non-contrast enhanced CT. ROC curve was used to evaluate the performance characteristics of Imamura nomogram. RESULTS: Overall, we enrolled 275 patients. Median age was 55 years (IQR: 46/64), median length of stone was 9.8 mm (IQR: 7.5/12). Pyuria was detected in 6/275 (2.1%) patients. Stones were located at ureteropelvic junction in 55/275 (19%) patients, proximal ureter in 74/275 (26%) patients, middle and distal ureter in 66/275 (24%) patients and 82/275 (30%) patients, respectively. At 1-month follow-up, 209/275 (76%) patients were stone free. Imamura nomogram presented an AUC of 0.67 (95% CI: 0.580-0.761) for the prediction of stone free rate. At the best cut-off value of 75%, sensitivity was 76%, specificity was 55%, positive predictive value (PPV) was 83% and negative predictive value was 45%. CONCLUSIONS: We firstly validated Imamura nomogram in a European cohort study. It proved a reasonable accuracy (area under curve: 0.67) and a good PPV (83%). Further studies should confirm our results to support the routine clinical use of Imamura nomogram as a tool to predict ULT outcomes.
