RESUMEN
Radiomic feature analysis has been shown to be effective at analyzing diagnostic images to model cancer outcomes. It has not yet been established how to best combine radiomic features in cancer patients with multifocal tumors. As the number of patients with multifocal metastatic cancer continues to rise, there is a need for improving personalized patient-level prognosis to better inform treatment. We compared six mathematical methods of combining radiomic features of 3,596 tumors in 831 patients with multiple brain metastases and evaluated the performance of these aggregation methods using three survival models: a standard Cox proportional hazards model, a Cox proportional hazards model with LASSO regression, and a random survival forest. Across all three survival models, the weighted average of the largest three metastases had the highest concordance index (95% confidence interval) of 0.627 (0.595-0.661) for the Cox proportional hazards model, 0.628 (0.591-0.666) for the Cox proportional hazards model with LASSO regression, and 0.652 (0.565-0.727) for the random survival forest model. This finding was consistent when evaluating patients with different numbers of brain metastases and different tumor volumes. Radiomic features can be effectively combined to estimate patient-level outcomes in patients with multifocal brain metastases. Future studies are needed to confirm that the volume-weighted average of the largest three tumors is an effective method for combining radiomic features across other imaging modalities and tumor types.
Asunto(s)
Neoplasias Encefálicas , Imagen por Resonancia Magnética , Modelos Biológicos , Radiocirugia , Anciano , Neoplasias Encefálicas/diagnóstico por imagen , Neoplasias Encefálicas/mortalidad , Neoplasias Encefálicas/radioterapia , Neoplasias Encefálicas/secundario , Supervivencia sin Enfermedad , Femenino , Estudios de Seguimiento , Humanos , Masculino , Persona de Mediana Edad , Metástasis de la Neoplasia , Estudios Retrospectivos , Tasa de SupervivenciaRESUMEN
Background: Radiomic feature analysis has been shown to be effective at modeling cancer outcomes. It has not yet been established how to best combine these radiomic features in patients with multifocal disease. As the number of patients with multifocal metastatic cancer continues to rise, there is a need for improving personalized patient-level prognostication to better inform treatment. Methods: We compared six mathematical methods of combining radiomic features of 3596 tumors in 831 patients with multiple brain metastases and evaluated the performance of these aggregation methods using three survival models: a standard Cox proportional hazards model, a Cox proportional hazards model with LASSO regression, and a random survival forest. Results: Across all three survival models, the weighted average of the largest three metastases had the highest concordance index (95% confidence interval) of 0.627 (0.595-0.661) for the Cox proportional hazards model, 0.628 (0.591-0.666) for the Cox proportional hazards model with LASSO regression, and 0.652 (0.565-0.727) for the random survival forest model. Conclusions: Radiomic features can be effectively combined to establish patient-level outcomes in patients with multifocal brain metastases. Future studies are needed to confirm that the volume-weighted average of the largest three tumors is an effective method for combining radiomic features across other imaging modalities and disease sites.
RESUMEN
Reaction of fluoride with waste oyster shell was studied. To enhance the stability and adsorption capacity, oyster shell was coated with Al(OH)3 and the adsorption behaviors were compared with the uncoated one. When at low fluoride concentration (<30â¯mg/L), fluoride removal efficiency decreased with increasing pH, and the adsorption could be modeled by Langmuir isotherm. At high fluoride concentration (>100â¯mg/L), linear adsorption isotherm fitted better, in which the adsorption capacity of fluoride increased linearly with increasing equilibrium fluoride concentration. The coated oyster shell showed higher adsorption capacity and wider workable pH range. From XPS analysis, the presence of CaF2 was confirmed by the peak at 684.7â¯eV when fluoride concentration increased. It was noted that magnesium content of waste oyster shell reacted with fluoride to form significant fractions of MgF2 whose corresponding peak was detected at 685.6-685.8â¯eV. For coated oyster shell, fluoride reacted with Ca, Mg, and Al. The reaction mechanism was mainly adsorption at low initial concentration, and precipitation-dominated at higher concentration.