Commercially Available Chest Radiograph AI Tools for Detecting Airspace Disease, Pneumothorax, and Pleural Effusion.

Background Commercially available artificial intelligence (AI) tools can assist radiologists in interpreting chest radiographs, but their real-life diagnostic accuracy remains unclear. Purpose To evaluate the diagnostic accuracy of four commercially available AI tools for detection of airspace disease, pneumothorax, and pleural effusion on chest radiographs. Materials and Methods This retrospective study included consecutive adult patients who underwent chest radiography at one of four Danish hospitals in January 2020. Two thoracic radiologists (or three, in cases of disagreement) who had access to all previous and future imaging labeled chest radiographs independently for the reference standard. Area under the receiver operating characteristic curve, sensitivity, and specificity were calculated. Sensitivity and specificity were additionally stratified according to the severity of findings, number of findings on chest radiographs, and radiographic projection. The χ2 and McNemar tests were used for comparisons. Results The data set comprised 2040 patients (median age, 72 years [IQR, 58-81 years]; 1033 female), of whom 669 (32.8%) had target findings. The AI tools demonstrated areas under the receiver operating characteristic curve ranging 0.83-0.88 for airspace disease, 0.89-0.97 for pneumothorax, and 0.94-0.97 for pleural effusion. Sensitivities ranged 72%-91% for airspace disease, 63%-90% for pneumothorax, and 62%-95% for pleural effusion. Negative predictive values ranged 92%-100% for all target findings. In airspace disease, pneumothorax, and pleural effusion, specificity was high for chest radiographs with normal or single findings (range, 85%-96%, 99%-100%, and 95%-100%, respectively) and markedly lower for chest radiographs with four or more findings (range, 27%-69%, 96%-99%, 65%-92%, respectively) (P < .001). AI sensitivity was lower for vague airspace disease (range, 33%-61%) and small pneumothorax or pleural effusion (range, 9%-94%) compared with larger findings (range, 81%-100%; P value range, > .99 to < .001). Conclusion Current-generation AI tools showed moderate to high sensitivity for detecting airspace disease, pneumothorax, and pleural effusion on chest radiographs. However, they produced more false-positive findings than radiology reports, and their performance decreased for smaller-sized target findings and when multiple findings were present. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Yanagawa and Tomiyama in this issue.

FGF23 in hemodialysis patients is associated with left ventricular hypertrophy and reduced ejection fraction / El FGF23 en pacientes en hemodiálisis se asocia con hipertrofia ventricular izquierda y fracción de eyección reducida

BACKGROUND: Fibroblast growth factor 23 (FGF23) is known to cause left ventricular hypertrophy (LVH), but controversy exists concerning its effect in dialysis. This study evaluated associations between FGF23 levels, echocardiography and prognosis in patients on hemodialysis (HD). METHODS: Patients >18 years on chronic HD were included in this cross-sectional study. Plasma C-terminal FGF23 concentration was measured with ELISA and transthoracic echocardiography was performed, both before and after HD treatment. RESULTS: 239 haemodialysis (HD) patients were included in the study. The FGF23 was median 3560 RU/ml (IQR 1447-9952). The mean left ventricular mass index (LVMI) was 110.2 ± 26.7 g/m2 and the left ventricular ejection fraction (LVEF) was 52.7 ± 9.9%. Defined by LVMI, LVH was found in 110 patients (46%), of which 92 (84%) had hypertension (p < 0.01). Patients with LVH had FGF23 levels of 5319 RU/ml (IQR 1858-12,859) and those without 2496 RU/ml (IQR 1141-7028) (p < 0.01). FGF23 was significant positive correlated with LVMI (p < 0.01), and negatively to LVEF (p < 0.01). In a multivariate analysis, FGF23 was correlated with LVEF (p < 0.01), but only marginally to LVMI (p < 0.01). Cardiovascular events in the follow up period was not correlated with FGF23. Furthermore, FGF23 was independently correlated with overall mortality (p< 0.001). CONCLUSION: FGF23 was positively correlated with LVH and negatively to LVEF. FGF23 was an independent predictor for overall mortality

ANTECEDENTES: Se sabe que el factor de crecimiento fibroblástico 23 (FGF23) provoca hipertrofia ventricular izquierda (HVI), pero existe controversia sobre su efecto en la diálisis. Este estudio evaluó las asociaciones entre los niveles del FGF23, la ecocardiografía y el pronóstico en pacientes en hemodiálisis (HD). MÉTODOS: Se incluyeron pacientes >18 años con HD crónica en este estudio transversal. La concentración del FGF23 en el extremo C del plasma se midió con ELISA y se realizó una ecocardiografía transtorácica, antes y después del tratamiento de HD. RESULTADOS: Se incluyeron 239 pacientes en HD en el estudio. El FGF23 tenía una mediana de 3.560 RU/ml (amplitud intercuartílica: 1.447-9.952). El índice de masa ventricular izquierdo (IMVI) medio fue de 110,2 ± 26,7 g/m2 y la fracción de eyección del ventrículo izquierdo (FEVI) fue del 52,7 ± 9,9%. Definida por el IMVI, la HVI se localizó en 110 pacientes (46%), de los cuales 92 (84%) presentaban hipertensión (p < 0,01). Los pacientes con HVI presentaron niveles del FGF23 de 5.319 RU/ml (amplitud intercuartílica: 1.858-12.859) y aquellos sin 2.496RU/ml (amplitud intercuartílica: 1.141-7.028) (p < 0,01). El FGF23 fue considerablemente positivo correlacionado con el IMVI (p < 0,01) y negativo con la FEVI (p < 0,01). En un análisis multivariante, el FGF23 se correlacionó con la FEVI (p <0,01), pero solo marginalmente con el IMVI (p < 0,01). Los episodios cardiovasculares en el período de seguimiento no se correlacionaron con el FGF23. Además, el FGF23 se correlacionó independientemente con la mortalidad general (p < 0,001). CONCLUSIÓN: El FGF23 se correlacionó positivamente con la HVI y negativamente con la FEVI. El FGF23 fue un factor independiente para la mortalidad general