Prevalencia del síndrome de desgaste en radiólogos españoles / Prevalence of burnout syndrome in Spanish radiologists

Objetivos: Analizar la prevalencia y grado del síndrome de desgaste profesional entre radiólogos en España. Como objetivos secundarios se pretende identificar sus posibles factores desencadenantes y atenuantes para implementar intervenciones preventivas y correctivas, disminuyendo el estrés asociado y aumentando el rendimiento y la satisfacción laboral de los radiólogos. Material y métodos: Estudio transversal y observacional realizado mediante una encuesta en línea, anónima y voluntaria, desarrollada a través de formularios de Google® y dirigida a radiólogos especialistas y en formación. La encuesta se estructura en tres apartados: una valoración cualitativa del grado del síndrome de desgaste profesional a través del Maslach Burnout Inventory Human Services Survey (MBI-HSS), el segundo constituido por una serie de preguntas sociodemográficas y laborales, y el último apartado centrado en las posibles causas de estrés y de mejora en el entorno laboral. Los resultados de la encuesta se analizaron estadísticamente para determinar la asociación entre las variables y el síndrome, así como para determinar posibles factores de riesgo y protectores.Resultados: Tras difundir la encuesta en redes sociales y correo electrónico se recibieron un total de 226 respuestas (175 de especialistas y 51 de residentes). La media de edad fue 41 años (desviación estándar de 11 años, rango de 25 a 68), sin predominancia de género (52% hombres). La prevalencia del síndrome fue del 33%, sin diferencias significativas entre adjuntos y residentes. No se han identificado factores de riesgo que se asocien con el desgaste profesional. Tener docencia en el lugar de trabajo fue el único factor de protección.(AU)

Background and aimsThe primary objective was to analyze the prevalence and degree of professional burnout in radiologists in Spain. Secondary objectives were to identify possible factors that increase or decrease the risk of burnout to enable preventive and corrective measures, decrease the stress associated with this condition, and thereby increase radiologists’ performance and satisfaction at work.Material and methodsThis cross-sectional observational study used a voluntary, anonymous online survey of attending radiologists and residents through Google Forms®. The survey was structured into three sections: a qualitative assessment of the degree of professional burnout with the Maslach Burnout Inventory Human Services Survey (MBI-HSS), a series of sociodemographic and work-related questions, and a final section centered on possible causes of stress and improvements to the working environment.The results of the survey were analyzed statistically to determine which variables were associated with burnout syndrome as well as to identify possible risk factors and protective factors.ResultsAfter disseminating the survey through social networks and email contacts, we received a total of 226 responses (175 from attending radiologists and 51 from residents; 52% men; mean age, 41±11 years; age range, 25-68). The prevalence of the syndrome was 33%, without significant differences between attending radiologists and residents. No risk factors associated with burnout were identified. Teaching in the workplace was the only protective factor.ConclusionsOne-third of the respondents had burnout syndrome. Because the consequences of this syndrome can affect professionals’ personal life and their ability to do their jobs, early detection and intervention should be prioritized.(AU)

Prevalence of burnout syndrome in Spanish radiologists.

BACKGROUND AND AIMS: The primary objective was to analyze the prevalence and degree of professional burnout in radiologists in Spain. Secondary objectives were to identify possible factors that increase or decrease the risk of burnout to enable preventive and corrective measures, decrease the stress associated with this condition, and thereby increase radiologists' performance and satisfaction at work. MATERIAL AND METHODS: This cross-sectional observational study used a voluntary, anonymous online survey of attending radiologists and residents through Google Forms®. The survey was structured into three sections: a qualitative assessment of the degree of professional burnout with the Maslach Burnout Inventory Human Services Survey (MBI-HSS), a series of sociodemographic and work-related questions, and a final section centered on possible causes of stress and improvements to the working environment. The results of the survey were analyzed statistically to determine which variables were associated with burnout syndrome as well as to identify possible risk factors and protective factors. RESULTS: After disseminating the survey through social networks and email contacts, we received a total of 226 responses (175 from attending radiologists and 51 from residents; 52% men; mean age, 41 ± 11 years; age range, 25-68). The prevalence of the syndrome was 33%, without significant differences between attending radiologists and residents. No risk factors associated with burnout were identified. Teaching in the workplace was the only protective factor. CONCLUSIONS: One-third of the respondents had burnout syndrome. Because the consequences of this syndrome can affect professionals' personal life and their ability to do their jobs, early detection and intervention should be prioritized.

Development of severity and mortality prediction models for covid-19 patients at emergency department including the chest x-ray.

OBJECTIVES: To develop prognosis prediction models for COVID-19 patients attending an emergency department (ED) based on initial chest X-ray (CXR), demographics, clinical and laboratory parameters. METHODS: All symptomatic confirmed COVID-19 patients admitted to our hospital ED between February 24th and April 24th 2020 were recruited. CXR features, clinical and laboratory variables and CXR abnormality indices extracted by a convolutional neural network (CNN) diagnostic tool were considered potential predictors on this first visit. The most serious individual outcome defined the three severity level: 0) home discharge or hospitalization ≤ 3 days, 1) hospital stay >3 days and 2) intensive care requirement or death. Severity and in-hospital mortality multivariable prediction models were developed and internally validated. The Youden index was used for the optimal threshold selection of the classification model. RESULTS: A total of 440 patients were enrolled (median 64 years; 55.9% male); 13.6% patients were discharged, 64% hospitalized, 6.6% required intensive care and 15.7% died. The severity prediction model included oxygen saturation/inspired oxygen fraction (SatO2/FiO2), age, C-reactive protein (CRP), lymphocyte count, extent score of lung involvement on CXR (ExtScoreCXR), lactate dehydrogenase (LDH), D-dimer level and platelets count, with AUC-ROC = 0.94 and AUC-PRC = 0.88. The mortality prediction model included age, SatO2/FiO2, CRP, LDH, CXR extent score, lymphocyte count and D-dimer level, with AUC-ROC = 0.97 and AUC-PRC = 0.78. The addition of CXR CNN-based indices did not improve significantly the predictive metrics. CONCLUSION: The developed and internally validated severity and mortality prediction models could be useful as triage tools in ED for patients with COVID-19 or other virus infections with similar behaviour.

Prevalence of burnout syndrome during the COVID-19 pandemic and associated factors.

BACKGROUND: The coronavirus 2019 (COVID-19) epidemic spread throughout the world from the beginning of 2020, increasing healthcare professionals' workloads and levels of physical and emotional stress. AIMS: To determine the prevalence of burnout syndrome in Spanish radiologists during the COVID-19 pandemic and the factors associated with the development of this syndrome, and to compare these findings with those obtained before the pandemic. METHODS: This observation study took place between April 2020 and August 2020 (during the pandemic) through an online survey. A total of 150 responses were obtained. Demographic and work-related information was compiled. Burnout syndrome was measured with the Maslach Burnout Inventory Human Services Survey (MBI-HSS). The prevalence and characteristics of burnout syndrome obtained in this survey were compared with those of the same survey done in 2019. We performed a statistical analysis to identify possible risk factors and protective factors associated with this syndrome and to determine the homogeneity of the two samples. RESULTS: The prevalence of burnout syndrome increased during the COVID-19 pandemic (49.3% vs. 33.6%, p = 0.002). No risk factors or protective factors that were valid both before and after the pandemic were identified. No correlations were identified between sociodemographic or work-related characteristics and burnout syndrome. CONCLUSION: This study demonstrates that burnout syndrome increased significantly in radiologists during the COVID-19 pandemic, affecting nearly half of all those who responded to the survey. These results underline the need to assess support for professional wellbeing of radiologists in Spain. No correlations were identified between burnout and gender, age, number of calls, years in the job, annual income, teaching, marital status, number of children, or type of contract.

Elaboración de modelos predictivos de la gravedad y la mortalidad en pacientes con COVID-19 que acuden al servicio de urgencias, incluida la radiografía torácica / Development of severity and mortality prediction models for covid-19 patients at emergency department including the chest x-ray

Objetivos: Desarrollar modelos de predicción de pronóstico para pacientes con COVID-19 que acuden a urgencias, basados en la radiografía de tórax inicial (RXT), parámetros demográficos, clínicos y de laboratorio. Métodos: Se reclutaron todos los pacientes sintomáticos con COVID-19 confirmada, que ingresaron en urgencias de nuestro hospital entre el 24 de febrero y el 24 de abril de 2020. Los parámetros de la RXT, las variables clínicas y de laboratorio y los índices de hallazgos en RXT extraídos por una herramienta diagnóstica de inteligencia artificial en esta primera visita se consideraron potenciales predictores. El desenlace individual más grave definió los tres niveles de gravedad: 0) alta domiciliaria u hospitalización de 3 días o inferior, 1) hospitalización más de 3 días y 2) necesidad de cuidados intensivos o muerte. Se desarrollaron y validaron internamente modelos de predicción multivariable de gravedad y mortalidad hospitalaria. El índice de Youden se utilizó para la selección del umbral óptimo del modelo de clasificación. Resultados: Se registraron 440 pacientes (mediana de 64 años; 55,9% hombres); el 13,6% de los pacientes fueron dados de alta, el 64% estuvo hospitalizado más de 3 días, el 6,6% requirió cuidados intensivos y un 15,7% falleció. El modelo de predicción de gravedad incluyó saturación de oxígeno/fracción de oxígeno inspirado (SatO2/FiO2), edad, proteína C reactiva (PCR), linfocitos, puntuación de la extensión de la afectación pulmonar en la RXT (ExtScoreRXT), lactato deshidrogenasa (LDH), dímero D y plaquetas, con AUC-ROC=0,94 y AUC-PRC=0,88. El modelo de predicción de mortalidad incluyó edad, SatO2/FiO2, PCR, LDH, ExtScoreRXT, linfocitos y dímero D, con AUC-ROC=0,97 y AUC-PRC=0,78. La adición de índices radiológicos obtenidos por inteligencia artificial no mejoró significativamente las métricas predictivas.(AU)

Objectives: To develop prognosis prediction models for COVID-19 patients attending an emergency department (ED) based on initial chest X-ray (CXR), demographics, clinical and laboratory parameters. Methods: All symptomatic confirmed COVID-19 patients admitted to our hospital ED between February 24th and April 24th 2020 were recruited. CXR features, clinical and laboratory variables and CXR abnormality indices extracted by a convolutional neural network (CNN) diagnostic tool were considered potential predictors on this first visit. The most serious individual outcome defined the three severity level: 0) home discharge or hospitalization ≤ 3 days, 1) hospital stay>3 days and 2) intensive care requirement or death. Severity and in-hospital mortality multivariable prediction models were developed and internally validated. The Youden index was used for the optimal threshold selection of the classification model. Results: A total of 440 patients were enrolled (median 64 years; 55.9% male); 13.6% patients were discharged, 64% hospitalized, 6.6% required intensive care and 15.7% died. The severity prediction model included oxygen saturation/inspired oxygen fraction (SatO2/FiO2), age, C-reactive protein (CRP), lymphocyte count, extent score of lung involvement on CXR (ExtScoreCXR), lactate dehydrogenase (LDH), D-dimer level and platelets count, with AUC-ROC=0.94 and AUC-PRC=0.88. The mortality prediction model included age, SatO2/FiO2, CRP, LDH, CXR extent score, lymphocyte count and D-dimer level, with AUC-ROC=0.97 and AUC-PRC=0.78. The addition of CXR CNN-based indices did not improve significantly the predictive metrics. Conclusion: The developed and internally validated severity and mortality prediction models could be useful as triage tools in ED for patients with COVID-19 or other virus infections with similar behaviour.(AU)

[Development of severity and mortality prediction models for covid-19 patients at emergency department including the chest x-ray]. / Elaboración de modelos predictivos de la gravedad y la mortalidad en pacientes con COVID-19 que acuden al servicio de urgencias, incluida la radiografía torácica.

Objectives: To develop prognosis prediction models for COVID-19 patients attending an emergency department (ED) based on initial chest X-ray (CXR), demographics, clinical and laboratory parameters. Methods: All symptomatic confirmed COVID-19 patients admitted to our hospital ED between February 24th and April 24th 2020 were recruited. CXR features, clinical and laboratory variables and CXR abnormality indices extracted by a convolutional neural network (CNN) diagnostic tool were considered potential predictors on this first visit. The most serious individual outcome defined the three severity level: 0) home discharge or hospitalization ≤ 3 days, 1) hospital stay >3 days and 2) intensive care requirement or death. Severity and in-hospital mortality multivariable prediction models were developed and internally validated. The Youden index was used for the optimal threshold selection of the classification model. Results: A total of 440 patients were enrolled (median 64 years; 55.9% male); 13.6% patients were discharged, 64% hospitalized, 6.6% required intensive care and 15.7% died. The severity prediction model included oxygen saturation/inspired oxygen fraction (SatO2/FiO2), age, C-reactive protein (CRP), lymphocyte count, extent score of lung involvement on CXR (ExtScoreCXR), lactate dehydrogenase (LDH), D-dimer level and platelets count, with AUC-ROC = 0.94 and AUC-PRC = 0.88. The mortality prediction model included age, SatO2/FiO2, CRP, LDH, CXR extent score, lymphocyte count and D-dimer level, with AUC-ROC = 0.97 and AUC-PRC = 0.78. The addition of CXR CNN-based indices did not improve significantly the predictive metrics. Conclusion: The developed and internally validated severity and mortality prediction models could be useful as triage tools in ED for patients with COVID-19 or other virus infections with similar behaviour.

[Prevalence of burnout syndrome during the COVID-19 pandemic and associated factors]. / Prevalencia y factores de desgaste profesional en radiólogos durante la pandemia COVID-19.

Background: The coronavirus 2019 (COVID-19) epidemic spread throughout the world from the beginning of 2020, increasing healthcare professionals' workloads and levels of physical and emotional stress. Aims: To determine the prevalence of burnout syndrome in Spanish radiologists during the COVID-19 pandemic and the factors associated with the development of this syndrome, and to compare these findings with those obtained before the pandemic. Methods: This observation study took place between April 2020 and August 2020 (during the pandemic) through an online survey. A total of 150 responses were obtained. Demographic and work-related information was compiled. Burnout syndrome was measured with the Maslach Burnout Inventory Human Services Survey (MBI-HSS). The prevalence and characteristics of burnout syndrome obtained in this survey were compared with those of the same survey done in 2019. We performed a statistical analysis to identify possible risk factors and protective factors associated with this syndrome and to determine the homogeneity of the two samples. Results: The prevalence of burnout syndrome increased during the COVID-19 pandemic (49.3% vs. 33.6%, p = 0.002). No risk factors or protective factors that were valid both before and after the pandemic were identified. No correlations were identified between sociodemographic or work-related characteristics and burnout syndrome. Conclusion: This study demonstrates that burnout syndrome increased significantly in radiologists during the COVID-19 pandemic, affecting nearly half of all those who responded to the survey. These results underline the need to assess support for professional wellbeing of radiologists in Spain. No correlations were identified between burnout and gender, age, number of calls, years in the job, annual income, teaching, marital status, number of children, or type of contract.

Prevalencia y factores de desgaste profesional en radiólogos durante la pandemia COVID-19 / Prevalence of burnout syndrome during the COVID-19 pandemic and associated factors

Antecedentes: La epidemia por coronavirus 2019 (COVID-19) se ha extendido por todo el mundo desde principios de 2020, sometiendo a los profesionales sanitarios a una sobrecarga laboral y a un mayor nivel de estrés físico y emocional. Objetivos: El objetivo de este estudio es determinar la prevalencia de desgaste profesional y sus posibles factores asociados en los radiólogos españoles durante la COVID-19, y su comparación con la situación previa a la pandemia. Métodos: Estudio observacional realizado entre los meses de abril y agosto de 2020 (durante la pandemia) mediante una encuesta en línea. Se obtuvieron un total de 150 respuestas. Se recopiló y comparó la información demográfica y laboral de los encuestados. Se determinó la presencia del desgaste profesional con el cuestionario Maslach Burnout Inventory Human Services Survey (MBI-HSS) y se comparó su prevalencia y características con el estudio realizado de la misma manera en 2019. Se hizo un análisis estadístico para identificar los posibles factores de riesgo y protectores asociados con este síndrome, así como un análisis de homogeneidad entre las dos muestras. Resultados: La prevalencia del síndrome aumentó de forma significativa (p=0,002) durante la pandemia COVID-19 (49,3% frente a 33,6%). Ningún factor de riesgo o de protección se ha identificado como constante antes y después de la pandemia. No se ha identificado ninguna correlación del desgaste con las características sociodemográficas o laborales. Conclusión: Este estudio demuestra un aumento importante del desgaste profesional durante la pandemia por la COVID-19 con afectación de casi la mitad de los radiólogos encuestados. Estos resultados destacan la necesidad de valorar el apoyo orientado al bienestar profesional de los radiólogos en España. No se ha identificado correlación entre el síndrome y género, edad, número de guardias, antigüedad, ingreso anual, docencia, estado civil, número de hijos o tipo de contrato laboral.(AU)

Background: The coronavirus 2019 (COVID-19) epidemic spread throughout the world from the beginning of 2020, increasing healthcare professionals’ workloads and levels of physical and emotional stress. Aims: To determine the prevalence of burnout syndrome in Spanish radiologists during the COVID-19 pandemic and the factors associated with the development of this syndrome, and to compare these findings with those obtained before the pandemic. Methods: This observation study took place between April 2020 and August 2020 (during the pandemic) through an online survey. A total of 150 responses were obtained. Demographic and work-related information was compiled. Burnout syndrome was measured with the Maslach Burnout Inventory Human Services Survey (MBI-HSS). The prevalence and characteristics of burnout syndrome obtained in this survey were compared with those of the same survey done in 2019. We performed a statistical analysis to identify possible risk factors and protective factors associated with this syndrome and to determine the homogeneity of the two samples. Results: The prevalence of burnout syndrome increased during the COVID-19 pandemic (49.3% vs. 33.6%, p=0.002). No risk factors or protective factors that were valid both before and after the pandemic were identified. No correlations were identified between sociodemographic or work-related characteristics and burnout syndrome. Conclusion: This study demonstrates that burnout syndrome increased significantly in radiologists during the COVID-19 pandemic, affecting nearly half of all those who responded to the survey. These results underline the need to assess support for professional wellbeing of radiologists in Spain. No correlations were identified between burnout and gender, age, number of calls, years in the job, annual income, teaching, marital status, number of children, or type of contract.(AU)

Differences in multi-echo chemical shift encoded MRI proton density fat fraction estimation based on multifrequency fat peaks selection in non-alcoholic fatty liver disease patients.

AIM: To compare the performance of multi-echo chemical-shift-encoded (MECSE) magnetic resonance imaging (MRI) proton density fat fraction (PDFF) estimation, considering three different fat frequency peak combinations, for the quantification of steatosis in patients with non-alcoholic fatty liver disease (NAFLD). MATERIALS AND METHODS: The present study was a prospective cross-sectional research of 121 patients with metabolic syndrome and evidence of hepatic steatosis on ultrasound, who underwent a 3 T MRI examination. All patients were studied with a multifrequency MECSE sequence. The PDFF was calculated using six peaks (MECSEp123456), three peaks (MECSEp456), and a single peak (MECSEp5) model. The two simpler fat peak models were compared to the six peaks model, which was considered the reference standard. Linearity was evaluated using linear regression while agreement was described using Bland-Altman analysis. RESULTS: The mean age was 47 (±9) years and BMI was 29.9 (±2.9) kg/m2. Steatosis distribution was 15%/31%/54% (S1/S2/S3, respectively). Compared to MECSEp123456, both models provided linear PDFF measurements (R2= 0.99 and 0.97, MECSEp456 and MECSEp5 respectively). Regression slope (0.92; p<0.001) and mean Bland-Altman bias (-1.5%; 95% limits of agreement: -3.19%, 0.22%) indicated minimal underestimation by using PDFF-MECSEp456. Nonetheless, mean differences in PDFF estimations varied from -1.5% (MECSEp456,p=0.006) to -2.2% (MECSEp5,p<0.001) when compared to full six fat frequencies model. CONCLUSION: Although simpler spectral fat MECSE analysis shows a linear relationship with the standard six peaks model, their variation in estimated PDFF values introduces a low but clinically significant bias in fat quantification and steatosis grading in NAFLD patients.

Magnetic Resonance imaging analysis of liver fibrosis and inflammation: overwhelming gray zones restrict clinical use.

Magnetic resonance (MR) identification and grading of subjects with liver fibrosis and inflammation represents a clinical challenge. MR elastography plays a well-defined role in fibrosis estimation, but its use is not widely available in clinical settings. Given that liver MR is becoming the reference standard for fat and iron quantitation, there is a need to clarify whether there is any role for MR imaging in the concomitant evaluation of fibrosis and inflammation in this setting. This review summarizes the diagnostic estimations of different MR imaging parameters obtained from conventional non-contrast-enhanced multiple b values diffusion-weighted acquisitions, variable flip angles T1 relaxation maps and STIR images. Although some derived parameters have shown a significant correlation to histological scores, a small magnitude of effect with wide overlap across severity grades is the rule. Contrary to fat and iron quantification, the low precision and reproducibility of MR imaging metrics limits its clinical relevance in fibrosis and inflammation assessment. In a sequential clinical approach combining different methodologies, MR imaging has no applicability for ruling-out and low accuracy for ruling-in advanced fibrosis. Thereby, MR elastography remains as the only image method with high diagnostic accuracy for the detection of advanced fibrosis. Until date, inflammation remains in a gray zone where biopsy cannot be replaced, and further investigations are needed. The present review offers an in-depth discuss of the MR imaging diagnostic performance for the evaluation of liver fibrosis and inflammation, highlighting the need for scientific improvements.

Cuantificación por resonancia magnética de esteatosis hepática y pancreática en hepatopatía crónica / Quantifying steatosis in the liver and pancreas with MRI in patient with chronic liver disease

OBJETIVO: Comparar la esteatosis pancreática y hepática mediante la determinación de la fracción de grasa por densidad protónica (FGDP) por resonancia magnética (RM) en pacientes con enfermedad hepática crónica. MATERIAL Y MÉTODOS: Estudio transversal de 46 pacientes adultos con biopsia hepática por hepatitis viral crónica (n=19) o por enfermedad hepática crónica no alcohólica (EHNA) (n=27). La biopsia de hígado se utilizó como referencia para la gradación de la esteatosis hepática. Todos los pacientes se sometieron a valoración clínica y estudio de RM con una secuencia eco de gradiente codificado por desplazamiento químico con múltiples ecos (MECSE) para la cuantificación de la FGDP en hígado y páncreas. Se utilizó el coeficiente de correlación de Spearman para calcular el grado de asociación entre la FGDP hepática y los grados de esteatosis por biopsia, y entre la FGDP pancreática y la afectación hepática (grados de esteatosis y FGDP). El T-test se realizó para comparar variables continuas/ordinales en los grupos de hepatitis viral crónica y EHNA. Las variables categóricas se evaluaron mediante la prueba de gi. RESULTADOS: Se observó una correlación significativa entre la FGDP hepática y los grados de esteatosis (Rs=0,875, p < 0,001). También se evidenció una correlación positiva entre la FGDP del páncreas y la afectación hepática: grados de esteatosis (Rs=0,573, p < 0,001) y FGDP (Rs=0,536, p < 0,001). En el subgrupo de pacientes con EHNA crónica se mantuvo la correlación positiva significativa entre la FGDP pancreática y hepática (Rs=0,632, p < 0,001) y con la esteatosis hepática (Rs=0,608, p < 0,001). Estas relaciones se perdieron en el subgrupo de pacientes con hepatitis viral. CONCLUSIÓN: El depósito de grasa pancreática se correlaciona con la esteatosis hepática en pacientes con EHNA crónica. Esta relación se pierde en los pacientes con hepatitis viral crónica

AIM: To compare pancreatic and hepatic steatosis quantified by proton density fat fraction (PDFF) on magnetic resonance imaging (MRI) in patients with chronic liver disease. MATERIAL AND METHODS: This cross-sectional study included 46 adult patients who underwent liver biopsy for chronic viral hepatitis (n=19) or other chronic non-alcoholic liver diseases (NALD) (n=27). Liver biopsy was used as the gold standard for diagnosing and grading hepatic steatosis. All patients underwent clinical evaluation and MRI with a multi-echo chemical shift-encoded (MECSE) gradient-echo sequence for liver and pancreas PDFF quantification. We used Spearman's correlation coefficient to determine the degree of association between hepatic PDFF and steatosis grade, and between pancreatic PDFF and steatosis grade and hepatic PDFF. To compare the chronic viral hepatitis group and the NALD group, we used t-tests for continuous or ordinal variables and chi-square tests for categorical variables. RESULTS: Hepatic PDFF measurements correlated with steatosis grades (RS=0.875, p < 0.001). Pancreatic PDFF correlated with hepatic steatosis grades (RS=0.573, p < 0.001) and hepatic PDFF measurements (RS=0.536, p < 0.001). In the subgroup of patients with chronic NALD, the correlations remained significant between pancreatic PDFF and hepatic PDFF (RS=0.632, p < 0.001) and between pancreatic PDFF and liver steatosis (RS=0.608, p < 0.001); however, in the subgroup of patients with viral hepatitis these correlations were no longer significant. CONCLUSION: Pancreatic fat deposition correlates with hepatic steatosis in patients with chronic NALD, but not in those with chronic viral hepatitis

Valoración de la grasa hepática y pancreática como biomarcadores de imagen en el síndrome metabólico / Hepatic and pancreatic fat as imaging biomarkers of metabolic syndrome

OBJETIVO: Valorar objetivamente la afectación hepática y pancreática en el síndrome metabólico mediante biomarcadores de resonancia magnética (RM). MATERIAL Y MÉTODOS: Serie retrospectiva inicial de 407 pacientes con diagnóstico de síndrome metabólico, estudiados con RM en un único centro durante 2 años. Se excluyeron 154 pacientes por falta de datos clínico-analíticos, alteraciones pancreáticas o inadecuada calidad de la RM. Para la medición de la grasa hepática y pancreática se utilizaron las imágenes con desplazamiento químico (en fase y fase opuesta), con medidas por regiones de interés de la fracción grasa (%) en el páncreas (FGP) e hígado (FGH). La asociación entre las variables clínico-analíticas seleccionadas y la fracción grasa se evaluó mediante modelos de regresión beta. RESULTADOS: Se incluyeron finalmente 253 pacientes. La FGH fue del 4,9% y la FGP del 7,9%. La FGH no presentó ninguna asociación estadística con las variables clínico-analíticas. Sin embargo, la FGP se asoció positivamente con la edad (odds ratio [OR]=1,025, p <0,001) y la glucosa basal (OR=1,005, p <0,001). Se observó que los pacientes con diabetes presentaban valores más altos de FGP (OR=2,64, p = 0,038). La FGP y la FGH estaban relacionadas de manera estadísticamente positiva (OR=69,44, p <0,001). CONCLUSIONES: La esteatosis pancreática puede considerarse un marcador del síndrome metabólico y la diabetes. La RM cuantitativa permite el diagnóstico y la gradación de pacientes con páncreas graso mediante técnicas sencillas de desplazamiento químico

OBJECTIVE: To objectively evaluate hepatic and pancreatic involvement in metabolic syndrome through magnetic resonance imaging (MRI) biomarkers. MATERIAL AND METHODS: From an initial retrospective sample of 407 patients diagnosed with metabolic syndrome studied by MRI in a single center during a 2-year period, 154 were excluded because of a lack of clinical and/or laboratory data, pancreatic abnormalities, or inadequate quality of MRI studies. To measure hepatic and pancreatic fat, we used chemical shift imaging (in-phase and out-of-phase), measuring the fat fraction (%) in regions of interest in the pancreas and liver. Associations between the fat fraction and selected clinical and laboratory variables were assessed with beta regression models. RESULTS: In the end, 253 patients were included. The hepatic fat fraction was 4.9% and the pancreatic fat fraction was 7.9%. We found no significant associations between the hepatic fat fraction and any of the clinical or laboratory variables. However, the pancreatic fat fraction was positively associated with age (OR=1.025, p < 0.001) and baseline glucose (OR=1.005, p < 0.001). Patients with diabetes had higher values of pancreatic fat fraction (OR=2.64, p = 0.038). Pancreatic fat fraction and hepatic fat fraction were positively associated (OR=69.44, p < 0.001). CONCLUSIONS: Pancreatic steatosis can be considered a marker of metabolic syndrome and diabetes. Quantitative MRI enables the diagnosis and grading of fatty pancreas through simple chemical shift techniques

Critical review of HCC imaging in the multidisciplinary setting: treatment allocation and evaluation of response.

Imaging has not only an established role in screening and diagnosis of hepatocellular carcinoma (HCC) in patients with chronic liver inflammatory diseases, but also a crucial importance for patient stratification and treatment allocation, as well as for assessing treatment response. In the setting of increasing therapeutic options for HCC, the Barcelona Clinic Liver Cancer (BCLC) system still remains the most appropriate way to select candidate cohorts for best treatments. This classification takes into account the imaging information on tumor burden and extension, liver function, and cancer-related symptoms, stratifying patients in five risk categories (Stages 0, A, B, C and D) associated with different treatment options. Still now, there are no clear roles for biomarkers use in treatment allocation. The increasing use of locoregional non-surgical therapies in the different stages is highly dependent on reliable evaluation of treatment response, in particular when they are used with curative intention or for downstaging at liver transplantation re-assessment. Moreover, objective response (OR) has emerged as an important imaging biomarker, providing information on tumor biology, which can contribute for further prognostic assessment. Current guidelines for OR assessment recommend only the measurement of viable tumor according to mRECIST criteria, with further classification into complete response, partial response, stable disease or progressive disease. Either computed tomography (CT) or magnetic resonance (MR) imaging can be used for this purpose, and the Liver Imaging Reporting and Data System (LI-RADS) committee has recently provided some guidance for reporting after locoregional therapies. Nevertheless, imaging pitfalls resulting from treatment-related changes can impact with the correct evaluation of treatment response, especially after transarterial radioembolization (TARE). Volume criteria and emerging imaging techniques might also contribute for a better refinement in the assessment of treatment response and monitoring. As the role of imaging deeply expands in the multidisciplinary assessment of HCC, our main objective in this review is to discuss state-of-the-art decision-making aspects for treatment allocation and provide guidance for treatment response evaluation.

Quantifying steatosis in the liver and pancreas with MRI in patient with chronic liver disease. / Cuantificación por resonancia magnética de esteatosis hepática y pancreática en hepatopatía crónica.

AIM: To compare pancreatic and hepatic steatosis quantified by proton density fat fraction (PDFF) on magnetic resonance imaging (MRI) in patients with chronic liver disease. MATERIAL AND METHODS: This cross-sectional study included 46 adult patients who underwent liver biopsy for chronic viral hepatitis (n=19) or other chronic non-alcoholic liver diseases (NALD) (n=27). Liver biopsy was used as the gold standard for diagnosing and grading hepatic steatosis. All patients underwent clinical evaluation and MRI with a multi-echo chemical shift-encoded (MECSE) gradient-echo sequence for liver and pancreas PDFF quantification. We used Spearman's correlation coefficient to determine the degree of association between hepatic PDFF and steatosis grade, and between pancreatic PDFF and steatosis grade and hepatic PDFF. To compare the chronic viral hepatitis group and the NALD group, we used t-tests for continuous or ordinal variables and chi-square tests for categorical variables. RESULTS: Hepatic PDFF measurements correlated with steatosis grades (RS=0.875, p<0.001). Pancreatic PDFF correlated with hepatic steatosis grades (RS=0.573, p<0.001) and hepatic PDFF measurements (RS=0.536, p<0.001). In the subgroup of patients with chronic NALD, the correlations remained significant between pancreatic PDFF and hepatic PDFF (RS=0.632, p<0.001) and between pancreatic PDFF and liver steatosis (RS=0.608, p<0.001); however, in the subgroup of patients with viral hepatitis these correlations were no longer significant. CONCLUSION: Pancreatic fat deposition correlates with hepatic steatosis in patients with chronic NALD, but not in those with chronic viral hepatitis.

Hepatic and pancreatic fat as imaging biomarkers of metabolic syndrome. / Valoración de la grasa hepática y pancreática como biomarcadores de imagen en el síndrome metabólico.

OBJECTIVE: To objectively evaluate hepatic and pancreatic involvement in metabolic syndrome through magnetic resonance imaging (MRI) biomarkers. MATERIAL AND METHODS: From an initial retrospective sample of 407 patients diagnosed with metabolic syndrome studied by MRI in a single center during a 2-year period, 154 were excluded because of a lack of clinical and/or laboratory data, pancreatic abnormalities, or inadequate quality of MRI studies. To measure hepatic and pancreatic fat, we used chemical shift imaging (in-phase and out-of-phase), measuring the fat fraction (%) in regions of interest in the pancreas and liver. Associations between the fat fraction and selected clinical and laboratory variables were assessed with beta regression models. RESULTS: In the end, 253 patients were included. The hepatic fat fraction was 4.9% and the pancreatic fat fraction was 7.9%. We found no significant associations between the hepatic fat fraction and any of the clinical or laboratory variables. However, the pancreatic fat fraction was positively associated with age (OR=1.025, p<0.001) and baseline glucose (OR=1.005, p<0.001). Patients with diabetes had higher values of pancreatic fat fraction (OR=2.64, p=0.038). Pancreatic fat fraction and hepatic fat fraction were positively associated (OR=69.44, p<0.001). CONCLUSIONS: Pancreatic steatosis can be considered a marker of metabolic syndrome and diabetes. Quantitative MRI enables the diagnosis and grading of fatty pancreas through simple chemical shift techniques.

Re-evaluating the significance of the dive response during voluntary surface apneas in the bottlenose dolphin, Tursiops truncatus.

The dive response is well documented for marine mammals, and includes a significant reduction in heart rate (fH) during submersion as compared while breathing at the surface. In the current study we assessed the influence of the Respiratory Sinus Arrhythmia (RSA) while estimating the resting fH while breathing. Using transthoracic echocardiography we measured fH, and stroke volume (SV) during voluntary surface apneas at rest up to 255 s, and during recovery from apnea in 11 adult bottlenose dolphins (Tursiops truncatus, 9 males and 2 females, body mass range: 140-235 kg). The dolphins exhibited a significant post-respiratory tachycardia and increased SV. Therefore, only data after this RSA had stabilized were used for analysis and comparison. The average (±s.d.) fH, SV, and cardiac output (CO) after spontaneous breaths while resting at the surface were 44 ± 6 beats min-1, 179 ± 31 ml, and 7909 ± 1814 l min-1, respectively. During the apnea the fH, SV, and CO decreased proportionally with the breath-hold duration, and after 255 s they, respectively, had decreased by an average of 18%, 1-21%, and 12-37%. During recovery, the fH, SV, and CO rapidly increased by as much as 117%, 34%, and 190%, respectively. Next, fH, SV and CO rapidly decreased to resting values between 90-110 s following the surface apnea. These data highlight the necessity to define how the resting fH is estimated at the surface, and separating it from the RSA associated with each breath to evaluate the significance of cardiorespiratory matching during diving.

Análisis estructural cuantitativo del hueso alveolar trabecular de la mandíbula en tomografía computarizada multidetector: diferencias por tipo y estado dentario / Quantitative structural analysis of trabecular alveolar bone in the mandible by multidetector computed tomography: differences according to tooth presence and type

Antecedentes y objetivo: Existe una carencia de métricas cuantitativas de la calidad del hueso trabecular alveolar, factor determinante en implantología. El objetivo de este estudio es desarrollar una metodología con tomografía computarizada multidetector para objetivar la calidad del hueso trabecular y establecer diferencias entre los distintos tipos y el estado de las piezas dentarias mediante procesado de imágenes y análisis estructural. Materiales y métodos: Se analizan 20 pacientes con exploración de tomografía computarizada multidetector dental para la valoración del hueso mandibular y posiciones dentales. El análisis de las imágenes incluyó la segmentación automática de la mandíbula, obtención de secciones perpendiculares a la arcada dentaria y análisis estructural del hueso trabecular de cada sección. Se obtuvieron la ratio entre volumen de hueso y volumen total de la sección, el grosor, la separación y el número trabecular, y la atenuación promedio en unidades Hounsfield. Se analizaron diferencias entre tipos de diente (incisivos, caninos, premolares y molares) y entre estados de las piezas dentarias (ausente o presente). Resultados: Se obtuvieron diferencias estadísticamente significativas entre los tipos y estados de las piezas. Por tipo, los incisivos mostraron mayor ratio de hueso trabecular, con disminución progresiva para caninos, premolares y molares. Por estado, las secciones pertenecientes a dientes ausentes presentaron mayor ratio de hueso que con el diente presente. Conclusiones: La metodología desarrollada permite cuantificar las propiedades estructurales del hueso alveolar a partir de imágenes de tomografía computarizada multidetector. Los resultados obtenidos objetivan el estado del sustrato óseo de cara a la planificación y seguimiento de la colocación de implantes dentales

Background and objective: There is a lack of quantitative measures of the quality of alveolar trabecular bone, an important factor in implantology. This study aimed to develop a method of objectively assessing the quality of trabecular bone by means of image processing and structural analysis of multidetector computed tomography images and to establish differences between tooth types and tooth presence/absence. Materials and methods: We analyzed 20 patients who underwent multidetector computed tomography to evaluate mandibular bone and tooth positioning. Image analysis included automatic segmentation of the mandible, obtainment of sections perpendicular to the dental arch, and structural analysis of the trabecular bone in each section. We calculated the ratio between the volume of bone and the total volume of the section, the thickness, the trabecular number, and the mean attenuation in Hounsfield units. We analyzed the differences among different tooth types (incisors, canines, premolars, and molars) and between present and absent teeth. Results: We found statistically significant differences between different tooth types and between sections in which teeth were present or absent. Incisors had a greater ratio of trabecular bone; the ratio of trabecular bone progressively decreased from the incisors to the canines, premolars, and molars. The ratio of trabecular bone was greater in sections in which teeth were absent than in those in which teeth were present. Conclusions: The method allows to quantify the structural properties of alveolar bone from multidetector computed tomography images. Our results provide an objective picture of the bone substrate that can be useful for planning and following up dental implant procedures

Quantitative structural analysis of trabecular alveolar bone in the mandible by multidetector computed tomography: differences according to tooth presence and type. / Análisis estructural cuantitativo del hueso alveolar trabecular de la mandíbula en tomografía computarizada multidetector: diferencias por tipo y estado dentario.

BACKGROUND AND OBJECTIVE: There is a lack of quantitative measures of the quality of alveolar trabecular bone, an important factor in implantology. This study aimed to develop a method of objectively assessing the quality of trabecular bone by means of image processing and structural analysis of multidetector computed tomography images and to establish differences between tooth types and tooth presence/absence. MATERIALS AND METHODS: We analyzed 20 patients who underwent multidetector computed tomography to evaluate mandibular bone and tooth positioning. Image analysis included automatic segmentation of the mandible, obtainment of sections perpendicular to the dental arch, and structural analysis of the trabecular bone in each section. We calculated the ratio between the volume of bone and the total volume of the section, the thickness, the trabecular number, and the mean attenuation in Hounsfield units. We analyzed the differences among different tooth types (incisors, canines, premolars, and molars) and between present and absent teeth. RESULTS: We found statistically significant differences between different tooth types and between sections in which teeth were present or absent. Incisors had a greater ratio of trabecular bone; the ratio of trabecular bone progressively decreased from the incisors to the canines, premolars, and molars. The ratio of trabecular bone was greater in sections in which teeth were absent than in those in which teeth were present. CONCLUSIONS: The method allows to quantify the structural properties of alveolar bone from multidetector computed tomography images. Our results provide an objective picture of the bone substrate that can be useful for planning and following up dental implant procedures.