Usefulness of magnetic resonance enterography in the clinical decision-making process for patients with inflammatory bowel disease.

OBJECTIVE: To evaluate the impact of magnetic resonance enterography (MRE) diagnosis on clinical decision-making regarding treatment choice and maintenance of treatment over time in patients with inflammatory bowel disease (IBD). METHODS: A cohort of patients who underwent MRE for IBD assessment between 2011 and 2014 was analyzed. From clinical records, we retrospectively retrieved their demographic data and clinical data on their IBD at the time of MRE, the results of MRE and the patient's clinical course. Medical management decisions made during the three months following MRE and at the 15-month follow-up were assessed. RESULTS: In total, 474 MREs were reviewed. In the first three-month period, MRE results led to changes in the medical management of 266 patients (56.1%). Of those, maintenance therapy was altered in 140 patients (68.3%) (90.7% step-up and 9.3% top-down strategy), 65 (24.4%) were prescribed a course of steroids and 61 (22.9%) underwent surgery. MRE confirmed a CD diagnosis in 14/41 patients (34.1%) previously diagnosed with indeterminate colitis or ulcerative colitis and in 4/18 patients (22.2%) with suspected IBD. At the 15-month follow-up, treatment remained unchanged in 289 patients (65.8%). CONCLUSIONS: These results suggest that MRE is a diagnostic tool that provides valid information for the clinical-decision making process for patients with CD.

Comparison of computed tomography and dual-energy X-ray absorptiometry in the evaluation of body composition in patients with obesity.

Objective: a) To evaluate the accuracy of the pre-existing equations (based on cm2 provided by CT images), to estimate in kilograms (Kg) the body composition (BC) in patients with obesity (PwO), by comparison with Dual-energy X-ray absorptiometry (DXA). b) To evaluate the accuracy of a new approach (based on both cm2 and Hounsfield Unit parameters provided by CT images), using an automatic software and artificial intelligence to estimate the BC in PwO, by comparison with DXA. Methods: Single-centre cross-sectional study including consecutive PwO, matched by gender with subjects with normal BMI. All the subjects underwent BC assessment by Dual-energy X-ray absorptiometry (DXA) and skeletal-CT at L3 vertebrae. CT images were processed using FocusedON-BC software. Three different models were tested. Model 1 and 2, based on the already existing equations, estimate the BC in Kg based on the tissue area (cm2) in the CT images. Model 3, developed in this study, includes as additional variables, the tissue percentage and its average Hounsfield unit. Results: 70 subjects (46 PwO and 24 with normal BMI) were recruited. Significant correlations for BC were obtained between the three models and DXA. Model 3 showed the strongest correlation with DXA (r= 0.926, CI95% [0.835-0.968], p<0.001) as well as the best agreement based on Bland - Altman plots. Conclusion: This is the first study showing that the BC assessment based on skeletal CT images analyzed by automatic software coupled with artificial intelligence, is accurate in PwO, by comparison with DXA. Furthermore, we propose a new equation that estimates both the tissue quantity and quality, that showed higher accuracy compared with those currently used, both in PwO and subjects with normal BMI.

The current state of knowledge on imaging informatics: a survey among Spanish radiologists.

BACKGROUND: There is growing concern about the impact of artificial intelligence (AI) on radiology and the future of the profession. The aim of this study is to evaluate general knowledge and concerns about trends on imaging informatics among radiologists working in Spain (residents and attending physicians). For this purpose, an online survey among radiologists working in Spain was conducted with questions related to: knowledge about terminology and technologies, need for a regulated academic training on AI and concerns about the implications of the use of these technologies. RESULTS: A total of 223 radiologists answered the survey, of whom 76.7% were attending physicians and 23.3% residents. General terms such as AI and algorithm had been heard of or read in at least 75.8% and 57.4% of the cases, respectively, while more specific terms were scarcely known. All the respondents consider that they should pursue academic training in medical informatics and new technologies, and 92.9% of them reckon this preparation should be incorporated in the training program of the specialty. Patient safety was found to be the main concern for 54.2% of the respondents. Job loss was not seen as a peril by 45.7% of the participants. CONCLUSIONS: Although there is a lack of knowledge about AI among Spanish radiologists, there is a will to explore such topics and a general belief that radiologists should be trained in these matters. Based on the results, a consensus is needed to change the current training curriculum to better prepare future radiologists.

Artificial intelligence for the detection of pancreatic lesions.

PURPOSE: Pancreatic cancer is one of the most lethal neoplasms among common cancers worldwide, and PCLs are well-known precursors of this type of cancer. Artificial intelligence (AI) could help to improve and speed up the detection and classification of pancreatic lesions. The aim of this review is to summarize the articles addressing the diagnostic yield of artificial intelligence applied to medical imaging (computed tomography [CT] and/or magnetic resonance [MR]) for the detection of pancreatic cancer and pancreatic cystic lesions. METHODS: We performed a comprehensive literature search using PubMed, EMBASE, and Scopus (from January 2010 to April 2021) to identify full articles evaluating the diagnostic accuracy of AI-based methods processing CT or MR images to detect pancreatic ductal adenocarcinoma (PDAC) or pancreatic cystic lesions (PCLs). RESULTS: We found 20 studies meeting our inclusion criteria. Most of the AI-based systems used were convolutional neural networks. Ten studies addressed the use of AI to detect PDAC, eight studies aimed to detect and classify PCLs, and 4 aimed to predict the presence of high-grade dysplasia or cancer. CONCLUSION: AI techniques have shown to be a promising tool which is expected to be helpful for most radiologists' tasks. However, methodologic concerns must be addressed, and prospective clinical studies should be carried out before implementation in clinical practice.

Usefulness of magnetic resonance enterography in the clinical decision-making process for patients with inflammatory bowel disease / Utilidad de la enterografía por resonancia magnética en la toma de decisiones clínicas en pacientes con enfermedad inflamatoria intestinal

OBJECTIVE: To evaluate the impact of magnetic resonance enterography (MRE) diagnosis on clinical decision-making regarding treatment choice and maintenance of treatment over time in patients with inflammatory bowel disease (IBD). METHODS: A cohort of patients who underwent MRE for IBD assessment between 2011 and 2014 was analyzed. From clinical records, we retrospectively retrieved their demographic data and clinical data on their IBD at the time of MRE, the results of MRE and the patient's clinical course. Medical management decisions made during the three months following MRE and at the 15-month follow-up were assessed. RESULTS: In total, 474 MREs were reviewed. In the first three-month period, MRE results led to changes in the medical management of 266 patients (56.1%). Of those, maintenance therapy was altered in 140 patients (68.3%) (90.7% step-up and 9.3% top-down strategy), 65 (24.4%) were prescribed a course of steroids and 61 (22.9%) underwent surgery. MRE confirmed a CD diagnosis in 14/41 patients (34.1%) previously diagnosed with indeterminate colitis or ulcerative colitis and in 4/18 patients (22.2%) with suspected IBD. At the 15-month follow-up, treatment remained unchanged in 289 patients (65.8%). CONCLUSIONS: These results suggest that MRE is a diagnostic tool that provides valid information for the clinical-decision making process for patients with CD

OBJETIVO: Evaluar el impacto del diagnóstico de la enterografía por resonancia magnética (ERM) en la toma de decisiones clínicas con respecto a la elección del tratamiento y el mantenimiento del mismo a lo largo del tiempo en pacientes con enfermedad inflamatoria intestinal (EII). MÉTODOS: Se analizó una cohorte de pacientes que se sometieron a ERM para la evaluación de EII entre 2011 y 2014. De los registros clínicos recuperamos retrospectivamente sus datos demográficos y datos clínicos sobre su EII en el momento de la ERM, los resultados de la ERM y la evolución clínica del paciente. Se evaluaron las decisiones de manejo médico tomadas durante los 3 meses posteriores a la ERM y a los 15 meses de seguimiento. RESULTADOS: Se revisaron 474 ERM. En el primer período de 3 meses, los resultados de la ERM llevaron a cambios en el manejo médico en 266 pacientes (56,1%). De ellos, se modificó el tratamiento de mantenimiento en 140 (68,3%) pacientes (se escaló en el 90,7% y top-down en el 9,3%), 65 (24,4%) recibieron un curso de esteroides y 61 (22,9%) se sometieron a cirugía. La ERM confirmó un diagnóstico de enfermedad de Crohn (EC) en 14/41 pacientes (34,1%) diagnosticados previamente con colitis indeterminada o colitis ulcerosa y en 4/18 pacientes (22,2%) con sospecha de EII. A los 15 meses de seguimiento, el tratamiento se mantuvo sin cambios en 289 (65,8%) pacientes. CONCLUSIONES: Estos resultados sugieren que la ERM es una herramienta de diagnóstico que proporciona información válida para el proceso de toma de decisiones clínicas para pacientes con EC

Oclusión intestinal por aceituna / Intestinal obstruction due to olive

No disponible

Neurocisticercosis / Neurocysticercosis

No disponible