Propuesta de modelo basado en redes neuronales para la clasificación de regiones del esqueleto a partir de imágenes TC

Existen múltiples contextos clínicos en los que la segmentación y diferenciación de las regiones del esqueleto pueden resultar de gran utilidad para observar la diferente afectación de los huesos en función de su localización. Actualmente, existen algunos estudios que han desarrollado algoritmos basados en árboles de segmentación jerárquica con este fin. Sin embargo, no existen estudios que apliquen técnicas de Machine Learning para lograr esta clasificación. Por este motivo, en el presente estudio se propone un modelo 2D basado en redes neuronales para la clasificación del esqueleto en 8 regiones anatómicas a partir de imágenes de Tomografía Computarizada. Para ello, se ha realizado una previa clasificación manual de 64 volúmenes de esqueleto en estas etiquetas, utilizando 54 para entrenamiento y 10 para test. Posteriormente, se ha evaluado la base de datos con 32 modelos 2D de diferente complejidad, variando el número de capas ocultas (N) y el número de neuronas en estas capas (U). Se observa como un aumento de la complejidad no siempre se corresponde con una mejora del rendimiento, a pesar de que si se requiere cierta complejidad para alcanzar resultados satisfactorios. Por otro lado, se observa como un modelo con un mayor N requiere de un mayor valor de U para conseguir una mejor clasificación. Finalmente, se ha concluido que el modelo de mejor rendimiento es aquel formado por 4 capas ocultas y 200 neuronas por capa, alcanzando un índice Dice general de 0,863, y Dice mayor a 0,7 para todas las regiones.Este trabajo está parcialmente financiado por una beca predoctoral (ayuda del Programa Propio de I+D+i 2020) de la Universidad Politécnica de Madrid. Este trabajo se ha desarrollado dentro del marco de la comunidad EELISA Health in the City

Lysine acetylation regulates the interaction between proteins and membranes

Lysine acetylation regulates the function of soluble proteins in vivo, yet it remains largely unexplored whether lysine acetylation regulates membrane protein function. Here, we use bioinformatics, biophysical analysis of recombinant proteins, live-cell fluorescent imaging and genetic manipulation of Drosophila to explore lysine acetylation in peripheral membrane proteins. Analysis of 50 peripheral membrane proteins harboring BAR, PX, C2, or EHD membrane-binding domains reveals that lysine acetylation predominates in membrane-interaction regions. Acetylation and acetylation-mimicking mutations in three test proteins, amphiphysin, EHD2, and synaptotagmin1, strongly reduce membrane binding affinity, attenuate membrane remodeling in vitro and alter subcellular localization. This effect is likely due to the loss of positive charge, which weakens interactions with negatively charged membranes. In Drosophila, acetylation-mimicking mutations of amphiphysin cause severe disruption of T-tubule organization and yield a flightless phenotype. Our data provide mechanistic insights into how lysine acetylation regulates membrane protein function, potentially impacting a plethora of membrane-related processes

An international survey on the pragmatic management of epistaxis

Epistaxis is one of the most common ear, nose and throat emergencies. The management of epistaxis has evolved significantly in recent years, including the use of nasal cautery and packs. However, a correct treatment requires the knowledge of nasal anatomy, potential risks, and complications of treatment. Epistaxis is often a simple and readily treatable condition, even though a significant bleed may have potentially severe consequences. At present, there are very few guidelines concerning this topic. The current Survey explored the pragmatic approach in managing epistaxis. A questionnaire, including 7 practical questions has been used. The current International Survey on epistaxis management reported a relevant prevalence (21.7%), mainly during childhood and senescence, an important hospitalization rate (11.8%), the common use of anterior packing and electrocoagulation, and the popular prescription of a vitamin supplement and intranasal creams

The value of metabolic parameters and textural analysis in predicting prognosis in locally advanced cervical cancer treated with chemoradiotherapy

CRUE-CSIC (Acuerdos Transformativos 2022)Objective The aim of the study was to assess the impact of clinical and metabolic parameters derived from 18F-FDG PET/CT (positron emission tomography–computed tomography) in patients with locally advanced cervical cancer (LACC) on prognosis. Methods Patients with LACC of stage IB2-IVA treated by primary radiochemotherapy followed by brachytherapy were enrolled in this retrospective study. Indexes derived from standardized uptake value (SUV), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and textural features of the primary tumor were measured for each patient. Overall survival (OS) and recurrence-free survival (RFS) rates were calculated according to Kaplan–Meier and survival curves were compared using the log-rank test. Uni- and multivariate analyses were performed using the Cox regression model. Results A total of 116 patients were included. Median follow-up was 58 months (range: 1–129). A total of 36 (31%) patients died. Five-year OS and RFS rates were 69 and 60%, respectively. Univariate analyses indicated that FIGO stage, the presence of hydronephrosis, high CYFRA 21.1 levels, and textural features had a significant impact on OS and RFS. MTV as well as SCC-Ag concentration were also significantly associated with OS. On multivariate analysis, the presence of hydronephrosis, CYFRA 21.1, and sphericity were independent prognostics factors for OS and RFS. Also, SCC-Ag level, MTV, and GLZLM (gray-level zone length matrix) ZLNU (zone length non-uniformity) were significantly associated with OS. Conclusion Classical prognostic factors and tumor heterogeneity on pretreatment PET/CT were significantly associated with prognosis in patients with LACC.Depto. de MedicinaDepto. de Radiología, Rehabilitación y FisioterapiaFac. de MedicinaTRUEpu

The value of metabolic parameters and textural analysis in predicting prognosis in locally advanced cervical cancer treated with chemoradiotherapy

Objective The aim of the study was to assess the impact of clinical and metabolic parameters derived from 18F-FDG PET/CT (positron emission tomography–computed tomography) in patients with locally advanced cervical cancer (LACC) on prognosis. Methods Patients with LACC of stage IB2-IVA treated by primary radiochemotherapy followed by brachytherapy were enrolled in this retrospective study. Indexes derived from standardized uptake value (SUV), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and textural features of the primary tumor were measured for each patient. Overall survival (OS) and recurrence-free survival (RFS) rates were calculated according to Kaplan–Meier and survival curves were compared using the log-rank test. Uni- and multivariate analyses were performed using the Cox regression model. Results A total of 116 patients were included. Median follow-up was 58 months (range: 1–129). A total of 36 (31%) patients died. Five-year OS and RFS rates were 69 and 60%, respectively. Univariate analyses indicated that FIGO stage, the presence of hydronephrosis, high CYFRA 21.1 levels, and textural features had a significant impact on OS and RFS. MTV as well as SCC-Ag concentration were also significantly associated with OS. On multivariate analysis, the presence of hydronephrosis, CYFRA 21.1, and sphericity were independent prognostics factors for OS and RFS. Also, SCC-Ag level, MTV, and GLZLM (gray-level zone length matrix) ZLNU (zone length non-uniformity) were significantly associated with OS. Conclusion Classical prognostic factors and tumor heterogeneity on pretreatment PET/CT were significantly associated with prognosis in patients with LACC