Background: Dysphagia negatively impacts quality of life and requires diets with specifically modified textures. The IDDSI (International Dysphagia Diet Standardization Initiative) scale provides standardized criteria to ensure food safety. This research aims to explore and validate the IDDSI scale adapted to the consumption of foods developed with 3D printing in patients with dysphagia. Methodology: Different dishes were designed and validated using 3D printing and were evaluated by both healthcare professionals and people with dysphagia. In the second phase, participants analyzed their texture using the IDDSI scale. A mixed methodological approach was applied, combining quantitative data (from validated scales) and qualitative data (obtained through interviews and focus groups), ensuring methodological triangulation. Methods: In the first phase of the study, different dishes were cooked and designed using 3D printing technology and were previously evaluated by both healthcare professionals and people with dysphagia. In the second phase, all the dishes validated in the first phase were analyzed and classified according to their texture using the IDDSI. Results: A total of 24 dishes, backed by 204 validations, were determined to be suitable for people with dysphagia and compatible with 3D printing. According to the IDDSI analysis, 36% of these dishes were classified as level 3 (soft texture) and 64% as level 4 (thick purée), levels internationally recognized as safe and suitable for people with dysphagia and suitable for 3D printing. The application of the IDDSI scale eliminated ambiguities in the description of textures, facilitating clear communication between healthcare professionals, caregivers, people with dysphagia, and companies that produce 3D-printed foods, as well as the standardization of 3D food printing processes related to textures. The application of the IDDSI scale eliminated ambiguities in the description of textures, facilitating clear communication between healthcare professionals, caregivers, people with dysphagia, and companies producing 3D-printed food products. This enabled the standardization of 3D food printing processes and the definition of their textures. At the same time, 3D printing proved to be a viable and effective tool for customizing meals that are safe, appropriate, and sensorially appealing. Conclusions: The feasibility of combining the IDDSI scale with 3D printing to develop diets tailored to the needs of people with dysphagia is confirmed. This integrative approach represents an innovation in the field of nutrition for people with swallowing problems, especially in contexts with limited scientific evidence, combining the validation of modified textures with 3D printing technology. There are effective tools for producing safe, suitable and sensorially appealing meals.

El objetivo del presente trabajo fue explorar el impacto psicosocial por la introducción de alimentos impresos con tecnología 3D, en la calidad de vida percibida de pacientes con disfagia. Para ello se diseñó un estudio pre-post con intervención específica basada en la degustación de menú completo (dos comidas principales y tres postres), entre 16 pacientes con alteraciones en la deglución en diferentes grados. Los participantes respondieron el SWAL-QoL (versión española) y una entrevista semiestructurada para identificar las áreas de la vida afectadas por la disfunción, así como las expectativas que podría suponer la incorporación en su vida diaria, de un programa alimentario alternativo por impresión 3D. Los datos cualitativos fueron tratados con el programa Atlas.ti (V9), bajo el criterio de saturación de datos. Los resultados cualitativos revelan que las limitaciones en la deglución generan, por una parte, estados emocionales negativos como el sentimiento de dependencia, inapetencia generalizada, tristeza o resignación y por la otra; alteración en la esfera social por la pérdida de autonomía, reducido contacto social y escasas actividades de ocio. Las conclusiones apuntan que sólo la posibilidad de incorporar variedad de alimentos, especialmente de sabores, impresos con tecnología 3D, mejora la calidad de vida en términos prospectivos. Esto significa que sólo con la expectativa, en un futuro cercano, de ingerir libremente una variedad de alimentos y sabores, los pacientes experimentan emociones positivas y una mejora en sus relaciones vitales con familiares y cuidadores en el presente.

The morphology of blood vessels in retinal fundus images is a key biomarker for diagnosing conditions such as glaucoma, hypertension, and diabetic retinopathy. This study introduces a deep learning-based method for automatic blood vessel segmentation, trained from scratch on 44 clinician-annotated images. The proposed architecture integrates Bidirectional Long Short-Term Memory (Bi-LSTM) layers with dropout to mitigate overfitting. A distinguishing feature of this approach is the column-wise processing, which improves feature extraction and segmentation accuracy. Additionally, a custom data augmentation technique tailored for retinal images is implemented to improve training performance. The results are presented in their raw form—without post-processing—to objectively assess the method’s effectiveness and limitations. Further refinements, including pre- and post-processing and the use of image rotations to combine multiple segmentation outputs, could significantly boost performance. Overall, this work offers a novel and effective approach to the still unresolved task of retinal vessel segmentation, contributing to more reliable automated analysis in ophthalmic diagnostics.