Pub Date : 2021-04-01DOI: 10.4067/S0717-93082021000100046
E. LucasEbensperger, G. HuáscarRodríguez, H. DavidLadróndeGuevara
{"title":"Caso de desafío diagnóstico","authors":"E. LucasEbensperger, G. HuáscarRodríguez, H. DavidLadróndeGuevara","doi":"10.4067/S0717-93082021000100046","DOIUrl":"https://doi.org/10.4067/S0717-93082021000100046","url":null,"abstract":"","PeriodicalId":35339,"journal":{"name":"Revista Chilena de Radiologia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41451856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-01DOI: 10.4067/S0717-93082021000100004
Alejandro Canelo L., Arturo Canelo M., F. de Barbieri M.
{"title":"¿Qué dijo doctor? Una revisión de términos radiológicos conflictivos","authors":"Alejandro Canelo L., Arturo Canelo M., F. de Barbieri M.","doi":"10.4067/S0717-93082021000100004","DOIUrl":"https://doi.org/10.4067/S0717-93082021000100004","url":null,"abstract":"","PeriodicalId":35339,"journal":{"name":"Revista Chilena de Radiologia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44611425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-01DOI: 10.4067/S0717-93082021000100003
J. P. C. Quiroga
{"title":"¿Gadolinio sin restricciones?","authors":"J. P. C. Quiroga","doi":"10.4067/S0717-93082021000100003","DOIUrl":"https://doi.org/10.4067/S0717-93082021000100003","url":null,"abstract":"","PeriodicalId":35339,"journal":{"name":"Revista Chilena de Radiologia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46866443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-01DOI: 10.4067/S0717-93082021000100040
A. Castillo, A. Astorga, N. D. Bazaes, C. Kara, P. Méndez
{"title":"Caso de desafío diagnóstico","authors":"A. Castillo, A. Astorga, N. D. Bazaes, C. Kara, P. Méndez","doi":"10.4067/S0717-93082021000100040","DOIUrl":"https://doi.org/10.4067/S0717-93082021000100040","url":null,"abstract":"","PeriodicalId":35339,"journal":{"name":"Revista Chilena de Radiologia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45978791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-01DOI: 10.4067/S0717-93082021000100017
Eleonora Horvath
Molecular subtypes of breast cancer - what breast imaging radiologists need to know Conclusiones: Los radiólogos dedicados a imágenes mamarias deben estar familiarizados con los conceptos de la clasificación molecular, necesarios para la correlación radio-patológica de los resultados de biopsias mamarias y para proporcionar una atención óptima a las pacientes. Abstract Objective: Summarize the impact generated by the introduction of the molecular classification of breast cancer in the different specialties involved so as to offer radiologists a global view of the current management of this disease, from diagnosis to treatment. Findings: In the last two decades, molecular information based on genomic analysis has helped to understand the biological diversity of breast cancers and generated profound changes in the clinical oncological practice. With simpler and available immunohistochemical tests, it is possible to approximate the molecular classification, enabling the prediction of clinical behavior of the different subtypes (Luminal, HER2-positive, Triple-negative) and their response to different therapies, facilitating the design of personalized treatments. Although no findings absolutely pathognomonic have been described in mammography, ultrasound or magnetic resonance imaging, the molecular classification concept has already two concrete uses: for predicting Luminal A or Triple-negative phenotype on images and for evaluating the neoadjuvant chemotherapy response by magnetic resonance. A future application is expected in the area of radiogenomics. Conclusions: Radiologists dedicated to breast imaging should be familiar with the concepts of molecular classification, necessary for radio-pathological correlation of breast biopsy results and in order to provide an optimal patient care.
结论:Los radiólogos dedicados a imágenes mamarias deben estar familiarizados con Los conceptos de la clasificación Molecular, necesarios para correlación radio-patológica de Los resultados de biopsias mamarias as para proporciar una atención óptima a las pacentes。摘要目的:总结乳腺癌分子分类在不同专科的引入所产生的影响，为放射科医师提供从诊断到治疗的乳腺癌管理的全局视图。在过去的二十年中，基于基因组分析的分子信息有助于了解乳腺癌的生物多样性，并在临床肿瘤学实践中产生了深刻的变化。通过更简单和可用的免疫组织化学测试，可以近似地进行分子分类，从而可以预测不同亚型(Luminal, her2阳性，三重阴性)的临床行为及其对不同治疗的反应，从而促进个性化治疗的设计。虽然在乳房x线摄影、超声或磁共振成像中没有发现绝对的病理特征，但分子分类概念已经有两个具体的用途:预测图像上的Luminal A或三阴性表型，以及通过磁共振评估新辅助化疗的反应。在放射基因组学领域有望有一个未来的应用。结论:致力于乳腺成像的放射科医生应该熟悉分子分类的概念，这对于乳腺活检结果的放射病理相关性和提供最佳的患者护理是必要的。
{"title":"Subtipos moleculares del cáncer mamario - lo que el radiólogo dedicado a imágenes mamarias debe saber","authors":"Eleonora Horvath","doi":"10.4067/S0717-93082021000100017","DOIUrl":"https://doi.org/10.4067/S0717-93082021000100017","url":null,"abstract":"Molecular subtypes of breast cancer - what breast imaging radiologists need to know Conclusiones: Los radiólogos dedicados a imágenes mamarias deben estar familiarizados con los conceptos de la clasificación molecular, necesarios para la correlación radio-patológica de los resultados de biopsias mamarias y para proporcionar una atención óptima a las pacientes. Abstract Objective: Summarize the impact generated by the introduction of the molecular classification of breast cancer in the different specialties involved so as to offer radiologists a global view of the current management of this disease, from diagnosis to treatment. Findings: In the last two decades, molecular information based on genomic analysis has helped to understand the biological diversity of breast cancers and generated profound changes in the clinical oncological practice. With simpler and available immunohistochemical tests, it is possible to approximate the molecular classification, enabling the prediction of clinical behavior of the different subtypes (Luminal, HER2-positive, Triple-negative) and their response to different therapies, facilitating the design of personalized treatments. Although no findings absolutely pathognomonic have been described in mammography, ultrasound or magnetic resonance imaging, the molecular classification concept has already two concrete uses: for predicting Luminal A or Triple-negative phenotype on images and for evaluating the neoadjuvant chemotherapy response by magnetic resonance. A future application is expected in the area of radiogenomics. Conclusions: Radiologists dedicated to breast imaging should be familiar with the concepts of molecular classification, necessary for radio-pathological correlation of breast biopsy results and in order to provide an optimal patient care.","PeriodicalId":35339,"journal":{"name":"Revista Chilena de Radiologia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48375953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-01DOI: 10.4067/S0717-93082021000100008
Enzo Raschio A., Cassandra Contreras R., Felipe Allende N., Pablo Maturana Q.
tórax posteroanterior. Los resultados obtenidos demostraron una exactitud del 100% para el primer modelo en la clasificación de estructuras torácicas, mientras que para la identificación de cardiomegalia la exactitud fue de 99.2 ± 0.8%. El segundo modelo de segmentación autónoma tiene una exactitud del 93 ± 29.0%. A partir de estos resultados y con el desarrollo actual de Deep Learning basado en la clasificación y localización consideramos que esta herramienta permitirá en el futuro automatizar algunos procesos que facilitarán la tarea de todos quienes se relacionan al diagnóstico por imágenes. Abstract Artificial intelligence algorithms have developed a great advance in image recognition related tasks, being able to identify complex patterns and providing quantitative information. This paper shows the design process of two new Deep Learning models, the first one capable of classifying thoracic structures and the presence of cardiomegaly; the second one allows posterior rib arches autonomous segmentation in posterior-anterior chest X-rays. The results showed 100% accuracy for the thoracic structures classification model, while for the cardiomegaly identification model, the accuracy was 99.2 ± 0.8%. The second autonomous segmentation model showed 93 ± 29.0% accuracy. Based on these results and with the current Deep Learning development, we consider this tool will help automate processes that will facilitate the task of all those who are related to diagnostic imaging.
{"title":"Inteligencia artificial: Desarrollo de algoritmos de clasificación y segmentación en radiografía de tórax","authors":"Enzo Raschio A., Cassandra Contreras R., Felipe Allende N., Pablo Maturana Q.","doi":"10.4067/S0717-93082021000100008","DOIUrl":"https://doi.org/10.4067/S0717-93082021000100008","url":null,"abstract":"tórax posteroanterior. Los resultados obtenidos demostraron una exactitud del 100% para el primer modelo en la clasificación de estructuras torácicas, mientras que para la identificación de cardiomegalia la exactitud fue de 99.2 ± 0.8%. El segundo modelo de segmentación autónoma tiene una exactitud del 93 ± 29.0%. A partir de estos resultados y con el desarrollo actual de Deep Learning basado en la clasificación y localización consideramos que esta herramienta permitirá en el futuro automatizar algunos procesos que facilitarán la tarea de todos quienes se relacionan al diagnóstico por imágenes. Abstract Artificial intelligence algorithms have developed a great advance in image recognition related tasks, being able to identify complex patterns and providing quantitative information. This paper shows the design process of two new Deep Learning models, the first one capable of classifying thoracic structures and the presence of cardiomegaly; the second one allows posterior rib arches autonomous segmentation in posterior-anterior chest X-rays. The results showed 100% accuracy for the thoracic structures classification model, while for the cardiomegaly identification model, the accuracy was 99.2 ± 0.8%. The second autonomous segmentation model showed 93 ± 29.0% accuracy. Based on these results and with the current Deep Learning development, we consider this tool will help automate processes that will facilitate the task of all those who are related to diagnostic imaging.","PeriodicalId":35339,"journal":{"name":"Revista Chilena de Radiologia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43536925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-01DOI: 10.4067/S0717-93082020000400131
J. P. C. Quiroga
{"title":"Congreso chileno virtual de radiología: Una mirada en retrospectiva","authors":"J. P. C. Quiroga","doi":"10.4067/S0717-93082020000400131","DOIUrl":"https://doi.org/10.4067/S0717-93082020000400131","url":null,"abstract":"","PeriodicalId":35339,"journal":{"name":"Revista Chilena de Radiologia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41580080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-01DOI: 10.4067/S0717-93082020000400145
C. Alvarez, Jaime, I. Concejo, Paula, A. Ferreiro, Concepción, G. Gálvez, Esther, G. Hoyas, María Azahara, T. Zubiaguirre, Íñigo, R. Rodríguez, Cristián, T. Ocampo, Wilmar, O. Sánchez, Francisca, P. Martínez
Abstract: Given the current pandemic caused by SARS-CoV-2, the scientific community is making an effort to share knowledge of this emerging disease To contribute to this effort, we have done a comprehensive review of the clinical history and imaging tests in patients affected by COVID-19 in our institution, one of the most affected by the pandemic in the Community of Madrid (Spain) The aim of this review is to describe the radiological findings in the lungs and show the most frequent extrapulmonary pathology as well as some entities that may be confused with COVID-19 will be discussed Radiologists should become familiar with these imaging features of COVID-19 to design specific imaging protocols that allow prompt diagnosis and treatment
{"title":"Hallazgos de imagen en Covid-19. Complicaciones y enfermedades simuladoras","authors":"C. Alvarez, Jaime, I. Concejo, Paula, A. Ferreiro, Concepción, G. Gálvez, Esther, G. Hoyas, María Azahara, T. Zubiaguirre, Íñigo, R. Rodríguez, Cristián, T. Ocampo, Wilmar, O. Sánchez, Francisca, P. Martínez","doi":"10.4067/S0717-93082020000400145","DOIUrl":"https://doi.org/10.4067/S0717-93082020000400145","url":null,"abstract":"Abstract: Given the current pandemic caused by SARS-CoV-2, the scientific community is making an effort to share knowledge of this emerging disease To contribute to this effort, we have done a comprehensive review of the clinical history and imaging tests in patients affected by COVID-19 in our institution, one of the most affected by the pandemic in the Community of Madrid (Spain) The aim of this review is to describe the radiological findings in the lungs and show the most frequent extrapulmonary pathology as well as some entities that may be confused with COVID-19 will be discussed Radiologists should become familiar with these imaging features of COVID-19 to design specific imaging protocols that allow prompt diagnosis and treatment","PeriodicalId":35339,"journal":{"name":"Revista Chilena de Radiologia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46198236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.4067/s0717-93082020000300088
A. FelipeCastillo, N. DiegoBazaes, G. AlvaroHuete
Resumen: La pandemia causada por el nuevo coronavirus (SARS-CoV-2) ha derivado en nuevos desafios en la manera que radiologia apoya el trabajo clinico y presta servicios oportunos. El presente articulo revisa las principales publicaciones en la literatura radiologica a la fecha, con enfasis en los sistemas de informe estructurado en tomografia computada y radiografia de torax. Se relata ademas nuestra experiencia en las modificaciones realizadas en el Departamento de Radiologia para hacer frente a la pandemia.
{"title":"Radiología en la Pandemia COVID-19: Uso actual, recomendaciones para la estructuración del informe radiológico y experiencia de nuestro departamento","authors":"A. FelipeCastillo, N. DiegoBazaes, G. AlvaroHuete","doi":"10.4067/s0717-93082020000300088","DOIUrl":"https://doi.org/10.4067/s0717-93082020000300088","url":null,"abstract":"Resumen: La pandemia causada por el nuevo coronavirus (SARS-CoV-2) ha derivado en nuevos desafios en la manera que radiologia apoya el trabajo clinico y presta servicios oportunos. El presente articulo revisa las principales publicaciones en la literatura radiologica a la fecha, con enfasis en los sistemas de informe estructurado en tomografia computada y radiografia de torax. Se relata ademas nuestra experiencia en las modificaciones realizadas en el Departamento de Radiologia para hacer frente a la pandemia.","PeriodicalId":35339,"journal":{"name":"Revista Chilena de Radiologia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45245374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.4067/s0717-93082020000300100
G. Díaz-Muñoz
The teaching of research covers all aspects of the research process, involving pilot studies. In biomedical research, the first step in the execution of a project is the realization of a pilot study, with the objective of testing on smaller scale logistic aspects of the execution of the study, which will avoid making mistakes in the larger studies. This review aims to expose fundamental aspects in the use and planning of pilot studies, which will serve to optimize research processes in the areas of health.
{"title":"Metodología del estudio piloto","authors":"G. Díaz-Muñoz","doi":"10.4067/s0717-93082020000300100","DOIUrl":"https://doi.org/10.4067/s0717-93082020000300100","url":null,"abstract":"The teaching of research covers all aspects of the research process, involving pilot studies. In biomedical research, the first step in the execution of a project is the realization of a pilot study, with the objective of testing on smaller scale logistic aspects of the execution of the study, which will avoid making mistakes in the larger studies. This review aims to expose fundamental aspects in the use and planning of pilot studies, which will serve to optimize research processes in the areas of health.","PeriodicalId":35339,"journal":{"name":"Revista Chilena de Radiologia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44669404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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