Espectro de coinfecciones pulmonares fúngicas oportunistas en COVID-19: lo que el radiólogo debe saber / Spectrum of opportunistic fungal lung co-infections in COVID-19: What the radiologist needs to know

Las coinfecciones pulmonares fúngicas asociadas a la COVID-19 pueden ocurrir en pacientes gravemente enfermos o con comorbilidades subyacentes e inmunosupresión. Las infecciones fúngicas invasivas más comunes son causadas por aspergilosis, mucormicosis, y las debidas a Pneumocystis, criptococo y cándida. Los radiólogos integran las características clínicas de la enfermedad con el enfoque basado en patrones de TAC y desempeñan un papel crucial en la identificación de estas coinfecciones en la COVID-19 para ayudar a los médicos a realizar un diagnóstico seguro, iniciar el tratamiento y prevenir complicaciones.(AU)

Fungal lung co-infections associated with COVID-19 may occur in severely ill patients or those with underlying co-morbidities, and immunosuppression. The most common invasive fungal infections are caused by aspergillosis, mucormycosis, pneumocystis, cryptococcus, and candida. Radiologists integrate the clinical disease features with the CT pattern-based approach and play a crucial role in identifying these co-infections in COVID-19 to assist clinicians to make a confident diagnosis, initiate treatment and prevent complications.(AU)

Barriers to artificial intelligence implementation in radiology practice: What the radiologist needs to know.

Artificial Intelligence has the potential to disrupt the way clinical radiology is practiced globally. However, there are barriers that radiologists should be aware of prior to implementing Artificial Intelligence in daily practice. Barriers include regulatory compliance, ethical issues, data privacy, cybersecurity, AI training bias, and safe integration of AI into routine practice. In this article, we summarize the issues and the impact on clinical radiology.

Dificultades en la implantación de la inteligencia artificial en la práctica radiológica: lo que el radiólogo necesita saber / Barriers to Artificial Intelligence implementation in radiology practice: What the Radiologist needs to know

La inteligencia artificial (IA) ofrece la posibilidad de cambiar la práctica de la radiología clínica en todo el mundo. Sin embargo, existen dificultades que los radiólogos deben conocer antes de aplicar la inteligencia artificial en la práctica diaria. Estas dificultades incluyen cuestiones de cumplimiento de la legislación, cuestiones éticas, aspectos relacionados con la privacidad de los datos y la ciberseguridad, el sesgo de aprendizaje automático y la integración segura de la IA en la práctica habitual. En este artículo, resumimos estas cuestiones y su repercusión en la radiología clínica.(AU)

Artificial Intelligence has the potential to disrupt the way clinical radiology is practiced globally. However, there are barriers that radiologists should be aware of prior to implementing Artificial Intelligence in daily practice. Barriers include regulatory compliance, ethical issues, data privacy, cybersecurity, AI training bias, and safe integration of AI into routine practice. In this article, we summarize the issues and the impact on clinical radiology.(AU)

Use of magnetic resonance imaging in rectal cancer patients: Society of Abdominal Radiology (SAR) rectal cancer disease-focused panel (DFP) recommendations 2017.

PURPOSE: To propose guidelines based on an expert-panel-derived unified approach to the technical performance, interpretation, and reporting of MRI for baseline and post-treatment staging of rectal carcinoma. METHODS: A consensus-based questionnaire adopted with permission and modified from the European Society of Gastrointestinal and Abdominal Radiologists was sent to a 17-member expert panel from the Rectal Cancer Disease-Focused Panel of the Society of Abdominal Radiology containing 268 question parts. Consensus on an answer was defined as ≥ 70% agreement. Answers not reaching consensus (< 70%) were noted. RESULTS: Consensus was reached for 87% of items from which recommendations regarding patient preparation, technical performance, pulse sequence acquisition, and criteria for MRI assessment at initial staging and restaging exams and for MRI reporting were constructed. CONCLUSION: These expert consensus recommendations can be used as guidelines for primary and post-treatment staging of rectal cancer using MRI.

Optimisation of preoperative assessment in patients diagnosed with rectal cancer.

AIMS: Treatment decision making for patients with rectal cancer is complex and optimal preoperative assessment is important to ensure patients receive appropriate and high-quality care. Therefore, our objective was to develop an evidence-based, multidisciplinary guideline to assist physicians treating rectal cancer to ensure that preoperative assessment is optimal. MATERIALS AND METHODS: A multidisciplinary expert panel of physicians who treat rectal cancer was selected as members of the Cancer Care Ontario Preoperative Assessment for Rectal Cancer Guideline Development Group (GDG). This group initially met to identify important clinical questions with respect to optimisation of preoperative assessment in patients diagnosed with rectal cancer. A systematic review, specific to each of these clinical questions, was then conducted using MEDLINE, EMBASE and the Cochrane Library databases. The GDG met at regular intervals to review the evidence and to develop guidelines to address each of the clinical questions. RESULTS: The GDG identified seven important clinical questions with respect to the optimisation of preoperative assessment in patients diagnosed with rectal cancer. The clinical questions pertained to: (i) investigations required to assess distant metastasis (one question); (ii) imaging for local staging of rectal cancer (five questions); (iii) multidisciplinary cancer conference (MCC) (one question); (iv) restaging-magnetic resonance imaging (one question). The systematic reviews related to these clinical questions yielded 31 articles that were abstracted and reviewed by the GDG. Based on the systematic reviews, a guideline was developed containing seven recommendations that were either adapted from existing guidelines, based on review of the evidence or by consensus when evidence was limited. CONCLUSIONS: A set of seven recommendations have been developed in order to optimise pretreatment assessment in patients with rectal cancer by promoting evidence-based practice. These guidelines are based on the best available evidence and have been peer reviewed by two independent multidisciplinary expert panels for relevance and validity.