Publications by authors named "F Gomez-Munoz"

Artificial intelligence (AI) has made tremendous advances in recent years and will presumably have a major impact in health care. These advancements are expected to affect different aspects of clinical medicine and lead to improvement of delivered care but also optimization of available resources. As a modern specialty that extensively relies on imaging, interventional radiology (IR) is primed to be on the forefront of this development.

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Article Synopsis
  • The study aimed to evaluate the safety and effectiveness of using percutaneous cryoablation on patients with non-visceral abdominal metastases following previous surgery.
  • A total of 11 patients with 14 metastases underwent the procedure, achieving technical success in all cases, with most experiencing good local control and no major complications.
  • The findings indicate that cryoablation could be a viable minimally invasive treatment for select patients dealing with this type of cancer recurrence in the abdomen.
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Purpose: Predicting early local tumor progression after thermal ablation treatment for colorectal liver metastases patients is critical for the decision of subsequent follow-up and treatment. Radiomics features derived from medical images show great potential for prediction and prognosis. The aim is to develop and validate a machine learning radiomics model to predict local tumor progression based on the pre-ablation CT scan of colorectal liver metastases patients.

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Interventional radiology plays an important and increasing role in cancer treatment. Follow-up is important to be able to assess treatment success and detect locoregional and distant recurrence and recommendations for follow-up are needed. At ECIO 2018, a joint ECIO-ESOI session was organized to establish follow-up recommendations for oncologic intervention in liver, renal, and lung cancer.

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