Search Tag: radiomics
2024 16 Sep
Hepatocellular carcinoma (HCC) remains one of the leading causes of cancer-related deaths globally, with mortality rates rising steadily. Accurate mortality risk prediction is a cornerstone for optimising treatment and management strategies in patients diagnosed with HCC. Traditional scoring systems rely on simplistic models that consider limited...Read more
2024 09 Sep
Breast cancer is one of the most prevalent cancers among women worldwide and a leading cause of cancer-related deaths. Among the key factors influencing the prognosis and treatment planning for patients with locally advanced breast cancer (LABC) is the presence of axillary lymph node metastases (ALNMs). Accurate detection of ALNMs is crucial as...Read more
2024 08 Sep
Clear cell renal cell carcinoma (ccRCC) is the most prevalent type of renal cancer, accounting for approximately 70% of all renal cancer cases. This aggressive subtype poses significant challenges due to its high metastatic potential, with metastases being a key determinant of patient prognosis. Traditional diagnostic methods often fail to accurately...Read more
2024 30 Jul
Stroke remains a leading global health concern, ranking as the second most common cause of death worldwide. Among the various types of strokes, acute anterior-circulation large vessel occlusion (LVO) strokes are particularly challenging, often leading to severe disability or death. The advent of endovascular thrombectomy (EVT) has revolutionised...Read more
2024 25 Jul
Radiomics is a transformative field within medical imaging that seeks to extract quantitative imaging biomarkers from medical images. Unlike traditional qualitative analysis, which relies on subjective interpretation, radiomics uses advanced algorithms to analyse pixel-level data, uncovering features that are imperceptible to the human eye. This...Read more
2024 19 Jun
Radiomics is a method that extracts detailed data, known as radiomic features, from medical images like CT and MRI. These features can reveal tissue characteristics at a microscopic level, potentially serving as biomarkers in oncology. They offer a non-invasive way to assess entire tumours and track changes over time. Radiomic features include...Read more
2024 06 Jun
In recent decades, significant progress has been made in biomedical and technological fields, enabling the capture of various health-related traits like molecular, genetic, metabolic, and morphological characteristics. This progress has paved the way for personalised approaches to disease management. Imaging techniques such as computed tomography,...Read more
2024 29 May
Lung cancer remains the foremost cause of cancer-related mortality globally, with a disheartening overall 5-year relative survival rate of just 22.9%. However, the prognosis improves significantly when lung cancer is detected early. Patients diagnosed with localized lung cancer have a 5-year survival rate of 61.2%, in stark contrast to the 7% for...Read more
2024 13 Mar
Radiomics, a technique for extracting quantitative features from medical images, aims to build predictive models for clinical decision-making. However, a gap between research and practice exists due to poor methodology, hindering reproducibility. Researchers set out in a new study to develop a new quality scoring tool, METhodological RadiomICs...Read more
2024 02 Mar
Multidetector computed tomography (MDCT) accompanied by its multiple postprocessing capabilities (maximum intensity projection, multiplanar reconstruction, and volume-rendering technique) provides an alternative non-invasive imaging modality. Radiomics is a rapidly evolving field of research concerned with the extraction of quantitative metrics—the...Read more
2024 07 Feb
A groundbreaking study has introduced a pioneering method to predict lymph node metastasis (LNM) in patients with non-functional pancreatic neuroendocrine tumours (NF-PanNETs), aiding in tailored treatment strategies and enhancing patient outcomes. Recently published in eClinicalMedicine, the research team from the University of Tsukuba harnessed...Read more
2024 07 Feb
A groundbreaking study has introduced a pioneering method to predict lymph node metastasis (LNM) in patients with non-functional pancreatic neuroendocrine tumours (NF-PanNETs), aiding in tailored treatment strategies and enhancing patient outcomes. Recently published in eClinicalMedicine, the research team from the University of Tsukuba harnessed...Read more
2023 09 Oct
The aim of this recent study was to assess both the intra- and inter-rater reliability of the total radiomics quality score (RQS) and to examine the reproducibility of individual RQS items’ score in a comprehensive multi-reader investigation. Nine raters with diverse backgrounds were randomly assigned to three groups, each group reflecting...Read more
2023 28 Feb
Radiomics may lead to personalised management and treatment of cardiovascular diseases, which could impact patients’ prognosis. Key Points In recent years, multiple radiomics-based tools have been investigated in the field of cardiovascular imaging. Radiomics may predict outcomes of cardiac diseases without the need of...Read more
2023 28 Feb
Radiomics may lead to personalised management and treatment of cardiovascular diseases, which could impact patients’ prognosis. Key Points In recent years, multiple radiomics-based tools have been investigated in the field of cardiovascular imaging. Radiomics may predict outcomes of cardiac diseases without the need of...Read more
2023 28 Feb
Radiomics may lead to personalised management and treatment of cardiovascular diseases, which could impact patients’ prognosis. Key Points In recent years, multiple radiomics-based tools have been investigated in the field of cardiovascular imaging. Radiomics may predict outcomes of cardiac diseases without the need of...Read more
2023 28 Feb
Radiomics may lead to personalised management and treatment of cardiovascular diseases, which could impact patients’ prognosis. Key Points In recent years, multiple radiomics-based tools have been investigated in the field of cardiovascular imaging. Radiomics may predict outcomes of cardiac diseases without the need of...Read more
2022 08 Jul
This paper provides an overview of current research at the Department of Radiology of the University of Florence. It concerns radiomics along with Artificial Intelligence (AI) applied to various medical fields. The need for personalised medicine and the transition from qualitative to quantitative imaging are at the heart of the projects...Read more
2021 26 Nov
Dr Renato Cuocolo, radiologist and research fellow at the University of Naples ‘Federico II’, recently spoke at the 2021 European Society of Medical Imaging Informatics (EuSoMII) Annual Meeting about the challenges in assessing research quality in radiomics. Given radiomics’ transformative potential for medical imaging, HealthManagement.org met...Read more
2020 30 Nov
Machine learning and radiomics may lead to personalised management and treatment of glioma patients, hopefully improving quality of life and survival. Key Points In the past few years, multiple radiomics-based tools have been introduced in the field of neuro-oncology and in particular for imaging of brain gliomas. Radiogenomics...Read more
2020 09 Mar
HealthManagement.org rounds up exciting developments that have all the marks of healthcare game changers. What do you think? Advancements in Cardiac Imaging Conventional imaging still remains important for the assessment of cardiac structure and function. However, advanced echocardiography with strain imaging techniques, tissue characterisation...Read more
2020 09 Mar
Summary: Radiomics holds great promise for personalised imaging but without a set of standards for all modalities, the data extraction method will falter. A leading proponent of standardisation for MRI radiomics speaks to HealthManagement.org about the opportunities and pitfalls ahead. Why is it important that standardisation...Read more
2020 22 Jan
Breast cancer is complex for clinicians to diagnose owing to how greatly cells within one tumour can vary. This complexity and challenge is highlighted by the fact that a biopsy only targets a sample of cells. You might also like: Radiomics Model Betters Radiologistsin Lesions Categorisation A new study from Penn Medicine addresses...Read more
2020 16 Jan
New findings show that radiomics and machine learning (ML) can be combined to help ascertain if late gadolinium enhancement (LGE) on cardiac MR images indicated myocardial infarction (MI) or myocarditis. You might also like: Machine Learning Improves Breast Cancer Screening and Diagnosis A study published in Radiology: Cardiothoracic...Read more
2019 22 Feb
CEUS for children, ultrasound simulation and gamification models for training and education, EFSUMB initiatives. Prof. Sidhu, EFSUMB president, talks to Healthmanagement.org about his ECR 2019 presentations: using ultrasound simulation models as tools for training and education, the greatest potential in combining ultrasound with contrast-enhanced...Read more
2019 22 Feb
Imaging acquisition advances & big data envision a bright future for diagnostic imaging, which should continue to be led by the AI-powered radiologist. Technical advances in imaging acquisition and big data envision a bright future for diagnostic imaging. Radiologists working as data scientists can play a central role in precision medicine,...Read more
2019 22 Feb
Review of some state-of-the-art applications of artificial intelligence on mammography and MRI. Computer aided imaging is not novel, having been around for 50 years. Developments have boosted the accuracy of computer-based analysis and breast imaging is at the forefront, as large databases are available, and radiologists tasks on images are...Read more
2019 06 Feb
Executive Summary Artificial intelligence ( AI ) is clearly the new trend in automation. This article, "The AI-powered radiologist" , authored by Dr. María Jesús Díaz Candamio , a radiologist at the Servicio de Radiología, Hospital Universitario de A Coruña (Spain), highlights the advances in AI technology that will propel a revolution in...Read more
2018 18 Dec
Researchers combine mammography with AI to determine the biological composition of a tumor's tissue, developing a new method that may help reduce the number of unnecessary breast biopsies, according to a new study published in the journal Radiological Society of North America . Research has shown that more than 10 percent of women are called...Read more