Diagnostic imaging peer review

INTRODUCTION: A non-contrast CT head scan (NCCTH) is the most common cross-sectional imaging investigation requested in the emergency department. Advances in computer vision have led to development of several artificial intelligence (AI) tools to detect abnormalities on NCCTH. These tools are intended to provide clinical decision support for clinicians, rather than stand-alone diagnostic devices. However, validation studies mostly compare AI performance against radiologists, and there is relative paucity of evidence on the impact of AI assistance on other healthcare staff who review NCCTH in their daily clinical practice...

OBJECTIVES: The aim of our study was to determine if patients with obesity have different postoperative outcomes than their peers. MATERIAL AND METHODS: A single-center retrospective review of all fluoroscopically-guided percutaneous gastrostomy tube, with 183 patients and 90 patients in the BAG and dilator groups, respectively. Patients were stratified, based on body mass index (BMI) percentile and for age. Demographic information and data on medical comorbidities and post-operative complications were collected...

The gastrin-releasing peptide receptor (GRPR) is known to be overexpressed in breast cancer, making it a promising target for both imaging and therapy within a theranostic framework. Various radioligands targeting GRPR have undergone investigation in preclinical and clinical studies related to breast cancer. This systematic scoping review aimed to assess the current evidence on GRPR-targeted radioligands for diagnostic and therapeutic applications in breast cancer. The methodology followed the PRISMA-ScR protocol...

BACKGROUND: The objective of this study is to systematically analyze the current state of the literature regarding novel artificial intelligence (AI) machine learning models utilized in non-invasive imaging for the early detection of nonmelanoma skin cancers. Furthermore, we aimed to assess their potential clinical relevance by evaluating the accuracy, sensitivity, and specificity of each algorithm and assessing for the risk of bias. METHODS: Two reviewers screened the MEDLINE, Cochrane, PubMed, and Embase databases for peer-reviewed studies that focused on AI-based skin cancer classification involving nonmelanoma skin cancers and were published between 2018 and 2023...

This review article presents an appraisal of pioneering technologies poised to revolutionize the diagnosis and management of aortic aneurysm disease, with a primary focus on the thoracic aorta while encompassing insights into abdominal manifestations. Our comprehensive analysis is rooted in an exhaustive survey of contemporary and historical research, delving into the realms of machine learning (ML) and computer-assisted diagnostics. This overview draws heavily upon relevant studies, including Siemens' published field report and many peer-reviewed publications...

BACKGROUND: Lung diseases, both infectious and non-infectious, are the most prevalent cause of mortality overall in the world. Medical research has identified pneumonia, lung cancer, and Corona Virus Disease 2019 (COVID-19) as prominent lung diseases prioritized over others. Imaging modalities, including X-rays, computer tomography (CT) scans, magnetic resonance imaging (MRIs), positron emission tomography (PET) scans, and others, are primarily employed in medical assessments because they provide computed data that can be utilized as input datasets for computer-assisted diagnostic systems...

INTRODUCTION: Fast and accurate diagnosis of acute stroke is crucial to timely initiate reperfusion therapies. Conventional high-field (HF) MRI yields the highest accuracy in discriminating early ischaemia from haemorrhages and mimics. Rapid access to HF-MRI is often limited by contraindications or unavailability. Low-field (LF) MRI (<0.5T) can detect several types of brain injury, including ischaemic and haemorrhagic stroke. Implementing LF-MRI in acute stroke care may offer several advantages, including extended applicability, increased safety, faster administration, reduced staffing and costs...

Artificial Intelligence (AI), encompassing Machine Learning and Deep Learning, has increasingly been applied to fracture detection using diverse imaging modalities and data types. This systematic review and meta-analysis aimed to assess the efficacy of AI in detecting fractures through various imaging modalities and data types (image, tabular, or both) and to synthesize the existing evidence related to AI-based fracture detection. Peer-reviewed studies developing and validating AI for fracture detection were identified through searches in multiple electronic databases without time limitations...

INTRODUCTION: Neuropathic pain in low back-related leg pain has gained increasing interest in contemporary research. Identification of neuropathic pain in low back-related leg pain is essential to inform precision management. Diagnostic investigations are commonly used to identify neuropathic pain in low back-related leg pain; yet the diagnostic utility of these investigations is unknown. This systematic review aims to investigate the diagnostic utility of diagnostic investigations to identify neuropathic pain in low back-related leg pain...

"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence . This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. Purpose To compare the image quality and diagnostic capability in detecting malignant liver tumors of low-dose CT (LDCT, 33% dose) with deep learning-based de-noising (DLD) and standard-dose CT (SDCT, 100% dose) with model-based iterative reconstruction (MBIR)...

OBJECTIVE: Measure actionability of recommendations for additional imaging (RAI) in head and neck CT and MRI, where there is a near-complete absence of best practices or guidelines, identify the most common recommendations, and assess radiologist factors associated with actionability. METHODS: We retrospectively reviewed all head and neck CT and MRI radiology reports across our multi-institution, multi-practice healthcare system from 6/1/2021-5/31/2022. Actionability of RAI was scored using a validated taxonomy...

INTRODUCTION: Research has been performed by sonographers (also known as ultrasound reporting radiographers) for many years for improving diagnosis of disease, developing new imaging approaches, and enhancing patient outcomes. Despite this, sonographers' perspectives on research have not been well studied. To understand the views of sonographers is essential, as they have an important role in the successful implementation of research outcomes during their daily work. The study aimed to explore sonographers' perspectives on research...

BACKGROUND: Computed tomography (CT) scan is a common imaging technique used to evaluate the severity of a head injury. The overuse of diagnostic interventions in the health system is a growing concern worldwide. Objectives: The aim of this systematic review is to investigate the rate of CT scan overuse in cases of mild head injury. METHODS: Eligibility criteria: We encompassed observational studies-either designed as cohort, case-control, or cross-sectional investigations-that reported on CT scan overuse rates for mild head injuries...

Recent advancements in deep learning and artificial intelligence (AI) have profoundly impacted various fields, including diagnostic imaging. Integrating AI technologies such as deep learning and convolutional neural networks has the potential to drastically improve diagnostic methods in the field of dentistry and maxillofacial radiography. A systematic study that adhered to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards was carried out to examine the efficacy and uses of AI in dentistry and maxillofacial radiography...

Interventional oncology (IO) is the field of Interventional Radiology that provides minimally invasive procedures under imaging guidance for the diagnosis and treatment of malignant tumors. Sophisticated devices can be utilized to increase standardization, accuracy, outcomes, and "repeatability" in performing percutaneous Interventional Oncology techniques. These technologies can reduce variability, reduce human error, and outperform human hand-to-eye coordination and spatial relations, thus potentially normalizing an otherwise broad diversity of IO techniques, impacting simulation, training, navigation, outcomes, and performance, as well as verification of desired minimum ablation margin or other measures of successful procedures...

"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence . This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. Tuberculosis, which primarily affects developing countries, remains a significant global health concern. Since the 2010s, the role of chest radiography has expanded in tuberculosis triage and screening beyond its traditional complementary role in the diagnosis of tuberculosis...

Alzheimer's disease is defined by the presence of β-amyloid plaques and neurofibrillary tau tangles potentially preceding clinical symptoms by many years. Previously only detectable post-mortem, these pathological hallmarks are now identifiable using biomarkers, permitting an in vivo definitive diagnosis of Alzheimer's disease. 18 F-flortaucipir (previously known as 18 F-T807; 18 F-AV-1451) was the first tau positron emission tomography tracer to be introduced and is the only Food and Drug Administration-approved tau positron emission tomography tracer (Tauvid™)...

This literature review was conducted to analyze the current and future effects of intravenous contrast media shortages and how these shortages affect patient care within the field of computed tomography (CT). Substitutions and conservation methods were examined. One of the most important results of this review was to improve current and future patient care while actively making a conscious effort to help aid others in future shortages. Limitations can be found when looking at the research field concerning the substitutions for contrast media, such as nanoparticles and saline chasers following contrast boluses...

Mentoring relationships are encouraging, nurturing and supportive and are based on mutual trust between mentors and mentees. Peer mentorship allows senior students to support and educate students at a lower level in their training. In radiography, carefully planned peer mentorship programs can be beneficial to both mentors and mentees. In this narrative review, mentorship and peer mentorship are discussed. Arguments surrounding the incorporation of social learning theory, gender issues, and love are also included...

BACKGROUND: Traditional health care systems face long-standing challenges, including patient diversity, geographical disparities, and financial constraints. The emergence of artificial intelligence (AI) in health care offers solutions to these challenges. AI, a multidisciplinary field, enhances clinical decision-making. However, imbalanced AI models may enhance health disparities. OBJECTIVE: This systematic review aims to investigate the economic performance and equity impact of AI in diagnostic imaging for skin, neurological, and pulmonary diseases...