Radiation therapy (RT) can lead to late-onset cardiac toxicity, especially in patients receiving treatment for breast, thoracic, or hematologic malignancies. Early identification of subclinical cardiac injury is essential to guide surveillance and intervention strategies. This narrative review synthesizes imaging-based evidence published between 2014 and 2025 on the detection and prediction of RT-induced cardiac toxicity. We screened 1535 studies and included 78 studies that employed echocardiography, cardiac magnetic resonance imaging (CMR), positron emission tomography (PET) and single-photon emission CT (SPECT), cardiac CT, or multimodal approaches. Echocardiographic strain imaging, particularly global longitudinal strain (GLS), consistently identified early subclinical dysfunction. CMR offered spatial and tissue-level characterization of myocardial fibrosis and inflammation, while PET/SPECT revealed perfusion and metabolic changes in irradiated myocardium. CT-based methods such as coronary artery calcium scoring and coronary CT angiography detected subclinical atherosclerosis with dose correlations. Several predictive models integrating imaging, dose, and clinical data demonstrated strong performance in identifying high-risk patients. Despite encouraging results from such models, variability in timing and endpoint selection limits clinical adoption. Standardized imaging protocols and prospective validation of predictive models are urgently needed. Imaging biomarkers may help tailor follow-up strategies to individual risk and guide the design of future cardio-oncology trials and radiation treatment planning strategies.
Prostate cancer is a common malignancy in men. With the advent of multiparametric MRI and the Prostate Imaging-Reporting and Data System (PI-RADS) framework for grading lesions, there have been multiple advancements in the management and treatment of the disease. There are several new advancements in prostate MRI technology that suggest further exciting developments in the field, ranging from novel imaging sequences to the application of machine learning methods and artificial intelligence (AI) across the imaging pipeline. In this review, we aim to provide context on the current advancements in prostate MRI and will discuss the benefits and drawbacks of several new imaging techniques including hybrid multidimensional MRI, low field strength MRI, restriction spectrum imaging, Vascular, Extracellular, and Restricted Diffusion for Cytometry in Tumour (VERDICT) MRI, luminal water imaging, and hyperpolarized C-13 MRI. Additionally, we will introduce several novel AI methods that have been proposed to improve MRI image quality, prostate lesion detection and characterization, as well as touch on the ethical implications of AI in medical imaging of the prostate.
Objectives:To compare radiation dose and image quality of abdominopelvic CT studies performed on dual-energy energy-integrating detector CT (EID-CT) and photo-counting CT (PCCT) for the same patient cohort with clinically aligned protocols. Methods:An IRB-approved retrospective cohort study included 49 patients who underwent portal venous phase abdominopelvic CT exams using both dual-energy CT and PCCT scanners within a maximum interval of 3 months. Images reconstructed included virtual monoenergetic images at 50, 60, and 70 keV and mixed images. CTDIvol values were recorded to assess radiation dose. Regions of interest were drawn in the 6 anatomical locations for quantitative analysis. The overall image quality, contrast enhancement, image noise, and presence of artifacts were evaluated using a 5-point Likert scale. Results:No significant differences were observed in image quality scores between PCCT and EID-CT for most comparisons. Calculated contrast-to-noise ratios (CNR) were significantly higher on PCCT except for 70 keV. PCCT demonstrated a significantly lower radiation dose, with an average reduction of 20% ± 15%, up to 51%. Conclusion:For abdominopelvic CT exams with our institutional protocol settings, PCCT has demonstrated a significant reduction in radiation dose while maintaining similar image quality as EID-CT. Advances in knowledge:With clinically aligned protocols for the same cohort of patients, the results provided robust evidence for understanding the benefits of PCCT. It also provided a possible pathway to transit from EID-CT to PCCT in the abdominopelvic imaging.
Diffuse cystic lung diseases (DCLDs) comprise a broad spectrum of disorders characterized by diffusely distributed pulmonary cysts, posing significant diagnostic challenges due to overlapping imaging features. High-resolution CT serves as the cornerstone for the diagnosis of DCLDs, yet its reliability is limited by technical constraints, including insufficient spatial resolution for subtle cysts and variable correlation with functional impairment. Furthermore, persistent discrepancies between imaging findings and underlying pathology highlight the inherent limitations of current modalities. This review synthesizes current diagnostic workflows, emphasizing the integration of imaging with clinical, genetic, and histopathological data within a multidisciplinary framework and appraising the impact of emerging technologies on diagnostic precision. Throughout this evolution, radiologists retain a central role in timely recognition, collaborative decision-making, and outcome optimization for patients with DCLDs.
Objectives:This study aimed to provide a comprehensive analysis of the increasing demand for PET-CT imaging in England, driven by advancements in technology and updated clinical guidelines. By comparing the 2013 and 2022 guidelines issued by the Royal College of Radiologists, the analysis sought to quantify the gap between actual PET-CT provision and modeled requirements, benchmarked against international comparators, to inform strategic planning for equitable access to advanced imaging. Methods:A detailed modeling approach was developed, mapping guideline-based PET-CT scan requirements to disease incidence and stage for major oncological indications (prostate, lymphoma, neuroendocrine tumors, lung, breast, gynecological cancers) and key non-oncological conditions (dementia, cardiovascular disease). Actual scan volumes were extracted from the NHS Diagnostic Imaging Dataset and cross-referenced with provider data. Unmodeled indications were estimated using proportional scaling. Model outputs were validated against PET-CT utilization rates in Finland, adjusted for UK disease incidence. Future demand projections incorporated population growth, demographic shifts, and evolving disease prevalence. Results:For 2021, modeled estimates indicated a substantial shortfall in PET-CT provision for several high-impact indications, notably prostate cancer, dementia, neuroendocrine tumors, and breast cancer, where actual scan volumes were 2-7 times lower than modeled need. Modeled demand for England (361 900 scans/year) exceeded actual provision (239 367 scans/year) by over 50%. Comparative analysis with Finland confirmed that England's PET-CT rates lagged for most indications except lung cancer. Projections suggest continued growth in demand, particularly for dementia and neuroendocrine tumors, with overall PET-CT needs expected to rise sharply by 2040. Conclusions:England's current PET-CT capacity falls significantly short of evidence-based requirements, especially for emerging indications in neurology and oncology. Without strategic investment and expansion, this gap will widen, risking delayed diagnosis and suboptimal care. Enhanced data collection and ongoing validation are critical for responsive service planning. Advances in knowledge:This is the first study to comprehensively model PET-CT demand in England across multiple disease categories using updated clinical guidelines and international benchmarking. It provides a robust, data-driven framework for forecasting imaging needs, supporting national policy and equitable resource allocation.
