BJR open最新文献

A subset of patients with interstitial lung diseases (ILDs) experiences disease progression despite standard treatment protocols. Similar to idiopathic pulmonary fibrosis, the archetype of progressive fibrotic ILDs, these patients exhibit worsening clinical symptoms, declining lung function, and progressive radiological changes, often resulting in shortened survival. This progressive disease pattern is classified under the term progressive pulmonary fibrosis or progressive fibrosing ILD. Radiological imaging, particularly high-resolution computed tomography (HRCT), is integral to diagnosing ILDs and plays a critical role within multidisciplinary ILD boards. HRCT is instrumental in identifying patients at a higher risk for disease progression and may provide valuable prognostic insights. Additionally, serial imaging is essential for detecting progression over time. While visual assessment remains the primary method for evaluating disease advancement, emerging quantitative techniques, including those utilizing machine learning, are currently undergoing validation.

Diffusion-weighted imaging (DWI) is an advanced MRI technique that harnesses the movement of water molecules within tissues to assess and characterize a wide range of musculoskeletal disorders. By differentiating between isotropic and anisotropic diffusion, DWI provides critical insights into tissue integrity and pathology, proving instrumental in diagnosing conditions. Its sensitivity to changes in tissue microstructure is quantified through metrics like the apparent diffusion coefficient (ADC) and fractional anisotropy (FA). Advanced methodologies, including diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI), further enhance DWI's ability to evaluate complex tissue architectures, offering vital information on muscle, ligament, tendon, and cartilage health. DWI also excels in the assessment of soft tissue tumours, infections, and joint pathologies, enabling accurate differentiation between benign and malignant lesions and facilitating early detection of conditions like osteomyelitis. Additionally, DWI plays a crucial role in monitoring treatment responses, with ADC changes correlating to tumour necrosis and recurrence. Despite its advantages, DWI faces limitations, such as technical artefacts and challenges in interpretation that can impact diagnostic accuracy. This review explores the diverse applications of DWI and DTI in musculoskeletal imaging, highlighting their potential to improve diagnostic precision and clinical outcomes while addressing ongoing challenges in the field.

Objectives: An accurate morphological classification of distinct pulmonary phenotypes in sarcoidosis is lacking. Recently, a multinational Delphi study was conducted to reach a consensus on recognizable high-resolution computer tomography (HRCT) phenotypes in pulmonary sarcoidosis as a basis for a more distinctive classification. The reliability of these phenotypes has not yet been evaluated.

Methods: HRCT scans of adult sarcoidosis patients from the pulmonology department of a single sarcoidosis referral center were scored by three blinded independent readers. Seven phenotypes were distinguished as described in the Delphi study. They were divided into two subgroups: "non-fibrotic" and "likely-to-be fibrotic". Intra- and inter-reader reliability for scoring the predominant phenotype and the subgroup was assessed using weighted Kappa (K_w) statistics.

Results: Forty-five patients (mean age, 47 years ± 12, 28 men) were included. For the scoring of the predominant phenotype, inter-reader reliability between all readers was substantial with an overall Fleiss' kappa of 0.69 (CI 0.622-0.765, P < .001). We observed a substantial inter-reader reliability between readers A and B (K _w of 0.76), between readers B and C (K_w of 0.66) and between readers A and C (K _w of 0.66). For the scoring of the subgroups "non-fibrotic" vs. "likely-to-be fibrotic," overall Fleiss' Kappa was substantial (K = 0.78, CI 0.607-0.944, P < .001). We observed a K _w score of 0.76 between readers A and B; 0.81 between readers A and C; 0.76 between readers B and C. Intra-reader reliability was substantial between the scores of A in scoring the predominant phenotypes (K _w of 0.71) and it was almost perfect in scoring the subgroups (K _w of 0.95). Intra-reader reliability was substantial between the scores of B in scoring the predominant phenotype (K _w of 0.66) and subgroups (K _w of 0.72).

Conclusions: The inter- and intra-reader reliability of the newly proposed HRCT phenotypes obtained from the Delphi study is very acceptable.

Advances in knowledge: This study is the first to assess the reliability of these HRCT phenotypes and supports the use of them for classification purposes in future clinical and pathogenetic studies.

This study examines the shortage of radiation oncologists in Italy and Europe, analysing systemic challenges in postgraduate training and proposing solutions to enhance the appeal of radiation oncology. A review of literature from Italy and Europe evaluated trends in training programmes, workforce dynamics. Analysis included residency vacancies, economic constraints, training disparities, and visibility of the field during medical education. In Italy, 55.3% of radiation oncology residency positions have gone unfilled or been abandoned since 2016, with 90% of positions vacant in 2023. Contributing factors include inadequate exposure to radiotherapy during medical training, limited financial opportunities, negative societal perceptions, and high levels of burnout. Across Europe, similar challenges persist. Training disparities, outdated infrastructure, and regional inequalities exacerbate workforce shortages, particularly in low-income countries. Addressing the radiation oncology crisis requires a multifaceted strategy, including enhancing visibility of the field in medical education, improving working conditions, offering financial incentives, and addressing disparities in training quality across Europe. The European radiotherapist shortage is a systemic issue requiring coordinated efforts to standardize training, address economic barriers, and improve the specialty's appeal. By fostering collaboration and reform, European nations can meet the growing demand for cancer care and secure a sustainable workforce for the future.

Artificial intelligence (AI) has made significant strides in cardiac imaging, offering advancements in image acquisition, risk prediction, and workflow automation. However, its readiness for widespread clinical adoption remains debated. This review explores both sides of the argument across key domains. It discusses the advantages and challenges of AI for cardiac imaging regarding pre-and post-processing, risk-stratification and prognostication, workflow augmentation, regulatory and ethical frameworks, and cost-effectiveness of AI tools. It will discuss the diagnostic accuracy shown by AI for automated measurements, improved image quality and workflow efficiency with AI-driven worklist prioritization. The potential of personalized care using AI-based prognostic models. It discusses regulatory frameworks for approving AI tools, while ethical frameworks to ensure safe and ethical use of AI are being implemented, simultaneously reimbursement is becoming available, signalling growing trust in their safety and efficacy. It also addresses the challenges AI has yet to overcome, such as the lack of generalizability across diverse populations, limited availability of outcome data and cost-efficacy studies. Despite progress, regulatory and ethical frameworks still struggle to keep pace with AI's rapid evolution, raising concerns about accountability, patient safety, bias, data privacy, and algorithmic transparency.

Background: Rheumatoid arthritis (RA) patients frequently report fatigue, which notably diminishes their quality of life. Emerging research points to a correlation between inflammation-induced fatigue and brain structural alterations.

Objectives: This study evaluates the variance in myelin integrity among patients with RA-related fatigue, investigating the potential of magnetization transfer ratio (MTR) as a biomarker, in comparison with healthy controls.

Methods: A prospective cohort analysis was conducted comprised 60 RA patients with fatigue, categorized into active (n = 30) and non-active (n = 30) disease states, alongside 20 healthy controls (HC). A 3 Tesla MRI system was utilized to perform diffusion tensor imaging (DTI) and magnetization transfer imaging (MTI) sequences. MTR maps were generated using in-house MATLAB code and co-registered with DTI data using SPM8. These were then analyzed through tract-based spatial statistics (TBSS) with threshold-free cluster enhancement (TFCE) and corrected for multiple comparisons. MTR values were assessed using Randomize from the FSL toolkit, applying a general linear model (GLM) for voxel-wise analysis and TFCE for p-value generation, with family-wise error (FWE) control (P < .05) for multiple comparisons.

Results: The RF group exhibited significantly lower myelin integrity (TFCE, P < .05) compared to HCs, particularly in the middle cerebellar peduncle and splenium of the corpus callosum, with no marked difference between active and non-active RA disease statuses. There is a discernible disparity in myelin integrity between RA patients with fatigue and healthy individuals, suggesting microstructural white matter alterations that are congruent with DTI findings.

Conclusion: This study reveals that rheumatoid arthritis (RA) patients with fatigue exhibit significantly lower myelin integrity, particularly in the middle cerebellar peduncle and splenium of the corpus callosum, compared to healthy controls. Notably, this finding was consistent regardless of the active or non-active status of the RA disease, highlighting persistent white matter alterations in this patents cohort.

Advances in knowledge: The research demonstrates that magnetization transfer ratio (MTR) imaging can effectively map microstructural changes in RA patients with fatigue, suggesting its potential as a biomarker for assessing white matter integrity in this condition. While it does not establish a direct causal relationship, it provides valuable insights into the role of MTR mapping in understanding brain alterations in patients with fatigue-related RA.

Objectives: Over 9000 patients are diagnosed with oesophageal cancer annually in the United Kingdom (UK). Decision-making about treatment options is influenced by radiological staging, which may include computed tomography (CT), positron emission tomography (PET), and endoscopic ultrasound (EUS). The use of EUS varies considerably around the UK and, since the introduction of PET-CT, the added value of EUS has been questioned. The VALUE study aims to understand this variation and determine how often and why EUS changes treatment decisions. VALUE will also evaluate patient and clinician experiences and opinions of EUS.

Methods: This is a prospective, observational study investigating EUS in oesophageal cancer staging. Patients will be recruited at up to eleven sites in the UK, where they will be consented (if eligible) and registered onto iMedidata RAVE. Clinical and demographic data, TNM staging, pre and post EUS treatment decisions, and complications will be collected. We will attempt to sample patients from ethnic minority backgrounds in the study population, as they are underrepresented in research. Up to 30 patients and 30 clinicians will be interviewed to evaluate the use of EUS and experiences of both patient and clinician. The primary endpoint is the proportion of cases that EUS changes treatment decisions. Secondary endpoints include identification of factors that clinicians' and patients consider when deciding if EUS should be used, the time from diagnosis to treatment decision before and after EUS, and the reasons why EUS changed management. The study has been registered on Clinicaltrials.gov: NCT06440174. The trial is open to recruitment.

Results: In total, 180 patients with potentially curable oesophageal cancer who are suitable for EUS will participate. Recruitment is currently planned until September 2025 and study results will be reported after June 2026.

Conclusion: The VALUE study will enable a better understanding of how and why EUS is used in oesophageal cancer. This research will identify important factors that clinicians and patients consider when deciding EUS use and determine the frequency that EUS changes treatment decisions in the modern staging pathway.

Advances in knowledge: The VALUE study is a prospective, multi-centre observational study investigating the use of EUS in the modern era of oesophageal cancer staging. The study aims to determine how often and why EUS changes treatment decisions. A qualitative component will explore both clinician and patient attitudes towards EUS.

Lung cancer is the second most commonly diagnosed cancer worldwide. In the present era of targeted therapy for various lung cancer mutations, it is essential to be aware of the imaging correlates of various lung cancer mutations on contrast enhanced computed tomography of thorax. In this article, we have discussed the imaging patterns of various types of lung cancer including different mutations and also comprehensively reviewed the imaging recommendations (National Comprehensive Cancer Network [NCCN], European Society of Medical Oncology [ESMO] and American Society of Clinical Oncology [ASCO]) and management guidelines of lung cancer (non-small cell, small cell and other neuroendocrine tumours). We have also discussed guidelines for screening, diagnosis, staging (recent 9th edition tumour node metastasis [TNM]), treatment response evaluation, and follow up. Role of interventional radiology in the treatment of primary lung cancer, lung metastasis, and management of posttreatment complications, have also been described in detail in this article. In addition, current status of artificial intelligence in lung cancer has also been briefly discussed.

Objectives: To investigate how anti-PD-1 treatment affects both Programmed Death-Ligand 1 (PD-L1) expression and glucose metabolism within normal tissues of advanced non-small cell lung cancer (NSCLC) patients using a dual SPECT/CT and PET/CT imaging approach.

Methods: Ten advanced NSCLC patients (NCT04436406) undergoing anti-PD-1 therapy ± chemotherapy underwent imaging at baseline and 9 weeks. PD-L1 expression was measured using [^99mTc]-labelled single-domain PD-L1 antibody single-photon emission computed tomography/computed tomography ([^99mTc]NM-01 SPECT/CT). Glucose uptake was measured using [¹⁸F]-Fluorodeoxyglucose positron emission tomography/computed tomography ([¹⁸F]FDG PET/CT). Two independent observers marked regions of interest across normal organs (liver, lung, spleen, bone marrow, muscle, kidney, pancreas, left ventricular myocardium, and blood pool) to determine maximum and mean standardized uptake values (SUV) at both time points. Observer agreement was measured with an intraclass correlation coefficient (ICC).

Results: No significant changes in SUVs, indicating PD-L1 expression and glucose metabolism, were detected in normal organs after 9 weeks of treatment (all P > .05). No patients developed immune-related adverse events (irAEs) during the study period. Observer measurements showed excellent consistency with an ICC of 0.99 (95% confidence interval 0.99-0.99).

Conclusions: Our study showed stable PD-L1 expression and glucose metabolism within normal organs in advanced NSCLC patients treated with anti-PD-1 therapy ± chemotherapy. Interobserver reliability between observers was excellent. Additional studies with larger patient groups and a specific focus on irAE cases are needed.

Advances in knowledge: Through a dual-modality molecular imaging approach, this research provides novel insight into anti-PD-1 therapy's effects on PD-L1 expression and glucose metabolism in normal organs of NSCLC patients, demonstrating that these parameters remain stable post-treatment.

Objective: To report the clinical application, dosimetric features, efficacy, and toxicity profile of HyperArc (HA) for benign orbital tumours not amenable to surgical resection.

Methods: A retrospective interventional cohort study. Gross target volume included the radiologically evident tumour and the optic nerve (excluded in case of haemangioma). Dosimetry was compared between HA and volumetric modulated arc therapy (VMAT) radiotherapy. Patients were treated with HA and followed-up clinically and radiologically for response and toxicity assessment.

Results: Eight patients were included in our study, six patients with an optic nerve sheath meningioma, one cavernous haemangioma and one orbital schwannoma. All patients demonstrated tumour regression, mean tumour volume prior to treatment of was 4916 mm³ and reduced to 3239 mm³ (P = .03). Three of eight patients showed improvement of visual acuity, three retained excellent pre-treatment vision and two patients had a reduction of vision. HA and VMAT planning target volume coverage dosimetry was similar (D95%: 98.7% and 98.6%, P > .05). The dosimetry of the contralateral lens (32.2 vs 69.8 Gy), lacrimal gland (1.7 vs 7.8 Gy), optic nerve (9.0 vs 26.6 Gy), nasal cavity (10.2 vs 20.6 Gy) and ipsilateral temporal lobe (4.9 vs 11.6 Gy) was significantly improved (P < .001) with HA.

Conclusion: This is the first reported clinical application of HA for benign orbital tumours. HA was an effective and well tolerated treatment modality. HA offered better dosimetry for some of the OARs compared to VMAT.

Advances in knowledge: This is the first article reporting the use of the HA system for planning and delivery of radiotherapy for orbital tumours.