European Radiology最新文献

Perfusion MRI techniques-including dynamic susceptibility contrast (DSC) MRI, dynamic contrast-enhanced (DCE) MRI, arterial spin labeling (ASL) MRI, and intravoxel incoherent motion (IVIM) MRI-hold strong potential as imaging techniques for diagnosing, staging, and monitoring disease across a range of clinical applications. However, clinical adoption, especially of quantitative parameters, remains variable across techniques. Key barriers to broader implementation include a lack of standardized acquisition and analysis protocols, leading to poor reproducibility and reduced clinical confidence. Additionally, limited awareness and understanding of certain techniques among radiologists contribute to underutilization in practice. This work provides practice recommendations to support radiologists in integrating perfusion MRI into routine clinical workflows. It includes guidance on technique selection, acquisition, and analysis, supported by a flowchart outlining typical imaging pathways. These efforts align with ongoing initiatives such as the Quantitative Medical Imaging Coalition (formerly QIBA) and the ISMRM Open Science Initiative for Perfusion Imaging (OSIPI), which are developing standards and tools to enhance reproducibility and clinical utility. Ultimately, the successful adoption of state-of-the-art perfusion MRI depends on close collaboration between clinicians, researchers, and industry stakeholders to ensure robust, standardized, and clinically meaningful application. KEY POINTS: Perfusion MRI parameters hold great promise as imaging biomarkers, but their clinical adoption, especially of quantitative parameters, remains variable across perfusion MRI techniques. An overview of perfusion MRI techniques, explaining the physics, illustrating clinical applications, and addressing common technical challenges, is provided to support perfusion MRI use in clinical practice. Successful adoption of state-of-the-art perfusion MRI depends on close collaboration between clinicians, researchers, and industry stakeholders to ensure robust, standardized, and clinically meaningful applications for patient care.

Objectives: Intracranial hemorrhage (ICH) is a time-critical neurological emergency in which rapid CT-based assessment directly informs treatment decisions. This study aimed to develop an automated deep-learning pipeline to enhance ICH detection, segmentation, and localization, complemented by clinical decision-making support through a large language model.

Materials and methods: The detection model was trained on 21,784 labeled and 3528 unlabeled CT scans from the RSNA dataset using semi-supervised learning. The segmentation model was trained on 1226 scans from the HS dataset to delineate six ICH subtypes. Hydrocephalus and midline-shift models were trained on a dedicated 507-scan subset of the HS dataset. Hemorrhage and edema locations were registered to standard brain regions to improve interpretability. For evaluation, the CQ500 dataset (491 patients) was used as an external validation and test cohort. Clinical recommendations were generated using the GPT-4o Assistants API based on published guidelines and trials.

Results: On the test set, detection achieved an AUC of 0.96 (95% CI: 0.94-0.98), and segmentation yielded Dice values ranging from 0.71 to 0.93 with corresponding 95% CIs from 0.61-0.76 to 0.90-0.96, while volume estimation showed high concordance (CCC 0.820-0.996). Intraparenchymal hemorrhage (IPH) localization demonstrated strong agreement with κ values of 0.85-1.00 across brain regions. Clinical decisions generated by the pipeline were highly rated, with one neurosurgeon assigning median scores of 4 and 5 for examination and treatment, and the other assigning 5 for both.

Conclusions: This deep learning pipeline combines imaging analysis with actionable clinical decisions, demonstrating significant potential as a valuable tool for emergency care.

Key points: Question Rapid and accurate identification of ICH on CT is critical for guiding treatment, yet remains difficult using standard emergency radiological evaluation. Findings The end-to-end artificial intelligence pipeline achieved high accuracy in ICH detection, segmentation, and localization, with strong concordance to manual measurements and reliable clinical recommendations. Clinical relevance By automating image analysis and clinical decision-making, the pipeline demonstrated significant potential to reduce diagnostic delays, improve treatment guidance, and enhance patient outcomes in emergency care settings.

Objectives: To gain insight into emergency radiologists' views on the role of contrast-enhanced CT (CECT) in sepsis management.

Materials and methods: This analysis of a survey distributed in 2023 to members of the European Society of Emergency Radiology (ESER) (n = 297) gathered perspectives on the role of CECT in patients with sepsis. The previously validated questionnaire used for this survey encompassed demographic information, clinical experience, and inquiries regarding the timing and rationale for CT. Results were compared with data from a prior single-center survey among clinicians and general radiologists. Responses were collected anonymously and analyzed using descriptive statistics and chi-square tests. As not all items were mandatory, item-specific response numbers may vary and are reported accordingly throughout the manuscript.

Results: A total of 144 emergency radiologists participated, with most of them endorsing a 1-6-h timeframe for CECT after the diagnosis of sepsis (45.8%; n = 27/59). However, a notable proportion accepted longer intervals > 12 h (35.6%; n = 21/59). Emergency radiologists particularly opted for repeat imaging in patients with sepsis and clinical deterioration (35.3%; 24/68), whereas clinicians tended to be more hesitant (2.9%; n = 10/341).

Conclusion: The results of this survey indicate strong agreement among emergency radiologists on the relevance of prompt CECT for the timely diagnostic management of patients with sepsis. Several aspects related to timing and indication show significant interdisciplinary differences, requiring further study.

Key points: Question While contrast-enhanced CT can aid in detecting the infectious focus, this study explores emergency radiologists' perspectives on its role in sepsis management. Findings Radiologists and clinicians from different subspecialties agree on the importance of promptly performed (≥ 1-6 h) CECT in sepsis management and the contraindications of contrast application. Clinical relevance This survey shows that radiologists and clinicians largely agree on the importance of CECT in sepsis management.

Objectives: Lymphatic-venous anastomosis (LVA) is an effective surgical treatment for lymphedema, which requires accurate identification of lymphatic vessels. Indocyanine Green (ICG) lymphography, the most common method for lymphatic mapping, cannot always successfully identify lymphatic vessels. We aimed to explore high-frequency ultrasound (HFUS) and contrast-enhanced ultrasound (CEUS) as a reliable alternative for lymphatic mapping when ICG lymphography is not feasible.

Materials and methods: We performed combined HFUS and CEUS for lymphatic mapping on the patients who exhibited no obvious linear pattern on ICG lymphography. The inner and outer diameters and depths of the lymphatic vessels were measured. We subsequently evaluated the accuracy of US lymphatic mapping by comparing it with the operative results. And the postoperative volume and circumference of the affected limbs were compared with the preoperative measurements.

Results: We recruited 111 patients with lymphedema, including 96 limbs and 24 perineal areas affected. Three hundred forty-five lymphatics in the limbs and 52 in the perineum underwent anastomosis and were analyzed. Comparable lymphatic vessel diameter (inner: 0.5-0.9 mm; outer: 0.8-0.9 mm) and depth (9-10 mm) measurements across HFUS, CEUS, and combined HFUS + CEUS. However, HFUS + CEUS significantly improved detection sensitivity, identifying 313 vessels (91.1% accuracy) vs 114 (88.6%) for HFUS and 22 (90.9%) for CEUS. Significant postoperative reductions in limb circumference (39.3 ± 7.4 cm to 37.8 ± 7.1 cm) and volume (81.1 ± 35.8 L to 74.2 ± 33.4 L, p < 0.001). All ultrasound methods consistently showed volume reduction (HFUS: 93.3 ± 25.4 L to 89.6 ± 24.1 L; CEUS: 92.4 ± 28.9 L to 83.4 ± 19.8 L; HFUS + CEUS: 91.2 ± 31.8 L to 84.2 ± 21.5 L, p < 0.001-0.002).

Conclusions: High-frequency US combined with CEUS serves as a reliable pre-op lymphatic mapping alternative when ICG lymphography fails.

Key points: Question In over 40% of lymphedema patients, preoperative ICG lymphangiography fails to show a linear pattern; can HFUS and CEUS provide complementary information? Findings ICG failed to visualize in 42.53% of patients; HFUS and CEUS identified lymphatics in all and achieved 94.5% accuracy. Clinical relevance This study confirmed that HFUS combined with CEUS improves the detection of lymphatic vessels and the success of LVA in ICG-negative cases.

Objective: To evaluate the performance of model-based dynamic contrast-enhanced (DCE)-MRI and diffusion-weighted imaging (DWI) in determining the disease activity of thyroid-associated ophthalmopathy (TAO), and to establish their additional value to fat-suppressed T2-weighted imaging (FS-T2WI) for staging TAO.

Materials and methods: Seventy-two patients with TAO (48 active, 96 eyes; 24 inactive, 48 eyes) were prospectively enrolled. DCE-MRI, DWI and FS-T2WI were scanned for pre-treatment evaluation. Simplified histogram parameters (min, mean, max) of DCE-MRI-derived K^trans, K_ep and V_e, apparent diffusion coefficient (ADC) and signal intensity ratio (SIR) on FS-T2WI of extraocular muscles were calculated for each orbit and compared between active and inactive groups. Multivariate analyses were used to identify independent indicators for disease activity. Receiver operating characteristic (ROC) curves analyses and DeLong tests were performed to evaluate and compare the performances of the identified significant imaging parameters and their combinations.

Results: Active TAO patients showed significantly higher mean and maximum V_e, higher minimum, mean and maximum ADC, higher minimum, mean and maximum SIR than inactive patients (p < 0.05). Mean SIR (odds ratio (OR) = 3.449, p = 0.002), mean ADC (OR = 1.008, p < 0.001), and mean V_e (OR = 14.138, p = 0.022) were found to be independent predictors of active TAO. Combination of mean V_e, mean ADC and mean SIR outperformed mean SIR alone in staging TAO (area under ROC curves, 0.839 vs 0.769, p = 0.016).

Conclusion: DCE-MRI and DWI could determine the disease activity of TAO and provide additional value to FS-T2WI in staging TAO.

Key points: Question Fat-suppressed T2-weighted imaging was the most commonly used imaging technique for determining the disease activity of thyroid-associated ophthalmopathy; however, its performance needs to be improved. Findings Dynamic contrast-enhanced magnetic resonance imaging and diffusion-weighted imaging could provide added value to fat-suppressed T2-weighted imaging for determining the clinical activity of thyroid-associated ophthalmopathy. Clinical relevance Dynamic contrast-enhanced magnetic resonance imaging and diffusion-weighted imaging can provide information about tissue permeability and water molecule diffusion of extraocular muscles in patients with thyroid-associated ophthalmopathy (TAO), and therefore provide additional value to fat-suppressed T2-weighted imaging in staging TAO.