European Radiology最新文献

Objective: To compare the malignancy risk stratification performance and inter-reader reliability of four Reporting and Data System (RADS) algorithms for solitary bone lesions: CT Bone-RADS, MRI Bone-RADS, Osseous Tumor (OT)-RADS, and Bone Tumor Imaging (BTI)-RADS.

Materials and methods: This retrospective analysis included patients with solitary bone lesions who underwent both CT and MRI between March 2005 and September 2021. Three radiologists independently categorized each lesion using CT Bone-RADS (1-4), MRI Bone-RADS (1-4), OT-RADS (2-5), and BTI-RADS (1-4). Categories were dichotomized into high- versus low-risk for malignancy. Diagnostic performance metrics and area under the receiver operating characteristic curve (AUC) were calculated for each reader as well as for a consensus interpretation generated using a majority-vote method. The reference standard was either histopathologic confirmation or imaging surveillance. Inter-reader reliability was assessed using Gwet's AC1 statistic.

Results: A total of 207 patients (mean age, 49 ± 18 years; 111 men and 96 women) were included. Consensus malignancy risk stratification performance (AUC; sensitivity/specificity/positive predictive value/negative predictive value/accuracy, %) was as follows: CT Bone-RADS (0.52; 95/9/43/73/44), MRI Bone-RADS (0.60; 98/12/44/88/47), OT-RADS (0.91; 93/71/69/94/80), and BTI-RADS (0.89; 98/39/53/96/63). Inter-reader reliability (AC1) was excellent for CT Bone-RADS (0.978), MRI Bone-RADS (0.931), and BTI-RADS (0.822), and moderate for OT-RADS (0.585).

Conclusion: Among the evaluated bone tumor-RADS, OT-RADS demonstrated the most balanced diagnostic performance with moderate inter-reader reliability. CT Bone-RADS, MRI Bone-RADS, and BTI-RADS showed excellent inter-reader reliability.

Key points: Question Evaluation of solitary bone lesions is important but often challenging. This study compared four bone tumor-RADS algorithms to determine which provides the best malignancy risk stratification. Findings Among the four RADS algorithms, OT-RADS demonstrated the most balanced overall diagnostic performance in consensus analysis, while CT Bone-RADS, MRI Bone-RADS, and BTI-RADS showed excellent inter-reader reliability. Clinical relevance Knowledge of each RADS system's performance characteristics helps clinicians apply these algorithms appropriately to optimize the assessment of solitary bone lesions.

Objectives: To identify predictors of early complete ablation zone resolution (within 1 year) after radiofrequency ablation (RFA) for low-risk papillary thyroid microcarcinoma (PTMC).

Materials and methods: A retrospective dual-center study enrolled 225 patients with low-risk PTMC (2017-2022). Ablation zone volume was tracked during follow-up, with the specific time of complete resolution modeled using exponential decay functions. Multivariable Cox regression and restricted cubic spline (RCS) analyses identified independent predictors of resolution.

Results: Cumulative complete resolution rates were 62.2% at 1 year and 98.7% at 2 years. Independent predictors of complete resolution within 1 year included normal thyroglobulin antibody (TgAb) levels (hazard ratio (HR): 2.64, 95% confidence Interval (CI): 1.38-5.07) and thyroid peroxidase antibody (TPOAb) levels (HR: 1.92, 95% CI: 1.34-2.75), nodule diameter ≤ 5 mm (HR: 1.53, 95% CI: 1.02-2.29), and absence of intratumoral vascularity (HR: 2.77, 95% CI: 1.83-4.21). Energy density showed an inverted U-shaped relationship with resolution probability within 1 year (p < 0.001 for non-linearity).

Conclusion: RFA achieves favorable long-term efficacy for low-risk PTMC, and complete resolution within 1 year is predictable by normal TgAb/TPOAb, smaller nodule size, absence of intratumoral vascularity, and moderate energy density. These findings may provide valuable insights for refining RFA techniques and the development of personalized follow-up.

Key points: Question Predicting early complete resolution of low-risk PTMC after RFA is critical to mitigate concerns about treatment outcomes and optimize follow-up. Findings Normal TgAb/TPOAb, smaller nodule size, absence of intratumoral vascularity, and moderate energy density independently predict early complete ablation zone resolution within 1 year after RFA. Clinical relevance Identifying predictors of early resolution enables optimized RFA energy delivery and pretreatment decision-making. This provides doctors and patients with evidence-based guidance to refine ablation strategies and personalize management plans.

Objectives: Automated artificial intelligence (AI)-based assessment of atherosclerosis burden applied to coronary computed tomography angiography (CCTA) can optimize image processing times, standardize interpretation, and minimize inter-observer variability. We investigated the diagnostic utility of AI-based CCTA quantification (AI-QCT) of coronary atherosclerosis in coronary segments co-registered with intravascular ultrasound (IVUS) of diseased and non-diseased segments.

Materials and methods: Patients who underwent CCTA and IVUS in the INVICTUS registry (ClinicalTrials.gov: NCT04066062) were enrolled. Images were analyzed by independent core laboratories blinded to each modality's findings. Vessel external elastic membrane (EEM), lumen, plaque volumes, plaque burden, and percent atheroma volume (PAV) were quantified in whole co-registered segments and subsegments containing non-calcified and low-attenuation plaques. A calcium index was calculated for the whole co-registered segment.

Results: A total of 108 vessels from 85 patients were included. Pearson's correlation demonstrated strong associations between AI-QCT and IVUS in quantifying the EEM volume (r = 0.899), lumen volume (r = 0.943), and plaque volume (r = 0.833), length-normalized PAV (r = 0.851), and calcium index (r = 0.960) in the whole-segment analysis. Strong correlations were seen for vessel, lumen, and plaque volumes in non-calcified (Pearson's coefficient: 0.95, 0.97, and 0.83, respectively) and low-attenuation (Pearson's coefficient: 0.90, 0.86, and 0.86, respectively) plaque segments. The minimum lumen area was 0.61 ± 1.18 mm² (95% CI, -0.83 to -0.38) smaller by AI-QCT than IVUS, with a similar lumen area stenosis (mean difference, 1.26 ± 24.17; 95% CI, -3.37 to 5.90).

Conclusions: AI-QCT quantification of atherosclerosis burden showed high correlations and close agreement with IVUS in whole-segment and segments with non-calcified and low-attenuation plaques.

Key points: Question Coronary atheroma burden is a powerful predictor of cardiovascular events. Can AI-based coronary CT angiography (CCTA) accurately quantify atherosclerotic burden across the full disease spectrum when compared with intravascular ultrasound (IVUS)? Findings AI-based CCTA quantification (AI-QCT) showed strong correlations with IVUS for plaque volume, burden, and calcium across whole coronary segments, including non-calcified and low-attenuation plaques. Clinical relevance AI-QCT provides rapid, automatic, and accurate atherosclerosis quantification without reader-dependent variability, enabling standardized cardiovascular risk assessment, treatment monitoring, and therapeutic decision-making across all disease severity spectrum in routine clinical practice.

Objectives: In breast cancer screening, determining the optimal balance between the number of screen-detected cancer cases and false-positive recalls is essential. This study explored the relationship between these indicators for the Dutch Digital Mammography Screening Program and aimed to determine the optimal recall rate.

Materials and methods: From March to June 2019, 21 screening radiologists provided continuous Probability-of-Malignancy (PoM) scores during their standard reading sessions. Scores ranged from 'no suspicion' (PoM = -100) to 'highest suspicion' (PoM = 100). Follow-up data were obtained in June 2024 and included recall decisions after double reading, outcomes of further assessments (false positive or screen-detected cancer), and interval cancer diagnoses. Recall-detection and receiver operating characteristic (ROC) curves were constructed for each reader and averaged to obtain summary curves, with error bars computed from hierarchical bootstrapping of cases within readers (1000 resamples). The overall screening performance was quantified using the area under the ROC curve (AUC).

Results: The final dataset comprised 40,829 screening records with 315 cancer cases. The overall recall rate was 2.33%, and the cancer detection rate after double reading was 6.4 per 1000 screens. Radiologist performance was high (AUC = 0.91). Moving the operating point results in either substantially lower cancer detection or relatively little gain.

Conclusion: This prospective study identified the trade-off between unconditional recall and detection rates, as well as conditional sensitivity and specificity. We found that Dutch screening radiologists perform at a high level and operate at a point that seems to optimize the false-positive recall and cancer detection rate trade-off.

Key points: Question Breast cancer screening requires a good balance between detection and false-positive rate. However, the interrelationship between these rates, and thus the optimal recall, is unknown. Findings Overall, the Dutch screening radiologists performed with high accuracy, and the current operating point optimizes the trade-off between cancer detection and false-positive recalls. Clinical relevance ROCS provides an efficient method to evaluate performance and determine target values based on data from screening practice. This method applies to various screening programs. Screening evaluation is essential for achieving and maintaining a positive benefit-to-harm ratio for participants.

Objectives: To investigate changes in the fatty acid composition of the lumbar vertebral bone marrow in patients with Crohn's disease (CD) and its relationships with disease activity and complex disease behavior.

Materials and methods: This study, designed as a single-center, cross-sectional, and prospective trial, was conducted between September 2023 and February 2025, with 83 CD patients and 70 healthy individuals. Disease activity was evaluated using the CD activity index (CDAI). Disease behavior was recorded based on the Montreal classification. Quantitative analysis of saturated, unsaturated, monounsaturated, and polyunsaturated fatty acids (SFA, UFA, MUFA, and PUFA) for lumbar vertebrae by using a two-dimensional bipolar multi-echo 3-T MRI. Spearman correlation and logistic regression analyses were employed.

Results: PUFA was significantly lower, whereas MUFA was significantly higher in the CD than in the control group (p = 0.03 and 0.04, respectively). CDAI was positively correlated with UFA and PUFA (r = 0.30 and 0.47; p = 0.01 and p < 0.001, respectively), and negatively correlated with SFA (r = -0.29, p = 0.01). The complicated disease behavior negatively correlated with PUFA only (r = -0.31; p = 0.01). Regression analysis showed that PUFA was an independent risk factor for CDAI (p = 0.01). PUFA and disease duration were independent impact factors for complicated disease behavior (p = 0.02 and 0.01, respectively).

Conclusions: CD patients exhibited alterations in bone marrow fatty acid composition compared to healthy controls. Bone marrow PUFA was a potential predictor of disease activity state and complicated disease behavior.

Key points: Questions What was the relationship of bone marrow fatty acids with disease activity and complex disease behavior in patients with Crohn's disease (CD)? Findings Alterations in bone marrow fatty acid composition were found in CD. Polyunsaturated fatty acids were related to disease activity and complex disease behavior. Clinical relevance Non-invasive MRI imaging assessment of bone marrow fatty acids in vivo has the potential to monitor disease activity and treatment response, which may provide a new imaging marker for insight into the inflammation in CD.