European Radiology最新文献

Objectives: There is limited evidence of the pericoronary fat attenuation index (FAI) as an imaging marker to assess cancer therapy-related cardiovascular toxicity. We aimed to measure FAI in four consecutive coronary CT angiography (CTA) scans before and 3, 6, and 12 months after anthracycline treatment in patients with breast cancer to determine trends in dynamic changes in FAI after treatment.

Methods: We performed a post hoc analysis of a prospective study (between August 2019 and July 2020) in which anthracycline-induced myocardial injury was evaluated using cardiac CT. FAI was quantified using coronary CTA images before and 3, 6, and 12 months after anthracycline treatment. The FAIs of the three coronary arteries were averaged to calculate the FAI (Total).

Results: FAI was analyzed on 14 patients with breast cancer who had adequate CT image quality (mean age, 62 years ± 11 (SD); 14 women). During the observation period, all 14 patients treated with anthracycline developed mild asymptomatic cardiac dysfunction related to cancer treatment (CTRCD). FAI (Total) showed a gradual increase during the observation period compared to baseline (baseline: -77.3 ± 5.6 HU, 3 months: -77.1 ± 4.8 HU, 6 months: -76.5 ± 5.4 HU, 12 months: -73.8 ± 5.8 HU). FAI (Total) was significantly elevated at 12 months compared to baseline (p < 0.001).

Conclusion: In patients with breast cancer, FAI showed a gradual increase at 3, 6, and 12 months after treatment with anthracyclines compared to before treatment. FAI may be used as an imaging biomarker of coronary artery inflammation in the follow-up of anthracycline therapy and may contribute to the personalization of therapy through early detection of coronary toxicity.

Key points: Question Is pericoronary fat attenuation index (FAI) a potential imaging biomarker for assessing changes in pericoronary adipose tissue related to cancer therapy-related cardiovascular toxicity? Findings In 14 patients with breast cancer, FAI showed a gradual increase at 3, 6, and 12 months after treatment with anthracyclines compared to before treatment. Clinical relevance FAI may be an imaging biomarker for the detection and treatment of cancer therapy-related cardiovascular toxicity.

Objective: To compare the clinical outcomes of patients with unifocal paratracheal papillary thyroid microcarcinoma (PTMC) after thermal ablation (TA) vs. partial thyroidectomy (PT).

Materials and methods: This retrospective multicenter study included 436 patients with unifocal, clinical N0 paratracheal PTMC who underwent TA (210 patients) or PT (236 patients) between June 2014 and December 2020. The propensity score matching method was used to mitigate confounding factors between the two groups. Disease progression, progression-free survival (PFS), complications, and treatment variables were compared. Adjusted Cox regression models were utilized to assess the impact of treatment on disease progression.

Results: After matching, a comparable incidence of disease progression (3.3% vs. 2.2%, p = 0.79) and comparable 5-year PFS rates (97.0% vs. 97.4%, p = 0.75) were observed between the TA and PT groups. Adjusted Cox regression models showed no significant correlation between TA and disease progression. TA was associated with shorter hospitalization (0 vs. 6.0 days), less estimated blood loss (0 vs. 15.0 mL), shorter incision length (0.3 vs. 6.0 cm), and lower costs ($1748.3 vs. $2898.0) compared with PT (all p < 0.001). The complication rate was 1.1% after TA and 3.3% after PT (p = 0.28), with permanent complications were exclusively observed in the PT group.

Conclusion: The mid-term incidence of disease progression and PFS rates were similar between TA and PT in patients with unifocal paratracheal PTMC. TA might represent a promising alternative treatment to PT for eligible patients with paratracheal PTMC.

Key points: Question Is thermal ablation a viable alternative treatment to partial thyroidectomy for treating paratracheal papillary thyroid microcarcinoma? Findings Comparable incidence of disease progression and 5-year progression-free survival rates were observed between thermal ablation and partial thyroidectomy. Clinical relevance Thermal ablation, as a minimally invasive procedure, provides a promising alternative to partial thyroidectomy, with comparable clinical outcomes for patients with paratracheal papillary thyroid microcarcinoma.

Lung cancer is the most common and deadly cancer worldwide. The 9th edition of the tumor node meta (TNM) classification system, effective from January 1, 2025, introduces significant updates. Notably, the N2 category is newly divided into N2a (single-station involvement) and N2b (multiple-station involvement), which reflects distinct prognostic implications. Additionally, the M1c category is now subcategorized into M1c1 (multiple metastases in a single organ system) and M1c2 (metastases in multiple organ systems), affecting stage classification. This reclassification allows for potential downstaging, which could expand treatment options for affected patients. Accurate imaging remains crucial for the classification of anatomical stages. As the TNM system evolves, enhanced imaging precision will play a key role in implementing these updates and ultimately improve patient outcomes. KEY POINTS: Question The 9th TNM for lung cancer introduces changes in the N2 and M1c descriptors, to better align with new therapeutic options and outcome studies. Findings Proper knowledge of the key changes of the 9th TNM can help radiologists offer clinicians a meaningful report. Clinical relevance Radiologists should incorporate the 9th TNM classification into their reports and discussions in multidisciplinary meetings, thus ensuring a common language across disciplines to enable clearer communication with other specialists, supporting more precise and cohesive decision-making in patient care.

Objective: This study aimed to develop an open-source multimodal large language model (CXR-LLaVA) for interpreting chest X-ray images (CXRs), leveraging recent advances in large language models (LLMs) to potentially replicate the image interpretation skills of human radiologists.

Materials and methods: For training, we collected 592,580 publicly available CXRs, of which 374,881 had labels for certain radiographic abnormalities (Dataset 1) and 217,699 provided free-text radiology reports (Dataset 2). After pre-training a vision transformer with Dataset 1, we integrated it with an LLM influenced by the LLaVA network. Then, the model was fine-tuned, primarily using Dataset 2. The model's diagnostic performance for major pathological findings was evaluated, along with the acceptability of radiologic reports by human radiologists, to gauge its potential for autonomous reporting.

Results: The model demonstrated impressive performance in test sets, achieving an average F1 score of 0.81 for six major pathological findings in the MIMIC internal test set and 0.56 for six major pathological findings in the external test set. The model's F1 scores surpassed those of GPT-4-vision and Gemini-Pro-Vision in both test sets. In human radiologist evaluations of the external test set, the model achieved a 72.7% success rate in autonomous reporting, slightly below the 84.0% rate of ground truth reports.

Conclusion: This study highlights the significant potential of multimodal LLMs for CXR interpretation, while also acknowledging the performance limitations. Despite these challenges, we believe that making our model open-source will catalyze further research, expanding its effectiveness and applicability in various clinical contexts.

Key points: Question How can a multimodal large language model be adapted to interpret chest X-rays and generate radiologic reports? Findings The developed CXR-LLaVA model effectively detects major pathological findings in chest X-rays and generates radiologic reports with a higher accuracy compared to general-purpose models. Clinical relevance This study demonstrates the potential of multimodal large language models to support radiologists by autonomously generating chest X-ray reports, potentially reducing diagnostic workloads and improving radiologist efficiency.

Purpose: To investigate the test-retest repeatability of radiomic features in myocardial native T1 and T2 mapping.

Methods: In this prospective study, 50 healthy volunteers (29 women and 21 men, mean age 39.4 ± 13.7 years) underwent two identical cardiac magnetic resonance imaging (MRI) examinations at 1.5 T. The protocol included native T1 and T2 mapping in both short-axis and long-axis orientation. For T1 mapping, we investigated standard (1.9 × 1.9 mm) and high (1.4 × 1.4 mm) spatial resolution. After manual segmentation of the left ventricular myocardium, 100 radiomic features from seven feature classes were extracted and analyzed. Test-retest repeatability of radiomic features was assessed using the intraclass correlation coefficient (ICC) and classified as poor (ICC < 0.50), moderate (0.50-0.75), good (0.75-0.90), and excellent (> 0.90).

Results: For T1 maps acquired in short-axis orientation at standard resolution, repeatability was excellent for 6 features, good for 29 features, moderate for 19 features, and poor for 46 features. We identified 15 features from 6 classes which showed good to excellent reproducibility for T1 mapping in all resolutions and all orientations. For short-axis T2 maps, repeatability was excellent for 6 features, good for 25 features, moderate for 23 features, and poor for 46 features. 12 features from 5 classes were found to have good to excellent repeatability in T2 mapping independent of slice orientation.

Conclusion: We have identified a subset of features with good to excellent repeatability independent of slice orientation and spatial resolution. We recommend using these features for further radiomics research in myocardial T1 and T2 mapping.

Key points: Question The study addresses the need for reliable radiomic features for quantitative analysis of the myocardium to ensure diagnostic consistency in cardiac MRI. Findings We have identified a subset of radiomic features demonstrating good to excellent repeatability in native T1 and T2 mapping independent of slice orientation and resolution. Clinical relevanceRadiomic features have been proposed as diagnostic and prognostic biomarkers in various heart diseases. By identifying a subset of particularly reproducible radiomic features our study serves to inform the selection of radiomic features in future research and clinical applications.

Purpose: To assess the success rate of confirmation of ultrasound-guided intranodal needle positioning by saline injection for dynamic contrast-enhanced magnetic resonance lymphangiography (DCMRL) in pediatric patients.

Material and methods: Data from children undergoing nodal DCMRL after ultrasound-guided needle positioning into inguinal lymph nodes and validation of the needle position by injection of plain saline solution between 05/2020 and 12/2022 were reviewed. On injection of saline solution, adequate needle position was confirmed by lymph node distension without leakage. Detection rates and lymph node diameters were recorded. Technical success of needle placement was defined as enhancement of ipsilateral iliac draining lymph vessels on DCMRL, while clinical success was based on enhancement of central lymphatics and/or lymphatic pathologies being observed.

Results: One hundred sixteen DCMRL were performed in 90 children (58 male, mean age 6.1 years, range 3 weeks-18 years). In 232/232 groins lymph nodes were identified on ultrasound with a mean diameter of 2.5 mm (smallest diameter 1 mm in n = 24 patients). Due to skin inflammation, no puncture was performed in 2/232 groins. Saline injection showed lymph node distension in 230/230 punctured nodes. On MR contrast injection enhancement of draining lymph vessels was seen in 228/230 nodes. In 1/230 nodes, in-bore needle retraction led to lymphatic enhancement, so a total of 229/230 needle placements were technically successful. One of the 230 DCMRLs was successful with only a unilateral contrast application. Overall, 116/116 DCMRLs were clinically successful.

Conclusion: Confirmation of ultrasound-guided needle positioning for nodal DCMRL using saline injection is a reliable technique with a very high success rate in pediatric patients with small lymph nodes.

Key points: Question Evaluation of ultrasound-guided injection needle positioning for dynamic contrast-enhanced MR-lymphangiography in children requires validation. Findings Confirmation of needle positioning by ultrasound-guided saline injection is a reliable technique with a very high success rate for MR-lymphangiography in pediatric patients. Clinical relevance Intranodal needle position for dynamic contrast-enhanced lymphangiography can be confirmed with a very high success rate using saline injection alone in a pediatric cohort.

Objective: To provide up-to-date European Society of Urogenital Radiology (ESUR) guidelines for staging and follow-up of patients with ovarian cancer (OC).

Methods: Twenty-one experts, members of the female pelvis imaging ESUR subcommittee from 19 institutions, replied to 2 rounds of questionnaires regarding imaging techniques and structured reporting used for pre-treatment evaluation of OC patients. The results of the survey were presented to the other authors during the group's annual meeting. The lexicon was aligned with the Society of American Radiology (SAR)-ESUR lexicon; a first draft was circulated, and then comments and suggestions from the other authors were incorporated.

Results: Evaluation of disease extent at diagnosis should be performed by chest, abdominal, and pelvic CT. The radiological report should map the disease with specific mention of sites that may preclude optimal cytoreductive surgery. For suspected recurrence, CT and [¹⁸F]FDG PET-CT are both valid options. MRI can be considered in experienced centres, as an alternative to CT, considering the high costs and the need for higher expertise in reporting.

Conclusions: CT is the imaging modality of choice for preoperative evaluation and follow-up in OC patients. A structured radiological report, including specific mention of sites that may preclude optimal debulking, is of value for patient management.

Key points: Question Guidelines were last published for ovarian cancer (OC) imaging in 2010; here, guidance on imaging techniques and reporting, incorporating advances in the field, are provided. Findings Structured reports should map out sites of disease, highlighting sites that limit cytoreduction. For suspected recurrence, CT and 18FDG PET-CT are options, and MRI can be considered. Clinical relevance Imaging evaluation of OC patients at initial diagnosis (mainly based on CT), using a structured report that considers surgical needs is valuable in treatment selection and planning.

Objectives: The aim is to assess the feasibility and accuracy of a novel quantitative ultrasound (US) method based on global speed-of-sound (g-SoS) measurement using conventional US machines, for breast density assessment in comparison to mammographic ACR (m-ACR) categories.

Materials and methods: In a prospective study, g-SoS was assessed in the upper-outer breast quadrant of 100 women, with 92 of them also having m-ACR assessed by two radiologists across the entire breast. For g-SoS, ultrasonic waves were transmitted from varying transducer locations and the image misalignments between these were then related analytically to breast SoS. To test reproducibility, two consecutive g-SoS acquisitions each were taken at two similar breast locations by the same operator.

Results: Measurements were found highly repeatable, with a mean absolute difference ± standard deviation of 3.16 ± 3.79 m/s. Multiple measurements were combined yielding a single g-SoS estimate per each patient, which strongly correlated to m-ACR categories (Spearman's = 0.773). The g-SoS values for categories A-D were 1459.6 ± 0.74, 1475.6 ± 15.92, 1515.6 ± 27.10, and 1545.7 ± 20.62, with all groups (except A-B) being significantly different from each other. Dense breasts (m-ACR C&D) were classified with 100% specificity at 78% sensitivity, with an area under the curve (AUC) of 0.931. Extremely dense breasts (m-ACR D) were classified with 100% sensitivity at 77.5% specificity (AUC = 0.906).

Conclusion: Quantitative g-SoS measurement of the breast was shown feasible and repeatable using conventional US machines, with values correlating strongly with m-ACR assessments.

Key points: Question Breast density is a strong predictor of risk for breast cancer, which frequently develops in dense tissue regions. Therefore, density assessment calls for refined non-ionizing methods. Findings Quantitative global speed-of-sound (g-SoS) measurement of the breast is shown to be feasible using conventional US machines, repeatable, and able to classify breast density with high accuracy. Clinical relevance Being effective in classifying dense breasts, where mammography has reduced sensitivity, g-SoS can help stratify patients for alternative modalities. Ideal day for mammography or MRI can be determined by monitoring g-SoS. Furthermore, g-SoS can be integrated into personalized risk assessment.

Objectives: To evaluate the image quality and lung nodule detectability of ultralow-dose CT (ULDCT) with adaptive statistical iterative reconstruction-V (ASiR-V) post-processed using a deep learning image reconstruction (DLIR)-based image domain compared to low-dose CT (LDCT) and ULDCT without DLIR.

Materials and methods: A total of 210 patients undergoing lung cancer screening underwent LDCT (mean ± SD, 0.81 ± 0.28 mSv) and ULDCT (0.17 ± 0.03 mSv) scans. ULDCT images were reconstructed with ASiR-V (ULDCT-ASiR-V) and post-processed using DLIR (ULDCT-DLIR). The quality of the three CT images was analyzed. Three radiologists detected and measured pulmonary nodules on all CT images, with LDCT results serving as references. Nodule conspicuity was assessed using a five-point Likert scale, followed by further statistical analyses.

Results: A total of 463 nodules were detected using LDCT. The image noise of ULDCT-DLIR decreased by 60% compared to that of ULDCT-ASiR-V and was lower than that of LDCT (p < 0.001). The subjective image quality scores for ULDCT-DLIR (4.4 [4.1, 4.6]) were also higher than those for ULDCT-ASiR-V (3.6 [3.1, 3.9]) (p < 0.001). The overall nodule detection rates for ULDCT-ASiR-V and ULDCT-DLIR were 82.1% (380/463) and 87.0% (403/463), respectively (p < 0.001). The percentage difference between diameters > 1 mm was 2.9% (ULDCT-ASiR-V vs. LDCT) and 0.5% (ULDCT-DLIR vs. LDCT) (p = 0.009). Scores of nodule imaging sharpness on ULDCT-DLIR (4.0 ± 0.68) were significantly higher than those on ULDCT-ASiR-V (3.2 ± 0.50) (p < 0.001).

Conclusion: DLIR-based image domain improves image quality, nodule detection rate, nodule imaging sharpness, and nodule measurement accuracy of ASiR-V on ULDCT.

Key points: Question Deep learning post-processing is simple and cheap compared with raw data processing, but its performance is not clear on ultralow-dose CT. Findings Deep learning post-processing enhanced image quality and improved the nodule detection rate and accuracy of nodule measurement of ultralow-dose CT. Clinical relevance Deep learning post-processing improves the practicability of ultralow-dose CT and makes it possible for patients with less radiation exposure during lung cancer screening.

Objectives: Conduct a systematic review and meta-analysis on the application of the Radiomics Quality Score (RQS).

Materials and methods: A search was conducted from January 1, 2022, to December 31, 2023, for systematic reviews which implemented the RQS. Identification of articles prior to 2022 was via a previously published review. Quality scores of individual radiomics papers, their associated criteria scores, and these scores from all readers were extracted. Errors in the application of RQS criteria were noted and corrected. The RQS of radiomics papers were matched with the publication date, imaging modality, and country, where available.

Results: A total of 130 systematic reviews were included, and individual quality scores 117/130 (90.0%), criteria scores 98/130 (75.4%), and multiple reader data 24/130 (18.5%) were extracted. 3258 quality scores were correlated with the radiomics study date of publication. Criteria scoring errors were discovered in 39/98 (39.8%) of articles. Overall mean RQS was 9.4 ± 6.4 (95% CI, 9.1-9.6) (26.1% ± 17.8% (25.3%-26.7%)). Quality scores were positively correlated with publication year (Pearson R = 0.32, p < 0.01) and significantly higher after publication of the RQS (year < 2018, 5.6 ± 6.1 (5.1-6.1); year ≥ 2018, 10.1 ± 6.1 (9.9-10.4); p < 0.01). Only 233/3258 (7.2%) scores were ≥ 50% of the maximum RQS. Quality scores were significantly different across imaging modalities (p < 0.01). Ten criteria were positively correlated with publication year, and one was negatively correlated.

Conclusion: Radiomics study adherence to the RQS is increasing with time, although a vast majority of studies are developmental and rarely provide a high level of evidence to justify the clinical translation of proposed models.

Key points: Question What level of adherence to the Radiomics Quality Score have radiomics studies achieved to date, has it increased with time, and is it sufficient? Findings A meta-analysis of 3258 quality scores extracted from 130 review articles resulted in a mean score of 9.4 ± 6.4. Quality scores were positively correlated with time. Clinical relevance Although quality scores of radiomics studies have increased with time, many studies have not demonstrated sufficient evidence for clinical translation. As new appraisal tools emerge, the current role of the Radiomics Quality Score may change.