European Radiology最新文献

Objectives: To compare the diagnostic accuracy of ULDCT to CXR for detecting non-traumatic pulmonary diseases at the emergency department (ED) and to study diagnostic confidence levels.

Methods: Secondary analysis of the prospective OPTIMACT trial (2418 ED participants randomly allocated to ULDCT or CXR). Diagnoses at imaging at the ED were compared to the reference diagnosis on day 28. Ratios of positive diagnoses, true positives (TP), false positives (FP), false negatives (FN), and positive predictive values (PPV) were assessed with 95% confidence intervals (CI). The diagnostic confidence levels of the radiologists were studied.

Results: One thousand one hundred sixty-one ULDCT participants (mean age, 59 years ± 18 [standard deviation], 587 female) and 1151 CXR participants (mean age, 59 years ± 18 [standard deviation], 561 female) were evaluated. With ULDCT, pneumonia was 1.55 times (95% CI: 1.33-1.80) more often diagnosed at imaging at the ED, with significantly more TP (ratio 1.50; 95% CI: 1.26-1.76) and fewer FN (0.61; 95% CI: 0.37-0.99) but more FP (1.75; 95% CI: 1.19-2.58); a similar pattern was observed for other lower respiratory tract infections (LRTI). Pulmonary congestion was less often observed with ULDCT (0.45; 95% CI: 0.34-0.61), with fewer TP (0.50; 95% CI: 0.34-0.73), and FP (0.40; 95% CI: 0.24-0.65). PPVs were not significantly different. With ULDCT, radiologists were more often certain in diagnosing pneumonia (ULDCT 121/324, 37% vs CXR 48/208, 23%), LRTI (84/192, 44% vs 18/63, 29%), and no established disease (350/382, 92% vs 447/544, 82%).

Conclusion: Compared to CXR, ULDCT led to more TP but also more FP in detecting pneumonia and LRTI, while fewer TP and FP were found for pulmonary congestion. PPVs were comparable.

Key points: Question Is ultra-low dose CT (ULDCT) more accurate than chest X-ray (CXR) for identifying non-traumatic pulmonary diseases in patients presenting at the ED? Findings ULDCT detects more pulmonary infections in patients presenting at the ED with non-traumatic pulmonary complaints, while CXR detects more pulmonary congestion. Clinical relevance ULDCT is superior to CXR in detecting pneumonia and other LRTI in ED patients, while CXR is superior in detecting pulmonary congestion. ULDCT can be an alternative for CXR in a selected group of patients.

Objective: To conduct a meta-analysis assessing the diagnostic performance of the node reporting and data system (Node-RADS) for detecting lymph node (LN) invasion.

Method: We performed a systematic literature search of online scientific publication databases from inception up to July 31, 2024. We used the quality assessment of diagnostic accuracy studies-2 (QUADAS-2) to assess the study quality, and heterogeneity was determined by the Q-test and measured with I² statistics. We employed the hierarchic summary ROC (HSROC) model to estimate the summary sensitivity and specificity. Subgroup analyses were conducted according to the imaging modality and cutoff values.

Results: A total of 13 studies involving 1341 participants met the inclusion criteria. Pooled summary estimates of sensitivity, specificity, and area under the curve of HSROC were 0.79 (95% CI: 0.66-0.88), 0.86 (95% CI: 0.80-0.90), and 0.90 (95% CI: 0.87-0.92). Subgroup analysis showed that the pooled sensitivity and specificity for CT were 0.74 (95% CI: 0.63-0.83) and 0.84 (95% CI: 0.74-0.91), whereas for MRI were 0.84 (95% CI: 0.59-0.95) and 0.88 (95% CI: 0.81-0.93), respectively.

Conclusion: Node-RADS demonstrates the promising potential for the prediction of LN invasion, with high specificity but moderate sensitivity, particularly with optimal cutoff value ≥ 3. Indirect comparisons showed no significant difference between CT and MRI regarding overall diagnostic accuracy.

Key points: Question Since the Node-RADS has been proposed, a number of studies have assessed its diagnostic performance for evaluating LN invasion. Findings Node-RADS demonstrated high specificity but moderate sensitivity, and cutoff ≥ 3 is the optimal threshold; indirect comparison suggested no significant difference between CT and MRI. Clinical relevance This study synthesized currently available evidence on studies of utilizing Node-RADS for assessing LNI in patients with various cancers, providing valuable insights for radiologists for utilizing this new risk scoring system in clinical practice.

Chest imaging in children presents unique challenges due to varying requirements across age groups. For chest radiographs, achieving optimal images often involves careful positioning and immobilisation techniques. Antero-posterior projections are easier to obtain in younger children, while lateral decubitus radiographs are sometimes used when expiratory images are difficult to obtain and for free air exclusion. Chest CT protocols should be age-dependent to minimise radiation exposure and motion artefacts. MRI is primarily used in specialised centres to reduce radiation exposure, requiring specific expertise and sedation in younger children. Respiratory distress syndrome is a leading cause of morbidity in preterm neonates, diagnosed through characteristic radiographic findings and a history of prematurity. Bronchopulmonary dysplasia is the most common complication of extreme preterm birth and chronic oxygen therapy; imaging is used for predicting outcomes for the assessment of severe cases. Transient tachypnoea of the newborn and meconium aspiration syndrome are common in term infants, with specific imaging characteristics aiding in their differentiation. Congenital lung malformations present diagnostic and management challenges, with imaging playing a crucial role in diagnosis and surgical planning. Finally, imaging is essential in detecting complications from pneumonia in children, such as empyema and necrotic pneumonia, or in identifying foreign object aspiration. CLINICAL RELEVANCE STATEMENT: This review summarises current radiology practice of paediatric chest pathologies, aiding in the accurate diagnosis and management of neonatal and congenital pulmonary conditions and pneumonia complications, ultimately improving patient outcomes through precise imaging interpretation and targeted clinical intervention. KEY POINTS: Chest radiographs should be systematically assessed for pathology. Ensure accurate differential diagnosis of neonatal lung diseases by collecting information on gestational age, method of delivery, presenting symptoms, ventilation type, and fetal ultrasound findings. Radiographs and ultrasound are initial diagnostic tools for paediatric pulmonary disease; CT should be reserved for complex cases. Referral to paediatric hospital should be considered when the use of chest MRI is indicated.

Objectives: This study aimed to develop a multimodal radiopathomics model utilising preoperative ultrasound (US) and fine-needle aspiration cytology (FNAC) to predict large-number cervical lymph node metastasis (CLNM) in patients with clinically lymph node-negative (cN0) papillary thyroid carcinoma (PTC).

Materials and methods: This multicentre retrospective study included patients with PTC between October 2017 and June 2024 across seven institutions. Patients were categorised based on the presence or absence of large-number CLNM in training, validation, and external testing cohorts. A clinical model was developed based on the maximum diameter of thyroid nodules. Radiomics features were extracted from US images and pathomics features were extracted from FNAC images. Feature selection was performed using univariate analysis, correlation analysis, and least absolute shrinkage and selection operator regression. Six machine learning (ML) algorithms were employed to construct radiomics, pathomics, and radiopathomics models. Predictive performance was assessed using the area under the curve (AUC), and decision curve analysis (DCA).

Results: A total of 426 patients with PTC (41.65 ± 12.47 years; 124 men) were included in this study, with 213 (50%) exhibiting large-number CLNM. The multimodal radiopathomics model demonstrated excellent predictive capabilities with AUCs 0.921, 0.873, 0.903; accuracies (ACCs) 0.852, 0.800, 0.833; sensitivities (SENs) 0.876, 0.867, 0.857; specificities (SPEs) 0.829, 0.733, 0.810, for the training, validation, and testing cohorts, respectively. It significantly outperformed the clinical model (AUCs 0.730, 0.698, 0.630; ACCs 0.690, 0.656, 0.627; SENs 0.686, 0.378, 0.556; SPEs 0.695, 0.933, 0.698), the radiomics model (AUCs 0.819, 0.762, 0.783; ACCs 0.752, 0.722, 0.738; SENs 0.657, 0.844, 0.937; SPEs 0.848, 0.600, 0.540), and the pathomics model (AUCs 0.882, 0.786, 0.800; ACCs 0.829, 0.756, 0.786; SENs 0.819, 0.889, 0.857; SPEs 0.838, 0.633, 0.714).

Conclusion: The multimodal radiopathomics model demonstrated significant advantages in the preoperative prediction of large-number CLNM in patients with cN0 PTC.

Key points: Question Accurate preoperative prediction of large-number CLNM in PTC patients can guide treatment plans, but single-modality diagnostic performance remains limited. Findings The radiopathomics model utilising preoperative US and FNAC images effectively predicted large-number CLNM in both validation and testing cohorts, outperforming single predictive models. Clinical relevance Our study proposes a multimodal radiopathomics model based on preoperative US and FNAC images, which can effectively predict large-number CLNM in PTC preoperatively and guide clinicians in treatment planning.

Objectives: To analyze the CT imaging features of extranodal natural killer/T (NK/T)-cell lymphoma, nasal type (ENKTCL-NT) involving the gastrointestinal tract (GI), and to compare them with those of Crohn's disease (CD) and diffuse large B-cell lymphoma (DLBCL).

Materials and methods: Data were retrospectively collected from 17 patients diagnosed with GI ENKTCL-NT, 68 patients with CD, and 47 patients with DLBCL. The CT findings of ENKTCL-NT were analyzed and compared with those of CD and DLBCL. Data were analyzed using SPSS (version 25.0) and MedCalc (version 18.2.1). p < 0.05 was considered statistically significant.

Results: The 17 patients with ENKTCL-NT included 11 males (64.7%) and 6 females (35.3%) (mean age, 46.41 ± 4.12 years). The CT features of ENKTCL-NT included: circumferential symmetric thickening (100%), moderate thickening (70.6%), skip lesions (52.9%), contiguous lesion (47.1%), mucosal or layered enhancement (70.6%), moderate mural enhancement (64.7%) with non-enhanced regions (47.1%), absence of lymphadenopathy (76.5%), bowel perforation or fistula (17.6%), and peri-enteric blurred fat space (70.6%). The presence of circumferential symmetric thickening, moderate mural enhancement, and non-enhanced regions were more indicative of ENKTCL-NT than CD (17/17 vs. 17/68, 11/17 vs. 22/68, 8/17 vs. 0/68, p < 0.05). The presence of skip lesions, mucosal or layered enhancement, and absence of peri-enteric lymphadenopathy were more indicative of ENKTCL-NT than DLBCL (9/17 vs. 2/47, 12/17 vs. 1/37, 13/17 vs. 19/47, p < 0.05).

Conclusion: CT imaging features can provide useful information for the early diagnosis of ENKTCL-NT and effectively differentiate it from CD and DLBCL.

Key points: Question Extranodal natural killer/T-cell lymphoma, nasal type (ENKTCL-NT) involving the gastrointestinal tract (GI) is highly malignant but easily misdiagnosed by clinicians and endoscopic examination. Findings CT could provide useful information in the diagnosis of ENKTCL-NT involving GI and in differentiating it from Crohn's disease and diffuse large B-cell lymphoma. Clinical relevance This study will help improve the ability of radiologists to diagnose ENKTCL-NT involving GI, and a more predictive diagnosis will also alert clinicians to perform multiple deep endoscopic biopsies, which will contribute to the early diagnosis and treatment of ENKTCL-NT.

Objective: To investigate the predictive value of tumor iodine concentration obtained with dual-energy CT (DECT) for treatment response in patients treated with immune checkpoint inhibitors (ICI).

Materials and methods: Retrospective single-center study of consecutive metastatic melanoma and renal cell carcinoma (RCC) patients undergoing first-line ICI treatment. The iodine concentration measurement time points include prior to initiation of therapy (baseline [BL]), after initiation (follow-up [FU1]), and either time point nearest to 12 months or at time of progression (final follow-up [FFU]). Target lesion DECT-based whole-volume tumor normalized iodine concentration average (NICave) and size measurements were obtained. Reference standard was individual lesion FFU status categorized as responders or nonresponders per RECIST 1.1. Logistic regression model assessed NICave change and FU1 lesion response as predictors of FFU lesion outcome. Model's performance was summarized with AUC. Intraclass correlation coefficient (ICC) summarized inter-rater agreement of NICave.

Results: Forty-six patients were included (mean age 61 ± 11 years, 12 women; 16 melanoma). Sixty-four of 175 target lesions were confirmed nonresponders at FFU. In a multivariable model, lesion status at FU1 (odds ratio [OR]: 27.4, p < 0.001) and changes in NICave from BL to FU1 (OR: 2.42 per 1-SD increase, p = 0.019) were significant predictors of lesion status at FFU. The model's AUC was 0.86 (95% CI: 0.76-0.93). Inter-rater reliability of NICave was 0.98 (95% CI: 0.97-0.99).

Conclusions: Changes in iodine concentration from baseline to first follow-up improve identification of delayed responding metastatic melanoma and RCC lesions treated with immune checkpoint inhibitor, initially classified as nonresponders by size change.

Key points: Question How can pseudoprogression/delayed treatment response in metastatic renal cell carcinoma (RCC) and melanoma patients on first-line immune checkpoint inhibitors be accurately identified? Findings Combining iodine concentration change from Dual-energy CT (baseline to first follow-up) with RECIST-based lesion size change improved prediction of final lesion outcome. Clinical relevance DECT-based whole-volume tumor iodine concentration for target lesions is useful as a predictive imaging biomarker for distinguishing delayed response from true progression in patients with metastatic RCC and melanoma treated with first-line immune checkpoint inhibitors.

Objectives: Chest wall infiltration in primary lung cancer affects the surgical and therapeutic strategies. This study evaluates the efficacy of the chest wall vessel involvement in subpleural lung cancer (CWVI)　on ultra-high-resolution CT (UHR-CT) for detecting chest wall invasion.

Materials and methods: A retrospective analysis of lung cancer cases with confirmed pleural and chest wall invasion was conducted from November 2019 to April 2022. Seventy-seven patients (mean ± standard deviation age 70 ± 8 years, 64 males) who underwent preoperative contrast-enhanced UHR-CT were included. They were grouped into 51 non-chest wall infiltration (pl1 and pl2) and 26 chest wall infiltration (pl3). Clinical, histopathological, and UHR-CT findings were reviewed.

Results: Upper lobe tumors exhibited a higher chest wall invasion rate (p < 0.001). Rib destruction was evident in five patients with chest wall invasion but none with pleural invasion (p < 0.001). CWVI was present in 19 of 26 patients with chest wall invasion and 2 of 51 patients with pleural invasion (p < 0.001). The maximum tumor diameter (Dmax), arch distance which means the interface length between the primary tumor and the chest wall (Adist), and the ratio of Dmax to Adist were higher in chest wall invasion cases (all p < 0.001). After excluding patients with rib destruction, in multivariate logistic regression analysis, only CWVI was a significant predictor for chest wall invasion (odds ratio 29.22 (95% confidence interval 9.13-262.90), p < 0.001).

Conclusion: CWVI on UHR-CT can help diagnose lung cancer infiltrating the chest wall, offering a potential tool for clinical decision-making.

Key points: Question Chest wall infiltration in primary lung cancer has implications for the treatment plan, but diagnosis is often difficult with conventional CT. Findings Chest wall vessel involvement in subpleural lung cancer on ultra-high-resolution CT is a valuable predictor for diagnosing chest wall infiltration. Clinical relevance The delineation of chest wall vessels with contrast-enhanced ultra-high-resolution CT may improve the diagnosis of chest wall infiltration and allow accurate staging and optimal treatment options for subpleural primary lung cancer.