European Radiology最新文献

Objective: To retrospectively evaluate the long-term outcomes after percutaneous cryoablation of abdominal wall endometriosis (AWE).

Method: The Institutional Review Board approved this retrospective observational review of 40 consecutive patients, of a median age of 37 years (interquartile range [IQR] 32-40 years), presenting with a total of 52 symptomatic AWE nodules. All patients underwent cryoablation between January 2013 and May 2022 with a minimum follow-up period of 12 months. Outcomes were assessed using a visual analog scale (VAS) that measured pain, as well as by magnetic resonance imaging (MRI). The pain-free survival rates were derived using the Kaplan-Meier estimator. Adverse events were analyzed and graded using the classification system of the Cardiovascular and Interventional Radiological Society of Europe.

Results: The median follow-up time was 40.5 months (IQR 26.5-47.2 months). The median VAS score before cryoablation was 8 (IQR 7-9). Complete relief of symptoms was documented in 80% (32/40) of patients at 3 months after initial cryoablation and correlated with the absence of residual endometriosis nodules on MRI. The median pain-free survival rates were 89.2% [95% CI, 70.1-96.4%] at 36 months and 76.8% [95% CI, 55.3-83.8%] after 60 months. No patient or lesion characteristics were found to be prognostic of failure. No major adverse events or side effects were reported in long term.

Conclusion: Cryoablation safely and effectively afforded long-term pain relief for patients with AWE nodules.

Clinical relevance statement: AWE cryoablation was found to be safe and effective in the long-term.

Key points: • Cryoablation is highly effective with 80% of patients experiencing complete relief of AWE symptoms after a single procedure. • Cryoablation is safe without long-term adverse events or side effects. • The median pain-free survival rates are 89.2% at 36 months and 76.8% at 60 months.

Objectives: To assess the diagnostic performance of ultrafast magnetic resonance imaging (UF-DCE MRI) in differentiating benign from malignant breast lesions.

Materials and methods: A comprehensive search was conducted until September 1, 2023, in Medline, Embase, and Cochrane databases. Clinical studies evaluating the diagnostic performance of UF-DCE MRI in breast lesion stratification were screened and included in the meta-analysis. Pooled summary estimates for sensitivity, specificity, diagnostic odds ratio (DOR), and hierarchic summary operating characteristics (SROC) curves were pooled under the random-effects model. Publication bias and heterogeneity between studies were calculated.

Results: A final set of 16 studies analyzing 2090 lesions met the inclusion criteria and were incorporated into the meta-analysis. Using UF-DCE MRI kinetic parameters, the pooled sensitivity, specificity, DOR, and area under the curve (AUC) for differentiating benign from malignant breast lesions were 83% (95% CI 79-88%), 77% (95% CI 72-83%), 18.9 (95% CI 13.7-26.2), and 0.876 (95% CI 0.83-0.887), respectively. We found no significant difference in diagnostic accuracy between the two main UF-DCE MRI kinetic parameters, maximum slope (MS) and time to enhancement (TTE). DOR and SROC exhibited low heterogeneity across the included studies. No evidence of publication bias was identified (p = 0.585).

Conclusions: UF-DCE MRI as a stand-alone technique has high accuracy in discriminating benign from malignant breast lesions.

Clinical relevance statement: UF-DCE MRI has the potential to obtain kinetic information and stratify breast lesions accurately while decreasing scan times, which may offer significant benefit to patients.

Key points: • Ultrafast breast MRI is a novel technique which captures kinetic information with very high temporal resolution. • The kinetic parameters of ultrafast breast MRI demonstrate a high level of accuracy in distinguishing between benign and malignant breast lesions. • There is no significant difference in accuracy between maximum slope and time to enhancement kinetic parameters.

Background: Personalising management of primary oesophageal adenocarcinoma requires better risk stratification. Lack of independent validation of proposed imaging biomarkers has hampered clinical translation. We aimed to prospectively validate previously identified prognostic grey-level co-occurrence matrix (GLCM) CT features for 3-year overall survival.

Methods: Following ethical approval, clinical and contrast-enhanced CT data were acquired from participants from five institutions. Data from three institutions were used for training and two for testing. Survival classifiers were modelled on prespecified variables ('Clinical' model: age, clinical T-stage, clinical N-stage; 'ClinVol' model: clinical features + CT tumour volume; 'ClinRad' model: ClinVol features + GLCM_Correlation and GLCM_Contrast). To reflect current clinical practice, baseline stage was also modelled as a univariate predictor ('Stage'). Discrimination was assessed by area under the receiver operating curve (AUC) analysis; calibration by Brier scores; and clinical relevance by thresholding risk scores to achieve 90% sensitivity for 3-year mortality.

Results: A total of 162 participants were included (144 male; median 67 years [IQR 59, 72]; training, 95 participants; testing, 67 participants). Median survival was 998 days [IQR 486, 1594]. The ClinRad model yielded the greatest test discrimination (AUC, 0.68 [95% CI 0.54, 0.81]) that outperformed Stage (ΔAUC, 0.12 [95% CI 0.01, 0.23]; p = .04). The Clinical and ClinVol models yielded comparable test discrimination (AUC, 0.66 [95% CI 0.51, 0.80] vs. 0.65 [95% CI 0.50, 0.79]; p > .05). Test sensitivity of 90% was achieved by ClinRad and Stage models only.

Conclusions: Compared to Stage, multivariable models of prespecified clinical and radiomic variables yielded improved prediction of 3-year overall survival.

Clinical relevance statement: Previously identified radiomic features are prognostic but may not substantially improve risk stratification on their own.

Key points: • Better risk stratification is needed in primary oesophageal cancer to personalise management. • Previously identified CT features-GLCM_Correlation and GLCM_Contrast-contain incremental prognostic information to age and clinical stage. • Compared to staging, multivariable clinicoradiomic models improve discrimination of 3-year overall survival.

Objectives: To distinguish isocitrate dehydrogenase (IDH) genotypes and tumor subtypes of adult-type diffuse gliomas based on the fifth edition of the World Health Organization classification of central nervous system tumors (WHO CNS5) in 2021 using standard, high, and ultra-high b-value diffusion-weighted imaging (DWI).

Materials and methods: This prospective study enrolled 70 patients with adult-type diffuse gliomas who underwent multiple b-value DWI. Apparent diffusion coefficient (ADC) values including ADC_b500/b1000, ADC_b500/b2000, ADC_b500/b3000, ADC_b500/b4000, ADC_b500/b6000, ADC_b500/b8000, and ADC_b500/b10000 in tumor parenchyma (TP) and contralateral normal-appearing white matter (NAWM) were calculated. The ADC ratios of TP/NAWM were assessed for correlations with IDH genotypes, tumor subtypes, and Ki-67 status; diagnostic performances were compared.

Results: All ADCs were significantly higher in IDH mutant gliomas than in IDH wild-type gliomas (p < 0.01 for all); ADC_b500/b8000 had the highest area under the curve (AUC) of 0.866. All ADCs were significantly lower in glioblastoma than in astrocytoma (p < 0.01 for all). ADCs other than ADC_b500/b1000 were significantly lower in glioblastoma than in oligodendroglioma (p < 0.05 for all). ADC_b500/b8000 and ADC_b500/b10000 were significantly higher in oligodendroglioma than in astrocytoma (p = 0.034 and 0.023). The highest AUCs were 0.818 for ADC_b500/b6000 when distinguishing glioblastoma from astrocytoma, 0.979 for ADC_b500/b8000 and ADC_b500/b10000 when distinguishing glioblastoma from oligodendroglioma, and 0.773 for ADC_b500/b10000 when distinguishing astrocytoma from oligodendroglioma. Additionally, all ADCs were negatively correlated with Ki-67 status (p < 0.05 for all).

Conclusion: Ultra-high b-value DWI can reliably separate IDH genotypes and tumor subtypes of adult-type diffuse gliomas using WHO CNS5 criteria.

Clinical relevance statement: Ultra-high b-value diffusion-weighted imaging can accurately distinguish isocitrate dehydrogenase genotypes and tumor subtypes of adult-type diffuse gliomas, which may facilitate personalized treatment and prognostic assessment for patients with glioma.

Key points: • Ultra-high b-value diffusion-weighted imaging can accurately distinguish subtle differences in water diffusion among biological tissues. • Ultra-high b-value diffusion-weighted imaging can reliably separate isocitrate dehydrogenase genotypes and tumor subtypes of adult-type diffuse gliomas. • Compared with standard b-value diffusion-weighted imaging, high and ultra-high b-value diffusion-weighted imaging demonstrate better diagnostic performances.

Objectives: To predict tumor recurrence in patients who underwent surgical resection of ampullary adenocarcinoma using preoperative magnetic resonance (MR) imaging findings combined with clinical findings.

Methods: In this multicenter study, a total of 113 patients (mean age, 62.9 ± 9.8 years; 58 men and 55 women) with ampullary adenocarcinoma who underwent preoperative MR imaging and surgery with margin-negative resection between 2006 and 2017 were retrospectively included. The MR imaging findings were evaluated by two radiologists. Preoperative clinical findings were obtained. Cox proportional regression analyses were used to identify the independent prognostic factors for recurrence-free survival (RFS). A nomogram was created based on the multivariable analysis and was internally validated.

Results: Multivariable analysis revealed that presence of infiltrative tumor margin (hazard ratio [HR]: 2.18, p = 0.019), adjacent organ invasion (HR: 3.31, p = 0.006), adjacent vessel invasion (HR: 5.42, p = 0.041), peripancreatic lymph node enlargement (HR: 2.1, p = 0.019), and jaundice (HR: 1.93, p = 0.043) were significantly associated with worse RFS of ampullary adenocarcinoma after surgical resection. These MR imaging and clinical findings were used to construct a nomogram. On internal validation, the calibration plots showed excellent agreement between the predicted probabilities and the actual rates of tumor recurrence, with Harrell's c-index of 0.746.

Conclusions: Combination of preoperative MR imaging and clinical findings can be useful for predicting tumor recurrence after surgical resection of ampullary adenocarcinoma. Identifying these features before surgery may aid in better treatment planning and management of these patients.

Clinical relevance statement: A predictive nomogram using preoperative MR imaging and clinical findings can be useful in estimating the recurrence-free survival after surgical resection of ampullary adenocarcinoma.

Key points: • Presently, tumor size on imaging is the only non-invasive factor that correlates with recurrence-free survival from ampullary adenocarcinoma; other factors are obtained postoperatively. • Infiltrative tumor margin, adjacent organ invasion, adjacent vessel invasion, peripancreatic lymph node enlargement on MRI, and jaundice are significant predictors for recurrence. • A nomogram incorporating significant MR imaging and clinical findings showed good performance in predicting recurrence-free survival, which can help in treatment planning.

Objectives: To develop an algorithm to link undiagnosed patients to previous patient histories based on radiographs, and simultaneous classification of multiple bone tumours to enable early and specific diagnosis.

Materials and methods: For this retrospective study, data from 2000 to 2021 were curated from our database by two orthopaedic surgeons, a radiologist and a data scientist. Patients with complete clinical and pre-therapy radiographic data were eligible. To ensure feasibility, the ten most frequent primary tumour entities, confirmed histologically or by tumour board decision, were included. We implemented a ResNet and transformer model to establish baseline results. Our method extracts image features using deep learning and then clusters the k most similar images to the target image using a hash-based nearest-neighbour recommender approach that performs simultaneous classification by majority voting. The results were evaluated with precision-at-k, accuracy, precision and recall. Discrete parameters were described by incidence and percentage ratios. For continuous parameters, based on a normality test, respective statistical measures were calculated.

Results: Included were data from 809 patients (1792 radiographs; mean age 33.73 ± 18.65, range 3-89 years; 443 men), with Osteochondroma (28.31%) and Ewing sarcoma (1.11%) as the most and least common entities, respectively. The dataset was split into training (80%) and test subsets (20%). For k = 3, our model achieved the highest mean accuracy, precision and recall (92.86%, 92.86% and 34.08%), significantly outperforming state-of-the-art models (54.10%, 55.57%, 19.85% and 62.80%, 61.33%, 23.05%).

Conclusion: Our novel approach surpasses current models in tumour classification and links to past patient data, leveraging expert insights.

Clinical relevance statement: The proposed algorithm could serve as a vital support tool for clinicians and general practitioners with limited experience in bone tumour classification by identifying similar cases and classifying bone tumour entities.

Key points: • Addressed accurate bone tumour classification using radiographic features. • Model achieved 92.86%, 92.86% and 34.08% mean accuracy, precision and recall, respectively, significantly surpassing state-of-the-art models. • Enhanced diagnosis by integrating prior expert patient assessments.

Objective: To evaluate the efficacy, safety, and improvement of symptoms by ultrasound-guided microwave ablation (MWA) for patients with large benign thyroid nodules (BTNs).

Methods: Eighty-seven patients with 87 BTNs (≥ 4 cm) treated with MWA between April 2015 and March 2021 were enrolled in this retrospective multicenter study, with clinical and ultrasound examinations performed at the 1st, 3rd, 6th, and 12th months. A multivariable linear mixed effects model was employed to explore the alterations in volume and volume reduction ratio (VRR), as well as the potential factors associated with VRR.

Results: The mean age of the 87 patients was 45.69 ± 14.21 years (range 18-76 years), and the ratio of men to women was 1:4.8. The mean volumes were much decreased at the 12th month after ablation compared to the initial volumes (p < .001). The mean VRR was 76.09% at the 12th month. The technique efficacy (VRR > 50%) was 90.80% at the 12th month. A multivariate analysis revealed that VRR was related to the initial volume (p = .015), annular flow (p = .010), and nodule composition (p = .024). The mean symptomatic score decreased from 4.40 ± 0.28 to 0.26 ± 0.06 at the 12th month (p < .001). At the same time, the mean cosmetic score decreased from 3.22 ± 0.10 to 1.31 ± 0.08 (p < .001).

Conclusion: MWA could serve as a safe and effective therapy for large BTNs, significantly reducing the volume of BTNs and significantly improving compressive symptoms and appearance problems.

Clinical relevance statement: Microwave ablation could serve as a safe and effective therapy for large benign thyroid nodules, leading to significant volume reduction and satisfied symptom and cosmetic alleviation period.

Key points: • This multicenter study investigated the feasibility and safety of microwave ablation for large benign thyroid nodules. • After ablation, the nodule volume was significantly reduced, and patients' symptoms and appearance problems were significantly improved. • Microwave ablation is feasible for large benign thyroid nodules and has been a supplement treatment.

Objectives: Evaluate microcalcification detectability in digital breast tomosynthesis (DBT) and synthetic 2D mammography (SM) for different acquisition setups using a virtual imaging trial (VIT) approach.

Materials and methods: Medio-lateral oblique (MLO) DBT acquisitions on eight patients were performed at twice the automatic exposure controlled (AEC) dose. The noise was added to the projections to simulate a given dose trajectory. Virtual microcalcification models were added to a given projection set using an in-house VIT framework. Three setups were evaluated: (1) standard acquisition with 25 projections at AEC dose, (2) 25 projections with a convex dose distribution, and (3) sparse setup with 13 projections, every second one over the angular range. The total scan dose and angular range remained constant. DBT volume reconstruction and synthetic mammography image generation were performed using a Siemens prototype algorithm. Lesion detectability was assessed through a Jackknife-alternative free-response receiver operating characteristic (JAFROC) study with six observers.

Results: For DBT, the area under the curve (AUC) was 0.97 ± 0.01 for the standard, 0.95 ± 0.02 for the convex, and 0.89 ± 0.03 for the sparse setup. There was no significant difference between standard and convex dose distributions (p = 0.309). Sparse projections significantly reduced detectability (p = 0.001). Synthetic images had a higher AUC with the convex setup, though not significantly (p = 0.435). DBT required four times more reading time than synthetic mammography.

Discussion: A convex setup did not significantly improve detectability in DBT compared to the standard setup. Synthetic images exhibited a non-significant increase in detectability with the convex setup. Sparse setup significantly reduced detectability in both DBT and synthetic mammography.

Clinical relevance statement: This virtual imaging trial study allowed the design and efficient testing of different dose distribution trajectories with real mammography images, using a dose-neutral protocol.

Key points: • In DBT, a convex dose distribution did not increase the detectability of microcalcifications compared to the current standard setup but increased detectability for the SM images. • A sparse setup decreased microcalcification detectability in both DBT and SM images compared to the convex and current clinical setups. • Optimal microcalcification cluster detection in the system studied was achieved using either the standard or convex dose setting, with the default number of projections.