Insights into Imaging最新文献

Thoracic manifestations of inflammatory bowel disease (IBD) are rare, occurring in less than 1% of patients. Unlike most other extra-intestinal manifestations, they predominate in patients with ulcerative colitis rather than in Crohn's disease. In most patients, thoracic involvement follows the onset of IBD by several years. However, thoracic involvement may also occur synchronously or even precede the onset of digestive symptoms. The thoracic manifestations of IBD include airway involvement and parenchymal lung abnormalities. Airways are the most frequent anatomical site for thoracic involvement in IBD. Airway manifestations usually develop several years after the onset of intestinal manifestations, preferentially when the latter are stable or in remission. Airway manifestations include bronchial wall thickening, bronchiectasis, small airway disease, and tracheal wall thickening. Parenchymal lung abnormalities are less prevalent in IBD and include organizing pneumonia, necrobiotic nodules, noncaseating granulomatous nodules, drug-induced pneumonia, and rarely interstitial lung diseases. The differential diagnosis between organizing pneumonia, necrobiotic nodules, and noncaseating granulomatous nodules is difficult and usually requires histopathological analysis for a definite diagnosis. Radiologists play a key role in the detection of thoracic manifestations of Crohn's disease and ulcerative colitis and, therefore, need to be familiar with their imaging findings. This article aims to offer an overview of the imaging findings of thoracic manifestations in patients with Crohn's disease or ulcerative colitis. CRITICAL RELEVANCE STATEMENT: Thoracic manifestations of Crohn's disease and ulcerative colitis include tracheal involvement, bronchiectasis, small airway disease, and parenchymal lung abnormalities such as organizing pneumonia and necrobiotic nodules. These rare manifestations (< 1% of patients) more often affect patients with ulcerative colitis. KEY POINTS: Thoracic manifestations of inflammatory bowel disease are rare, occurring in less than 1% of patients. Thoracic manifestations are more frequent in patients with ulcerative colitis than Crohn's disease. Bronchial disease is the most frequent thoracic manifestation of Crohn's disease and ulcerative colitis.

Congenital cholesteatoma (CC) is a non-neoplastic lesion of keratin debris lined by epithelium found in the temporal bone. It is the lesser-known sibling of the acquired cholesteatoma and may be classified as congenital middle ear cholesteatoma and congenital petrous bone cholesteatoma. The incidence is rising, probably owing to increased recognition and advances in imaging modalities. Cone beam CT provides detailed anatomical information, highlighting quadrant location, ossicular involvement, and mastoid extension. MRI aids in lesion characterization and detection of complications. The classification systems for congenital middle ear and petrous bone cholesteatoma are helpful in the preoperative workup and have a role in predicting postoperative recurrence rates. Management almost invariably involves surgical intervention aimed at preserving middle and inner ear function. Follow-up of CC is mainly based on MRI together with otoscopic examination. Non-echo planar diffusion-weighted imaging, especially, has proven essential for detecting residual disease. This review article emphasizes the significance of imaging in the timely diagnosis and management of CCs. CLINICAL RELEVANCE STATEMENT: This article underscores the crucial role of imaging for prompt detection, preoperative assessment, and postoperative follow-up of CCs, a condition with rising incidence associated with potentially severe complications. KEY POINTS: Timely diagnosis of CCs is imperative for avoiding complications. Imaging is key in detection, preoperative evaluation, and postoperative management. Cone Beam CT and non-echo planar DWI represent state-of-the-art imaging techniques.

Objectives: Transjugular intrahepatic portosystemic shunt (TIPS) is a catheter-based, minimally invasive procedure to reduce portal hypertension. The aim of the study was to investigate dysfunction and mortality after TIPS and to identify factors associated with these events.

Methods: A retrospective analysis of 834 patients undergoing TIPS implantation in a single center from 1993-2018 was performed. Cumulative incidence curves were estimated, and frailty models were used to assess associations between potentially influential variables and time to dysfunction or death.

Results: 1-, 2-, and 5-year mortality rates were 20.9% (confidence interval (CI) 17.7-24.1), 22.5% (CI 19.1-25.8), and 25.0% (CI: 21.1-28.8), 1-year, 2-year, and 5-year dysfunction rates were 28.4% (CI 24.6-32.3), 38.9% (CI 34.5-43.3), and 52.4% (CI 47.2-57.6). The use of covered stents is a protective factor regarding TIPS dysfunction (hazard ratio (HR) 0.47, CI 0.33-0.68) but does not play a major role in survival (HR 0.95, CI 0.58-1.56). Risk factors for mortality are rather TIPS in an emergency setting (HR 2.78, CI 1.19-6.50), a previous TIPS dysfunction (HR 2.43, CI 1.28-4.62), and an increased Freiburg score (HR 1.45, CI 0.93-2.28).

Conclusion: The use of covered stents is an important protective factor regarding TIPS dysfunction. Whereas previous TIPS dysfunction, emergency TIPS implantation, and an elevated Freiburg score are associated with increased mortality. Awareness of risk factors could contribute to a better selection of patients who may benefit from a TIPS procedure and improve clinical follow-up with regard to early detection of thrombosis/stenosis.

Critical relevance statement: The use of covered stents reduces the risk of dysfunction after transjugular intrahepatic portosystemic shunt (TIPS). TIPS dysfunction, emergency TIPS placement, and a high Freiburg score are linked to higher mortality rates in TIPS patients.

Key points: The risk of dysfunction is higher for uncovered stents compared to covered stents. Transjugular intrahepatic portosystemic shunt dysfunction increases the risk of instantaneous death after the intervention. A higher Freiburg score increases the rate of death after the intervention. Transjugular intrahepatic portosystemic shunt implantations in emergency settings reduce survival rates.

Background: Preoperative evaluation of axillary lymph node status is crucial for the selection of both systemic and surgical treatment in early breast cancer. This study assessed the particular role of additional shear wave elastography (SWE) in axillary staging in patients undergoing initial breast cancer diagnostics.

Methods: One hundred patients undergoing axillary lymph node biopsy due to a sonographically suspicious axillary lymph node were prospectively evaluated with SWE using virtual touch tissue imaging quantification (VTIQ). Mean values of tissue stiffness for axillary tissue and lymph node tissue were measured prior to core-cut biopsy of the lymph node. All lymph nodes were clip-marked during the biopsy. Cut-off values to differentiate between malignant and benign lymph nodes were defined using Youden's index.

Results: Lymph nodes with evidence of malignant tumor cells in the final pathological examination showed a significantly higher velocity as measured by SWE, with a mean velocity of 3.48 ± 1.58 m/s compared to 2.33 ± 0.62 m/s of benign lymph nodes (p < 0.0001). The statistically optimal cutoff to differentiate between malignant and benign lymph nodes was 2.66 m/s with a sensitivity of 69.8% and a specificity of 87.5%.

Conclusions: Lymph node metastases assessed with SWE showed significantly higher elasticity values compared to benign lymph nodes. Thus, SWE provides an additional useful and quantifiable parameter for the sonographic assessment of suspicious axillary lymph nodes in the context of pre-therapeutic axillary staging in order to differentiate between benign and metastatic processes and support the guidance of definitive biopsy work-up.

Critical relevance statement: Shear-wave elastography provides an additional useful and quantifiable parameter for the assessment of suspicious axillary lymph nodes in the context of pre-therapeutic axillary staging in order to differentiate between benign and metastatic processes and support guiding the definitive biopsy work-up.

Key points: SWE is a quantifiable ultrasound parameter in breast cancer diagnosis. SWE shows a significantly higher velocity in malignant lymph nodes. SWE is useful in improving the sensitivity and specificity of axillary staging.

Objectives: To evaluate the performance and potential biases of deep-learning models in detecting chronic obstructive pulmonary disease (COPD) on chest CT scans across different ethnic groups, specifically non-Hispanic White (NHW) and African American (AA) populations.

Materials and methods: Inspiratory chest CT and clinical data from 7549 Genetic epidemiology of COPD individuals (mean age 62 years old, 56-69 interquartile range), including 5240 NHW and 2309 AA individuals, were retrospectively analyzed. Several factors influencing COPD binary classification performance on different ethnic populations were examined: (1) effects of training population: NHW-only, AA-only, balanced set (half NHW, half AA) and the entire set (NHW + AA all); (2) learning strategy: three supervised learning (SL) vs. three self-supervised learning (SSL) methods. Distribution shifts across ethnicity were further assessed for the top-performing methods.

Results: The learning strategy significantly influenced model performance, with SSL methods achieving higher performances compared to SL methods (p < 0.001), across all training configurations. Training on balanced datasets containing NHW and AA individuals resulted in improved model performance compared to population-specific datasets. Distribution shifts were found between ethnicities for the same health status, particularly when models were trained on nearest-neighbor contrastive SSL. Training on a balanced dataset resulted in fewer distribution shifts across ethnicity and health status, highlighting its efficacy in reducing biases.

Conclusion: Our findings demonstrate that utilizing SSL methods and training on large and balanced datasets can enhance COPD detection model performance and reduce biases across diverse ethnic populations. These findings emphasize the importance of equitable AI-driven healthcare solutions for COPD diagnosis.

Critical relevance statement: Self-supervised learning coupled with balanced datasets significantly improves COPD detection model performance, addressing biases across diverse ethnic populations and emphasizing the crucial role of equitable AI-driven healthcare solutions.

Key points: Self-supervised learning methods outperform supervised learning methods, showing higher AUC values (p < 0.001). Balanced datasets with non-Hispanic White and African American individuals improve model performance. Training on diverse datasets enhances COPD detection accuracy. Ethnically diverse datasets reduce bias in COPD detection models. SimCLR models mitigate biases in COPD detection across ethnicities.

Reader variability is intrinsic to radiologic oncology assessments, necessitating measures to enhance consistency and accuracy. RECIST 1.1 criteria play a crucial role in mitigating this variability by standardizing evaluations, aiming to establish an accepted "truth" confirmed by histology or patient survival. Clinical trials utilize Blind Independent Centralized Review (BICR) techniques to manage variability, employing double reads and adjudicators to address inter-observer discordance effectively. It is essential to dissect the root causes of variability in response assessments, with a specific focus on the factors influencing RECIST evaluations. We propose proactive measures for radiologists to address variability sources such as radiologist expertise, image quality, and accessibility of contextual information, which significantly impact interpretation and assessment precision. Adherence to standardization and RECIST guidelines is pivotal in diminishing variability and ensuring uniform results across studies. Variability factors, including lesion selection, new lesion appearance, and confirmation bias, can have profound implications on assessment accuracy and interpretation, underscoring the importance of identifying and addressing these factors. Delving into the causes of variability aids in enhancing the accuracy and consistency of response assessments in oncology, underscoring the role of standardized evaluation protocols and mitigating risk factors that contribute to variability. Access to contextual information is crucial. CRITICAL RELEVANCE STATEMENT: By understanding the causes of diagnosis variability, we can enhance the accuracy and consistency of response assessments in oncology, ultimately improving patient care and clinical outcomes. KEY POINTS: Baseline lesion selection and detection of new lesions play a major role in the occurrence of discordance. Image interpretation is influenced by contextual information, the lack of which can lead to diagnostic uncertainty. Radiologists must be trained in RECIST criteria to reduce errors and variability.

Objectives: To compare the prevalence of femoral head decentration (FHD) on different MR imaging planes in patients undergoing direct/indirect hip MR arthrography (MRA) with asymptomatic controls and to evaluate its association with osseous deformities.

Methods: IRB-approved retrospective single-center study of symptomatic hips undergoing direct or indirect hip MRA at 3 T. Asymptomatic participants underwent non-contrast hip MRI at 3 T. FHD was defined as a continuous fluid layer between the acetabulum and femoral head and assessed on axial, sagittal and radial images. The association of intra-articular/intra-venous contrast agents and the prevalence of FHD was evaluated. The association of FHD with osseous deformities and joint damage was assessed using multiple logistic regression analysis.

Results: Three-hundred ninety-four patients (447 hips, mean age 31 ± 9 years, 247 females) were included and compared to 43 asymptomatic controls (43 hips, mean age 31 ± 6 years, 26 females). FHD was most prevalent on radial images and more frequent in symptomatic hips (30% versus 2%, p < 0.001). FHD prevalence was not associated with the presence/absence of intra-articular contrast agents (30% versus 22%, OR = 1.5 (95% CI 0.9-2.5), p = 0.125). FHD was associated with hip dysplasia (OR = 6.1 (3.3-11.1), p < 0.001), excessive femoral torsion (OR = 3.0 (1.3-6.8), p = 0.010), and severe cartilage damage (OR = 3.6 (2.0-6.7), p < 0.001).

Conclusion: While rare in asymptomatic patients, femoral head decentration in symptomatic patients is associated with osseous deformities predisposing to hip instability, as well as with extensive cartilage damage.

Critical relevance statement: Decentration of the femoral head on radial MRA may be interpreted as a sign of hip instability in symptomatic hips without extensive cartilage defects. Its presence could unmask hip instability and yield promise in surgical decision-making.

Key points: The best method of identifying femoral head decentration is radial MRI. The presence/absence of intra-articular contrast is not associated with femoral head decentration. Femoral head decentration is associated with hip deformities predisposing to hip instability.

Objectives: Pulmonary neuroendocrine neoplasms (NENs) are the most frequent cause of ectopic adrenocorticotropic hormone syndrome (EAS); lung infection is common in EAS. An imaging finding of infection in EAS patients can mimic NENs. This retrospective study investigated EAS-associated pulmonary imaging indicators.

Methods: Forty-five pulmonary NENs and 27 tumor-like infections from 59 EAS patients (45 NEN and 14 infection patients) were included. Clinical manifestations, CT features, ¹⁸F-FDG, or ⁶⁸Ga-DOTATATE-PET/CT images and pathological results were collected.

Results: High-sensitivity C-reactive protein (p < 0.001) and expectoration occurrence (p = 0.04) were higher, and finger oxygen saturation (p = 0.01) was lower in the infection group than the NENs group. Higher-grade NENs were underrepresented in our cohort. Pulmonary NENs were solitary primary tumors, 80% of which were peripheral tumors. Overlying vessel sign and airway involvement were more frequent in the NENs group (p < 0.001). Multifocal (p = 0.001) and peripheral (p = 0.02) lesions, cavity (p < 0.001), spiculation (p = 0.01), pleural retraction (p < 0.001), connection to pulmonary veins (p = 0.02), and distal atelectasis or inflammatory exudation (p = 0.001) were more frequent in the infection group. The median CT value increment between the non-contrast and arterial phases was significantly higher in NENs lesions (p < 0.001). Receiver operating characteristic curve analysis indicated a moderate predictive ability at 48.3 HU of delta CT value (sensitivity, 95.0%; specificity, 54.1%).

Conclusion: Chest CT scans are valuable for localizing and characterizing pulmonary lesions in rare EAS, thereby enabling prompt differential diagnosis and treatment. CRITICAL RELEVANCE STATEMENT: Thin-slice CT images are valuable for the localization and identification of pulmonary ectopic adrenocorticotropic hormone syndrome lesions, leading to prompt differential diagnosis and effective treatment.

Key points: Lung tumor-like infections can mimic neuroendocrine neoplasms (NENs) in ectopic adrenocorticotropic hormone syndrome (EAS) patients. NENs are solitary lesions, whereas infections are multiple peripheral pseudotumors each with identifying imaging findings. Typical CT signs aid in localization and creating an appropriate differential diagnosis.

Purpose: To evaluate the diagnostic performance of image-based artificial intelligence (AI) studies in predicting muscle-invasive bladder cancer (MIBC). (2) To assess the reporting quality and methodological quality of these studies by Checklist for Artificial Intelligence in Medical Imaging (CLAIM), Radiomics Quality Score (RQS), and Prediction model Risk of Bias Assessment Tool (PROBAST).

Materials and methods: We searched Medline, Embase, Web of Science, and The Cochrane Library databases up to October 30, 2023. The eligible studies were evaluated using CLAIM, RQS, and PROBAST. Pooled sensitivity, specificity, and the diagnostic performances of these models for MIBC were also calculated.

Results: Twenty-one studies containing 4256 patients were included, of which 17 studies were employed for the quantitative statistical analysis. The CLAIM study adherence rate ranged from 52.5% to 75%, with a median of 64.1%. The RQS points of each study ranged from 2.78% to 50% points, with a median of 30.56% points. All models were rated as high overall ROB. The pooled area under the curve was 0.85 (95% confidence interval (CI) 0.81-0.88) for computed tomography, 0.92 (95% CI 0.89-0.94) for MRI, 0.89 (95% CI 0.86-0.92) for radiomics and 0.91 (95% CI 0.88-0.93) for deep learning, respectively.

Conclusion: Although AI-powered muscle-invasive bladder cancer-predictive models showed promising performance in the meta-analysis, the reporting quality and the methodological quality were generally low, with a high risk of bias.

Critical relevance statement: Artificial intelligence might improve the management of patients with bladder cancer. Multiple models for muscle-invasive bladder cancer prediction were developed. Quality assessment is needed to promote clinical application.

Key points: Image-based artificial intelligence models could aid in the identification of muscle-invasive bladder cancer. Current studies had low reporting quality, low methodological quality, and a high risk of bias. Future studies could focus on larger sample sizes and more transparent reporting of pathological evaluation, model explanation, and failure and sensitivity analyses.