Abdominal Radiology最新文献

Purpose: To investigate the utility of intracellular enhancement (ICE) technique which suppresses signals from the extracellular space for the evaluation of hepatic function on gadoxetic acid-enhanced hepatobiliary-phase (HBP) images.

Methods: We subjected 67 patients with suspected neoplastic hepatic lesions to gadoxetic acid-enhanced HBP imaging with and without ICE [i-HBP, conventional-HBP (c-HBP)]. A radiologist calculated the liver/spleen contrast (LSC) [LSC = signal intensity (SI) of liver/SI of spleen]. Receiver-operating analysis was used to evaluate the diagnostic value of the LSC on i-HBP- (i-LSC) and c-HBP images (c-LSC) to differentiate between Child-Pugh classes A and B.

Results: Of the 67 patients, 57 were in Child-Pugh class A and 10 were in class B. For their differentiation, the area under the curve value of i-LSC was higher than of c-LSC (0.81 vs. 0.68).

Conclusions: ICE technique can improve the accuracy of estimating hepatic function on HBP images.

Esophageal motility disorders are commonly encountered in the outpatient setting during the evaluation of difficulty swallowing. They typically present with symptoms of dysphagia to solids or liquids, non-cardiac chest pain, or regurgitation. Practitioners rely on both invasive and non-invasive testing to evaluate these complaints, often utilizing endoscopy, fluoroscopic evaluations, and functional esophageal motility testing to characterize symptoms into formal motility disorders, when able. Many of these tests complement each other and more than one is often needed to fully characterize a patient's symptoms. For the past fifteen years, gastroenterologists have primarily used the Chicago Classification for defining esophageal motility disorders by esophageal manometry and this classification scheme has evolved into its 4th iteration. The following paper will review the initial approach to patients presenting with obstructive esophageal symptoms and provide a working knowledge of the Chicago Classification system and additional motility testing used commonly by gastroenterologists.

Cross-sectional interventional radiology procedures can be performed using a range of techniques with approaches varying across institutions. One area in which practices for these procedures may differ is in the use of moderate sedation. This perspective discusses the pros and cons of using moderate sedation for deep organ biopsies commonly experienced in radiology departments.

Objective: This study aimed to investigate the diagnostic performance of Follicle numbers measured on ultrasound (US), conventional magnetic resonance imaging (2D MRI), and three-dimensional (3D) MRI in patients with polycystic ovary syndrome (PCOS) and to compare the diagnostic efficacy of these imaging modalities.

Method: In this prospective study, 58 PCOS patients and 60 healthy women underwent US, conventional 2D MRI, and 3D MRI. Clinical laboratory tests and ovarian volume were compared between PCOS and control groups. Follicle numbers measured on US (FN-US), 2D MRI (FN-2D), and 3D MRI (FN-3D) using SegmentWithSAM were compared between PCOS and control groups using receiver operating characteristic (ROC) curve analysis and the DeLong test.

Results: Ovarian volume and follicle numbers were significantly higher in the PCOS group than in the control group. The diagnostic performance was found with FN-3D achieving the highest AUC of 0.94 (95% CI: 0.90-0.98), superior to that of US (0.80 [95% CI: 0.72-0.88]) and 2D MRI (0.90 [95% CI: 0.84-0.96]), respectively. Significant differences in the diagnostic efficacy of follicle counts were observed between US, conventional MRI, and 3D MRI, with 3D MRI showing superior results.

Conclusion: 3D MRI was superior to US and 2D MRI in diagnosing PCOS, with the ability to display small follicles.

Background and aim: Prior investigations of the natural history of abdominal aortic aneurysms (AAAs) have been constrained by small sample sizes or uneven assessments of aggregated data. Natural language processing (NLP) can significantly enhance the investigation and treatment of patients with AAAs by swiftly and effectively collecting imaging data from health records. This meta-analysis aimed to evaluate the efficacy of NLP techniques in reliably identifying the existence or absence of AAAs and measuring the maximal abdominal aortic diameter in extensive datasets of radiology study reports.

Method: The PubMed, Scopus, Web of Science, Embase, and Science Direct databases were searched until March 2024 to obtain pertinent papers. The RAYYAN intelligent tool for systematic reviews was utilized to screen the studies. The meta-analysis was conducted using STATA v18 software. Egger's test was employed to evaluate publication bias. The Newcastle Ottawa Scale was employed to assess the quality of the listed studies. A plot digitizer was employed to extract digital data.

Result: A total of 39,094 individuals with AAA were included in this analysis. Twenty-seven thousand three hundred twenty-six patients were male, and 11,383 were female. The mean age of the total participants was 73.1 ± 1.25 years. Analysis results for pooled estimation of performance variables such as: The sensitivity, specificity, precision, and accuracy of the implemented NLP model were analyzed as follows: 0.89(0.88-0.91), 0.88 (0.87-0.89), 0.92 (0.89-0.95), and 0.91 (0.89-0.93) respectively. The aneurysm diameter size difference reported in follow-up before and after NLP implementation in the included studies showed a 0.05 cm reduction in size, which was statistically significant.

Conclusion: NLP holds great potential for automating the detection of AAA size and presence in radiology reports, enhancing efficiency and scalability over manual review. However, challenges persist. Variability in report formats, terminology, and unstructured data can compromise accuracy. Additionally, NLP models rely on high-quality, annotated training datasets, which may be incomplete or unrepresentative. While NLP aids in identifying AAA-related data, human oversight is essential to ensure decisions are informed by the patient's broader clinical context. Ongoing algorithm refinement and seamless integration into clinical workflows are key to improving NLP's utility and reliability in this field.

Purpose: Metabolic dysfunction-associated steatotic liver disease (MASLD) and non-alcoholic fatty pancreatic disease (NAFPD) are metabolic diseases with rising incidence. Fatty infiltration may lead to dysfunction of the liver and pancreatic tissues. This study aims to quantify liver and pancreatic fat fractions and examine their correlation with disease severity in acute pancreatitis patients.

Methods: The severity of acute pancreatitis was assessed using the revised Atlanta classification (RAC), computed tomography severity index (CTSI), and modified CTSI (mCTSI). Proton density fat fraction (PDFF) levels of the liver and pancreas were measured via IDEAL MRI. Patients were categorized into biliary and non-biliary pancreatitis groups. Correlations between PDFF levels and the RAC, CTSI, and mCTSI scores were analyzed.

Results: A total of 127 patients were included, with MASLD present in 40.9% and NAFPD in 30%. Liver PDFF values were significantly higher in non-biliary pancreatitis (p = 0.040). Patients with MASLD exhibited higher CTSI and mCTSI scores (p = 0.009, p = 0.033, respectively). No significant differences were observed in severity scales between patients with and without NAFPD. Liver PDFF was positively correlated with CTSI and mCTSI scores in biliary pancreatitis. ROC analysis identified a liver PDFF > 3.9% (p = 0.002) and pancreatic corpus PDFF > 12.1% (0.028) as diagnostic markers for severe pancreatitis. In addition, a liver PDFF < 4.5% (p = 0.042) was an indicator for biliary pancreatitis.

Conclusion: MASLD is associated with increased severity in acute pancreatitis. IDEAL MRI-derived PDFF levels of the liver and pancreas show potential in predicting severe acute pancreatitis and distinguishing between biliary and non-biliary etiologies.

Purpose: Shear wave elastography (SWE) provides a means for adding information about the mechanical properties of tissues to a diagnostic ultrasound examination. It is important to understand the physics and methods by which the measurements are made to aid interpretation of the results as they relate to disease processes.

Methods: The components of how ultrasound is used to generate shear waves and make measurements of the induced motion are reviewed. The physics of shear wave propagation are briefly described for elastic and viscoelastic tissues. Additionally, shear wave propagation in homogeneous and inhomogeneous cases is addressed.

Results: SWE technology has been implemented by many clinical vendors with different capabilities. Various quality metrics are used to define valid measurements based on aspects of the shear wave signals or wave velocity estimates.

Conclusion: There are many uses for SWE in abdominal imaging, but it is important to understand how the measurements are performed to gauge their utility for diagnosis of different conditions. Continued efforts to make the technology robust in complex clinical situations are ongoing, but many applications actively benefit from added information about tissue mechanical properties for a more holistic view of the patient for diagnosis or assessment of prognosis and treatment management.

Background: Pneumatosis intestinalis on CT presents a diagnostic dilemma, because it could reflect bowel ischemia or benign finding.

Purpose: To determine radiological and clinical features that can predict bowel ischemia in patients with pneumatosis intestinalis on CT.

Materials and methods: Patients with "pneumatosis" in abdominal CT reports performed between 1/1/2002 and 12/31/2018 were retrospectively included. Pneumatosis intestinalis was confirmed by review of images. Radiological features of pneumatosis, laboratory data, clinical signs and symptoms were collected. Pathologic pneumatosis intestinalis (PPI) was defined as presence of ischemic (viable or dead) bowel on surgery or death during admission or within 30 days of discharge due to ischemia. Univariate statistical analysis was used to identify features associated with PPI, followed by multivariate logistic regression models.

Results: A total of 313 consecutive patients with pneumatosis intestinalis (162 (52%) men, median age 67 years, IQR 55-78 years) were included. Pathologic pneumatosis intestinalis was present in 114/313 (36%) patients. Presence of arterial or venous thrombosis, porto-mesenteric gas, fat stranding, and location in the small bowel were significantly associated with PPI. A combined clinical and radiological model, which included age, WBC, creatinine, abdominal distention, rebound or guarding, shock, presence of porto-mesenteric gas and fat stranding showed an AUC of 0.85 for prediction of PPI, higher than models using clinical (AUC = 0.80, p = 0.005) or radiological factors (AUC = 0.80, p < 0.0001) alone.

Conclusion: Improved prediction of pathological pneumatosis intestinalis can be achieved by a model incorporating both clinical and radiological features (AUC = 0.85)rather than by either clinical (AUC = 0.80) or radiological (AUC = 0.80) features alone.

Objectives: To develop and validate a lesion-based grading system using clinicopathological and MRI features for predicting positive surgical margin (PSM) following robotic-assisted laparoscopic prostatectomy (RALP) among prostate cancer (PCa) patients.

Methods: Consecutive MRI examinations of patients undergoing RALP for PCa were retrospectively collected from two medical institutions. Patients from center 1 undergoing RALP between January 2020 and December 2021 were included in the derivation cohort and those between January 2022 and December 2022 were allocated to the validation cohort. Patients from center 2 were assigned to the test cohort. PSM associated imaging and clinicopathological predictors were assessed. A grading system was developed through fixed effect logistic regression and classification and regression tree analysis. The area under the curve (AUC), sensitivity and specificity were calculated and compared by Delong test and McNemar test.

Results: A total 489 lesions from 396 patients were included and 82 (29.1%), 32 (35.6%) and 42 (35.9%) of lesions were observed PSM after RALP in the derivation, validation and test cohorts, respectively. The grading system comprised tumor morphology, tumor location, anatomical feature and clinical risk stratification. The grading system demonstrated good prediction performance for PSM in the derivation (AUC 0.82 [95% CI: 0.77, 0.86]), validation (AUC 0.76 [95% CI: 0.66, 0.85]) and test (AUC 0.81 [95% CI: 0.72, 0.88]) cohorts. When compared with Park's model (AUC: 0.73 [95% CI: 0.64, 0.81]) in the test cohort, our grading system demonstrated significantly higher AUC and specificity (P < 0.05).

Conclusion: The lesion-based grading system can assess the likelihood of PSM after RALP, assisting surgeons in minimizing the occurrence rate of PSM while optimizing functional preservation.