Abdominal Radiology最新文献

Objectives: Combining Computed Tomography (CT) intuitive anatomical features with Three-Dimensional (3D) CT multimodal radiomic imaging features to construct a model for assessing the aggressiveness of pancreatic neuroendocrine tumors (pNETs) prior to surgery.

Methods: This study involved 242 patients, randomly assigned to training (170) and validation (72) cohorts. Preoperative CT and 3D CT radiomic features were used to develop a model predicting pNETs aggressiveness. The aggressiveness of pNETs was characterized by a combination of factors including G3 grade, nodal involvement (N + status), presence of distant metastases, and/or recurrence of the disease.

Results: Three distinct predictive models were constructed to evaluate the aggressiveness of pNETs using CT features, 3D CT radiomic features, and their combination. The combined model demonstrated the greatest predictive accuracy and clinical applicability in both the training and validation sets (AUCs (95% CIs) = 0.93 (0.90-0.97) and 0.89 (0.79-0.98), respectively). Subsequently, a nomogram was developed using the features from the combined model, displaying strong alignment between actual observations and predictions as indicated by the calibration curves. Using a nomogram score of 86.06, patients were classified into high- and low-aggressiveness groups, with the high-aggressiveness group demonstrating poorer overall survival and shorter disease-free survival.

Conclusion: This study presents a combined model incorporating CT and 3D CT radiomic features, which accurately predicts the aggressiveness of PNETs preoperatively.

Background: Across multiple procedural specialties, female trainees tend to perform fewer procedures and receive less autonomy than their male counterparts. However, there is currently no data on procedure contribution levels for radiology trainees.

Objective: To evaluate whether there was a difference in the degree of reported participation in ultrasound-guided procedures between male and female trainees at our institution.

Methods: This retrospective study assessed for differences in the reported level of participation between male and female trainees in ultrasound (US) guided paracentesis and thoracentesis. We performed a radiology information system (RIS) search of US guided procedures performed on adult patients from 7/1/2018 to 2/29/2024. Trainee participation levels in the procedures were determined per available reports and classified into independently performed, assisted, or observed. We evaluated the differential reporting of procedure contributions for male and female trainees based on observed vs. expected frequencies, as well as the effect of the trainees' and supervising physicians' gender and experience level on these contributions.

Results: A total of 189 trainees (52 female, 137 male) and 58 supervising physicians (18 female and 40 male) were included. The study evaluated 4156 reports, which showed no difference in the percentage of independently completed procedures (females 80.9% vs. 81.9%, X² (1, N = 4156) = 0.494, p = 0.48) except when supervised by junior physicians less than 2 years out of training (females 81.0% vs. 86.5%, X² (1, N = 1908) = 8.19, p = 0.0042). However, female trainees were more likely than male trainees to report observing procedures (females 9.2% vs. 5.2%, X2 (1, N = 4156) = 21.1, p < 0.00001) rather than actively participating in procedures despite a similar training level; this difference was not observed when supervising physicians were females.

Conclusion: Female radiology trainees report a similar percentage of independently performed procedures but a lower rate of active participation than male trainees.

Purpose: We analyzed the additional value of systematic biopsy (SB) to MR-Ultrasound fusion biopsy (MRgFbx) for detection of clinically significant prostate cancer (csPCa), as increased sampling may cause increased morbidity.

Materials and methods: This retrospective study cohort was comprised of 1229 biopsy sessions between July 2016 and May 2020 in men who had a Prostate Imaging-Reporting and Data System (PI-RADSv2) category ≥ 3 lesion on 3 Tesla multiparametric MRI (3TmpMRI) and subsequent combined biopsy (CB; MRgFbx and SB) for suspected prostate cancer (PCa). Cancer detection rates (CDR) were calculated for CB, MRgFbx and SB in the study cohort and sub-cohorts stratified by biopsy history and PI-RADSv2 category. For 927 men with unilateral MR-visible lesions, SB CDR was additionally calculated for contralateral (SBc) and ipsilateral (SBi) subcohorts.

Results: On CB, the CDR for csPCa was 54.8% (673/1229). CDR for csPCa was significantly higher for MRgFbx (50.0%, CI 47.1-52.8%) compared to SB (35.3%, CI 32.6-38.1%) for all PI-RADSv2 ≥ 3 categories (p < .05). The MRgFbx CDR for PI-RADSv2 categories 3, 4, and 5 were 81.5%, 88.5%, and 95.6% respectively. For unilateral lesion cases, significantly more csPCa was detected in the SBi compared to the SBc subcohort (30.1% (279/927) vs. 10.4%, (96/927), p < 0.001). The combination of MRgFbx and SBi detected csPCa in 97.0% (480) of the 495 csPCa detected by CB.

Conclusion: MRgFbx had a higher CDR for csPCa than SB. While CB detected more csPCa than either method alone, in patients with a PI-RADSv2 category of 5, MRgFbx approximated the performance of CB. In unilateral lesion cases, SBc provided minimal added benefit.

Objective: This study evaluates the potential of dual-energy CT (DECT) for preoperative prediction of tumor budding (TB) and lymphovascular invasion (LVI) in colon cancer.

Methods: This prospective study enrolled 153 patients (mean age 61.33 years ± 0.88) with pathologically confirmed colon cancer. All participants underwent arterial and venous phase DECT scans within one week before surgery. Two radiologists independently analyzed the images, assessing tumor location, clinical N stage (cN stage), iodine concentration (IC), effective atomic number (Z-eff), and dual-energy index (DEI). The normalized iodine concentration (nIC) was obtained by comparing measured IC to the abdominal aortic IC. Logistic regression identified independent risk factors for high-grade TB and LVI positivity. The Akaike Information Criterion guided model selection, and the area under the curve (AUC) was calculated. Bootstrap validation with 1000 iterations was used for internal validation.

Results: Tumor location and cN stage were identified as independent risk factors for high-grade TB, and nIC_{A tumor} and cN stage for LVI positivity. The optimal model for predicting high-grade TB included tumor location, cN stage, and DEI_{V tumor}, with an AUC of 0.763 (sensitivity: 75.0%; specificity: 64.7%) and a mean AUC of 0.712. Similarly, the model for LVI positivity included nIC_{A tumor}, cN stage, and nIC_{A peripheral fat}, with an AUC of 0.811 (sensitivity: 71.7%; specificity: 76.6%) and a mean AUC of 0.814.

Conclusion: DECT could consistently quantify colon cancer characteristics, and DECT-based models performed well in the preoperative prediction of TB and LVI.

Objectives: Contrast enhanced ultrasound (CEUS) now joins the ranks of CT and MRI for noninvasive diagnosis of hepatocellular carcinoma (HCC). CEUS LI-RADS provides greater than 95% specificity for diagnosis within LR-5. Unlike CT/MRI, CEUS is nodule based. Currently, LI-RADS does not recommend CEUS of nodules occult or invisible on pre-contrast ultrasound except by experts. This study addresses our ability to find occult nodules using CEUS and to characterize them with CEUS LI-RADS.

Methods: 100 patients at risk for HCC, 81 with cirrhosis, with occult lesions were retrospectively identified from our archived patient logs. All patients had CEUS examination. Three specialized CEUS techniques (blindshot injection, portal venous (PVP) sweep of the liver, and on-top injection) are used to evaluate nodules.

Results: There were 114 occult lesions in 100 patients. The origin of 78(68%) lesions was an MRI (n = 69) or CT scan (n = 9) with an observation of abnormal enhancement, generally arterial phase hyperenhancement (APHE). All these patients had blindshot CEUS injection looking for a correlate with APHE. The remainder of occult lesions (n = 36)(32%) were first detected during CEUS, generally as washout foci on PVP sweeps or incidental APHE or washout nearby other targets. All washout areas had subsequent on-top injection to assess for APHE. Application of CEUS LI-RADS algorithm categorized 26 LR-5, 34 LR-4, and 5 LR-M. CEUS upgraded LI-RADS category of 24/50(48%) occult lesions reported on CT/MRI. 29(25%) occult lesions were offered treatment and from categories LR-5 and LR-M, 5 had biopsy confirmation and 15 were treated. From both sources, MR/CT and CEUS, there were 12 occult lesions scanned for treatment response, categorized as 7 LR-TR viable, 1 LR-TR nonviable, and 4 LR-TR equivocal on CEUS.

Conclusion: Our study shows we can find and characterize occult nodules using CEUS techniques and CEUS LI-RADS algorithm, with positive impact on clinical management.

Objectives: This study aimed to compare apparent diffusion coefficient (ADC) values derived from diffusion-weighted imaging (DWI) of different Borrmann types of advanced gastric cancer (AGC) and correlate these ADC values with Ki-67 expression and serum CEA levels in AGC.

Methods: A total of 84 patients with AGC who underwent DWI of the upper abdomen before tumor resection in our hospital between June 2014 and July 2018 were included in the present study. DWI was obtained with a single-shot echo planar imaging sequence in the axial plane (b values: 0, 100, 700 and 1000 s/mm²). Mean ADC values were calculated from tumor regions. Postoperatively, specimens were used to determine Borrmann type (1-4). Then, ADC values for AGCs categorized by Borrmann type were compared by one-way analysis of variance with Bonferroni correction for multiple comparisons. Subsequently, associations between ADC values and Ki-67 expression and serum CEA levels were evaluated by Spearman's correlation analysis.

Results: The mean ADC value for Borrmann type 3 AGC was significantly lower compared to the mean ADC value for Borrmann type 2 AGC (p < 0.01). There were significant negative correlations between ADC values and Ki-67 scores (r = -0.639, p < 0.001), and between ADC values and serum CEA levels (r = -0.575, p < 0.001).

Conclusions: DWI can help characterize Borrmann types of AGC. ADC values may reflect Ki-67 expression and serum CEA levels in patients with AGC, and have utility as a non-invasive indicator for evaluating the aggressiveness and prognosis of AGC.

Purpose: Mesenteric artery embolism (MAE) is a relatively uncommon abdominal surgical emergency, but it can lead to catastrophic clinical outcomes if the diagnosis is delayed. This study aims to build a prediction model of clinical-radiomics nomogram for early diagnosis of MAE based on non-contrast computed tomography (CT) and biomarkers.

Method: In this retrospective study, a total of 364 patients confirmed as MAE (n = 131) or non-MAE (n = 233) who were randomly divided into a training cohort (70%) and a validation cohort (30%). In the training cohort, the minimum redundancy maximum relevance (mRMR) and the least absolute shrinkage and selection operator (LASSO) algorithms were used to select optimal radiomics features from non-contrast CT images for calculating Radscore which was utilized to establish the radiomics model. Logistic regression analysis was performed to screen clinical factors, and then generate the clinical model. A predictive nomogram model was built using Radscore and the selected clinical risk factors, which was evaluated through the receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis (DCA).

Results: Thirteen radiomics features were chosen to calculate Radscore. Age, white blood cell (WBC) count, creatine kinase (CK) and D-dimer were determined as the independent clinical factors. The clinical-radiomics nomogram model showed the best performance in training cohort. The nomogram model was with higher area under curve (AUC) value of 0.93, compared to radiomics model with AUC value of 0.90 or clinical model with AUC value of 0.78 in the validation cohort. The calibration curve showed that nomogram model achieved a good fit in both cohorts (P  = 0.59 and 0.92, respectively). The DCA indicated that nomogram model was significantly favorable for clinical usefulness of MAE diagnosis.

Conclusions: The nomogram provides an effective tool for the early diagnosis of MAE, which may play a crucial role in shortening the time for therapeutic decision-making, thereby reducing the risk of intestinal necrosis and death.

Common pancreatobiliary epithelial malignancies such as pancreatic ductal adenocarcinoma, cholangiocarcinoma and gallbladder carcinoma have poor prognosis. A small but significant portion of these malignancies arise from mass-forming grossly and radiologically visible premalignant epithelial neoplasms in the pancreatobiliary tree. Several lesions, including a few recently described entities, fall under this category and predominantly include papillary epithelial lesions with or without mucin production. These include common lesions such as intraductal papillary mucinous lesions (IPMN) in pancreas and less common to rare lesions such intraductal papillary neoplasms of the bile ducts (IPNB), pancreatic and biliary intraductal oncocytic papillary neoplasms (IOPN) and intraductal tubulopapillary neoplasms (ITPN), intracholecystic neoplasms (ICN) in the gallbladder, intra-ampullary papillary-tubular neoplasms (IAPN) in the ampulla and mucinous cystic neoplasms in the pancreas, biliary tree and gallbladder. These lesions have an excellent prognosis before malignant transformation and even with malignant transformation, often fare better than the conventional malignant counterparts. These lesions have characteristic histologic, radiologic, and molecular characteristic features. Several of these neoplastic lesions are associated with field-effect phenomenon which means that in presence of even one of these lesions, the entire background ductal epithelium is at risk of developing synchronous or metachronous malignancies. Awareness of these lesions and their imaging appearances as well as utilization of relevant molecular diagnostics can help practicing radiologists and clinicians improve patient outcomes by detecting early and treating or surveilling such lesions before malignant transformation or before metastatic dissemination.

The barium swallow study is a fluoroscopic study which provides valuable insights into the motility, function and morphology of the pharynx, oesophagus, gastroesophageal junction, proximal stomach and duodenum. It has been observed that the skill of radiology doctors with barium swallow studies in adults has diminished. This reduced proficiency with barium swallow study is closely linked to and perpetuated by the heterogeneity of technique amongst radiologists. Factors pertaining to the individual radiologist, patient factors, healthcare factors, and the widespread use of alternative investigations have led to this increased variance in performing the barium swallow study. Despite this reduction in its usage, the study remains a valuable tool in the care of patients. We advocate for standardised guidelines to increase consistency and improve radiologist familiarity with this procedure.

Background: To develop and validate a clinical-radiomics model for preoperative prediction of lymphovascular invasion (LVI) in rectal cancer.

Methods: This retrospective study included data from 239 patients with pathologically confirmed rectal adenocarcinoma from two centers, all of whom underwent MRI examinations. Cases from the first center (n = 189) were randomly divided into a training set and an internal validation set at a 7:3 ratio, while cases from the second center (n = 50) constituted the external validation set. The clinical features and MRI imaging characteristics of the patients in the training set were analyzed. Univariate and multivariate logistic regression analyses were used to identify independent risk factors for LVI in rectal cancer, and these risk factors were then used to construct a clinical model. Regions of interest (ROIs) were delineated on T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) sequences for feature extraction. After feature reduction and selection, the most strongly correlated features were identified, and their respective regression coefficients were calculated to construct the radiomics model. Finally, a combined clinical-radiomics model was built using a weighted linear combination of features and was visualized as a nomogram. The predictive performance of each model was quantified using receiver operating characteristics (ROC) curves and the area under the curve (AUC) in both training and validation sets, with DeLong analysis being used to compare model performance. Decision curve analysis (DCA) was used to evaluate the clinical utility of each model in the validation sets.

Results: In the 239 patients, the combined model outperformed the clinical and radiomics models in predicting LVI in rectal cancer. The combined model showed excellent predictive performance in the training, internal validation, and external validation sets, with AUCs of 0.90 (0.88-0.97), 0.88 (0.78-0.99), and 0.88 (0.78-0.95), respectively. The sensitivity values were 75.9%, 68.8%, and 80.0%, respectively, and the specificity values were 90.3%, 92.7%, and 88.6%. DCA results indicated that the nomogram of the combined model had superior clinical utility compared with the clinical and radiomics models.

Conclusions: The clinical-radiomics nomogram serves as a valuable tool for non-invasive preoperative prediction of LVI status in patients with rectal cancer.