Abdominal Radiology最新文献

Background

Rectosigmoid endometriosis (RSE) presents with a diverse array of MRI findings that impact surgical planning. No standardized reporting and data system has been established for RSE.

Purpose

We propose a novel MRI scoring system designed to predict the likelihood of muscularis propria (MP) involvement in RSE, which would, in turn, influence surgical planning.

Materials and methods

The records of patients with bowel endometriosis treated surgically from May 2018 to June 2022 were retrieved. Surgery was classified as partial thickness discoid, full thickness discoid, or segmental resection. Each pre-treatment MRI was scored based on the mutual agreement of two abdominal radiologists (reference score). The MRI score was defined as (1) score 0: no evidence of RSE, (2) score 1: minimal tethering involving the serosal surface without MP involvement, (3) score 2: intermediate soft tissue thickening involving the rectosigmoid colon with indeterminate MP involvement, or (4) score 3: definite mushroom cap sign or definite MP involvement. In the reader study, two radiologists independently scored each exam. The area under the curve (AUC) was evaluated for predicting the need for segmental or full thickness discoid resection.

Results

The cohort consisted of 95 patients (median age: 36 years); 16, 14, 30, and 35 patients had MRI score 0, 1, 2, and 3, respectively. Patients with MRI scores 3 and 2 underwent partial thickness discoid (6% vs. 50%), full thickness discoid (6% vs. 17%), and segmental resection (89% vs. 33%), respectively. All patients with MRI scores 1 or 0 either underwent partial thickness discoid resection or did not undergo rectosigmoid surgery. The AUCs were 92.2%, 84.5% and 93.9% for MRI scores of the reference, reader 1, and 2, respectively.

Conclusion

Our MRI scoring system based on suspected depth of bowel invasion showed good diagnostic performance to predict the type of surgical intervention needed.

Purpose

This preliminary study investigated the effectiveness of conventional ultrasound (US) and Doppler US in evaluating rectosigmoid ratio (R/S) and blood flow dynamics in children with functional constipation (FC).

Methods

A total of 62 children aged 5–18 years were enrolled, including 32 patients with FC and 30 healthy controls. Rectal and sigmoid diameters, R/S ratio, and mesenteric blood flow parameters (PSV, PI, and RI) were assessed using standardized US and Doppler US techniques before and after a three-month treatment regimen including behavioral therapy and osmotic laxatives.

Results

The R/S ratio significantly improved after treatment in the FC group (p = 0.036), while no significant changes were observed in mesenteric blood flow velocities or resistive indices. Patients with R/S ≥ 1 had significantly lower celiac artery PSV values compared to those with R/S < 1 (p = 0.009).

Conclusions

While Doppler US did not yield substantial clinical benefits in assessing intestinal blood flow in FC, the non-invasive evaluation of the R/S ratio proved useful in monitoring treatment response. This preliminary study suggests that rectosigmoid measurements may aid in patient management and calls for further research with larger cohorts.

Purpose

To evaluate the outcomes of Transjugular Intrahepatic Portosystemic Shunt (TIPS) or variations of portosystemic shunt creation procedure in cancer patients with portal hypertension (PHTN).

Materials and methods

A single-center retrospective study was performed on cancer patients who underwent TIPS from September 2016 through June 2023. Forty consecutive cancer patients (mean age 61 years; 30 men, 10 women) were reviewed. For each patient, data regarding indication, the Child–Pugh (C-P) classification, international normalized ratio (INR), serum bilirubin level, creatinine level, and Model for End-Stage Liver Disease (MELD) score before the procedure and 1 month after the procedure were collected. Clinical efficacy was evaluated based on response, defined as the absence of significant variceal bleeding or clinically detectable ascites or hydrothorax following TIPS placement. Technical safety, complications, overall survival (OS), and incidence of hepatic encephalopathy (HE) were also assessed.

Results

One month after TIPS, 31 (77.5%) patients had clinical response, and 9 (22.5%) had no response. The technical success rate was 100%. There were no major procedure-related complications. The primary indications for shunt creation were ascites in 18 (45%), variceal bleeding (47.5%), and hydrothorax (7.5%). The 1-, 3-, and 6-month mortality rates were 10%, 25%, and 40%, respectively. Among the 40 patients included, 24 (60%) had cirrhosis, most commonly due to hepatitis C infection, hepatitis B infection, alcoholic liver disease, or NASH. The remaining 16 patients (40%) were non-cirrhotic. The median MELD score pre-TIPS was 11.5 (range 6.5–20.1). C-P score before intervention included 4 (10%) cases in class A, 33 (82.5%) in B, and 3 (7.5%) in C. The median OS was 15.4 months (range 0.03–61 months) and significantly differed by C-P score for each group (P < 0.001). No significant correlations existed between OS and the MELD score or pre-TIPS laboratory data. Fourteen patients developed HE (34%) after the procedure, and only one patient (2.5%) required shunt reduction. Responders had significantly longer OS, with a median of 26.5 months compared to 1.1 months in non-responders (P < 0.001, 95% CI: 2.14–13.19). Nine (22.5%) patients had a stent placed through the tumor. Twenty-six patients (65%) had an unchanged C-P class after the procedure, while C-P worsened in 6 (15%) and improved in 4 (10%).

Conclusion

These findings suggest that TIPS and its variations for the portosystemic shunt creation can be a safe and effective option for managing portal hypertension complications in carefully selected cancer patients with relatively preserved liver function. The study demonstrated high technical success and encouraging clinical response rates. Additionally, overall survival appeared longer in patients who responded to TIPS compared to non-responders.

Purpose

To investigate the prognostic value of apparent diffusion coefficient (ADC) metrics, MRI characteristics, and clinicopathological parameters in predicting non-muscle-invasive bladder urothelial carcinoma (UCB) recurrence, and to develop a novel multiparametric risk stratification framework.

Methods

This retrospective single-center study (n = 135) with histologically confirmed non-muscle-invasive UCB diagnosed between January 2015 and March 2023. ADC values, vesical imaging reporting and data system (VI-RADS) scores, and clinicopathological variables were analyzed with recurrence-free survival (RFS) as the primary endpoint. Prognostic determinants were identified using univariate and multivariate Cox proportional hazard regression models. An advanced risk stratification system was developed using independent predictors and validated against the European Association of Urology (EAU) risk classification using concordance index (C-index).

Results

Multivariate analysis identified three independent predictors: ADC values (HR = 0.104, 95% confidence interval (CI) 0.025–0.436), hemoglobin levels (HR = 0.463, 95% CI 0.223–0.960), and pathological grade (HR = 2.079, 95% CI 1.098–3.936). The combined model incorporating these parameters demonstrated moderate predictive accuracy (C-index = 0.724, 95% CI 0.655–0.794). Notably, VI-RADS scores showed no independent prognostic value. Risk stratification based on ADC (≤ 1343.22 × 10⁻⁶ mm²/s), hemoglobin (< 113.2 g/L), and pathological grade demonstrated superior discriminative capacity compared to EAU criteria (C-index: 0.667 vs. 0.605).

Conclusion

A multidimensional prognostic framework integrating quantitative ADC metrics, hemoglobin levels, and pathological grading significantly outperforms conventional EAU stratification in predicting non-muscle-invasive UCB recurrence, providing clinically actionable thresholds for personalized risk stratification and UCB management.

The umbilicus is a scar of the umbilical cord containing various embryonic remnants that can lead to postnatal diseases. It is the collection point for blood and lymphatic flow and other structures. Hence, various diseases and conditions can occur. In this review, we aimed to categorize umbilical diseases based on the embryonic remnants, including urachal remnants, omphalomesenteric duct anomalies, and complications of the umbilical arteries and veins. The urachus, formed from the allantois, can result in anomalies such as patent urachus and urachal cysts, with infections being the most common complication. Radiologists must note that urachal carcinoma is a rare complication presenting with characteristic imaging findings. The omphalomesenteric duct can lead to Meckel’s diverticulum, the most prevalent gastrointestinal anomaly. In addition, obliterated umbilical arteries and veins can cause various conditions, including hernias and abscesses. This review also summarizes the umbilical ring lesions, such as gastroschisis and omphalocele, and iatrogenic lesions associated with laparoscopic procedures and catheter placement. Imaging techniques such as ultrasound, computed tomography, and magnetic resonance imaging are crucial for diagnosing and managing these conditions. Understanding the embryological basis and imaging features of umbilical diseases is vital for timely diagnosis and treatment.

Graphical abstract

Objective

To assess the diagnostic performance of standardized qualitative assessment of hepatic steatosis on grayscale ultrasound.

Methods

This retrospective, single-center, multi-case, multi-reader study included 200 patients with ultrasound examinations of the liver. Three readers assessed hepatic steatosis based on a standardized system of 3 ultrasound features: presence of increased fine echoes, visualization of right hemidiaphragm, and visualization of portal triads, assigning a four-grade category (normal, mild, moderate, or severe). Magnetic resonance imaging proton density fat fraction (MRI-PDFF) was used as reference standard. Binary discrimination (normal vs. steatosis) was summarized with binary area under the curve (AUC), sensitivity, and specificity. Discrimination across four categories was performed with pairwise comparisons. Reader differences were tested with the Obuchowski-Rockette-Hillis model. Inter-reader agreement was calculated with Gwet’s agreement coefficient (AC).

Results

Of the 200 patients, 27% (54/200) had normal liver (MRI-PDFF < 5%), 35% (70/200) had mild steatosis (MRI-PDFF ≥ 5-17.4%), 15% (29/200) had moderate steatosis (MRI-PDFF > 17.4–22.1%), and 24% (47/200) had severe steatosis (MRI-PDFF > 22.1%). Median time interval between ultrasound and MRI exams was 4 days (IQR 1–28). Sensitivity, specific, and binary AUC for readers 1/2/3 were 90%/82%/94%, 65%/82%/54%, and 0.87/0.85/0.88 with no statistically significant difference between readers (p = 0.46). Four-class category analysis showed excellent performance of ultrasound to distinguish extreme categories (AUC > 0.95 for normal vs. severe). Inter-reader agreement was substantial (Gwet’s AC 0.63) for steatosis category assignment and moderate to substantial (Gwet’s AC 0.55–0.71) for ultrasound features.

Conclusion

Contrary to popular belief, qualitative ultrasound assessment of hepatic steatosis is accurate in detecting and grading steatosis when evaluation criteria are standardized.

The use of immune checkpoint inhibitors has increased in the field of oncology; however, various immune-related adverse events affecting multiple organs have been reported. Herein, we present a case of concurrent hepatitis, cholangitis, and pancreatitis as immune-related adverse events (irAE); a case of autoimmune disease due to oncologic immunotherapy. A man in his 80s who was undergoing pembrolizumab therapy for recurrent renal pelvic cancer presented to the emergency department with a loss of appetite. Laboratory tests revealed elevated levels of inflammatory markers and liver enzymes. Initial non-contrast computed tomography (CT) suggested cholecystitis and cholangitis, for which antibiotics were administered. However, because of poor improvement, contrast-enhanced dynamic CT and gadolinium-ethoxybenzyl-diethylenetriamine-pentaacetic acid-enhanced magnetic resonance imaging (MRI) were performed two weeks after visiting the emergency department to reassess the underlying cause. In these examinations, besides the bile dust wall thickening and edematous changes along Glisson’s sheath suggesting the cholangitis, inflammatory enlargement in pancreatic tail was also revealed. Considering these imaging findings suggesting the cholangitis and pancreatitis during pembrolizumab therapy, irAE was suspected as the cause of symptoms. A liver biopsy subsequently performed strongly indicated hepatitis and cholangitis as irAE. Based on these findings, concurrent hepatitis, cholangitis, and pancreatitis as irAE by pembrolizumab were diagnosed. Imaging findings of irAE cholangitis are similar to those of primary sclerosing cholangitis and IgG4-related cholangitis. Particularly in cases like this one, where pancreatitis is also present. However, if a history of immune checkpoint inhibitor use is known, it is possible to include irAE in the differential diagnosis, as observed in this case. Therefore, by keeping the use of immune checkpoint inhibitors in mind during imaging interpretation, imaging examinations could be a clue to suggest the possibility of irAE. Recognizing the imaging findings associated with irAEs and the existence of cases where irAE cholangitis and irAE pancreatitis coexist, it can aid earlier diagnosis of irAEs.

The rapid advancements in artificial intelligence (AI) carry the promise to reshape abdominal imaging by offering transformative solutions to challenges in disease detection, classification, and personalized care. AI applications, particularly those leveraging deep learning and radiomics, have demonstrated remarkable accuracy in detecting a wide range of abdominal conditions, including but not limited to diffuse liver parenchymal disease, focal liver lesions, pancreatic ductal adenocarcinoma (PDAC), renal tumors, and bowel pathologies. These models excel in the automation of tasks such as segmentation, classification, and prognostication across modalities like ultrasound, CT, and MRI, often surpassing traditional diagnostic methods. Despite these advancements, widespread adoption remains limited by challenges such as data heterogeneity, lack of multicenter validation, reliance on retrospective single-center studies, and the “black box” nature of many AI models, which hinder interpretability and clinician trust. The absence of standardized imaging protocols and reference gold standards further complicates integration into clinical workflows. To address these barriers, future directions emphasize collaborative multi-center efforts to generate diverse, standardized datasets, integration of explainable AI frameworks to existing picture archiving and communication systems, and the development of automated, end-to-end pipelines capable of processing multi-source data. Targeted clinical applications, such as early detection of PDAC, improved segmentation of renal tumors, and improved risk stratification in liver diseases, show potential to refine diagnostic accuracy and therapeutic planning. Ethical considerations, such as data privacy, regulatory compliance, and interdisciplinary collaboration, are essential for successful translation into clinical practice. AI’s transformative potential in abdominal imaging lies not only in complementing radiologists but also in fostering precision medicine by enabling faster, more accurate, and patient-centered care. Overcoming current limitations through innovation and collaboration will be pivotal in realizing AI’s full potential to improve patient outcomes and redefine the landscape of abdominal radiology.

Purpose

A critical limitation to deployment and utilization of Artificial Intelligence (AI) algorithms in radiology practice is the actual integration of algorithms directly into the clinical Picture Archiving and Communications Systems (PACS). Here, we sought to integrate an AI-based pipeline for prostate organ and intraprostatic lesion segmentation within a clinical PACS environment to enable point-of-care utilization under a prospective clinical trial scenario.

Methods

A previously trained, publicly available AI model for segmentation of intra-prostatic findings on multiparametric Magnetic Resonance Imaging (mpMRI) was converted into a containerized environment compatible with MONAI Deploy Express. An inference server and dedicated clinical PACS workflow were established within our institution for evaluation of real-time use of the AI algorithm. PACS-based deployment was prospectively evaluated in two phases: first, a consecutive cohort of patients undergoing diagnostic imaging at our institution and second, a consecutive cohort of patients undergoing biopsy based on mpMRI findings. The AI pipeline was executed from within the PACS environment by the radiologist. AI findings were imported into clinical biopsy planning software for target definition. Metrics analyzing deployment success, timing, and detection performance were recorded and summarized.

Results

In phase one, clinical PACS deployment was successfully executed in 57/58 cases and were obtained within one minute of activation (median 33 s [range 21–50 s]). Comparison with expert radiologist annotation demonstrated stable model performance compared to independent validation studies. In phase 2, 40/40 cases were successfully executed via PACS deployment and results were imported for biopsy targeting. Cancer detection rates for prostate cancer were 82.1% for ROI targets detected by both AI and radiologist, 47.8% in targets proposed by AI and accepted by radiologist, and 33.3% in targets identified by the radiologist alone.

Conclusions

Integration of novel AI algorithms requiring multi-parametric input into clinical PACS environment is feasible and model outputs can be used for downstream clinical tasks.

Gastrointestinal (GI) cancers are a leading cause of cancer-related mortality worldwide. Accurate identification of lymphatic spread is essential for staging, prognosis, and treatment planning. The first metastatic lymph nodes vary depending on the primary tumor site, representing the initial echelon of nodal involvement. This pictorial essay reviews the lymphatic drainage patterns of major gastrointestinal cancers—including esophageal, gastric, pancreatic, hepatobiliary, and colorectal tumors—highlighting key nodal stations commonly involved in metastatic spread emphasizing their diagnostic and clinical relevance. By integrating multimodality imaging findings, we highlight key lymph node groups involved in metastasis, discuss their anatomical significance, and illustrate their appearance on computed tomography (CT) and magnetic resonance imaging (MRI). Understanding these patterns is critical for optimizing oncologic management.