Abdominal Radiology最新文献

Purpose: To compare same-day photon-counting detector CT (PCD-CT) to conventional energy-integrating detector CT (EID-CT) for detection of small renal stones (≤ 3 mm).

Methods: Patients undergoing clinical dual-energy EID-CT for known or suspected stone disease underwent same-day research PCD-CT. Patients with greater than 10 stones and no visible stones under 3 mm were excluded. Three radiologists selected the optimal reconstruction configuration for each CT modality and created the reference standard for renal stone presence. Two other radiologists, blinded to imaging modality, independently reviewed anonymized images to detect renal stones, rating confidence in potential stones using a Likert scale (1 = Definitely present, 2 = Probably present, 3 = Questionably present, 4 = Not seen). Sensitivity and false positive detections for PCD and EID-CT were calculated.

Results: Twenty-one patients underwent clinical EID-CT followed by same-day PCD-CT, with the reference standard identifying 121 renal stones (mean size 2.8 ± 2.6 mm). 0.4-mm PCD-CT images were more likely to display a stone as definitely present compared to 1- or 2-mm EID-CT images (p < 0.0001). Overall sensitivity for detection of all stones was greater at PCD-CT (0.75 vs. 0.55, p < 0.05). Pooled sensitivity of stones $\le$ 3 mm was also significantly higher at PCD-CT (0.67 vs. 0.41, p < 0.05), with false positive detections differing between readers and modalities (PCD-CT vs. EID-CT: R1-7 v. 5; R2 - 7 v. 1).

Conclusion: Sensitivity for renal stones was significantly higher using high spatial resolution PCD-CT vs. EID-CT, especially for stones 3 mm or less in size, which may be important for at-risk patient populations. Prospective evaluation in larger patient populations that will benefit from detection of small stones is warranted.

Purpose: T1-weighted signal intensity ratios (SIR) comparing pancreas to spleen (SIRps) or muscle (SIRpm) can semiquantitatively assess T1 signal change associated with pancreatitis. However, there is no standardized methodology for generating these ratios. We set out to determine the impact of MRI sequence as well as region of interest (ROI) location, shape, and size on T1 SIR.

Methods: Retrospective analysis of T1-weighted MR images from 118 patients acquired 2018-2023. A single observer placed ovoid ROIs in the pancreas body/tail and head/uncinate, spleen, and left erector spinae muscle and large irregular ROIs in the pancreas tail and spleen. ROIs were placed on images from two sequences: 3D radial 2 point mDIXON RF spoiled gradient recalled echo sequence (radial) and breath-hold 3D 2-point mDIXON RF spoiled gradient echo (BH). T1 SIR were calculated from mean signal intensity, and agreement was calculated with intraclass correlations coefficients (ICC) and Bland-Altman difference analyses.

Results: 118 participants, 57 (48%) female, with mean age 13.7 ± 5.6 years (48%) were included. Agreement was good for SIRps based on irregular versus round ROIs (radial: ICC = 0.90; BH: ICC = 0.91). Agreement was moderate for SIR based on sampling the pancreas body/tail versus head/uncinate (ICC = 0.67-0.76) and poor to moderate based on reference organ (muscle vs. spleen) (ICC = 0.41-0.61). Between sequences, agreement was moderate (ICC = 0.55-0.72, mean difference 0.04-0.09).

Conclusion: The size and shape of the ROI used to sample the pancreas does not meaningfully change T1 SIR but the location sampled, the reference organ used, and the MRI sequence used meaningfully change T1 SIR, potentially impacting disease diagnosis and staging.

Purpose: To explore the anatomical features of left iliac vein (LIV) in non-thrombotic venous leg ulcers (VLUs) and to identify the impact of these anatomical features on VLUs based on computed tomography venography (CTV).

Methods: This is a retrospective, single-center study of a database (2021-2023) of 431 patients with non-thrombotic chronic venous insufficiency. According to CEAP clinical (C) classifications, cases of C6 and C2 were included for analysis as case and control groups. Based on CTV data, variables that reflected the anatomical characteristics of LIV and lower lumbar degenerative changes were compared between the two groups. Multivariate logistic regression analysis was performed to evaluate impact of the anatomical features of LIV on VLUs.

Results: A total of 116 patients (group C6 (n = 33) and C2 (n = 83)) were included. Variables including anterior lumbar vertebral osteophytes (ALVO), minimum diameter of LIV, the number of sites of LIV stenosis, proportion of cases with percentage compression of LIV ≥ 75%, proportion of cases with triple or dual LIV stenosis showed significant difference between the two groups (all P ˂0.05). Logistic regression analysis showed ALVO [odds ratio (OR) = 3.852, P = 0.025], number of sites of LIV stenosis [OR = 2.654, P = 0.027] and minimum diameter of LIV [OR = 0.585, P = 0.010] were all significant for VLUs.

Conclusions: The factors of ALVO and number of sites of LIV stenosis were risk factors, whereas minimum diameter of LIV was a protective factor for VLUs. This provided a direction for preoperative planning of non-thrombotic LIV stenting.

Objectives: Liver transplant (LT) is an effective treatment for hepatocellular carcinoma (HCC) in appropriately selected patients. Locoregional therapy (LRT) is often performed to extend a patient's eligibility for LT. Imaging has a modest sensitivity of approximately 40-77% for detecting pathologically viable HCC in post-LRT patients. The impact on overall survival (OS) and disease-free survival (DFS) is unclear. We hypothesize that Liver Imaging Reporting & Data Systems Treatment Response (LI-RADS TR) category is equivalently correlated with long-term survival and overall disease-free progression when compared to explant pathology findings. We additionally hypothesize that neoadjuvant LRT can improve OS and DFS in LT patients initially within MC.

Methods: Patients found to have HCC on explant between January 2005 and December 2021 were included. A total of 167 patients were divided into treatment (any pre-LT LRT except for Y-90 therapy) and control (no pre-LT LRT) groups. Of the patients who received pre-LT LRT, imaging studies were reviewed by two abdominal radiologists using 2018 LI-RADS criteria. Statistical analysis was performed using Kaplan-Meier survival curves and Cox proportional hazard models to assess OS and DFS.

Results: No statistically significant difference in OS or DFS (p = 0.23 and p = 0.22 respectively) was initially found. Given significant difference in age between the groups (p < 0.0001), Cox proportional hazard models were used to adjust for age with statistical significance reached for better OS and DFS in the treatment group (p = 0.05 and p = 0.05 respectively). Contrary to our hypothesis, there was no difference between treatment response groups regarding overall survival or disease-free survival, presumably because of low number of HCC recurrences in our patient population (4%).

Conclusion: Despite not reaching statistical significance, LI-RADS TR categorization demonstrates a good interreader agreement (Kappa 0.6), helping radiologists feel comfortable that modest sensitivity of the LI-RADS TR treatment response category for detecting pathologically active malignancy does not confer a negative clinical outcome.

Objectives: This study aimed to investigate the accuracy of multiparametric magnetic resonance imaging (mpMRI), genetic urinary test (GUT), and prostate cancer prevention trial risk calculator version 2.0 (PCPTRC2) for the clinically significant prostate cancer (csPCa) diagnostic in biopsy-naïve patients.

Materials and methods: In a single center study between 2021 and 2024 participants underwent prostate mpMRI, GUT, and ultrasound (US) guided biopsy. The csPCa risk was calculated using PCPTRC2. After conducting a digital rectal examination (DRE), a GUT was performed. It incorporated the RNA levels of prostate cancer antigen 3 (PCA3) and transmembrane serine protease 2 (TMPRSS2) gene and ETS-related gene (ERG) fusion genes (T: E), along with the patient's age and PSA density. The McNemar test compared detection rates between modalities.

Results: 208 (mean age 62.9 years +/- 8.2) men were included prospectively. A positive GUT score was found in 67.8% and PIRADS ≥3 in 81.7% of all cases. The combination of GUT with mpMRI showed significantly higher sensitivity (99.1%) than GUT and mpMRI alone, 84.4% and 93.8%, respectively (p ≤ 0.05). Similarly, very high sensitivity (99.0%) was achieved by combining mpMRI with PCPTCR2. Nevertheless, mpMRI plus GUT combination exceeded mpMRI plus PCPTCR2 by allowing to save a higher fraction of unnecessary biopsies, 25% and 2.4%, respectively.

Conclusion: GUT and mpMRI combination would allow saving a substantial fraction of unnecessary biopsies with minimal risk of missing csPCa cases.

Purpose: To evaluate the measurement of main pancreatic duct (MPD) diameter on MRI for predicting MPD involvement in intraductal papillary mucinous neoplasms (IPMN).

Methods: This retrospective study included 595 patients with surgically confirmed IPMN who underwent preoperative MRI from 2015 to 2022. Three independent readers measured the maximum MPD diameter on two-dimensional axial and coronal T2-weighted imaging. Inter-plane and inter-reader agreements were assessed using the intraclass correlation coefficient (ICC). Multivariable logistic regression identified clinical and radiological factors associated with MPD involvement. Accuracy, sensitivity, and specificity of MPD diameter cutoffs, including the 5-mm threshold from the 2024 International Consensus Guidelines, were calculated.

Results: Of the 595 patients (mean age: 64.6 years ± 8.6, 394 men), 423 (71.1%) had IPMN with MPD involvement, whereas 172 (28.9%) did not have MPD involvement. The mean maximum MPD diameter was 7.9 ± 5.1 mm. Inter-plane agreement was excellent (ICC = 0.977-0.988), as was inter-reader agreement (ICC = 0.963). Only a large MPD diameter on MRI was independently associated with MPD involvement (odds ratio = 1.29 [95% confidence interval; 1.14-1.47], p <.01). Use of a maximum MPD diameter cutoff of ≥ 5 mm for MPD involvement yielded accuracy, sensitivity, and specificity of 76.0%, 79.2%, and 68.0%, respectively.

Conclusion: Despite excellent inter-plane and inter-reader agreement, the MRI-based prediction of MPD involvement in IPMN has limitations.

Purpose: To establish a prognostic model to estimate progression-free survival (PFS) probability in bladder cancer (BCa) patients undergoing partial cystectomy.

Material and methods: Consecutive patients who underwent partial cystectomy between August 2012 and April 2021 were enrolled. The primary endpoint was PFS during the follow-up. The following features were assessed: tumor location, amount, size, tortuous blood vessels around or within the lesions, perivesical fat stranding, stalk, computed tomography (CT) enhancement, calcification, cystic degeneration, CT reported lymph nodes status, and presence of hydronephrosis. Univariate Cox regression and LASSO regression, followed by backward stepwise multivariable Cox, were used to construct the nomogram.

Results: A total of 106 patients were enrolled. Gender, histology, tortuous blood vessels, and perivesical fat stranding were used to fit the nomogram. The overall Harrell's concordance index (C-index) was 0.752. The area under the receiver operator characteristic curves (AUC) at 1-year, 2-year and 3-year were 0.733, 0.789 and 0.833, respectively. The calibration curves showed remarkable consistency.

Conclusion: A nomogram model constructed based on the CT features and clinical risk factors is potentially feasible for predicting the PFS within 3 years after PC for BCa, which can assist in the choice of treatment and follow-up scheduling.

Background: To investigative potential clinicopathological characteristics and imaging-related risk factors of clinically significant prostate cancer (csPCa) undercategorized in patients with negative or equivocal MRI.

Methods: This retrospective study included 581 patients with pathologically confirmed csPCa (Gleason score ≥ 3 + 4), including 108 undercategorized csPCa and 473 detected csPCa. All patients underwent multiparametric MRI (mpMRI). The undercategorized csPCa was defined as a MRI result with PI-RADS ≤ 3. The clinicopathological characteristics and imaging-related factors were compared between the undercategorized group(Group A) (PI-RADS 1-3) and detected group (Group B) (PI-RADS 4-5).

Results: The age, total PSA levels, PSAD, free PSA, prostate imaging quality (PI-QUAL) scores, and Gleason scores were significantly lower in the Group A than Group B. The lesions were larger and involved in peripheral and transition zones in the Group B. A significant difference in the second reading opinion. Age (odds ratio [OR], 0.94), PSAD (OR, 0.09), and PI-QUAL scores (OR, 0.25) were significantly associated with the undercategorized csPCa. The rate of undercategorized csPCa with these three risk factors (age, PSAD, and PI-QUAL scores of < 71, < 0.355, and < 3, respectively) was 68.62%. The lack of zoomed-DWI resulted in lower PI-QUAL scores. Finally, the probability of undercategorized csPCa without zoomed DWI was 3.186 times higher than that with zoomed DWI when the PSAD ratio is lower than 0.355.

Conclusions: Low image quality, younger age, and lower PSAD contribute to csPCa undercategorized by mpMRI. Moreover, the use of zoomed DWI decreased undercategorized csPCa by improving PI-QUAL scores of MRI images.

Objectives: To develop a nomogram based on the radiomics features of tumour and perigastric adipose tissue adjacent to the tumor in dual-layer spectral detector computed tomography (DLCT) for lymph node metastasis (LNM) prediction in gastric cancer (GC).

Methods: A retrospective analysis was conducted on 175 patients with gastric adenocarcinoma. They were divided into training cohort (n = 125) and validation cohort (n = 50). The radiomics features from the tumour and perigastric fat based on DLCT spectral images were extracted to construct radiomics models for LNM prediction using Lasso-GLM method. Preoperative clinicopathological features, DLCT routine parameters, and the optimal radiomics models were analyzed to establish the clinical-DLCT model, clinical-DLCT-radiomics model and a nomogram. All models were internally validated using the Bootstrap method and evaluated using receiver operating characteristic (ROC) curve.

Results: The area under the ROC curve (AUC) values of optimal radiomics models based on tumour (Model 1) and perigastric fat (Model 2) were 0.923 and 0.822 in training cohort, 0.821 and 0.767 in validation cohort. The clinical-DLCT model based on Nct and ECV_ID demonstrated an AUC value of 0.728 in training cohort and 0.657 in validation cohort. The clinical-DLCT-radiomics model and the nomogram were established by incorporating Nct, ECV_ID and the linear predictive values of Models 1 and 2, exhibiting superior predictive efficacy with an AUC value of 0.935 in training cohort and 0.876 invalidation cohort.

Conclusions: The nomogram based on Nct, ECV_ID, and the radiomics features of tumour and perigastric fat in DLCT demonstrates potential for predicting LNM in GC. This approach may contribute to the development of treatment strategies and improve the clinical outcomes for GC patients.

Purpose: To explore the evaluation value of contrast enhanced ultrasound (CEUS) quantitative parameters in ischemic-type biliary lesions after liver transplantation to assist its early-diagnosis.

Methods: Patients who underwent liver transplantation and intravenous CEUS at Beijing Friendship Hospital, Capital Medical University from June 25, 2020 to December 28, 2022 and were diagnosed with Ischemic-type biliary lesions (ITBLs) by Magnetic Resonance Cholangiopancreatography (MRCP) or Endoscopic Retrograde Cholangiopancreatography (ERCP) or Percutaneous Transhepatic Cholangiography (PTC) were prospectively enrolled. SonoLiver software was used to quantitatively analyze the contrast images, transplanted livers with normal biliary tracts as the control group. SPSS 25.0 software was used to analyze the data.

Results: There was a total of 35 patients enrolled in the study, and 15 ITBLs and 30 normal biliary tract of transplanted livers, respectively. The dynamic vascular patterns (DVP) curve of the ITBLs group was negative wave, while the DVP curve of the normal biliary tract group was positive wave. Compared with the patients with normal biliary tract, the Maximum intensity (IMAX), Rise slope 50% (Rs50), Area under curve (AUC), Area under curve in Wash-in phase (WinAUC), Wash in Rate (WinR), Rise slope 10-90% (Rs1090), and Wash out Rate (WouR) of the ITBLs group were lower, while the Fall slope (Fs50) was higher. There was no significant difference in Rise time (RT), Time to Peak (TTP), Fall half time (FHT), Mean transit time (mTT), Fall time (FT), WioAUC ((WioAUC = WinAUC + WouAUC)), and Area under curve in Wash-out phase (WouAUC) between the two groups (P > 0.05). The ROC curve results showed that Fs50 > -2.64 was the cutoff value for predicting ITBLs, with an area under the curve of 0.816 (95%CI: 0.683-0.949), and a sensitivity and specificity of 0.846 and 0.607; Rs50 < 7.08, AUC < 39761.7050, WinR < 101.7 and WouR < 474.52 were the cutoff values ​​for predicting ITBLs, with areas under the curve of 0.853 (95%CI: 0.728-0.979), 0.911 (95%CI: 0.783-1.000), 0.756 (95%CI: 0.615-0.896) and 0.700 (95%CI: 0.536-0.864).

Conclusion: The quantitative parameters of CEUS imaging, such as IMAX, Rs50, AUC, WinAUC, WinR, Rs1090, WouR, and Fs50, are helpful in predicting ITBLs and improving the reproducibility of diagnosis. The threshold of these quantitative parameters will aid in the early diagnosis of ischemic-type biliary lesions after liver transplantation.