Journal of Computer Assisted Tomography最新文献

{"title":"Beyond Human Limits: The Promise and Pitfalls of Large Language Models in Radiology Research.","authors":"Chloe Reyes, Evie Nguyen, Lauren F Alexander, Rajesh Bhayana, Zoe Deahl, Ashish Khandelwal, Connor Mayes, Maria Zulfiqar, Nelly Tan","doi":"10.1097/RCT.0000000000001709","DOIUrl":"https://doi.org/10.1097/RCT.0000000000001709","url":null,"abstract":"<p><p>This review examines the applications and challenges of large language models (LLMs), like OpenAI's ChatGPT, in radiology research. ChatGPT can assist radiology researchers in generating new ideas, finding and summarizing research papers, designing studies, analyzing data, and facilitating manuscript writing. LLMs are powerful tools with numerous applications in radiology research. However, users should be mindful of potential pitfalls, such as producing incorrect or biased outputs and inconsistent responses, along with ethical and privacy concerns. We discuss approaches to optimize models and address these issues, including prompting techniques like chain-of-thought prompting, retrieval-augmented generation, and fine-tuning. For researchers, prompt engineering can be particularly effective. This review seeks to demonstrate how researchers can utilize ChatGPT for radiology research while offering strategies to mitigate associated risks. We aim to help researchers harness these potent tools to safely boost their productivity.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143968765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pilot Study Examining the Use of DCE MRI With Pharmacokinetic Analysis to Evaluate Hypoxia in Prostate Cancer.","authors":"Eduardo Miguel Febronio, André de Freitas Secaf, Fernando Chahud, Jorge Elias, Rodolfo B Reis, Valdair F Muglia","doi":"10.1097/RCT.0000000000001707","DOIUrl":"https://doi.org/10.1097/RCT.0000000000001707","url":null,"abstract":"<p><strong>Purpose: </strong>This study aimed to investigate the association between tumor hypoxia, assessed through anti-HIF (hypoxia-inducible factor) staining, and aggressiveness in prostate cancer using a pharmacokinetic model, particularly those derived from the Tofts model, in predicting tumor aggressiveness.</p><p><strong>Material and methods: </strong>From January 2019 to April 2021, we conducted a retrospective search of patients with confirmed prostate cancer and a previous magnetic resonance imaging (MRI) examination. After exclusions, a total of 57 consecutive patients were enrolled. Patient data, including demographic, laboratory, and pathologic variables, were collected. MRI acquisition followed PI-RADS guidelines, encompassing T2-weighted, diffusion-weighted imaging, and dynamic contrast-enhanced imaging. An experienced abdominal radiologist conducted both morphologic and quantitative MRI analyses, evaluating parameters such as lesion size, apparent diffusion coefficient values, and the Tofts pharmacokinetics (TF) model. The histopathologic analysis included the International Society of Uropathology (ISUP) score and hypoxia marker immunohistochemistry.</p><p><strong>Results: </strong>There were no significant demographic and imaging differences between hypoxic and nonhypoxic tumors, except for elevated prostate-specific antigen levels in the latter and decreased normalized apparent diffusion coefficient in the former. Morphologic assessments revealed larger lesions in the hypoxia group. While Ktrans showed a positive association with hypoxia, it did not independently predict high-risk lesions.</p><p><strong>Conclusions: </strong>Our results suggest that pharmacokinetic analysis by the Tofts model was associated with tumors with hypoxia. However, this parameter was not an independent predictor of more aggressive tumors. Further studies, with a larger number of patients, multi-institutional and prospective, are needed to verify this possible association.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143995910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Radiomics Analysis of Apparent Diffusion Coefficient Maps of Parotid Gland to Diagnose Morphologically Normal Sjogren Syndrome.","authors":"Chen Chu, Jie Meng, Huayong Zhang, Qianqian Feng, Shengnan Zhao, Weibo Chen, Jian He, Zhengyang Zhou","doi":"10.1097/RCT.0000000000001754","DOIUrl":"https://doi.org/10.1097/RCT.0000000000001754","url":null,"abstract":"<p><strong>Objective: </strong>This study investigated novel radiomic features derived from apparent diffusion coefficient (ADC) maps for diagnosing Sjögren syndrome (SS) in patients without visible magnetic resonance morphologic changes.</p><p><strong>Materials and methods: </strong>This study prospectively analyzed 119 consecutive patients with SS and 95 healthy volunteers using 3.0 T magnetic resonance imaging, including diffusion-weighted imaging with b values of 0 and 1000 s/mm2. Regions of interest (ROIs) were manually delineated along the margins of the largest parotid gland slice on ADC maps, from which 838 quantitative features were automatically extracted. Based on the intraclass correlation coefficient and absolute correlation coefficient, 45 radiomic parameters were selected for analysis. The differentiation between patients with SS and healthy controls was evaluated using univariate analysis and receiver operating characteristic analysis. Multiple radiomic features were integrated using binary logistic regression analysis. Through machine learning algorithms, 4 predictive models were developed, and each was thoroughly evaluated for predictive performance. The Shapley Additive exPlanations (SHAP) approach was employed to elucidate the predictive factors influencing the model.</p><p><strong>Results: </strong>Twenty-two radiomic parameters demonstrated significant differences between SS and control groups. The AUCs were 0.681 ± 0.100 (0.559~0.878). The optimal diagnostic combination for SS consisted of 6 parameters: 0.975Quantile, 180dr_D(4)_Cluster Prominence, 225dr_D(7)_Entropy, 315dr_D(7)_Entropy, Compactness2, and Max3D Diameter, achieving an AUC of 0.956. The SVM, GBM, and XGBoost models were effectively distinguished SS from healthy controls. Among all the parameters, Max3DDiameter demonstrated the strongest predictive power in the model.</p><p><strong>Conclusions: </strong>Radiomic features derived from ADC maps demonstrate significant potential in facilitating the early diagnosis of SS.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144023722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of Computed Tomography/Magnetic Resonance Imaging Characteristics of Acute Pancreatitis Between Cholecystectomy and Non-cholecystectomy Patients.","authors":"Zi Sheng Zhao, Di Tao, Jun Hui Chen, Xing Hui Li, Yi Fan Ji, Xiao Ming Zhang","doi":"10.1097/RCT.0000000000001760","DOIUrl":"https://doi.org/10.1097/RCT.0000000000001760","url":null,"abstract":"<p><strong>Objective: </strong>This study aimed to compare computed tomography (CT)/magnetic resonance imaging (MRI) characteristics of acute pancreatitis (AP) between patients with cholecystectomy and non-cholecystectomy and to validate the effect of prior cholecystectomy on the severity of subsequent pancreatitis.</p><p><strong>Methods: </strong>This retrospective study included 384 inpatients with AP at our hospital from January 1, 2020 to December 31, 2023. Based on their history of cholecystectomy, the patients were split into cholecystectomy and non-cholecystectomy groups. propensity score matching was applied, considering age and sex, in a 1:3 ratio. Demographic, clinical, laboratory, and CT/MRI parameters of each group were analyzed.</p><p><strong>Results: </strong>There were 200 (52.1%) males and 184 (47.9%) females, with a mean age of 53.55 ± 13.86 years (range: 18-98 y). Ninety-six patients were in the cholecystectomy group that had previously undergone cholecystectomy, and 288 in the non-cholecystectomy group. Creatinine and C-reactive protein levels were lower in the patients with cholecystectomy than in patients with non-cholecystectomy (P1 = 0.001, P2 = 0.049). In the prevalence of biliary pancreatitis, the cholecystectomy patients are 27.1%, whereas the non-cholecystectomy patients are 45.8% (P = 0.005). The non-cholecystectomy patients had a significantly higher mean CT/MRI severity index score (3.57 ± 1.72 points) than the cholecystectomy group (3.00 ± 1.58 points; P < 0.001). Regarding local complications, In the groups that underwent cholecystectomy and those that did not, the prevalence of acute peripancreatic fluid collection was 40.4% and 21.9%, respectively. (P < 0.001).</p><p><strong>Conclusions: </strong>AP following cholecystectomy exhibits unique imaging characteristics. Cholecystectomy reduces the severity and acute peripancreatic fluid collection rate of subsequent pancreatitis on CT/MRI.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144026944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CT Evaluation of Labyrinth Structures in Patients With Incomplete Partition Type II Anomaly.","authors":"Ipek Sel, Abdullah Soydan Mahmutoglu, Yesim Karagoz, Direnc Ozlem Aksoy, Ece Ates Kus","doi":"10.1097/RCT.0000000000001758","DOIUrl":"https://doi.org/10.1097/RCT.0000000000001758","url":null,"abstract":"<p><strong>Objective: </strong>Incomplete partition type II (IP-II) is one of the most common inner ear malformations that necessitates cochlear implantation. It is characterized by a cystic cochlear apex resulting from the coalescence of middle and apical turns due to modiolar hypoplasia and distal interscalar septal defect. Radiologic diagnosis of IP-II anomaly could be difficult with equivocal changes in tiny labyrinthine structures, especially with inexperienced observers. In our study, we aimed to determine pertinent quantitative radioanatomical measurements of inner ear structures (lateral interscalar notch angle, lateral interscalar notch depth, and lateral height) that may contribute to the diagnosis of IP-II anomaly using temporal bone high-resolution computed tomography (HRCT).</p><p><strong>Methods: </strong>Our study was a retrospective case-control study approved by the institutional review board. We retrospectively reviewed temporal bone HRCT examinations for the preoperative assessment of cochlear implantation of patients with sensorineural hearing loss (SNHL), using the diagnosis code of IP-II anomaly. Patients with SNHL and a radiologic diagnosis of IP-II anomaly according to the Sennaroglu classification were recruited. Thirty-four SNHL patients with IP-II anomaly (66 ears) and 24 patients without SNHL (48 ears) who underwent temporal CT imaging for inflammatory conditions or trauma not involving labyrinthine structures were included in the study. The lateral interscalar notch angle, lateral interscalar notch depth, and lateral height were independently measured by 2 observers (a senior head and neck radiologist and a novice radiologist). The parameters measured in patient and control groups were compared using the Mann-Whitney U test, and interobserver reliability was calculated.</p><p><strong>Results: </strong>Lateral interscalar notch angle and lateral height values were found to be significantly larger, while lateral interscalar notch depth value was significantly smaller in the IP-II group (P<0.05). The agreement between the observers in all measurements, evaluated separately in IP-II and control groups, was excellent (P<0.05). The cutoff values for determining the IP-II anomaly were found to be consistent between the 2 observers, with high sensitivity and specificity.</p><p><strong>Conclusions: </strong>CT measurements of inner ear structures in SNHL could help to diagnose IP-II anomalies, especially in patients with equivocal audiological and radiologic findings. This study validates CT measurements in the evaluation of IP-II anomaly conducted by histologic specimens and MRI in previous studies. Lateral cochlear measurements with an angle of >130 degrees, a depth of ≤0.35 mm, and a height of >3.15 mm could support the diagnosis of the IP-II anomaly. These measurements are also reproducible.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143968240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Photon-counting CT for Chest Imaging-What Have We Learned So Far?","authors":"Fides R Schwartz","doi":"10.1097/RCT.0000000000001756","DOIUrl":"https://doi.org/10.1097/RCT.0000000000001756","url":null,"abstract":"<p><p>CT imaging has advanced significantly, with dual-energy CT (DECT) marking a milestone by using 2 energy spectra for enhanced tissue characterization. The latest innovation is photon-counting detectors (PCD), which offer superior spatial resolution, contrast-to-noise ratio (CNR), and potential for reduced radiation dose compared with traditional energy-integrating detectors (EID). Photon-counting CT (PCD-CT), which directly counts individual photons using semiconductors, has important implications for chest imaging, especially for complex disease processes that benefit from imaging at higher spatial resolution. PCD-CT achieves improved spatial resolution by eliminating the blurring effects associated with EID scintillators. Enhanced CNR is achieved through energy discrimination and selective use of photon energies, which also helps to minimize electronic noise. PCD-CT facilitates significant radiation dose reduction, particularly valuable for patients who receive regular follow-ups, like in lung cancer screening. In addition, PCD-CT provides spectral capabilities in every scan, unlike DECT, which requires preselecting a specific spectral scan mode. In chest imaging, PCD-CT shows promise in detecting and definitively characterizing infectious diseases, interstitial lung disease, malignancies, and vascular conditions at low radiation doses, offering higher diagnostic accuracy and patient safety. Despite these advancements, challenges remain in optimizing spectral imaging and integrating PCD-CT into routine clinical workflows, necessitating ongoing research and development.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144007376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MRI Radiomics-Based Diagnosis of Knee Meniscal Injury.","authors":"Jing Liao, Ke Yu","doi":"10.1097/RCT.0000000000001759","DOIUrl":"https://doi.org/10.1097/RCT.0000000000001759","url":null,"abstract":"<p><strong>Objective: </strong>This study aims to explore a grading diagnostic method for the binary classification of meniscal tears based on magnetic resonance imaging radiomics. We hypothesize that a radiomics model can accurately grade meniscal injuries in the knee joint. By extracting T2-weighted imaging features, a radiomics model was developed to distinguish meniscal tears from nontear abnormalities.</p><p><strong>Materials and methods: </strong>This retrospective study included imaging data from 100 patients at our institution between May 2022 and May 2024. The study subjects were patients with knee pain or functional impairment, excluding those with severe osteoarthritis, infections, meniscal cysts, or other relevant conditions. The patients were randomly allocated to the training group and test group in a 4:1 ratio. Sagittal fat-suppressed T2-weighted imaging sequences were utilized to extract radiomic features. Feature selection was performed using the minimum Redundancy Maximum Relevance (mRMR) method, and the final model was constructed using the Least Absolute Shrinkage and Selection Operator (LASSO) regression. Model performance was evaluated on both the training and test sets using receiver operating characteristic curves, sensitivity, specificity, and accuracy.</p><p><strong>Results: </strong>The results showed that the model achieved area under the curve values of 0.95 and 0.94 on the training and test sets, respectively, indicating high accuracy in distinguishing meniscal injury from noninjury. In confusion matrix analysis, the sensitivity, specificity, and accuracy of the training set were 88%, 92%, and 87%, respectively, while the test set showed sensitivity, specificity, and accuracy of 89%, 82%, and 85%, respectively.</p><p><strong>Conclusions: </strong>Our radiomics model demonstrates high accuracy in distinguishing meniscal tears from nontear abnormalities, providing a reliable tool for clinical decision-making. Although the model demonstrated slightly lower specificity in the test set, its overall performance was good with high diagnostic capabilities. Future research could incorporate more clinical data to optimize the model and further improve diagnostic accuracy.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143982109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Novel Deep Learning Reconstruction to Augment Contrast Enhancement: Initial Evaluation.","authors":"Corey T Jensen, Vincenzo K Wong, Gauruv S Likhari, Taher E Daoud, Roland Bassett, Sarah Pasyar, Yasuhiro Imai, Risa Shigemasa, Alicia M Roman-Colon, Ke Li, Xinming Liu","doi":"10.1097/RCT.0000000000001755","DOIUrl":"https://doi.org/10.1097/RCT.0000000000001755","url":null,"abstract":"<p><strong>Objective: </strong>To assess image quality between single-energy CT (SECT) and dual-energy CT (DECT) scans compared with a novel deep learning (DL) reconstruction for SECT used to improve contrast enhancement.</p><p><strong>Methods: </strong>The raw data from a prior prospective HIPAA-compliant study (March through August 2022) was used to create a novel reconstruction in patients with biopsy-proven colorectal adenocarcinoma and liver metastases. Patients underwent 120 kVp SECT and DECT (50 keV reconstruction) abdominal scans in the portal venous phase in the same breath hold. Two readers independently assessed the scans.</p><p><strong>Results: </strong>The final study group was 13 men and 2 women with a mean age of 60 years ± 10, a mean height of 171 cm ± 8, a mean weight of 87 kg ± 23, and a mean body mass index of 30 kg/m2 ± 6. Liver, pancreas, spleen, psoas muscle, and aorta HUs were all significantly higher with the virtual DL reconstruction compared with the 120 kVp series, but significantly lower than the 50 keV series (P<0.05). Readers scored the DL reconstruction to have better contrast enhancement than the standard 120 kVp series and improved artifacts, noise texture, and resolution compared with the 50 keV series (P<0.05).</p><p><strong>Conclusions: </strong>Contrast enhancement with the new reconstruction is superior compared with the standard 120 kVp series approaching that of 50 keV DECT, but with improved perception of artifacts, noise texture, and resolution.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144017038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing Coronary CT Image Reconstruction With Deep Learning for Improved Quality: A Retrospective Study.","authors":"Agata Zdanowicz-Ratajczyk, Michał Puła, Adrian Korbecki, Arkadiusz Kacała, Maciej Guziński","doi":"10.1097/RCT.0000000000001746","DOIUrl":"https://doi.org/10.1097/RCT.0000000000001746","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate the impact of deep learning image reconstruction on image quality in CCTA compared with adaptive statistical iterative reconstruction (ASIR).</p><p><strong>Materials and methods: </strong>CCTA data sets from 100 consecutive patients with suspected CAD were acquired with a Revolution Apex 256-row CT scanner, reconstructed with ASIR-V and DLIR-H, and subsequently analyzed. Image noise, SNR, and CNR in five regions of interest (25 mm) were calculated and t tested. The normality of quantitative variables was assessed using the Shapiro-Wilk test. For non-normally distributed data, the Mann-Whitney U test was applied. The concordance of HU values within specific ROIs was analyzed with Bland-Altman plots. Correlation between ASIR-V and DLIR-H was conducted using the Spearman rank correlation test.Subjective image analysis was conducted using a 5-point scale to evaluate noise level, vascular enhancement smoothness, artifact reduction, and diagnostic confidence. Intraclass correlation (ICC) was used to assess the reliability and consistency of subjective ratings among the reader.</p><p><strong>Results: </strong>DLIR-H significantly reduced image noise across all ROIs (from 15% to 41%, all P<0.05), compared with ASIR-V. Mean SNR (ASIR-V vs. DLIR-H) were septum=4.3±1.7 versus 6.4±2.2; cavity of the left ventricle=24.3±8.3 versus 36.6±11.7; CNR: septum=8.2±2.5 versus 12.4±3.5; cavity of left ventricle= 28.2±9.1 versus 42.5±13.0. Spearman rank correlation ranged from 0.64 to 0.79 (P<0.05). Bland-Altman analysis showed good agreement between ASIR-V and DLIR-H, with no discernible patterns. Subjectively, DLIR-H significantly outperformed ASIR-V across all evaluated criteria (all P<0.05). ICC values indicated strong agreement among readers, demonstrating excellent reliability for most criteria and good reliability for vascular enhancement smoothness.</p><p><strong>Conclusions: </strong>DLIR-H significantly improved CCTA image quality compared with ASIR-V, which contributes to a more accurate diagnosis in patients with suspected CAD.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144017572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ultrasound-MRI Agreement in Individuals Undergoing Surveillance of Fontan-associated Liver Disease.","authors":"Harris Wang, Derek Rubadeux, Andrew T Trout, Cara E Morin, Alexander R Opotowsky, Alexandra Glenn, Joseph J Palermo, Khurram Bari, Jonathan R Dillman","doi":"10.1097/RCT.0000000000001751","DOIUrl":"https://doi.org/10.1097/RCT.0000000000001751","url":null,"abstract":"<p><strong>Objective: </strong>To assess agreement between abdominal ultrasound and MRI for the detection of focal liver lesions and manifestations of portal hypertension in patients with Fontan circulation.</p><p><strong>Materials and methods: </strong>To perform this single-center, retrospective study, we identified patients with Fontan circulation who underwent clinical abdominal ultrasound and MRI examinations within ±12 months between January 1, 2018 and June 30, 2023. Imaging reports were reviewed for the presence of liver lesions (specifically noting lesions >1 cm and radiologist-indicated suspicious lesions), features of portal hypertension (ie, presence of ascites and spleen length), abnormal liver contour, and liver stiffness. Intermodality agreement, sensitivity and specificity of ultrasound relative to MRI, and Spearman correlation were used to compare ultrasound and MRI measurements. Follow-up of detected lesions was also performed using electronic health records.</p><p><strong>Results: </strong>There were 58 patients included. Agreement between MRI and ultrasound for the findings of Fontan-associated liver disease (FALD) was as follows: presence of a liver lesion of any size [k = 0.20 (95% CI: 0.08 to 0.32)], presence of a liver lesion >1 cm [k = 0.43 (95% CI: 0.18 to 0.68)], radiologist-indicated suspicious liver lesion(s) [k = 0.07 (95% CI: -0.13 to 0.27)], presence of ascites [k = 0.57 (95% CI: 0.32 to 0.81)], abnormal liver contour [k = 0.31 (95% CI: 0.03 to 0.59)], and spleen length [intraclass correlation coefficient = 0.81 (95% CI: 0.58 to 0.92)]. Sensitivity and specificity of ultrasound using MRI as the reference standard were as follows: 34% (95% CI: 20% to 50%) and 100% (95% CI: 77% to 100%) for the presence of a liver lesion of any size, and 39% (95% CI: 17% to 64%) and 98% (95% CI: 87% to 100%) for the presence of a liver lesion >1 cm. There was a poor correlation between ultrasound and MRI liver stiffness measurements [rho = 0.22 (95% CI: -0.14 to 0.53); P = 0.23]. Of 44 patients with liver lesions, 3 (6.8%) had biopsy-confirmed hepatocellular neoplasms, including 2 adenomas and 1 hepatocellular carcinoma. All 3 lesions were detected by both MRI and ultrasound.</p><p><strong>Conclusions: </strong>There is poor to fair agreement between ultrasound and MRI for detecting manifestations of FALD, with ultrasound having poor sensitivity compared with MRI. While ultrasound detected all 3 clinically important liver lesions in our study, our results raise questions about whether ultrasound is an appropriate screening tool for FALD in patients post-Fontan.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143752992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}