Abdominal Radiology最新文献

{"title":"Prediction study of surrounding tissue invasion in clear cell renal cell carcinoma based on multi-phase enhanced CT radiomics.","authors":"Mengwei Wu, Hanlin Zhu, Zhijiang Han, Xingjian Xu, Yiming Liu, Huijun Cao, Xisong Zhu","doi":"10.1007/s00261-024-04712-y","DOIUrl":"https://doi.org/10.1007/s00261-024-04712-y","url":null,"abstract":"<p><strong>Objective: </strong>To examine the effectiveness of a nomogram model that combines clinical-image features and CT radiomics in predicting surrounding tissue invasion (STI) in clear cell renal cell carcinoma (ccRCC) patients before surgery.</p><p><strong>Methods: </strong>Postoperative pathological data of 248 ccRCC patients from two centers were retrospectively collected. Univariate and multivariate regression analyses were used to identify clinical and image features of ccRCC patients to construct a clinical model. Radiomics features were extracted from three CT scans, including tumoral, intratumor, and peritumoral regions. A nomogram was developed by integrating clinical model with optimal radiomics signature. The Shapley Additive Explanations (SHAP) method was used for interpretation.</p><p><strong>Results: </strong>This study included 65 ccRCC patients with STI and 183 patients without STI. The AUC of the clinical model was 0.766, 0.765, and 0.698 in the training cohort, internal validation cohort, and external validation cohort, respectively. The AUCs were higher in the radiomics signature based on ROI4 in NP than other radiomics (training cohort: 0.837 vs. 0.775-0.847; internal validation cohort: 0.831 vs. 0.695-0.811; external validation cohort: 0.762 vs. 0.623-0.731). Integrating the optimal radiomics signature with the clinical model to construct a combined model resulted in an AUC of 0.890, 0.886, and 0.826 in the training cohort, internal validation cohort, external validation cohort, respectively. SHAP values analysis revealed the top three radiomics features to be Small Dependence Low Gray Level Emphasis, Maximum 3D Diameter, and Maximum Probability.</p><p><strong>Conclusion: </strong>A nomogram based on preoperative CT and clinical image features is a reliable tool for predicting STI in ccRCC patients. The use of SHAP values can help popularize this tool.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142715008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of therapeutic response to transarterial chemoembolization plus systemic therapy regimen in hepatocellular carcinoma using pretreatment contrast-enhanced MRI based habitat analysis and Crossformer model.","authors":"Yuemin Zhu, Tao Liu, Jianwei Chen, Liting Wen, Jiuquan Zhang, Dechun Zheng","doi":"10.1007/s00261-024-04709-7","DOIUrl":"https://doi.org/10.1007/s00261-024-04709-7","url":null,"abstract":"<p><strong>Purpose: </strong>To develop habitat and deep learning (DL) models from multi-phase contrast-enhanced magnetic resonance imaging (CE-MRI) habitat images categorized using the K-means clustering algorithm. Additionally, we aim to assess the predictive value of identified regions for early evaluation of the responsiveness of hepatocellular carcinoma (HCC) patients to treatment with transarterial chemoembolization (TACE) plus molecular targeted therapies (MTT) and anti-PD-(L)1.</p><p><strong>Methods: </strong>A total of 102 patients with HCC from two institutions (A, n = 63 and B, n = 39) who received TACE plus systemic therapy were enrolled from September 2020 to January 2024. Multiple CE-MRI sequences were used to outline 3D volumes of interest (VOI) of the lesion. Subsequently, K-means clustering was applied to categorize intratumoral voxels into three distinct subgroups, based on signal intensity values of images. Using data from institution A, the habitat model was built with the ExtraTrees classifier after extracting radiomics features from intratumoral habitats. Similarly, the Crossformer model and ResNet50 model were trained on multi-channel data in institution A, and a DL model with Transformer-based aggregation was constructed to predict the response. Finally, all models underwent validation at institution B.</p><p><strong>Results: </strong>The Crossformer model and the habitat model both showed high area under the receiver operating characteristic curves (AUCs) of 0.869 and 0.877 (training cohort). In validation, AUC was 0.762 for the Crossformer model and 0.721 for the habitat model.</p><p><strong>Conclusion: </strong>The habitat model and DL model based on CE-MRI possesses the capability to non-invasively predict the efficacy of TACE plus systemic therapy in HCC patients, which is critical for precision treatment and patient outcomes.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142715005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of intravoxel incoherent motion and diffusion kurtosis imaging and 18- FDG PET/CT in response assessment in rectosigmoid carcinoma.","authors":"Stuti Chandola, Abhishek Soni, Soham Banerjee, Hemanga K Bhattacharjee, Raju Sharma, Ankita Phulia, Sushmita Pathy, Chandan J Das","doi":"10.1007/s00261-024-04689-8","DOIUrl":"https://doi.org/10.1007/s00261-024-04689-8","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate the performance of intravoxel incoherent motion and diffusion kurtosis imaging (IVIM- DKI) in response assessment of rectosigmoid carcinoma to chemo-radiotherapy (CRT) and compare with 18-FDG PET/CT parameters.</p><p><strong>Methods: </strong>A total of 30 patients of recto-sigmoid cancer on CRT underwent baseline staging and follow-up with IVIM - DKI. Out of this cohort, 20 patients underwent 18-FDG PET/CT. IVIM- DKI MRI and PET/CT parameters were noted from both pre and post-chemoradiotherapy (done at 6 weeks after completion) scans. Quantitative IVIM-DKI parameters, viz. apparent (ADC) and molecular (D) diffusion coefficient, perfusion coefficient (f), and kurtosis (K) were measured from non-necrotic areas and semi-quantitative PET parameters including SUV max, SUV ratio, metabolic tumor volume (MTV), total lesion glycolysis (TLG) were also measured. All these parameters correlated with the patient's response keeping RECIST 1.1 criteria as reference standard.</p><p><strong>Results: </strong>A statistically significant increase in D and ADC with a significant decline in K was noted after therapy in the entire cohort. These changes were observed in both responders as well as non-responders. No significant differences were observed in the percentage changes of these parameters post therapy amongst both groups. Among 20 patients with follow-up PET/CT imaging, a significant decline in all parameters of primary lesion was seen post-therapy. Responders (n = 12) showed a significant decline in MTV and TLG from baseline after therapy, whereas non-responders did not show any such decline. Change in TLG (ɗ TLG), followed by ɗ MTV had the strongest correlation with a positive response. A ɗ TLG value of ≥ 54.19 carried a 79% sensitivity and 83% specificity in differentiating responders from non responders.</p><p><strong>Conclusion: </strong>18-FDG PET/CT is a more accurate single modality for assessing both response and tumor burden post therapy, while ADC and D from IVIM MRI are useful adjuncts to response assessment.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142708606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing US for HCC surveillance.","authors":"Shuchi K Rodgers, David T Fetzer, James H Seow, Kathryn McGillen, David P Burrowes, Christopher Fung, Ashlesha S Udare, Stephanie R Wilson, Aya Kamaya","doi":"10.1007/s00261-024-04631-y","DOIUrl":"https://doi.org/10.1007/s00261-024-04631-y","url":null,"abstract":"<p><p>Ultrasound is the primary imaging modality used for surveillance of patients at risk for HCC. In 2017, the American College of Radiology Liver Imaging Reporting and Data Systems (ACR LI-RADS) introduced US LI-RADS to standardize the performance, interpretation, and reporting of US for HCC surveillance, with the algorithm recently updated as LI-RADS US Surveillance v2024. The American Association for the Study of Liver Diseases (AASLD) recommends reporting both the examination-level LI-RADS US Category as well as the US Visualization Score. The US Category conveys the overall findings of the exam and primarily determines follow up recommendations. The US Visualization Score conveys the expected sensitivity of the test and stratifies patients into appropriate surveillance pathways. One of the goals of routine surveillance is the detection of HCC at an early, potentially curable stage. Therefore, optimizing US technique is of critical importance. Increasing North American and worldwide utilization of LI-RADS US Surveillance, which includes technical recommendations, through education and outreach will undoubtedly benefit patients undergoing US HCC surveillance.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142708765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating the role of quantitative computed tomography perfusion parameters in differentiating hepatocellular carcinoma from other hepatic neoplasms.","authors":"Sudipta Mohakud, Vimal Sreejith, Nerbadyswari Deep Bag, Susama Patra, Manas Kumar Panigrahi, Pankaj Kumar, Brahmadatta Pattnaik, Tanmay Dutta, Suprava Naik, Taraprasad Tripathy, Ranjan Kumar Patel, M Divya, Dillip Kumar Muduly, Madhabananda Kar","doi":"10.1007/s00261-024-04688-9","DOIUrl":"https://doi.org/10.1007/s00261-024-04688-9","url":null,"abstract":"<p><strong>Background: </strong>Differentiating the various liver tumors is pivotal due to distinct treatments and prognoses. Sometimes, it is difficult to accurately differentiate hepatocellular carcinoma (HCC) from other hepatic neoplasms non-invasively because of overlap in the triple-phase contrast-enhanced computed tomography (CECT) features, contraindication of an invasive biopsy, particularly in multifocal lesions with cirrhosis or ascites or when an MRI is unavailable or not feasible.</p><p><strong>Objectives: </strong>To assess the utility of CT perfusion (CTP) parameters in differentiating HCC from other hepatic neoplasms.</p><p><strong>Methods: </strong>Forty-eight patients with suspicious liver lesions underwent CTP imaging. Perfusion parameters were assessed within the tumor and the adjacent normal liver using the post-processing software. Statistical significance (p-value), sensitivity, and specificity value of the individual parameters were assessed. The receiver operating characteristic (ROC) curve analysis was done to threshold values of the parameters.</p><p><strong>Results: </strong>The mean values of perfusion parameters like HAP (hepatic arterial perfusion), PVP (portal venous perfusion), HPI (hepatic perfusion index), BF (blood flow), BV (blood volume), MTT (mean transit time), and TTP (time to peak) were statistically significant (p-value < 0.05) between HCC and other hepatic neoplasms. Among the parameters, BV had the greatest AUC of 0.938. With a threshold value of 8.3 ml/100 ml/min, the sensitivity and specificity were 96.6% and 80%, respectively, in distinguishing HCC from other hepatic neoplasms. HPI, BF, BV, and TTP were statistically significant in differentiating hypervascular metastases from HCCs. HAP, HPI, BF, BV, and TTP were statistically significant in differentiating HCC from hypovascular metastases. BF and BV were significant in differentiating hypervascular from hypovascular metastases. HAP, PVP, HPI, BF, BV, and TTP were statistically significant in differentiating HCCs from intrahepatic cholangiocarcinomas.</p><p><strong>Conclusion: </strong>CTP provides a quantitative, non-invasive method to differentiate HCC from other hepatic neoplasms with high efficacy. It can be a problem-solving tool when a conventional CECT scan cannot characterize a lesion as HCC, where biopsy is not feasible.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142708734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Classics in abdominal imaging: a tangle of vessels in the mesentery.","authors":"Hui Yu Tham, Ming Ngan Aloysius Tan, Chern Yue Glen Ong","doi":"10.1007/s00261-024-04687-w","DOIUrl":"https://doi.org/10.1007/s00261-024-04687-w","url":null,"abstract":"","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142708538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Surgical management of achalasia.","authors":"Margaux Mustian, Kristen Wong","doi":"10.1007/s00261-024-04664-3","DOIUrl":"https://doi.org/10.1007/s00261-024-04664-3","url":null,"abstract":"<p><p>Achalasia is a chronic esophageal motility disorder comprised of ineffective esophageal peristalsis and incomplete relaxation of the lower esophageal sphincter. This disease had historically been managed through medical means as well as endoscopic dilations. However, surgical interventions are now considered standard of care, including minimally invasive Heller myotomy, which was popularized in 1990s, followed by per oral endoscopic myotomy in the 2010s. Both surgical approaches provide acceptable resolution of dysphagia symptoms. Classification of the achalasia as well as other patient-level factors may drive the clinical decision-making between the two approaches, as well as surgical training and surgeon preference.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142708768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Image-guided renal parenchymal biopsies- how we do it.","authors":"Paul B Shyn, Maitray D Patel, Malak Itani, Amar C Gupta, Constantine M Burgan, Virginia Planz, Samuel J Galgano, Ramit Lamba, Steven S Raman, Marcia H Yoshikawa","doi":"10.1007/s00261-024-04690-1","DOIUrl":"https://doi.org/10.1007/s00261-024-04690-1","url":null,"abstract":"<p><p>This paper is a multi-institutional review of image-guided renal parenchymal biopsies. Among the topics covered are indications, preprocedural considerations, biopsy technique, complications, and postprocedural management. Both native kidney and transplant kidney biopsies are considered in this review.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142708736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Role of Superb Microvascular Imaging (SMI) vascularity index values and vascularity patterns in the differential diagnosis of malignant liver lesions.","authors":"Halil Serdar Aslan, Muhammet Arslan, Kadir Han Alver, Sercan Vurgun, Mahmut Demirci, Muhammed Tekinhatun","doi":"10.1007/s00261-024-04711-z","DOIUrl":"https://doi.org/10.1007/s00261-024-04711-z","url":null,"abstract":"<p><strong>Purpose: </strong>To evaluate the Superb Microvascular Imaging (SMI) vascular patterns and vascularity index (VI) values of malignant focal liver lesions (FLLs), assess their role in differential diagnosis, and examine interobserver agreement.</p><p><strong>Materials and methods: </strong>A total of 107 patients (52 males, 55 females; mean age 62 ± 12.8 years, range 25-87) referred to the interventional radiology clinic for FLL biopsy between April 2022 and April 2023 were analyzed. Two radiologists independently assessed the SMI vascular patterns and calculated VI values. Differences among three lesion groups - hepatocellular carcinoma (HCC, n = 16), non-HCC primary liver malignancies (n = 16), and metastases (n = 75) - were evaluated, and interobserver agreement was assessed.</p><p><strong>Results: </strong>Most metastases (88%) demonstrated hypovascular patterns, while HCCs predominantly exhibited hypervascular patterns (68.7-81.3%). Non-HCC primary malignancies showed no dominant vascular pattern. Significant differences in SMI patterns were observed among lesion types (p = 0.001-0.035). VI values for HCCs (7.53-7.73) were significantly higher than those for non-HCC malignancies (2.73-2.93) and metastases (1.35-1.36) (p = 0.0001). ROC analysis based on VI values yielded AUCs of 0.886-0.887, with a cutoff of 2.92 providing 81.3% sensitivity and 79.1-80.2% specificity for HCC diagnosis. The inter-reader agreement for SMI patterns had a kappa score of 0.634, while the intraclass correlation coefficient (ICC) for VI values was 0.959.</p><p><strong>Conclusion: </strong>HCCs displayed more hypervascular SMI patterns and significantly higher VI values compared to other malignant FLLs, emphasizing the diagnostic potential of VI in distinguishing HCC from non-HCC tumors. Although metastases primarily exhibited hypovascular patterns and low VI values, no dominant vascular pattern was identified in non-HCC primary liver malignancies. Assessing VI values provided higher interobserver agreement compared to SMI patterns, enhancing objectivity and reproducibility.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142685750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Classics in abdominal radiology: the jumping deer sign.","authors":"Samantha Elliott, Trent Taros, Adam Lustig","doi":"10.1007/s00261-024-04699-6","DOIUrl":"https://doi.org/10.1007/s00261-024-04699-6","url":null,"abstract":"<p><p>The \"jumping deer sign\" is an ultrasonographic pattern that aids in identifying normal liver anatomy and distinguishing it from pathology. It includes the portal vein (deer's head and body), the gallbladder or cystic duct (tail), and the inferior vena cava (obstacle). This sign helps differentiate portal veins from intrahepatic ducts, crucial for diagnosing conditions like portal hypertension. It also assists in identifying gallbladder pathologies and assessing the IVC for hydration status. The jumping deer sign provides a clear reference for clinicians, improving diagnostic accuracy, especially for those with limited ultrasound experience.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142685746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}