Journal of Computer Assisted Tomography最新文献

{"title":"Coronary Computed Tomography Angiography Using an Optimal Acquisition Time Window Based on Heart Rate Determined During Breath-Holding Following Free Breathing.","authors":"Zi-Yan Liu, Ze-Peng Ma, Kai Gao, Wei Ding, Yong-Xia Zhao","doi":"10.1097/RCT.0000000000001666","DOIUrl":"10.1097/RCT.0000000000001666","url":null,"abstract":"<p><strong>Objectives: </strong>To compare the image quality and radiation dose in coronary computed tomography angiography (CCTA) based on different acquisition time windows corresponding to the heart rate of breath-holding after free breathing.</p><p><strong>Methods: </strong>Two hundred patients who underwent CCTA with a basal heart rate between 70 and 85 beats/min were divided into groups A and B, with 100 patients in each group. Patients in groups A and B were scanned with the acquisition time window corresponding to the heart rate determined during a breath hold obtained after free breathing and the basal heart rate during free breathing, respectively. Computed tomography (CT) attenuation values of the coronary artery, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were calculated. The subjective image scores of the groups were assessed blindly by 2 experienced physicians using a 4-point system, and score consistency was compared using the κ test. The volume CT dose index and dose-length product were recorded for each patient, and the effective dose (ED) was calculated. The Kruskal-Wallis H test was performed to evaluate differences in age, heart rate, and body mass index. A χ2 test was used to evaluate sex differences. An independent-sample t test was employed to compare objective and subjective data such as dose-length product, volume CT dose index, ED, SNR, CNR, and averaged subjective assessment scores. Statistical significance was set at P  < 0.05.</p><p><strong>Results: </strong>No statistically significant differences occurred in sex, age, or body mass index between patients in group A and group B (all P  > 0.05). No significant differences occurred in the mean CT values, mean SNR values, mean CNR values, or mean subjective scores of CCTA images between the patients in groups A and B ( P  > 0.05). The ED values of the patients in group A were 52.93% lower than those in group B ( P  < 0.001).</p><p><strong>Conclusion: </strong>The radiation dose in CCTA examinations can be significantly reduced while maintaining image quality by narrowing the acquisition time window for breath-holding after free breathing.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":"265-270"},"PeriodicalIF":1.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142288263","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":"Contrast-Enhanced Digital Mammography for the Diagnosis and Determination of Extent of Disease in Invasive Lobular Carcinoma: Our Experience and Literature Review.","authors":"Margaret Johansson Lipinski, Tal Friehmann, Shlomit Tamir, Eli Atar, Ahuva Grubstein","doi":"10.1097/RCT.0000000000001663","DOIUrl":"10.1097/RCT.0000000000001663","url":null,"abstract":"<p><strong>Objective: </strong>Contrast-enhanced imaging, including magnetic resonance imaging and, more recently, contrast-enhanced digital mammography (CEM), is indicated for the precise diagnosis of invasive lobular carcinoma (ILC). The aim of our study was to further validate the use of CEM for evaluation of extent of disease in ILC cases, with digital breast tomosynthesis (DBT) as an adjunct.</p><p><strong>Methods: </strong>A retrospective, institutional review board approved study was conducted in a tertiary medical center. All CEM examinations performed on ILC patients between 2017 and 2023 were reread by 2 dedicated breast radiologists. Clinical data and pathology reports were retrieved from electronic medical records. The longest diameter of the enhancing lesion was correlated to pathology findings. In addition, for each case, the readers provided brief commentary on the added value of DBT.</p><p><strong>Results: </strong>Twenty-four CEM examinations were evaluated. The subjects in the study cohort were on average older than expected for ILC patients (74 vs 63 years) and were unable to undergo breast magnetic resonance imaging due to advanced age and comorbidities. Three subjects were treated with neoadjuvant therapy and thus were excluded from the correlation to pathology analysis. Enhancing lesions, ranging from 4-75 mm, strongly correlated to pathology results, with statistical significance. This was demonstrated for mass and nonmass lesions ( r  = 0.94, P  < 0.001 and r  = 0.99, P  = 0.002, respectively). For most lesions (17/24, 71%), readers remarked that the addition of DBT allowed for improved characterization of lesion margins, mainly detecting architectural distortion.</p><p><strong>Conclusions: </strong>When compared with the pathology findings, ILC was accurately diagnosed and assessed using CEM. The addition of DBT was reported by the interpreting radiologists as a valuable adjunct for margin analysis.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":"258-264"},"PeriodicalIF":1.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142501195","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":"Application of a Deep Learning-Based Contrast-Boosting Algorithm to Low-Dose Computed Tomography Pulmonary Angiography With Reduced Iodine Load.","authors":"Minsu Park, Minhee Hwang, Ji Won Lee, Kun-Il Kim, Chulkyun Ahn, Young Ju Suh, Yeon Joo Jeong","doi":"10.1097/RCT.0000000000001665","DOIUrl":"10.1097/RCT.0000000000001665","url":null,"abstract":"<p><strong>Objective: </strong>The aim of this study was to assess the effectiveness of a deep learning-based image contrast-boosting algorithm by enhancing the image quality of low-dose computed tomography pulmonary angiography at reduced iodine load.</p><p><strong>Methods: </strong>This study included 179 patients who underwent low-dose computed tomography pulmonary angiography with a reduced iodine load using 64 mL of a 1:1 mixture of contrast medium from January 1 to June 30, 2023. For single-energy computed tomography, the noise index was set at 15.4 to maintain a CTDI vol of <2 mGy at 80 kVp, and for dual-energy computed tomography, fast kV-switching between 80 and 140 kVp was employed with a fixed tube current of 145 mA. Images were reconstructed by 50% adaptive statistical iterative reconstruction (AR50) and a commercially available deep learning image reconstruction (TrueFidelity) package at a high strength level (TFH). In addition, AR50 images were further processed using a deep learning-based contrast-boosting algorithm (AR50-CB). Quantitative and qualitative image qualities and numbers of involved vessels with thrombus at each pulmonary artery level were compared in the 3 image types using the Friedman test and Wilcoxon signed rank test.</p><p><strong>Results: </strong>Five hundred thirty-seven reconstructed image datasets of 179 patients were analyzed. Quantitative image analysis showed AR50-CB (30.8 ± 10.0 and 28.1 ± 9.6, respectively) had significantly higher signal-to-noise ratio and contrast-to-noise ratio values than AR50 (20.2 ± 6.2 and 17.8 ± 6.2, respectively) ( P  < 0.001) or TFH (28.3 ± 8.3 and 24.9 ± 8.1, respectively) ( P  < 0.001). Qualitative image analysis showed that contrast enhancement and noise scores of AR50-CB were significantly greater than those of AR50 ( P  < 0.001) and that AR50-CB enhancement scores were significantly higher than TFH enhancement scores ( P  < 0.001). The number of subsegmental pulmonary arteries affected by thrombus detected was significantly greater for AR50-CB (30 for AR50, 30 for TFH, and 55 for AR50-CB, P  < 0.001).</p><p><strong>Conclusions: </strong>The use of a deep learning-based contrast-boosting algorithm improved image quality in terms of signal-to-noise ratio and contrast-to-noise ratio values and the detection of thrombi in subsegmental pulmonary arteries.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":"288-296"},"PeriodicalIF":1.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142501194","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":"Evaluation of Splenic Involvement in Lymphomas Using Extracellular Volume Fraction Computed Tomography.","authors":"Suqin Xu, Meimei Cao, Longlan Chen, Jinfang Shi, Xiaoxia Wang, Lan Li, Lu Wang, Jiuquan Zhang","doi":"10.1097/RCT.0000000000001664","DOIUrl":"10.1097/RCT.0000000000001664","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate whether the extracellular volume (ECV) fraction can be used to identify splenic involvement in lymphoma patients and whether it can be used to improve the diagnostic performance of conventional computed tomography (CT) in the diagnosis of splenic diffuse involvement.</p><p><strong>Methods: </strong>Consecutive patients with newly diagnosed lymphoma who underwent abdomen contrast-enhanced CT and 18 F-fluorodeoxyglucose positron emission tomography/CT for diagnosis or staging were retrospectively enrolled. Patients were divided into the splenic involvement (diffuse or focal) and noninvolvement groups. The ECV fraction was obtained in all patients. In the splenic diffuse involvement and noninvolvement groups, spleen vertical length (SVL) >13 cm and obliteration of normal heterogeneous enhancement of the spleen in arterial phase were recorded. Receiver operating characteristic curve was used to analyze the diagnostic performance, and area under the curve (AUC) comparison was performed using the Delong test.</p><p><strong>Results: </strong>A total of 135 patients were included, 56 patients with splenic involvement (36 diffuse and 20 focal) and 79 patients with noninvolvement. Splenic involvement can be identified via the ECV fraction (AUC = 0.839). In distinguishing splenic diffuse involvement, the AUC of the ECV fraction was superior to the SVL >13 cm (0.788 vs 0.627, P  = 0.007) and obliteration of normal heterogeneous enhancement of the spleen (0.788 vs 0.596, P  = 0.001). The combination of ECV fraction and SVL >13 cm demonstrated superior diagnostic performance, with an AUC of 0.830, surpassing all other parameters.</p><p><strong>Conclusion: </strong>The ECV fraction can be used to identify splenic involvement. The ECV fraction combined with SVL >13 cm is recommended for the prediction of splenic diffuse involvement.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":"225-233"},"PeriodicalIF":1.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142501196","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":"Development and Clinical Evaluation of a Contrast Optimizer for Contrast-Enhanced CT Imaging of the Liver.","authors":"Hananiel Setiawan, Francesco Ria, Ehsan Abadi, Daniele Marin, Lior Molvin, Ehsan Samei","doi":"10.1097/RCT.0000000000001677","DOIUrl":"10.1097/RCT.0000000000001677","url":null,"abstract":"<p><strong>Objective: </strong>Patient characteristics, iodine injection, and scanning parameters can impact the quality and consistency of contrast enhancement of hepatic parenchyma in CT imaging. Improving the consistency and adequacy of contrast enhancement can enhance diagnostic accuracy and reduce clinical practice variability, with added positive implications for safety and cost-effectiveness in the use of contrast medium. We developed a clinical tool that uses patient attributes (height, weight, sex, age) to predict hepatic enhancement and suggest alternative injection/scanning parameters to optimize the procedure.</p><p><strong>Methods: </strong>The tool was based on a previously validated neural network prediction model that suggested adjustments for patients with predicted insufficient enhancement. We conducted a prospective clinical study in which we tested this tool in 24 patients aiming for a target portal-venous parenchyma CT number of 110 HU ± 10 HU.</p><p><strong>Results: </strong>Out of the 24 patients, 15 received adjustments to their iodine contrast injection parameters, resulting in median reductions of 8.8% in volume and 9.1% in injection rate. The scan delays were reduced by an average of 42.6%. We compared the results with the patients' previous scans and found that the tool improved consistency and reduced the number of underenhanced patients. The median enhancement remained relatively unchanged, but the number of underenhanced patients was reduced by half, and all previously overenhanced patients received enhancement reductions.</p><p><strong>Conclusions: </strong>Our study showed that the proposed patient-informed clinical framework can predict optimal contrast enhancement and suggest empiric injection/scanning parameters to achieve consistent and sufficient contrast enhancement of hepatic parenchyma. The described GUI-based tool can prospectively inform clinical decision-making predicting optimal patient's hepatic parenchyma contrast enhancement. This reduces instances of nondiagnostic/insufficient enhancement in patients.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":"239-246"},"PeriodicalIF":1.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11925662/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142949470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Environmental Impact of Iodinated Contrast Media: Strategies for Optimized Use and Recycling.","authors":"Giuseppe V Toia, Lakshmi Ananthakrishnan","doi":"10.1097/RCT.0000000000001674","DOIUrl":"10.1097/RCT.0000000000001674","url":null,"abstract":"<p><strong>Abstract: </strong>Iodinated contrast media (ICM) is an integral and ubiquitous component of modern diagnostic imaging. Although most radiology practices are familiar with ICM administration and physiological excretion, they may be less aware of how much ICM is wasted on a per exam basis. Furthermore, radiologists may not recognize the environmental fate of discarded ICM waste. In an evolving world where medical practices are increasingly cognizant of their environmental footprint and radiology practices are considered high consumers of resources, it behooves the radiology community to understand the ICM lifecycle and ways to mitigate unnecessary waste. This review article explains the origin and environmental fate of discarded ICM, with special focus on wastewater contamination. Secondly, the article focuses on feasible options to both optimize use and decrease consumable waste. Specifically, the article addresses ICM vial size inventory diversification, multi-use ICM vials, syringeless contrast injectors, and the potential for using multi-energy imaging (dual-energy or photon counting CT) to accomplish these goals. Finally, the authors share their institutional experience participating in an ICM recycling program and its current departmental impact.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":"203-214"},"PeriodicalIF":1.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142780229","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":"Node Reporting and Data System Combined With Computed Tomography Radiomics Can Improve the Prediction of Nonenlarged Lymph Node Metastasis in Gastric Cancer.","authors":"Changqin Jiang, Wei Fang, Na Wei, Wenwen Ma, Cong Dai, Ruixue Liu, Anzhen Cai, Qiang Feng","doi":"10.1097/RCT.0000000000001673","DOIUrl":"10.1097/RCT.0000000000001673","url":null,"abstract":"<p><strong>Objectives: </strong>To investigate the diagnostic performance of Node Reporting and Data System (Node-RADS) combined with computed tomography (CT) radiomics for assessing nonenlargement regional lymph nodes in gastric cancer (GC).</p><p><strong>Methods: </strong>Preoperative CT images were retrospectively collected from 376 pathologically confirmed of gastric adenocarcinoma from January 2019 to December 2023, with 605 lymph nodes included for analysis. They were divided into training (n = 362) and validation (n = 243) sets. Radiomics features were extracted from venous-phase, and the radiomics score was obtained. Clinical information, CT parameters, and Node-RADS classification were collected. A combined model was built using machine-learning approach and tested in validation set using receiver operating characteristic curve analysis. Further validation was conducted in different subgroups of lymph node short-axis diameter (SD) range.</p><p><strong>Results: </strong>Node-RADS score, SD, maximum diameter of thickness of tumor, and radiomics were identified as the most predictive factors. The results demonstrated that the integrated model combining SD, maximum diameter of thickness of tumor, Node-RADS, and radiomics outperformed the model excluding radiomics, yielding an area under the receiver operating characteristic curve of 0.82 compared with 0.79, with a statistically significant difference ( P  < 0.001). Subgroup analysis based on different SDs of lymph nodes also revealed enhanced diagnostic accuracy when incorporating the radiomics score for the 4- to 7.9-mm subgroups, all P  < 0.05. However, for the 8- to 9.9-mm subgroup, the combination of the radiomics did not significantly improve the prediction, with an area under the receiver operating characteristic curve of 0.85 versus 0.85, P  = 0.877.</p><p><strong>Conclusion: </strong>The integration of radiomics scores with Node-RADS assessments significantly enhances the accuracy of lymph node metastasis evaluation for GC. This combined model is particularly effective for lymph nodes with smaller standard deviations, yielding a marked improvement in diagnostic precision.</p><p><strong>Clinical relevance statement: </strong>The findings of this study indicate that a composite model, which incorporates Node-RADS, radiomics features, and conventional parameters, may serve as an effective method for the assessment of nonenlarged lymph nodes in GC.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":"215-224"},"PeriodicalIF":1.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142501197","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":"Commentary: Foreword from the Editor-in-Chief to Guest Section on Sustainability.","authors":"Eric P Tamm","doi":"10.1097/RCT.0000000000001723","DOIUrl":"10.1097/RCT.0000000000001723","url":null,"abstract":"","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":"49 2","pages":"167"},"PeriodicalIF":1.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143669854","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":"Garbage Out: A Radiologist's Guide to Hospital Waste Streams.","authors":"Claire E White-Dzuro, Patrick W Doyle, Michael C Larson, Katherine C Frederick-Dyer","doi":"10.1097/RCT.0000000000001681","DOIUrl":"10.1097/RCT.0000000000001681","url":null,"abstract":"<p><strong>Abstract: </strong>What happens to trash after disposal? The management and processing of discarded items is often opaque and taken for granted, but an understanding of hospital waste streams is important for radiology departments and hospital systems for economic, regulatory, and environmental reasons. In this paper, we discuss the numerous waste pathways including general, hazardous, pharmaceutical, radioactive, and electronic waste as well as sustainable waste streams including laundry services, composting, and recycling. Costs, regulatory issues, and environmental considerations associated with each pathway are reviewed. We also describe radiology's specific contributions to each waste stream as well as variations in department practices, tips for optimal use, and future research investigations that could impact waste volume. Healthcare garbage disposal pathways will only increase in importance as our healthcare needs and systems continue to grow, and waste optimization efforts yield benefits to operation costs, environmental ecosystems, and human health.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":"180-190"},"PeriodicalIF":1.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142780216","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":"Predictive Model Based on Texture Analysis of Noncontrast Cardiac Magnetic Resonance Images for the Prognostic Evaluation of Cardiac Amyloidosis.","authors":"Jiaqi She, Jiajun Guo, Yi Sun, Yinyin Chen, Mengsu Zeng, Meiying Ge, Hang Jin","doi":"10.1097/RCT.0000000000001671","DOIUrl":"10.1097/RCT.0000000000001671","url":null,"abstract":"<p><strong>Objectives: </strong>We aimed to develop a predictive model based on textural features of noncontrast cardiac magnetic resonance (CMR) imaging for risk stratification toward adverse events in patients with cardiac amyloidosis (CA).</p><p><strong>Methods: </strong>A cohort of 78 patients with CA was grouped into training (n = 54) and validation (n = 24) sets at a ratio of 7:3. A total of 275 textural features were extracted from the CMR images. MaZda and a support vector machine (SVM) were used for feature selection and model construction. An SVM model incorporating radiological and textural features was built to predict endpoint events by evaluating the area under the curve.</p><p><strong>Results: </strong>In the entire cohort, 52 patients experienced major adverse cardiovascular events and 26 patients did not. By combining 2 radiological features and 8 texture features, extracted from cine and T2-weighted imaging images, the SVM model achieved area under the curves of the receiver operating characteristic and precision-recall curves of 0.930 and 0.962 in the training cohort and that of 0.867 and 0.941 in the validated cohort, respectively. The Kaplan-Meier curve of this SVM model criterion significantly stratified the CA outcomes (log-rank test, P  < 0.0001).</p><p><strong>Conclusions: </strong>The SVM model based on radiological and textural features derived from noncontrast CMR images can be a reliable biomarker for adverse events prognostication in patients with CA.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":"271-280"},"PeriodicalIF":1.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142501198","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}