Journal of Computer Assisted Tomography最新文献

{"title":"Diagnostic Value of the Color Doppler Ultrasound Standardized Semiquantitative Score Combined With Sound Touch Elastography in Liver Fibrosis in Patients With Chronic Hepatitis B: A Retrospective Cohort Study.","authors":"Yali Wu, Huiying Dai, Dan Li, Li Li, Liang Ou","doi":"10.1097/RCT.0000000000001712","DOIUrl":"10.1097/RCT.0000000000001712","url":null,"abstract":"<p><strong>Purpose: </strong>This study aims to evaluate the diagnostic value of standardized semiquantitative scoring of color Doppler ultrasound combined with liver stiffness measurement (LSM) of sound touch elastography (STE) in chronic hepatitis B (CHB) patients, providing a reference for the liver fibrosis diagnosis.</p><p><strong>Methods: </strong>We performed ultrasound and STE on CHB patients, with liver biopsies as the benchmark. We compared the differences in ultrasound standardized semiquantitative scoring and LSM among patients with different stages of liver fibrosis, and evaluated the diagnostic efficacy of significant liver fibrosis using receiver operating characteristic (ROC) curves and the area under the ROC curve alone or in combination.</p><p><strong>Results: </strong>The total scores of ultrasound semiquantitative scoring and LSM showed statistically significant differences among patients with different stages of liver fibrosis ( P  < 0.05). There was no statistically significant difference in the total scores of S0 and S1 stages or in the LSM values ( P  > 0.05). However, the total scores and LSM values for patients at stages S2 and S3 were both higher than those at stage S0, and increased with the severity of fibrosis staging, with statistically significant differences ( P  < 0.05). The results of the ROC curve analysis showed that the combined diagnosis of significant liver fibrosis with ultrasound standardized semiquantitative scoring and STE had an area under the curve of 0.807, which was significantly greater than using ultrasound standardized semiquantitative scoring (0.694, P  < 0.05) or shear wave elastography alone (0.706, P  < 0.05).</p><p><strong>Conclusions: </strong>Color Doppler ultrasound with standardized semiquantitative scoring combined with STE examination can detect significant liver fibrosis (≥S2) in CHB patients.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":"563-570"},"PeriodicalIF":1.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142949475","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":"Assessment of a New CT Detector and Filtration Technology: Part 2-Image Quality in Phantoms, Cadavers, and Patients.","authors":"Izabella Barreto, Graham Stoddard, Anahita Heshmat, Tara Massini, Ibrahim Tuna, Lynn Rill, Manuel Arreola","doi":"10.1097/RCT.0000000000001711","DOIUrl":"10.1097/RCT.0000000000001711","url":null,"abstract":"<p><strong>Purpose: </strong>The purpose of this work was to evaluate the image quality of a commercial CT scanner equipped with a novel detector and filtration technology called PureVision Optics (PVO).</p><p><strong>Methods: </strong>CT number, noise, contrast-to-noise ratio (CNR), modulation transfer function (MTF), and noise power spectrum (NPS) were assessed using the ACR CT Accreditation phantom scanned with various acquisitions at 80 kV, 100 kV, 120 kV, and 135 kV, each with multiple CTDI vol values of 20 mGy, 40 mGy, and 65 mGy. Artifacts were evaluated in an anthropomorphic head phantom, a cadaver head, and in patient studies. Two neuroradiologists assessed image quality features in various patients who were examined with unenhanced brain CT on both scanners.</p><p><strong>Results: </strong>Compared with the conventional scanner, for the same CTDI vol , the PVO scanner produced 20.3% less image noise ( P  < 0.001), 18.9% higher CNR ( P  < 0.01), and 24.6% higher spatial resolution ( P  < 0.001). Streak artifacts were less severe with the PVO scanner for the phantom, cadaver, and patient scans ( P  < 0.05). Radiologists scored the PVO scanner as significantly better for visualization of the cerebrospinal fluid space over the cerebral sulci in high convexity, image noise in gray and white matter, and artifacts in the posterior fossa. They also significantly preferred the PVO scanner for visualization of the border between brain gray and white matter, cerebrospinal fluid space around the mesencephalon, and overall diagnostic acceptability.</p><p><strong>Conclusions: </strong>For matched CTDI vol values, the scanner equipped with PVO technology produced better objective and subjective image quality metrics in brain CT imaging compared with a conventional CT scanner without PVO. In clinical settings, PVO may allow for lower doses while enhancing imaging through dense areas, improving visualization of subtle details, and offering more effective options for examining obese patients.This research received financial support from Canon Medical Systems USA. The study design and data were fully controlled by the coauthors, of which none are employees or consultants of Canon Medical Systems USA.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":"631-639"},"PeriodicalIF":1.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143059121","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":"3D Segmentation of Whole Lung and Metastatic Lung Nodules Using Adaptive Region Growing and Shape-based Morphology.","authors":"Esha Baidya Kayal, Shuvadeep Ganguly, Archana Sasi, D S Dheeksha, Manish Saini, Swetambri Sharma, Shivansh Gupta, Nikhil Sharma, Krithika Rangarajan, Sameer Bakhshi, Devasenathipathy Kandasamy, Amit Mehndiratta","doi":"10.1097/RCT.0000000000001719","DOIUrl":"10.1097/RCT.0000000000001719","url":null,"abstract":"<p><strong>Objective: </strong>Early diagnosis of primary and metastatic lung nodules is critical for effective therapeutic planning. Manual delineation of lung nodules is not time-efficient and is prone to human error as well as interobserver and intraobserver variability. This study aimed to address the unmet need for an open-source computer-aided detection (CAD) system for 3D segmentation of lung and metastatic lung nodules along with radiomic feature extraction.</p><p><strong>Methods: </strong>The proposed adaptive region-growing-based lung nodule segmentation (RGLNS) tool was developed in-house, requiring only manual input to select a seed point within the nodule on computed tomography (CT) images. A total of 230 CT scans from 100 patients with sarcomas were screened. Lung nodules were present in 200 CT scans, which were further analyzed. The accuracy of the lung and nodule segmentation was evaluated qualitatively using a 5-point Likert scale (uninterpretable: 1; poor: 2; fair: 3; good: 4; excellent: 5) and quantitatively using the Dice coefficient and Jaccard index.</p><p><strong>Results: </strong>A total of 200 CT scans comprising 12,000 CT slices were analyzed, among which 786 lung nodules were identified. Quantitative lung segmentation accuracies (n=2400 slices) yielded a Dice coefficient of 0.92±0.06 and a Jaccard index of 0.85±0.05. Qualitative scores (n=9600 slices) for lung boundary correction (4.56±1.18) and inclusion of pulmonary vessels (4.75±0.72) were rated as good to excellent. Quantitative nodule segmentation (n=142 nodules) accuracies were as follows: dice coefficient=0.92±0.03, 0.88±0.04, 0.86±0.03, 0.85±0.03, 084±0.04 and Jaccard index=0.84±0.03, 0.81±0.04, 0.78±0.04, 0.78±0.02, 0.76±0.04 for solitary (n=73), juxtapleural (n=32), juxtavascular (n=28), fissure-attached (n=6), and ground-glass (n=6) nodules, respectively. Qualitative scores (n=644 nodules) for nodule-boundary were good to excellent [solitary (n=342): 4.97±0.15; juxtapleural (n=155): 4.45±0.60; juxtavascular (n=127): 4.40±0.65; fissure-attached (n=9): 4.40±0.70; ground-glass (n=11): 4.25±0.75] and for exclusion of pulmonary vessels/pleura from nodules were good [juxtapleural (n=155): 4.10±0.66; juxtavascular (n=127): 4.08±0.64; fissure-attached (n=9): 4.30±0.67].</p><p><strong>Conclusions: </strong>The proposed semiautomated CAD system, RGLNS, requiring minimal manual input, demonstrated robust, and promising segmentation results for the whole lung and various types of metastatic lung nodules.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":"611-624"},"PeriodicalIF":1.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143059328","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":"The Clinical Value of the MAR + Metal Artifact Reduction Algorithm for Postoperative Assessment of Lumbar Internal Fixation.","authors":"Jiayi Fang, Fei Yu, Bin Yang, Guan Wang, Guangyan Si","doi":"10.1097/RCT.0000000000001724","DOIUrl":"10.1097/RCT.0000000000001724","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;With the widespread use of lumbar pedicle screws for internal fixation, the morphology of the screws and the surrounding tissues should be evaluated. The metal artifact reduction (MAR) technique can reduce the artifacts caused by pedicle screws, improve the quality of computed tomography (CT) images after pedicle fixation, and provide more imaging information to the clinic.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Purpose: &lt;/strong&gt;To explore whether the MAR + method, a projection-based algorithm for correcting metal artifacts through multiple iterative operations, can reduce metal artifacts and have an impact on the structure of the surrounding metal.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Materials and methods: &lt;/strong&gt;A total of 57 patients who underwent lumbar spine CT examination after lumbar internal fixation from January to December 2023 in our hospital were retrospectively enrolled. The CT images were reconstructed using MAR + and non-MAR + techniques and were subdivided into MAR + and non-MAR + groups. The CT number (in Hounsfield units) and the SD noise values of the spinal canal, vertebral body, psoas major muscle, and adjacent fat were measured in the 2 groups of CT images, and the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. The subjective score was evaluated by two diagnostic radiologists using a double-blind method for image quality evaluation of the MAR + group and the non-MAR + group, and the image quality was classified on a 5-point scale. The rank-sum test was utilized to compare the subjective and objective scores of the 2 groups.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The SD values of the spinal canal ( Z =-4.12, P &lt;0.01), vertebral body ( Z =-3.81, P &lt;0.01), and psoas major muscle ( Z =-3.87, P &lt;0.01) in the MAR + group were significantly lower than those in the non-MAR + group ( P &lt;0.05). However, the SD values of the adjacent fat ( Z =-2.03, P =0.42) in the MAR + group, although smaller than those in the non-MAR + group, were not statistically significant. The CNR values of vertebral canal ( Z =-2.67, P =0.008) and fat ( Z =-2.60, P =0.009) were higher in the MAR + group than in the non-MAR + group, whereas the CNR values of the vertebral body ( Z =-6.74, P &lt;0.01) in the MAR + group were smaller than those in the non-MAR + group, and the difference of all of them was statistically significant ( P &lt;0.05). Furthermore, for both CT and SNR values, the MAR group's values were all less than those of the non-MAR group and were statistically significant ( P &lt;0.05). The subjective scores of the measurement points were all higher in the MAR + group than in the non-MAR + group.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;The MAR + technique has a noise reduction effect on different tissues and artifacts are significantly reduced. Although the artifacts caused by metal screws were not completely eliminated, the MAR + technique was able to reduce the interference of artifacts in the diagnosis of CT images, thus improving their diagnos","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":"675-681"},"PeriodicalIF":1.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12237113/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143059142","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":"Assessment of a New CT Detector and Filtration Technology: Part 1 - X-ray Beam Characterization and Radiation Dosimetry.","authors":"Izabella Barreto, Nathalie Correa, Patricia Moser, Ibrahim Tuna, Tara Massini, Lynn Rill, Manuel Arreola","doi":"10.1097/RCT.0000000000001710","DOIUrl":"10.1097/RCT.0000000000001710","url":null,"abstract":"<p><strong>Purpose: </strong>This study evaluated beam quality and radiation dosimetry of a CT scanner equipped with a novel detector and filtration technology called PureVision Optics (PVO). PVO features miniaturized electronics, a detector cut with microblade technology, and increased filtration in order to increase x-ray detection and reduce image noise.</p><p><strong>Methods: </strong>We assessed the performance of two similar 320-detector CT scanners: one equipped with PVO and one without. Beam quality was measured by determining the half-value layer (HVL) and effective energy ( Eeff ) for both scanners using all tube voltages (80 kV, 100 kV, 120 kV, 135 kV) and bowtie filters (small, medium, large) available. Energy correction factors were identified for optically stimulated luminescent dosimeters (OSLDS) compared to a calibrated ionization chamber. Surface and internal doses were measured for an anthropomorphic CT angiography head phantom and a cadaver head scanned with CTDI vol matched as close as possible at the conventional (55.1 mGy) and PVO (55.4 mGy) CT scanners.</p><p><strong>Results: </strong>For all scan settings, the PVO scanner showed significantly higher HVL (range, 4.33-11.02 mm Al) and effective energy (range, 39.4-68.0 keV) values compared to the conventional scanner (HVL, 4.19-8.25 mm Al; effective energy, 38.4-55.2 keV). For equivalent CTDI vol values, the energy-corrected surface skin and lens doses were on average 6.7% lower with the PVO scanner than the conventional scanner ( P  < 0.01).</p><p><strong>Conclusions: </strong>PVO technology yielded higher HVL and effective energies and, for the same CTDI vol , resulted in lower surface organ doses, indicating a potential for reduced patient radiation exposure in clinical settings.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":"625-630"},"PeriodicalIF":1.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143059119","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":"Using Computed Tomography Coronary Angiography to Differentiate Atypical Cardiac Myxoma From Thrombus.","authors":"Nannan Zhang, Chuanqiang Lan, Zeliu Du, Guihan Lin, Yi Zhong, Jingle Fei, Kan Liu, Jiansong Ji, Chenying Lu","doi":"10.1097/RCT.0000000000001708","DOIUrl":"10.1097/RCT.0000000000001708","url":null,"abstract":"<p><strong>Objective: </strong>Atypical cardiac myxoma usually presents as an isolated mass attached to the atrial septum on imaging, with no movement and a wider attachment base. It is difficult to distinguish it from cardiac thrombus through conventional echocardiography or computed tomography (CT). The purpose of this study is to evaluate the value of CT coronary angiography imaging features in distinguishing atypical cardiac myxoma from cardiac thrombus.</p><p><strong>Materials and methods: </strong>This retrospective study included patients with atypical myxoma of the heart confirmed by histopathology (n = 18) and with thrombus disappearance after anticoagulation treatment (n = 23). All patients underwent a third-generation dual-source CT coronary angiography. We compared the clinical features and CT coronary angiography image characteristics of the 2 groups and used maximum-intensity projection and multiplanar reconstruction to show neovascularization of atypical cardiac myxoma.</p><p><strong>Results: </strong>There are significant differences in the origin, surface, and enhancement patterns between atypical cardiac myxoma and thrombus ( P < 0.05, respectively). Specifically, supplied vessels were observed in the atypical cardiac myxoma group, while no neovascularization was detected in the thrombus group (83.33% vs. 0%, P < 0.001).</p><p><strong>Conclusions: </strong>Noninvasive CT coronary angiography can help distinguish atypical cardiac myxoma and cardiac thrombus through imaging features, especially by detecting the supplying vessels. However, supplementary examinations such as cardiac magnetic resonance imaging are still needed to identify different cardiac tumors.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":"595-603"},"PeriodicalIF":1.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143500812","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":"Deep Learning-accelerated MRI in Body and Chest.","authors":"Naveen Rajamohan, Barun Bagga, Bhavik Bansal, Luke Ginocchio, Amit Gupta, Hersh Chandarana","doi":"10.1097/RCT.0000000000001762","DOIUrl":"10.1097/RCT.0000000000001762","url":null,"abstract":"<p><p>Deep learning reconstruction (DLR) provides an elegant solution for MR acceleration while preserving image quality. This advancement is crucial for body imaging, which is frequently marred by the increased likelihood of motion-related artifacts. Multiple vendor-specific models focusing on T2, T1, and diffusion-weighted imaging have been developed for the abdomen, pelvis, and chest, with the liver and prostate being the most well-studied organ systems. Variational networks with supervised DL models, including data consistency layers and regularizers, are the most common DLR methods. The common theme for all single-center studies on this subject has been noninferior or superior image quality metrics and lesion conspicuity to conventional sequences despite significant acquisition time reduction. DLR also provides a potential for denoising, artifact reduction, increased resolution, and increased signal-noise ratio (SNR) and contrast-to-noise ratio (CNR) that can be balanced with acceleration benefits depending on the imaged organ system. Some specific challenges faced by DLR include slightly reduced lesion detection, cardiac motion-related signal loss, regional SNR variations, and variabilities in ADC measurements as reported in different organ systems. Continued investigations with large-scale multicenter prospective clinical validation of DLR to document generalizability and demonstrate noninferior diagnostic accuracy with histopathologic correlation are the need of the hour. The creation of vendor-neutral solutions, open data sharing, and diversifying training data sets are also critical to strengthening model robustness.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":"531-544"},"PeriodicalIF":1.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144064127","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":"Combining Low-energy Images in Dual-energy Spectral CT With Deep Learning Image Reconstruction Algorithm to Improve Inferior Vena Cava Image Quality.","authors":"Wei Wei, Yongjun Jia, Ming Li, Nan Yu, Shan Dang, Jian Geng, Dong Han, Yong Yu, Yunsong Zheng, Lihua Fan","doi":"10.1097/RCT.0000000000001713","DOIUrl":"10.1097/RCT.0000000000001713","url":null,"abstract":"<p><strong>Objective: </strong>To explore the application of low-energy image in dual-energy spectral CT (DEsCT) combined with deep learning image reconstruction (DLIR) to improve inferior vena cava imaging.</p><p><strong>Materials and methods: </strong>Thirty patients with inferior vena cava syndrome underwent contrast-enhanced upper abdominal CT with routine dose, and the 40, 50, 60, 70, and 80 keV images in the delayed phase were first reconstructed with the ASiR-V40% algorithm. Image quality was evaluated both quantitatively [CT value, SD, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) for inferior vena cava] and qualitatively to select an optimal energy level with the best image quality. Then, the optimal-energy images were reconstructed again using deep learning image reconstruction medium strength (DLIR-M) and DLIR-H (high strength) algorithms and compared with that of ASiR-V40%.</p><p><strong>Results: </strong>The objective CT value, SD, SNR, and CNR increased with the decrease in energy level, with statistically significant differences (all P <0.05). The 40 keV images had the highest CT values, SNR, and CNR and good diagnostic acceptability, and 40 keV was selected as the best energy level. Compared with ASiR-V40% and DLIR-M, DLIR-H had the lowest SD, highest SNR and CNR, and subjective score (all P <0.001) with good consistencies between the 2 physicians (all k ≥0.75). The 40 keV images with DLIR-H had the highest overall image quality, showing sharper edges of inferior vena cava vessels and clearer lumen in patients with Budd-Chiari syndrome.</p><p><strong>Conclusions: </strong>Compared with the ASiR-V algorithm, DLIR-H significantly reduces image noise and provides the highest CNR and best diagnostic image quality for the 40 keV DEsCT images in imaging inferior vena cava.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":"604-610"},"PeriodicalIF":1.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12237118/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143059123","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":"Effect of Saline Sealing After CT-Guided Lung Biopsy on Pneumothorax and Hemoptysis.","authors":"Xiaoxia Zhang, Jianli An, Jingpeng Wu, Xiuxiu Jing, Hongzhi Lu, Ye Tian","doi":"10.1097/RCT.0000000000001725","DOIUrl":"10.1097/RCT.0000000000001725","url":null,"abstract":"<p><strong>Objective: </strong>To confirm that saline sealing of the needle trace after computed tomography (CT)-guided lung biopsy reduces the incidence of pneumothorax and chest tube insertion, and to observe its effects on pulmonary hemorrhage and hemoptysis.</p><p><strong>Materials and methods: </strong>Patients who underwent CT-guided lung biopsy at our hospital between January 2018 and January 2024 were included in the study. Patients were divided into 2 groups according to whether the needle trace was sealed with saline after tissue sampling. Patient baseline characteristics, lung lesion factors, procedural factors, pneumothorax rates, chest tube insertion rates, pulmonary hemorrhage rates, and hemoptysis rates were recorded.</p><p><strong>Results: </strong>The incidence of pneumothorax was 28.9% (38/132) and 15.8% (15/95) in groups A (control) and B (with sealed traces), respectively ( P =0.002). The incidence of pneumothorax requiring chest tube insertion was significantly lower in group B than in group A (1.1% vs. 6.8%; P =0.048). The incidence of pulmonary hemorrhage was similar between the 2 groups (38.6% vs. 42.1%; P =0.599). No significant difference was observed in the hemoptysis of patients in groups A and B (6.8% vs. 10.5%; P =0.320). In the binary logistic regression analysis, significant risk factors for pneumothorax included lack of saline sealing, smaller lesion size, multiple passes through the pleura, and the lateral decubitus position. Smaller lesions and longer biopsy trace lengths were independent risk factors for hemoptysis.</p><p><strong>Conclusions: </strong>Sealing the needle trace with saline significantly reduced the incidences of pneumothorax and chest tube insertion due to pneumothorax. Moreover, it did not significantly increase the incidence of pulmonary hemorrhage or hemoptysis. This technique is recommended for use in CT-guided lung biopsies.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":"640-645"},"PeriodicalIF":1.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143059098","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":"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":"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":"545-553"},"PeriodicalIF":1.0,"publicationDate":"2025-07-01","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}