Insights into Imaging最新文献

{"title":"Characterization of adrenal glands on computed tomography with a 3D V-Net-based model.","authors":"Yuanchong Chen, Yaofeng Zhang, Xiaodong Zhang, Xiaoying Wang","doi":"10.1186/s13244-025-01898-7","DOIUrl":"10.1186/s13244-025-01898-7","url":null,"abstract":"<p><strong>Objectives: </strong>To evaluate the performance of a 3D V-Net-based segmentation model of adrenal lesions in characterizing adrenal glands as normal or abnormal.</p><p><strong>Methods: </strong>A total of 1086 CT image series with focal adrenal lesions were retrospectively collected, annotated, and used for the training of the adrenal lesion segmentation model. The dice similarity coefficient (DSC) of the test set was used to evaluate the segmentation performance. The other cohort, consisting of 959 patients with pathologically confirmed adrenal lesions (external validation dataset 1), was included for validation of the classification performance of this model. Then, another consecutive cohort of patients with a history of malignancy (N = 479) was used for validation in the screening population (external validation dataset 2). Parameters of sensitivity, accuracy, etc., were used, and the performance of the model was compared to the radiology report in these validation scenes.</p><p><strong>Results: </strong>The DSC of the test set of the segmentation model was 0.900 (0.810-0.965) (median (interquartile range)). The model showed sensitivities and accuracies of 99.7%, 98.3% and 87.2%, 62.2% in external validation datasets 1 and 2, respectively. It showed no significant difference comparing to radiology reports in external validation datasets 1 and lesion-containing groups of external validation datasets 2 (p = 1.000 and p > 0.05, respectively).</p><p><strong>Conclusion: </strong>The 3D V-Net-based segmentation model of adrenal lesions can be used for the binary classification of adrenal glands.</p><p><strong>Critical relevance statement: </strong>A 3D V-Net-based segmentation model of adrenal lesions can be used for the detection of abnormalities of adrenal glands, with a high accuracy in the pre-surgical scene as well as a high sensitivity in the screening scene.</p><p><strong>Key points: </strong>Adrenal lesions may be prone to inter-observer variability in routine diagnostic workflow. The study developed a 3D V-Net-based segmentation model of adrenal lesions with DSC 0.900 in the test set. The model showed high sensitivity and accuracy of abnormalities detection in different scenes.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"16 1","pages":"17"},"PeriodicalIF":4.1,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11732807/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142978370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing safety in CT-guided lung biopsies: correlation of MinIP imaging with pneumothorax risk prediction.","authors":"Michael P Brönnimann, Leonie Manser, Bernhard Gebauer, Timo A Auer, Dirk Schnapauff, Federico Collettini, Alexander Pöllinger, Alois Komarek, Miltiadis E Krokidis, Johannes T Heverhagen","doi":"10.1186/s13244-024-01890-7","DOIUrl":"10.1186/s13244-024-01890-7","url":null,"abstract":"<p><strong>Objectives: </strong>This study aimed to evaluate whether minimum-intensity projection (MinIP) images could predict complications in CT-guided lung biopsies.</p><p><strong>Methods: </strong>We retrospectively analyzed 72 procedures from January 2019 to December 2023, categorizing patients by pneumothorax and the severity of hemorrhage (grade 2 or higher). Radiodensity measurements were performed using lung window (LW) and MinIP (10-mm slab) images. Regions of interest (ROIs) were placed at sites of the lowest density along the biopsy pathway. Absolute values were recorded, categorized by a radiodensity level of -850 HU, and assessed using our bridged radiological observations with measurement-optimized model (BROM-OLB) model with validation from three additional ROIs. Emphysema was visually scored. Statistical analysis included univariate analysis (Fisher's exact and Mann-Whitney U-tests) and binomial logistic regression to identify confounders.</p><p><strong>Results: </strong>Lower radiodensity values in MinIP images in the access route, particularly with the BROM-OLB MinIP method, were significantly associated with a higher risk of pneumothorax (5/39, 13% vs 27/33, 82%, p < 0.01; Sensitivity 81.8% and Specificity 87.2%). Pneumothorax was more common with longer procedures (p < 0.05). Lower LW density values correlated with higher pulmonary hemorrhage rates (p < 0.01). Binomial logistic regression identified positive BROM-OLB MinIP results (OR 28.244, 95% CI: 7.675-103.9, p < 0.01) and lower LW density (OR 0.992, 95% CI: 0.985-0.999, p = 0.025) as independent risk factors. The optimal threshold values to predict pneumothorax were -868 HU in MinIP images and -769 HU in LW.</p><p><strong>Conclusion: </strong>The assessment of MinIP images is superior, and in combination with relative quantitative measurement of radiodensity for access route planning, it can reduce the risk of pneumothorax in CT-guided lung biopsies.</p><p><strong>Critical relevance statement: </strong>This article critically evaluates the risk factors for complications in CT-guided lung biopsies, highlighting the potential of MinIP images for predicting pneumothorax risk, thereby advancing clinical radiology practices to improve patient safety and reduce healthcare costs.</p><p><strong>Key points: </strong>This work investigates if MinIP images efficiently predict CT-guided lung biopsy complications. MinIP imaging identified higher pneumothorax risk post-CT lung biopsy with superior accuracy. Our method detects high-risk lung changes linked to pneumothorax without additional software.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"16 1","pages":"16"},"PeriodicalIF":4.1,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11730046/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142969801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Critical reflection on the indication for computed tomography: an interdisciplinary survey of risk and benefit management in patients with sepsis.","authors":"Maria Isabel Opper Hernando, Denis Witham, Ann-Christine Stahl, Peter Richard Steinhagen, Stefan Angermair, Wolfgang Bauer, Friederike Compton, Andreas Edel, Jan Matthias Kruse, York Kühnle, Gunnar Lachmann, Susanne Marz, Holger Müller-Redetzky, Jens Nee, Oliver Paul, Damaris Praeger, Carsten Skurk, Miriam Stegemann, Alexander Uhrig, Stefan Wolf, Myrto Bolanaki, Kerstin Rubarth, Joachim Seybold, Elke Zimmermann, Marc Dewey, Julian Pohlan","doi":"10.1186/s13244-024-01894-3","DOIUrl":"10.1186/s13244-024-01894-3","url":null,"abstract":"<p><strong>Objectives: </strong>To survey physicians' views on the risks and benefits of computed tomography (CT) in the management of septic patients and indications for and contraindications to contrast media use in searching for septic foci.</p><p><strong>Methods: </strong>A web-based questionnaire was administered to physicians at a large European university medical center in January 2022. A total of 371 questionnaires met the inclusion criteria and were analyzed with physicians' work experience, workplace, and medical specialty as independent variables. Chi-square tests were used for exploratory analysis.</p><p><strong>Results: </strong>While physicians with all levels of work experience were included, the largest group (35.0%, n = 130/371) had 3-7 years of experience. Most physicians agreed that the benefits of CT outweigh its potential adverse effects in septic patients (90.5%, n = 336/371). Responders saw the strongest indication for contrast media administration in septic patients for (1) CT examinations of the abdomen (92.7%, n = 333/359) and (2) combined CT examinations of the chest, abdomen, and pelvis (94.1%, n = 337/358). While radiologists were most likely to consider manifest hyperthyroidism an absolute contraindication to contrast media administration (43.8%, n = 14/32), most other groups of physicians opted for appropriate preparation before contrast media administration in this subset of septic patients.</p><p><strong>Conclusion: </strong>In this survey, most participating physicians considered CT an essential diagnostic modality to detect an infectious focus in septic patients. Whereas the risk of ionizing radiation was regarded as justifiable by most physicians, different specialties varied in their assessment of the risks of contrast media administration.</p><p><strong>Key points: </strong>Physicians recognize CT as a relevant imaging modality in the diagnostic management of patients with sepsis. There is an interdisciplinary consensus that the use of ionizing radiation is justified in septic patients. There is disagreement about indications for and contraindications to contrast media administration among physicians from different medical specialties.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"16 1","pages":"15"},"PeriodicalIF":4.1,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11730041/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142970623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automatic segmentation model and machine learning model grounded in ultrasound radiomics for distinguishing between low malignant risk and intermediate-high malignant risk of adnexal masses.","authors":"Lu Liu, Wenjun Cai, Feibo Zheng, Hongyan Tian, Yanping Li, Ting Wang, Xiaonan Chen, Wenjing Zhu","doi":"10.1186/s13244-024-01874-7","DOIUrl":"10.1186/s13244-024-01874-7","url":null,"abstract":"<p><strong>Objective: </strong>To develop an automatic segmentation model to delineate the adnexal masses and construct a machine learning model to differentiate between low malignant risk and intermediate-high malignant risk of adnexal masses based on ovarian-adnexal reporting and data system (O-RADS).</p><p><strong>Methods: </strong>A total of 663 ultrasound images of adnexal mass were collected and divided into two sets according to experienced radiologists: a low malignant risk set (n = 446) and an intermediate-high malignant risk set (n = 217). Deep learning segmentation models were trained and selected to automatically segment adnexal masses. Radiomics features were extracted utilizing a feature analysis system in Pyradiomics. Feature selection was conducted using the Spearman correlation analysis, Mann-Whitney U-test, and least absolute shrinkage and selection operator (LASSO) regression. A nomogram integrating radiomic and clinical features using a machine learning model was established and evaluated. The SHapley Additive exPlanations were used for model interpretability and visualization.</p><p><strong>Results: </strong>The FCN ResNet101 demonstrated the highest segmentation performance for adnexal masses (Dice similarity coefficient: 89.1%). Support vector machine achieved the best AUC (0.961, 95% CI: 0.925-0.996). The nomogram using the LightGBM algorithm reached the best AUC (0.966, 95% CI: 0.927-1.000). The diagnostic performance of the nomogram was comparable to that of experienced radiologists (p > 0.05) and outperformed that of less-experienced radiologists (p < 0.05). The model significantly improved the diagnostic accuracy of less-experienced radiologists.</p><p><strong>Conclusions: </strong>The segmentation model serves as a valuable tool for the automated delineation of adnexal lesions. The machine learning model exhibited commendable classification capability and outperformed the diagnostic performance of less-experienced radiologists.</p><p><strong>Critical relevance statement: </strong>The ultrasound radiomics-based machine learning model holds the potential to elevate the professional ability of less-experienced radiologists and can be used to assist in the clinical screening of ovarian cancer.</p><p><strong>Key points: </strong>We developed an image segmentation model to automatically delineate adnexal masses. We developed a model to classify adnexal masses based on O-RADS. The machine learning model has achieved commendable classification performance. The machine learning model possesses the capability to enhance the proficiency of less-experienced radiologists. We used SHapley Additive exPlanations to interpret and visualize the model.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"16 1","pages":"14"},"PeriodicalIF":4.1,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11729609/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142970615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ultra-low dose dual-layer detector spectral CT for pulmonary nodule screening: image quality and diagnostic performance.","authors":"Li Ding, Mingwang Chen, Xiaomei Li, Yuting Wu, Jingxu Li, Shuting Deng, Yikai Xu, Zhao Chen, Chenggong Yan","doi":"10.1186/s13244-024-01888-1","DOIUrl":"10.1186/s13244-024-01888-1","url":null,"abstract":"<p><strong>Objectives: </strong>To investigate the image quality and diagnostic performance with ultra-low dose dual-layer detector spectral CT (DLSCT) by various reconstruction techniques for evaluation of pulmonary nodules.</p><p><strong>Materials and methods: </strong>Between April 2023 and December 2023, patients with suspected pulmonary nodules were prospectively enrolled and underwent regular-dose chest CT (RDCT; 120 kVp/automatic tube current) and ultra-low dose CT (ULDCT; 100 kVp/10 mAs) on a DLSCT scanner. ULDCT was reconstructed with hybrid iterative reconstruction (HIR), electron density map (EDM), and virtual monoenergetic images at 40 keV and 70 keV. Quantitative and qualitative image analysis, nodule detectability, and Lung-RADS evaluation were compared using repeated one-way analysis of variance, Friedman test, and weighted kappa coefficient.</p><p><strong>Results: </strong>A total of 249 participants (mean age ± standard deviation, 50.0 years ± 12.9; 126 male) with 637 lung nodules were included. ULDCT resulted in a significantly lower mean radiation dose than RDCT (0.3 mSv ± 0.0 vs. 3.6 mSv ± 0.8; p < 0.001). Compared with RDCT, ULDCT EDM showed significantly higher signal-noise-ratio (44.0 ± 77.2 vs. 4.6 ± 6.6; p < 0.001) and contrast-noise-ratio (26.7 ± 17.7 vs. 5.0 ± 4.4; p < 0.001) with qualitative scores ranked higher or equal to the average. Using the regular-dose images as a reference, ULDCT EDM images had a satisfactory nodule detection rate (84.6%) and good inter-observer agreements compared with RDCT (κw > 0.60).</p><p><strong>Conclusion: </strong>Ultra-low dose dual-layer detector CT with 91.2% radiation dose reduction achieves sufficient image quality and diagnostic performance of pulmonary nodules.</p><p><strong>Critical relevance statement: </strong>Dual-layer detector spectral CT enables substantial radiation dose reduction without impairing image quality for the follow-up of pulmonary nodules or lung cancer screening.</p><p><strong>Key points: </strong>Radiation dose is a major concern for patients requiring pulmonary nodules CT screening. Ultra-low dose dual-layer detector spectral CT with 91.2% dose reduction demonstrated satisfactory performance. Dual-layer detector spectral CT has the potential for lung cancer screening and management.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"16 1","pages":"11"},"PeriodicalIF":4.1,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11723867/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142947949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decreased attenuation difference between non-contrast and portal-venous phases of CT predicts the ultrasonography-unspecified adnexal torsion.","authors":"Weili Xie, Zhongren Huang, Hongmei Kuang, Xiaoxing Li, Rixin Zhang, Wei Zeng, Cheng Jin, Junyuan Zhong, Jidong Peng, Weiling Cheng, Fuqing Zhou","doi":"10.1186/s13244-024-01885-4","DOIUrl":"10.1186/s13244-024-01885-4","url":null,"abstract":"<p><strong>Objectives: </strong>To evaluate the value of contrast-enhanced CT in diagnosing ultrasonography-unspecified adnexal torsion (AT).</p><p><strong>Methods: </strong>Surgically confirmed patients with painful pelvic masses (n = 165) were retrospectively collected from two institutes. Two senior radiologists independently reviewed the CT images and determined the Hounsfield unit difference between non-contrast vs portal venous phases (ΔHU_PV-NC) in both derivation and validation samples. The cutoff value, sensitivity, specificity, predictivity, and reproducibility of the ΔHU_PV-NC and other visually assessed CT signs were analyzed and compared using the receiver-operating characteristic curve, multivariable regression, and inter-rater agreement assays, respectively.</p><p><strong>Results: </strong>Women with twisted (n = 73 [47 ± 19 years]) or untwisted (n = 92 [40 ± 15 years]) adnexal lesions were reviewed. The ΔHU_PV-NC ≤ 17.5 HU (AUC: 0.91 [95% CI: 0.86, 0.96]; sensitivity: 95% [95% CI: 87, 98]; and specificity: 88% [95% CI: 80, 94]) was the independent predictor of AT (OR: 137 [95% CI: 39, 481], p < 0.001). After training in ΔHU_PV-NC measurement, the agreement between two junior residents and the consensus increased from fair (resident-1: 0.29 [95% CI: 0.17, 0.41]; resident-2: 0.24 [95% CI: 0.1, 0.39]) to substantial (resident-1: 0.75 [95% CI: 0.65, 0.85]; resident-2: 0.72 [95% CI: 0.62, 0.83]). The post-training diagnostic accuracy (both residents: 81% [95% CI: 74, 87]) was higher than the pre-training accuracy (resident-1: 67% [95% CI: 59, 74], p = 0.007; resident-2: 66% [95% CI: 58, 73], p = 0.002).</p><p><strong>Conclusion: </strong>The sign of ΔHU_PV-NC ≤ 17.5 HU in contrast-enhanced CT can be used to predict the ultrasonography-unspecified AT.</p><p><strong>Critical relevance statement: </strong>The decreased attenuation difference between non-contrast vs portal venous phases, a quantitative measurement-based CT sign, highlights the value of using contrast-enhanced CT as a second-line imaging approach after an equivocal ultrasonographic examination to diagnose AT in emergency settings.</p><p><strong>Key points: </strong>The value of contrast-enhanced CT in diagnosing ultrasonography-unspecified AT is underestimated. The ΔHU_PV-NC ≤ 17.5 HU is the only predictor to diagnose the ultrasonography-unspecified AT. Contrast-enhanced CT can be used as a second-line imaging approach after an equivocal ultrasonographic examination.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"16 1","pages":"12"},"PeriodicalIF":4.1,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11723866/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142948259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficacy of bolus injections of landiolol hydrochloride as premedication in coronary artery CT angiography.","authors":"Mark Barwig, Michael Janisch, Johannes Gessl, Wolfgang Kübler, Christopher König, Gerold Schwantzer, Helmut Schöllnast","doi":"10.1186/s13244-024-01892-5","DOIUrl":"10.1186/s13244-024-01892-5","url":null,"abstract":"<p><strong>Purpose: </strong>To assess the efficacy of bolus injections of landiolol hydrochloride as premedication in coronary artery CT angiography (CCTA).</p><p><strong>Methods: </strong>The study population consisted of 37 patients (17 female; median age, 56 years; IQR, 19 years; range, 19-88 years) who underwent CCTA after intravenous injection of landiolol hydrochloride due to a heart rate > 60 bpm. Landiolol hydrochloride was administered in a stepwise manner until a heart rate of ≤ 60 bpm was achieved or a maximum dose of 60 mg was reached after six injections. Heart rates routinely displayed continuously on the CT scanner before the start of the landiolol hydrochloride injection (HR_PRE), after each partial dose (HR_1-6), during the CT scan (HR_CT), and after the examination before moving from the CT table (HR_POST) were recorded. Furthermore, the blood pressure routinely measured before (BP_PRE) and after the examination before moving from the CT table (BP_POST) was recorded.</p><p><strong>Results: </strong>A HR_CT of ≤ 60 bpm was achieved in 13 patients (35%) and a HR_CT ≤ 65 bpm was achieved in 25 patients (68%). The mean difference (± SD) between HR_PRE and HR_CT was -11 ± 9 bpm in total, -14 ± 10 bpm in patients without oral beta-blocker premedication and -6 ± 5 bpm in patients with oral Beta-blocker premedication.</p><p><strong>Conclusions: </strong>Landiolol hydrochloride enables a reduction of the heart rate in patients with and without oral beta-blocker premedication, whereby the use of serial partial doses is a simple and effective approach in clinical routine.</p><p><strong>Critical relevance statement: </strong>In cardiac CT, weight-independent, stepwise landiolol hydrochloride injection up to 40 mg reduces heart rate by -14 bpm without and -5 bpm with oral beta-blocker premedication, and achieves heart rates of ≤ 65 bpm in a significant proportion of patients.</p><p><strong>Key points: </strong>The ideal heart rate for cardiac CT is ≤ 60-65 bpm, which improves image quality and reduces radiation dose. In cardiac CT, landiolol hydrochloride intravenously reduces heart rate by -14 bpm. Heart rate of ≤ 65 bpm can be achieved in a significant proportion of patients.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"16 1","pages":"13"},"PeriodicalIF":4.1,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11723858/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142948175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fluoroscopy-guided aspiration of the acutely dislocated total hip arthroplasty: a feasible, high-yield, and safe procedure.","authors":"Dyan V Flores, Abdullah Felemban, Taryn Hodgdon, Paul Beaulé, George Grammatopolous, Kawan S Rakhra","doi":"10.1186/s13244-024-01880-9","DOIUrl":"10.1186/s13244-024-01880-9","url":null,"abstract":"<p><strong>Objective: </strong>To determine the feasibility, yield, and safety of fluoroscopic-guided aspiration of the acutely dislocated total hip arthroplasty (AD-THA).</p><p><strong>Materials and methods: </strong>IRB-approved, retrospective review of fluoroscopic-guided aspirations of AD-THA (January 2005-December 2023) was performed. Data from electronic charts and fluoroscopy images/reports were obtained. Positive yield was defined as spontaneous aspirate or saline rinse adequate for microbiology analysis. Sub-analysis by needle target (acetabular cup or femur) was performed for spontaneous aspiration rate, aspirate volume and fluoroscopy time. Differences between groups were analyzed with unpaired, t-test (2-tail) and between proportions with Fisher's exact test, with significance p < 0.05.</p><p><strong>Results: </strong>Aspiration of 20 AD-THA in 19 patients (12 female, mean age (SD) of 73 years (16)) targeted the acetabular cup in 45% (9/20) or femur in 55% (11/20) of cases. Positive yield was obtained in 95% (19/20), with spontaneous aspirate in 75% (15/20) and saline rinse in 20% (4/20) of cases; in 5% (1/20), no diagnostic sample was obtained. Spontaneous aspirate mean volume (SD, range) for all cases was 8.3 mL (6.9, 0.2-25), and higher when targeting the acetabular cup 11.2 mL (6.9, 5-25) versus the femur 4.0 mL (4.4, 0.2-12) (p = 0.026). The rate of spontaneous aspiration was higher for the acetabular cup 100% (9/9) versus the femur 55% (6/11) (p = 0.038). The mean fluoroscopy time (SD, range) for all cases was 43 s (25, 19-102), and shorter for targeting the acetabular cup 32 s (16, 19-75) versus the femur 56 s (28, 28-102) (p = 0.034). No immediate complications occurred in all aspirations.</p><p><strong>Conclusion: </strong>Fluoroscopy-guided aspiration of AD-THA is a feasible, high-yield, and safe procedure. Targeting the acetabular cup results in a higher rate of spontaneous aspirate, larger aspiration volume, and lower fluoroscopy time.</p><p><strong>Critical relevance statement: </strong>Although technically more challenging, radiologists should feel confident aspirating the acutely dislocated total hip arthroplasty (AD-THA) under fluoroscopic guidance.</p><p><strong>Key points: </strong>Total hip arthroplasty (THA) infection can be evaluated with synovial fluid aspiration. Fluoroscopic-guided aspiration of the dislocated THA is feasible, high-yield, and safe. Targeting of the acetabular cup is recommended over the femoral prosthetic component. Acetabular cup targeting gives larger, spontaneous aspirates with lower fluoroscopy time.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"16 1","pages":"9"},"PeriodicalIF":4.1,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11723859/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142948176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of deep learning model based on unenhanced chest CT for opportunistic screening of osteoporosis: a multicenter retrospective cohort study.","authors":"Chengbin Huang, Dengying Wu, Bingzhang Wang, Chenxuan Hong, Jiasen Hu, Zijian Yan, Jianpeng Chen, Yaping Jin, Yingze Zhang","doi":"10.1186/s13244-024-01817-2","DOIUrl":"10.1186/s13244-024-01817-2","url":null,"abstract":"<p><strong>Introduction: </strong>A large number of middle-aged and elderly patients have an insufficient understanding of osteoporosis and its harm. This study aimed to establish and validate a convolutional neural network (CNN) model based on unenhanced chest computed tomography (CT) images of the vertebral body and skeletal muscle for opportunistic screening in patients with osteoporosis.</p><p><strong>Materials and methods: </strong>Our team retrospectively collected clinical information from participants who underwent unenhanced chest CT and dual-energy X-ray absorptiometry (DXA) examinations between January 1, 2022, and December 31, 2022, at four hospitals. These participants were divided into a training set (n = 581), an external test set 1 (n = 229), an external test set 2 (n = 198) and an external test set 3 (n = 118). Five CNN models were constructed based on chest CT images to screen patients with osteoporosis and compared with the SMI model to predict the performance of osteoporosis patients.</p><p><strong>Results: </strong>All CNN models have good performance in predicting osteoporosis patients. The average F1 score of Densenet121 in the three external test sets was 0.865. The area under the curve (AUC) of Desenet121 in external test set 1, external test set 2, and external test set 3 were 0.827, 0.859, and 0.865, respectively. Furthermore, the Densenet121 model demonstrated a notably superior performance compared to the SMI model in predicting osteoporosis patients.</p><p><strong>Conclusions: </strong>The CNN model based on unenhanced chest CT vertebral and skeletal muscle images can opportunistically screen patients with osteoporosis. Clinicians can use the CNN model to intervene in patients with osteoporosis and promptly avoid fragility fractures.</p><p><strong>Critical relevance statement: </strong>The CNN model based on unenhanced chest CT vertebral and skeletal muscle images can opportunistically screen patients with osteoporosis. Clinicians can use the CNN model to intervene in patients with osteoporosis and promptly avoid fragility fractures.</p><p><strong>Key points: </strong>The application of unenhanced chest CT is increasing. Most people do not consciously use DXA to screen themselves for osteoporosis. A deep learning model was constructed based on CT images from four institutions.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"16 1","pages":"10"},"PeriodicalIF":4.1,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11723875/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142948258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating CT-based radiomics and clinical features to better predict the prognosis of acute pancreatitis.","authors":"Hang Chen, Yao Wen, Xinya Li, Xia Li, Liping Su, Xinglan Wang, Fang Wang, Dan Liu","doi":"10.1186/s13244-024-01887-2","DOIUrl":"10.1186/s13244-024-01887-2","url":null,"abstract":"<p><strong>Objectives: </strong>To develop and validate the performance of CT-based radiomics models for predicting the prognosis of acute pancreatitis.</p><p><strong>Methods: </strong>All 344 patients (51 ± 15 years, 171 men) in a first episode of acute pancreatitis (AP) were retrospectively enrolled and randomly divided into training (n = 206), validation (n = 69), and test (n = 69) sets with the ratio of 6:2:2. The patients were dichotomized into good and poor prognosis subgroups based on follow-up CT and clinical data. The radiomics features were extracted from contrast-enhanced CT. Logistic regression analysis was applied to analyze clinical-radiological features for developing clinical and radiomics-derived models. The predictive performance of each model was evaluated using the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA).</p><p><strong>Results: </strong>Eight pancreatic and six peripancreatic radiomics features were identified after reduction and selection. In the training set, the AUCs of clinical, pancreatic, peripancreatic, radiomics, and combined models were 0.859, 0.800, 0.823, 0.852, and 0.899, respectively. In the validation set, the AUCs were 0.848, 0.720, 0.746, 0.773, and 0.877, respectively. The combined model exhibited the highest AUC among radiomics-based models (pancreatic, peripancreatic, and radiomics models) in both the training (0.899) and validation (0.877) sets (all p < 0.05). Further, the AUC of the combined model was 0.735 in the test set. The calibration curve and DCA indicated the combined model had favorable predictive performance.</p><p><strong>Conclusions: </strong>CT-based radiomics incorporating clinical features was superior to other models in predicting AP prognosis, which may offer additional information for AP patients at higher risk of developing poor prognosis.</p><p><strong>Critical relevance statement: </strong>Integrating CT radiomics-based analysis of pancreatic and peripancreatic features with clinical risk factors enhances the assessment of AP prognosis, allowing for optimal clinical decision-making in individuals at risk of severe AP.</p><p><strong>Key points: </strong>Radiomics analysis provides help to accurately assess acute pancreatitis (AP). CT radiomics-based models are superior to the clinical model in the prediction of AP prognosis. A CT radiomics-based nomogram integrated with clinical features allows a more comprehensive assessment of AP prognosis.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"16 1","pages":"8"},"PeriodicalIF":4.1,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11717748/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142946870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}