Radiology. Cardiothoracic imaging最新文献

{"title":"Intercostal Nerve Protection Using Extrapleural Air during Percutaneous Cryoablation of Peripheral Lung Tumors.","authors":"Julian A Westphal, Alexander Graur, Florian J Fintelmann","doi":"10.1148/ryct.250057","DOIUrl":"https://doi.org/10.1148/ryct.250057","url":null,"abstract":"<p><p>Purpose To assess the feasibility of extrapleural air injection as a simple technique to protect intercostal nerves against thermal injury during image-guided percutaneous cryoablation of peripheral lung tumors. Materials and Methods This retrospective single-center interventional cohort study analyzed data from patients who underwent cryoablation of peripheral lung tumors combined with air injection deep to the endothoracic fascia between August 2022 and November 2024. Technical success was defined as the presence of extrapleural air at the level of the shortest tumor-pleura distance on intraprocedural CT images. Patients were evaluated for pain, pneumothorax, and hemoptysis immediately following and at 1 day, 1 week, and 1 month after the procedure. Adverse events were graded according to the Common Terminology Criteria for Adverse Events (CTCAE) version 5.0. Results Injection of extrapleural air deep to the endothoracic fascia was performed during 27 sessions targeting 31 lung tumors (81% [25 of 31] of metastases from extrathoracic primary malignancies; median tumor size, 9.0 mm; range, 4.0-35.0 mm) in 26 patients (mean age, 64 years ± 15 [SD]; 17 female; Eastern Cooperative Oncology Group performance status 0-2). Technical success was achieved in 24 sessions (89%; 24 of 27 [95% CI: 72, 96]). No adverse events related to extrapleural air injection occurred. Among patients with successful air injection, none reported intercostal neuralgia. No adverse events with a CTCAE grade of 4 or higher occurred. Conclusion This study suggests feasibility of extrapleural air injection into the endothoracic fascia as a simple technique to protect intercostal nerves from thermal injury during cryoablation of peripheral lung tumors. <b>Keywords:</b> Lung Tumors, Image-guided Thermal Ablation, Percutaneous Cryoablation, Intercostal Neuralgia, Cryosurgery, Ablation Techniques, Percutaneous, Thorax, Lung © RSNA, 2025.</p>","PeriodicalId":21168,"journal":{"name":"Radiology. Cardiothoracic imaging","volume":"7 5","pages":"e250057"},"PeriodicalIF":4.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145302944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cardiovascular MRI Feature-Tracking Strain Rate for Assessment of Diastolic Function.","authors":"Jian L Yeo, Abhishek Dattani, Aseel Alfuhied, Anna-Marie Marsh, Kelly S Parke, Sarah L Ayton, Lavanya Athithan, Joanna M Bilak, Alastair J Moss, Emer M Brady, J Ranjit Arnold, Prathap Kanagala, Christopher D Steadman, Matthew P M Graham-Brown, Melanie J Davies, Anvesha Singh, Iain B Squire, Leong L Ng, Gaurav S Gulsin, Gerry P McCann","doi":"10.1148/ryct.240447","DOIUrl":"https://doi.org/10.1148/ryct.240447","url":null,"abstract":"<p><p>Purpose To compare left ventricular (LV) peak early diastolic strain rate (PEDSR) and peak late diastolic strain rate (PLDSR) using cardiac MRI feature tracking (FT) across a spectrum of diastolic dysfunction and determine the association between diastolic strain rates and cardiac remodeling. Materials and Methods Between October 2008 and December 2022, cardiac MRI and echocardiography were performed in prospectively recruited cohorts with type 2 diabetes mellitus, heart failure with preserved ejection fraction, and severe aortic stenosis, as well as asymptomatic participants without diabetes. Diastolic dysfunction was classified using established echocardiography guidelines. Global circumferential and longitudinal PEDSR and PLDSR were measured at cardiac MRI. Linear regression was performed to identify independent associations between LV diastolic strain rates and remodeling. Results A total of 600 participants (mean age, 65.2 years ± 8.4 [SD]; 361 of 600 male participants [60%]) were included. Proportions of participants with normal diastolic function and those with grade 1, indeterminate, and grade 2 or 3 diastolic dysfunction were 92 of 600 (15%), 401 of 600 (67%), 85 of 600 (14%), and 22 of 600 (4%), respectively. Compared with participants who had normal function, PEDSR decreased in those with grade 1 dysfunction (circumferential PEDSR, 0.99 sec^-1 ± 0.22 vs 0.81 sec^-1 ± 0.24 [<i>P</i> < .001]; longitudinal PEDSR, 0.79 sec^-1 ± 0.19 vs 0.60 sec^-1 ± 0.19 [<i>P</i> < .001]) and remained low throughout worsening stages of diastolic dysfunction. In contrast, compared with participants who had normal diastolic function, PLDSR increased in those with grade 1 dysfunction (circumferential PLDSR, 0.70 sec^-1 ± 0.17 vs 0.82 sec^-1 ± 0.23 [<i>P</i> < .001]; longitudinal PLDSR, 0.73 sec^-1 ± 0.18 vs 0.80 sec^-1 ± 0.27 [<i>P</i> < .001]) and declined progressively with worsening diastolic dysfunction. After multivariable adjustment for risk factors, inverse associations persisted between PEDSR and PLDSR with cardiac remodeling. Conclusion A distinctive pattern of cardiac MRI FT early and late diastolic strain rates was observed across the range of diastolic dysfunction. <b>Keywords:</b> Diastolic Dysfunction, Peak Early Diastolic Strain Rate, Peak Late Diastolic Strain Rate, Feature Tracking <i>Supplemental material is available for this article.</i> © The Author(s) 2025. Published by the Radiological Society of North America under a CC BY 4.0 license.</p>","PeriodicalId":21168,"journal":{"name":"Radiology. Cardiothoracic imaging","volume":"7 5","pages":"e240447"},"PeriodicalIF":4.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145207490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing Xenon 129 Ventilation MRI in Cystic Fibrosis with Spiral Imaging and Flip-Angle Correction.","authors":"Riaz Hussain, Joseph W Plummer, Abdullah S Bdaiwi, Matthew M Willmering, Elizabeth L Kramer, Laura L Walkup, Zackary I Cleveland","doi":"10.1148/ryct.240574","DOIUrl":"https://doi.org/10.1148/ryct.240574","url":null,"abstract":"&lt;p&gt;&lt;p&gt;Purpose To implement and evaluate two-dimensional spiral hyperpolarized xenon 129 (&lt;sup&gt;129&lt;/sup&gt;Xe) ventilation MRI with flip-angle (FA) correction, as compared with conventional N4ITK (N4) correction, in healthy individuals and those with cystic fibrosis (CF). Materials and Methods In this prospective study, participants with mild CF and age-matched healthy control participants underwent &lt;sup&gt;129&lt;/sup&gt;Xe ventilation MRI using both rapid spiral (approximately 3 seconds) and conventional Cartesian (approximately 10 seconds) acquisitions. Images were corrected using N4 bias correction, and ventilation defect percentage (VDP) was calculated using median-anchored generalized linear binning (mGLB). Separately, B&lt;sub&gt;1&lt;/sub&gt; inhomogeneities in spiral images were FA-corrected and analyzed using mGLB. Gravitational gradients in ventilation were quantified from uncorrected and N4- and FA-corrected images in healthy participants. VDP from N4-corrected (VDP&lt;sub&gt;N4&lt;/sub&gt;) and FA-corrected (VDP&lt;sub&gt;FA&lt;/sub&gt;) images were compared between participant groups and against reader-segmented VDP (VDP&lt;sub&gt;RS&lt;/sub&gt;). Statistical analyses included Wilcoxon signed rank test, Pearson correlation, and Bland-Altman analysis. Results The final analysis included 38 participants with CF (mean age, 16 years ± 6 [SD]; 20 female) and 25 healthy controls (mean age, 18 years ± 7; 13 male). Qualitatively, Cartesian and spiral acquisitions produced similar regional ventilation images. There was no evidence of a difference in VDP&lt;sub&gt;N4&lt;/sub&gt; between acquisition types (Cartesian = 9.1% ± 8.1; spiral = 9.3% ± 8.7; &lt;i&gt;P&lt;/i&gt; = .97) with strong correlation (&lt;i&gt;r&lt;/i&gt;&lt;sup&gt;2&lt;/sup&gt; = 0.95; &lt;i&gt;P&lt;/i&gt; &lt; .001) and no systemic bias (mean difference, -0.2%; 95% CI: 3.6, -3.9). FA correction removed coil-related inhomogeneities while preserving physiologic heterogeneity, including gravitational gradients that were removed by N4 correction (mean slope in healthy participants: FA-corrected = 0.026 &lt;i&gt;S&lt;/i&gt;&lt;sub&gt;Norm&lt;/sub&gt;/cm ± 0.013; N4-corrected = 0.002 &lt;i&gt;S&lt;/i&gt;&lt;sub&gt;Norm&lt;/sub&gt;/cm ± 0.001; &lt;i&gt;P&lt;/i&gt; &lt; .001). VDP&lt;sub&gt;N4&lt;/sub&gt; and VDP&lt;sub&gt;FA&lt;/sub&gt; were strongly correlated with VDP&lt;sub&gt;RS&lt;/sub&gt; (&lt;i&gt;r&lt;/i&gt;&lt;sup&gt;2&lt;/sup&gt; = 0.94 and 0.95, respectively; &lt;i&gt;P&lt;/i&gt; &lt; .001 for both). Defect masks from FA-corrected images showed better agreement with reader segmentations compared with N4-corrected image-based defect masks (17% higher Dice score from FA-corrected images; mean Dice score: N4-corrected, 0.41 ± 0.31; FA-corrected, 0.48 ± 0.29; &lt;i&gt;P&lt;/i&gt; =.001) and better depicted regional hypo- and hyperventilation. Conclusion Two-dimensional spiral acquisition combined with FA correction and mGLB analysis enabled rapid &lt;sup&gt;129&lt;/sup&gt;Xe ventilation MRI, effectively mitigating inhomogeneities while preserving physiologic heterogeneity. This approach provided accurate and efficient quantification of ventilation abnormalities in both healthy individuals and individuals with CF. &lt;b&gt;Keywords:&lt;/b&gt; MRI, Pulmonary, Lung, Xe","PeriodicalId":21168,"journal":{"name":"Radiology. Cardiothoracic imaging","volume":"7 5","pages":"e240574"},"PeriodicalIF":4.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145207508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Deep Learning-based Artificial Intelligence Assistance on Reader Agreement in Coronary CT Angiography Interpretation.","authors":"Roberto Farì, Marly van Assen, Raymundo Quintana, Philipp von Knebel Doeberitz, Benjamin Böttcher, Guido Ligabue, Alex Rezai, Max Schoebinger, George S K Fung, Carlo N De Cecco","doi":"10.1148/ryct.240563","DOIUrl":"https://doi.org/10.1148/ryct.240563","url":null,"abstract":"<p><p>Purpose To evaluate the impact of a fully automated, multitask deep learning (DL) algorithm on interreader agreement of coronary artery disease (CAD) detection and stenosis classification using coronary CT angiography (CCTA). Materials and Methods This retrospective study included CCTA examinations (<i>n</i> = 623 patients) performed for clinical indications on CT systems from multiple vendors between January 2010 and December 2019. An expert reader (reader 1) analyzed all CCTA scans manually and with artificial intelligence (AI)-assisted reading at the lesion, coronary segment, and patient levels using the CAD Reporting and Data System (CAD-RADS). The AI algorithm detected, quantified, and classified coronary lesions. Interreader agreement was evaluated using a second expert reader (reader 2), who analyzed a randomly selected subset of 274 patients. CAD-RADS scores from radiologist reports (reader 3) were available for 362 patients. In a subgroup of 30 patients with disagreements, R2 also interpreted the cases using AI assistance. Agreement between readings, with and without AI, was assessed using Spearman correlation, and logistic regression and mixed models evaluated the impact of AI-assisted reading on CAD-RADS classification. Results The final study sample included 11 214 coronary segments analyzed from 623 patients (mean age ± SD, 54.8 years ± 15.7; 341 male). Of these patients, 295 (47.9%) had no CAD (CAD-RADS 0), 213 (33.6%) had low risk of coronary obstruction (CAD-RADS < 3), and 115 (18.5%) had high risk of obstructive disease (CAD-RADS ≥ 3). With AI assistance, reader 1 demonstrated improved agreement with reader 2 (ρ = 0.899-0.949; <i>P</i> < .001) and reader 3 (ρ = 0.889-0.938; <i>P</i> < .001). In the subgroup with reader 1-AI disagreement, agreement between reader 1 and reader 2 was low with manual readings (ρ = 0.688) but increased substantially when both readers used AI-assisted reading (ρ = 0.975; <i>P</i> < .001). Conclusion AI-assisted reading using a DL algorithm significantly improved interreader agreement for CAD-RADS classification at CCTA. <b>Keywords:</b> Applications - CT, CT-Coronary Angiography, Deep Learning <i>Supplemental material is available for this article.</i> © RSNA, 2025.</p>","PeriodicalId":21168,"journal":{"name":"Radiology. Cardiothoracic imaging","volume":"7 5","pages":"e240563"},"PeriodicalIF":4.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145252422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pericoronary Adipose Tissue Attenuation: Need for a Paradigm Shift?","authors":"Niraj Nirmal Pandey, Mansi Verma","doi":"10.1148/ryct.250281","DOIUrl":"https://doi.org/10.1148/ryct.250281","url":null,"abstract":"","PeriodicalId":21168,"journal":{"name":"Radiology. Cardiothoracic imaging","volume":"7 5","pages":"e250281"},"PeriodicalIF":4.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145302898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Ninth Edition TNM Staging System for Thymic Epithelial Tumors: A Comprehensive Review.","authors":"Maximiliano Klug, Zehavit Kirshenboim, Mylene T Truong, Vera Sorin, Efrat Keren Gilat, Chad D Strange, Edith Michelle Marom","doi":"10.1148/ryct.250144","DOIUrl":"https://doi.org/10.1148/ryct.250144","url":null,"abstract":"<p><p>Accurate cancer staging is essential for guiding treatment decisions and predicting outcomes. The TNM classification is based on three principal elements: size and extent of the primary tumor (T), the degree of spread to regional lymph nodes (N), and the presence of distant metastases (M). In thymic epithelial tumors, clinical TNM staging relies predominantly on cross-sectional imaging, particularly CT and MRI, placing radiologists at the forefront of staging accuracy. Their assessments substantially impact both clinical decision-making and the quality of data in staging registries. A major update in this field is the ninth edition of the TNM classification for thymic epithelial tumors, effective January 2025, which refines TNM category definitions to improve staging accuracy and clinical applicability. This review article outlines these updates, illustrating their application through case examples, and emphasizes the radiologist's crucial role in cancer staging, including selection of appropriate imaging techniques, interpretation of key radiologic features, and effective communication of findings to multidisciplinary teams. These insights aim to enhance staging precision and improve patient outcomes in thymic malignancies. <b>Keywords:</b> Thymus, Staging © RSNA, 2025.</p>","PeriodicalId":21168,"journal":{"name":"Radiology. Cardiothoracic imaging","volume":"7 5","pages":"e250144"},"PeriodicalIF":4.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145346939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Relation of Coronary Artery Disease and High-Sensitivity Cardiac Troponin: Evaluation with CCTA and AI-enabled Plaque Quantification.","authors":"Aaisha Ferkh, John King Khoo, Selma Hasific, Caroline Park, Emily Xing, Fionn Coughlan, Alexander Haenel, Abdulaziz Binzaid, Oliver Haidari, Mattea Lewis, Elina Khasanova, Anthony Chuang, David Meier, Stéphane Fournier, Philipp Blanke, Frank Scheuermeyer, Jonathon Leipsic, Damini Dey, Stephanie Sellers, Georgios Tzimas","doi":"10.1148/ryct.250002","DOIUrl":"https://doi.org/10.1148/ryct.250002","url":null,"abstract":"<p><p>Purpose To evaluate the relationship between artificial intelligence (AI)-quantified coronary plaque characteristics derived from coronary CT angiography (CCTA), stenosis severity, and high-sensitivity cardiac troponin T (hs-cTnT) levels in predicting adverse cardiovascular outcomes in emergency department patients. Materials and Methods This single-center retrospective cohort study included patients who presented acutely to the emergency department and underwent hs-cTnT testing (February 2016-March 2021). Based on peak hs-cTnT levels, patients were categorized into three groups: undetectable (<5 ng/L), intermediate (5-13 ng/L), and elevated (≥14 ng/L). All patients underwent CCTA, and those with Coronary Artery Disease Reporting and Data System score > 0 underwent plaque quantification using an AI-based plaque tool. Patients were followed up for major adverse cardiovascular events (MACE), including acute coronary syndrome, stroke, all-cause mortality, and late revascularization. Statistical analysis included nonparametric tests, χ² tests, and Cox hazards regression. Results Among 527 patients (291 [55%] male; mean age, 56 years ± 12 [SD]), 141 had undetectable, 275 had intermediate, and 111 had elevated hs-cTnT levels. Coronary artery disease prevalence at CCTA was 59% overall and 55% in patients with nonelevated hs-cTnT levels. Total, calcified, noncalcified, and low-density noncalcified plaque volumes increased significantly with higher troponin levels (<i>P</i> < .001). Over a median 29-month follow-up period, 22 MACE occurred. Elevated hs-cTnT level was not associated with increased MACE risk, whereas total plaque volume > 250 mm³ was a significant predictor of both MACE (hazard ratio [HR], 2.62 [95% CI: 1.13, 6.07]; <i>P</i> = .02) and all-cause mortality (HR, 3.62 [95% CI: 1.25, 10.50]; <i>P</i> = .02). Conclusion In this cohort, AI-quantified total plaque volume predicted MACE whereas troponin level did not. This study supports the use of CCTA with AI-based plaque quantification for risk stratification in a real-world population. <b>Keywords:</b> CT Angiography, Coronary Arteries, Arteriosclerosis, Coronary Artery Disease, Plaque Quantification, Troponin, Coronary Computed Tomography Angiography, Artificial Intelligence <i>Supplemental material is available for this article.</i> © RSNA, 2025.</p>","PeriodicalId":21168,"journal":{"name":"Radiology. Cardiothoracic imaging","volume":"7 5","pages":"e250002"},"PeriodicalIF":4.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145252465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Left Ventricular Assist Devices: Advances, Complications, and Pitfalls.","authors":"Robert Ambrosini, Keva Green, Katherine Kaproth-Joslin, Jeffrey Alexis, Bryan Barrus, Igor Gosev, Abhishek Chaturvedi, Susan K Hobbs","doi":"10.1148/ryct.240218","DOIUrl":"https://doi.org/10.1148/ryct.240218","url":null,"abstract":"<p><p>Left ventricular assist devices (LVADs) are used for short-term support, as a bridge to transplant, or as destination therapy in patients with end-stage systolic heart failure. Imaging plays a crucial role in assessing the anatomic suitability for implantation and in detecting complications following both implantation and explantation. LVAD-associated complications can affect the pump, inflow cannula, outflow graft, or driveline. Echocardiography is effective for evaluating inflow cannula position and certain parameters, such as inflow and outflow velocities, valvular regurgitation, and ventricular dilatation; however, its ability to visualize the interiors of the inflow and outflow cannulas is limited. MRI is contraindicated for patients with LVADs. Contrast-enhanced chest CT imaging has become the preferred diagnostic modality for evaluating outflow graft complications. This imaging essay describes the CT findings and complications associated with LVADs, particularly the commercially available HeartMate II and HeartMate 3 devices (Abbott Laboratories). The HeartWare device (Medtronic), although recalled by the U.S. Food and Drug Administration, will also be mentioned. <b>Keywords:</b> Cardiac Assist Devices, CT Imaging <i>Supplemental material is available for this article.</i> © RSNA, 2025.</p>","PeriodicalId":21168,"journal":{"name":"Radiology. Cardiothoracic imaging","volume":"7 4","pages":"e240218"},"PeriodicalIF":4.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cardiac CT for Aortic Stenosis: Novel Quantitative Techniques for Comprehensive Patient Assessment.","authors":"Davide Margonato, Miho Fukui, Takahiro Nishihara, Paul Sorajja, Vinayak Bapat, Maurice Enriquez-Sarano, João L Cavalcante","doi":"10.1148/ryct.240572","DOIUrl":"10.1148/ryct.240572","url":null,"abstract":"<p><p>In recent years, the landscape for the diagnosis and management of patients with aortic stenosis (AS) has rapidly changed, with a dramatic increase in therapeutic options and substantial advances in different imaging modalities. Multidetector CT (MDCT) has become an essential imaging tool for evaluating the feasibility of both surgical and interventional treatments for patients with severe AS. Novel MDCT imaging acquisition protocols, postprocessing tools, and technological advances offer not only detailed anatomic information for adequate procedural planning but also comprehensive quantitative evaluation of the myocardium for assessment of remodeling and function, both of which have prognostic and therapeutic implications. This review provides a comprehensive update on the role of novel MDCT quantitative techniques in the assessment of patients with severe AS. <b>Keywords:</b> CT, Cardiac, Valves, Aortic Stenosis © RSNA, 2025.</p>","PeriodicalId":21168,"journal":{"name":"Radiology. Cardiothoracic imaging","volume":"7 4","pages":"e240572"},"PeriodicalIF":4.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144856177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hyperpolarized ¹²⁹Xe MRI and Spectroscopy: Quantitative Measurements, Results, and Emerging Opportunities.","authors":"Alexandra Schmidt, James A Liggins, Haad Bhutta, Sharon D Dell, Janice M Leung, Don D Sin, Jonathon A Leipsic, Jonathan H Rayment, Rachel L Eddy","doi":"10.1148/ryct.240562","DOIUrl":"https://doi.org/10.1148/ryct.240562","url":null,"abstract":"<p><p>Hyperpolarized xenon 129 (¹²⁹Xe) MRI uses inhaled ¹²⁹Xe gas to visualize pulmonary function and microstructure. This review aims to summarize established and emerging quantitative measurements derived from ¹²⁹Xe MRI and MR spectroscopy (MRS) and illustrate their clinical applications in the characterization and management of cardiopulmonary diseases. They are well tolerated by adults and children with pulmonary disease, employ no ionizing radiation, and their measurements have been validated by correlation with pulmonary function tests in various cardiopulmonary diseases. ¹²⁹Xe fills unobstructed airspaces, producing three-dimensional maps of ventilation and enabling quantification of ventilation defects, dynamics, and heterogeneity. Leveraging ¹²⁹Xe's biologic solubility, gas exchange imaging and spectroscopy allow for quantification of gas transfer between airspaces, alveolar membrane, and red blood cells and are sensitive to blood oxygenation and vascular remodeling. Diffusion-weighted imaging quantifies airspace enlargement, providing models of alveolar microstructure. ¹²⁹Xe MRI can help detect early-stage disease, adding value where reference-standard tools, such as pulmonary function tests, lack sensitivity. The ability of ¹²⁹Xe MRI to assess function regionally creates opportunities for the detection of localized functional deficits and the improvement of image-guided interventions. Applications of ¹²⁹Xe MRI and MRS include planning treatment, monitoring disease progression and treatment response, and developing surrogate endpoints for clinical and therapeutic studies. <b>Keywords:</b> MR Imaging, MR Spectroscopy, Thorax, Lung, Hyperpolarized ¹²⁹Xe, MRI, MRS, Lung Function, Ventilation, Gas Exchange, Alveolar Microstructure © RSNA, 2025.</p>","PeriodicalId":21168,"journal":{"name":"Radiology. Cardiothoracic imaging","volume":"7 4","pages":"e240562"},"PeriodicalIF":4.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144795261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}