Diagnostic and Interventional Imaging最新文献

{"title":"Deep learning reconstruction for accelerated high-resolution upper abdominal MRI improves lesion detection without time penalty","authors":"Jan M. Brendel ,&nbsp;Johann Jacoby ,&nbsp;Reza Dehdab ,&nbsp;Judith Herrmann ,&nbsp;Stephan Ursprung ,&nbsp;Sebastian Werner ,&nbsp;Sebastian Gassenmaier ,&nbsp;Dominik Nickel ,&nbsp;Konstantin Nikolaou ,&nbsp;Saif Afat ,&nbsp;Haidara Almansour","doi":"10.1016/j.diii.2024.09.008","DOIUrl":"10.1016/j.diii.2024.09.008","url":null,"abstract":"<div><h3>Purpose</h3><div>The purpose of this study was to compare a conventional T1-weighted volumetric interpolated breath-hold examination (VIBE) sequence with a DL-reconstructed accelerated high-resolution VIBE sequence (HR-VIBE_DL) in terms of image quality, lesion conspicuity, and lesion detection.</div></div><div><h3>Materials and methods</h3><div>Consecutive patients referred for upper abdominal MRI between December 2023 and March 2024 at a single tertiary center were prospectively enrolled. Participants underwent 1.5 T upper abdominal MRI with acquisition of spectrally fat-saturated unenhanced and gadobutrol-enhanced conventional VIBE (fourfold acceleration, 3.0 mm slice thickness, 72 axial slices) and HR-VIBE_DL (sixfold acceleration, 2.0 mm, 108 slices). Both sequences had an identical acquisition time of 16 s. Image analysis was performed by three readers in a blinded and randomized fashion, with respect to image quality, lesion conspicuity, and lesion detection in liver, pancreas, spleen, lymph nodes and adrenal glands. Image quality parameters were compared using repeated measures analysis of variance. Lesion detection rates were compared using Fisher exact test. Inter-reader agreement was assessed using Fleiss κ test.</div></div><div><h3>Results</h3><div>Among 744 consecutive patients, 50 participants were evaluated. There were 30 men and 20 women, with a mean age of 60 ± 15 (standard deviation [SD]) years (age range: 18–88 years). HR-VIBE_DL images demonstrated superior signal-to-noise ration and edge sharpness by comparison with conventional VIBE images (<em>P</em> &lt; 0.001 for both), with substantial interreader agreement (κ: 0.70–0.90). Lesion conspicuity was higher with for HR-VIBE_DL images (3.50 ± 0.83 [SD]) by comparison with conventional VIBE images (3.21 ± 0.98 [SD]) (<em>P</em> = 0.005). There were 171 upper abdominal lesions, yielding a total of 513 for all three readers. HR-VIBE_DL images yielded higher lesion detection rate (97.5 %; 500/513) compared to conventional VIBE images (93.2 %; 478/513) (<em>P</em> = 0.002).</div></div><div><h3>Conclusion</h3><div>HR-VIBE_DL images of the upper abdomen result in superior image quality, better lesion conspicuity, and improved lesion detection without time penalty by comparsion with conventional VIBE images.</div></div>","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":"106 3","pages":"Pages 85-92"},"PeriodicalIF":4.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142682851","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":"Generative AI smartphones: From entertainment to potentially serious risks in radiology","authors":"Loïc Duron ,&nbsp;Philippe Soyer ,&nbsp;Augustin Lecler","doi":"10.1016/j.diii.2024.10.002","DOIUrl":"10.1016/j.diii.2024.10.002","url":null,"abstract":"","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":"106 2","pages":"Pages 76-78"},"PeriodicalIF":4.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142382083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ultra-high resolution spectral photon-counting CT outperforms dual layer CT for lung imaging: Results of a phantom study","authors":"Hugo Lacombe ,&nbsp;Joey Labour ,&nbsp;Fabien de Oliveira ,&nbsp;Antoine Robert ,&nbsp;Angèle Houmeau ,&nbsp;Marjorie Villien ,&nbsp;Sara Boccalini ,&nbsp;Jean-Paul Beregi ,&nbsp;Philippe C. Douek ,&nbsp;Joël Greffier ,&nbsp;Salim A. Si-Mohamed","doi":"10.1016/j.diii.2024.09.011","DOIUrl":"10.1016/j.diii.2024.09.011","url":null,"abstract":"<div><h3>Purpose</h3><div>The purpose of this study was to compare lung image quality obtained with ultra-high resolution (UHR) spectral photon-counting CT (SPCCT) with that of dual-layer CT (DLCT), at standard and low dose levels using an image quality phantom and an anthropomorphic lung phantom.</div></div><div><h3>Methods</h3><div>An image quality phantom was scanned using a clinical SPCCT prototype and an 8 cm collimation DLCT from the same manufacturer at 10 mGy. Additional acquisitions at 6 mGy were performed with SPCCT only. Images were reconstructed with dedicated high-frequency reconstruction kernels, slice thickness between 0.58 and 0.67 mm, and matrix between 512² and 1024² mm, using a hybrid iterative algorithm at level 6. Noise power spectrum (NPS), task-based transfer function (TTF) for iodine and air inserts, and detectability index (<em>d’</em>) were assessed for ground-glass and solid nodules of 2 mm to simulate highly detailed lung lesions. Subjective analysis of an anthropomorphic lung phantom was performed by two radiologists using a five-point quality score.</div></div><div><h3>Results</h3><div>At 10 mGy, noise magnitude was reduced by 29.1 % with SPCCT images compared to DLCT images for all parameters (27.1 ± 11.0 [standard deviation (SD)] HU vs. 38.2 ± 1.0 [SD] HU, respectively). At 6 mGy with SPCCT images, noise magnitude was reduced by 8.9 % compared to DLCT images at 10 mGy (34.8 ± 14.1 [SD] HU vs. 38.2 ± 1.0 [SD] HU, respectively). At 10 mGy and 6 mGy, average NPS spatial frequency (f_av) was greater for SPCCT images (0.75 ± 0.17 [SD] mm^-1) compared to DLCT images at 10 mGy (0.55 ± 0.04 [SD] mm^-1) while remaining constant from 10 to 6 mGy. At 10 mGy, TTF at 50 % (f₅₀) was greater for SPCCT images (0.92 ± 0.08 [SD] mm^-1) compared to DLCT images (0.67 ± 0.06 [SD] mm^-1) for both inserts. At 6 mGy, f₅₀ decreased by 1.1 % for SPCCT images, while remaining greater compared to DLCT images at 10 mGy (0.91 ± 0.06 [SD] mm^-1 vs. 0.67 ± 0.06 [SD] mm^-1, respectively). At both dose levels, <em>d’</em> were greater for SPCCT images compared to DLCT for all clinical tasks. Subjective analysis performed by two radiologists revealed a greater median image quality for SPCCT (5; Q1, 4; Q3, 5) compared to DLCT images (3; Q1, 3; Q3, 3).</div></div><div><h3>Conclusion</h3><div>UHR SPCCT outperforms DLCT in terms of image quality for lung imaging. In addition, UHR SPCCT contributes to a 40 % reduction in radiation dose compared to DLCT.</div></div>","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":"106 2","pages":"Pages 60-67"},"PeriodicalIF":4.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142367077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CT, MRI and contrast-enhanced ultrasound features of mucinous cystic neoplasm of the liver","authors":"Emily Rius ,&nbsp;Raphael Dautry ,&nbsp;Stylianos Tzedakis","doi":"10.1016/j.diii.2024.10.003","DOIUrl":"10.1016/j.diii.2024.10.003","url":null,"abstract":"","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":"106 2","pages":"Pages 79-80"},"PeriodicalIF":4.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142407067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Combining photon-counting coronary CT and artificial intelligence to detect coronary artery stenosis","authors":"David A. Bluemke,&nbsp;Prashant Nagpal","doi":"10.1016/j.diii.2024.11.005","DOIUrl":"10.1016/j.diii.2024.11.005","url":null,"abstract":"","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":"106 2","pages":"Pages 45-46"},"PeriodicalIF":4.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142787407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editor's note: 2024-the year in review for Diagnostic & Interventional Imaging","authors":"Philippe Soyer","doi":"10.1016/j.diii.2025.01.003","DOIUrl":"10.1016/j.diii.2025.01.003","url":null,"abstract":"","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":"106 2","pages":"Pages 47-48"},"PeriodicalIF":4.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143014591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coronary artery disease detection using deep learning and ultrahigh-resolution photon-counting coronary CT angiography","authors":"Jan M. Brendel ,&nbsp;Jonathan Walterspiel ,&nbsp;Florian Hagen ,&nbsp;Jens Kübler ,&nbsp;Andreas S. Brendlin ,&nbsp;Saif Afat ,&nbsp;Jean-François Paul ,&nbsp;Thomas Küstner ,&nbsp;Konstantin Nikolaou ,&nbsp;Meinrad Gawaz ,&nbsp;Simon Greulich ,&nbsp;Patrick Krumm ,&nbsp;Moritz T. Winkelmann","doi":"10.1016/j.diii.2024.09.012","DOIUrl":"10.1016/j.diii.2024.09.012","url":null,"abstract":"<div><h3>Purpose</h3><div>The purpose of this study was to evaluate the diagnostic performance of automated deep learning in the detection of coronary artery disease (CAD) on photon-counting coronary CT angiography (PC-CCTA).</div></div><div><h3>Materials and methods</h3><div>Consecutive patients with suspected CAD who underwent PC-CCTA between January 2022 and December 2023 were included in this retrospective, single-center study. Non-ultra-high resolution (UHR) PC-CCTA images were analyzed by artificial intelligence using two deep learning models (CorEx, Spimed-AI), and compared to human expert reader assessment using UHR PC-CCTA images. Diagnostic performance for global CAD assessment (at least one significant stenosis ≥ 50 %) was estimated at patient and vessel levels.</div></div><div><h3>Results</h3><div>A total of 140 patients (96 men, 44 women) with a median age of 60 years (first quartile, 51; third quartile, 68) were evaluated. Significant CAD on UHR PC-CCTA was present in 36/140 patients (25.7 %). The sensitivity, specificity, accuracy, positive predictive value), and negative predictive value of deep learning-based CAD were 97.2 %, 81.7 %, 85.7 %, 64.8 %, and 98.9 %, respectively, at the patient level and 96.6 %, 86.7 %, 88.1 %, 53.8 %, and 99.4 %, respectively, at the vessel level. The area under the receiver operating characteristic curve was 0.90 (95 % CI: 0.83–0.94) at the patient level and 0.92 (95 % CI: 0.89–0.94) at the vessel level.</div></div><div><h3>Conclusion</h3><div>Automated deep learning shows remarkable performance for the diagnosis of significant CAD on non-UHR PC-CCTA images. AI pre-reading may be of supportive value to the human reader in daily clinical practice to target and validate coronary artery stenosis using UHR PC-CCTA.</div></div>","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":"106 2","pages":"Pages 68-75"},"PeriodicalIF":4.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142376173","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":"Photon-counting CT systems: A technical review of current clinical possibilities","authors":"Joël Greffier ,&nbsp;Anaïs Viry ,&nbsp;Antoine Robert ,&nbsp;Mouad Khorsi ,&nbsp;Salim Si-Mohamed","doi":"10.1016/j.diii.2024.09.002","DOIUrl":"10.1016/j.diii.2024.09.002","url":null,"abstract":"<div><div>In recent years, computed tomography (CT) has undergone a number of developments to improve radiological care. The most recent major innovation has been the development of photon-counting detectors. By comparison with the energy-integrating detectors traditionally used in CT, these detectors offer better dose efficiency, eliminate electronic noise, improve spatial resolution and have intrinsic spectral sensitivity. These detectors also allow the energy of each photon to be counted, thus improving the sampling of the X-ray spectrum in multiple energy bins, to better distinguish between photoelectric and Compton attenuation coefficients, resulting in better spectral images and specific color K-edge images. The purpose of this article was to make the reader more familiar with the basic principles and techniques of new photon-counting CT systems equipped with photon-counting detectors and also to describe the currently available devices that could be used in clinical practice.</div></div>","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":"106 2","pages":"Pages 53-59"},"PeriodicalIF":4.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142298960","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":"An introductory guide to statistics for the radiologist","authors":"Emma O'Shaughnessy ,&nbsp;Emmanuel Detrinidad ,&nbsp;Philippe Soyer ,&nbsp;Augustin Lecler","doi":"10.1016/j.diii.2024.11.003","DOIUrl":"10.1016/j.diii.2024.11.003","url":null,"abstract":"<div><div>Radiology generates both qualitative and quantitative data. As a consequence, statistical analysis is essential to validate data interpretation, and support reliable conclusions. Statistics serves as a cornerstone of radiology research, objectively verifying observations and establishing relationships between variables. This article provides a practical guide to basic statistical methods for radiology researchers, enabling them to structure their analyses more effectively and highlight their findings in a meaningful way. Although not exhaustive, this article covers basic statistical principles.</div></div>","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":"106 2","pages":"Pages 49-52"},"PeriodicalIF":4.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142796547","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":"Assessment of ischemia in mechanical small bowel obstruction: The time has come for dual-energy CT","authors":"Marc Zins ,&nbsp;Julien Frandon ,&nbsp;Ingrid Millet","doi":"10.1016/j.diii.2025.01.001","DOIUrl":"10.1016/j.diii.2025.01.001","url":null,"abstract":"","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":"106 4","pages":"Pages 113-114"},"PeriodicalIF":4.9,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143030149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}