European Radiology Experimental最新文献

{"title":"Improving image quality of sparse-view lung tumor CT images with U-Net.","authors":"Annika Ries, Tina Dorosti, Johannes Thalhammer, Daniel Sasse, Andreas Sauter, Felix Meurer, Ashley Benne, Tobias Lasser, Franz Pfeiffer, Florian Schaff, Daniela Pfeiffer","doi":"10.1186/s41747-024-00450-4","DOIUrl":"https://doi.org/10.1186/s41747-024-00450-4","url":null,"abstract":"<p><strong>Background: </strong>We aimed to improve the image quality (IQ) of sparse-view computed tomography (CT) images using a U-Net for lung metastasis detection and determine the best tradeoff between number of views, IQ, and diagnostic confidence.</p><p><strong>Methods: </strong>CT images from 41 subjects aged 62.8 ± 10.6 years (mean ± standard deviation, 23 men), 34 with lung metastasis, 7 healthy, were retrospectively selected (2016-2018) and forward projected onto 2,048-view sinograms. Six corresponding sparse-view CT data subsets at varying levels of undersampling were reconstructed from sinograms using filtered backprojection with 16, 32, 64, 128, 256, and 512 views. A dual-frame U-Net was trained and evaluated for each subsampling level on 8,658 images from 22 diseased subjects. A representative image per scan was selected from 19 subjects (12 diseased, 7 healthy) for a single-blinded multireader study. These slices, for all levels of subsampling, with and without U-Net postprocessing, were presented to three readers. IQ and diagnostic confidence were ranked using predefined scales. Subjective nodule segmentation was evaluated using sensitivity and Dice similarity coefficient (DSC); clustered Wilcoxon signed-rank test was used.</p><p><strong>Results: </strong>The 64-projection sparse-view images resulted in 0.89 sensitivity and 0.81 DSC, while their counterparts, postprocessed with the U-Net, had improved metrics (0.94 sensitivity and 0.85 DSC) (p = 0.400). Fewer views led to insufficient IQ for diagnosis. For increased views, no substantial discrepancies were noted between sparse-view and postprocessed images.</p><p><strong>Conclusions: </strong>Projection views can be reduced from 2,048 to 64 while maintaining IQ and the confidence of the radiologists on a satisfactory level.</p><p><strong>Relevance statement: </strong>Our reader study demonstrates the benefit of U-Net postprocessing for regular CT screenings of patients with lung metastasis to increase the IQ and diagnostic confidence while reducing the dose.</p><p><strong>Key points: </strong>• Sparse-projection-view streak artifacts reduce the quality and usability of sparse-view CT images. • U-Net-based postprocessing removes sparse-view artifacts while maintaining diagnostically accurate IQ. • Postprocessed sparse-view CTs drastically increase radiologists' confidence in diagnosing lung metastasis.</p>","PeriodicalId":36926,"journal":{"name":"European Radiology Experimental","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11065797/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140871392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence in interventional radiology: state of the art","authors":"Pierluigi Glielmo, Stefano Fusco, Salvatore Gitto, Giulia Zantonelli, Domenico Albano, Carmelo Messina, Luca Maria Sconfienza, Giovanni Mauri","doi":"10.1186/s41747-024-00452-2","DOIUrl":"https://doi.org/10.1186/s41747-024-00452-2","url":null,"abstract":"<p>Artificial intelligence (AI) has demonstrated great potential in a wide variety of applications in interventional radiology (IR). Support for decision-making and outcome prediction, new functions and improvements in fluoroscopy, ultrasound, computed tomography, and magnetic resonance imaging, specifically in the field of IR, have all been investigated. Furthermore, AI represents a significant boost for fusion imaging and simulated reality, robotics, touchless software interactions, and virtual biopsy. The procedural nature, heterogeneity, and lack of standardisation slow down the process of adoption of AI in IR. Research in AI is in its early stages as current literature is based on pilot or proof of concept studies. The full range of possibilities is yet to be explored.</p><p><b>Relevance statement</b> Exploring AI’s transformative potential, this article assesses its current applications and challenges in IR, offering insights into decision support and outcome prediction, imaging enhancements, robotics, and touchless interactions, shaping the future of patient care.</p><p><b>Key points</b></p><p>• AI adoption in IR is more complex compared to diagnostic radiology.</p><p>• Current literature about AI in IR is in its early stages.</p><p>• AI has the potential to revolutionise every aspect of IR.</p><h3 data-test=\"abstract-sub-heading\">Graphical Abstract</h3>\u0000","PeriodicalId":36926,"journal":{"name":"European Radiology Experimental","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140838791","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":"Diffusion probabilistic versus generative adversarial models to reduce contrast agent dose in breast MRI","authors":"Gustav Müller-Franzes, Luisa Huck, Maike Bode, Sven Nebelung, Christiane Kuhl, Daniel Truhn, Teresa Lemainque","doi":"10.1186/s41747-024-00451-3","DOIUrl":"https://doi.org/10.1186/s41747-024-00451-3","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Background</h3><p>To compare denoising diffusion probabilistic models (DDPM) and generative adversarial networks (GAN) for recovering contrast-enhanced breast magnetic resonance imaging (MRI) subtraction images from virtual low-dose subtraction images.</p><h3 data-test=\"abstract-sub-heading\">Methods</h3><p>Retrospective, ethically approved study. DDPM- and GAN-reconstructed single-slice subtraction images of 50 breasts with enhancing lesions were compared to original ones at three dose levels (25%, 10%, 5%) using quantitative measures and radiologic evaluations. Two radiologists stated their preference based on the reconstruction quality and scored the lesion conspicuity as compared to the original, blinded to the model. Fifty lesion-free maximum intensity projections were evaluated for the presence of false-positives. Results were compared between models and dose levels, using generalized linear mixed models.</p><h3 data-test=\"abstract-sub-heading\">Results</h3><p>At 5% dose, both radiologists preferred the GAN-generated images, whereas at 25% dose, both radiologists preferred the DDPM-generated images. Median lesion conspicuity scores did not differ between GAN and DDPM at 25% dose (5 <i>versus</i> 5, <i>p</i> = 1.000) and 10% dose (4 <i>versus</i> 4, <i>p</i> = 1.000). At 5% dose, both readers assigned higher conspicuity to the GAN than to the DDPM (3 <i>versus</i> 2, <i>p</i> = 0.007). In the lesion-free examinations, DDPM and GAN showed no differences in the false-positive rate at 5% (15% <i>versus</i> 22%), 10% (10% <i>versus</i> 6%), and 25% (6% <i>versus</i> 4%) (<i>p</i> = 1.000).</p><h3 data-test=\"abstract-sub-heading\">Conclusions</h3><p>Both GAN and DDPM yielded promising results in low-dose image reconstruction. However, neither of them showed superior results over the other model for all dose levels and evaluation metrics. Further development is needed to counteract false-positives.</p><h3 data-test=\"abstract-sub-heading\">Relevance statement</h3><p>For MRI-based breast cancer screening, reducing the contrast agent dose is desirable. Diffusion probabilistic models and generative adversarial networks were capable of retrospectively enhancing the signal of low-dose images. Hence, they may supplement imaging with reduced doses in the future.</p><h3 data-test=\"abstract-sub-heading\">Key points</h3><p>• Deep learning may help recover signal in low-dose contrast-enhanced breast MRI.</p><p>• Two models (DDPM and GAN) were trained at different dose levels.</p><p>• Radiologists preferred DDPM at 25%, and GAN images at 5% dose.</p><p>• Lesion conspicuity between DDPM and GAN was similar, except at 5% dose.</p><p>• GAN and DDPM yield promising results in low-dose image reconstruction.</p><h3 data-test=\"abstract-sub-heading\">Graphical Abstract</h3>\u0000","PeriodicalId":36926,"journal":{"name":"European Radiology Experimental","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140838412","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":"Phantom-based analysis of variations in automatic exposure control across three mammography systems: implications for radiation dose and image quality in mammography, DBT, and CEM","authors":"Gisella Gennaro, Sara Del Genio, Giuseppe Manco, Francesca Caumo","doi":"10.1186/s41747-024-00447-z","DOIUrl":"https://doi.org/10.1186/s41747-024-00447-z","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Background</h3><p>Automatic exposure control (AEC) plays a crucial role in mammography by determining the exposure conditions needed to achieve specific image quality based on the absorption characteristics of compressed breasts. This study aimed to characterize the behavior of AEC for digital mammography (DM), digital breast tomosynthesis (DBT), and low-energy (LE) and high-energy (HE) acquisitions used in contrast-enhanced mammography (CEM) for three mammography systems from two manufacturers.</p><h3 data-test=\"abstract-sub-heading\">Methods</h3><p>Using phantoms simulating various breast thicknesses, 363 studies were acquired using all available AEC modes 165 DM, 132 DBT, and 66 LE-CEM and HE-CEM. AEC behaviors were compared across systems and modalities to assess the impact of different technical components and manufacturers’ strategies on the resulting mean glandular doses (MGDs) and image quality metrics such as contrast-to-noise ratio (CNR).</p><h3 data-test=\"abstract-sub-heading\">Results</h3><p>For all systems and modalities, AEC increased MGD for increasing phantom thicknesses and decreased CNR. The median MGD values (interquartile ranges) were 1.135 mGy (0.772–1.668) for DM, 1.257 mGy (0.971–1.863) for DBT, 1.280 mGy (0.937–1.878) for LE-CEM, and 0.630 mGy (0.397–0.713) for HE-CEM. Medians CNRs were 14.2 (7.8–20.2) for DM, 4.91 (2.58–7.20) for a single projection in DBT, 11.9 (8.0–18.2) for LE-CEM, and 5.2 (3.6–9.2) for HE-CEM. AECs showed high repeatability, with variations lower than 5% for all modes in DM, DBT, and CEM.</p><h3 data-test=\"abstract-sub-heading\">Conclusions</h3><p>The study revealed substantial differences in AEC behavior between systems, modalities, and AEC modes, influenced by technical components and manufacturers’ strategies, with potential implications in radiation dose and image quality in clinical settings.</p><h3 data-test=\"abstract-sub-heading\">Relevance statement</h3><p>The study emphasized the central role of automatic exposure control in DM, DBT, and CEM acquisitions and the great variability in dose and image quality among manufacturers and between modalities. Caution is needed when generalizing conclusions about differences across mammography modalities.</p><h3 data-test=\"abstract-sub-heading\">Key points</h3><p>• AEC plays a crucial role in DM, DBT, and CEM.</p><p>• AEC determines the “optimal” exposure conditions needed to achieve specific image quality.</p><p>• The study revealed substantial differences in AEC behavior, influenced by differences in technical components and strategies.</p><h3 data-test=\"abstract-sub-heading\">Graphical Abstract</h3>\u0000","PeriodicalId":36926,"journal":{"name":"European Radiology Experimental","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140578538","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":"Reconstruction of 3D knee MRI using deep learning and compressed sensing: a validation study on healthy volunteers","authors":"Thomas Dratsch, Charlotte Zäske, Florian Siedek, Philip Rauen, Nils Große Hokamp, Kristina Sonnabend, David Maintz, Grischa Bratke, Andra Iuga","doi":"10.1186/s41747-024-00446-0","DOIUrl":"https://doi.org/10.1186/s41747-024-00446-0","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Background</h3><p>To investigate the potential of combining compressed sensing (CS) and artificial intelligence (AI), in particular deep learning (DL), for accelerating three-dimensional (3D) magnetic resonance imaging (MRI) sequences of the knee.</p><h3 data-test=\"abstract-sub-heading\">Methods</h3><p>Twenty healthy volunteers were examined using a 3-T scanner with a fat-saturated 3D proton density sequence with four different acceleration levels (10, 13, 15, and 17). All sequences were accelerated with CS and reconstructed using the conventional and a new DL-based algorithm (CS-AI). Subjective image quality was evaluated by two blinded readers using seven criteria on a 5-point-Likert-scale (overall impression, artifacts, delineation of the anterior cruciate ligament, posterior cruciate ligament, menisci, cartilage, and bone). Using mixed models, all CS-AI sequences were compared to the clinical standard (sense sequence with an acceleration factor of 2) and CS sequences with the same acceleration factor.</p><h3 data-test=\"abstract-sub-heading\">Results</h3><p>3D sequences reconstructed with CS-AI achieved significantly better values for subjective image quality compared to sequences reconstructed with CS with the same acceleration factor (<i>p</i> ≤ 0.001). The images reconstructed with CS-AI showed that tenfold acceleration may be feasible without significant loss of quality when compared to the reference sequence (<i>p</i> ≥ 0.999).</p><h3 data-test=\"abstract-sub-heading\">Conclusions</h3><p>For 3-T 3D-MRI of the knee, a DL-based algorithm allowed for additional acceleration of acquisition times compared to the conventional approach. This study, however, is limited by its small sample size and inclusion of only healthy volunteers, indicating the need for further research with a more diverse and larger sample.</p><h3 data-test=\"abstract-sub-heading\">Trial registration</h3><p>DRKS00024156.</p><h3 data-test=\"abstract-sub-heading\">Relevance statement</h3><p>Using a DL-based algorithm, 54% faster image acquisition (178 s <i>versus</i> 384 s) for 3D-sequences may be possible for 3-T MRI of the knee.</p><h3 data-test=\"abstract-sub-heading\">Key points</h3><p>• Combination of compressed sensing and DL improved image quality and allows for significant acceleration of 3D knee MRI.</p><p>• DL-based algorithm achieved better subjective image quality than conventional compressed sensing.</p><p>• For 3D knee MRI at 3 T, 54% faster image acquisition may be possible.</p><h3 data-test=\"abstract-sub-heading\">Graphical Abstract</h3>\u0000","PeriodicalId":36926,"journal":{"name":"European Radiology Experimental","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140578799","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 [1-13C]-pyruvate MRS evaluates immune potential and predicts response to radiotherapy in cervical cancer","authors":"Gigin Lin, Ching-Yi Hsieh, Ying-Chieh Lai, Chun-Chieh Wang, Yenpo Lin, Kuan-Ying Lu, Wen-Yen Chai, Albert P. Chen, Tzu-Chen Yen, Shu-Hang Ng, Chyong-Huey Lai","doi":"10.1186/s41747-024-00445-1","DOIUrl":"https://doi.org/10.1186/s41747-024-00445-1","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Background</h3><p>Monitoring pyruvate metabolism in the spleen is important for assessing immune activity and achieving successful radiotherapy for cervical cancer due to the significance of the abscopal effect. We aimed to explore the feasibility of utilizing hyperpolarized (HP) [1-¹³C]-pyruvate magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) to evaluate pyruvate metabolism in the human spleen, with the aim of identifying potential candidates for radiotherapy in cervical cancer.</p><h3 data-test=\"abstract-sub-heading\">Methods</h3><p>This prospective study recruited six female patients with cervical cancer (median age 55 years; range 39–60) evaluated using HP [1-¹³C]-pyruvate MRI/MRS at baseline and 2 weeks after radiotherapy. Proton (¹H) diffusion-weighted MRI was performed in parallel to estimate splenic cellularity. The primary outcome was defined as tumor response to radiotherapy. The Student <i>t</i>-test was used for comparing ¹³C data between the groups.</p><h3 data-test=\"abstract-sub-heading\">Results</h3><p>The splenic HP [1-¹³C]-lactate-to-total carbon (tC) ratio was 5.6-fold lower in the responders than in the non-responders at baseline (<i>p</i> = 0.009). The splenic [1-¹³C]-lactate-to-tC ratio revealed a 1.7-fold increase (<i>p</i> = 0.415) and the splenic [1-¹³C]-alanine-to-tC ratio revealed a 1.8-fold increase after radiotherapy (<i>p</i> = 0.482). The blood leukocyte differential count revealed an increased proportion of neutrophils two weeks following treatment, indicating enhanced immune activity (<i>p</i> = 0.013). The splenic apparent diffusion coefficient values between the groups were not significantly different.</p><h3 data-test=\"abstract-sub-heading\">Conclusions</h3><p>This exploratory study revealed the feasibility of HP [1-¹³C]-pyruvate MRS of the spleen for evaluating baseline immune potential, which was associated with clinical outcomes of cervical cancer after radiotherapy.</p><h3 data-test=\"abstract-sub-heading\">Trial registration</h3><p>ClinicalTrials.gov NCT04951921, registered 7 July 2021.</p><h3 data-test=\"abstract-sub-heading\">Relevance statement</h3><p>This prospective study revealed the feasibility of using HP ¹³C MRI/MRS for assessing pyruvate metabolism of the spleen to evaluate the patients’ immune potential that is associated with radiotherapeutic clinical outcomes in cervical cancer.</p><h3 data-test=\"abstract-sub-heading\">Key points</h3><p>• Effective radiotherapy induces abscopal effect via altering immune metabolism.</p><p>• Hyperpolarized ¹³C MRS evaluates patients’ immune potential non-invasively.</p><p>• Pyruvate-to-lactate conversion in the spleen is elevated following radiotherapy.</p><h3 data-test=\"abstract-sub-heading\">Graphical Abstract</h3>\u0000","PeriodicalId":36926,"journal":{"name":"European Radiology Experimental","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140578534","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":"Public data homogenization for AI model development in breast cancer","authors":"Vassilis Kilintzis, Varvara Kalokyri, Haridimos Kondylakis, Smriti Joshi, Katerina Nikiforaki, Oliver Díaz, Karim Lekadir, Manolis Tsiknakis, Kostas Marias","doi":"10.1186/s41747-024-00442-4","DOIUrl":"https://doi.org/10.1186/s41747-024-00442-4","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Background</h3><p>Developing trustworthy artificial intelligence (AI) models for clinical applications requires access to clinical and imaging data cohorts. Reusing of publicly available datasets has the potential to fill this gap. Specifically in the domain of breast cancer, a large archive of publicly accessible medical images along with the corresponding clinical data is available at The Cancer Imaging Archive (TCIA). However, existing datasets cannot be directly used as they are heterogeneous and cannot be effectively filtered for selecting specific image types required to develop AI models. This work focuses on the development of a homogenized dataset in the domain of breast cancer including clinical and imaging data.</p><h3 data-test=\"abstract-sub-heading\">Methods</h3><p>Five datasets were acquired from the TCIA and were harmonized. For the clinical data harmonization, a common data model was developed and a repeatable, documented “extract-transform-load” process was defined and executed for their homogenization. Further, Digital Imaging and COmmunications in Medicine (DICOM) information was extracted from magnetic resonance imaging (MRI) data and made accessible and searchable.</p><h3 data-test=\"abstract-sub-heading\">Results</h3><p>The resulting harmonized dataset includes information about 2,035 subjects with breast cancer. Further, a platform named RV-Cherry-Picker enables search over both the clinical and diagnostic imaging datasets, providing unified access, facilitating the downloading of all study imaging that correspond to specific series’ characteristics (<i>e.g.</i>, dynamic contrast-enhanced series), and reducing the burden of acquiring the appropriate set of images for the respective AI model scenario.</p><h3 data-test=\"abstract-sub-heading\">Conclusions</h3><p>RV-Cherry-Picker provides access to the largest, publicly available, homogenized, imaging/clinical dataset for breast cancer to develop AI models on top.</p><h3 data-test=\"abstract-sub-heading\">Relevance statement</h3><p>We present a solution for creating merged public datasets supporting AI model development, using as an example the breast cancer domain and magnetic resonance imaging images.</p><h3 data-test=\"abstract-sub-heading\">Key points</h3><p>• The proposed platform allows unified access to the largest, homogenized public imaging dataset for breast cancer.</p><p>• A methodology for the semantically enriched homogenization of public clinical data is presented.</p><p>• The platform is able to make a detailed selection of breast MRI data for the development of AI models.</p><h3 data-test=\"abstract-sub-heading\">Graphical Abstract</h3>\u0000","PeriodicalId":36926,"journal":{"name":"European Radiology Experimental","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140578794","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":"3D amide proton transfer-weighted imaging may be useful for diagnosing early-stage breast cancer: a prospective monocentric study","authors":"Yeqin Li, Yan Zhang, Liwen Tian, Ju Li, Huihua Li, Ximing Wang, Cuiyan Wang","doi":"10.1186/s41747-024-00439-z","DOIUrl":"https://doi.org/10.1186/s41747-024-00439-z","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Background</h3><p>We investigated the value of three-dimensional amide proton transfer-weighted imaging (3D-APTWI) in the diagnosis of early-stage breast cancer (BC) and its correlation with the immunohistochemical characteristics of malignant lesions.</p><h3 data-test=\"abstract-sub-heading\">Methods</h3><p>Seventy-eight women underwent APTWI and dynamic contrast-enhanced (DCE)-MRI. Pathological results were categorized as either benign (<i>n</i> = 43) or malignant (<i>n</i> = 37) lesions. The parameters of APTWI and DCE-MRI were compared between the benign and malignant groups. The diagnostic value of 3D-APTWI was evaluated using the area under the receiver operating characteristic curve (ROC-AUC) to establish a diagnostic threshold. Pearson’s correlation was used to analyze the correlation between the magnetization transfer asymmetry (MTR_asym) and immunohistochemical characteristics.</p><h3 data-test=\"abstract-sub-heading\">Results</h3><p>The MTR_asym and time-to-peak of malignancies were significantly lower than those of benign lesions (all <i>p</i> &lt; 0.010). The volume transfer constant, rate constant, and wash-in and wash-out rates of malignancies were all significantly greater than those of benign lesions (all <i>p</i> &lt; 0.010). ROC-AUCs of 3D-APTWI, DCE-MRI, and 3D-APTWI+DCE to differential diagnosis between early-stage BC and benign lesions were 0.816, 0.745, and 0.858, respectively. Only the difference between AUC_APT+DCE and AUC_DCE was significant (<i>p</i> &lt; 0.010). When a threshold of MTR_asym for malignancy for 2.42%, the sensitivity and specificity of 3D-APTWI for BC diagnosis were 86.5% and 67.6%, respectively; MTR_asym was modestly positively correlated with pathological grade (<i>r</i> = 0.476, <i>p</i> = 0.003) and Ki-67 (<i>r</i> = 0.419, <i>p</i> = 0.020).</p><h3 data-test=\"abstract-sub-heading\">Conclusions</h3><p>3D-APTWI may be used as a supplementary method for patients with contraindications of DCE-MRI. MTR_asym can imply the proliferation activities of early-stage BC.</p><h3 data-test=\"abstract-sub-heading\">Relevance statement</h3><p>3D-APTWI can be an alternative diagnostic method for patients with early-stage BC who are not suitable for contrast injection.</p><h3 data-test=\"abstract-sub-heading\">Key points</h3><p>• 3D-APTWI reflects the changes in the microenvironment of early-stage breast cancer.</p><p>• Combined 3D-APTWI is superior to DCE-MRI alone for early-stage breast cancer diagnosis.</p><p>• 3D-APTWI improves the diagnostic accuracy of early-stage breast cancer.</p><h3 data-test=\"abstract-sub-heading\">Graphical Abstract</h3>\u0000","PeriodicalId":36926,"journal":{"name":"European Radiology Experimental","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140578801","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":"Multimaterial decomposition in dual-energy CT for characterization of clots from acute ischemic stroke patients","authors":"Melina Gassenhuber, Maximilian E. Lochschmidt, Johannes Hammel, Tobias Boeckh-Behrens, Benno Ikenberg, Silke Wunderlich, Friederike Liesche-Starnecker, Jürgen Schlegel, Franz Pfeiffer, Marcus R. Makowski, Claus Zimmer, Isabelle Riederer, Daniela Pfeiffer","doi":"10.1186/s41747-024-00443-3","DOIUrl":"https://doi.org/10.1186/s41747-024-00443-3","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Background</h3><p>Nowadays, there is no method to quantitatively characterize the material composition of acute ischemic stroke thrombi prior to intervention, but dual-energy CT (DE-CT) offers imaging-based multimaterial decomposition. We retrospectively investigated the material composition of thrombi <i>ex vivo</i> using DE-CT with histological analysis as a reference.</p><h3 data-test=\"abstract-sub-heading\">Methods</h3><p>Clots of 70 patients with acute ischemic stroke were extracted by mechanical thrombectomy and scanned <i>ex vivo</i> in formalin-filled tubes with DE-CT. Multimaterial decomposition in the three components, <i>i.e.</i>, red blood cells (RBC), white blood cells (WBC), and fibrin/platelets (F/P), was performed and compared to histology (hematoxylin/eosin staining) as reference. Attenuation and effective <i>Z</i> values were assessed, and histological composition was compared to stroke etiology according to the Trial of ORG 10172 in Acute Stroke Treatment (TOAST) criteria.</p><h3 data-test=\"abstract-sub-heading\">Results</h3><p>Histological and imaging analysis showed the following correlation coefficients for RBC (<i>r</i> = 0.527, <i>p</i> &lt; 0.001), WBC (<i>r</i> = 0.305, <i>p</i> = 0.020), and F/P (<i>r</i> = 0.525, <i>p</i> &lt; 0.001). RBC-rich thrombi presented higher clot attenuation in Hounsfield units than F/P-rich thrombi (51 HU <i>versus</i> 42 HU, <i>p</i> &lt; 0.01). In histological analysis, cardioembolic clots showed less RBC (40% <i>versus</i> 56%, <i>p</i> = 0.053) and more F/P (53% <i>versus</i> 36%, <i>p</i> = 0.024), similar to cryptogenic clots containing less RBC (34% <i>versus</i> 56%, <i>p</i> = 0.006) and more F/P (58% <i>versus</i> 36%, <i>p</i> = 0.003) than non-cardioembolic strokes. No difference was assessed for the mean WBC portions in all TOAST groups.</p><h3 data-test=\"abstract-sub-heading\">Conclusions</h3><p>DE-CT has the potential to quantitatively characterize the material composition of ischemic stroke thrombi.</p><h3 data-test=\"abstract-sub-heading\">Relevance statement</h3><p>Using DE-CT, the composition of ischemic stroke thrombi can be determined. Knowledge of histological composition prior to intervention offers the opportunity to define personalized treatment strategies for each patient to accomplish faster recanalization and better clinical outcomes.</p><h3 data-test=\"abstract-sub-heading\">Key points</h3><p>• Acute ischemic stroke clots present different recanalization success according to histological composition.</p><p>• Currently, no method can determine clot composition prior to intervention.</p><p>• DE-CT allows quantitative material decomposition of thrombi <i>ex vivo</i> in red blood cells, white blood cells, and fibrin/platelets.</p><p>• Histological clot composition differs between stroke etiology.</p><p>• Insights into the histological composition <i>in situ</i> offer personalized treatment strategies.</p><h3 data-test=\"abstract-sub-headi","PeriodicalId":36926,"journal":{"name":"European Radiology Experimental","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140578713","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":"Right main pulmonary artery distensibility on dynamic ventilation CT and its association with respiratory function","authors":"Tatsuya Oki, Yukihiro Nagatani, Shota Ishida, Masayuki Hashimoto, Yasuhiko Oshio, Jun Hanaoka, Ryo Uemura, Yoshiyuki Watanabe","doi":"10.1186/s41747-024-00441-5","DOIUrl":"https://doi.org/10.1186/s41747-024-00441-5","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Background</h3><p>Heartbeat-based cross-sectional area (CSA) changes in the right main pulmonary artery (MPA), which reflects its distensibility associated with pulmonary hypertension, can be measured using dynamic ventilation computed tomography (DVCT) in patients with and without chronic obstructive pulmonary disease (COPD) during respiratory dynamics. We investigated the relationship between MPA distensibility (MPAD) and respiratory function and how heartbeat-based CSA is related to spirometry, mean lung density (MLD), and patient characteristics.</p><h3 data-test=\"abstract-sub-heading\">Methods</h3><p>We retrospectively analyzed DVCT performed preoperatively in 37 patients (20 female and 17 males) with lung cancer aged 70.6 ± 7.9 years (mean ± standard deviation), 18 with COPD and 19 without. MPA-CSA was separated into respiratory and heartbeat waves by discrete Fourier transformation. For the cardiac pulse-derived waves, CSA change (CSAC) and CSA change ratio (CSACR) were calculated separately during inhalation and exhalation. Spearman rank correlation was computed.</p><h3 data-test=\"abstract-sub-heading\">Result</h3><p>In the group without COPD as well as all cases, CSACR exhalation was inversely correlated with percent residual lung volume (%RV) and RV/total lung capacity (<i>r</i> = -0.68, <i>p</i> = 0.003 and <i>r</i> = -0.58, <i>p</i> = 0.014). In contrast, in the group with COPD, CSAC inhalation was correlated with MLDmax and MLD change rate (MLDmax/MLDmin) (<i>r</i> = 0.54, <i>p</i> = 0.020 and <i>r</i> = 0.64, <i>p</i> = 0.004) as well as CSAC exhalation and CSACR exhalation.</p><h3 data-test=\"abstract-sub-heading\">Conclusion</h3><p>In patients with insufficient exhalation, right MPAD during exhalation was decreased. Also, in COPD patients with insufficient exhalation, right MPAD was reduced during inhalation as well as exhalation, which implied that exhalation impairment is a contributing factor to pulmonary hypertension complicated with COPD.</p><h3 data-test=\"abstract-sub-heading\">Relevance statement</h3><p>Assessment of MPAD in different respiratory phases on DVCT has the potential to be utilized as a non-invasive assessment for pulmonary hypertension due to lung disease and/or hypoxia and elucidation of its pathogenesis.</p><h3 data-test=\"abstract-sub-heading\">Key points</h3><p>• There are no previous studies analyzing all respiratory phases of right main pulmonary artery distensibility (MPAD).</p><p>• Patients with exhalation impairment decreased their right MPAD.</p><p>• Analysis of MPAD on dynamic ventilation computed tomography contributes to understanding the pathogenesis of pulmonary hypertension due to lung disease and/or hypoxia in patients with expiratory impairment.</p><h3 data-test=\"abstract-sub-heading\">Graphical Abstract</h3>\u0000","PeriodicalId":36926,"journal":{"name":"European Radiology Experimental","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140578719","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}