European Radiology Experimental最新文献

{"title":"The emerging role of photon-counting detector CT: primary experience on the integrated assessment of acute knee injuries.","authors":"Frank M Zijta, Alexander Truyens, Rene E Weijers, Joachim E Wildberger, Pieter J Emans, Thomas Flohr","doi":"10.1186/s41747-025-00616-8","DOIUrl":"10.1186/s41747-025-00616-8","url":null,"abstract":"<p><p>Early accurate diagnosis of osseous and soft tissue injuries following acute knee trauma is crucial for guiding clinical management and preventing chronic instability. Radiography is the appropriate first imaging test applied to detect traumatic osseous injuries. CT is indicated based on clinical symptoms and radiographic concordance. In this acute phase, soft tissue injuries are often clinically overlooked due to swelling and restricted motion, which significantly limit comprehensive physical examination. Moreover, both x-ray and conventional CT imaging are insufficient for addressing this issue due to their limited soft tissue contrast resolution. If clinical suspicion of soft tissue injury persists, an MRI will be performed at a later stage. This may lead to undesirable delays in diagnosis and treatment, thereby potentially impacting patient outcomes. Photon-counting detector CT (PCD-CT) offers enhanced, integrated diagnostic possibilities. The use of spectral imaging data, including color-coded virtual non-calcium (VNCa) images, enables the detection of bone marrow edema (BME) and visualization of key stabilizing soft tissue structures, which may assist emergency department clinicians in determining initial treatment, follow-up, and the need for additional imaging. This technical note illustrates the integral use of ultra-high resolution spectral PCD-CT in a case of a knee injury following an alpine skiing accident. RELEVANCE STATEMENT: The integration of photon-counting detector computed tomography with spectral imaging in acute knee trauma enhances visualization of osseous and soft tissue structures, improving diagnostic accuracy. It may optimize early triage and guide initial treatment for soft tissue injuries. KEY POINTS: Photon-counting detector CT (PCD-CT) enables comprehensive fracture, edema, and soft tissue assessment. Case-based notable correlation between injuries suspected on color-coded spectral imaging and MRI. Photon-counting detector CT (PCD-CT) may enhance early clinical decision-making in knee trauma.</p>","PeriodicalId":36926,"journal":{"name":"European Radiology Experimental","volume":"9 1","pages":"71"},"PeriodicalIF":3.6,"publicationDate":"2025-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12335411/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144812541","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":"MRI-based 3D models of cranial nerves in clinical care: a systematic review.","authors":"Manon C M Moll, Luc H E Karssemakers, Milou Baarsma, Loes M M Braun, Leon C Ter Beek, Stevie van der Mierden, Baris Karakullukcu, Ludi E Smeele, Maarten J A van Alphen, Matthijs H Valstar","doi":"10.1186/s41747-025-00608-8","DOIUrl":"10.1186/s41747-025-00608-8","url":null,"abstract":"<p><strong>Background: </strong>Technical advances in magnetic resonance imaging (MRI) acquisition and reconstruction have improved the visualization of anatomical structures such as cranial nerves (CNs) and enabled subsequent three-dimensional (3D) models for use in clinical care. However, a comprehensive overview of indications and techniques is lacking. The current study aimed to comprehensively describe and assess the techniques and applications used in MRI-based 3D modeling of CNs.</p><p><strong>Methods: </strong>We conducted a systematic review of articles published in Medline, Embase, and Scopus databases on clinically applied MRI-based 3D models of CNs up to December 2023. We modified the Quality Assessment Tool for Diagnostic Accuracy Studies to assess the risk of bias.</p><p><strong>Results: </strong>We analyzed 37 studies presenting virtual 3D models of CNs II, III, and V-X in proximity to pathologies in the head and neck area and intracranial, including vestibular schwannoma, skull base tumors, cerebellopontine angle tumors, and neurovascular compression syndrome. Certain studies explored alternative visualization modalities, including printed and augmented reality models. The creation of these 3D models involved the utilization of several MRI sequences and segmentation tools. The models demonstrate potential benefits for preoperative planning, intraoperative decision-making, and patient counseling.</p><p><strong>Conclusion: </strong>MRI-specific sequences and segmentation techniques render CNs in 3D models, helping before and during surgery.</p><p><strong>Relevance statement: </strong>MRI-based 3D models of cranial nerves help surgeons before and during surgery and enhance patient understanding of the procedure and its risks. Wider clinical adoption requires an established workflow, technical expertise, and collaboration to ensure accessibility and knowledge sharing.</p><p><strong>Key points: </strong>3D modeling of cranial nerves is a promising tool for preoperative planning, surgery, and patient-doctor communication. Data heterogeneity and small sample sizes hinder definitive conclusions about the best MRI techniques and segmentation protocols for 3D visualization of cranial nerves. Adopting MRI-based 3D models widely needs a set workflow, technical skills, and team collaboration.</p>","PeriodicalId":36926,"journal":{"name":"European Radiology Experimental","volume":"9 1","pages":"70"},"PeriodicalIF":3.6,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12334392/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144800541","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":"The influence of hepatic arterial blood flow rate on holmium microsphere distribution: an MRI study in perfused porcine livers.","authors":"Tess J Snoeijink, Anne van den Brekel, Jan L van der Hoek, Jaap G M Greve, H Remco Liefers, Milou Boswinkel, Simon J S Ruiter, Joey Roosen, Erik Groot Jebbink, J Frank W Nijsen","doi":"10.1186/s41747-025-00609-7","DOIUrl":"10.1186/s41747-025-00609-7","url":null,"abstract":"<p><strong>Background: </strong>Transarterial radioembolisation (TARE) is a treatment for liver malignancies, involving the injection of radioactive microspheres in the hepatic artery (HA). Tumour-to-nontumour uptake varies among patients, possibly influenced by patient-specific blood flow profiles. To examine the impact of HA blood flow rate and high microsphere dosages on microsphere distribution in normal liver parenchyma, ex vivo magnetic resonance imaging (MRI)-guided machine perfusion experiments were conducted in porcine livers.</p><p><strong>Materials and methods: </strong>Porcine livers were subjected to oxygenated normothermic machine perfusion at three HA flow rates (0.02, 0.15, and 0.22 mL/min/g liver tissue; n = 3 per condition). Five fractions of 250 mg nonradioactive ¹⁶⁵Ho-loaded microspheres were administered to n = 9 livers, and four additional fractions of 1,000 mg to n = 6 livers. Dynamic contrast-enhanced and Ho-sensitive T2*-weighed MR scans were acquired to extract perfusion rates, fictive dose maps, and homogeneity indices (HI).</p><p><strong>Results: </strong>Microsphere distribution correlated moderately with perfusion rate at low HA flow rate (r = 0.611), and very strongly at higher HA flow rates (r = 0.977 and 0.951 for 0.15 and 0.22 mL/min/g, respectively). Homogeneity increased with increasing flow rates, with HIs ranging from 3.68-4.72 at low, to 2.01-2.66 at medium, and 1.60-2.36 at high HA flow rate. HI decreased with higher microsphere concentrations, though distribution patterns remained unchanged.</p><p><strong>Conclusion: </strong>In our ex vivo model, higher HA flow rates resulted in more homogeneous microsphere distributions. The impact on tumourous tissue needs further investigation to determine whether pre-TARE HA blood flow measurements could improve microsphere distribution predictions.</p><p><strong>Relevance statement: </strong>Mapping of the hepatic arterial blood flow rate before transarterial radioembolisation and adjusting the treatment accordingly may help to improve outcomes for patients with liver cancer.</p><p><strong>Key points: </strong>Parameters influencing microsphere distribution were studied in MRI-perfused healthy porcine livers. Higher hepatic arterial blood flow rates led to more homogeneous microsphere distributions. Administering large numbers of microspheres did not alter microsphere distribution patterns. Impact on tumour tissue should be further investigated.</p>","PeriodicalId":36926,"journal":{"name":"European Radiology Experimental","volume":"9 1","pages":"69"},"PeriodicalIF":3.6,"publicationDate":"2025-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12328857/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144795795","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":"Deep learning using nasal endoscopy and T2-weighted MRI for prediction of sinonasal inverted papilloma-associated squamous cell carcinoma: an exploratory study.","authors":"Jiliang Ren, Zhe Ren, Duo Zhang, Ying Yuan, Meng Qi","doi":"10.1186/s41747-025-00610-0","DOIUrl":"10.1186/s41747-025-00610-0","url":null,"abstract":"<p><strong>Background: </strong>Detecting malignant transformation of sinonasal inverted papilloma (SIP) into squamous cell carcinoma (SIP-SCC) before surgery is a clinical need. We aimed to explore the value of deep learning (DL) that leverages nasal endoscopy and T2-weighted magnetic resonance imaging (T2W-MRI) for automated tumor segmentation and differentiation between SIP and SIP-SCC.</p><p><strong>Methods: </strong>We conducted a retrospective analysis of 174 patients diagnosed with SIPs, who were divided into a training cohort (n = 121) and a testing cohort (n = 53). Three DL architectures were utilized to train automated segmentation models for endoscopic and T2W-MRI images. DL scores predicting SIP-SCC were generated using DenseNet121 from both modalities and combined to create a dual-modality DL nomogram. The diagnostic performance of the DL models was assessed alongside two radiologists, evaluated through the area under the receiver operating characteristic curve (AUROC), with comparisons made using the Delong method.</p><p><strong>Results: </strong>In the testing cohort, the FCN_ResNet101 and VNet exhibited superior performance in automated segmentation, achieving mean dice similarity coefficients of 0.95 ± 0.03 for endoscopy and 0.93 ± 0.02 for T2W-MRI, respectively. The dual-modality DL nomogram based on automated segmentation demonstrated the highest predictive performance for SIP-SCC (AUROC 0.865), outperforming the radiology resident (AUROC 0.672, p = 0.071) and the attending radiologist (AUROC 0.707, p = 0.066), with a trend toward significance. Notably, both radiologists improved their diagnostic performance with the assistance of the DL nomogram (AUROCs 0.734 and 0.834).</p><p><strong>Conclusion: </strong>The DL framework integrating endoscopy and T2W-MRI offers a fully automated predictive tool for SIP-SCC.</p><p><strong>Relevance statement: </strong>The integration of endoscopy and T2W-MRI within a well-established DL framework enables fully automated prediction of SIP-SSC, potentially improving decision-making for patients with suspicious SIP.</p><p><strong>Key points: </strong>Detecting the transformation of SIP into SIP-SCC before surgery is both critical and challenging. Endoscopy and T2W-MRI were integrated using DL for predicting SIP-SCC. The dual-modality DL nomogram outperformed two radiologists. The nomogram may improve decision-making for patients with suspicious SIP.</p>","PeriodicalId":36926,"journal":{"name":"European Radiology Experimental","volume":"9 1","pages":"68"},"PeriodicalIF":3.7,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12279620/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144683295","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":"Is a score enough? Pitfalls and solutions for AI severity scores.","authors":"Michael H Bernstein, Marly van Assen, Michael A Bruno, Elizabeth A Krupinski, Carlo De Cecco, Grayson L Baird","doi":"10.1186/s41747-025-00603-z","DOIUrl":"10.1186/s41747-025-00603-z","url":null,"abstract":"<p><p>Severity scores, which often refer to the likelihood or probability of a pathology, are commonly provided by artificial intelligence (AI) tools in radiology. However, little attention has been given to the use of these AI scores, and there is a lack of transparency into how they are generated. In this comment, we draw on key principles from psychological science and statistics to elucidate six human factors limitations of AI scores that undermine their utility: (1) variability across AI systems; (2) variability within AI systems; (3) variability between radiologists; (4) variability within radiologists; (5) unknown distribution of AI scores; and (6) perceptual challenges. We hypothesize that these limitations can be mitigated by providing the false discovery rate and false omission rate for each score as a threshold. We discuss how this hypothesis could be empirically tested. KEY POINTS: The radiologist-AI interaction has not been given sufficient attention. The utility of AI scores is limited by six key human factors limitations. We propose a hypothesis for how to mitigate these limitations by using false discovery rate and false omission rate.</p>","PeriodicalId":36926,"journal":{"name":"European Radiology Experimental","volume":"9 1","pages":"67"},"PeriodicalIF":3.7,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12259500/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144627359","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":"²³Na MRI quantification of sodium content in porcine eyes after immersion in saltwater and freshwater en route to time in water estimation.","authors":"Tobias Lindner, Adrian Konstantin Luyken, Chris Lappe, Oliver Stachs, Thoralf Niendorf, Matthias Lütgens, Stefan Polei, Brigitte Vollmar, Andreas Buettner, Sönke Langner, Marc-André Weber, Ebba Beller","doi":"10.1186/s41747-025-00605-x","DOIUrl":"10.1186/s41747-025-00605-x","url":null,"abstract":"<p><strong>Background: </strong>Differentiation between saltwater and freshwater immersion as well as estimating the corpse's time in water can be challenging. We aimed to establish and examine the feasibility of a novel approach based on sodium magnetic resonance imaging (²³Na MRI) of the eye to facilitate noninvasive sodium quantification.</p><p><strong>Methods: </strong>Enucleated porcine eyes were immersed in NaCl 0.9%, NaCl 3.0%, NaCl 5.85%, distilled water (DW) or lake water (LW) at different time intervals, followed by ²³Na 7-T MRI sodium quantification.</p><p><strong>Results: </strong>After 6 h of immersion, a significant difference in vitreous body (VB) sodium concentration was found for NaCl 5.85% versus DW or LW (p ≤ 0.019). After 24 and 48 h of immersion, a significant difference in VB sodium concentration was found for NaCl 5.85% versus DW, LW, NaCl 3.0% or NaCl 0.9%, as well as for NaCl 3.0% versus DW, LW or NaCl 0.9% (p ≤ 0.001). After 24 h of immersion, lens sodium concentration showed a significant difference for NaCl 5.85% versus DW, LW, NaCl 3.0% or NaCl 0.9% (p ≤ 0.009); after 48 h of immersion, for NaCl 5.85% versus DW, LW, NaCl 3.0% or NaCl 0.9% (p ≤ 0.001), as well as for NaCl 3.0% versus DW, LW or NaCl 0.9% (p ≤ 0.007). For VB, sodium concentration changes over immersion time, and exponential curves were fitted to the data.</p><p><strong>Conclusion: </strong>Using ²³Na MRI in ex vivo porcine eyes with different immersion times in various saltwater concentrations and freshwater equivalents allowed noninvasive quantification of VB and lens sodium concentrations.</p><p><strong>Relevance statement: </strong>Although not a substitute for autopsy, ²³Na MRI assessment of VB and lens sodium concentrations may provide biochemical support in suspected drowning, especially in cases where an internal examination of the body is not authorized or where objections to autopsy are upheld.</p><p><strong>Key points: </strong>Postmortem porcine eyes with different immersion times in saltwater and freshwater. Noninvasive quantification of vitreous body and lens sodium concentrations with ²³Na MRI. Exponential time course of vitreous body sodium concentration in saltwater and freshwater.</p>","PeriodicalId":36926,"journal":{"name":"European Radiology Experimental","volume":"9 1","pages":"66"},"PeriodicalIF":3.7,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12240899/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144601796","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":"In vivo photoacoustic tomography of porcine abdominal organs using Fabry-Pérot sensing integrated platform.","authors":"Damien Gasteau, Alexis Vrignaud, Arnaud Biallais, Fabrice Richard, Gilles Blancho, Julien Branchereau, Benoît Mesnard","doi":"10.1186/s41747-025-00601-1","DOIUrl":"10.1186/s41747-025-00601-1","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate in vivo a fully integrated photoacoustic tomography imaging system based on Fabry-Pérot ultrasound sensing method applied on porcine abdominal organs. This approach could be used by surgeons during intraoperative clinical procedures.</p><p><strong>Methods: </strong>The photoacoustic imaging system was fully integrated into a single structure, and the detection technology was based on a Fabry-Pérot interferometer. The detection probe connected to the imaging system was applied directly to the organs of a male \"large white\" Sus scrofa pig weighing 80 kg, either manually or using a stand, with or without a gel interface. All experiments were performed in compliance with EU Directive 2010/63/EU on animal experimentation (APAFiS #31507).</p><p><strong>Results: </strong>All intraperitoneal and retroperitoneal organs were evaluated using photoacoustic imaging. The evaluation of both hollow and solid organs was successfully conducted with consistent three-dimensional image quality. We demonstrate the system's ability to image blood vessels with diameters ranging from several millimeters down to less than 100 µm. Macroscopic evaluation of the organs using photoacoustic tomography imaging did not reveal any damage or burns caused by the excitation laser.</p><p><strong>Conclusion: </strong>To our knowledge, this is the first reported imaging session of abdominal organs in an in vivo porcine model, performed using a photoacoustic tomography system with Fabry-Pérot interferometer detection. We present a high-resolution photoacoustic tomography system that is closer to routine clinical translation, thanks to a fully integrated system.</p><p><strong>Relevance statement: </strong>Photoacoustic evaluation of organs using a fully integrated system could become a valuable tool for surgical teams for intraprocedural assessment of vascularization.</p><p><strong>Key points: </strong>Photoacoustic imaging visualizes blood vessels without contrast agents or ionizing radiation. Photoacoustic imaging systems detect blood vessels ranging from millimeters to 100 µm. Fully integrated photoacoustic imaging systems are autonomously operable by surgical teams.</p>","PeriodicalId":36926,"journal":{"name":"European Radiology Experimental","volume":"9 1","pages":"65"},"PeriodicalIF":3.7,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12241532/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144601797","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":"Gender difference in cross-sectional area and fat infiltration of thigh muscles in the elderly population on MRI: an AI-based analysis.","authors":"Sara Bizzozero, Tito Bassani, Luca Maria Sconfienza, Carmelo Messina, Matteo Bonato, Cecilia Inzaghi, Federica Marmondi, Paola Cinque, Giuseppe Banfi, Stefano Borghi","doi":"10.1186/s41747-025-00606-w","DOIUrl":"10.1186/s41747-025-00606-w","url":null,"abstract":"<p><strong>Background: </strong>Aging alters musculoskeletal structure and function, affecting muscle mass, composition, and strength, increasing the risk of falls and loss of independence in older adults. This study assessed cross-sectional area (CSA) and fat infiltration (FI) of six thigh muscles through a validated deep learning model. Gender differences and correlations between fat, muscle parameters, and age were also analyzed.</p><p><strong>Methods: </strong>We retrospectively analyzed 141 participants (67 females, 74 males) aged 52-82 years. Participants underwent magnetic resonance imaging (MRI) scans of the right thigh and dual-energy x-ray absorptiometry to determine appendicular skeletal muscle mass index (ASMMI) and body fat percentage (FAT%). A deep learning-based application was developed to automate the segmentation of six thigh muscle groups.</p><p><strong>Results: </strong>Deep learning model accuracy was evaluated using the \"intersection over union\" (IoU) metric, with average IoU values across muscle groups ranging from 0.84 to 0.99. Mean CSA was 10,766.9 mm² (females 8,892.6 mm², males 12,463.9 mm², p < 0.001). The mean FI value was 14.92% (females 17.42%, males 12.62%, p < 0.001). Males showed larger CSA and lower FI in all thigh muscles compared to females. Positive correlations were identified in females between the FI of posterior thigh muscle groups (biceps femoris, semimembranosus, and semitendinosus) and age (r or ρ = 0.35-0.48; p ≤ 0.004), while no significant correlations were observed between CSA, ASMMI, or FAT% and age.</p><p><strong>Conclusion: </strong>Deep learning accurately quantifies muscle CSA and FI, reducing analysis time and human error. Aging impacts on muscle composition and distribution and gender-specific assessments in older adults is needed.</p><p><strong>Relevance statement: </strong>Efficient deep learning-based MRI image segmentation to assess the composition of six thigh muscle groups in over 50 individuals revealed gender differences in thigh muscle CSA and FI. These findings have potential clinical applications in assessing muscle quality, decline, and frailty.</p><p><strong>Key points: </strong>Deep learning model enhanced MRI segmentation, providing high assessment accuracy. Significant gender differences in cross-sectional area and fat infiltration across all thigh muscles were observed. In females, fat infiltration of the posterior thigh muscles was positively correlated with age.</p>","PeriodicalId":36926,"journal":{"name":"European Radiology Experimental","volume":"9 1","pages":"64"},"PeriodicalIF":3.7,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12234423/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144585073","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":"Impact on the microstructure of deep gray matter in unvaccinated patients after moderate-to-severe COVID-19: insights from MRI T1 mapping.","authors":"Masia Fahim, Elke Hattingen, Alina Jurcoane, Jan R Schüre, Svenja Klinsing, Julia Koepsell, Kolja Jahnke, Michael W Ronellenfitsch, Ulrich Pilatus, Maria J G T Vehreschild, Ralf Deichmann, Christophe T Arendt","doi":"10.1186/s41747-025-00598-7","DOIUrl":"10.1186/s41747-025-00598-7","url":null,"abstract":"<p><strong>Background: </strong>To determine changes in quantitative T1 relaxation times (qT1) in deep gray matter in patients recovered from coronavirus disease 2019 (COVID-19).</p><p><strong>Methods: </strong>Unvaccinated COVID-19 participants ≥ 3 months after seropositivity and age- and sex-matched controls were examined using 3-T magnetic resonance imaging. Bilateral measures of thalamus, pallidum, putamen, caudate and accumbens nuclei, and hippocampus were extracted from qT1 maps after automated segmentation. Baseline characteristics and results of tests assessing neurological functions (standardized exam), ability to smell (4-Item Pocket Smell Test), depression (Beck Depression Inventory-II), sleepiness (Epworth Sleepiness Scale), sleep quality (Pittsburgh Sleep Quality Index), health-related quality of life (EQ-5D), and cognitive performance (Montreal Cognitive Assessment) were evaluated.</p><p><strong>Results: </strong>One hundred forty-five subjects (median age, 46 years; 73 females) were included (11/2020-12/2021): 69 recovered after COVID-19 and 76 controls (age, p = 0.532; sex, p = 0.799), without significant differences in qT1 values overall (all p-values > 0.050). Subgroup analysis of participants aged ≥ 40 (age, p = 0.675; sex, p = 0.447) revealed higher qT1 values in previously hospitalized COVID-19 subjects (23/69) compared to controls (47/76) in left and right caudate nuclei (p = 0.009; p = 0.027), left accumbens nucleus (p = 0.017), right putamen (p = 0.041), and right hippocampus (p = 0.020). No correlations were found with macroscopic imaging findings, pre-existing conditions, time since COVID-19 diagnosis, inpatient treatment duration, or test results.</p><p><strong>Conclusion: </strong>T1 mapping revealed microstructural changes in striatal and hippocampal regions of unvaccinated individuals aged ≥ 40 who recovered from moderate-to-severe COVID-19 during the pre-Omicron era.</p><p><strong>Relevance statement: </strong>This study elucidates brain involvement following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, underscoring the need for further longitudinal analyses to assess the potential reversibility, stability or deterioration of these findings.</p><p><strong>Key points: </strong>We hypothesized altered T1 relaxation times in deep gray matter after COVID-19. Unvaccinated participants ≥ 40 years exhibited higher striatal, hippocampal qT1 after moderate-to-severe COVID-19. No qT1 correlations were found with hospitalization duration, pre-existing conditions, or neuro-(psycho)logical tests.</p>","PeriodicalId":36926,"journal":{"name":"European Radiology Experimental","volume":"9 1","pages":"63"},"PeriodicalIF":3.7,"publicationDate":"2025-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12228859/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144567953","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 for predicting the risk of bone fragility fractures in osteoporosis.","authors":"Fabio Massimo Ulivieri, Carmelo Messina, Francesco Maria Vitale, Luca Rinaudo, Enzo Grossi","doi":"10.1186/s41747-025-00572-3","DOIUrl":"10.1186/s41747-025-00572-3","url":null,"abstract":"<p><p>Osteoporosis is widespread with a high incidence rate, resulting in fragility fractures which are a major contributor to mortality among the elderly. Artificial intelligence (AI), in particular artificial neural networks, appears to be useful in managing osteoporosis complexity, where bone mineral density usually reduces with aging, losing the pivotal role in decision-making regarding fracture prediction and treatment choice. Nevertheless, only some osteoporotic patients develop fragility fractures, and treatments often are not prescribed because of the high costs and poor patient adherence. AI can help clinicians to identify patients prone to fragility fractures who can benefit from preventive interventions. We describe herein the methodology issues underlying the potential advantages of introducing AI methods to support clinical decision-making in osteoporosis, being aware of challenges regarding data availability and quality, model interpretability, integration into clinical workflows, and validation of predictive accuracy. The fact that no AI fracture risk prediction software is still publicly available can be related to the fact that few high-quality datasets are available and that AI models, particularly deep learning approaches, often act as 'black boxes', making it difficult to understand how predictions are made. In addition, the effective implementation of predictive software has not reached sufficient integration with existing systems. RELEVANCE STATEMENT: With aging, bone mineral density may lose the pivotal role in osteoporosis decision-making regarding fracture prediction and treatment choice. In this scenario, AI, particularly artificial neural networks (ANNs), can be useful in supporting the clinical management of patients affected by osteoporosis. KEY POINTS: Osteoporosis is a complex disease with many interlinked clinical and radiological variables. Bone mineral density and other known indices do not allow optimal decision-making in patients affected by osteoporosis. ANN analysis can better discriminate osteoporotic patients particularly prone to fragility fractures and can predict future fractures.</p>","PeriodicalId":36926,"journal":{"name":"European Radiology Experimental","volume":"9 1","pages":"62"},"PeriodicalIF":3.7,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12187619/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144486295","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}