Radiologia Medica最新文献

{"title":"Deep learning-driven abbreviated knee MRI protocols: diagnostic accuracy in clinical practice.","authors":"Giovanni Foti, Flavio Spoto, Alessandro Spezia, Luigi Romano, Simone Caia, Francesco Camerani, Damiano Benedetti, Thomas Mignolli","doi":"10.1007/s11547-025-02038-3","DOIUrl":"10.1007/s11547-025-02038-3","url":null,"abstract":"<p><strong>Background: </strong>Deep learning (DL) reconstruction shows potential in reducing MRI acquisition times while preserving image quality, but the impact of varying acceleration factors on knee MRI diagnostic accuracy remains undefined.</p><p><strong>Purpose: </strong>Evaluate diagnostic performance of twofold, fourfold, and sixfold DL-accelerated knee MRI protocols versus standard protocols.</p><p><strong>Materials/methods: </strong>In this prospective study, 71 consecutive patients underwent knee MRI with standard, DL2, DL4, and DL6 accelerated protocols. Four radiologists assessed ligament tears, meniscal lesions, bone marrow edema, chondropathy, and extensor abnormalities. Sensitivity, specificity, and interobserver agreement were calculated.</p><p><strong>Results: </strong>DL2 and DL4 demonstrated high diagnostic accuracy. For ACL tears, DL2/DL4 achieved 98-100% sensitivity/specificity, while DL6 showed reduced sensitivity (91-96%). In meniscal evaluation, DL2 maintained 96-100% sensitivity and 98-100% specificity; DL4 showed 94-98% sensitivity and 97-99% specificity. DL6 exhibited decreased sensitivity (82-92%) for subtle lesions. Bone marrow edema detection remained excellent across acceleration factors. Interobserver agreement was excellent for DL2/DL4 (W = 0.91-0.97) and good for DL6 (W = 0.78-0.89).</p><p><strong>Conclusion: </strong>DL2 protocols demonstrate performance nearly identical to standard protocols, while DL4 maintains acceptable diagnostic accuracy for most pathologies. DL6 shows reduced sensitivity for subtle abnormalities, particularly among less experienced readers. DL2 and DL4 protocols represent optimal balance between acquisition time reduction (50-75%) and diagnostic confidence.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"1460-1471"},"PeriodicalIF":4.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144560906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction: Transarterial embolization for acute lower gastrointestinal bleeding: a retrospective bicentric study.","authors":"Francesco Tiralongo, Daniele Perini, Luca Crimi, Makoto Taninokuchi Tomassoni, Lorenzo Braccischi, Davide Giuseppe Castiglione, Francesco Modestino, Francesco Vacirca, Daniele Falsaperla, Federica Maria Rosaria Libra, Stefano Palmucci, Pietro Valerio Foti, Francesco Lionetti, Cristina Mosconi, Antonio Basile","doi":"10.1007/s11547-025-02024-9","DOIUrl":"10.1007/s11547-025-02024-9","url":null,"abstract":"","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"1516"},"PeriodicalIF":4.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12454612/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144111573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a deep learning model for predicting skeletal muscle density from ultrasound data: a proof-of-concept study.","authors":"Federico Pistoia, Marta Macciò, Riccardo Picasso, Federico Zaottini, Giovanni Marcenaro, Simone Rinaldi, Deborah Bianco, Gabriele Rossi, Luca Tovt, Michelle Pansecchi, Sara Sanguinetti, Mehrnaz Hamedani, Angelo Schenone, Carlo Martinoli","doi":"10.1007/s11547-025-02047-2","DOIUrl":"10.1007/s11547-025-02047-2","url":null,"abstract":"<p><p>Reduced muscle mass and function are associated with increased morbidity, and mortality. Ultrasound, despite being cost-effective and portable, is still underutilized in muscle trophism assessment due to its reliance on operator expertise and measurement variability. This proof-of-concept study aimed to overcome these limitations by developing a deep learning model that predicts muscle density, as assessed by CT, using Ultrasound data, exploring the feasibility of a novel Ultrasound-based parameter for muscle trophism.A sample of adult participants undergoing CT examination in our institution's emergency department between May 2022 and March 2023 was enrolled in this single-center study. Ultrasound examinations were performed with a L11-3 MHz probe. The rectus abdominis muscles, selected as target muscles, were scanned in the transverse plane, recording an Ultrasound image per side. For each participant, the same operator calculated the average target muscle density in Hounsfield Units from an axial CT slice closely matching the Ultrasound scanning plane.The final dataset included 1090 Ultrasound images from 551 participants (mean age 67 ± 17, 323 males). A deep learning model was developed to classify Ultrasound images into three muscle-density classes based on CT values. The model achieved promising performance, with a categorical accuracy of 70% and AUC values of 0.89, 0.79, and 0.90 across the three classes.This observational study introduces an innovative approach to automated muscle trophism assessment using Ultrasound imaging. Future efforts should focus on external validation in diverse populations and clinical settings, as well as expanding its application to other muscles.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"1386-1395"},"PeriodicalIF":4.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144584669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Italian radiologists and dual-energy CT: a state of the art from a shared document by the computed tomography subspecialty section of the Italian society of radiology.","authors":"Maria Antonietta Mazzei, Alfonso Cerase, Giulio Bagnacci, Armando Perrella, Nunzia Di Meglio, Francesco Giuseppe Mazzei, Luca Volterrani, Giulia A Zamboni, Michaela Cellina, Susanna Guerrini, Giuseppe Minetti, Laura Maria Cacioppa, Giorgio Ascenti, Chiara Floridi, Andrea Giovagnoni, Teresa Arcadi, Giovanni Maria Argiolas, Francesco Marcello Arico, Velio Ascenti, Luca Ausili Cefaro, Vittoria Balletta, Claudia Barillà, Stefano Bastaniello, Eugenio Belatti, Raffaele Bisogno, Giovanni Bonenti, Antonio Bottari, Pasquale Bufano, Guido Buonomenna, Cristina Calandra, Tanio Campagnuolo, Delia Campanella, Roberto Cannella, Danilo Caudo, Giuseppe Cicero, Giuseppe Cittadini, Valeria Consoli, Tommaso D'Angelo, Annemilia Del Ciello, Vito Di Martino, Margherita Di Stefano, Alessandra Farchione, Antonio Pio Francioso, Barbara Frittoli, Rachele Fruzza, Valeria Garufi, Chiara Gennari, Francesco Gentili, Ivan Gigantelli, Mariangela Iodice, Anna Rita Larici, Enrica Liguori, Stefano Lofino, Antonio Lo Tito, Nicola Maggialetti, Francesca Menchini, Cinzia Micheli, Vittorio Miele, Nicola Migliaccio, Bruno Minopoli, Ilaria Monteleone, Emanuele Neri, Luca Panebianco, Fabio Perotto, Matteo Pignatelli, Andrea Pisano, Gabriele Polonara, Giuseppe Posillico, Sergio Racchiusa, Lorenzo Santini, Francesco Secchi, Cristian Sica, Salvatore Silipigni, Carmelo Sofia, Alberto Stagno, Silvia Storer, Corrado Tagliati, Ilaria Tanga, Francesco Testa, Michele Tonerini, Giorgio Torrigiani, Chiara Torrisi, Francesco Toscano, Silvia Tresoldi, Umberto Tupputi, Francesco Verde, Carlo Zanolini, Fabio Zecca","doi":"10.1007/s11547-025-02044-5","DOIUrl":"10.1007/s11547-025-02044-5","url":null,"abstract":"<p><strong>Objective: </strong>The main objective was to assess the geographical distribution and main areas of use of dual-energy CT (DECT) scanners in Italy prior to the implementation of the National Recovery and Resilience Plan (NRRP) within the Next Generation EU (NGEU) framework. Secondary objectives included the level of knowledge of DECT among radiologists and some possible solutions to maximize its use.</p><p><strong>Methods: </strong>Between February and March 2022, an anonymous questionnaire was conducted among the members of the Italian Society of Medical and Interventional Radiology (SIRM), using the Google form platform.</p><p><strong>Results: </strong>A total of 261 radiologists (mean age 41 ± 11.7 years) from 90 Italian cities participated in the questionnaire. 42% of them worked in an academic center, and diagnostic imaging was the main area of work for most participants (87%). Most radiologists had some knowledge gap, especially those who did not have a DECT scanner available in their hospital (48.3%). Weekly use of DECT protocols varied widely between centers. Oncological imaging (70.4%) was the main area of use. Radiologists use DECT to improve contrast resolution (65.9%), characterize materials (64.4%), and reduce the amount of contrast agent (60%). 91.1% of participants reported that DECT improved their diagnostic accuracy.</p><p><strong>Conclusion: </strong>DECT scanners have become increasingly available in Italy in recent years, and their number is expected to increase with the NRRP. There is a wide variation in their use and in the expertise of radiologists, leading to a huge untapped potential, that can be improved by specific training. A similar questionnaire will be conducted at the end of the NRRP in 2027.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"1396-1408"},"PeriodicalIF":4.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12454489/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144637816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating the reproducibility of AAST-OIS CT scoring for splenic injuries: the need for standardization.","authors":"Skander Sammoud, Sophie Bastide, Julien Ghelfi, Catherine Arvieux, Valérie Monnin-Bares, Jean-Paul Beregi, Fatah Tidadini, Julien Frandon","doi":"10.1007/s11547-025-02021-y","DOIUrl":"10.1007/s11547-025-02021-y","url":null,"abstract":"<p><strong>Background: </strong>The spleen is frequently injured in blunt abdominal trauma, and proper management depends on accurate CT assessment using the AAST-OIS scoring system. However, the reproducibility of CT scoring in trauma patients remains uncertain.</p><p><strong>Purpose: </strong>To assess the reproducibility of AAST-OIS scoring for high-grade splenic injuries (grades 3, 4, and 5) without vascular anomalies on initial CT scans and to evaluate the clinical impact of misclassification, particularly in relation to hemorrhagic complications.</p><p><strong>Methods: </strong>This study is an ancillary analysis of the SPLASH-randomized clinical trial, which involved 6 Level 1 trauma centers in France. Initial CT scans were scored by the trauma center's radiology team and then independently reviewed by two expert radiologists. Interobserver agreement as assessed between the trauma center radiologists and the expert reviewers, as well as between the two independent experts. The study also examined whether underestimation of injury severity influenced early clinical outcomes.</p><p><strong>Results: </strong>The agreement between trauma center radiologists and expert reviewers was moderate, with kappa coefficients of 0.493 using linear weighting and 0.511 using quadratic weighting, whereas inter-expert agreement was excellent (kappa: 0.905 linear, 0.917 quadratic). The primary source of discordance was the underestimation of parenchymal devascularization, which frequently led to misclassification of grade 4 injuries as grade 3. hile overall complications on Day 5 did not significantly differ between correctly classified and misclassified patients (p = 0.0593), patients whose injuries were underestimated (false negatives) had a threefold higher risk of hemorrhagic complications compared to the rest of the cohort (p = 0.0351).</p><p><strong>Conclusion: </strong>This study highlights the moderate reproducibility of AAST-OIS scoring in emergency trauma settings, emphasizing the need for standardized evaluation protocols to improve diagnostic consistency. Given the higher risk of hemorrhagic complications in underestimated cases, increased awareness of parenchymal devascularization and improved radiological training are essential to optimizing patient outcomes. The integration of AI-based decision-support tools and structured reporting templates may enhance real-time injury classification and reduce observer variability.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"1313-1324"},"PeriodicalIF":4.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144209314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Virtual biopsy through CT imaging: can radiomics differentiate between subtypes of non-small cell lung cancer?","authors":"Federica Palmeri, Marta Zerunian, Michela Polici, Stefano Nardacci, Chiara De Dominicis, Bianca Allegra, Andrea Monterubbiano, Massimiliano Mancini, Riccardo Ferrari, Pasquale Paolantonio, Domenico De Santis, Andrea Laghi, Damiano Caruso","doi":"10.1007/s11547-025-02022-x","DOIUrl":"10.1007/s11547-025-02022-x","url":null,"abstract":"<p><strong>Objective: </strong>This study evaluated the performance of CT radiomics in distinguishing between lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC) at baseline imaging, exploring its potential as a noninvasive virtual biopsy.</p><p><strong>Materials and methods: </strong>A retrospective analysis was conducted, enrolling 330 patients between September 2015 and January 2023. Inclusion criteria were histologically proven ADC or SCC and baseline contrast-enhanced chest CT. Exclusion criteria included significant motion artifacts and nodules < 6 mm. Radiological features, including lung lobe affected, peripheral/central location, presence of emphysema, and T/N radiological stage, were assessed for each patient. Volumetric segmentation of lung cancers was performed on baseline CT scans at the portal-venous phase using 3DSlicer software (v5.2.2). A total of 107 radiomic features were extracted and selected using the least absolute shrinkage and selection operator (LASSO) and tenfold cross-validation. Multivariable logistic regression analysis was employed to develop three predictive models: radiological features-only, radiomics-only, and a combined model, with statistical significance set at p < 0.05. Additionally, an independent external validation cohort of 16 patients, meeting the same inclusion and exclusion criteria, was identified.</p><p><strong>Results: </strong>The final cohort comprised 200 ADC and 100 SCC patients (mean age 68 ± 10 years, 184 men). Two radiological and 21 radiomic features were selected (p < 0.001). The Radiological model achieved AUC 0.73 (95% CI 0.68-0.78, p < 0.001), 72.3% accuracy. The radiomics model achieved AUC 0.80 (95% CI 0.75-0.85, p < 0.001), 75.6% accuracy. The combined model achieved AUC 0.84 (95% CI 0.80-0.88, p < 0.001), 75.3% accuracy. External validation (n = 15) yielded AUC 0.78 (p = 0.05).</p><p><strong>Conclusion: </strong>The combined radiologic-radiomics model showed the best performance in differentiating ADC from SCC.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"1363-1372"},"PeriodicalIF":4.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12454503/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144120726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 magnetic resonance image compilation (MAGiC) abilities of therapeutic selection and prediction on recurrence risk factors and short-term treatment efficacy in cervical cancer.","authors":"Xiaorong Ou, Hui Liu, Weiyin Vivian Liu, Yue Li, Wenguang Liu, Yu Bai, Jinbiao Chen, ZhengHao Deng, Wenzheng Li, Yigang Pei","doi":"10.1007/s11547-025-02042-7","DOIUrl":"10.1007/s11547-025-02042-7","url":null,"abstract":"<p><strong>Objectives: </strong>To investigate the feasibility of MAGiC (hereafter, sy-T2WI; T1, T2, and PD maps) in determination of treatment plan and prediction of recurrence risk factors (RRF) and short-term treatment efficacy (STE) in patients with cervical cancer (CC) using hr-T2WI and DWI as reference standards.</p><p><strong>Methods: </strong>119 consecutive CC patients who underwent MAGiC, hr-T2WI and DWI were prospectively recruited from October 2021 to March 2024. The subjective evaluation of image quality and tumor staging using sy-T2WI and hr-T2WI was conducted. The accuracy, sensitivity and specificity of sy-T2WI were analyzed for selection of a treatment strategy (stage IB-IIA: surgical operation; stage IIB-IVA: CCRT). RRF and STE were evaluated in staging IB-IIA and IIB-IVA CC patients respectively. Then, the area under the curve (AUC) was used to objectively predict RRF and STE using the quantitative T1, T2, PD maps, their combinations, and apparent diffusion coefficient (ADC).</p><p><strong>Results: </strong>There was no significant difference of image quality (all P > 0.05), but a strong agreement on tumor staging (Kappa value = 0.935; p < 0.001) between sy-T2WI and hr-T2WI. The accuracy, sensitivity, and specificity of sy-T2WI in deciding treatment strategies were 0.908, 0.908, and 0.999, respectively. Furthermore, the combination of T1 and T2 values was superior to ADC values for predicting RRF (AUC: 0.980 vs. 0.776; p = 0.005) in staging IB-IIA and STE (AUC: 0.982 vs. 0.737; p < 0.001) in IIB-IVA CC subjects.</p><p><strong>Conclusions: </strong>MAGiC is a promising technique for determination on treatment selection, RRF prediction and STE prognosis in CC patients as its performance is equivalent and even superior to hr-T2WI and DWI.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"1325-1338"},"PeriodicalIF":4.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12454491/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144560905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 hypothalamic macrostructure in episodic cluster headache: a volumetric segmentation MRI study.","authors":"Davide Chiffi, Antonio Di Renzo, Giada Giuliani, Chiara Abagnale, Marta Altieri, Gabriele Sebastianelli, Francesco Casillo, Vittorio Di Piero, Gianluca Coppola, Francesca Caramia","doi":"10.1007/s11547-025-02041-8","DOIUrl":"10.1007/s11547-025-02041-8","url":null,"abstract":"<p><strong>Purpose: </strong>The functional involvement of the hypothalamus in the pathophysiology of episodic cluster headache (eCH) is well known, but its macrostructural involvement remains unclear. In this study, we investigated differences in the volumetry of the entire hypothalamus and its subunits in patients with in-bout eCH during headache-free periods.</p><p><strong>Material and methods: </strong>We examined hypothalamic volumes in 26 eCH patients (scanned during bout periods but outside of active attacks and off prophylactic medications) and 20 age- and sex-matched healthy controls (HCs). Magnetic resonance imaging (MRI) with T1-weighted sequences was used to perform volumetric segmentation of hypothalamic subunits (anterior-inferior, anterior-superior, posterior, tubular inferior, and tubular superior) and total hypothalamic volume. General linear models were used to assess volumetric differences, adjusting for age, sex, and total intracranial volume.</p><p><strong>Results: </strong>No statistically significant differences were found in either hypothalamic subunit volumes or total hypothalamic volumes between eCH patients and HCs (p > 0.05). Additionally, no correlations emerged between the hypothalamic volumes and CH clinical features.</p><p><strong>Conclusion: </strong>These findings align with previous studies, suggesting that CH pathophysiology may involve network-level functional alterations rather than macrostructural hypothalamic changes.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"1483-1488"},"PeriodicalIF":4.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144507965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Aortic valve and coronary artery calcium scoring: impact of half- versus standard-dose protocols.","authors":"Cesare Mantini, Filippo Cademartiri, Luca Procaccini, Claudio Tana, Domenico Mastrodicasa, Luca Saba, Sabina Gallina, Marco Tana, Massimo Caulo, Fabrizio Ricci","doi":"10.1007/s11547-025-02027-6","DOIUrl":"10.1007/s11547-025-02027-6","url":null,"abstract":"<p><strong>Aims: </strong>CT acquisition parameters and reconstruction techniques may affect the accuracy of calcium scoring measurements with a potential impact on clinical decision making. We evaluated the agreement of half- versus standard-dose protocols for assessment of aortic valve (AVCS HD and AVCS SD protocols) and coronary artery calcium scoring (CACS HD and CACS SD protocols) with and without the application of iterative reconstruction.</p><p><strong>Methods: </strong>We enrolled 144 consecutive patients (mean age 83 ± 9 years) with known aortic stenosis undergoing 128-row prospective sequential CT with standard (120 kVp/20 mAs) and half-dose (120 kVp/10 mAs) protocols for both AVCS and CACS evaluation. The half-dose dataset was processed with and without iterative reconstruction. Agreement and precision of different protocols were evaluated using linear regression and Bland-Altman analysis. Additionally, we assessed the reclassification of cardiovascular risk based on the Mayo Clinic system and the likelihood of severe aortic stenosis using sex-specific categories.</p><p><strong>Results: </strong>Compared with the standard dose, the half-dose protocol with or without iterative reconstruction demonstrated optimum agreement for the evaluation of AVCS (r = 0.99; R² = 0.97) and CACS (r = 0.96; R² = 0.93). The half-dose iterative reconstruction protocol yielded a very low rate of reclassification aortic stenosis severity (1.4%) and cardiovascular risk (6.2%). The half-dose protocol resulted in 47.5% radiation dose reduction compared to standard dose (dose-length product: 8.5 ± 1.1 vs. 17.9 ± 2.7; p < 0.001).</p><p><strong>Conclusions: </strong>Our findings suggest that the half-dose protocol with iterative reconstruction provides reliable and accurate results for both AVCS and CACS assessment. This evidence underscores the potential to optimize radiation dose while preserving the precision of diagnostic outcomes, thereby minimally impacting clinical management.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"1352-1362"},"PeriodicalIF":4.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144249325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Does arterial spin labelling represent a valid alternative to other MR perfusion techniques in neuro-oncology?","authors":"Andrea Romano, Allegra Romano, Giulia Moltoni, Giulia de Rosa, Silvia D'Eufemia, Antonella Blandino, Cristiana Monopoli, Lidia Zema, Sara De Giorgi, Sara Tristano, Tamara Ius, Alessia Rega, Vittorio Pio Mancini, Gabriele Madonia, Alessandro Bozzao","doi":"10.1007/s11547-025-02048-1","DOIUrl":"10.1007/s11547-025-02048-1","url":null,"abstract":"<p><p>This review examines the distinctive role of arterial spin labelling (ASL) in neuro-oncology. ASL is a completely non-invasive MRI technique that quantifies cerebral perfusion without exogenous contrast agents, making it an attractive alternative to dynamic susceptibility contrast (DSC) and dynamic contrast-enhanced (DCE) perfusion-particularly WHEN gadolinium cannot be administered or when serial follow-up studies are required. Unlike DSC, ASL is immune to magnetic susceptibility artefacts, and, unlike DCE, it does not demand lengthy acquisitions or complex post-processing. The available evidence indicates that ASL performs well in grading gliomas and in characterizing brain metastases, lymphomas, and meningiomas. Its superiority over other perfusion methods becomes most apparent in longitudinal follow-up of cerebral gliomas, where it reliably tracks haemodynamic changes, and in assessing tumour-related conditions such as epilepsy and paraneoplastic syndromes. Overall, ASL offers a repeatable and dependable assessment of tumour perfusion and vascularity, thereby supporting more accurate diagnosis, grading, and treatment monitoring in neuro-oncology.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"1489-1502"},"PeriodicalIF":4.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144637815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}