Acta radiologica最新文献

{"title":"The worth of diffusion-weighted imaging for quantifying liver iron concentration in transfusion-dependent thalassemia patients.","authors":"Chaotian Luo, Fei Peng, Cheng Tang, Xiaojing Ning, Yanyan Zhang, Zengqin Liang, Peng Peng","doi":"10.1177/02841851261483225","DOIUrl":"https://doi.org/10.1177/02841851261483225","url":null,"abstract":"<p><p>BackgroundMagnetic resonance imaging (MRI) is currently the primary method for evaluating liver iron concentration (LIC); however, most techniques necessitate intricate data post-processing. Consequently, the development of simple quantitative methods is highly desirable.PurposeTo investigate the value of diffusion-weighted imaging (DWI) for quantifying LIC in patients with transfusion-dependent thalassemia (TDT).Material and MethodsData were collected on patients with TDT, including conventional MRI iron quantification sequences such as FerriScan R2, T2*, and DWI data. The liver's apparent diffusion coefficient (ADC) and T2* values were measured, and these measurements were compared to the LIC reports obtained from MRI-R2/FerriScan, which are U.S. Food and Drug Administration certified, to evaluate the utility of ADC values in quantitatively assessing LIC.ResultsAmong the 58 patients with TDT, the linear regression analysis indicated R² values in the range of approximately 0.4765-0.6022 for ADC values and LIC, with non-linear regression R² in the range of 0.6263-0.6479. The T2* model demonstrated excellent diagnostic accuracy for extremely severe liver iron overload with an area under the receiver operating characteristic curve (AUC) of 0.996, whereas the ADC model exhibited a similarly high AUC in the range of 0.891-0.941.ConclusionIn patients with known hepatic iron overload due to TDT, ADC values show a correlation with liver iron content and have the potential to serve as a supplementary method for quantitative measurement of liver iron by T2*/R2*.</p>","PeriodicalId":7143,"journal":{"name":"Acta radiologica","volume":" ","pages":"2841851261483225"},"PeriodicalIF":1.2,"publicationDate":"2026-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148910522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Should We Be Aiming For A \"Stent-first Strategy\" in the Management of Malignant Biliary Obstruction? A Retrospective Single-Center Analysis.","authors":"Rathna B Veerni, Sana Sheykhzadeh, Alexander Valentinov Jordanov, Frank Carey, Tariq Ali","doi":"10.1177/02841851261459117","DOIUrl":"https://doi.org/10.1177/02841851261459117","url":null,"abstract":"<p><p>BackgroundPercutaneous transhepatic cholangiography (PTC) is essential when endoscopic retrograde cholangiopancreatography (ERCP) fails or is contraindicated. Despite emerging evidence favoring primary stenting, data directly comparing it with the traditional two-staged drainage approach remain scarce.PurposeTo evaluate the efficacy, complication rates, and reintervention burden of initial stent placement versus drainage.Material and MethodsA retrospective single-center analysis of 96 patients undergoing PTC (2021-2024) was conducted; 95 received intervention (primary stent n = 30, drain n = 65). Outcomes (bilirubin kinetics, clinical success, complications, reinterventions) were compared using Welch's <i>t</i>-test, chi-square test, or Fisher's exact test, with multivariable adjustment for baseline differences.ResultsMalignant obstruction accounted for 96.8% of cases; technical success was 97.9% (CIRSE standards). Bilirubin reduction was greater with stents (45.7% vs. 35.5%; mean difference 10.2 percentage points, 95% confidence interval = 0.3-20.0; <i>P</i> = 0.043), attenuated after adjustment (<i>β</i> = 9.8 pp; <i>P</i> = 0.093). Complications, all reinterventions, and combined adverse events were lower with stents (23.3% vs. 55.4%, 16.7% vs. 73.8%, and 30.0% vs. 86.2%; all <i>P</i> ≤0.004); adjusted analyses confirmed independently reduced odds (adjusted odds ratio = 0.26, 0.08, and 0.07, respectively). Clinical success trended higher with stents (46.7% vs. 38.5%) but was not statistically significant. Overall, 30-day mortality was 17.7% with 2% procedure-related. Median post-intervention survival was 101 days.ConclusionIn this retrospective single-center cohort, a stent-first approach was associated with greater bilirubin reduction and fewer complications and reinterventions than drainage-first, without compromising technical success or survival. Findings are hypothesis-generating and require prospective multicenter validation.</p>","PeriodicalId":7143,"journal":{"name":"Acta radiologica","volume":" ","pages":"2841851261459117"},"PeriodicalIF":1.2,"publicationDate":"2026-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148890670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence in prostate MRI: Comparative diagnostic performance in a high-prevalence cohort.","authors":"Nádia Gonçalves Ferreira, Owen Matthew Truscott Thomas, Kjell-Inge Gjesdal, Stig Müller, Jan Oldenburg, Ingrid Framås Syversen, Anders Christian Hansen, Jonn Terje Geitung","doi":"10.1177/02841851261470455","DOIUrl":"10.1177/02841851261470455","url":null,"abstract":"<p><p>BackgroundArtificial intelligence (AI) is increasingly used in prostate cancer diagnostic workflows but remains insufficiently validated in high-prevalence cohorts often encountered in academic referral centers.PurposeTo compare the diagnostic performance of licensed AI software with routine radiologist readings of prostate MRI, using histopathology as the reference standard.Material and MethodsIn this retrospective study, 1000 patients underwent prostate MRI for suspected prostate cancer (between May 2020 and December 2024), followed by transperineal biopsy; 391 subsequently underwent radical prostatectomy. Diagnostic performance was assessed using sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy across PI-RADS thresholds. Receiver operating characteristic (ROC) analysis, Cohen's kappa for inter-rater agreement, and paired McNemar's test were performed.ResultsIn total, 959 patients (mean age = 69.7 ± 8.4 years) were included; clinically significant prostate cancer (csPCa) was found in 830 (86.5%) patients. AI assigned more cases to PI-RADS 1-2 and fewer to PI-RADS 3 (κ = 0.388; <i>P</i> <.001). At the PI-RADS ≥3 threshold, radiologists showed sensitivity 96.0%, specificity 20.9%, accuracy 85.9%, PPV 88.7%, and NPV 45.0%, compared with 91.3%, 37.2%, 84.0%, 90.3%, and 40.0% for AI (<i>P</i> <.001). ROC performance was comparable (AUC 0.763 vs. 0.739; <i>P</i> = .28). In the prostatectomy subgroup, AI demonstrated a higher false-negative rate (8.4% vs. 4.1%; odds ratio = 3.83, 95% confidence interval [CI] = 1.52-11.51).ConclusionAI showed diagnostic performance comparable to that of radiologists for csPCa detection, with no significant difference in AUC. AI reduced indeterminate PI-RADS 3 scores but missed more significant cancers.</p>","PeriodicalId":7143,"journal":{"name":"Acta radiologica","volume":" ","pages":"765-774"},"PeriodicalIF":1.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13530345/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148590029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Inter-observer variation in rectal cancer gross tumor volume delineation by radiologist and oncologist.","authors":"Iuliana Stratulat, Lennart Nedar, Erik Almhagen, Alexander Valdman","doi":"10.1177/02841851261468005","DOIUrl":"10.1177/02841851261468005","url":null,"abstract":"<p><p>BackgroundThe PRORECT trial compares proton and photon radiotherapy in rectal cancer.PurposeTo evaluate inter-observer agreement in gross tumor volume (GTV) delineation between a radiation oncologist and a radiologist in the PRORECT trial. In addition, we evaluated baseline tumor volume and length as predictors of clinical complete response (cCR) and compared tumor length and tumor and nodal staging (TN-stage) between diagnostic magnetic resonance imaging (dMRI) and treatment planning MRI (tpMRI).Material and MethodsA total of 50 consecutive patients underwent dMRI and tpMRI. GTV on tpMRI were delineated by a radiation oncologist (GTVo) and a radiologist (GTVr). Tumor lengths and TN staging were determined by the radiologist on both dMRI and tpMRI.ResultsPatients underwent dMRI and tpMRI with a median interval of 23 days (range=10-51 days). Median GTVo and GTVr volumes were 41.3 cm³ (range=3.7-149.9 cm³) and 29.6 cm³ (range=1.1-137 cm³), respectively. The median Dice score was 0.75 (range=0.3-0.86). GTVo and GTVr were highly positively correlated (r(48) = 0.919; <i>P</i> < 0.001) and the median volume difference was significant (W, Z = -4.5214; <i>P</i> < 0.001). GTVr volume, but not tumor length, was significantly correlated with cCR (<i>r</i>_pb = -0.395, <i>n</i> = 50; <i>P</i> = 0.005). Increasing GTVr was associated with reduced likelihood of achieving cCR. No changes in TN stage between dMRI and tpMRI were observed.ConclusionThe overall inter-observer agreement in GTV delineation between radiologist and radiation oncologist was good (median Dice score = 0.75 [range=0.3-0.86]). There was a small difference in measured tumor length between dMRI and tpMRI, but no change in TN stage between dMRI and tpMRI. GTVr was a significant predictor of achieving cCR.</p>","PeriodicalId":7143,"journal":{"name":"Acta radiologica","volume":" ","pages":"749-755"},"PeriodicalIF":1.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148519769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated brain MRI protocol adaptation based on imaging findings using AI: diagnostic performance and agreement with neuroradiologists.","authors":"Kaining Sheng, Alexander Cuculiza Henriksen, David Mihal, Matthew Poturalski, Douglas Martin, Stephen Jones, Andreas Hjelm Brandt, Natalia Grundtvig, Simon Yamasaki Jensen, Akshay Pai, Thomas Truelsen, Michael Bachmann Nielsen, Jonathan Frederik Carlsen, Chintan Shah","doi":"10.1177/02841851261464151","DOIUrl":"10.1177/02841851261464151","url":null,"abstract":"<p><p>BackgroundSelecting optimal brain magnetic resonance imaging (MRI) protocols is a manual, error-prone process, often complicated by incomplete clinical information. Automated AI-based analysis of initial imaging sequences offers a potential strategy for dynamic protocol adaptation while the patient is still in the scanner.PurposeTo evaluate the diagnostic performance and agreement with neuroradiologists of an AI tool designed to automatically adapt brain MRI protocols based on the detection of critical findings (brain infarcts, acute hemorrhages, and mass lesions) using three initial imaging sequences.Material and MethodsWe retrospectively collected consecutive cohorts of brain MRI scans from two tertiary medical centers. The cohorts were consecutively enriched with positive findings of brain infarcts, hemorrhages, and mass lesions. An AI tool and neuroradiologists independently assessed three sequences (diffusion-weighted imaging, T2-FLAIR, SWI/T2*-GRE) for critical findings and recommended protocol adaptations from seven options. Diagnostic performance was compared against reference findings based on radiological reports and de novo imaging review.ResultsA total of 752 patients were included (325 men; mean age=61 years). The AI tool's pooled sensitivity for detecting infarcts, hemorrhages, and mass lesions was 92% (95% CI=86-96), 75% (95% CI=64-84), and 71% (95% CI=61-79), with pooled specificity of 93% (95% CI=90-95), 86% (95% CI=83-88), and 90% (95% CI=87-92), respectively. Agreement on protocol adaptation between the AI and neuroradiologists was moderate (κ=0.47), though concordance was high (84%-87%) for scans requiring no further adaptations.ConclusionThe AI tool demonstrated reasonable pathology detection, relevant protocol recommendations, and potential to ensure appropriate imaging protocols in high-volume, low-risk scan scenarios, but expert oversight is required.</p>","PeriodicalId":7143,"journal":{"name":"Acta radiologica","volume":" ","pages":"756-764"},"PeriodicalIF":1.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148534778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical evaluation of deep learning-accelerated 3D FLAIR imaging at 1.5T and 3T for visualization of cerebral white matter lesions.","authors":"Sittaya Buathong, Alexandra Filippakis, Chen Hua Chiang, Eugene Milshteyn, Mary Thomas, Dan Rettmann, Christopher Hemond, Susie Y Huang, Ivan Jambor","doi":"10.1177/02841851261460842","DOIUrl":"10.1177/02841851261460842","url":null,"abstract":"<p><p>BackgroundFluid-attenuated inversion recovery (FLAIR) imaging is a standard sequence used for the detection of white matter lesions; however, 1-mm isotropic FLAIR can take 5-7 min at 1.5T and 3T using routine methods, limiting routine use of high-resolution 3D FLAIR imaging.PurposeTo evaluate a deep learning (DL)-based unrolled optimization 3D FLAIR technique, Sonic DL™ 3D (SDL), in comparison to a standard 3D FLAIR protocol, both combined with DL-based post-processing (AIR™ Recon DL) at 1.5T and 3T.Material and MethodsA total of 67 patients (15 scanned at 1.5T and 52 at 3T) with suspected white matter lesions were included. Two neuroradiologists performed blinded, head-to-head image quality evaluation (motion, noise, and overall diagnostic quality). Quantitative lesion volume and lesion counts were derived from automated segmentation using SPM 12. Cohen's kappa, Wilcoxon signed-rank tests, and paired <i>t</i>-tests were applied.ResultsAt 1.5T, SDL FLAIR (4 min 53 s) reduced scan times by 15% compared to standard 3D FLAIR (5 min 43 s) and performed similarly or better in lesion visualization and image quality, with significantly (<i>P</i> <0.05) improved noise quality. At 3T, SDL FLAIR (2 min 45 s) achieved a reduction in scan time of approximately 35% compared to standard 3D FLAIR (4 min 15 s) and showed improved lesion conspicuity (periventricular, juxtacortical, and other regions) and image quality metrics. However, except for noise quality, these differences did not reach statistical significance despite moderate to almost perfect interrater agreement (Cohen's kappa 0.55-0.85; <i>P</i> <0.001).ConclusionAccelerated SDL FLAIR demonstrated improved diagnostic quality, comparable lesion conspicuity, and volumetric measurements to standard 3D FLAIR sequence at 1.5T and 3T.</p>","PeriodicalId":7143,"journal":{"name":"Acta radiologica","volume":" ","pages":"775-783"},"PeriodicalIF":1.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148590082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficacy and safety of boosted transarterial radioembolization in patients with chemoembolization-refractory hepatocellular carcinoma.","authors":"Gun Ha Kim, Eunbyeol Ko, Jeongyeon Kim, Minyoung Oh, Changhwan Sung, Jin Hyoung Kim, Dong Il Gwon","doi":"10.1177/02841851261468006","DOIUrl":"10.1177/02841851261468006","url":null,"abstract":"<p><p>BackgroundRepeated transarterial chemoembolization (TACE) may lead to treatment refractoriness, in which tumors fail to respond despite technically adequate procedures. However, evidence to guide optimal management strategies for patients with TACE-refractory hepatocellular carcinoma (HCC) remains limited.PurposeTo assess the efficacy and safety of boosted transarterial radioembolization (TARE) in patients with TACE-refractory HCC.Material and MethodsA total of 41 consecutive patients with TACE-refractory HCC underwent boosted TARE between November 2021 and December 2025. Tumor response, time to local tumor progression (TTLTP), time to progression (TTP), overall survival (OS), and adverse events were retrospectively analyzed.ResultsIn total, 41 patients (36 men; mean age=66.1 ± 9.3 years) were evaluated. The median number of prior TACE sessions was 4 (range=2-11). Best index tumor response was complete response in 31 (75.6%) patients, partial response in 6 (14.6%), and stable disease in 3 (7.3%), yielding an objective response rate of 90.2%. Median TTLTP was not reached at the time of analysis. Median TTP was 6.5 months (95% confidence interval [CI]=3.1-8.8). Median OS was 31.8 months (95% CI=19.4-not reached). Among 25 patients with disease beyond the Milan criteria, 20 (80.0%) were successfully downstaged to within the Milan criteria, of whom seven subsequently underwent curative-intent surgery. Longer OS was observed in surgical patients compared with non-surgical patients (<i>P</i> = .048). Severe adverse events occurred in 4 (9.8%) patients. One patient died from sepsis after tumor rupture.ConclusionBoosted TARE may provide favorable local tumor control in selected patients with TACE-refractory HCC. Careful patient selection and dosimetry remain essential.</p>","PeriodicalId":7143,"journal":{"name":"Acta radiologica","volume":" ","pages":"737-748"},"PeriodicalIF":1.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148434659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnostic performance of deep-learning algorithms in radiographic grading of knee osteoarthritis: a systematic review and meta-analysis.","authors":"Xiaolu Ren, Xinyu Jin, ZhiJun Wang, Ting Li","doi":"10.1177/02841851261462501","DOIUrl":"10.1177/02841851261462501","url":null,"abstract":"<p><p>BackgroundDeep learning (DL) has been increasingly applied to grade knee osteoarthritis (KOA) on radiographs, but reported diagnostic performance varies across Kellgren-Lawrence (K-L) grades.PurposeTo systematically evaluate the diagnostic performance of DL models for radiographic KOA grading.Material and MethodsPubMed, Embase, and Web of Science were searched through November 2024 for studies using DL algorithms to grade KOA on X-ray images. Sensitivity and precision were synthesized. Heterogeneity was assessed using the <i>I</i>² statistic. Subgroup analyses and meta-regression were conducted according to transfer learning, external validation, multi-task learning, joint training strategy, and data splitting. Publication bias was assessed using funnel plots and Egger's test. Study quality was evaluated using the revised QUADAS-2 tool.ResultsOf 1004 records screened, 32 studies were included. Pooled sensitivity for K-L grades 0-4 was 0.90, 0.66, 0.80, 0.87, and 0.88, respectively, and pooled precision was 0.87, 0.71, 0.81, 0.86, and 0.91, respectively. Diagnostic performance was poorest for K-L grade 1, particularly in sensitivity, indicating limited reliability for early-stage KOA detection. Heterogeneity was high across outcomes and grades, particularly for sensitivity in K-L grades 1 and 2 and precision in K-L grades 0 and 1. Meta-regression identified transfer learning and data splitting as potential sources of heterogeneity. Egger's tests suggested no statistically significant small-study effects.ConclusionDL models showed better diagnostic performance for moderate-to-severe radiographic KOA than for early-stage disease. However, the poor sensitivity for K-L grade 1, substantial heterogeneity, and limited external validation suggest that current DL models are not yet reliable for early KOA detection or ready for routine clinical implementation. Further standardized reporting, robust validation, and multicenter external evaluation are required.</p>","PeriodicalId":7143,"journal":{"name":"Acta radiologica","volume":" ","pages":"723-736"},"PeriodicalIF":1.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148468227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A magnetic resonance imaging analysis of cognitively discordant monozygotic and dizygotic twins: a comparative study of visual rating method and tensor-based morphometry.","authors":"Terhi Tuokkola, Riitta Parkkola, Juha Koikkalainen, Tero Vahlberg, Jaakko Kaprio, Jyrki Lötjönen, Vuoksimaa Eero, Juha Rinne","doi":"10.1177/02841851261438991","DOIUrl":"10.1177/02841851261438991","url":null,"abstract":"<p><p>BackgroundAtrophy of the medial temporal lobes and deep gray matter, along with ventricular enlargement, are typical structural magnetic resonance imaging (MRI) findings in the brains of patients with Alzheimer's disease (AD). However, there are few twin studies on this subject.PurposeTo determine whether the visual rating method (VRM) and tensor-based morphometry (TBM) can detect the structural brain changes in monozygotic and dizygotic twin pairs discordant for memory performance.Material and MethodsA total of 12 monozygotic and 24 same-sex dizygotic twin pairs discordant for memory performance and 44 cognitively healthy non-twin volunteers were studied.ResultsSignificant within-twin pair differences in brain atrophy were detected in the medial temporal lobes and ventricular areas (both with VRM and TBM), and in deep gray matter structures (TBM only). When monozygotic and dizygotic twin pairs were analyzed separately, the differences were not statistically significant.ConclusionOur study yielded promising TBM results in distinguishing memory-discordant co-twins in temporal and deep gray matter atrophy. In addition, the findings confirm the assumption that AD affects twins in the same way, independent of genes. Studies with larger twin cohorts would better reveal possible differences between monozygotic and dizygotic twin pairs.</p>","PeriodicalId":7143,"journal":{"name":"Acta radiologica","volume":" ","pages":"784-798"},"PeriodicalIF":1.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148700427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Acta Radiologica Prizes 2025: Xenia Forsselliana 2025 and the International Scientific Prize.","authors":"Lars Lonn, Janne Nurminen","doi":"10.1177/02841851261465096","DOIUrl":"https://doi.org/10.1177/02841851261465096","url":null,"abstract":"","PeriodicalId":7143,"journal":{"name":"Acta radiologica","volume":" ","pages":"2841851261465096"},"PeriodicalIF":1.2,"publicationDate":"2026-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148862867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}