Acta radiologica最新文献

{"title":"A study on the changes of white matter microstructure in breast cancer patients undergoing chemotherapy based on DTI technology.","authors":"Yuan Li, Ya-Qi Song, Zhong-Ru Sun, Ning Wang, Jian-Guo Xia, Wei-Zhong Tian, Mei Lin","doi":"10.1177/02841851251321104","DOIUrl":"https://doi.org/10.1177/02841851251321104","url":null,"abstract":"<p><p>BackgroundBreast cancer is a prevalent cancer affecting women globally, with incidence rates rising rapidly.PurposeTo examine the diffusion tensor imaging (DTI) data of patients with breast cancer before and after chemotherapy through tract-based spatial statistical analysis (TBSS).Material and MethodsCognitive and neuropsychological tests and whole-brain DTI were administered to patients with breast cancer who did not receive postoperative chemotherapy (C-) or received postoperative chemotherapy (C+) and healthy controls (HCs). Structural differences across groups were compared through fractional anisotropy (FA), mean diffusivity rate (MD), radial diffusivity tensor (RD), and axial diffusivity tensor (AD). Spearman's correlation analysis was employed to explore the association of FA, MD, RD, and AD values in different brain regions with the results of cognitive and neuropsychological tests, as well as the relationship between DTI parameters and cognitive performance as measured by the Montreal Cognitive Assessment (MoCA) scores.ResultsCompared with the C- group, the C + group exhibited significant reduced FA values and increased MD and RD values in the genu of the corpus callosum, bilateral anterior and superior corona radiata, left posterior thalamic radiation, left external capsule, and bilateral superior longitudinal fasciculus. Spearman's correlation analysis showed a notable association between reduced FA values in specific regions and decreased cognitive performance, as measured by MoCA scores.ConclusionThese findings suggest that the alterations in white matter microstructure induced by breast cancer chemotherapy may contribute to cognitive decline. Further research is warranted to strengthen evidence for this relationship.</p>","PeriodicalId":7143,"journal":{"name":"Acta radiologica","volume":" ","pages":"2841851251321104"},"PeriodicalIF":1.1,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143623149","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":"Glioblastoma IDH-wild type: imaging independent predictors of gross total resection (GTR) using the VASARI feature set and tumoral volumetric measurements.","authors":"David Timaran-Montenegro, Luis Nunez, Antonio Dono, Octavio Arevalo, Andres Rodriguez, Kamand Khalaj, Jennifer McCarty, Jay-Jiguang Zhu, Yoshua Esquenazi, Roy Riascos","doi":"10.1177/02841851251316400","DOIUrl":"https://doi.org/10.1177/02841851251316400","url":null,"abstract":"<p><p>BackgroundExtent of resection (EOR), including gross total resection (GTR), is one of the most important factors in predicting overall survival (OS) in IDH-wild type (IDH-WT) glioblastoma patients. Although GTR represents the complete resection of all visible contrast-enhancing parts of the tumor, imaging predictors of achieving this extent still need to be better understood.PurposeTo assess the impact of preoperative imaging phenotypes as defined by the VASARI feature set and tumoral volumetry to determine predictors of GTR in patients with IDH-WT glioblastoma.Material and MethodsThis retrospective, single-center study analyzed imaging characteristics based on the VASARI features in the preoperative scans of IDH-WT glioblastoma patients. Volumetric analysis was performed to determine associations with clinical outcomes. Univariate analysis was used to determine the association of VASARI features with GTR. A multivariate analysis model was used to determine predictors of GTR.ResultsGTR was achieved in 79/144 (54.8%) patients, near total resection in 15 (10.4%), and subtotal resection in 50 (34.7%) patients. Our results showed non-eloquent tumor regions (55% vs. 35%; <i>P </i>= 0.04) and thick margin of enhancement (56.1% vs. 43.9%; <i>P </i>= 0.04) were associated with GTR and ependymal extension (37% vs. 63%; <i>P </i>= 0.02). Deep white matter invasion (36.3% vs. 63.7%; <i>P </i>= 0.03) was significantly associated with non-gross total resection. Lower tumoral volumes were also associated with gross total resection (<i>P </i>< 0.01). After performing multivariate analysis, the thickness of the tumoral enhancing margins was correlated with GTR with an OR of 1.57 (95% CI=1.1-2.23). Furthermore, the volume of the enhancing component was significantly different according to EOR with a calculated OR of 0.95 (95% CI = 0.92-0.97; <i>P </i>< 0.01).ConclusionImaging characteristics on standard-of-care MRI can predict the rate of GTR in patients with IDH-WT glioblastomas. The thickness of enhancing margins predicts GTR after multivariate analysis. A diagnostic model that includes a combination of the discriminating depicted features on MRI and brain tumor volumetrics has an acceptable diagnostic performance with a specificity >90%.</p>","PeriodicalId":7143,"journal":{"name":"Acta radiologica","volume":" ","pages":"2841851251316400"},"PeriodicalIF":1.1,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143623152","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 value of contrast-enhanced ultrasound in ovarian cancer: a meta-analysis.","authors":"Jing Li, Wei-Min Kong","doi":"10.1177/02841851241297201","DOIUrl":"https://doi.org/10.1177/02841851241297201","url":null,"abstract":"<p><p>BackgroundOvarian cancer has been reported to be the eighth most common cancer among women worldwide.PurposeTo assess the diagnostic efficacy of contrast-enhanced ultrasound (CEUS) in distinguishing between benign and malignant ovarian tumors.Material and MethodsA comprehensive search of scientific literature databases, including PubMed, Cochrane Library, Web of Science, Wanfang, and CNKI, was conducted from their inception to November 2019 to identify relevant studies on the use of CEUS in the differential diagnosis of benign and malignant ovarian tumors. Sensitivity (SEN), specificity (SPE), positive and negative likelihood ratios (LR+/LR-), diagnostic odds ratios (DORs), and their corresponding 95% confidence intervals (CIs) were retrieved and analyzed using Stata 15.0.ResultsAfter rigorous screening, a total of 15 high-quality clinical studies encompassing 934 patients with ovarian cancer, comprising 969 ovarian tumors (403 malignant tumors and 566 benign tumors), were included in the analysis. Data analysis revealed significant correlations between CEUS and various diagnostic indices for ovarian tumors: the combined SEN and SPE were 0.93 (95% CI = 0.88-0.96) and 0.93 (95% CI = 0.90-0.96), respectively, and the combined LR+ and LR- were 14.07 (95% CI = 9.46-20.92) and 0.08 (95% CI = 0.05-0.13), respectively, with a combined DOR of 185.15 (95% CI = 93.31-367.41). The area under the summary receiver operating characteristic curve (AUC) was 0.98 (95% CI = 0.96-0.99). No publication bias was detected in the meta-analysis (<i>P</i> = 0.62).ConclusionCEUS demonstrates significant value in the diagnosis and differential diagnosis of benign and malignant ovarian tumors.</p>","PeriodicalId":7143,"journal":{"name":"Acta radiologica","volume":" ","pages":"2841851241297201"},"PeriodicalIF":1.1,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143603377","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":"Opportunistic screening of osteoporosis using CT urography: comparison of diagnostic performance between contrast phases.","authors":"Youngjune Kim, Sejoon Lee, Eugene Lee, Joon Woo Lee","doi":"10.1177/02841851251322928","DOIUrl":"https://doi.org/10.1177/02841851251322928","url":null,"abstract":"<p><strong>Background: </strong>Opportunistic screening of osteoporosis using computed tomography (CT) should be optimized according to CT protocols. However, to date, no study has evaluated the different contrast phases of CT urography in osteoporosis screening.</p><p><strong>Purpose: </strong>To compare the diagnostic performance of different contrast phases of CT urography in opportunistic screening of osteoporosis.</p><p><strong>Material and methods: </strong>In this single-center retrospective study, 210 consecutive patients (181 men, 29 women; mean age = 72.0 ± 9.5 years) who underwent both CT urography and dual-energy X-ray absorptiometry (DXA) within 3 months in July to December 2020 were included. The attenuation value was measured at the center of the L1 vertebral body in the axial plane of the precontrast, corticomedullary, and excretory phases. The mean and standard deviation (SD) of attenuation values were calculated. The area under the receiver operating characteristic curve (AUC) in differentiating osteoporosis versus osteopenia/normal was measured in each phase, and non-parametric comparisons between precontrast and the other phases were performed.</p><p><strong>Results: </strong>According to DXA results, 90, 90, and 30 patients were classified into the normal, osteopenia, and osteoporosis groups, respectively. The mean ± SD of attenuation values in the precontrast, corticomedullary, and excretory phases were 114.9 ± 47.8, 132.8 ± 49.3, and 126.2 ± 47.2 HU, respectively. A significant difference was observed between AUCs measured in the precontrast (0.804, 95% confidence interval [CI] = 0.717-0.890) and corticomedullary phases (0.760, 95% CI = 0.661-0.860) (<i>P </i>= 0.003) and those between the precontrast and excretory phases (0.774, 95% CI = 0.678-0.869) (<i>P </i>= 0.005).</p><p><strong>Conclusion: </strong>The precontrast phase outperformed the other phases in the opportunistic screening of osteoporosis using CT urography.</p>","PeriodicalId":7143,"journal":{"name":"Acta radiologica","volume":" ","pages":"2841851251322928"},"PeriodicalIF":1.1,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143536340","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":"The clinical value of radiomics models based on multi-parameter MRI features in evaluating the different expression status of HER2 in breast cancer.","authors":"Tingting Liu, Jialu Lin, Jiulou Zhang, Jianjuan Lou, Qigui Zou, Siqi Wang, Cong Wang, Yanni Jiang","doi":"10.1177/02841851251319110","DOIUrl":"https://doi.org/10.1177/02841851251319110","url":null,"abstract":"<p><strong>Background: </strong>Accurate preoperative non-invasive assessment of HER2 expression in breast cancer is crucial for personalized treatment and prognostic stratification.</p><p><strong>Purpose: </strong>To evaluate the effectiveness of radiomics models based on multi-parametric magnetic resonance imaging (MRI) in distinguishing HER2 expression status in invasive breast cancer.</p><p><strong>Material and methods: </strong>We conducted a retrospective analysis of baseline MRI scans and clinical data from 400 patients with breast cancer between January 2018 and December 2019. Two-dimensional regions of interest were manually segmented on the maximum tumor images obtained from turbo inversion recovery magnitude (TIRM), dynamic contrast-enhanced magnetic resonance imaging phase 2 (DCE2), dynamic contrast-enhanced magnetic resonance imaging phase 4 (DCE4), diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) sequences using ITK-SNAP software. Features were extracted and screened for dimensionality reduction. Logistic regression models were developed to predict HER2 expression status.</p><p><strong>Results: </strong>In distinguishing HER2-overexpression from non-HER2-overexpression, the DCE2 model outperformed other single-parameter models, with areas under the curve (AUCs) of 0.91 (training) and 0.88 (test). Combination models with DCE features showed significantly improved performance (<i>P</i> ≤ 0.001). The multiparameter model achieved the highest AUCs of 0.93 (training) and 0.91 (test). In distinguishing HER2-low from HER2-zero, the TIRM model performed best among single-parameter models, with AUCs of 0.80 (training) and 0.72 (test). The multiparameter model further enhanced prediction, yielding an AUC of 0.83 (test).</p><p><strong>Conclusion: </strong>Radiomics models based on multi-parametric MRI features demonstrated strong clinical utility in assessing HER2 expression status in invasive breast cancer, particularly in identifying HER2-overexpression and HER2-low expression subtypes.</p>","PeriodicalId":7143,"journal":{"name":"Acta radiologica","volume":" ","pages":"2841851251319110"},"PeriodicalIF":1.1,"publicationDate":"2025-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143536341","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":"Utilizing deep learning for automatic segmentation of the cochleae in temporal bone computed tomography.","authors":"Zhenhua Li, Langtao Zhou, Songhua Tan, Bin Liu, Yu Xiao, Anzhou Tang","doi":"10.1177/02841851241307333","DOIUrl":"10.1177/02841851241307333","url":null,"abstract":"<p><p>BackgroundSegmentation of the cochlea in temporal bone computed tomography (CT) is the basis for image-guided otologic surgery. Manual segmentation is time-consuming and laborious.PurposeTo assess the utility of deep learning analysis in automatic segmentation of the cochleae in temporal bone CT to differentiate abnormal images from normal images.Material and MethodsThree models (3D U-Net, UNETR, and SegResNet) were trained to segment the cochlea on two CT datasets (two CT types: GE 64 and GE 256). One dataset included 77 normal samples, and the other included 154 samples (77 normal and 77 abnormal). A total of 20 samples that contained normal and abnormal cochleae in three CT types (GE 64, GE 256, and SE-DS) were tested on the three models. The Dice similarity coefficient (DSC) and Hausdorff distance (HD) were used to assess the models.ResultsThe segmentation performances of the three models improved after adding abnormal cochlear images for training. SegResNet achieved the best performance. The average DSC on the test set was 0.94, and the HD was 0.16 mm; the performance was higher than those obtained by the 3D U-Net and UNETR models. The DSCs obtained using the GE 256 CT, SE-DS CT, and GE 64 CT models were 0.95, 0.94, and 0.93, respectively, and the HDs were 0.15, 0.18, and 0.12 mm, respectively.ConclusionThe SegResNet model is feasible and accurate for automated cochlear segmentation of temporal bone CT images.</p>","PeriodicalId":7143,"journal":{"name":"Acta radiologica","volume":" ","pages":"305-311"},"PeriodicalIF":1.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142998337","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":"The magnetic resonance imaging appearance of the normal anatomy and injury pattern of capsuloligamentous complex of the first metatarsophalangeal joint.","authors":"Zhan-Hua Qian, Jin-E Wang, Rong-Jie Bai, Hui-Li Zhan, Wen-Ting Li, Nai-Li Wang, Yuming Yin","doi":"10.1177/02841851241309522","DOIUrl":"10.1177/02841851241309522","url":null,"abstract":"<p><p>BackgroundThe capsuloligamentous complex injury of the first metatarsophalangeal joint (MTPJ) is a common cause of turf toe.PurposeTo investigate whether high<b>-</b>resolution 3 T magnetic resonance imaging (MRI) could demonstrate all the normal anatomic structures and the MR features of the capsuloligamentous complex injury of the first MTPJ, and to evaluate the diagnostic performance of MRI in the diagnosis of the capsuloligamentous complex injuries of the first MTPJ.Material and MethodsA total of 115 feet were included in this study, including 48 feet from 24 healthy volunteers and 67 feet from 67 patients with the capsuloligamentous complex of the first MTPJ injuries. All feet had MRI examination. The MRI features of the capsuloligamentous complex of the first MTPJ of the volunteers and patients were analyzed. Diagnostic sensitivity, specificity, and accuracy of MRI were calculated using the surgery as the standard of reference. The inter-observer agreement was assessed using kappa analysis.ResultsThe central portion of the plantar plate and ligament injury manifested as discontinuity, with an indistinct appearance with hyperintense signal within the involved structures. The sensitivities, specificities, and diagnostic accuracy value of MRI for diagnosing most structures of the capsuloligamentous complex injuries of the first MTPJ were 67%-100%, 93%-100%, and 0.82-0.99, respectively, and overall good to perfect inter-observer agreements (kappa=0.63-0.95).ConclusionHigh-resolution MRI allows adequate visualization of normal anatomic structures of the first MTPJ. The best visualized structure is sesamoid phalangeal ligament and the most frequent injury is complete tear of the medial sesamoid phalangeal ligament.</p>","PeriodicalId":7143,"journal":{"name":"Acta radiologica","volume":" ","pages":"328-340"},"PeriodicalIF":1.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143078148","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":"Comparative diagnostic performance of ⁶⁸Ga-PSMA-11 PET/CT and ⁶⁸Ga-PSMA-11 PET/MRI in detecting biochemical recurrent bone metastasis in prostate cancer: a systematic review and meta-analysis.","authors":"Xin Wen, Cheng-Yi Jiang, Xu Jiang, Yan Chen, Meng Li","doi":"10.1177/02841851241307336","DOIUrl":"10.1177/02841851241307336","url":null,"abstract":"<p><p>BackgroundThe comparative diagnostic performance of ⁶⁸Gallium (Ga)-PSMA-11 PET/CT and ⁶⁸Ga-PSMA-11 PET/MRI in detecting bone metastases in prostate cancer (PCa) remains unclear.PurposeTo systematically evaluate the early detection rate of biochemical recurrent (BCR) bone metastasis in PCa utilizing ⁶⁸Ga-PSMA-11 PET/CT and ⁶⁸Ga-PSMA-11 PET/MRI.Material and MethodsWe searched PubMed, Embase, and Web of Science for relevant articles up to April 2023 and extracted studies that examined the positivity rate of both ⁶⁸Ga-PSMA-11 PET/CT and ⁶⁸Ga-PSMA-11 PET/MRI in the context of the BCR bone metastasis of PCa patients. Random-effects model was used to compare positivity rates for two imaging modalities. Heterogeneity among studies was assessed using the <i>I</i>² statistic. To evaluate the methodological quality of studies, we employed Quality Assessment of Diagnostic Performance Studies method. The study protocol was registered in PROSPERO (CRD42023454118).ResultsA total of 1670 publications were originally identified; 58 studies, encompassing a cohort of 8037 patients, met the inclusion criteria. Regarding the evaluation of BCR bone metastasis, results suggest no statistically significant difference in the utilization of ⁶⁸Ga-PSMA-11 PET/CT versus ⁶⁸Ga-PSMA-11 PET/MRI in 58 non-head-to-head studies (0.21, 95% CI=0.19-0.24 and 0.17, 95% CI=0.11-0.23; <i>P </i>= 0.19) and four head-to-head studies (0.16, 95% CI=0.08-0.27 and 0.16, 95% CI=0.08-0.27; <i>P </i>= 1.00). Meta-regression showed the study design of influenced the heterogeneity in the PET/MRI group (<i>P</i> < 0.01); but analysis of PET/CT did not identify the potential reason for heterogeneity.ConclusionThere was no statistically significant difference in identifying BCR bone metastasis in PCa patients between ⁶⁸Ga-PSMA-11 PET/CT and ⁶⁸Ga-PSMA-11 PET/MRI.</p>","PeriodicalId":7143,"journal":{"name":"Acta radiologica","volume":" ","pages":"312-327"},"PeriodicalIF":1.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143045408","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 utility of magnetic resonance imaging in autoimmune encephalitis: prognostic implications.","authors":"Poornima Narayanan Nambiar, K Y Manisha, Jayakumari Nandana, Ramshekhar N Menon, S Vinayagamani, Bejoy Thomas, Ashalatha Radhakrishnan","doi":"10.1177/02841851241307330","DOIUrl":"https://doi.org/10.1177/02841851241307330","url":null,"abstract":"<p><p>BackgroundThe role of imaging in autoimmune encephalitis (AIE) remains unclear, and there are limited data on the utility of magnetic resonance imaging (MRI) to diagnose, treat, or prognosticate AIE.PurposeTo evaluate whether MRI is a diagnostic and prognostic marker for AIE and assess its efficacy in distinguishing between various AIE subtypes.Material and MethodsWe analyzed data from 96 AIE patients from our prospective autoimmune registry. MRI sequences examined were FLAIR, diffusion, SWI, T2WI, ASL, and contrast enhancement. Short-term outcomes were measured using the Modified Rankin Scale (mRS) at discharge; long-term outcomes were assessed with the Functional Independence Measure (FIM) at 6 months.ResultsMRI confirmed AIE in cases of new-onset seizures (82.1%, <i>P</i> < 0.001) and dementia (100%, <i>P</i> = 0.02). Antibody-negative AIE exhibited significant multifocal FLAIR abnormalities compared to antibody-positive cases (<i>P</i> = 0.002). LGI1 and CASPR2 encephalitis frequently involved the mesial temporal region (<i>P</i> = 0.004), while ASL revealed hyperperfusion of the contralateral basal ganglia in faciobrachial dystonic seizures (<i>P</i> = 0.016). GAD65 encephalitis predominantly affected the cerebellum (<i>P</i> = 0.002), and NMDA encephalitis showed contrast enhancement in five cases (<i>P</i> = 0.045). MRI was not useful for predicting short-term outcomes but was associated with long-term outcomes; specifically, a normal MRI was linked to a better long-term outcome in 47.8% of patients (<i>P</i> = 0.035), and resolution of abnormalities correlated with a favorable FIM score (>54) in 76.7% (<i>P</i> = 0.016).ConclusionMRI is valuable for early detection of seizures or dementia as initial manifestations of AIE and for differentiating AIE subtypes. Follow-up MRI is significant in predicting long-term outcomes.</p>","PeriodicalId":7143,"journal":{"name":"Acta radiologica","volume":"66 3","pages":"295-304"},"PeriodicalIF":1.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143727139","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":"Infarct core segmentation using U-Net in CT perfusion imaging: a feasibility study.","authors":"Ching-Ching Yang, Shih-Sheng Chen","doi":"10.1177/02841851241305736","DOIUrl":"10.1177/02841851241305736","url":null,"abstract":"<p><p>BackgroundThe wide variability in thresholds on computed tomography (CT) perfusion parametric maps has led to controversy in the stroke imaging community about the most accurate measurement of core infarction.PurposeTo investigate the feasibility of using U-Net to perform infarct core segmentation in CT perfusion imaging.Material and MethodsCT perfusion parametric maps were the input of U-Net, while the ground truth segmentation was determined based on diffusion-weighted imaging (DWI). The dataset used in this study was from the ISLES2018 challenge, which contains 63 acute stroke patients receiving CT perfusion imaging and DWI within 8 h of stroke onset. The segmentation accuracy of model outputs was assessed by calculating Dice similarity coefficient (DSC), sensitivity, and intersection over union (IoU).ResultsThe highest DSC was observed in U-Net taking mean transit time (MTT) or time-to-maximum (Tmax) as input. Meanwhile, the highest sensitivity and IoU were observed in U-Net taking Tmax as input. A DSC in the range of 0.2-0.4 was found in U-Net taking Tmax as input when the infarct area contains < 1000 pixels. A DSC of 0.4-0.6 was found in U-Net taking Tmax as input when the infarct area contains 1000-1999 pixels. A DSC value of 0.6-0.8 was found in U-Net taking Tmax as input when the infarct area contains ≥ 2000 pixels.ConclusionOur model achieved good performance for infarct area containing ≥ 2000 pixels, so it may assist in identifying patients who are contraindicated for intravenous thrombolysis.</p>","PeriodicalId":7143,"journal":{"name":"Acta radiologica","volume":" ","pages":"245-255"},"PeriodicalIF":1.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143021770","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}