Radiologia Medica最新文献

{"title":"MRI-guided stereotactic body radiation therapy for very elderly patients with primary lung cancer: a retrospective analysis of safety and efficacy profiles.","authors":"Luca Boldrini, Angela Romano, Ilaria Castanò, Antonella Martino, Filippo Lococo, Giuseppe Cicchetti, Matteo Nardini, Giulia Panza, Lorenzo Placidi, Giuditta Chiloiro","doi":"10.1007/s11547-025-02056-1","DOIUrl":"https://doi.org/10.1007/s11547-025-02056-1","url":null,"abstract":"<p><strong>Purpose: </strong>Non-small cell lung cancer is the most common malignancy of the lung, with over 40% of the cases in patients aged 75 years or older. Many of these patients are inoperable due to comorbidities, limiting treatment options. Stereotactic body radiotherapy (SBRT) offers a curative alternative, achieving local control (LC) rates similar to surgery with manageable toxicity. This retrospective analysis aimed to investigate the efficacy and safety of MRI-guided SBRT (MRIgSBRT) for elderly lung cancer patients.</p><p><strong>Materials and methods: </strong>Data of patients aged ≥ 75 years, treated in our Institution between 2017 and 2023, were retrospectively collected. Survival curves for local recurrence-free survival (LRFS), progression-free survival and overall survival (OS) were estimated using the Kaplan-Meier method. Toxicity was assessed using the Common Terminology Criteria for Adverse Events (CTCAE version 5.0) scale.</p><p><strong>Results: </strong>The study included 38 patients with a total of 45 lung lesions, median age of 82 years (range 75-87). The median total radiotherapy dose was 62,5 Gy (range 24-75 Gy) delivered in 5 fractions (range 3-8). The median follow-up was of 16.9 months (range 0,97-66,7). The 1-, 2- and 3-year OS rates were 98% 96% and 80%, respectively, while the 1-, 2- and 3-year LRFS was 97,5%. Six patients (15.78%) and one patient (2.63%) had late G1 radiation-induced pneumonia and G2 dyspnoea, respectively.</p><p><strong>Conclusions: </strong>MRIgSBRT is a valid therapeutic option for patients aged ≥ 75 with comorbidities, frailty and risk factors limiting their performance status and eligibility for invasive treatments, offering good LC and favourable toxicity profile.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":""},"PeriodicalIF":9.7,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144691356","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":"The added value of artificial intelligence using Quantib Prostate for the detection of prostate cancer at multiparametric magnetic resonance imaging.","authors":"Tommaso Russo, Leonardo Quarta, Francesco Pellegrino, Michele Cosenza, Enrico Camisassa, Salvatore Lavalle, Giovanni Apostolo, Paolo Zaurito, Simone Scuderi, Francesco Barletta, Clara Marzorati, Armando Stabile, Francesco Montorsi, Francesco De Cobelli, Giorgio Brembilla, Giorgio Gandaglia, Alberto Briganti","doi":"10.1007/s11547-025-02017-8","DOIUrl":"10.1007/s11547-025-02017-8","url":null,"abstract":"<p><strong>Purpose: </strong>Artificial intelligence (AI) has been proposed to assist radiologists in reporting multiparametric magnetic resonance imaging (mpMRI) of the prostate. We evaluate the diagnostic performance of radiologists with different levels of experience when reporting mpMRI with the support of available AI-based software (Quantib Prostate).</p><p><strong>Material and methods: </strong>This is a single-center study (NCT06298305) involving 110 patients. Those with a positive mpMRI (PI-RADS ≥ 3) underwent targeted plus systematic biopsy (TBx plus SBx), while those with a negative mpMRI but a high clinical suspicion of prostate cancer (PCa) underwent SBx. Three readers with different levels of experience, identified as R1, R2, and R3 reviewed all mpMRI. Inter-reader agreement among the three readers with or without the assistance of Quantib Prostate as well as sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy for the detection of clinically significant PCa (csPCa) were assessed.</p><p><strong>Results: </strong>102 patients underwent prostate biopsy and the csPCa detection rate was 47%. Using Quantib Prostate resulted in an increased number of lesions identified for R3 (101 vs. 127). Inter-reader agreement slightly increased when using Quantib Prostate from 0.37 to 0.41 without vs. with Quantib Prostate, respectively. PPV, NPV and diagnostic accuracy (measured by the area under the curve [AUC]) of R3 improved (0.51 vs. 0.55, 0.65 vs.0.82 and 0.56 vs. 0.62, respectively). Conversely, no changes were observed for R1 and R2.</p><p><strong>Conclusions: </strong>Using Quantib Prostate did not enhance the detection rate of csPCa for readers with some experience in prostate imaging. However, for an inexperienced reader, this AI-based software is demonstrated to improve the performance.</p><p><strong>Trial registration: </strong>Name of registry: clinicaltrials.gov.</p><p><strong>Trial registration number: </strong>NCT06298305. Date of registration: 2022-09.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"1105-1114"},"PeriodicalIF":9.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143995747","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":"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/s11547-025-02012-z","DOIUrl":"10.1007/s11547-025-02012-z","url":null,"abstract":"<p><p>Transcatheter arterial embolization (TAE) represents an effective treatment option for acute lower gastrointestinal bleeding (LGIB). This retrospective, bicentric study evaluated the safety and efficacy of TAE in 77 patients with LGIB. The mean patient age was 68.39 ± 17.54 years, and the mean pre-procedural hemoglobin was 7.87 ± 1.89 g/dL. The most common cause of LGIB was angiodysplasia (36.2%). Pre-procedural computed tomography angiography (CTA) detected active bleeding in 83% of cases. Technical success was achieved in 98.7% of patients, and 30-day clinical success was achieved in 87%. The rebleeding rate was 13%, and the ischemic complication rate was 11.7%. There were no significant associations between clinical success and sex, age, coagulopathy, first-line management, active bleeding signs, culprit vessel, superior mesenteric artery, or time between CTA and digital subtraction angiography. TAE is a safe and effective procedure for LGIB, with high technical and acceptable clinical success rates. It should be considered a standard procedure in select patients, especially when endoscopic treatment is contraindicated or not feasible.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"1050-1057"},"PeriodicalIF":4.8,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12263760/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144008497","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":"The use of machine learning in transarterial chemoembolisation/transarterial embolisation for patients with intermediate-stage hepatocellular carcinoma: a systematic review.","authors":"Lakshya Soni, Jasen Soopramanien, Amish Acharya, Hutan Ashrafian, Stamatia Giannarou, Nicos Fotiadis, Ara Darzi","doi":"10.1007/s11547-025-02013-y","DOIUrl":"10.1007/s11547-025-02013-y","url":null,"abstract":"<p><p>Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related deaths worldwide. Intermediate-stage HCC is often treated with either transcatheter arterial chemoembolisation (TACE) or transcatheter arterial embolisation (TAE). Integrating machine learning (ML) offers the possibility of improving treatment outcomes through enhanced patient selection. This systematic review evaluates the effectiveness of ML models in improving the precision and efficacy of both TACE and TAE for intermediate-stage HCC. A comprehensive search of PubMed, EMBASE, Web of Science, and Cochrane Library databases was conducted for studies applying ML models to TACE and TAE in patients with intermediate-stage HCC. Seven studies involving 4,017 patients were included. All included studies were from China. Various ML models, including deep learning and radiomics, were used to predict treatment response, yielding a high predictive accuracy (AUC 0.90). However, study heterogeneity limited comparisons. While ML shows potential in predicting treatment outcomes, further research with standardised protocols and larger, multi-centre trials is needed for clinical integration.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"1124-1138"},"PeriodicalIF":4.8,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12263724/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144027592","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":"Enhancing hepatocellular carcinoma diagnosis in non-high-risk patients: a customized ChatGPT model integrating contrast-enhanced ultrasound.","authors":"Meng-Fei Xian, Wen-Tong Lan, Zhe Zhang, Ming-De Li, Xin-Xin Lin, Yang Huang, Hui Huang, Li-Da Chen, Qing-Hua Huang, Wei Wang","doi":"10.1007/s11547-025-01994-0","DOIUrl":"10.1007/s11547-025-01994-0","url":null,"abstract":"<p><strong>Purpose: </strong>This study aims to improve hepatocellular carcinoma (HCC) diagnostic accuracy in non-high-risk populations by utilizing GPTs that incorporate integrated risk coefficients, and to explore its feasibility.</p><p><strong>Material and methods: </strong>Between August 2016 and June 2019, patients with focal liver lesions (FLLs) in non-high-risk populations, confirmed by histopathology or clinical/imaging evidence, were retrospectively included. A logistic regression model was developed using baseline characteristics and contrast-enhanced ultrasound (CEUS) features to identify independent HCC risk factors. Three ChatGPT-based models were evaluated: ChatGPT 4o (a general-purpose model developed by OpenAI), BaseGPT (a customized model with HCC diagnostic knowledge), and RiskGPT (a further customized model integrating HCC knowledge and identified risk factors). Their intra-agreement and diagnostic performance were compared.</p><p><strong>Results: </strong>Logistic regression identified male, obesity, HBcAb or HBeAb positivity, elevated alpha-fetoprotein, and mild washout on CEUS as associated with HCC. RiskGPT achieved the highest area under a receiver operating characteristic curve (AUC) (0.89) and demonstrated superior accuracy (90.3%) in HCC identification; significantly outperforming both ChatGPT 4o (AUC 0.79, P = 0.002; accuracy 83.1%, P = 0.02) and BaseGPT (AUC 0.81, P = 0.008; accuracy 80.6%, P = 0.002). RiskGPT demonstrated superior sensitivity compared to ChatGPT 4o (85.5% vs. 66.3%) and outperformed BaseGPT in specificity (92.7% vs. 80.6%) and positive predictive value (85.5% vs. 67.7%) (all P < 0.001). Additionally, RiskGPT showed substantial intra-consistency in diagnosing FLLs, with a κ value of 0.78.</p><p><strong>Conclusion: </strong>RiskGPT improves HCC diagnostic accuracy in non-high-risk patients by integrating clinical, imaging features, and risk coefficients, demonstrating significant diagnostic potential.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"1013-1023"},"PeriodicalIF":9.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143993016","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":"In reply to the letter to editor by Paz-Manrique et al. regarding \"What the urologist needs to know before radical prostatectomy: MRI effective support to pre-surgery planning\".","authors":"Ludovica Laschena, Emanuele Messina, Rocco Simone Flammia, Antonella Borrelli, Simone Novelli, Daniela Messineo, Costantino Leonardo, Alessandro Sciarra, Valeria Panebianco","doi":"10.1007/s11547-025-02011-0","DOIUrl":"10.1007/s11547-025-02011-0","url":null,"abstract":"","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"989-990"},"PeriodicalIF":9.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144018446","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":"Diagnostic performance of a fully automated AI algorithm for lesion detection and PI-RADS classification in patients with suspected prostate cancer.","authors":"Hannes Engel, Andrea Nedelcu, Robert Grimm, Heinrich von Busch, August Sigle, Tobias Krauss, Christopher L Schlett, Jakob Weiss, Matthias Benndorf, Benedict Oerther","doi":"10.1007/s11547-025-02003-0","DOIUrl":"10.1007/s11547-025-02003-0","url":null,"abstract":"<p><strong>Purpose: </strong>To evaluate the diagnostic performance of a fully automated, commercially available AI algorithm for detecting prostate cancer and classifying lesions according to PI-RADS.</p><p><strong>Material and methods: </strong>In this retrospective single-center cohort study, we included consecutive patients with suspected prostate cancer who underwent 3T MRI between May 2017 and May 2020. Histopathological ground truth was targeted transperineal ultrasound-fusion guided biopsy and extensive systematic biopsy. We compared the results of the AI algorithm to those of human readers on both the lesion and patient level and determined the diagnostic performance.</p><p><strong>Results: </strong>A total of 272 patients with 436 target lesions were evaluated. Of these patients, 135 (49.6%) had clinically significant prostate cancer (sPCa), 35 (12.9%) had clinically insignificant prostate cancer (ISUP = 1), and 102 (37.5%) were benign. On patient level, the cancer detection rates of sPCa for AI versus human readers were 11% versus 18% for PI-RADS ≤ 2, 27% versus 11% for PI-RADS 3, 54% versus 41% for PI-RADS 4, and 74% versus 92% for PI-RADS 5. The AI showed significantly higher accuracy: 74% versus 63% for PI-RADS ≥ 4 (p < 0.01) and 70% versus 52% for PI-RADS ≥ 3 (p < 0.01). Additionally, the AI correctly classified 62 patients with human reading PI-RADS ≥ 3 as true negatives.</p><p><strong>Conclusion: </strong>The AI algorithm proved to be a reliable and robust tool for lesion detection and classification. Its cancer detection rates and PI-RADS category distribution align with the results of recent meta-analyses, indicating precise risk stratification.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"1039-1049"},"PeriodicalIF":9.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12263473/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144042492","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":"The role of gravitational effects and pre-puncture techniques in reducing pneumothorax during CT-guided lung biopsies.","authors":"Michael P Brönnimann, Maria C Barroso, Leonie Manser, Bernhard Gebauer, Timo A Auer, Federico Collettini, Patrick Dorn, Adrian T Huber, Johannes T Heverhagen, Martin H Maurer","doi":"10.1007/s11547-025-02007-w","DOIUrl":"10.1007/s11547-025-02007-w","url":null,"abstract":"<p><strong>Purpose: </strong>The study aimed to evaluate whether the relative height (RH) of the entry point (EP) during CT-guided lung biopsies, adjusted for patient positioning, can predict the risk of pneumothorax during the intervention, leveraging the gravitational effects on pleural pressure.</p><p><strong>Materials and methods: </strong>We retrospectively analyzed 128 percutaneous CT-guided lung biopsies performed at a single center between January 2018 and December 2023. Patients were grouped based on pneumothorax occurrence. Various measurement methods indirectly assessed the influence of gravitational force on pleural pressure, focusing on the RH at the EP with prone positioning adjustments (PP). Other confounding factors like patient demographics, lesion characteristics, pre-puncture fluid administration and other procedural details were assessed. Test performance metrics were compared using Chi-Square, Fisher's exact, and Mann-Whitney U tests. Univariate and binomial logistic regression assessed the influence of different parameters on pneumothorax occurrence.</p><p><strong>Results: </strong>All measurements of lower RH at EP and pre-puncture fluid administration were significantly associated with a reduced incidence of peri-interventional pneumothorax (p < 0.01). The RH at EP adjusted for the prone position demonstrated the best predictive performance (AUC = 0.844). After adjusting for various confounding factors, both lower RH at EP adjusted for the prone position (OR 110.114, p < 0.001) and pleural fluid administration (OR 0.011, p = 0.011) remained independently associated with a lower risk of pneumothorax.</p><p><strong>Conclusion: </strong>Strategic use of gravity by selecting the lowest possible entry point, ideally positioning the patient laterally, combined with pre-puncture pleural fluid administration, could be the key to reducing pneumothorax in CT-guided lung biopsies.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"1024-1038"},"PeriodicalIF":9.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12263723/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144022081","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":"Letter to the Editor regarding \"What the urologist needs to know before radical prostatectomy: MRI effective support to pre‑surgery planning\": Open Radical Prostatectomy Remains Relevant.","authors":"Nicanor Rodriguez-Gutarra, Mauricio Vassallo, Roberto Paz-Manrique","doi":"10.1007/s11547-025-02010-1","DOIUrl":"10.1007/s11547-025-02010-1","url":null,"abstract":"","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"987-988"},"PeriodicalIF":9.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143995797","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":"Simple cystic lesions of the pancreas: image quality and diagnostic accuracy of photon-counting detector computed tomography.","authors":"Stephan Rau, Thomas Stein, Alexander Rau, Caroline Wilpert, Fabian Pallasch, Balazs Bogner, Sebastian Faby, Fabian Bamberg, Jakob Weiss","doi":"10.1007/s11547-025-02015-w","DOIUrl":"10.1007/s11547-025-02015-w","url":null,"abstract":"<p><strong>Purpose: </strong>To evaluate image quality and diagnostic accuracy of photon-counting detector (PCD) CT for the detection of pancreatic cystic lesions (PCLs) compared to energy-integrating detector (EID) CT with MRI serving as reference standard.</p><p><strong>Material and methods: </strong>We included consecutive patients who underwent contrast-enhanced PCD-CT of the abdomen and for whom an additional abdominal EID-CT was available. Multiparametric MRI served as the reference standard. CT images were assessed for the presence of PCLs by three radiologists independently in a blinded reading. Image quality, lesion conspicuity, and diagnostic confidence were rated on a 5-point Likert scale (5 = excellent). The coefficient of variation (CV) and the density difference between PCLs and visually normal pancreatic parenchyma were calculated as quantitative imaging measures. Radiation dose was assessed using CTDIvol [mGy].</p><p><strong>Results: </strong>Among 106 included patients (age 62.7 ± 12.6 years; 45 [42.5%] male), 46 had MRI-confirmed cystic lesions (mean size 8.7 ± 7.4 mm; range 2-45 mm). Diagnostic accuracy for PCLs was significantly higher for PCD-CT vs. EID-CT (area under the curve: 0.81 vs. 0.74; p = 0.002; sensitivity: 76.8% vs. 59.4%). Image quality, lesion conspicuity, and diagnostic confidence were rated superior for PCD-CT vs. EID-CT (all p < 0.001). Quantitative analyses revealed a significantly lower CV (0.19 vs. 0.24; p = 0.002) and a higher density difference (94.1 HU vs. 76.6 HU p < 0.001) between PCLs and visually normal pancreatic parenchyma at lower radiation doses (7.13 vs. 8.68 mGy; p < 0.001) for PCD-CT vs. EID-CT.</p><p><strong>Conclusion: </strong>PCD-CT provided significantly higher diagnostic accuracy and superior image quality for the detection of PCLs compared to conventional EID-CT at lower radiation dose.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"1064-1073"},"PeriodicalIF":9.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12263767/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144028865","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}