Radiologia Medica最新文献

{"title":"Recent advances in PET/MR imaging for head and neck tumors: a systematic review of the last three years.","authors":"Daniele Antonio Pizzuto, Minerva Becker, Patrick Veit-Haibach, Michael Messerli, Virginia Liberini, Antonio Giulio Gennari, Winnie Wing-Chuen Lam, Alexander Maurer, Tetsuro Sekine, Maria Picchio, Munenobu Nogami, Salvatore Annunziata, Ken Herrmann, Martin Huellner","doi":"10.1007/s11547-025-02075-y","DOIUrl":"https://doi.org/10.1007/s11547-025-02075-y","url":null,"abstract":"<p><strong>Purpose: </strong>This systematic review addresses the clinical relevance of PET/MR in patients with head and neck (HN) tumors, highlighting studies conducted over the last three years to provide an updated perspective on integrating a hybrid PET/MR scan into different clinical scenarios.</p><p><strong>Methods: </strong>We employed a search algorithm, combining terms (\"PET/MR\" OR (\"PET\" AND (\"MR\" OR \"MRI\")) OR \"PET/MRI\" OR \"PET-MR\" OR \"PET-MRI\" OR (\"PET\" AND \"magnetic\")) AND (\"head\" AND \"neck\"). Studies written in English and published throughout 2021, 2022 and 2023 up to November 15th were considered if were focused on: suspected HN tumors; confirmed HN tumors before surgery/radiotherapy/chemotherapy; HN tumor recurrence or therapy response assessment. Reviews, editorials or letters, case report/series or any other original unrelated studies to the topics were excluded.</p><p><strong>Results: </strong>Twenty out of 169 studies were deemed eligible. The HN tumor cohorts included sinonasal tumors, nasopharyngeal carcinoma and tumors in the oropharynx, oral cavity, hypopharynx and larynx, mostly of squamous cell carcinoma histology. Sixteen out of 20 articles focused on initial staging, including prognostic information before primary treatment, whereas 4/20 articles explored the clinical significance of PET/MR in restaging settings or other clinical purposes.</p><p><strong>Conclusion: </strong>This review consolidates previous findings by showing the relationship between morphology, metabolism, cellularity, and perfusion in HN tumors. Metrics provided by PET/MR are able to predict the histologic grade of HN tumors, EGFR status and patient outcome. PET/MR demonstrates high diagnostic performance for detecting locoregional tumor recurrence, distant metastases and second primary cancers.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":""},"PeriodicalIF":4.8,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966400","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":"Illuminating radiogenomic signatures in pediatric-type diffuse gliomas: insights into molecular, clinical, and imaging correlations. Part I: high-grade group.","authors":"Ryo Kurokawa, Akifumi Hagiwara, Daiju Ueda, Rintaro Ito, Tsukasa Saida, Maya Honda, Kentaro Nishioka, Akihiko Sakata, Masahiro Yanagawa, Koji Takumi, Seitaro Oda, Satoru Ide, Keitaro Sofue, Shunsuke Sugawara, Tadashi Watabe, Kenji Hirata, Mariko Kawamura, Mami Iima, Shinji Naganawa","doi":"10.1007/s11547-025-02078-9","DOIUrl":"https://doi.org/10.1007/s11547-025-02078-9","url":null,"abstract":"<p><p>Recent advances in molecular genetics have revolutionized the classification of pediatric-type high-grade gliomas in the 2021 World Health Organization central nervous system tumor classification. This narrative review synthesizes current evidence on the following four tumor types: diffuse midline glioma, H3 K27-altered; diffuse hemispheric glioma, H3 G34-mutant; diffuse pediatric-type high-grade glioma, H3-wildtype and IDH-wildtype; and infant-type hemispheric glioma. We conducted a comprehensive literature search for articles published through January 2025. For each tumor type, we analyze characteristic clinical presentations, molecular alterations, conventional and advanced magnetic resonance imaging features, radiological-molecular correlations, and current therapeutic approaches. Emerging radiogenomic approaches utilizing artificial intelligence, including radiomics and deep learning, show promise in identifying imaging biomarkers that correlate with molecular features. This review highlights the importance of integrating radiological and molecular data for accurate diagnosis and treatment planning, while acknowledging limitations in current methodologies and the need for prospective validation in larger cohorts. Understanding these correlations is crucial for advancing personalized treatment strategies for these challenging tumors.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":""},"PeriodicalIF":4.8,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966385","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":"Residual myocardial hyperemia in regadenoson stress/rest quantitative perfusion cardiac magnetic resonance.","authors":"Gorka Bastarrika, Ana Ezponda, Javier Muñiz-Sáenz-Diez, Marta Vidorreta, Amaia Ochoa González, Juan José Gavira, Nahikari Salterain","doi":"10.1007/s11547-025-02062-3","DOIUrl":"https://doi.org/10.1007/s11547-025-02062-3","url":null,"abstract":"<p><strong>Purpose: </strong>This study sought to investigate the presence of residual myocardial hyperemia on the recovery phase in patients undergoing stress CMR.</p><p><strong>Material and methods: </strong>Fifty patients with clinical indication for stress CMR underwent quantitative perfusion imaging in resting conditions, after regadenoson-induced hyperemia (400 mcg, 5 mL), and 10 min after recovery with euphylline. Studies showing hypoperfusion due to ischemia and/or prior myocardial infarction were excluded. Global myocardial blood flow during rest (MBF_rest), stress (MBF_stress) and recovery (MBF_recovery) and MPR indices (MPR_stress/rest and MPR_{stress/recovery}) were calculated using automated pixel-wise quantitative myocardial perfusion mapping.</p><p><strong>Results: </strong>A total of 30 patients (22 males, mean age of 62.7 ± 1 years) were included in the analysis. Global MBF_rest and MBF_stress were 0.83 ± 0.2 mL/g/min and 2.1 ± 0.6 mL/g/min, respectively. After recovery with euphylline, myocardial perfusion did not return to the resting values (MBF_recovery of 0.92 ± 0.3 mL/g/min) and statistically differed from MBF_rest (p < 0.01), suggesting residual myocardial hyperemia. This resulted in an abnormally low MPR_{stress/recovery} (2.43 ± 0.7) with respect to MPR_stress/rest (2.56 ± 0.7) (p = 0.03). A linear mixed-effects model accounting for repeated measures revealed statistically significant group differences over time in global MBF (mean difference 0.1, 95% CI 0.02-0.17, p = 0.01) and global MPR (mean difference -0.13, 95% CI -0.25 to -0.02, p = 0.02).</p><p><strong>Conclusion: </strong>Despite the use of euphylline to counteract the vasodilator effect, MBF does not completely revert to resting values and MBF_recovery cannot be used as a substitute for MBF_rest when regadenoson is used. Consequently, a rest/stress protocol is advised for quantitative CMR perfusion to obtain accurate MBF and MPR parameters.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":""},"PeriodicalIF":4.8,"publicationDate":"2025-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966426","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":"Application of artificial intelligence in the diagnosis of scaphoid fractures: impact of automated detection of scaphoid fractures in a real-life study.","authors":"Ana Isabel Hernáiz Ferrer, Chandra Bortolotto, Luisa Carone, Emma Maria Preda, Cristina Fichera, Alice Lionetti, Giulia Gambini, Eleonora Fresi, Federico Alberto Grassi, Lorenzo Preda","doi":"10.1007/s11547-025-02028-5","DOIUrl":"https://doi.org/10.1007/s11547-025-02028-5","url":null,"abstract":"<p><strong>Purpose: </strong>We evaluated the diagnostic performance of two AI software programs (BoneView and RBfracture) in assisting non-specialist radiologists (NSRs) in detecting scaphoid fractures using conventional wrist radiographs (X-rays).</p><p><strong>Methods: </strong>We retrospectively analyzed 724 radiographs from 264 patients with wrist trauma. Patients were classified into two groups: Group 1 included cases with a definitive diagnosis by a specialist radiologist (SR) based on X-rays (either scaphoid fracture or not), while Group 2 comprised indeterminate cases for the SRs requiring a CT scan for a final diagnosis. Indeterminate cases were defined as negative or doubtful X-rays in patients with persistent clinical symptoms. The X-rays were evaluated by AI and two NSRs, independently and in combination. We compared their diagnostic performances using sensitivity, specificity, area under the curve (AUC), and Cohen's kappa for diagnostic agreement.</p><p><strong>Results: </strong>Group 1 included 174 patients, with 80 cases (45.97%) of scaphoid fractures. Group 2 had 90 patients, of which 44 with uncertain diagnoses and 46 negative cases with persistent symptoms. Scaphoid fractures were identified in 51 patients (56.67%) in Group 2 after further CT imaging. In Group 1, AI performed similarly to NSRs (AUC: BoneView 0.83, RBfracture 0.84, NSR1 0.88, NSR2 0.90), without significant contribution of AI to the performance of NSRs. In Group 2, performances were lower (AUC: BoneView 0.62, RBfracture 0.65, NSR1 0.46, NSR2 0.63), but AI assistance significantly improved NSR performance (NSR2 + BoneView AUC = 0.75, p = 0.003; NSR2 + RBfracture AUC = 0.72, p = 0.030). Diagnostic agreement between NSR1 with AI support and SR was moderate (kappa = 0.576), and substantial for NSR2 (kappa = 0.712).</p><p><strong>Conclusions: </strong>AI tools may effectively assist NSRs, especially in complex scaphoid fracture cases.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":""},"PeriodicalIF":4.8,"publicationDate":"2025-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966693","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":"Unlocking the potential of radiomics in identifying fibrosing and inflammatory patterns in interstitial lung disease.","authors":"Leonardo Colligiani, Chiara Marzi, Vincenzo Uggenti, Sara Colantonio, Laura Tavanti, Francesco Pistelli, Greta Alì, Emanuele Neri, Chiara Romei","doi":"10.1007/s11547-025-02067-y","DOIUrl":"https://doi.org/10.1007/s11547-025-02067-y","url":null,"abstract":"<p><strong>Purpose: </strong>To differentiate interstitial lung diseases (ILDs) with fibrotic and inflammatory patterns using high-resolution computed tomography (HRCT) and a radiomics-based artificial intelligence (AI) pipeline.</p><p><strong>Materials and methods: </strong>This single-center study included 84 patients: 50 with idiopathic pulmonary fibrosis (IPF)-representative of fibrotic pattern-and 34 with cellular non-specific interstitial pneumonia (NSIP) secondary to connective tissue disease (CTD)-as an example of mostly inflammatory pattern. For a secondary objective, we analyzed 50 additional patients with COVID-19 pneumonia. We performed semi-automatic segmentation of ILD regions using a deep learning model followed by manual review. From each segmented region, 103 radiomic features were extracted. Classification was performed using an XGBoost model with 1000 bootstrap repetitions and SHapley Additive exPlanations (SHAP) were applied to identify the most predictive features.</p><p><strong>Results: </strong>The model accurately distinguished a fibrotic ILD pattern from an inflammatory ILD one, achieving an average test set accuracy of 0.91 and AUROC of 0.98. The classification was driven by radiomic features capturing differences in lung morphology, intensity distribution, and textural heterogeneity between the two disease patterns. In differentiating cellular NSIP from COVID-19, the model achieved an average accuracy of 0.89. Inflammatory ILDs exhibited more uniform imaging patterns compared to the greater variability typically observed in viral pneumonia.</p><p><strong>Conclusion: </strong>Radiomics combined with explainable AI offers promising diagnostic support in distinguishing fibrotic from inflammatory ILD patterns and differentiating inflammatory ILDs from viral pneumonias. This approach could enhance diagnostic precision and provide quantitative support for personalized ILD management.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":""},"PeriodicalIF":4.8,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966380","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":"Chest CT imaging for differentiating normal, PRISm, and COPD in comparison with pulmonary function tests.","authors":"Zongjing Ma, Yingli Sun, Zhuangxuan Ma, Ling Zhang, Fanzhi Cheng, Haihong Ma, Liang Jin, Ming Li","doi":"10.1007/s11547-025-02061-4","DOIUrl":"https://doi.org/10.1007/s11547-025-02061-4","url":null,"abstract":"<p><strong>Background: </strong>Preserved ratio impaired spirometry (PRISm) and chronic obstructive pulmonary disease (COPD) are progressive respiratory disorders associated with accelerated pulmonary function decline and systemic comorbidities. This multicenter study aimed to develop a three-category classification model that integrates clinical variables with thoracic computed tomography (CT) radiomics to distinguish normal pulmonary function, PRISm, and COPD.</p><p><strong>Methods: </strong>A total of 1018 participants from three centers (A, B, C) who underwent chest CT and pulmonary function tests (PFTs) within a 2-week interval were retrospectively analyzed. After applying inclusion and exclusion criteria, 797 individuals were included for analysis (Center A: 667 [training/internal test = 534:133]; Centers B, C: 130 external test). CT images were preprocessed via resampling and intensity normalization, followed by semi-automated segmentation of the airway tree and whole lung parenchyma using Mimics Research. PyRadiomics extracted 2436 radiomic features (1218 per region). Feature selection combined maximum relevance minimum redundancy with least absolute shrinkage and selection operator regression, employing tenfold cross-validation. Five models were developed using multinomial logistic regression: (1) clinical model, (2) airway model, (3) lung model, (4) airway fusion model, and (5) lung fusion model. Performance metrics included accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and the area under the receiver operating characteristic curve (AUC), with DeLong tests comparing model efficacy.</p><p><strong>Results: </strong>35 airway tree and 48 lung radiomic features were ultimately selected. The best performing model was the lung fusion model, which integrated three clinical predictors (age, gender, and BMI) with selected lung radiomic features. In external test set, it achieved superior performance with AUCs of 0.939 (95% CI 0.898-0.979) for PFT-normal, 0.830 (0.758-0.902) for PRISm, and 0.904 (0.841-0.966) for COPD, with an overall accuracy of 83.59%. DeLong tests indicated that across all three datasets, the lung fusion model outperformed the other four models.</p><p><strong>Conclusion: </strong>Combining age, gender, BMI, and lung radiomic features significantly improves detection of PRISm and COPD compared to alternative models. These findings underscore the potential of CT-based radiomics for the early identification and risk stratification of abnormal pulmonary function.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":""},"PeriodicalIF":4.8,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966659","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":"Simultaneous generation of color-coded arteriography, venography, and dynamic angiography: methodology and clinical applications in stroke.","authors":"Heekyung Kim, Hong Gee Roh, Jin Tae Kwak, Hee Jong Ki, In Seong Kim, Sumin Jung, Hyun Yang, Jeong Jin Park, Yoo Sung Jeon, Hyun Jeong Kim","doi":"10.1007/s11547-025-02074-z","DOIUrl":"https://doi.org/10.1007/s11547-025-02074-z","url":null,"abstract":"<p><p>Cerebrovascular accident is a leading cause of death and disability. Early detection of cerebrovascular diseases is crucial for timely treatment. This study introduces a novel method for the simultaneous generation of color-coded arteriography, venography, and dynamic angiography derived from dynamic contrast-enhanced magnetic resonance angiography and computed tomography perfusion. By realigning source images into time series volume data, this approach enables the classification of five dynamic phases, allowing for the creation of detailed angiographic images and facilitating a comprehensive evaluation of cerebrovascular accidents in the emergency room. The method enables rapid assessment of ischemic strokes, improving patient selection for recanalization therapy, and aids in the early diagnosis of other cerebrovascular diseases, including cerebral venous thrombosis and arteriovenous shunts. We demonstrate the clinical applications of this technique, highlighting its potential to enhance the accuracy and speed of cerebrovascular imaging, making it a valuable first-line diagnostic tool for stroke patients.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":""},"PeriodicalIF":4.8,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966356","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":"Predicting tumor recurrence site after reirradiation in head and neck cancer: a retrospective external validation of a published [18F]-FDG PET radiomic signature.","authors":"Arnaud Beddok, Kira Grogg, Christophe Nioche, Laura Rozenblum, Fanny Orlhac, Valentin Calugaru, Gilles Crehange, Helen A Shih, Thibault Marin, Irène Buvat, Georges El Fakhri","doi":"10.1007/s11547-025-02072-1","DOIUrl":"https://doi.org/10.1007/s11547-025-02072-1","url":null,"abstract":"<p><strong>Purpose: </strong>This study evaluates the efficacy of a previously published [18F]-FDG PET radiomic signature in predicting locoregional failure locations post-reirradiation in head and neck cancer (HNC) patients, using an independent cohort from a different institution.</p><p><strong>Materials and methods: </strong>Among the 66 patients reirradiated for recurrent HNC at Massachusetts General Hospital between 2012 and 2022, 31 underwent pre-reirradiation PET, constituting the external cohort for this analysis. These patients were characterized using the same radiomic features as the original model (Intensity_histogram_min, Kurtosis, Correlation, and Contrast), projected as a supplementary individual onto the published first principal component, and assigned to one of two groups using the published cutoff. The cutoff was then optimized for the external cohort to determine the loss of performance due to technical or population shifts.</p><p><strong>Results: </strong>Among the 31 patients, 22 experienced a second locoregional failure, distributed between 12 \"in-field\" and 10 \"outside\" recurrences. With the original cutoff, the model achieved a BA of 70% and a positive predictive value (PPV) of 86% for detecting \"in-field\" recurrences. After recalibrating the cutoff, the model achieved a BA of 78% and a PPV of 89%, close to the 84.5% BA obtained in the original article.</p><p><strong>Conclusion: </strong>The study validates the ability of the previously established PET radiomic signature to predict \"in-field\" relapses following reRT with a high PPV. These results support the potential of PET radiomics in identifying patients who may benefit from \"in-field\" dose escalation in reRT schemes. The model is freely available through the user-friendly LIFEx software.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":""},"PeriodicalIF":4.8,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966392","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 adaptation of the European guidelines for breast cancer diagnosis, staging, and preoperative planning: a GRADE-ADOLOPMENT approach.","authors":"Paola Mantellini, Andrea Guida, Erika Del Prete, Francesca Battisti, Flori Degrassi, Adriana Bonifacino, Beniamino Brancato, Cristian Scatena, Livia Giordano, Leopoldo Costarelli, Alfredo Santinelli, Catia Angiolini, Francesca Pietribiasi, Marco Zappa, Prassede Foxi, Matteo Capobussi, Francesco Sardanelli, Paolo Giorgi Rossi, Lauro Bucchi, Silvia Deandrea","doi":"10.1007/s11547-025-02065-0","DOIUrl":"https://doi.org/10.1007/s11547-025-02065-0","url":null,"abstract":"<p><p>An Italian guideline panel issued the national recommendations for breast cancer diagnosis, staging, and preoperative planning. The panel employed the ADOLOPMENT process to adopt or adapt the guidelines developed by the European Commission Initiative on Breast Cancer (ECIBC). This process utilises the Grading of Recommendations Assessment, Development and Evaluation evidence-to-decision framework. Hereby, we present 15 prioritised recommendations from the second chapter of the Italian guidelines. All of the recommendations as originally developed by the ECIBC were adopted. For the assessment of women with positive screening result, the diagnostic recommendations suggest using digital breast tomosynthesis instead of additional mammographic projections. Recommendations include using needle core biopsy (NCB) instead of fine-needle aspiration for suspicious lesions, and stereotactic-guided -rather than ultrasound-guided- NCB for suspicious calcifications. For preoperative planning, they recommend clip marking after biopsy and not using additional magnetic resonance imaging (MRI) for confirmed ductal carcinoma in situ. Contrast-enhanced mammography is preferred over MRI for presurgical planning, when needed. Other imaging tests are not recommended for stage I, IIa, and IIb BC without signs of metastasis, while positron emission tomography-computed tomography alone is suggested for stage III BC. Adjuvant hormone therapy is recommended when 1% or more tumour cells show oestrogen or progesterone receptor positivity, which replaces the 10% threshold. Adopting shared and trustworthy guidelines for BC screening across Europe will help standardise the process across settings and advance healthcare quality and equity.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":""},"PeriodicalIF":4.8,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144874838","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":"Development and validation of deep learning model for detection of obstructive coronary artery disease in patients with acute chest pain: a multi-center study.","authors":"Jin Young Kim, Jiyong Park, Kye Ho Lee, Ji Won Lee, Jinho Park, Pan Ki Kim, Kyunghwa Han, Song-Ee Baek, Dong Jin Im, Byoung Wook Choi, Jin Hur","doi":"10.1007/s11547-025-02064-1","DOIUrl":"10.1007/s11547-025-02064-1","url":null,"abstract":"<p><strong>Purpose: </strong>This study aimed to develop and validate a deep learning (DL) model to detect obstructive coronary artery disease (CAD, ≥ 50% stenosis) in coronary CT angiography (CCTA) among patients presenting to the emergency department (ED) with acute chest pain.</p><p><strong>Materials and methods: </strong>The training dataset included 378 patients with acute chest pain who underwent CCTA (10,060 curved multiplanar reconstruction [MPR] images) from a single-center ED between January 2015 and December 2022. The external validation dataset included 298 patients from 3 ED centers between January 2021 and December 2022. A DL model based on You Only Look Once v4, requires manual preprocessing for curved MPR extraction and was developed using 15 manually preprocessed MPR images per major coronary artery. Model performance was evaluated per artery and per patient.</p><p><strong>Results: </strong>The training dataset included 378 patients (mean age 61.3 ± 12.2 years, 58.2% men); the external dataset included 298 patients (mean age 58.3 ± 13.8 years, 54.6% men). Obstructive CAD prevalence in the external dataset was 27.5% (82/298). The DL model achieved per-artery sensitivity, specificity, positive predictive value, negative predictive value (NPV), and area under the curve (AUC) of 92.7%, 89.9%, 62.6%, 98.5%, and 0.919, respectively; and per-patient values of 93.3%, 80.7%, 67.7%, 96.6%, and 0.871, respectively.</p><p><strong>Conclusions: </strong>The DL model demonstrated high sensitivity and NPV for identifying obstructive CAD in patients with acute chest pain undergoing CCTA, indicating its potential utility in aiding ED physicians in CAD detection.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":""},"PeriodicalIF":4.8,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144856202","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}