Radiologia Medica最新文献

{"title":"Advancing precision in CT-guided bone biopsies: exploring the potential of dual-energy CT imaging.","authors":"Enrico Boninsegna, Enrico Piovan, Carlo Sozzi, Emilio Simonini, Giacomo Aringhieri, Dania Cioni, Emanuele Neri","doi":"10.1007/s11547-024-01935-3","DOIUrl":"10.1007/s11547-024-01935-3","url":null,"abstract":"<p><strong>Objective: </strong>This study aimed to investigate the integration of dual-energy CT (DECT) into CT-guided bone biopsy procedures, comparing it with conventional CT techniques. The focus was on technical aspects, accuracy and radiation dose exposure.</p><p><strong>Materials and methods: </strong>A total of 51 bone biopsies were conducted, with 36 using conventional CT and 15 utilizing DECT. Patient data, lesion characteristics and biopsy techniques were analyzed. Statistical analyses, including Fisher's exact test and independent samples t-test, were performed to compare accuracy and radiation doses between the two methods.</p><p><strong>Results: </strong>DECT-guided biopsies demonstrated a significantly higher accuracy (93.33%) compared to conventional CT biopsies (86.11%). The radiation dose exposure for DECT was comparable to conventional CT. DECT's ability to differentiate tissues, especially in bone marrow edema detection, led to higher precision.</p><p><strong>Conclusion: </strong>Integrating DECT into CT-guided bone biopsies enhances tissue differentiation and accuracy without significantly increasing radiation exposure. This advancement holds promise for improving musculoskeletal interventional radiology, leading to more precise diagnoses, informed treatment decisions and improved patient outcomes.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"143-149"},"PeriodicalIF":9.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142688598","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":"A multi-center, multi-organ, multi-omic prediction model for treatment-induced severe oral mucositis in nasopharyngeal carcinoma.","authors":"Alexander James Nicol, Sai-Kit Lam, Jerry Chi Fung Ching, Victor Chi Wing Tam, Xinzhi Teng, Jiang Zhang, Francis Kar Ho Lee, Kenneth C W Wong, Jing Cai, Shara Wee Yee Lee","doi":"10.1007/s11547-024-01901-z","DOIUrl":"10.1007/s11547-024-01901-z","url":null,"abstract":"<p><strong>Purpose: </strong>Oral mucositis (OM) is one of the most prevalent and crippling treatment-related toxicities experienced by nasopharyngeal carcinoma (NPC) patients receiving radiotherapy (RT), posing a tremendous adverse impact on quality of life. This multi-center study aimed to develop and externally validate a multi-omic prediction model for severe OM.</p><p><strong>Methods: </strong>Four hundred and sixty-four histologically confirmed NPC patients were retrospectively recruited from two public hospitals in Hong Kong. Model development was conducted on one institution (n = 363), and the other was reserved for external validation (n = 101). Severe OM was defined as the occurrence of CTCAE grade 3 or higher OM during RT. Two predictive models were constructed: 1) conventional clinical and DVH features and 2) a multi-omic approach including clinical, radiomic and dosiomic features.</p><p><strong>Results: </strong>The multi-omic model, consisting of chemotherapy status and radiomic and dosiomic features, outperformed the conventional model in internal and external validation, achieving AUC scores of 0.67 [95% CI: (0.61, 0.73)] and 0.65 [95% CI: (0.53, 0.77)], respectively, compared to the conventional model with 0.63 [95% CI: (0.56, 0.69)] and 0.56 [95% CI: (0.44, 0.67)], respectively. In multivariate analysis, only the multi-omic model signature was significantly correlated with severe OM in external validation (p = 0.017), demonstrating the independent predictive value of the multi-omic approach.</p><p><strong>Conclusion: </strong>A multi-omic model with combined clinical, radiomic and dosiomic features achieved superior pre-treatment prediction of severe OM. Further exploration is warranted to facilitate improved clinical decision-making and enable more effective and personalized care for the prevention and management of OM in NPC patients.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"161-178"},"PeriodicalIF":9.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11870888/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142682595","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":"Radiomics based on brain-to-tumor interface enables prediction of metastatic tumor type of brain metastasis: a proof-of-concept study.","authors":"Mingchen Jiang, Yiyao Sun, Chunna Yang, Zekun Wang, Ming Xie, Yan Wang, Dan Zhao, Yuqi Ding, Yan Zhang, Jie Liu, Huanhuan Chen, Xiran Jiang","doi":"10.1007/s11547-024-01934-4","DOIUrl":"10.1007/s11547-024-01934-4","url":null,"abstract":"<p><strong>Background: </strong>Early and accurate identification of the metastatic tumor types of brain metastasis (BM) is essential for appropriate treatment and management.</p><p><strong>Methods: </strong>A total of 450 patients were enrolled from two centers as a primary cohort who carry 764 BMs originated from non-small cell lung cancer (NSCLC, patient = 173, lesion = 187), small cell lung cancer (SCLC, patient = 84, lesion = 196), breast cancer (BC, patient = 119, lesion = 200), and gastrointestinal cancer (GIC, patient = 74, lesion = 181). A third center enrolled 28 patients who carry 67 BMs (NSCLC = 24, SCLC = 22, BC = 10, and GIC = 11) to form an external test cohort. All patients received contrast-enhanced T1-weighted (T1CE) and T2-weighted (T2W) MRI scans at 3.0 T before treatment. Radiomics features were calculated from BM and brain-to-tumor interface (BTI) region in the MRI image and screened using least absolute shrinkage and selection operator (LASSO) to construct the radiomics signature (RS). Volume of peritumor edema (VPE) was calculated and combined with RS to create a joint model. Performance of the models was assessed by receiver operating characteristic (ROC).</p><p><strong>Results: </strong>The BTI-based RS showed better performance compared to BM-based RS. The combined models integrating BTI features and VPE can improve identification performance in AUCs in the training (LC/NLC vs. SCLC/NSCLC vs. BC/GIC, 0.803 vs. 0.949 vs. 0.918), internal validation (LC/NLC vs. SCLC/NSCLC vs. BC/GIC, 0.717 vs. 0.854 vs. 0.840), and external test (LC/NLC vs. SCLC/NSCLC vs. BC/GIC, 0.744 vs. 0.839 vs. 0.800) cohorts.</p><p><strong>Conclusion: </strong>This study indicated that BTI-based radiomics features and VPE are associated with the metastatic tumor types of BM.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"190-201"},"PeriodicalIF":9.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142688600","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":"Metastasis-directed ablation of hepatocellular carcinoma with pulmonary oligometastases: a long-term multicenter study.","authors":"Qunfang Zhou, Ruixia Li, Songsong Wu, Yanyang Zhang, Wei Wang, Kangshun Zhu, Murong Wang, Zhimei Huang, Feng Duan","doi":"10.1007/s11547-024-01907-7","DOIUrl":"10.1007/s11547-024-01907-7","url":null,"abstract":"<p><strong>Purpose: </strong>Ablation is a promising approach for eliminating intrathoracic metastases. We compared the effectiveness of a combination of metastasis-directed ablation and systemic therapy with that of systemic therapy alone for patients with hepatocellular carcinoma (HCC) having pulmonary oligometastases.</p><p><strong>Materials and methods: </strong>We analyzed 679 patients with HCC and pulmonary oligometastases from seven tertiary hospitals. A total of 372 patients received systemic therapy (System group), whereas 307 patients received the combination therapy of pulmonary oligometastases ablation and systemic therapy (Ablation + System group).</p><p><strong>Results: </strong>The median progression-free survival (PFS) was 9.7 ± 0.6 and 11.5 ± 0.6 months in the System and Ablation + System groups, respectively. The Ablation + System group exhibited significantly better PFS (hazard ratio [HR], 0.71; 95% confidence interval [CI] 0.60-0.85; P < 0.001) and overall survival (OS) (HR, 0.65; 95% CI 0.52-0.81; P < 0.001) than the System group. The subgroup analysis revealed that OS (HR, 0.91; 95% CI 0.65-1.28; P = 0.590) and PFS (HR, 0.81; 95% CI 0.62-1.05; P = 0.100) did not differ between tyrosine kinase inhibitor (TKI) and TKI plus programmed cell death protein-1 (PD-1) inhibitor therapies in the Ablation + system group. In addition, PFS (HR, 0.53; 95% CI 0.38-0.74; P < 0.001) and OS (HR, 0.66; 95% CI 52-0.84; P < 0.001) showed obviously different for intrahepatic tumors with partial response (PR) status.</p><p><strong>Conclusion: </strong>The application of a combination of ablation of pulmonary oligometastases and systemic therapy resulted in longer PFS and OS than systemic therapy alone.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"25-36"},"PeriodicalIF":9.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142626992","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":"Enhancing detection of high-level axillary lymph node metastasis after neoadjuvant therapy in breast cancer patients with nodal involvement: a combined approach of axilla ultrasound and breast elastography.","authors":"Jia-Xin Huang, Feng-Tao Liu, Yu-Ting Tan, Xue-Yan Wang, Jia-Hui Huang, Shi-Yang Lin, Gui-Ling Huang, Yu-Ting Zhang, Xiao-Qing Pei","doi":"10.1007/s11547-024-01936-2","DOIUrl":"10.1007/s11547-024-01936-2","url":null,"abstract":"<p><strong>Purpose: </strong>To develop a combined approach using shear wave elastography (SWE) and conventional ultrasound (US) to determine the extent of positive axillary lymph nodes (LNs) following neoadjuvant therapy (NAT) in breast cancer patients with nodal involvement.</p><p><strong>Methods: </strong>This prospective, multicenter study was registered on the Chinese Clinical Trial Registry (ChiCTR2400085035). From October 2018 to February 2024, a total of 303 breast cancer patients with biopsy-proven positive LN were enrolled. The conventional US features of axillary LNs and SWE characteristics of breast lesions after NAT were analyzed. The diagnostic performances of axilla US, breast SWE, and their combination in detecting residual metastasis in axillary level III after NAT were assessed.</p><p><strong>Results: </strong>Pathologically positive LN(s) in axilla level III were detected in 13.75% of cases following NAT. The kappa value for the axilla level with positive LN confirmed by surgical pathology and detected by US is 0.39 (p < 0.001). The AUC of conventional axilla US to determine the status of axilla level III LNs after NAT was 0.67, with a sensitivity of 51.52%, a specificity of 74.36%. The breast SWE displayed moderate performance for detecting residual metastasis in axilla level III following NAT, with an AUC of 0.79, sensitivity of 84.85%, and specificity of 74.36%. Compared to axilla US and breast SWE alone, the combination of axilla US with breast SWE achieved a stronger discriminatory ability (AUC, 0.86 vs 0.67 vs 0.79, p < 0.05, Delong's test) and precise calibration (X² = 13.90, p = 0.085, HL test), with an improved sensitivity of 93.94% and a comparable specificity of 75.64%%.</p><p><strong>Conclusions: </strong>SWE outperformed conventional US in identifying the axilla levels with nodal metastasis following NAT in patients with initially diagnosed positive axilla. Furthermore, combining breast SWE with axilla US showed good diagnostic performance for detecting residual metastasis in axilla level III after NAT.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"121-131"},"PeriodicalIF":9.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11882731/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142676777","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":"Long-term clinical outcomes of thermal ablation for benign thyroid nodules and unresolved issues: a comprehensive systematic review.","authors":"So Yeong Jeong, Jung Hwan Baek","doi":"10.1007/s11547-024-01924-6","DOIUrl":"10.1007/s11547-024-01924-6","url":null,"abstract":"<p><p>Thermal ablation is widely accepted as an effective and safe method for treating benign thyroid nodules. Many studies reporting short-term results have consistently demonstrated the efficacy and safety of thermal ablation. However, as the clinical application of thermal ablation grows and follow-up periods extend, long-term clinical outcomes of thermal ablation have revealed several issues, including regrowth and diagnosis of malignancy in ablated lesions. In this systematic review, we analyze the long-term clinical outcomes of thyroid thermal ablation, focusing on regrowth, delayed surgery, and the potential for malignancy after thermal ablation and propose solutions to address these unresolved issues and enhance the management of benign thyroid nodules through thermal ablation.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"111-120"},"PeriodicalIF":9.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142669059","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":"Interictal EEG spikes increase perfusion in low-grade epilepsy-associated tumors: a pediatric arterial spin labeling study.","authors":"Antonio Giulio Gennari, Giulio Bicciato, Santo Pietro Lo Biundo, Raimund Kottke, Dorottya Cserpan, Ruth Tuura O'Gorman, Georgia Ramantani","doi":"10.1007/s11547-024-01923-7","DOIUrl":"10.1007/s11547-024-01923-7","url":null,"abstract":"<p><strong>Purpose: </strong>Arterial spin labeling (ASL), a noninvasive magnetic resonance (MRI) perfusion sequence, holds promise in the presurgical evaluation of pediatric lesional epilepsy patients, including those with low-grade epilepsy-associated tumors (LEATs). The interpretation of ASL-derived perfusion patterns, however, presents challenges. Our study aims to elucidate these perfusion changes in children with LEATs, exploring their correlations with clinical, electroencephalography (EEG), and anatomical MRI findings.</p><p><strong>Material and methods: </strong>Our cohort included 15 children with LEAT-associated focal lesional epilepsy who underwent single-delay pseudo-continuous ASL imaging; eight were imaged under sedation. We assessed perfusion images both qualitatively and quantitatively, focusing on LEAT-related perfusion changes, as indicated by the asymmetry index (AI) and regional cerebral blood flow (rCBF).</p><p><strong>Results: </strong>ASL revealed LEAT-related perfusion changes in all but two patients: 12 LEATs were hypoperfused and one was hyperperfused relative to the contralateral brain parenchyma (CBP). LEATs showed significantly lower perfusion compared to CBP (median: 38.7 vs. 59.1 mL/100 g/min for LEAT and CBP, respectively; p value = 0.004, Wilcoxon-Mann-Whitney), regardless of sedation. Notably, elevated AI and rCBF values correlated with interictal spikes on EEG (median: -0.008 and 0.84 vs -0.27 and 0.58, respectively), but not to other clinical, EEG, or MRI variables (p value = 0.036, Wilcoxon-Mann-Whitney).</p><p><strong>Conclusions: </strong>By highlighting the connection between LEAT and brain perfusion, and by correlating perfusion characteristics and epileptogenicity, our research enhanced our understanding of pediatric epilepsy associated with LEATs. Also, by proving the robustness of these findings to sedation we confirmed the importance of adding ASL to epilepsy protocols to as a valuable tool to supplement anatomical imaging.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"63-73"},"PeriodicalIF":9.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11882625/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142626987","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":"Prediction of tumor response to neoadjuvant chemotherapy in high-grade osteosarcoma using clustering-based analysis of magnetic resonance imaging: an exploratory study.","authors":"Giovanni Benvenuti, Simona Marzi, Antonello Vidiri, Jacopo Baldi, Serena Ceddia, Federica Riva, Renato Covello, Irene Terrenato, Vincenzo Anelli","doi":"10.1007/s11547-024-01921-9","DOIUrl":"10.1007/s11547-024-01921-9","url":null,"abstract":"<p><strong>Purpose: </strong>To evaluate the ability of magnetic resonance imaging (MRI)-based clustering analysis to predict the pathological response to neoadjuvant chemotherapy (NACT) in patients with primary high-grade osteosarcoma.</p><p><strong>Materials and methods: </strong>Twenty-two patients were included in this retrospective study. All patients underwent MRIs before and after NACT. The entire tumor volume was manually delineated on post-contrast T1-weighted images and subsegmented into three clusters using the K-means algorithm. Histogram-based parameters were calculated for each lesion. The response to NACT was obtained from the histopathological assessment of the tumor necrosis rate following resection. The Mann-Whitney test was used to compare poor and fair-to-good responders. The receiver operating characteristic curve was used to evaluate the diagnostic performance of the optimal parameters.</p><p><strong>Results: </strong>At baseline, poor responders showed a significantly larger volume of cluster1 (Vol1) than fair-to-good responders (p = 0.038). After NACT, they exhibited a lower 10th percentile (P10) and kurtosis (p = 0.038 and 0.002, respectively). Vol1 at baseline and P10 after NACT had an AUC of 77% (95% CI 56-98%). The kurtosis after NACT had the best discriminative power, with an AUC of 89.7% (95% CI 75-100%).</p><p><strong>Conclusion: </strong>The MRI-based histogram and clustering analysis provided a good ability to differentiate between poor and fair-to-good responders before and after NACT. Further investigations using larger datasets are required to corroborate our findings.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"13-24"},"PeriodicalIF":9.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142626995","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":"Improved prognostication of overall survival after radiotherapy in lung cancer patients by an interpretable machine learning model integrating lung and tumor radiomics and clinical parameters.","authors":"Tianchen Luo, Meng Yan, Meng Zhou, Andre Dekker, Ane L Appelt, Yongling Ji, Ji Zhu, Dirk de Ruysscher, Leonard Wee, Lujun Zhao, Zhen Zhang","doi":"10.1007/s11547-024-01919-3","DOIUrl":"10.1007/s11547-024-01919-3","url":null,"abstract":"<p><strong>Background: </strong>Accurate prognostication of overall survival (OS) for non-small cell lung cancer (NSCLC) patients receiving definitive radiotherapy (RT) is crucial for developing personalized treatment strategies. This study aims to construct an interpretable prognostic model that combines radiomic features extracted from normal lung and from primary tumor with clinical parameters. Our model aimed to clarify the complex, nonlinear interactions between these variables and enhance prognostic accuracy.</p><p><strong>Methods: </strong>We included 661 stage III NSCLC patients from three multi-national datasets: a training set (N = 349), test-set-1 (N = 229), and test-set-2 (N = 83), all undergoing definitive RT. A total of 104 distinct radiomic features were separately extracted from the regions of interest in the lung and the tumor. We developed four predictive models using eXtreme gradient boosting and selected the top 10 features based on the Shapley additive explanations (SHAP) values. These models were the tumor radiomic model (Model-T), lung radiomic model (Model-L), a combined radiomic model (Model-LT), and an integrated model incorporating clinical parameters (Model-LTC). Model performance was evaluated through Harrell's concordance index, Kaplan-Meier survival curves, time-dependent area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis. Interpretability was assessed using the SHAP framework.</p><p><strong>Results: </strong>Model-LTC exhibited superior performance, with notable predictive accuracy (C-index: training set, 0.87; test-set-2, 0.76) and time-dependent AUC above 0.75. Complex nonlinear relationships and interactions were evident among the model's variables.</p><p><strong>Conclusion: </strong>The integration of radiomic and clinical factors within an interpretable framework significantly improved OS prediction. The SHAP analysis provided insightful interpretability, enhancing the model's clinical applicability and potential for aiding personalized treatment decisions.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"96-109"},"PeriodicalIF":9.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142626984","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":"BPE on contrast-enhanced mammography: relationship with breast density, age and menopausal status.","authors":"Giuliana Moffa, Francesca Galati, Alessandra Spagnoli, Elena Fabrizi, Roberto Maroncelli, Sara Coppola, Veronica Rizzo, Federica Pediconi","doi":"10.1007/s11547-024-01912-w","DOIUrl":"10.1007/s11547-024-01912-w","url":null,"abstract":"<p><strong>Purpose: </strong>This retrospective study aimed to evaluate the relationship between BPE on CEM and breast density, age and menopausal status.</p><p><strong>Material and methods: </strong>Our analysis included all women eligible for CEM as a second-level examination in the diagnostic phase in a 12-month period. CEM were performed on a dedicated low-dose digital mammography unit after the injection of 1.5 ml/kg body weight Iohexol 350 mgI/ml. Both breast composition and BPE were assessed independently by two breast radiologists according to the CEM supplement to the 2013 ACR BI-RADS Mammography. A two-stage ordered probit regression model was fitted to evaluate the relationship between BPE and the other factors considered.</p><p><strong>Results: </strong>49 patients were included (median age = 55 years, 28.6% premenopausal and 71.4% postmenopausal). Breast composition was classified as ACR BI-RADS a in 4.1%, ACR BI-RADS b in 36.7%, ACR BI-RADS c in 46.9%, and ACR BI-RADS d in 12.2% of cases, by both Readers. A BPE 1 category was assigned in 53.1-55.1% of patients (by Reader 1 and 2, respectively), BPE 2 in 22.4%, BPE 3 in 18.4-12.2%, and BPE 4 in 6.1-10.2%. Higher breast density was strongly associated with higher levels of BPE, while BPE was not directly associated with age, both in fertile and postmenopausal patients. No significant differences were observed between the two Readers.</p><p><strong>Conclusion: </strong>Increased BPE is associated with a well-established breast cancer risk factor as high breast density, while it was not directly dependent on the other non-modifiable factors considered.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"74-80"},"PeriodicalIF":9.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142626965","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}