Environmental sustainability of ultrasound-guided core-needle breast biopsy: a survey on current practices by the European Society of Breast Imaging (EUSOBI) Andrea Cozzi, Serena Carriero, Maria Adele Marino, Simone Schiaffino, Fleur Kilburn-Toppin, Matthew G. Wallis, Paola Clauser, Michael H. Fuchsjäger, Elisabetta Giannotti, and Insights into Imaging, 2026 Objectives In the context of a global appraisal of the environmental impact of radiology, this survey among members of the European Society of Breast Imaging (EUSOBI) investigated procedural aspects of ultrasound-guided core-needle breast biopsy that may impact its environmental sustainability. Materials and methods A 25-item online questionnaire, developed by a panel of nine breast imaging experts, was distributed from September 25th to December 25th, 2024, within the EUSOBI mailing list and social media platforms. The survey investigated materials routinely used for ultrasound-guided core-needle biopsies, waste disposal practices, the relationship between perceived procedural hygiene levels and self-reported frequency of post-procedural infectious complications, and results’ communication methods. Replies were analysed with descriptive and non-parametric statistics. Results Among the 787/823 respondents (95.6%) who routinely perform ultrasound-guided core-needle biopsy, most (460/787, 58.4%) perceived to attain aseptic conditions, without significant associations ( p = 0.334) of hygiene levels with post-procedural infectious complications (never seen by 549/776 respondents, 70.7%). For most disposable materials, the majority of respondents used no more than one unit per procedure, including sterile gloves (551/787, 70.0%), sterile drapes (651/787, 82.7%), and sterile gel packets (729/787, 92.6%), also avoiding to use prepackaged biopsy kits (424/787, 53.9%). However, most respondents did not use recycling bins (404/787, 51.3%) and employed at least one resource-intensive modality to communicate benign results (in-person or by letter, 584/787, 74.2%). Conclusion Procedural aspects of ultrasound-guided core-needle biopsy carrying an environmental impact vary widely. In the absence of significant associations between perceived hygiene levels and post-procedural infectious complications, resource-intensive habits could be safely streamlined to improve sustainability. Critical relevance statement This EUSOBI survey demonstrates that, despite widely varying procedural aspects in ultrasound-guided core-needle breast biopsy, higher perceived sterility levels are not associated with fewer infections, highlighting opportunities to safely reduce resource use and environmental impact. Key Points This EUSOBI survey investigated how procedural habits and the use and amount of material in ultrasound-guided core-needle breast biopsy impact its environmental sustainability. Procedural aspects varied widely among the 787/823 respondents who routinely perform ultrasound-guided core-needle breast biopsy. While some economically driven sustainable behaviours are already in place, there are several opportunities to reduce materials use and waste. As no association was found between perceived hygiene levels and post-procedural infections, resource-intensive hygiene-related practices could be streamlined to improve sustainability. Graphical Abstract
ESR Essentials: artificial intelligence in breast imaging—practice recommendations by the European Society of Breast Imaging Simone Schiaffino, Daniela Bernardi, Nuala Healy, Maria Adele Marino, Valeria Romeo, Ioannis Sechopoulos, Ritse M. Mann, Katja Pinker European Radiology, 2026 Artificial intelligence (AI) can enhance the diagnostic performance of breast cancer imaging and improve workflow optimization, potentially mitigating excessive radiologist workload and suboptimal diagnostic accuracy. AI can also boost imaging capabilities through individual risk prediction, molecular subtyping, and neoadjuvant therapy response predictions. Evidence demonstrates AI’s potential across multiple modalities. The most robust data come from mammographic screening, where AI models improve diagnostic accuracy and optimize workflow, but rigorous post-market surveillance is required before any implementation strategy in this field. Commercial tools for digital breast tomosynthesis and ultrasound, potentially able to reduce interpretation time and improve accuracy, are also available, but post-implementation evaluation studies are likewise lacking. Besides basic tools for breast MRI with limited proven clinical benefit, AI applications for other modalities are not yet commercially available. Applications in contrast-enhanced mammography are still in the research stage, especially for radiomics-based molecular subtype classification. Applications of Large Language Models (LLMs) are in their infancy, and there are currently no clinical applications. Consequently, and despite their promise, all commercially available AI tools for breast imaging should currently still be regarded as techniques that, at best, aid radiologists in image evaluation. Their use is therefore optional, and the findings may always be overruled. Key Points AI systems improve diagnostic accuracy and efficiency of mammography screening, but long-term outcomes data are lacking. Commercial tools for digital breast tomosynthesis and ultrasound are available, but post-implementation evaluation studies are lacking. AI tools for breast imaging should still be regarded as a non-obligatory aid to radiologists for image interpretation.
Neuroendocrine Tumor Metastases to the Breast Mimic Breast Primary Carcinoma: Mammography and Multimodality US Assessment in Challenging Differential Diagnosis Francesco Marcello Aricò, Antonio Portaluri, Francesca Catanzariti, Elvira Condorelli, Demetrio Aricò, Mariagiovanna Zagami, Emilia Magliolo, Sara Monforte, Maria Adele Marino Diagnostics, 2025 Metastases to the breast from non-mammary malignancies are rare, accounting for 0.1–5% of all breast malignancies. Neuroendocrine tumors (NETs) rarely metastasize to the breast. PET-CT somatostatin receptor imaging plays a pivotal role in the staging and follow-up of NETs, leveraging tracers like 68Ga-DOTATOC that bind to somatostatin receptors (SSTRs) expressed on tumor cells. While both primary and metastatic NETs express SSTRs, primary breast tumors may also exhibit an uptake of 68Ga-somatostatin analogs, making the differential diagnosis between primary breast tumors and neuroendocrine metastases challenging. Additionally, imaging characteristics of breast metastases from NETs are poorly documented in the literature, posing a diagnostic challenge that extends to pathology, particularly when in the absence of clinical suspicion. Misdiagnosis in such cases can lead to inappropriate therapeutic interventions. We report the case of a 75-year-old female patient with a history of pancreatic NET who presented to our breast clinic for further evaluation of a breast mass after a PET-CT scan revealed moderate 68Ga-DOTATOC uptake. Multimodality breast examination, including mammography and multiparametric US with B-mode, Color Doppler, Strain Elastography (SE), Shear Wave Elastography (SWE), and contrast-enhanced US (CEUS), was performed. Following a core biopsy, the lesion underwent surgical excision, revealing the diagnosis of NET metastasis. This case highlights a rare instance of neuroendocrine tumor metastasis to the breast, assessed using various ultrasound techniques, with detailed imaging and quantitative analysis. The comprehensive multimodal assessment contributes to the limited body of literature and provides elements for the differential diagnosis of a rare breast lesion that should always be considered in the presence of a known primary NET.
Assessment of pediatric breast ultrasound less is more: a practical imaging approach Elisabetta Giannotti, Rachel Sun, Nuala Healy, Fleur Kilburn-Toppin, Carmelo Sofia, Andrew HS Lee, Maria Adele Marino Acta Radiologica, 2024 Background Breast cancer in pediatric patients is rare, but ultrasound (US) is widely utilized for symptomatic cases. Purpose To determine biopsy and cancer detection rates of pediatric patients and to assess if breast US can be omitted. Material and Methods A retrospective review of a 5-year period was conducted of single-center breast US performed in patients aged <19 years. Data regarding presentation, clinical opinion (P1–5 score), and US (U1–5 score) were collected. If biopsy or surgery was performed, pathology was reviewed (B1–5 score). Results In total, 579 patients were included (19 boys, 560 girls; mean age=16.2±1.9 years; age range=0–18 years). Clinical examination was normal or benign (P1/P2) in all boys (100%) and 557/560 (99.5%) girls, and P3 in 3 (0.5%) girls. Of US, 52% demonstrated normal findings (U1) for both sexes (300/579); in the remaining cases, the most frequent findings were gynecomastia in 12/19 boys and well-defined breast masses in 208/560 girls. Of the 560 girls, 6 (1%) underwent US-guided biopsy, with final histology of fibroadenoma (B2) in all cases, while 27 (5%) had a surgical excision, with final histology of fibroadenoma (22/27, 81.5%), hamartoma (2/27, 7.4%), benign phyllodes tumor (2/27, 7.4%), and angiomyxoma skin lesion (1/27, 3.7%). No malignant lesions were diagnosed at the time of clinical referral or during the 18-month follow-up in patients with a well-defined mass on US. Conclusion Breast malignancy is extremely rare in pediatric population. US can be safely omitted if clinical examination is normal; this approach would have avoided breast US in 52% of patients in this study.
Validation of the Mirai model for predicting breast cancer risk in Mexican women Daly Avendano, Maria Adele Marino, Beatriz A. Bosques-Palomo, Yesika Dávila-Zablah, Pedro Zapata, Pablo J. Avalos-Montes, Cecilio Armengol-García, Carmelo Sofia, Margarita Garza-Montemayor, Katja Pinker, Servando Cardona-Huerta, José Tamez-Peña Insights into Imaging, 2024 Objectives To validate the performance of Mirai, a mammography-based deep learning model, in predicting breast cancer risk over a 1–5-year period in Mexican women. Methods This retrospective single-center study included mammograms in Mexican women who underwent screening mammography between January 2014 and December 2016. For women with consecutive mammograms during the study period, only the initial mammogram was included. Pathology and imaging follow-up served as the reference standard. Model performance in the entire dataset was evaluated, including the concordance index (C-Index) and area under the receiver operating characteristic curve (AUC). Mirai’s performance in terms of AUC was also evaluated between mammography systems (Hologic versus IMS). Clinical utility was evaluated by determining a cutoff point for Mirai’s continuous risk index based on identifying the top 10% of patients in the high-risk category. Results Of 3110 patients (median age 52.6 years ± 8.9), throughout the 5-year follow-up period, 3034 patients remained cancer-free, while 76 patients developed breast cancer. Mirai achieved a C-index of 0.63 (95% CI: 0.6–0.7) for the entire dataset. Mirai achieved a higher mean C-index in the Hologic subgroup (0.63 [95% CI: 0.5–0.7]) versus the IMS subgroup (0.55 [95% CI: 0.4–0.7]). With a Mirai index score > 0.029 (10% threshold) to identify high-risk individuals, the study revealed that individuals in the high-risk group had nearly three times the risk of developing breast cancer compared to those in the low-risk group. Conclusions Mirai has a moderate performance in predicting future breast cancer among Mexican women. Critical relevance statement Prospective efforts should refine and apply the Mirai model, especially to minority populations and women aged between 30 and 40 years who are currently not targeted for routine screening. Key Points The applicability of AI models to non-White, minority populations remains understudied. The Mirai model is linked to future cancer events in Mexican women. Further research is needed to enhance model performance and establish usage guidelines. Graphical Abstract
MRI Insights in Breast Imaging Alessia Angela Maria Orlando, Paola Clauser, Calogero Zarcaro, Fabiola Ferraro, Calogero Curatolo, Maria Adele Marino, Tommaso Vincenzo Bartolotta Current Medical Imaging, 2024
Magnetism of materials: theory and practice in magnetic resonance imaging Michele Gaeta, Marco Cavallaro, Sergio Lucio Vinci, Enricomaria Mormina, Alfredo Blandino, Maria Adele Marino, Francesca Granata, Agostino Tessitore, Karol Galletta, Tommaso D’Angelo, Carmela Visalli Insights into Imaging, 2021
Radiology in oncoplastic surgery Maria Adele Marino, Ricardo Pardo, Elisabetta Giannotti Revista De Senologia Y Patologia Mamaria, 2021
New diagnostic tools for breast cancer Pascal A. T. Baltzer, Panagiotis Kapetas, Maria Adele Marino, Paola Clauser Memo Magazine of European Medical Oncology, 2017
Imaging and Management of Incidental Renal Lesions Silvio Mazziotti, Giuseppe Cicero, Tommaso D’Angelo, Maria Adele Marino, Carmela Visalli, Ignazio Salamone, Giorgio Ascenti, Alfredo Blandino Biomed Research International, 2017
