Publications by authors named "Silvia Penco"

Article Synopsis
  • - The study assesses how well MRI can diagnose breast implant ruptures and the effect of radiologist experience on accuracy.
  • - It involved 118 patients who had implant surgeries, finding that expert radiologists detected ruptures with much greater accuracy compared to less experienced ones.
  • - The results highlight the need for specialized training in radiology to enhance diagnostic precision, prompting a recommendation for updated radiological guidelines.
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Objectives: This meta-analysis compares the efficacy, limitations, and clinical implications of abbreviated breast MRI (AB-MRI) and full protocol MRI (FP-MRI), focusing on diagnostic accuracy across diverse populations. It extends previous analyses by including studies conducted after 2019 in both screening and diagnostic contexts.

Methods: We conducted a systematic review (November 2019 to December 2022), using a bivariate model to calculate summary estimates of sensitivity and specificity.

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Access to medical imaging is pivotal in healthcare, playing a crucial role in the prevention, diagnosis, and management of diseases. However, disparities persist in this scenario, disproportionately affecting marginalized communities, racial and ethnic minorities, and individuals facing linguistic or cultural barriers. This paper critically assesses methods to mitigate these disparities, with a focus on breast cancer screening.

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: Breast cancer (BC) is a leading cause of morbidity and mortality worldwide, and accurate assessment of axillary lymph nodes (ALNs) is crucial for patient management and outcomes. We aim to summarize the current state of ALN assessment techniques in BC and provide insights into future directions. : This review discusses various imaging techniques used for ALN evaluation, including ultrasound, computed tomography, magnetic resonance imaging, and positron emission tomography.

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Objective: Breast magnetic resonance imaging (MRI) and contrast-enhanced mammography (CEM) are nowadays used in breast imaging but studies about their inter-reader agreement are lacking. Therefore, we compared the inter-reader agreement of CEM and MRI in breast cancer diagnosis in the same patients.

Methods: Breast MRI and CEM exams performed in a single center (09/2020-09/2021) for an IRB-approved study were retrospectively and independently evaluated by four radiologists of two different centers with different levels of experience who were blinded to the clinical and other imaging data.

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Article Synopsis
  • Researchers are looking into giving radiotherapy (RT) before surgery for breast cancer (BC), which could help more patients get better treatment.
  • * This new approach uses advanced technology to focus the treatment more accurately, reducing side effects and improving results.
  • * The study aims to gather important data that can help design better future treatments and make RT more personalized for patients with early-stage BC.
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Purpose: This study aimed to investigate the use of contrast-free magnetic resonance imaging (MRI) as an innovative screening method for detecting breast cancer in high-risk asymptomatic women. Specifically, the researchers evaluated the diagnostic performance of diffusion-weighted imaging (DWI) in this population.

Methods: MR images from asymptomatic women, carriers of a germline mutation in either the BRCA1 or BRCA2 gene, collected in a single center from January 2019 to December 2021 were retrospectively evaluated.

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Article Synopsis
  • Recent technology in artificial intelligence is helping doctors better understand and treat breast cancer, like figuring out if a tumor is aggressive and predicting how well a patient will respond to treatment.
  • Radiomics is a new way of analyzing medical images with advanced math to give doctors more useful information.
  • The article talks about how AI has developed in breast imaging, what the process looks like, the benefits it can bring, and also the challenges doctors face when trying to use it in everyday practice.
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The aim of this study was to evaluate the diagnostic performance of contrast-enhanced spectral mammography (CESM) in predicting breast lesion malignancy due to microcalcifications compared to lesions that present with other radiological findings. Three hundred and twenty-one patients with 377 breast lesions that underwent CESM and histological assessment were included. All the lesions were scored using a 4-point qualitative scale according to the degree of contrast enhancement at the CESM examination.

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A digital twin is a virtual model developed to accurately reflect a physical thing or a system. In radiology, a digital twin of a radiological device enables developers to test its characteristics, make alterations to the design or materials, and test the success or failure of the modifications in a virtual environment. Innovative technologies, such as AI and -omics sciences, may build virtual models for patients that are continuously adjustable based on live-tracked health/lifestyle parameters.

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Objective: Although breast cancer screening can benefit from Artificial Intelligence (AI), it is still unknown whether, to which extent or under which conditions, the use of AI is going to be accepted by the general population. The aim of our study is to evaluate what the females who are eligible for breast cancer screening know about AI and how they perceive such innovation.

Methods: We used a prospective survey consisting of a 11-multiple-choice questionnaire evaluating statistical associations with Chi-Square-test or Fisher-exact-test.

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We performed a systematic review and a meta-analysis of studies using MRI-radiomics for predicting the pathological complete response in breast cancer patients undergoing neoadjuvant therapy , and we evaluated their methodological quality using the radiomics-quality-score (RQS). Random effects meta-analysis was performed pooling area under the receiver operating characteristics curves. Publication-bias was assessed using the Egger's test and visually inspecting the funnel plot.

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Background: Breast-conserving surgery (BCS) and whole breast radiation therapy (WBRT) are the standard of care for early-stage breast cancer (BC). Based on the observation that most local recurrences occurred near the tumor bed, accelerated partial breast irradiation (APBI), consisting of a higher dose per fraction to the tumor bed over a reduced treatment time, has been gaining ground as an attractive alternative in selected patients with low-risk BC. Although more widely delivered in postoperative setting, preoperative APBI has also been investigated in a limited, though increasing, and number of studies.

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Article Synopsis
  • The study aimed to create a tool to predict if low-grade breast cancer (DCIS) would turn into a more serious form (invasive carcinoma) after surgery.
  • Researchers looked at data from 3100 breast biopsies and focused on 295 cases of low-grade DCIS.
  • They found that factors like age and the size of any remaining lesions after the biopsy could help predict the risk of cancer worsening, and they developed a simple chart to assist doctors in assessing this risk.
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Ductal carcinoma in situ (DCIS) is a non-obligate precursor of invasive breast cancer. It accounts for 25% of all breast cancers diagnosed, as a result of the expansion of breast cancer screening and is associated with a high survival rate. DCIS is particularly clinically challenging, due to its heterogeneous pathological and biological traits and its management is continually evolving towards more personalized and less aggressive therapies.

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Objectives: We aimed to determine whether radiomic features extracted from a highly homogeneous database of breast MRI could non-invasively predict pathological complete responses (pCR) to neoadjuvant chemotherapy (NACT) in patients with breast cancer.

Methods: One hundred patients with breast cancer receiving NACT in a single center (01/2017-06/2019) and undergoing breast MRI were retrospectively evaluated. For each patient, radiomic features were extracted within the biopsy-proven tumor on T1-weighted (T1-w) contrast-enhanced MRI performed before NACT.

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Radiomics is an emerging translational field of medicine based on the extraction of high-dimensional data from radiological images, with the purpose to reach reliable models to be applied into clinical practice for the purposes of diagnosis, prognosis and evaluation of disease response to treatment. We aim to provide the basic information on radiomics to radiologists and clinicians who are focused on breast cancer care, encouraging cooperation with scientists to mine data for a better application in clinical practice. We investigate the workflow and clinical application of radiomics in breast cancer care, as well as the outlook and challenges based on recent studies.

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Purpose: In order to evaluate the use of un-enhanced magnetic resonance imaging (MRI) for detecting breast cancer, we evaluated the accuracy and the agreement of diffusion-weighted imaging (DWI) through the inter-reader reproducibility between expert and non-expert readers.

Material And Methods: Consecutive breast MRI performed in a single centre were retrospectively evaluated by four radiologists with different levels of experience. The per-breast standard of reference was the histological diagnosis from needle biopsy or surgical excision, or at least one-year negative follow-up on imaging.

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Italy has one of the highest COVID-19 clinical burdens in the world and Lombardy region accounts for more than half of the deaths of the country. Since COVID-19 is a novel disease, early impactful decisions are often based on experience of referral centres.We report the re-organisation which our institute (IEO, European Institute of Oncology), a cancer referral centre in Lombardy, went through to make our breast-imaging division pandemic-proof.

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Breast cancer diagnosis and staging is based on mammography, ultrasound, and magnetic resonance imaging (MRI). Contrast enhanced spectral mammography (CESM) has gained momentum as an innovative and clinically useful method for breast assessment. CESM is based on abnormal enhancement of neoplastic tissue compared to surrounding breast tissue.

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MRI-guided vacuum-assisted breast biopsy (VABB) is used for suspicious breast cancer (BC) lesions which are detectable only with MRI: because the high sensitivity but limited specificity of breast MRI it is a fundamental tool in breast imaging divisions. We analyse our experience of MRI-guided VABB and critically discuss the potentialities of diffusion-weighted imaging (DWI) and artificial intelligence (AI) in this matter. We retrospectively analysed a population of consecutive women underwent VABB at our tertiary referral BC centre from 01/2011 to 01/2019.

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The diagnosis of breast cancer currently relies on radiological and clinical evaluation, confirmed by histopathological examination. However, such approach has some limitations as the suboptimal sensitivity, the long turnaround time for recall tests, the invasiveness of the procedure and the risk that some features of target lesions may remain undetected, making re-biopsy a necessity. Recent technological advances in the field of artificial intelligence hold promise in addressing such medical challenges not only in cancer diagnosis, but also in treatment assessment, and monitoring of disease progression.

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Purpose: To estimate the performance of diffusion-weighted imaging (DWI) for breast cancer detection.

Methods: Consecutive breast magnetic resonance imaging examinations performed from January to September 2016 were retrospectively evaluated. Examinations performed before/after neoadjuvant therapy, lacking DWI sequences or reference standard were excluded; breasts after mastectomy were also excluded.

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Introduction: Atypical ductal hyperplasia (ADH) is a high-risk benign lesion found in approximately 1-10% of breast biopsies and associated with a variable incidence of carcinoma after surgical excision. The main goal of our study is to present our experience in the management and long-term follow-up of 71 patients with ADH diagnosed on breast biopsy.

Materials And Methods: Results of 3808 breast biopsy specimens from 1 January 2000 to 31 December 2005 were analyzed to identify all biopsies which resulted in a diagnosis of ADH.

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Objectives: To evaluate the underestimation rate and clinical relevance of lobular neoplasia in vacuum-assisted breast biopsy (VABB).

Methods: A total of 161 cases of LN were retrieved from 6,435 VABB. The histological diagnosis was ALH (atypical lobular hyperplasia) in 80 patients, LCIS (lobular carcinoma in situ) in 69 patients and PLCIS (pleomorphic lobular carcinoma in situ) in 12 patients.

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