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Immune checkpoint inhibitors (ICIs) improve outcomes in advanced melanoma, but many patients are refractory or experience relapse. The gut microbiota modulates antitumor responses. However, inconsistent baseline predictors point to heterogeneity in responses and inadequacy of cross-sectional data. We followed patients with unresectable melanoma from baseline and during anti-PD-1 therapy, collecting fecal and blood samples that were surveyed for changes in the gut microbiota and immune markers. Varying patient responses were linked to different gut microbiota dynamics during ICI treatment. We select complete responders by their stable microbiota functions and validate them using multiple external cohorts and experimentally. We identify major histocompatibility complex class I (MHC class I)-restricted peptides derived from flagellin-related genes of Lachnospiraceae (FLach) as structural homologs of tumor-associated antigens, detect FLach-reactive CD8 + T cells in complete responders before ICI therapy, and demonstrate that FLach peptides improve antitumor immunity. These findings highlight the prognostic value of microbial functions and therapeutic potential of tumor-mimicking microbial peptides., Competing Interests: Declaration of interests L.N., T.M., P.A.A., and A.D.G.M. are named co-inventors on a patent application relating to this work (EP n. 24164184.4 “Flagellin-related peptides and uses”). M.C.A. reports advisory board participation, honoraria, or research funds to institutions from MSD Australia, BMS Australia, and Pierre Fabre Australia and is a named co-inventor on a patent application relating to Methods and compositions for treating cancer (WO2020106983A1), all unrelated to this work. P.A.A. reports grants or contracts from Bristol Myers Squibb, Roche-Genentech, Pfizer, and Sanofi; consulting fees from Bristol Myers Squibb, Roche-Genentech, Merck Sharp & Dohme, Novartis, Merck Serono, Pierre Fabre, Sun Pharma, Sanofi, Sandoz, Italfarmaco, Nektar, Pfizer, Lunaphore, Medicenna, Bio-Al Health, ValoTx, Replimmune, and Bayer; support for attending meetings and/or travel from Pfizer, Bio-Al Health, and Replimmune; and participating on a data safety monitoring board or advisory board for Bristol Myers Squibb, Roche-Genentech, Merck Sharp & Dohme, Novartis, AstraZeneca, Boehringer Ingelheim, Eisai, Regeneron, Daiichi Sankyo, Oncosec, Nouscom, Seagen, iTeos, and Erasca. L.N. reports research funds from BMS Europe unrelated to this work., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Objective: This study evaluates the diagnostic criteria of MRI for breast implant rupture and examines the influence of radiologist experience on the accuracy of rupture detection., Methods: A retrospective study was conducted in a single center, involving patients who underwent implant replacement surgery between March 2019 and October 2022. MRI evaluations by four radiologists of varying experience levels were compared with surgical outcomes., Results: The study included 118 explanted prostheses, with 25 identified as ruptured. Expert radiologists demonstrated near-perfect agreement (κ = 0.94) in identifying rupture signs, with high PPV and NPV, whereas non-experts showed only moderate agreement (κ = 0.44). Indicators such as the linguine sign, subcapsular line, and keyhole sign were identified with high accuracy by experts, contrasting with non-experts' lower detection rates., Conclusions: Expertise in radiology significantly impacts the accurate diagnosis of breast implant ruptures. This study supports updating radiological guidelines and underscores the importance of specialized training and experience in improving diagnostic outcomes in breast implant assessments., (© 2024. Italian Society of Medical Radiology.)

Background: Breast implants are not lifelong, with implant rupture being the third leading cause of revisional surgery in augmented women. Noncontrast MRI is a reliable tool to assess implant integrity; however, false positive and false negative diagnoses have been reported due to an incorrect interpretation of MRI signs. This study aims to investigate the incidence of these misleading results, comparing MRI findings with intraoperative surgical observations and exploring signs of nonunivocal interpretation., Materials and Methods: Between March 2019 and October 2022, our hospital, a referral center for breast cancer care, conducted 139 breast MRI examinations to evaluate implant integrity. Surgical intervention was deemed necessary for patients diagnosed with suspected or confirmed implant rupture at MRI. Those patients who did not undergo any surgical procedure (63 cases) or had surgery at different institutes (11 cases) were excluded., Results: Among the 65 patients who underwent preoperative MRI and subsequent surgery at our institute, surgical findings confirmed the preoperative MRI diagnosis in 48 women. Notably, 17 women exhibited a discordance between MRI and surgical findings: three false negatives, 11 false positives and three possible ruptures not confirmed. Signs of nonunivocal or misleading interpretation were assessed on a patient-by-patient basis. The importance of obtaining detailed information about a patient's breast implant, including fill materials, number of lumens, manufacturer and shape, proved immensely beneficial for interpreting MRI signs accurately., Conclusion: Pre-MRI knowledge of implant details and a meticulous evaluation of non-univocal signs can aid radiologists in accurately assessing implant integrity, reducing the risk of unnecessary revisional surgeries, and potentially averting allegations of medical malpractice., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Breast cancer (BC) is the most common malignancy in women and the second cause of cancer death. In recent years, there has been a strong development in artificial intelligence (AI) applications in medical imaging for several tasks. Our aim was to evaluate the potential of transfer learning with convolutional neural networks (CNNs) in discriminating suspicious breast lesions on ultrasound images., Methods: Transfer learning performances of five different CNNs (Inception V3, Xception, Densenet121, VGG 16, and ResNet50) were evaluated on a public and on an institutional dataset (526 and 392 images, respectively), customizing the top layers for the specific task. Institutional images were contoured by an expert radiologist and processed to feed the CNNs for training and testing. Postimaging biopsies were used as a reference standard for classification. The area under the receiver operating curve (AUROC) was used to assess diagnostic performance., Results: Networks performed very well on the public dataset (AUROC 0.938-0.996). The direct generalization to the institutional dataset resulted in lower performances (max AUROC 0.676); however, when tested on BI-RADS 3 and BI-RADS 5 only, results were improved (max AUROC 0.792). Good results were achieved on the institutional dataset (AUROC 0.759-0.818) and, when selecting a threshold of 2% for classification, a sensitivity of 0.983 was obtained for three of five CNNs, with the potential to spare biopsy in 15.3%-18.6% of patients., Conclusion: In conclusion, transfer learning with CNNs may achieve high sensitivity and might be used as a support tool in managing suspicious breast lesions on ultrasound images., Relevance Statement: Transfer learning is a powerful technique to exploit the performances of well-trained CNNs for image classification. In a clinical scenario, it might be useful for the management of suspicious breast lesions on breast ultrasound, potentially sparing biopsy in a non-negligible number of patients., Key Points: Properly trained CNNs with transfer learning are highly effective in differentiating benign and malignant lesions on breast ultrasound. Setting clinical thresholds increased sensitivity. CNNs might be useful as support tools in managing suspicious lesions on breast ultrasound., (© 2024. The Author(s).)

Background: Surgery is still the standard treatment for breast lesions such as in situ ductal carcinoma (DCIS); however, its survival benefit is minimal, particularly for low-grade DCIS. Surgical complications and related depression status can adversely affect patients' quality of life. Approximately 25% of breast cancer (BC) cases are in situ forms, with DCIS making up 90% of these. Low and intermediate-grade DCIS often grow slowly and do not always progress clinically significant diseases. Identifying non-invasive lesions could help prevent overtreatment. In this context, new diagnostic tools like vacuum-assisted excision (VAE) could enhance the management of these conditions., Methods: The prospective VACIS study explores the role of VAE in ensuring the absence of pathology at subsequent surgery and reducing the diagnostic underestimation of breast biopsies for microcalcifications. Patients with suspicious breast microcalcifications up to 15 mm, who are candidates for stereotactic biopsy, will be enrolled and randomised into two groups. The control group will complete the biopsy with typical sampling, aiming to collect some microcalcifications from the target, while the experimental group will focus on the complete removal of the biopsy target (confirmed by mammography on the biopsy table), followed by a second sequence of cleaning samples. Radiograms will confirm lesion removal. Pathologic outcomes at surgery will be compared between the groups, and the percentage of underestimation will be assessed. The sample size is calculated to be 70 patients per group, using statistical tests and multivariate logistic models to detect a significant difference in the absence of pathology. Data collected will include patient age, lesion characteristics, and details of the biopsy, pathology and surgery., Discussion: Current surgical treatments for low-and sometimes intermediate-grade DCIS offer limited survival benefits and may hurt patients' quality of life due to surgery-related complications and associated depression. These lesions often grow slowly and might not become clinically significant, suggesting a need to avoid overtreatment. Improved diagnostics procedures, such as VAE, could help distinguish non-invasive from potentially invasive lesions, reduce biopsy underestimation, enable personalised management and optimise treatment strategies. This study hypothesises that VAE could be a viable alternative to surgery, capable of removing pathology during the biopsy procedure., Clinical Trial Registration: Clinicaltrials.gov, identifier NCT05932758., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Nicosia, Mariano, Latronico, Bozzini, Bellerba, Gaeta, Pesapane, Mazzarol, Fusco, Corso, Sangalli, Giailan, Lazzeroni, Raimondi and Cassano.)

Competing Interests: The authors declare no conflicts of interest.

Radiological interpretations, while essential, are not infallible and are best understood as expert opinions formed through the evaluation of available evidence. Acknowledging the inherent possibility of error is crucial, as it frames the discussion on improving diagnostic accuracy and patient care. A comprehensive review of error classifications highlights the complexity of diagnostic errors, drawing on recent frameworks to categorize them into perceptual and cognitive errors, among others. This classification underpins an analysis of specific error types, their prevalence, and implications for clinical practice. Additionally, we address the psychological impact of radiological practice, including the effects of mental health and burnout on diagnostic accuracy. The potential of artificial intelligence (AI) in mitigating errors is discussed, alongside ethical and regulatory considerations in its application. This research contributes to the body of knowledge on radiological errors, offering insights into preventive strategies and the integration of AI to enhance diagnostic practices. It underscores the importance of a nuanced understanding of errors in radiology, aiming to foster improvements in patient care and radiological accuracy.

In the landscape of cancer treatment, particularly in the realm of breast cancer management, effective communication emerges as a pivotal factor influencing patient outcomes. This article delves into the nuanced intricacies of communication skills, specifically spotlighting the strategies embraced by breast radiologists. By examining the ramifications of communication on patient experience, interdisciplinary collaboration, and legal ramifications, this study underscores the paramount importance of empathetic and comprehensive communication approaches. A special emphasis is placed on the utilization of the SPIKES protocol, a structured method for conveying sensitive health information, and the deployment of strategies for navigating challenging conversations. Furthermore, the work encompasses the significance of communication with caregivers, the integration of artificial intelligence, and the acknowledgement of patients' psychological needs. By adopting empathetic communication methodologies and fostering multidisciplinary collaboration, healthcare practitioners have the potential to enhance patient satisfaction, promote treatment adherence, and augment the overall outcomes within breast cancer diagnosis. This paper advocates for the implementation of guidelines pertaining to psychological support and the allocation of sufficient resources to ensure the provision of holistic and patient-centered cancer care. The article stresses the need for a holistic approach that addresses patients' emotional and psychological well-being alongside medical treatment. Through thoughtful and empathetic communication practices, healthcare providers can profoundly impact patient experiences and breast cancer journeys in a positive manner.

Objectives: To investigate the influence of preoperative breast MRI on mastectomy and reoperation rates in patients with pure ductal carcinoma in situ (DCIS)., Methods: The MIPA observational study database (7245 patients) was searched for patients aged 18-80 years with pure unilateral DCIS diagnosed at core needle or vacuum-assisted biopsy (CNB/VAB) and planned for primary surgery. Patients who underwent preoperative MRI (MRI group) were matched (1:1) to those who did not receive MRI (noMRI group) according to 8 confounding covariates that drive referral to MRI (age; hormonal status; familial risk; posterior-to-nipple diameter; BI-RADS category; lesion diameter; lesion presentation; surgical planning at conventional imaging). Surgical outcomes were compared between the matched groups with nonparametric statistics after calculating odds ratios (ORs)., Results: Of 1005 women with pure unilateral DCIS at CNB/VAB (507 MRI group, 498 noMRI group), 309 remained in each group after matching. First-line mastectomy rate in the MRI group was 20.1% (62/309 patients, OR 2.03) compared to 11.0% in the noMRI group (34/309 patients, p = 0.003). The reoperation rate was 10.0% in the MRI group (31/309, OR for reoperation 0.40) and 22.0% in the noMRI group (68/309, p < 0.001), with a 2.53 OR of avoiding reoperation in the MRI group. The overall mastectomy rate was 23.3% in the MRI group (72/309, OR 1.40) and 17.8% in the noMRI group (55/309, p = 0.111)., Conclusions: Compared to those going directly to surgery, patients with pure DCIS at CNB/VAB who underwent preoperative MRI had a higher OR for first-line mastectomy but a substantially lower OR for reoperation., Clinical Relevance Statement: When confounding factors behind MRI referral are accounted for in the comparison of patients with CNB/VAB-diagnosed pure unilateral DCIS, preoperative MRI yields a reduction of reoperations that is more than twice as high as the increase in overall mastectomies., Key Points: • Confounding factors cause imbalance when investigating the influence of preoperative MRI on surgical outcomes of pure DCIS. • When patient matching is applied to women with pure unilateral DCIS, reoperation rates are significantly reduced in women who underwent preoperative MRI. • The reduction of reoperations brought about by preoperative MRI is more than double the increase in overall mastectomies., (© 2023. The Author(s).)

Objective: To evaluate the performance of radiomic analysis on contrast-enhanced mammography images to identify different histotypes of breast cancer mainly in order to predict grading, to identify hormone receptors, to discriminate human epidermal growth factor receptor 2 (HER2) and to identify luminal histotype of the breast cancer., Methods: From four Italian centers were recruited 180 malignant lesions and 68 benign lesions. However, only the malignant lesions were considered for the analysis. All patients underwent contrast-enhanced mammography in cranium caudal (CC) and medium lateral oblique (MLO) view. Considering histological findings as the ground truth, four outcomes were considered: (1) G1 + G2 vs. G3; (2) HER2 + vs. HER2 - ; (3) HR + vs. HR - ; and (4) non-luminal vs. luminal A or HR + /HER2-  and luminal B or HR + /HER2 + . For multivariate analysis feature selection, balancing techniques and patter recognition approaches were considered., Results: The univariate findings showed that the diagnostic performance is low for each outcome, while the results of the multivariate analysis showed that better performances can be obtained. In the HER2 + detection, the best performance (73% of accuracy and AUC = 0.77) was obtained using a linear regression model (LRM) with 12 features extracted by MLO view. In the HR + detection, the best performance (77% of accuracy and AUC = 0.80) was obtained using a LRM with 14 features extracted by MLO view. In grading classification, the best performance was obtained by a decision tree trained with three predictors extracted by MLO view reaching an accuracy of 82% on validation set. In the luminal versus non-luminal histotype classification, the best performance was obtained by a bagged tree trained with 15 predictors extracted by CC view reaching an accuracy of 94% on validation set., Conclusions: The results suggest that radiomics analysis can be effectively applied to design a tool to support physician decision making in breast cancer classification. In particular, the classification of luminal versus non-luminal histotypes can be performed with high accuracy., (© 2024. Italian Society of Medical Radiology.)

Introduction: Hereditary transthyretin-mediated amyloidosis (ATTRv, v for variant) is a progressive disease caused by mutations in the TTR gene, leading to sensory-motor, axonal and length-dependent neuropathy. However, some patients may show variable electrophysiological pattern. The aim of this study was to evaluate the electrophysiological features of TTR amyloid neuropathy at the time of the first nerve conduction study (NCS) to assess whether there were distinguishing features useful for early diagnosis., Methods: We retrospectively revised the first electrophysiological findings of ATTRv patients, and we categorized the neuropathy based on nerve conduction slowing, type of involved fibres and distribution pattern of PNS involvement. Cluster analysis was performed to evaluate the prevalence of neuropathy features between the early and late stage of disease, based on disease duration and disability burden assessed by NIS., Results: We recruited 33 patients (27 males) with mean age 63.9 ± 10.8 years, mean disease duration 2.8 ± 2.4 years and mean NIS 47.6 ± 41.8. Overall, the frequency analysis showed that the most common features of ATTRv neuropathy included the categories of axonal, sensory-motor and neuronopathic-like pattern. This electrophysiological pattern of PNS involvement was constant in patients in late stage of disease, whereas ATTRv patients in early stage of disease displayed variable electrophysiological pattern of PNS involvement., Discussion: Our findings demonstrated that ATTRv neuropathy may present at first NCS in a variable way, and it changes over the course of disease. Such heterogeneity makes the suspicion of ATTRv even more challenging at the time of first electrophysiological examination., (© 2023. The Author(s).)

Breast cancer remains the most prevalent cancer among women worldwide, necessitating advancements in diagnostic methods. The integration of artificial intelligence (AI) into mammography has shown promise in enhancing diagnostic accuracy. However, understanding patient perspectives, particularly considering the psychological impact of breast cancer diagnoses, is crucial. This narrative review synthesizes literature from 2000 to 2023 to examine breast cancer patients' attitudes towards AI in breast imaging, focusing on trust, acceptance, and demographic influences on these views. Methodologically, we employed a systematic literature search across databases such as PubMed, Embase, Medline, and Scopus, selecting studies that provided insights into patients' perceptions of AI in diagnostics. Our review included a sample of seven key studies after rigorous screening, reflecting varied patient trust and acceptance levels towards AI. Overall, we found a clear preference among patients for AI to augment rather than replace the diagnostic process, emphasizing the necessity of radiologists' expertise in conjunction with AI to enhance decision-making accuracy. This paper highlights the importance of aligning AI implementation in clinical settings with patient needs and expectations, emphasizing the need for human interaction in healthcare. Our findings advocate for a model where AI augments the diagnostic process, underlining the necessity for educational efforts to mitigate concerns and enhance patient trust in AI-enhanced diagnostics.

Breast cancer remains a significant global health challenge, with projections indicating a troubling increase in incidence. Breast cancer screening programs have long been hailed as life-saving initiatives, yet their true impact on mortality rates is a subject of ongoing debate. Screening poses the risk of false positives and the detection of indolent tumors, potentially leading to overtreatment. Bias factors, including lead time, length time, and selection biases, further complicate the assessment of screening efficacy. Recent studies suggest that AI-driven image analysis may revolutionize breast cancer screening, maintaining diagnostic accuracy while reducing radiologists' workload. However, the generalizability of these findings to diverse populations is a critical consideration. Personalized screening approaches and equitable access to advanced technologies are essential to mitigate disparities. In conclusion, the breast cancer screening landscape is evolving, emphasizing the need for risk stratification, appropriate imaging modalities, and a personalized approach to reduce overdiagnosis and focus on cancers with the potential to impact lives while prioritizing patient-centered care., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. This work was partially supported by the Italian Ministry of Health Ricerca Corrente 5 × 1000., (Copyright © 2024 Elsevier B.V. All rights reserved.)

This retrospective study investigates the histopathological outcomes, upgrade rates, and disease-free survival (DFS) of high-risk breast lesions, including atypical ductal hyperplasia (ADH or DIN1b) and lobular in situ neoplasms (LIN), following Vacuum-Assisted Breast Biopsy (VABB) and surgical excision. The study addresses the challenge posed by these lesions due to their association with synchronous or adjacent Breast Cancer (BC) and increased future BC risk. The research, comprising 320 patients who underwent stereotactic VABB, focuses on 246 individuals with a diagnosis of ADH (120) or LIN (126) observed at follow-up. Pathological assessments, categorized by the UK B-coding system, were conducted, and biopsy samples were compared with corresponding excision specimens to determine upgrade rates for in situ or invasive carcinoma. Surgical excision was consistently performed for diagnosed ADH or LIN. Finally, patient follow-ups were assessed and compared between LIN and ADH groups to identify recurrence signs, defined as histologically confirmed breast lesions on either the same or opposite side. The results reveal that 176 (71.5%) patients showed no upgrade post-surgery, with ADH exhibiting a higher upgrade rate to in situ pathology than LIN1 (Atypical Lobular Hyperplasia, ALH)/LIN2 (Low-Grade Lobular in situ Carcinoma, LCIS) (38% vs. 20%, respectively, p -value = 0.002). Considering only patients without upgrade, DFS at 10 years was 77%, 64%, and 72% for ADH, LIN1, and LIN2 patients, respectively ( p -value = 0.92). The study underscores the importance of a multidisciplinary approach, recognizing the evolving role of VABB. It emphasizes the need for careful follow-up, particularly for lobular lesions, offering valuable insights for clinicians navigating the complex landscape of high-risk breast lesions. The findings advocate for heightened awareness and vigilance in managing these lesions, contributing to the ongoing refinement of clinical strategies in BC care.

Contrast-enhanced mammography (CEM) is a relatively recent diagnostic technique increasingly being utilized in clinical practice. Until recently, there was a lack of standardized reporting for CEM findings. However, this has changed with the publication of a supplement in the Breast Imaging Reporting and Data System (BI-RADS). A comprehensive understanding of CEM is essential for further enhancing its role in both screening and managing patients with breast malignancies. CEM can also be beneficial for problem-solving, improving the management of uncertain breast findings. Practitioners in this field should become more cognizant of how and when to employ this technique and interpret the various CEM findings. This paper aims to outline the key findings in the updated version of the BI-RADS specifically dedicated to CEM. Additionally, it will present some clinical cases commonly encountered in clinical practice.Critical relevance statement Standardized reporting and a thorough understanding of CEM findings are pivotal for advancing the role of CEM in screening and managing breast cancer patients. This standardization contributes significantly to integrating CEM as an essential component of daily clinical practice.Key points • A complete knowledge and understanding of the findings outlined in the new BI-RADS CEM are necessary for accurate reporting.• BI-RADS CEM supplement is intuitive and practical to use.• Standardization of the CEM findings enables more accurate patient management., (© 2024. The Author(s).)

Multiple sclerosis (MS) is an autoimmune chronic disease characterized by inflammation and demyelination of the central nervous system (CNS). Despite numerous studies conducted, valid biomarkers enabling a definitive diagnosis of MS are not yet available. The aim of our study was to identify a marker from a blood sample to ease the diagnosis of MS. In this study, since there is evidence connecting the serotonin pathway to MS, we used an ELISA (Enzyme-Linked Immunosorbent Assay) to detect serum MS-specific auto-antibodies (auto-Ab) against the extracellular loop 1 (ECL-1) of the 5-hydroxytryptamine (5-HT) receptor subtype 2A (5-HT2A). We utilized an ELISA format employing poly-D-lysine as a pre-coating agent. The binding of 208 serum samples from controls, both healthy and pathological, and of 104 serum samples from relapsing-remitting MS (RRMS) patients was tested. We observed that the serum-binding activity in control cohort sera, including those with autoimmune and neurological diseases, was ten times lower compared to the RRMS patient cohort ( p = 1.2 × 10 -47 ), with a sensitivity and a specificity of 98% and 100%, respectively. These results show that in the serum of patients with MS there are auto-Ab against the serotonin receptor type 2A which can be successfully used in the diagnosis of MS due to their high sensitivity and specificity.

The primary aim of our study was to assess the main mammographic and ultrasonographic features of invasive male breast malignancies. The secondary aim was to evaluate whether a specific radiological presentation would be associated with a worse receptor profile. Radiological images (mammography and/or ultrasound) of all patients who underwent surgery for male invasive breast cancer in our institution between 2008 and 2023 were retrospectively analyzed by two breast radiologists in consensus. All significant features of radiological presentation known in the literature were re-evaluated. Fifty-six patients were selected. The mean age at surgery of patients was 69 years (range: 35-81); in 82% of cases (46 patients), the histologic outcome was invasive ductal carcinoma. A total of 28 out of 56 (50%) patients had preoperative mammography; in 9/28 cases (32%), we found a mass with microcalcifications on mammography. The mass presented high density in 25 out of 28 patients (89%); the mass showed irregular margins in 15/28 (54%) cases. A total of 46 out of 56 patients had preoperative ultrasounds. The lesion showed a solid mass in 41/46 (89%) cases. In 5/46 patients (11%), the lesion was a mass with a mixed (partly liquid-partly solid) structure. We did not find any statistically significant correlation between major types of radiological presentation and tumor receptor arrangement. Knowledge of the main radiologic presentation patterns of malignant male breast neoplasm can help better manage this type of disease, which is rare but whose incidence is increasing.

Purpose: To compare the diagnostic performance (detection, assessment of correct disease extent and multifocality/centricity) of Contrast-Enhanced Mammography (CEM) Versus Breast Magnetic Resonance (MRI) in the study of lobular neoplasms., Methods: We retrospectively selected all the patients who underwent surgery for a lobular breast neoplasm, either an in situ or an invasive tumor, and had undergone both breast CEM and MRI examinations during the pre-surgical planning. Wilcoxon Signed Rank test was performed to assess the differences between size measurements using the different methods and the post-surgical pathological measurements, considered the gold standard. The agreement in identifying multifocality/multicentricity among the different methods and the pathology was assessed using the Kappa statistics., Results: We selected 19 patients, of which one presented a bilateral neoplasm. Then, the images of these 19 patients were analyzed, for a total of 52 malignant breast lesions. We found no significant differences between the post-surgical pathological size of the lesions and the calculated size with CEM and MRI (p-value of the difference respectively 0.71 and 0.47). In all 20 cases, neoplasm detection was possible both with CEM and MRI. CEM and MRI showed an excellent ability to identify multifocal and multicentric cases (K statistic equal to 0.93 for both the procedures), while K statistic was 0.11 and 0.59 for FFDM and US, respectively., Conclusion: The findings of this study suggest that CEM is a reliable imaging technique in the preoperative setting of patients with lobular neoplasm, with comparable results to breast MRI., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

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. We underscore scientific mobility as a vital tool for radiologists to advocate for healthcare policy changes: it not only enhances diversity and cultural competence within the radiology community but also fosters international cooperation and knowledge exchange among healthcare institutions. Efforts to ensure cultural competency among radiologists are discussed, including ongoing cultural education, sensitivity training, and workforce diversification. These initiatives are key to improving patient communication and reducing healthcare disparities. This paper also highlights the crucial role of policy changes and legislation in promoting equal access to essential screening services like mammography. We explore the challenges and potential of teleradiology in improving access to medical imaging in remote and underserved areas. In the era of artificial intelligence, this paper emphasizes the necessity of validating its models across a spectrum of populations to prevent bias and achieve equitable healthcare outcomes. Finally, the importance of international collaboration is illustrated, showcasing its role in sharing insights and strategies to overcome global access barriers in medical imaging. Overall, this paper offers a comprehensive overview of the challenges related to disparities in medical imaging access and proposes actionable strategies to address these challenges, aiming for equitable healthcare delivery.