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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.

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. Random effect models were applied for summary area under the curve (AUC), and probability distributions for negative and positive predictive values were obtained. Subgroup analyses explored differences in sensitivity, specificity, and AUC between AB-MRI and FP-MRI., Results: From 11 eligible studies (1 prospective, 10 retrospective), statistical analysis revealed a significant difference in sensitivity between FP-MRI (95%) and AB-MRI (86%, P = .005), with no significant difference in specificity (P = .50). AB-MRI's shorter acquisition time suggests potential for higher patient throughput, but challenges remain in detecting small lesions and nonmass enhancements. Some studies recommend additional sequences, like diffusion-weighted imaging, to improve diagnostic performance., Conclusions: While FP-MRI remains the gold standard in breast cancer detection, AB-MRI offers a quicker alternative, especially in high-risk screening. However, its lower sensitivity limits its use as a standalone diagnostic tool. Future research should optimize AB-MRI protocols and consider patient-specific factors to enhance breast cancer screening and diagnostic strategies., Advances in Knowledge: This meta-analysis expands understanding of AB-MRI's role in breast cancer detection, highlighting its benefits and limitations compared to FP-MRI, particularly in terms of sensitivity and screening efficiency., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Institute of Radiology.)

Background and Aims: Charcot-Marie-Tooth (CMT) is a heterogeneous group of genetic neuropathies and is typically characterized by distal muscle weakness, sensory loss, pes cavus and areflexia. Herein we describe a case of CMT2CC presenting with proximal muscle weakness and equivocal electrophysiological features, that was misdiagnosed as chronic inflammatory demyelinating polyneuropathy (CIDP)., Case Report: A 30-year-old woman complained of proximal muscle weakness with difficulty climbing stairs. Neurological examination showed weakness in lower limb (LL) muscles, that was marked proximally and mild distally, and absence of deep tendon reflexes in the ankles. Nerve conduction studies (NCS) showed sensory-motor neuropathy with non-uniform NC velocity and a partial conduction block (CBs) in peroneal nerve and tibial nerves. Thus, a diagnosis of CIDP was entertained and the patient underwent ineffective treatment with intravenous immunoglobulins. At electrophysiological revaluation CB in peroneal nerve was undetectable as also distal CMAP had decreased whereas the CBs persisted in tibial nerves. Hypothesizing a hereditary neuropathy, we examined the proband's son, who presented mild weakness of distal and proximal muscles at lower limbs. Neurophysiological investigation showed findings consistent with an intermediate-axonal electrophysiological pattern. A targeted-NGS including 136 CMT genes showed the heterozygous frameshift mutation (c.3057dupG; p.K1020fs*43) in the NEFH gene, coding for the neurofilament heavy chain and causing CMT2CC., Interpretation: Diagnosis of a genetic neuropathy may be challenging when clinical features are atypical and/or electrophysiological features are misleading. The most common misdiagnosis is CIDP. Our report suggests that also CMT2CC patients with proximal muscle weakness and equivocal electrophysiological features might be misdiagnosed as CIDP., Competing Interests: Declarations Ethical statement The study was conducted in accordance with the Declaration of Helsinki. Ethical review and approval were waived for this study due to of the retrospective nature of the study and all the procedures being performed were part of the routine care. Conflicting interests The authors declare that there are no competing interests., (© 2024. Fondazione Società Italiana di Neurologia.)

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.

Breast cancer risk models represent the likelihood of developing breast cancer based on risk factors. They enable personalized interventions to improve screening programs. Radiologists identify mammographic density as a significant risk factor and test new imaging techniques. Pathologists provide data for risk assessment. Clinicians conduct individual risk assessments and adopt prevention strategies for high-risk subjects. Tumor genetic testing guides personalized screening and treatment decisions. Artificial intelligence in mammography integrates imaging, clinical, genetic and pathological data to develop risk models. Emerging imaging technologies, genetic testing and molecular profiling improve risk model accuracy. The complexity of the disease, limited data availability and model inputs are discussed. A multidisciplinary approach is essential for earlier detection and improved outcomes.

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. The reference standard was the histological diagnosis or at least 1-year negative imaging follow-up. Inter-reader agreement was examined using Cohen's and Fleiss' kappa (κ) statistics and compared with the Wald test., Results: Of the 750 patients, 395 met inclusion criteria (44.5 ± 14 years old), with 752 breasts available for CEM and MRI. Overall agreement was moderate (κ = 0.60) for MRI and substantial (κ = 0.74) for CEM. For expert readers, the agreement was substantial (κ = 0.77) for MRI and almost perfect (κ = 0.82) for CEM; for non-expert readers was fair (κ = 0.39); and for MRI and moderate (κ = 0.57) for CEM. Pairwise agreement between expert readers and non-expert readers was moderate (κ = 0.50) for breast MRI and substantial (κ = 0.74) for CEM and it showed a statistically superior agreement of the expert over the non-expert readers only for MRI (p = 0.011) and not for CEM (p = 0.062)., Conclusions: The agreement of CEM was superior to that of MRI (p = 0.012), including for both expert (p = 0.031) and non-expert readers (p = 0.005)., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: Breast cancer screening through mammography is crucial for early detection, yet the demand for mammography services surpasses the capacity of radiologists. Artificial intelligence (AI) can assist in evaluating microcalcifications on mammography. We developed and tested an AI model for localizing and characterizing microcalcifications., Methods: Three expert radiologists annotated a dataset of mammograms using histology-based ground truth. The dataset was partitioned for training, validation, and testing. Three neural networks (AlexNet, ResNet18, and ResNet34) were trained and evaluated using specific metrics including receiver operating characteristics area under the curve (AUC), sensitivity, and specificity. The reported metrics were computed on the test set (10% of the whole dataset)., Results: The dataset included 1,000 patients aged 21-73 years and 1,986 mammograms (180 density A, 220 density B, 380 density C, and 220 density D), with 389 malignant and 611 benign groups of microcalcifications. AlexNet achieved the best performance with 0.98 sensitivity, 0.89 specificity of, and 0.98 AUC for microcalcifications detection and 0.85 sensitivity, 0.89 specificity, and 0.94 AUC of for microcalcifications classification. For microcalcifications detection, ResNet18 and ResNet34 achieved 0.96 and 0.97 sensitivity, 0.91 and 0.90 specificity and 0.98 and 0.98 AUC, retrospectively. For microcalcifications classification, ResNet18 and ResNet34 exhibited 0.75 and 0.84 sensitivity, 0.85 and 0.84 specificity, and 0.88 and 0.92 AUC, respectively., Conclusions: The developed AI models accurately detect and characterize microcalcifications on mammography., Relevance Statement: AI-based systems have the potential to assist radiologists in interpreting microcalcifications on mammograms. The study highlights the importance of developing reliable deep learning models possibly applied to breast cancer screening., Key Points: • A novel AI tool was developed and tested to aid radiologists in the interpretation of mammography by accurately detecting and characterizing microcalcifications. • Three neural networks (AlexNet, ResNet18, and ResNet34) were trained, validated, and tested using an annotated dataset of 1,000 patients and 1,986 mammograms. • The AI tool demonstrated high accuracy in detecting/localizing and characterizing microcalcifications on mammography, highlighting the potential of AI-based systems to assist radiologists in the interpretation of mammograms., (© 2023. The Author(s).)

Mammary Paget disease (MPD) is a rare condition primarily affecting adult women, characterized by unilateral skin changes in the nipple-areolar complex (NAC) and frequently associated with underlying breast carcinoma. Histologically, MPD is identified by large intraepidermal epithelial cells (Paget cells) with distinct characteristics. Immunohistochemical profiles aid in distinguishing MPD from other skin conditions. Clinical evaluation and imaging techniques, including magnetic resonance imaging (MRI), are recommended if MPD is suspected, although definitive diagnosis always requires histological examination. This review delves into the historical context, epidemiology, pathogenesis, clinical manifestations, and diagnosis of MPD, emphasizing the need for early detection. The classification of MPD based on pathogenesis is explored, shedding light on its varied presentations. Treatment options, including mastectomy and breast-conserving surgery, are discussed with clear guidelines for different scenarios. Adjuvant therapies are considered, particularly in cases with underlying breast cancer. Prognostic factors are outlined, underlining the importance of early intervention. Looking to the future, emerging techniques, like liquid biopsy, new immunohistochemical and molecular markers, and artificial intelligence-based image analysis, hold the potential to transform MPD diagnosis and treatment. These innovations offer hope for early detection and improved patient care, though validation through large-scale clinical trials is needed.

Objective: The objective of the study was to evaluate the accuracy of radiomics features obtained by MR images to predict Breast Cancer Histological Outcome., Methods: A total of 217 patients with malignant lesions were analysed underwent MRI examinations. Considering histological findings as the ground truth, four different types of findings were used in both univariate and multivariate analyses: (1) G1 + G2 vs G3 classification; (2) presence of human epidermal growth factor receptor 2 (HER2 + vs HER2 -); (3) presence of the hormone receptor (HR + vs HR -); and (4) presence of luminal subtypes of breast cancer., Results: The best accuracy for discriminating HER2 + versus HER2 - breast cancers was obtained considering nine predictors by early phase T1-weighted subtraction images and a decision tree (accuracy of 88% on validation set). The best accuracy for discriminating HR + versus HR - breast cancers was obtained considering nine predictors by T2-weighted subtraction images and a decision tree (accuracy of 90% on validation set). The best accuracy for discriminating G1 + G2 versus G3 breast cancers was obtained considering 16 predictors by early phase T1-weighted subtraction images in a linear regression model with an accuracy of 75%. The best accuracy for discriminating luminal versus non-luminal breast cancers was obtained considering 27 predictors by early phase T1-weighted subtraction images and a decision tree (accuracy of 94% on validation set)., Conclusions: The combination of radiomics analysis and artificial intelligence techniques could be used to support physician decision-making in prediction of Breast Cancer Histological Outcome., (© 2023. Italian Society of Medical Radiology.)

Importance: Sentinel lymph node biopsy (SLNB) is the standard of care for axillary node staging of patients with early breast cancer (BC), but its necessity can be questioned since surgery for examination of axillary nodes is not performed with curative intent., Objective: To determine whether the omission of axillary surgery is noninferior to SLNB in patients with small BC and a negative result on preoperative axillary lymph node ultrasonography., Design, Setting, and Participants: The SOUND (Sentinel Node vs Observation After Axillary Ultra-Sound) trial was a prospective noninferiority phase 3 randomized clinical trial conducted in Italy, Switzerland, Spain, and Chile. A total of 1463 women of any age with BC up to 2 cm and a negative preoperative axillary ultrasonography result were enrolled and randomized between February 6, 2012, and June 30, 2017. Of those, 1405 were included in the intention-to-treat analysis. Data were analyzed from October 10, 2022, to January 13, 2023., Intervention: Eligible patients were randomized on a 1:1 ratio to receive SLNB (SLNB group) or no axillary surgery (no axillary surgery group)., Main Outcomes and Measures: The primary end point of the study was distant disease-free survival (DDFS) at 5 years, analyzed as intention to treat. Secondary end points were the cumulative incidence of distant recurrences, the cumulative incidence of axillary recurrences, DFS, overall survival (OS), and the adjuvant treatment recommendations., Results: Among 1405 women (median [IQR] age, 60 [52-68] years) included in the intention-to-treat analysis, 708 were randomized to the SLNB group, and 697 were randomized to the no axillary surgery group. Overall, the median (IQR) tumor size was 1.1 (0.8-1.5) cm, and 1234 patients (87.8%) had estrogen receptor-positive ERBB2 (formerly HER2 or HER2/neu), nonoverexpressing BC. In the SLNB group, 97 patients (13.7%) had positive axillary nodes. The median (IQR) follow-up for disease assessment was 5.7 (5.0-6.8) years in the SLNB group and 5.7 (5.0-6.6) years in the no axillary surgery group. Five-year distant DDFS was 97.7% in the SLNB group and 98.0% in the no axillary surgery group (log-rank P = .67; hazard ratio, 0.84; 90% CI, 0.45-1.54; noninferiority P = .02). A total of 12 (1.7%) locoregional relapses, 13 (1.8%) distant metastases, and 21 (3.0%) deaths were observed in the SLNB group, and 11 (1.6%) locoregional relapses, 14 (2.0%) distant metastases, and 18 (2.6%) deaths were observed in the no axillary surgery group., Conclusions and Relevance: In this randomized clinical trial, omission of axillary surgery was noninferior to SLNB in patients with small BC and a negative result on ultrasonography of the axillary lymph nodes. These results suggest that patients with these features can be safely spared any axillary surgery whenever the lack of pathological information does not affect the postoperative treatment plan., Trial Registration: ClinicalTrials.gov Identifier: NCT02167490.

Rationale and Objectives: The new version of the Contrast Enhanced Mammography (CEM) Breast imaging Reporting and Data System (BIRADs) encourages investigations of a new enhancement descriptor: "Lesion Conspicuity" (LC). The study aims to assess the diagnostic performance and the relationship with the receptor profile of this new enhancement descriptor., Materials and Methods: Three hundred twenty-five patients with 381 breast lesions who underwent CEM before histological assessmentwere selected. Four radiologists, blinded to each other, categorized LC into the following levels: absent, low, moderate, and high. Considering moderate and high evaluations as predictive of malignancy, the diagnostic performance of CEM was calculated using histological results of the biopsy as the gold standard. The association between LC values and the receptor profile of the neoplasms was also evaluated., Results: The median age at the CEM examination was 50 years (IQR: 45-59). Considering the value of LC of the most experienced radiologist with the interpretation of Low Energy images (LE), we obtained a sensitivity (SE) of 91.9% (95% CI: 88.6%-95.2%) and a specificity (SP) of 67.2% (95% CI: 58.9%-75.5%). An association between "high" lesion conspicuity with ER/PgR not expressed (p = 0.025), with Ki-67>20% (p = 0.033), and with Grading G3 (p = 0.020) was observed., Conclusion: The new feature of enhancement, "Lesion Conspicuity", demonstrated satisfactory performance in predicting the malignancy of lesions and significant correlation with the receptor profile of malignant breast neoplasms., Competing Interests: Declaration of Competing Interest This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors., (Copyright © 2023 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Many women with spinal muscular atrophy (SMA) types II, III, and IV reach fertile age, and some of them may consider pregnancy. However, limited data are available about the potential effects of pregnancy on the course of SMA and the outcomes of pregnancies in these patients. Furthermore, the use of several disease-modifying therapies for the treatment of all types of SMA is expected to increase the number of female SMA patients considering pregnancy in the coming years. The aim of this report is to provide clinicians with an overview of the patients in our cohort who have experienced pregnancies. We conducted a retrospective analysis on these women, through the administration of a questionnaire, which investigated how they experienced the different stages of the pregnancy. Ten patients (3 SMAII; 7 SMA III) participated in the survey; 40% had pregnancies for a total of nine, six of which were term-pregnancies. The mean age of first pregnancy was 32.5 ± 7.8 years for SMA II patients, and 30.5 ± 2.1 years for SMA III. All pregnancies ended in cesarean sections. Interestingly, the sitters had more frequent complications in pre-term labor and delivery, but the newborns were all healthy. This report shows that a successful pregnancy is possible in female patients with SMA. However, the ideal approach should involve a standardized multidisciplinary team capable of effectively addressing every possible scenario. For this reason, it is critically important that clinicians working with SMA patients gain more in-dept knowledge about this topic., Competing Interests: The authors declare no conflict of interest., (©2023 Gaetano Conte Academy - Mediterranean Society of Myology, Naples, Italy.)

Standardized radiological reports stimulate debate in the medical imaging field. This review paper explores the advantages and challenges of standardized reporting. Standardized reporting can offer improved clarity and efficiency of communication among radiologists and the multidisciplinary team. However, challenges include limited flexibility, initially increased time and effort, and potential user experience issues. The efforts toward standardization are examined, encompassing the establishment of reporting templates, use of common imaging lexicons, and integration of clinical decision support tools. Recent technological advancements, including multimedia-enhanced reporting and AI-driven solutions, are discussed for their potential to improve the standardization process. Organizations such as the ACR, ESUR, RSNA, and ESR have developed standardized reporting systems, templates, and platforms to promote uniformity and collaboration. However, challenges remain in terms of workflow adjustments, language and format variability, and the need for validation. The review concludes by presenting a set of ten essential rules for creating standardized radiology reports, emphasizing clarity, consistency, and adherence to structured formats.

Objectives: To report mastectomy and reoperation rates in women who had breast MRI for screening (S-MRI subgroup) or diagnostic (D-MRI subgroup) purposes, using multivariable analysis for investigating the role of MRI referral/nonreferral and other covariates in driving surgical outcomes., Methods: The MIPA observational study enrolled women aged 18-80 years with newly diagnosed breast cancer destined to have surgery as the primary treatment, in 27 centres worldwide. Mastectomy and reoperation rates were compared using non-parametric tests and multivariable analysis., Results: A total of 5828 patients entered analysis, 2763 (47.4%) did not undergo MRI (noMRI subgroup) and 3065 underwent MRI (52.6%); of the latter, 2441/3065 (79.7%) underwent MRI with preoperative intent (P-MRI subgroup), 510/3065 (16.6%) D-MRI, and 114/3065 S-MRI (3.7%). The reoperation rate was 10.5% for S-MRI, 8.2% for D-MRI, and 8.5% for P-MRI, while it was 11.7% for noMRI (p ≤ 0.023 for comparisons with D-MRI and P-MRI). The overall mastectomy rate (first-line mastectomy plus conversions from conserving surgery to mastectomy) was 39.5% for S-MRI, 36.2% for P-MRI, 24.1% for D-MRI, and 18.0% for noMRI. At multivariable analysis, using noMRI as reference, the odds ratios for overall mastectomy were 2.4 (p < 0.001) for S-MRI, 1.0 (p = 0.957) for D-MRI, and 1.9 (p < 0.001) for P-MRI., Conclusions: Patients from the D-MRI subgroup had the lowest overall mastectomy rate (24.1%) among MRI subgroups and the lowest reoperation rate (8.2%) together with P-MRI (8.5%). This analysis offers an insight into how the initial indication for MRI affects the subsequent surgical treatment of breast cancer., Key Points: • Of 3065 breast MRI examinations, 79.7% were performed with preoperative intent (P-MRI), 16.6% were diagnostic (D-MRI), and 3.7% were screening (S-MRI) examinations. • The D-MRI subgroup had the lowest mastectomy rate (24.1%) among MRI subgroups and the lowest reoperation rate (8.2%) together with P-MRI (8.5%). • The S-MRI subgroup had the highest mastectomy rate (39.5%) which aligns with higher-than-average risk in this subgroup, with a reoperation rate (10.5%) not significantly different to that of all other subgroups., (© 2023. The Author(s).)

Background and Objectives : 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. Materials and Methods : This review discusses various imaging techniques used for ALN evaluation, including ultrasound, computed tomography, magnetic resonance imaging, and positron emission tomography. It highlights advancements in these techniques and their potential to improve diagnostic accuracy. The review also examines landmark clinical trials that have influenced axillary management, such as the Z0011 trial and the IBCSG 23-01 trial. The role of artificial intelligence (AI), specifically deep learning algorithms, in improving ALN assessment is examined. Results : The review outlines the key findings of these trials, which demonstrated the feasibility of avoiding axillary lymph node dissection (ALND) in certain patient populations with low sentinel lymph node (SLN) burden. It also discusses ongoing trials, including the SOUND trial, which investigates the use of axillary ultrasound to identify patients who can safely avoid sentinel lymph node biopsy (SLNB). Furthermore, the potential of emerging techniques and the integration of AI in enhancing ALN assessment accuracy are presented. Conclusions : The review concludes that advancements in ALN assessment techniques have the potential to improve patient outcomes by reducing surgical complications while maintaining accurate disease staging. However, challenges such as standardization of imaging protocols and interpretation criteria need to be addressed. Future research should focus on large-scale clinical trials to validate emerging techniques and establish their efficacy and cost-effectiveness. Over-all, this review provides valuable insights into the current status and future directions of ALN assessment in BC, highlighting opportunities for improving patient care.

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. A radiologist with experience in breast imaging (R1) and a radiology resident (R2) independently evaluated DWI/ADC maps and, in case of doubts, T2-WI. The standard of reference was the pathological diagnosis through biopsy or surgery, or ≥1 year of clinical and radiological follow-up. Diagnostic performances were calculated for both readers with a 95% confidence interval (CI). The agreement was assessed using Cohen's kappa (κ) statistics., Results: Out of 313 women, 145 women were included (49.5 ± 12 years), totaling 344 breast MRIs with DWI/ADC maps. The per-exam cancer prevalence was 11/344 (3.2%). The sensitivity was 8/11 (73%; 95% CI: 46-99%) for R1 and 7/11 (64%; 95% CI: 35-92%) for R2. The specificity was 301/333 (90%; 95% CI: 87-94%) for both readers. The diagnostic accuracy was 90% for both readers. R1 recalled 40/344 exams (11.6%) and R2 recalled 39/344 exams (11.3%). Inter-reader reproducibility between readers was in moderate agreement (κ = 0.43)., Conclusions: In female carriers of a BRCA1/2 mutation, breast DWI supplemented with T2-WI allowed breast cancer detection with high sensitivity and specificity by a radiologist with extensive experience in breast imaging, which is comparable to other screening tests. The findings suggest that DWI and T2-WI have the potential to serve as a stand-alone method for unenhanced breast MRI screening in a selected population, opening up new perspectives for prospective trials.

Breast cancer is the most common forms of cancer and a leading cause of mortality in women. Early and correct diagnosis is, therefore, essential to save lives. The development of diagnostic imaging applied to the breast has been impressive in recent years and the most used diagnostic test in the world is mammography, a low-dose X-ray technique used for imaging the breast. In the first half of the 20th century, the diagnosis was in practice only clinical, with consequent diagnostic delay and an unfavorable prognosis in the short term. The rise of organized mammography screening has led to a remarkable reduction in mortality through the early detection of breast malignancies. This historical review aims to offer a complete panorama of the development of mammography and breast imaging during the last century. Through this study, we want to understand the foundations of the pillar of radiology applied to the breast through to the most modern applications such as contrast-enhanced mammography (CEM), artificial intelligence, and radiomics. Understanding the history of the development of diagnostic imaging applied to the breast can help us understand how to better direct our efforts toward an increasingly personalized and effective diagnostic approach. The ultimate goal of imaging applied to the detection of breast malignancies should be to reduce mortality from this type of disease as much as possible. With this paper, we want to provide detailed documentation of the main steps in the evolution of breast imaging for the diagnosis of breast neoplasms; we also want to open up new scenarios where the possible current and future applications of imaging are aimed at being more precise and personalized.

This study aims to evaluate the Average Glandular Dose (AGD) and diagnostic performance of CEM versus Digital Mammography (DM) as well as versus DM plus one-view Digital Breast Tomosynthesis (DBT), which were performed in the same patients at short intervals of time. A preventive screening examination in high-risk asymptomatic patients between 2020 and 2022 was performed with two-view Digital Mammography (DM) projections (Cranio Caudal and Medio Lateral) plus one Digital Breast Tomosynthesis (DBT) projection (mediolateral oblique, MLO) in a single session examination. For all patients in whom we found a suspicious lesion by using DM + DBT, we performed (within two weeks) a CEM examination. AGD and compression force were compared between the diagnostic methods. All lesions identified by DM + DBT were biopsied; then, we assessed whether lesions found by DBT were also highlighted by DM alone and/or by CEM. We enrolled 49 patients with 49 lesions in the study. The median AGD was lower for DM alone than for CEM (3.41 mGy vs. 4.24 mGy, p = 0.015). The AGD for CEM was significantly lower than for the DM plus one single projection DBT protocol (4.24 mGy vs. 5.55 mGy, p < 0.001). We did not find a statistically significant difference in the median compression force between the CEM and DM + DBT. DM + DBT allows the identification of one more invasive neoplasm one in situ lesion and two high-risk lesions, compared to DM alone. The CEM, compared to DM + DBT, failed to identify only one of the high-risk lesions. According to these results, CEM could be used in the screening of asymptomatic high-risk patients.

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. The histological results were considered the gold standard. In the first analysis, enhancement degree scores of 2 and 3 were considered predictive of malignity. The sensitivity (SE) and positive predictive value (PPV) were significative lower for patients with lesions with microcalcifications without other radiological findings (SE = 53.3% vs. 82.2%, p -value < 0.001 and PPV = 84.2% vs. 95.2%, p -value = 0.049, respectively). On the contrary, the specificity (SP) and negative predictive value (NPV) were significative higher among lesions with microcalcifications without other radiological findings (SP = 95.8% vs. 84.2%, p -value = 0.026 and NPV = 82.9% vs. 55.2%, p -value < 0.001, respectively). In a second analysis, degree scores of 1, 2, and 3 were considered predictive of malignity. The SE (80.0% vs. 96.8%, p -value < 0.001) and PPV (70.6% vs. 88.3%, p -value: 0.005) were significantly lower among lesions with microcalcifications without other radiological findings, while the SP (85.9% vs. 50.9%, p -value < 0.001) was higher. The enhancement of microcalcifications has low sensitivity in predicting malignancy. However, in certain controversial cases, the absence of CESM enhancement due to its high negative predictive value can help to reduce the number of biopsies for benign lesions.

Recent technological advances in the field of artificial intelligence hold promise in addressing medical challenges in breast cancer care, such as early diagnosis, cancer subtype determination and molecular profiling, prediction of lymph node metastases, and prognostication of treatment response and probability of recurrence. Radiomics is a quantitative approach to medical imaging, which aims to enhance the existing data available to clinicians by means of advanced mathematical analysis using artificial intelligence. Various published studies from different fields in imaging have highlighted the potential of radiomics to enhance clinical decision making. In this review, we describe the evolution of AI in breast imaging and its frontiers, focusing on handcrafted and deep learning radiomics. We present a typical workflow of a radiomics analysis and a practical "how-to" guide. Finally, we summarize the methodology and implementation of radiomics in breast cancer, based on the most recent scientific literature to help researchers and clinicians gain fundamental knowledge of this emerging technology. Alongside this, we discuss the current limitations of radiomics and challenges of integration into clinical practice with conceptual consistency, data curation, technical reproducibility, adequate accuracy, and clinical translation. The incorporation of radiomics with clinical, histopathological, and genomic information will enable physicians to move forward to a higher level of personalized management of patients with breast cancer.

The study aimed to evaluate the performance of radiomics features and one ultrasound CAD (computer-aided diagnosis) in the prediction of the malignancy of a breast lesion detected with ultrasound and to develop a nomogram incorporating radiomic score and available information on CAD performance, conventional Breast Imaging Reporting and Data System evaluation (BI-RADS), and clinical information. Data on 365 breast lesions referred for breast US with subsequent histologic analysis between January 2020 and March 2022 were retrospectively collected. Patients were randomly divided into a training group ( n = 255) and a validation test group ( n = 110). A radiomics score was generated from the US image. The CAD was performed in a subgroup of 209 cases. The radiomics score included seven radiomics features selected with the LASSO logistic regression model. The multivariable logistic model incorporating CAD performance, BI-RADS evaluation, clinical information, and radiomic score as covariates showed promising results in the prediction of the malignancy of breast lesions: Area under the receiver operating characteristic curve, [AUC]: 0.914; 95% Confidence Interval, [CI]: 0.876-0.951. A nomogram was developed based on these results for possible future applications in clinical practice.

Background: In the past decade, interest in applying Artificial Intelligence (AI) in radiology to improve diagnostic procedures increased. AI has potential benefits spanning all steps of the imaging chain, from the prescription of diagnostic tests to the communication of test reports. The use of AI in the field of radiology also poses challenges in doctor-patient communication at the time of the diagnosis. This systematic review focuses on the patient role and the interpersonal skills between patients and physicians when AI is implemented in cancer diagnosis communication., Methods: A systematic search was conducted on PubMed, Embase, Medline, Scopus, and PsycNet from 1990 to 2021. The search terms were: ("artificial intelligence" or "intelligence machine") and "communication" "radiology" and "oncology diagnosis". The PRISMA guidelines were followed., Results: 517 records were identified, and 5 papers met the inclusion criteria and were analyzed. Most of the articles emphasized the success of the technological support of AI in radiology at the expense of patient trust in AI and patient-centered communication in cancer disease. Practical implications and future guidelines were discussed according to the results., Conclusions: AI has proven to be beneficial in helping clinicians with diagnosis. Future research may improve patients' trust through adequate information about the advantageous use of AI and an increase in medical compliance with adequate training on doctor-patient diagnosis communication.

Background: Image-guided vacuum-assisted breast biopsy (VABB) of the tumour bed, performed after neoadjuvant therapy, is increasingly being used to assess residual cancer and to potentially identify to identify pathological complete response (pCR). In this study, the accuracy of preoperative VABB specimens was assessed and compared with surgical specimens in patients with triple-negative or human epidermal growth factor receptor 2 (HER2)-positive invasive ductal breast cancer after neoadjuvant therapy. As a secondary endpoint, the performance of contrast-enhanced MRI of the breast and PET-CT for response prediction was assessed., Methods: This single-institution prospective pilot study enrolled patients from April 2018 to April 2021 with a complete response on imaging (iCR) who subsequently underwent VABB before surgery. Those with a pCR at VABB were included in the primary analysis of the accuracy of VABB. The performance of imaging (MRI and PET-CT) was analysed for prediction of a pCR considering both patients with an iCR and those with residual disease at postneoadjuvant therapy imaging., Results: Twenty patients were included in the primary analysis. The median age was 44 (range 35-51) years. At surgery, 18 of 20 patients showed a complete response (accuracy 90 (95 per cent exact c.i. 68 to 99) per cent). Only two patients showed residual ductal intraepithelial neoplasia of grade 2 and 3 respectively. In the secondary analysis, accuracy was similar for MRI and PET-CT (77 versus 78 per cent; P = 0.76)., Conclusion: VABB in patients with an iCR might be a promising method to select patients for de-escalation of surgical treatment in triple-negative or HER2-positive breast cancer. The present results support such an approach and should inform the design of future trials on de-escalation of surgery., (© The Author(s) 2022. Published by Oxford University Press on behalf of BJS Society Ltd.)

Multiple sclerosis (MS) is a chronic, debilitating disease characterised by demyelination of the nerves of the central nervous system that results in patients progressively losing the ability to perform daily tasks. As there is no cure for this disease, rehabilitation therapy is an important aspect of care; assisting patients to regain or retain function and improve their physical, mental and social wellbeing. At present there is no current consistent model of care for MS, likely due to the variable symptom presentation. Various forms of rehabilitation therapy are available, and these include physical rehabilitation methods, such as balance and gait therapy, speech and respiration rehabilitation, and occupational therapy. Contrary to previous understanding, exercise-based therapies have shown various benefits for patients with MS, and in addition to improving MS-related physical symptoms, have been shown to reduce the risk of developing cardiovascular disease and can improve cognitive function. Cognition rehabilitation therapy specifically focuses on behavioural tasks and is divided into two main forms: compensatory rehabilitation, which offers cognitive functioning benefits, and restorative rehabilitation, which offers memory benefits. Excitation therapies include cranial stimulation and other stimulation rehabilitation methods such as focal muscle vibration therapy and these non-invasive techniques may improve patient's physical ability. Additionally, more novel rehabilitation methods include robot-assisted gait therapy and telerehabilitation, both of which are expected to play progressively more prominent roles in the future of rehabilitation therapy. The structure of the care team has been found to impact patient outcomes, and both in- and out-patient care settings have been found to be beneficial, dependant on the patient's circumstances, with certain patients better suited to a particular setting. While a single point of care is recommended for patients, a multidisciplinary care team and regular reassessment is recommended to manage changing symptoms and ensure continuity of care. The importance of the critical components of rehabilitation have been identified, and these are of vital importance in achieving beneficial outcomes. These components include the patients' participation in the treatment, goal setting with a multidisciplinary care team, a guiding-light purpose for the patient, which focusses on recognizing their personal potential and obtaining improvements through a tailored plan. The final critical component of rehabilitation is the results measurement, which highlights the need for a quantifiable reduction in impairment and improvement in activity and participation. Overall, a lack of standardisation in outcome measurements makes comparison challenging. This is particularly important when comparing standard methods of care with more novel rehabilitation techniques. However, within the broad area of rehabilitation therapies, it is clear that patients with MS can benefit from rehabilitation practices; physically, mentally and socially., Competing Interests: Declaration of Competing Interest None, (Copyright © 2022. Published by Elsevier B.V.)

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. Multinomial-logistic-regression was performed on items with more than two response categories. Odds ratio (OR) with 95% CI were computed to estimate the probability of a specific response according to patient's characteristics., Results: In the 800 analysed questionnaires, 51% of respondents confirmed to have knowledge of AI. Of these, 88% expressed a positive opinion about its use in medicine. Non-Italian respondents were associated with the belief of having a deep awareness about AI more often than Italian respondents (OR = 1.91;95% CI[1.10-3.33]). Higher education level was associated with better opinions on the use of AI in medicine (OR = 4.69;95% CI[1.36-16.12]). According to 94% of respondents, the radiologists should always produce their own report on mammograms, whilst 77% agreed that AI should be used as a second reader. Most respondents (52%) considered that both the software developer and the radiologist should be held accountable for AI errors., Conclusions: Most of the females undergoing screening in our Institute approve the introduction of AI, although only as a support to radiologist, and not in substitution thereof. Yet, accountability in case of AI errors is still unsolved. advances in knowledge:This survey may be considered as a pilot-study for the development of large-scale studies to understand females's demands and concerns about AI applications in breast cancer screening.

We aimed to investigate the association between the radiomic features of contrast-enhanced spectral mammography (CESM) images and a specific receptor pattern of breast neoplasms. In this single-center retrospective study, we selected patients with neoplastic breast lesions who underwent CESM before a biopsy and surgical assessment between January 2013 and February 2022. Radiomic analysis was performed on regions of interest selected from recombined CESM images. The association between the features and each evaluated endpoint (ER, PR, Ki-67, HER2+, triple negative, G2-G3 expressions) was investigated through univariate logistic regression. Among the significant and highly correlated radiomic features, we selected only the one most associated with the endpoint. From a group of 321 patients, we enrolled 205 malignant breast lesions. The median age at the exam was 50 years (interquartile range (IQR) 45-58). NGLDM&#95;Contrast was the only feature that was positively associated with both ER and PR expression ( p -values = 0.01). NGLDM&#95;Coarseness was negatively associated with Ki-67 expression ( p -value = 0.02). Five features SHAPE Volume(mL), SHAPE&#95;Volume(vx), GLRLM&#95;RLNU, NGLDM&#95;Busyness and GLZLM&#95;GLNU were all positively and significantly associated with HER2+; however, all of them were highly correlated. Radiomic features of CESM images could be helpful to predict particular molecular subtypes before a biopsy.

Botulinum toxin (BT) is an effective treatment for spasticity symptoms in multiple sclerosis (MS). Despite its wide use in clinical practices, only few studies have explored long-term persistence. We aim to evaluate the rate of discontinuation of BT treatment and the correlation with MS, spasticity, and injection variables. This retrospective study on 3-year prospectively collected data included 122 MS patients receiving BT injections for spasticity. We collected MS clinical variables (disease durations, Expanded Disability Status Scales [EDSSs], disease-modifying treatments [DMT], and Symbol Digit Modalities Tests [SDMTs]), modified Ashworth scales [MASs], concomitant treatments, and injection variables (formulation, dose, number of injections, and intervals between injections). A total of 14 out of the 122 patients discontinued BT after a mean time of 3.0 ± 1.5 years. In the Cox regression model including the MS clinical variables, the probability of BT discontinuations increased in patients with DMT changes during follow-ups (HR = 6.34; 95%Cl = 2.47, 18.08; p < 0.01) and with impaired SDMTs (HR = 1.20; 95%Cl = 1.04, 1.96; p < 0.01). In the model including the spasticity variables, there were no associations between BT discontinuation and MAS or other spasticity treatments. In the model including the injection variables, the probability of discontinuation decreased by 80% for each cumulative injection (HR = 0.16; 95%Cl = 0.05, 0.45; p < 0.01), but increased by 1% for each additional day over the 3-month interval between injections (HR = 1.27; 95%Cl = 1.07, 1.83; p < 0.01). BT discontinuation was associated with concomitant MS-related issues (e.g., treatment failure and DMT change) and the presence of cognitive impairment, which should be accounted for when planning injections. The interval between injections should be kept as short as possible from regulatory and clinical perspectives to maximize the response across all of the spasticity symptoms and to reduce discontinuation in the long term.

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. Accordingly, healthcare could use digital twins to improve personalized medicine. Furthermore, the accumulation of digital twin models from real-world deployments will enable large cohorts of digital patients that may be used for virtual clinical trials and population studies. Through their further refinement, development, and application into clinical practice, digital twins could be crucial in the era of personalized medicine, revolutionizing how diseases are detected and managed. Although significant challenges remain in the development of digital twins, a structural modification to the current operating models is occurring, and radiologists can guide the introduction of such technology into healthcare.

Purpose: To compare the accuracy of Contrast-Enhanced Spectral Mammography (CESM), MG, US, and breast MRI in estimating the size of breast lesions requiring surgery. The postoperative histology size of the lesion was used as the gold standard., Material and Methods: Two hundred thirty-three non-benign lesions in 189 patients were included in the analyses. All the selected patients underwent CESM and at least one other conventional diagnostic exam (US, MG, or MRI). Subsequently, all the patients underwent surgery preceded by cytological/histological examination. The largest diameter of the lesion at imaging was measured by a radiologist with more than 10 years' experience and then compared with the size of the lesion in the histological sample at the surgery (gold standard)., Results: Among the 233 breast lesions, 196 were evaluated with US, 206 with MG and 160 with MRI. We found no statistically significant differences between size measurements using CESM and MRI compared with the measurements at the surgery (p value 0.63 and 0.51), whereas a significant difference was found for MG and US (p < 0.001)., Conclusion: CESM is a reliable method for estimating the size of breast lesions: its performance seems superior to US and MG and comparable to MRI., (© 2022. Italian Society of Medical Radiology.)

Purpose: To present an overview of the management of male patients with Ductal Carcinoma In Situ of the breast (male DCIS)., Methods: We retrospectively studied all male patients with a diagnosis of pure DCIS from January 1999 to December 2018: 20 patients were identified in our cancer referral center. We collected data regarding clinical presentation, age of onset, radiological features, receptor status of the neoplasm, histological type, and the follow-up of those patients., Results: The median age was 62 years (range 21-80). All patients underwent surgery, in 15/20 (75%) cases a mastectomy was carried out. Two patients (10%) underwent endocrine treatment and 1/20 (5%) underwent radiotherapy. The receptor status for 15/20 patients was documented: 13/15 patients were ER+/Pr+. In 3 cases the Ki 67% was positive (i.e., > 20%). All cases were negative for Her2. The median follow-up time was 9.0 years (IQR 4.0-13.7). Only one patient had an ipsilateral recurrence with the finding of an infiltrating carcinoma in the same breast after 14 years. The 5-year disease-free survival was 92.9%., Conclusion: Pure DCIS in men is an extremely rare disease: proper diagnosis and management allow an excellent prognosis., (© 2022. The Author(s).)