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.

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.

Background: Contrast-enhanced mammography (CEM) has recently gained recognition as an effective alternative to breast magnetic resonance imaging (MRI) for assessing breast lesions, offering both morphological and functional imaging capabilities. However, the phenomenon of background parenchymal enhancement (BPE) remains a critical consideration, as it can affect the interpretation of images by obscuring or mimicking lesions. While the impact of BPE has been well-documented in MRI, limited data are available regarding the factors influencing BPE in CEM and its relationship with breast cancer (BC) characteristics. Materials: This retrospective study included 116 patients with confirmed invasive BC who underwent CEM prior to biopsy and surgery. Data collected included patient age, breast density, receptor status, tumor grading, and the Ki-67 proliferation index. BPE was evaluated by two radiologists using the 2022 ACR BI-RADS lexicon for CEM. Statistical analyses were conducted to assess the relationship between BPE, patient demographics, and tumor characteristics. Results: The study found a significant association between higher levels of BPE and specific patient characteristics. In particular, increased BPE was more commonly observed in patients with higher breast density (p < 0.001) and those who were pre-menopausal (p = 0.029). Among patients categorized under density level B, the majority exhibited minimal BPE, while those in categories C and D showed progressively higher levels of BPE, indicating a clear trend correlating higher breast density with increased enhancement. Additionally, pre-menopausal patients demonstrated a higher likelihood of moderate to marked BPE compared to post-menopausal patients. Despite these significant associations, the analysis did not reveal a meaningful correlation between BPE intensity and tumor subtypes (p = 0.77) or tumor grade (p = 0.73). The inter-reader agreement for BPE assessment was substantial, as indicated by a weighted kappa of 0.78 (95% CI: 0.68–0.89), demonstrating consistent evaluation between radiologists. Conclusions: These findings suggest that BPE in CEM is influenced by factors like breast density and age, aligning with patterns observed in MRI studies. However, BPE intensity was not associated with tumor subtypes or grades, indicating a poorer prognosis. These insights highlight the potential of BPE as a risk biomarker in preventive follow-up, particularly for patients with high breast density and pre-menopausal status. Further multicentric and prospective studies are needed to validate these results and deepen the understanding of BPE’s role in CEM diagnostics.

Contrast-enhanced magnetic resonance imaging (CE-MRI) has become an essential modality in breast cancer diagnosis and management. It is particularly used for locoregional staging, high-risk screening, monitoring treatment response, and assessing complications related to breast implants. The integration of gadolinium-based contrast agents (GBCAs) enhances the sensitivity and specificity of CE-MRI by providing detailed morphological and functional insights, particularly highlighting tumor neoangiogenesis. Despite its advantages, CE-MRI faces challenges such as high costs, limited accessibility, and concerns about gadolinium retention in tissues, prompting ongoing research into safer, high-relaxivity contrast agents like gadopiclenol. Advances in multiparametric imaging, including dynamic contrast-enhanced sequences and diffusion-weighted imaging, have refined diagnostic accuracy, enabling precise staging, and treatment planning. The introduction of abbreviated breast MRI (AB-MRI) protocols offers a promising solution to barriers of cost and scan duration, maintaining diagnostic efficacy while improving patient accessibility and comfort. Future innovations in contrast agents, imaging protocols, and patient-centered approaches hold the potential to further enhance the utility of breast MRI, ensuring equitable and effective application in global healthcare systems.