Evolving paradigms in breast cancer screening: Balancing efficacy, personalization, and equity.

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.

Advances in breast cancer risk modeling: integrating clinics, imaging, pathology and artificial intelligence for personalized risk assessment.

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.

Future Directions in the Assessment of Axillary Lymph Nodes in Patients with Breast Cancer.

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.

Disparities in Breast Cancer Diagnostics: How Radiologists Can Level the Inequalities.

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.

Contrast-Enhanced Spectral Mammography and tumor size assessment: a valuable tool for appropriate surgical management of breast lesions.

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.

The P.I.N.K. Study Approach for Supporting Personalized Risk Assessment and Early Diagnosis of Breast Cancer.

Breast cancer is a clear example of excellent survival when it is detected and properly treated in the early stage. Currently, screening of this cancer relies on mammography, which may be integrated by new imaging techniques for more exhaustive evaluation. The Personalized, Integrated, Network, Knowledge (P.I.N.K.) study is a longitudinal multicentric study involving several diagnostic centres across Italy, co-ordinated by the Italian National Research Council and co-funded by the Umberto Veronesi Foundation. Aim of the study is to evaluate the increased diagnostic accuracy in detecting cancers obtained with different combinations of imaging technologies, and find the most effective diagnostic pathway matching the characteristics of an individual patient. The study foresees the enrolment of 50,000 women over the age of 40 years presenting for breast examination and providing informed consent to data handling. So far, the 15 participating centres across Italy have recruited a total of 22,848 patients. Based on the analyses of the first 175 histopathological-proven breast cancers, mammographic sensitivity was estimated to be 61.7% (n = 108 cancers), whereas diagnostic accuracy increased by 35.5% (n = 44 cancers) when mammography was integrated with other imaging modalities (ultrasound and/or digital breast tomosynthesis). Increase was mainly determined by ultrasound alone. Given the ongoing data collection and recruitment, the number of cancers detected is too low to allow any further in-depth analysis to explore links to patient characteristics. Past studies show that the uniform approach of population screening guidelines should be revised in favour of more personalised regimens, where known standards are integrated by imaging techniques most suitable for the individual's characteristics. With the ultimate goal of identifying early breast cancer detection strategies, our preliminary results suggest that integrated diagnostic approach could lead to a paradigm shift from an age-based regimen toward more specific and effective risk-based personalised screening regimens, in order to reduce mortality from breast cancer.

Breast tissue composition and its dependence on demographic risk factors for breast cancer: non-invasive assessment by time domain diffuse optical spectroscopy.

BACKGROUND: Breast tissue composition is recognized as a strong and independent risk factor for breast cancer. It is a heritable feature, but is also significantly affected by several other elements (e.g., age, menopause). Nowadays it is quantified by mammographic density, thus requiring the use of ionizing radiation. Optical techniques are absolutely non-invasive and have already proved effective in the investigation of biological tissues, as they are sensitive to tissue composition and structure. METHODS: Time domain diffuse optical spectroscopy was performed at 7 wavelengths (635-1060 nm) on 200 subjects to derive their breast tissue composition (in terms of water, lipid and collagen content), blood parameters (total hemoglobin content and oxygen saturation level), and information on the microscopic structure (scattering amplitude and power). The dependence of all optically-derived parameters on age, menopausal status, body mass index, and use of oral contraceptives, and the correlation with mammographic density were investigated. RESULTS: Younger age, premenopausal status, lower body mass index values, and use of oral contraceptives all correspond to significantly higher water, collagen and total hemoglobin content, and lower lipid content (always p < 0.05 and often p < 10-4), while oxygen saturation level and scattering parameters show significant dependence only on some conditions. Even when age-adjusted groups of subjects are compared, several optically derived parameters (and in particular always collagen and total hemoglobin content) remain significantly different. CONCLUSIONS: Time domain diffuse optical spectroscopy can probe non-invasively breast tissue composition and physiologic blood parameters, and provide information on tissue structure. The measurement is suitable for in vivo studies and monitoring of changes in breast tissue (e.g., with age, lifestyle, chemotherapy, etc.) and to gain insight into related processes, like the origin of cancer risk associated with breast density.

Noninvasive assessment of breast cancer risk using time-resolved diffuse optical spectroscopy.

Breast density is a recognized strong and independent risk factor for breast cancer. We propose the use of time-resolved transmittance spectroscopy to estimate breast tissue density and potentially provide even more direct information on breast cancer risk. Time-resolved optical mammography at seven wavelengths (635 to 1060 nm) is performed on 49 subjects. Average information on breast tissue of each subject is obtained on oxy- and deoxyhemoglobin, water, lipids, and collagen content, as well as scattering amplitude and power. All parameters, except for blood volume and oxygenation, correlate with mammographic breast density, even if not to the same extent. A synthetic optical index proves to be quite effective in separating different breast density categories. Finally, the estimate of collagen content as a more direct means for the assessment of breast cancer risk is discussed.

Ultrasound-guided vacuum assisted breast biopsy in the assessment of C3 breast lesions by ultrasound-guided fine needle aspiration cytology: results and costs in comparison with surgery.

Breast lesions defined C3 at ultrasound (US)-guided fine needle aspiration cytology (FNAC) are probably benign, but exhibit atypias. We evaluate the results of US-guided vacuum assisted breast biopsy (VABB) of these lesions. Patients diagnosed C3 by US-FNAC, submitted to US-VABB and with a minimum follow-up of 36 months or surgery were enrolled. Cost outcome of this diagnostic protocol was evaluated. We evaluated 138 patients with non-palpable C3 lesions. In 2/138 (1.4%) cases VABB results were inadequate. VABB diagnosed: 17/138 (12.3%) malignant and 119/138 (86.2%) benign lesions. In 28/138 cases (20.3%) surgery retrieved 18/28 (64.3%) malignant lesions. One false negative result of VABB was observed. Sensitivity and specificity of VABB resulted 94.4% and 100%. Our diagnostic algorithm estimated a 45% mean decrease of costs using VABB when compared with surgical biopsy of all C3 lesions.