Diagnosis of early invasive breast cancer relies on radiology and clinical evaluation, supplemented by biopsy confirmation. At least three issues burden this approach: a) suboptimal sensitivity and suboptimal positive predictive power of radiology screening and diagnostic approaches, respectively; b) invasiveness of biopsy with discomfort for women undergoing diagnostic tests; c) long turnaround time for recall tests. In the screening setting, radiology sensitivity is suboptimal, and when a suspicious lesion is detected and a biopsy is recommended, the positive predictive value of radiology is modest. Recent technological advances in medical imaging, especially in the field of artificial intelligence applied to image analysis, hold promise in addressing clinical challenges in cancer detection, assessment of treatment response, and monitoring disease progression. Radiomics include feature extraction from clinical images; these features are related to tumor size, shape, intensity, and texture, collectively providing comprehensive tumor characterization, the so-called radiomics signature of the tumor. Radiomics is based on the hypothesis that extracted quantitative data derives from mechanisms occurring at genetic and molecular levels. In this article we focus on the role and potential of radiomics in breast cancer diagnosis and prognostication.

Sarcopenia indicates a loss of skeletal muscle mass, a condition that leads to a decline in physical performance. In 2018, the European Working Group on Sarcopenia in Older People met to update the original definition of sarcopenia: New scientific and clinical insights were introduced to emphasize the importance of muscle strength loss as a prime indicator of probable sarcopenia. In addition, the skeletal muscle is not only the organ related to mobility, but it is recognized as a secondary secretory organ too, with endocrine functions influencing several systems and preserving health. In this perspective, radiology could have a major role in early detection of sarcopenia and guarantee improvement in its treatment in clinical practice. We present here an update of clinical knowledge about sarcopenia and advantages and limitations of radiological evaluation of sarcopenia focusing on major body composition imaging modalities such as dual-energy X-ray absorptiometry, CT, and MRI. In addition, we discuss controversial such as the lack of consensus or standardization, different measurement methods, and diagnostic radiological cutoff points. Sarcopenia evaluation with radiological methods could enhance the role of radiologist in performing studies with relevant impact on medical and social outcome, placing radiology at the pinnacle of quality in evidence-based practice with high-level studies.

This study aimed to systematically review and to meta-analyse the accuracy of digital breast tomosynthesis (DBT) versus digital mammography (DM) in women with mammographically dense breasts in screening and diagnosis. Two independent reviewers identified screening or diagnostic studies reporting at least one of four outcomes (cancer detection rate-CDR, recall rate, sensitivity and specificity) for DBT and DM in women with mammographically dense breasts. Study quality was assessed using QUADAS-2. Meta-analysis of CDR and recall rate used a random effects model. Summary ROC curve summarized sensitivity and specificity. Sixteen studies were included (five diagnostic; eleven screening). In diagnosis, DBT increased sensitivity (84%–90%) versus DM alone (69%–86%) but not specificity. DBT improved CDR versus DM alone (RR: 1.16, 95% CI 1.02–1.31). In screening, DBT + DM increased CDR versus DM alone (RR: 1.33, 95% CI 1.20–1.47 for retrospective studies; RR: 1.52, 95% CI 1.08–2.11 for prospective studies). Recall rate was significantly reduced by DBT + DM in retrospective studies (RR: 0.72, 95% CI 0.64–0.80) but not in two prospective studies (RR: 1.12, 95% CI 0.76–1.63). In women with mammographically dense breasts, DBT+/−DM increased CDR significantly (versus DM) in screening and diagnosis. In diagnosis, DBT+/−DM increased sensitivity but not specificity. The effect of DBT + DM on recall rate in screening dense breasts varied between studies.