The National Cancer Institute (NCI) Cancer Imaging Program organized two related workshops on June 26-27, 2013, entitled "Correlating Imaging Phenotypes with Genomics Signatures Research" and "Scalable Computational Resources as Required for Imaging-Genomics Decision Support Systems." The first workshop focused on clinical and scientific requirements, exploring our knowledge of phenotypic characteristics of cancer biological properties to determine whether the field is sufficiently advanced to correlate with imaging phenotypes that underpin genomics and clinical outcomes, and exploring new scientific methods to extract phenotypic features from medical images and relate them to genomics analyses. The second workshop focused on computational methods that explore informatics and computational requirements to extract phenotypic features from medical images and relate them to genomics analyses and improve the accessibility and speed of dissemination of existing NIH resources. These workshops linked clinical and scientific requirements of currently known phenotypic and genotypic cancer biology characteristics with imaging phenotypes that underpin genomics and clinical outcomes. The group generated a set of recommendations to NCI leadership and the research community that encourage and support development of the emerging radiogenomics research field to address short-and longer-term goals in cancer research.

Breast cancer, the second most common cause of cancer in women, affects people across different ages, ethnicities, and incomes. However, while all women have some risk of breast cancer, studies have found that some populations are more vulnerable to poor breast cancer outcomes. Specifically, women with lower socioeconomic status and of Black and Hispanic ethnicity have been found to have more advanced stages of cancer upon diagnosis. These findings correlate with studies that have found decreased use of screening mammography services in these underserved populations. To alleviate these healthcare disparities, mobile mammography units are well positioned to provide convenient screening services to enable earlier detection of breast cancer. Mobile mammography services have been operating since the 1970s, and, in the current pandemic, they may be extremely helpful. The COVID-19 pandemic has significantly disrupted necessary screening services, and reinstatement and implementation of accessible mobile screenings may help to alleviate the impact of missed screenings. This review discusses the history and benefits of mobile mammography, especially for underserved women.

We have developed a novel, model-based active contour algorithm, termed “snakules”, for the annotation of spicules on mammography. At each suspect spiculated mass location that has been identified by either a radiologist or a computer-aided detection (CADe) algorithm, we deploy snakules that are converging open-ended active contours also known as snakes. The set of convergent snakules have the ability to deform, grow and adapt to the true spicules in the image, by an attractive process of curve evolution and motion that optimizes the local matching energy. Starting from a natural set of automatically detected candidate points, snakules are deployed in the region around a suspect spiculated mass location. Statistics of prior physical measurements of spiculated masses on mammography are used in the process of detecting the set of candidate points. Observer studies with experienced radiologists to evaluate the performance of snakules demonstrate the potential of the algorithm as an image analysis technique to improve the specificity of CADe algorithms and as a CADe prompting tool.