Automated calculation of symmetry measure on clinical photographs.

Breast cancer is one of the most prevalent forms of cancer in the world. Each year, there are approximately 250,000 cases of breast cancer diagnosed among women in the USA [1]. Fortunately, the survival rate is relatively high and continually increasing due to improved detection techniques and treatment methods. However, maintaining quality of life is a factor often poorly addressed for breast cancer survivors. Breast cancer treatments are often highly invasive and can adversely affect the breast tissue and lead to deformation of the breast. Currently, assessment of breast appearance is not objectively reported; instead subjective assessments of breast appearance by doctors, patients, and other observers are used [2]. Subjective assessments often have high inter- and intra-observer variability. As a result, there is a need for objective, quantifiable methods of assessing breast appearance that are more reliable than subjective observations in order to understand the impact of deformity on patient quality of life, to guide selection of current treatments, and to make rational treatment advances [2, 3]. Breast morphology can be objectively quantified using distances between fiducial points at common anatomical landmarks or ratios of such distances. Such approaches have been successfully implemented in the field of breast conservation therapy (e.g. [4, 5]). We have demonstrated that similar techniques can be designed for use in evaluating breast reconstruction [6]. Traditionally these measurements have been made directly on the body using a tape measure. However, there are drawbacks with traditional anthropometry. For example, the process is repetitive, tedious and time consuming and may be embarrassing for the patient. The advent of digital photography has provided a practical alternative known as photogrammetry. Photogrammetry is faster than traditional measuring techniques, since the patient need not wait until all measurements are made. Photographs can be stored and re-analyzed at a later date. Images taken at various time points can be used to track changes in the appearance of the patient over time. In the field of radiation oncology, a widely accepted method for quantifying the symmetry of the nipples positions’ is the Breast Retraction Assessment measure, or BRA, developed by Pezner et al [7]. A normalized version of the BRA measure, called pBRA, was developed by Limbergen et al. [8] in order to account for different magnifications of the patient images. The pBRA value is equal to the BRA value divided by the distance from a reference point, the sternal notch to the nipple of the untreated breast. This distance from the sternal notch to the nipple of the breast that did not undergo breast conservation therapy is always greater than the distance from the sternal notch to the treated breast [4, 5]. Van Limbergen et al. found smaller intra- and inter-observer variability based on pBRA than on subjective assessments [8]. However, a significant drawback of current approaches to computing measures of breast appearance such as pBRA is that they are dependent upon manual identification of the fiducial points on a digital photograph by a human observer. There is inherent variability in localizations made by human observers, which can thus introduce variability into measures computed from the annotated fiducial points. In a previous study in our laboratory, Kim et al. [6] studied the variability in manual localization of some fiducial points as part of an investigation of a new measure of ptosis that can be computed from digital photographs. Kim et al. demonstrated that the variability introduced by manual annotation is modest for some fiducial points, such as the nipples, and thus the impact on the measure computed from those annotations is minimal. More variation was observed with subtle points, such as the lateral terminus of the inframammary fold. Nevertheless, manual localization of fiducial points remains a key-limiting factor in the widespread adoption of computerized analysis of breast surgery outcomes from digital photography. Manual identification of fiducial points is time consuming and disruptive to the typical clinical workflow. Traditionally, the sternal notch has been used in the normalization of pBRA. However, the sternal notch is not always visible in digital photographs, particularly in photographs of women with a higher body-mass index (BMI). Hence, in this study, we propose the umbilicus as a reference point for normalizing our symmetry measure. The goal of this study was to develop and implement a fully automated method of localizing the umbilicus and the nipples on anterior-posterior digitized/digital photographs of women. The locations were used to automatically calculate a variant of pBRA, which we term pBRA2, for each subject. The automatic localizations were compared to manually-obtained fiducial points’ locations to assess the algorithms’ accuracy. Likewise, the corresponding pBRA measurements obtained using the automatically determined vs. manually determined fiducial points were compared.