Background: Evaluating the aesthetic success of breast reconstruction can be difficult. Patients, surgeons, and the general population may differ in what constitutes a successful outcome. Recently, crowdsourcing has emerged to accumulate and analyze data on a massive scale. The authors propose that crowdsourcing can be a useful tool to reliably rate aesthetic outcomes of breast reconstruction. Methods: One hundred one deidentified photographs of patients at various stages of breast reconstruction were gathered. Assessment tools included a five-point Likert scale and the transverse rectus abdominis myocutaneous (TRAM) visual assessment scale. Anonymous crowd workers and a group of expert reconstructive surgeons rated an identical set of photographs on the Likert scale. Crowd workers also rated the set of photographs on the TRAM scale. Results: The authors obtained 901 anonymous, layperson evaluations on both Likert and TRAM scales. Crowdsourced assessment data collection took 28.6 hours. Expert assessment took 15 months. Expert and crowdsourced scores were equivalent on the Likert scale (overall interrater reliability, κ = 0.99; 95 percent CI, 0.98 to 0.99). Intrarater reliability among each subcomponent was highly reproducible for the crowd (r = 0.98; 95 percent CI, 0.97 to 0.99) and experts (r = 0.82; 95 percent CI, 0.77 to 0.87). Breast contour and positioning were most predictive of overall aesthetic result. Skin patch and scar were least predictive of overall aesthetic appearance. Conclusions: Aesthetic outcomes rated by crowds were reliable and correlated closely with those by expert surgeons. Crowdsourcing can be a rapid, reliable, and valid way to assess aesthetic outcomes in the breast reconstruction patient.

he fields of plastic and reconstructive surgery, dermatology, and aesthetic medicine are concerned with changes in visual states of being. Whether seeking to improve the appearance of the aging face or reconstruct the diseased or damaged body, health care providers seek to move patients from a suboptimal state to a second state that is improved. To evaluate the success of therapeutic maneuvers, effective descriptions of changes in visual state are needed. This process requires that the appreciation of the first state and those that follow is valid and reliable (Fig. 1). Although visual assessment appears to be inherently subjective, there is a growing trend of largescale megadata that provide the necessary power for validation and reliability. This has the potential to transform the future of aesthetic medicine from the subjective into the objective. This review attempts to evaluate the current state of validated visual scales in the fields of dermatology, plastic