Patient data •Clinical data •Medical images •Surface scans Population data •Tissue elasticity •Breast shape model Digital Breast Surgery Patient •Coherent digital representation of the patient Surgical Planning •Incision lines •Resection volume •Sutures Outcome Simulation •Biomechanics •Wound healing •Radiotherapy •Aesthetic quantification Shared Decision Making •Multi-disciplinary team meeting •Patient-surgeon interaction PICTURE: Predicting the cosmetic outcome of breast cancer surgery Jörg Sabczynski 1 , Hans Barschdorf 1 , Thomas Bülow 1 , Maria João Cardoso 2,3 , Jaime S. Cardoso 3 , Alex Clarke 4 , Björn Eiben 5,1 , Pedro Gouveia 2 , David Hawkes 5 , John Hipwell 5 , Mohammed Keshtgar 4 , Rene Lacher 5 , Dominik Kutra 1 , Gerrit-Jan Liefers 6 , Kirsten Meetz 1 , Barbara Molenkamp 6 , João P. Monteiro 3 , Afshin Mosahebi 4 , Hélder P. Oliveira 3 , Ralph Sinkus 7 , Danail Stoyanov 6 , Vasileios Vavourakis 5 , Cornelis JH van de Velde 6 , Norman Williams 4 , Stewart Young 1 , Hooshiar Zolfagharnasab 3 1 Philips Technologie GmbH Innovative Technologies, 2 Fundação Champalimaud, 3 INESC TEC, 4 Royal Free London NHS Foundation Trust, 5 UCL-Centre for Medical Image Computing, 6 Leiden University Medical Center, 7 King’s College London Correspondence: Joerg.Sabczynski@Philips.com, Röntgenstraße 24-26, 22335 Hamburg, Germany Breast cancer is the most common cancer affecting women in Europe (1). It has become an increasingly treatable disease with a 10-year survival rate exceeding 80%. It is usually treated with surgery, often in conjunction with radiotherapy and systemic treatments. Two types of surgery are available:  breast-conserving surgery (also known as lumpectomy) or  mastectomy (i.e. the partial or complete removal of the breast). However, even breast-conserving surgery can affect the appearance of the breast, a prospect that can cause a great deal of stress. Therefore, a good aesthetic outcome is an important consideration in breast cancer therapies and is closely linked to the patient’s psychological recovery and self-image after treatment. Yet for an estimated 30% of women treated with breast-conserving surgery, the result is less than ideal aesthetically (2). Unfortunately, to date there is no objective way to assess or predict the aesthetic outcome of breast cancer treatment. In this paper, we report on the work of the project Patient Information Combined for the Assessment of Specific Surgical Outcomes in Breast Cancer (PICTURE), which is funded by the European Community’s Seventh Framework Programme. The goal of the project is to create, validate, and demonstrate a system for the patient-specific planning, evaluation, prediction, and quantification of the outcome of breast-conserving surgery. This system, the PICTURE demonstrator, supports the complete clinical workflow needed to plan and predict the appearance of the patient’s breast after therapy. The PICTURE demonstrator thus supports surgeons in surgical planning prior to the operation. It is also designed to aid patient-clinician communication by visualizing the foreseen outcome, and thereby empowers patients to take an active role in a Shared Decision Making process. Figure 1: Processing chain of the PICTURE demonstrator. Figure 1 illustrates the approach taken by the PICTURE project: At the beginning of the PICTURE demonstrator processing pipeline is the acquisition of individual patient data. Since the demonstrator should support visualisation of the shape and appearance of the breast in an upright position, it is essential that not only the shape of the breast is captured, but also skin texture and skin colour. For this purpose, we use low-cost and easy to use equipment such as standard digital cameras to capture views of the patient from multiple directions, or off-the-shelf depth sensors as developed by the gaming industry (e.g. Microsoft Kinect). The result of this acquisition is a 3D surface shape of the patient’s torso with coloured skin texture (3).