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Simulated breast lesion models, including microcalcification clusters and masses, have been used in several studies. Realistic lesion models are required for virtual clinical trials to be representative of clinical performance. Multiple methods exist to generate breast lesion models with various levels of realism depending on the application. First, lesion models can be obtained using mathematical methods, such as approximating a lesion with 3D geometric shapes or using algorithmic techniques such as iterative processes to grow a lesion. On the other hand, lesion models can be based on patient data. They can be either created starting from characteristics of real lesions or they can be a replica of clinical lesions by segmenting real cancer cases. Next, various approaches exist to embed these lesions into breast structures to create tumour cases. The simplest method, typically used for calcifications, is intensity scaling. Two other common approaches are the hybrid and total simulation method, in which the lesion model is inserted into a real breast image or a 3D breast model, respectively. In addition, artificial intelligence-based approaches can directly grow breast lesions in breast images. This article provides a review of the literature available on the development of lesion models, simulation methods to insert them into background structures and their applications, including optimisation studies, performance evaluation of software and education. |
