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This Special Report summarizes the 2022 AAPM Grand Challenge on Deep‐Learning spectral Computed Tomography (DL‐spectral CT) image reconstruction.

The purpose of the challenge is to develop the most accurate image reconstruction algorithm possible for solving the inverse problem associated with a fast kilovolt switching dual‐energy CT scan using a three tissue‐map decomposition. Participants could choose to use a deep‐learning (DL), iterative, or a hybrid approach.

The challenge is based on a 2D breast CT simulation, where the simulated breast phantom consists of three tissue maps: adipose, fibroglandular, and calcification distributions. The phantom specification is stochastic so that multiple realizations can be generated for DL approaches. A dual‐energy scan is simulated where the x‐ray source potential of successive views alternates between 50 and 80 …