Synthetic CT: simulating low dose single and dual energy protocols from a dual energy scan.

PURPOSE: The choice of CT protocol can greatly impact patient dose and image quality. Since acquiring multiple scans at different techniques on a given patient is undesirable, the ability to predict image quality changes starting from a high quality exam can be quite useful. While existing methods allow one to generate simulated images of lower exposure (mAs) from an acquired CT exam, the authors present and validate a new method called synthetic CT that can generate realistic images of a patient at arbitrary low dose protocols (kVp, mAs, and filtration) for both single and dual energy scans.
METHODS: The synthetic CT algorithm is derived by carefully ensuring that the expected signal and noise are accurate for the simulated protocol. The method relies on the observation that the material decomposition from a dual energy CT scan allows the transmission of an arbitrary spectrum to be predicted. It requires an initial dual energy scan of the patient to either synthesize raw projections of a single energy scan or synthesize the material decompositions of a dual energy scan. The initial dual energy scan contributes inherent noise to the synthesized projections that must be accounted for before adding more noise to simulate low dose protocols. Therefore, synthetic CT is subject to the constraint that the synthesized data have noise greater than the inherent noise. The authors experimentally validated the synthetic CT algorithm across a range of protocols using a dual energy scan of an acrylic phantom with solutions of different iodine concentrations. An initial 80/140 kVp dual energy scan of the phantom provided the material decomposition necessary to synthesize images at 100 kVp and at 120 kVp, across a range of mAs values. They compared these synthesized single energy scans of the phantom to actual scans at the same protocols. Furthermore, material decompositions of a 100/120 kVp dual energy scan are synthesized by adding correlated noise to the initial material decompositions. The aforementioned noise constraint also allows us to compute feasible mAs values that can be synthesized for each kVp.
RESULTS: The single energy synthesized and actual reconstructed images exhibit identical signal and noise properties at 100 kVp and at 120 kVp, and across a range of mAs values. For example, the noise in both the synthesized and actual images at 100 kVp increases by 2 when the mAs is halved. The synthesized and actual material decompositions of a dual energy protocol show excellent agreement when the decomposition images are linearly weighted to form monoenergetic images at energies from 40 to 100 keV. For simulated single energy protocols with kVp between 80 and 140, the highest feasible mAs exceeds that of either initial scan.
CONCLUSIONS: This work describes and validates the synthetic CT theory and algorithm by comparing its results to actual scans. Synthetic CT is a powerful new tool that allows users to realistically see how protocol selection affects CT images and enables radiologists to retrospectively identify the lowest dose protocol achievable that provides diagnostic quality images on real patients.