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Transcranial focused ultrasound (tFUS) is a therapeutic ultrasound methodthat focuses sound through the skull to a small region noninvasively and oftenunder MRI guidance. CT imaging is used to estimate the acoustic properties thatvary between individual skulls to enable effective focusing during tFUSprocedures, exposing patients to potentially harmful radiation. A method toestimate acoustic parameters in the skull without the need for CT would bedesirable. Here, we synthesized CT images from routinely acquired T1-weightedMRI by using a 3D patch-based conditional generative adversarial network (cGAN)and evaluated the performance of synthesized CT (sCT) images for treatmentplanning with tFUS. We compared the performance of sCT to real CT (rCT) imagesfor tFUS planning using Kranion and simulations using the acoustic toolbox,k-Wave. Simulations were performed for 3 tFUS scenarios: 1) no aberrationcorrection, 2) correction with phases calculated from Kranion, and 3) phaseshifts calculated from time-reversal. From Kranion, skull density ratio, skullthickness, and number of active elements between rCT and sCT had Pearson'sCorrelation Coefficients of 0.94, 0.92, and 0.98, respectively. Among 20targets, differences in simulated peak pressure between rCT and sCT werelargest without phase correction (12.4$\pm$8.1%) and smallest with Kranionphases (7.3$\pm$6.0%). The distance between peak focal locations between rCTand sCT was less than 1.3 mm for all simulation cases. Real and syntheticallygenerated skulls had comparable image similarity, skull measurements, andacoustic simulation metrics. Our work demonstrates the feasibility of replacingreal CTs with the MR-synthesized CT for tFUS planning. Source code and a dockerimage with the trained model are available athttps://github.com/han-liu/SynCT_TcMRgFUS

Evaluation of Synthetically Generated CT for use in Transcranial Focused Ultrasound Procedures