Does CS-SENSE acceleration influence the performance of an AI based synthetic CT algorithm? A volunteer study in the lumbar spine.

In this work, we investigated the performance of an AI based algorithm - synthetic CT generation - when subjected to compressed sensing-sensitivity encoding (CS-SENSE) accelerated gradient echo images. We performed MR experiments in five volunteers, using different CS-SENSE acceleration factors for the MR acquisitions. Our results showed that using CS-SENSE factors of 1.45 and 2 increased noise in the MR source images but did not compromise the sCT reconstruction on visual inspection, which was confirmed by quantitative metrics. However, CS-SENSE with a factor of 3 caused artifacts in the sCT images which may affect the safety and diagnostic performance of the product.