Search

Small animal micro computed tomography (μCT) is an important tool in cancer research and is used to quantify liver and lung tumors. A type of cancer that is intensively investigated with μCT is hepatocellular carcinoma (HCC). μCT scans acquire projections from different angles of the gantry which rotates X-ray source and detector around the animal. Motion of the animal causes inconsistencies between the projections which lead to artifacts in the resulting image. This is problematic in HCC research, where respiratory motion affects the image quality by causing hypodense intensity at the liver edge and smearing out small structures such as tumors. Dealing with respiratory motion is particularly difficult in a high throughput setting when multiple mice are scanned together and projection removal by retrospective respiratory gating may compromise image quality and dose efficiency. In mice, inhalation anesthesia leads to a regular respiration with short gasps and long phases of negligible motion. Using this effect and an iterative reconstruction which can cope with missing angles, we discard the relatively few projections in which the gasping motion occurs. Moreover, since gated acquisition, i.e., acquiring multiple projections from a single gantry angle is not a requirement, this method can be applied to existing scans. We applied our method in a high throughput setting in which four mice with HCC tumors were scanned simultaneously in a multi-mouse bed. To establish a ground truth, we manually selected projections with visible respiratory motion. Our automated intrinsic breathing projection selection achieved an accordance of 97% with manual selection. We reconstructed volumetric images and demonstrated that our intrinsic gating method significantly reduces the hypodense depiction at the cranial liver edge and improves the detectability of small tumors. Furthermore, we show that projection removal in a four mice scan discards only 7.5% more projections than in a single-mouse setting, i.e., four mouse scanning does not substantially compromise dose efficiency or image quality. To the best of our knowledge, no comparable method that combines multi-mouse scans for high throughput, intrinsic respiratory gating, and an available iterative reconstruction has been described for liver tumor imaging before.