PublicationDetail

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

A. Martinez-Möller, L. Marinelli, S. Weismüller, C. Castrop, M. Schwaiger, S. Nekolla
Automatic alignment of myocardial rest/stress perfusion imaging and its impact on the analysis workflow
Journal of Nuclear Medicine 2011, 51 (suppl. 1), p257. Proceedings of Annual Meeting of Society of Nuclear Medicine (SNM 2011), San Antonio, TX, USA, June 2011 (bib)

Objectives
The alignment of the rest/stress myocardial perfusion SPECT (MPS) images is typically done manually by defining the cardiac axis separately on each image. A biased axis definition in one or both datasets can lead to diagnostic errors. We propose a modified workflow with an automatic realignment of MPS images prior to its reorientation and further processing. Methods: 96 pts (age 68±10y) undergoing a rest/stress 99mTc-MIBI scan on a Siemens E.Cam were included. In addition to the routine analysis, a new analysis workflow with automated registration and one single definition of the cardiac axis for both images was used. Two experienced physicians determined which of the rest/stress reoriented views showed a better spatial matching and whether repetition due to deficient registration was needed. The polar maps were compared to normal databases to determine the extent of ischemia and scar. Results: The new workflow provided superior spatial matching in 56% of the cases, equivalent in 43% and inferior in 1%. Repetition of the analysis was needed in 26% of the cases with separate axis definition vs. 2% with automatic registration. The analysis time for a single patient was halved (59±7 vs. 123±95 sec). Considering the misregistration-related repetitions and assuming 5 min time for identification and communication of a needed repetition, 45 min are saved daily in a site with 15 pts/day. There was no significant difference in extent of ischemia, but a trend towards decreased ischemia and increased scar area with the automatic registration (avg. change of 1.2±3.3% of the LV, 11 pts with change >5%). Conclusions: Automatic registration allows a faster analysis and produces results which are less operator-dependent and show better spatial matching as compared to separate axis definition. Incorrect spatial matching can occasionally impact tissue classification with scar areas partially appearing as ischemic due to the misregistration.
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