INTRODUCTION: Head movement during CT brain perfusion (CTP) acquisition can deteriorate the accuracy of CTP analysis. Most CTP software packages can only correct in-plane movement and are limited to small ranges. The purpose of this study is to validate a novel 3D correction method for head movement during CTP acquisition. METHODS: Thirty-five CTP datasets that were classified as defective due to head movement were included in this study. All CTP time frames were registered with non-contrast CT data using a 3D rigid registration method. Location and appearance of ischemic area in summary maps derived from original and registered CTP datasets were qualitative compared with follow-up non-contrast CT. A quality score (QS) of 0 to 3 was used to express the degree of agreement. Furthermore, experts compared the quality of both summary maps and assigned the improvement score (IS) of the CTP analysis, ranging from -2 (much worse) to 2 (much better). RESULTS: Summary maps generated from corrected CTP significantly agreed better with appearance of infarct on follow-up CT with mean QS 2.3 versus mean QS 1.8 for summary maps from original CTP (P = 0.024). In comparison to original CTP data, correction resulted in a quality improvement with average IS 0.8: 17 % worsened (IS = -2, -1), 20 % remained unchanged (IS = 0), and 63 % improved (IS = +1, +2). CONCLUSION: The proposed 3D movement correction improves the summary map quality for CTP datasets with severe head movement.
INTRODUCTION: Head movement during CT brain perfusion (CTP) acquisition can deteriorate the accuracy of CTP analysis. Most CTP software packages can only correct in-plane movement and are limited to small ranges. The purpose of this study is to validate a novel 3D correction method for head movement during CTP acquisition. METHODS: Thirty-five CTP datasets that were classified as defective due to head movement were included in this study. All CTP time frames were registered with non-contrast CT data using a 3D rigid registration method. Location and appearance of ischemic area in summary maps derived from original and registered CTP datasets were qualitative compared with follow-up non-contrast CT. A quality score (QS) of 0 to 3 was used to express the degree of agreement. Furthermore, experts compared the quality of both summary maps and assigned the improvement score (IS) of the CTP analysis, ranging from -2 (much worse) to 2 (much better). RESULTS: Summary maps generated from corrected CTP significantly agreed better with appearance of infarct on follow-up CT with mean QS 2.3 versus mean QS 1.8 for summary maps from original CTP (P = 0.024). In comparison to original CTP data, correction resulted in a quality improvement with average IS 0.8: 17 % worsened (IS = -2, -1), 20 % remained unchanged (IS = 0), and 63 % improved (IS = +1, +2). CONCLUSION: The proposed 3D movement correction improves the summary map quality for CTP datasets with severe head movement.
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