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Z. Rumboldt, S. Tipnis, D. Vicent, M.V. Spampinato, G. Goldsberry, W. Huda

XIX Symposium Neuroradiologicum. Iterative Reconstruction Algorithm for Head CT. Z. Rumboldt, S. Tipnis, D. Vicent, M.V. Spampinato, G. Goldsberry, W. Huda. Medical University of South Carolina Charleston, SC, USA. Background. CT images traditionally reconstructed

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Z. Rumboldt, S. Tipnis, D. Vicent, M.V. Spampinato, G. Goldsberry, W. Huda

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  1. XIX Symposium Neuroradiologicum Iterative Reconstruction Algorithm for Head CT Z. Rumboldt, S. Tipnis, D. Vicent, M.V. Spampinato, G. Goldsberry, W. Huda Medical University of South Carolina Charleston, SC, USA

  2. Background CT images traditionally reconstructed using filtered back projection techniques (FBP) FBP limitations: geometry, data completeness, radiation dose Increased spatial resolution is directly correlated with increased image noise

  3. Background ITERATIVE IMAGE RECONSTRUCTION approaches recently proposed and introduced may allow for improved image quality and lower noise (2 Alternative Forced Choice methodology) need for a substantial increase in computation power compared to conventional FBP reconstruction iterative reconstruction may allow decoupling of spatial resolution and image noise

  4. After an image is reconstructed, “reprojection” simulates the CT measurement process, with the image as the object, followed by corrections

  5. Each time the image is updated, processing algorithm enhances spatial resolution at higher object contrasts & reduces image noise in low contrast areas

  6. Purpose Clinical evaluation of potential noise reduction and improved lesion detection Novel Methodology Comparison with normal scans for lesion detection, not side by side

  7. Material and Methods Part 1 10 adult head CTs – both FBP and IRIS 2 neuroradiologists evaluated simultaneously both sets for each patient at 3 levels - MCP, BG, and centrum semiovale (30 levels in all) for noise and artifacts raters blinded for the algorithm had 3 choices: preference for A, for B, no preference

  8. Materials and Methods Part 2 Total screened 228 Age range selected 25 through 85 24 abnormal subjects - 30 lesions: 21 hypo 7 hyper 1 mixed 1 iso 12 normal subjects selected to match

  9. Materials and Methods In house software (MUSC, Matthew Daniels, website accessible on campus network) Displayed pairs of single slice CT - Abnormal on Left Location and description of lesion given Rating scale 1 to 101 = Barely discernable 10 = Definitely see lesion PATHOLOGY COMPARED TO THE NORMAL 3 sets for each pair: FBP, NBC, IRIS

  10. Materials and Methods FBP IRIS NBC

  11. FBP

  12. IRIS

  13. NBC

  14. Every reader trained on practice set prior to study Individual randomization for every reader Every reader trained on practice set prior to study Individual randomization for every reader Materials and Methods Every reader trained on practice set prior to study Individual randomization for every reader Analysis Ratios of the obtained values: IRIS/FBP NBC/FBP

  15. Results FBP IRIS

  16. Results Part 1 In all evaluated images (30 levels) noise was considered lower with IRIS compared to FBP Artifacts were less prominent in 11 of the 30 evaluated levels using IRIS and in 3 using FBP (no preference was found for 16 levels)

  17. Results IRIS NBC

  18. Results IRIS NBC

  19. Part 2 Rater 1

  20. Results

  21. Results

  22. Conclusion Iterative reconstruction algorithm decreases noise in Head CT images It seems to improve lesion detection It may allow decreased radiation dose No clear difference between IRIS and NBC

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