TU-AB-BRA-03: Atlas-Based Algorithms with Local Registration-Goodness Weighting for MRI-Driven Electron Density Mapping

Journal Article · Wed Jun 15 04:00:00 EDT 2016 · Medical Physics

DOI:https://doi.org/10.1118/1.4957413· OSTI ID:22653948

Farjam, R; Tyagi, N ^[1]; Veeraraghavan, H; Apte, A; Zakian, K; Deasy, J ^[2]; Hunt, M ^[3]

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1. Memorial Sloan-Kettering Cancer Center, New York, NY (United States)
2. Memorial Sloan Kettering Cancer Center, New York, NY (United States)
3. Mem Sloan-Kettering Cancer Center, New York, NY (United States)

Purpose: To develop image-analysis algorithms to synthesize CT with accurate electron densities for MR-only radiotherapy of head & neck (H&N) and pelvis anatomies. Methods: CT and 3T-MRI (Philips, mDixon sequence) scans were randomly selected from a pool of H&N (n=11) and pelvis (n=12) anatomies to form an atlas. All MRIs were pre-processed to eliminate scanner and patient-induced intensity inhomogeneities and standardize their intensity histograms. CT and MRI for each patient were then co-registered to construct CT-MRI atlases. For more accurate CT-MR fusion, bone intensities in CT were suppressed to improve the similarity between CT and MRI. For a new patient, all CT-MRI atlases are deformed onto the new patients’ MRI initially. A newly-developed generalized registration error (GRE) metric was then calculated as a measure of local registration accuracy. The synthetic CT value at each point is a 1/GRE-weighted average of CTs from all CT-MR atlases. For evaluation, the mean absolute error (MAE) between the original and synthetic CT (generated in a leave-one-out scheme) was computed. The planning dose from the original and synthetic CT was also compared. Results: For H&N patients, MAE was 67±9, 114±22, and 116±9 HU over the entire-CT, air and bone regions, respectively. For pelvis anatomy, MAE was 47±5 and 146±14 for the entire and bone regions. In comparison with MIRADA medical, an FDA-approved registration tool, we found that our proposed registration strategy reduces MAE by ∼30% and ∼50% over the entire and bone regions, respectively. GRE-weighted strategy further lowers MAE by ∼15% to ∼40%. Our primary dose calculation also showed highly consistent results between the original and synthetic CT. Conclusion: We’ve developed a novel image-analysis technique to synthesize CT for H&N and pelvis anatomies. Our proposed image fusion strategy and GRE metric help generate more accurate synthetic CT using locally more similar atlases (Support: Philips Healthcare). The research is supported by Philips HealthCare.

• OSTI ID: 22653948
• Journal Information: Medical Physics, Journal Name: Medical Physics Journal Issue: 6 Vol. 43; ISSN 0094-2405; ISSN MPHYA6
• Country of Publication: United States
• Language: English

Related Subjects

60 APPLIED LIFE SCIENCES
61 RADIATION PROTECTION AND DOSIMETRY
ALGORITHMS
ANATOMY
IMAGE PROCESSING
NMR IMAGING
PATIENTS
PELVIS
SKELETON