Implementation of a Novel Algorithm For Generating Synthetic CT Images From Magnetic Resonance Imaging Data Sets for Prostate Cancer Radiation Therapy

Kim, Joshua; Glide-Hurst, Carri; Doemer, Anthony; Wen, Ning; Movsas, Benjamin; Chetty, Indrin J.

doi:10.1016/J.IJROBP.2014.09.015

Title: Implementation of a Novel Algorithm For Generating Synthetic CT Images From Magnetic Resonance Imaging Data Sets for Prostate Cancer Radiation Therapy

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Abstract

Purpose: To describe and evaluate a method for generating synthetic computed tomography (synCT) images from magnetic resonance simulation (MR-SIM) data for accurate digitally reconstructed radiograph (DRR) generation and dose calculations in prostate cancer radiation therapy. Methods and Materials: A retrospective evaluation was performed in 9 prostate cancer patients who had undergone MR-SIM in addition to CT simulation (CT-SIM). MR-SIM data were used to generate synCT images by using a novel, voxel-based weighted summation approach. A subset of patients was used for weight optimization, and the number of patients to use during optimization was determined. Hounsfield unit (HU) differences between CT-SIM and synCT images were analyzed via mean absolute error (MAE). Original, CT-based treatment plans were mapped onto synCTs. DRRs were generated, and agreement between CT and synCT-generated DRRs was evaluated via Dice similarity coefficient (DSC). Dose was recalculated, and dose-volume metrics and gamma analysis were used to evaluate resulting treatment plans. Results: Full field-of-view synCT MAE across all patients was 74.3 ± 10.9 HU with differences from CTs of 2.0 ± 8.1 HU and 11.9 ± 46.7 HU for soft tissue structures (prostate, bladder, and rectum) and femoral bones, respectively. Calculated DSCs for anterior-posterior and lateral DRRs were 0.90 ± 0.04 and 0.92 ± 0.05, respectively. Differences in D99%, mean dose,more »« less

Authors:: Kim, Joshua; Glide-Hurst, Carri; Doemer, Anthony; Wen, Ning; Movsas, Benjamin; Chetty, Indrin J.

Publication Date:: Thu Jan 01 00:00:00 EST 2015

OSTI Identifier:: 22423837

Resource Type:: Journal Article

Journal Name:: International Journal of Radiation Oncology, Biology and Physics

Additional Journal Information:: Journal Volume: 91; Journal Issue: 1; Other Information: Copyright (c) 2015 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0360-3016

Country of Publication:: United States

Language:: English

Subject:: 62 RADIOLOGY AND NUCLEAR MEDICINE; ALGORITHMS; AMINO ACIDS; BLADDER; CAT SCANNING; IMAGE PROCESSING; NEOPLASMS; NMR IMAGING; PATIENTS; PLANNING; PROSTATE; RADIATION DOSES; RADIOTHERAPY; RECTUM; SKELETON

Citation Formats


                    Kim, Joshua, Glide-Hurst, Carri, Doemer, Anthony, Wen, Ning, Movsas, Benjamin, and Chetty, Indrin J. Implementation of a Novel Algorithm For Generating Synthetic CT Images From Magnetic Resonance Imaging Data Sets for Prostate Cancer Radiation Therapy.  United States: N. p., 2015. 
        Web.  doi:10.1016/J.IJROBP.2014.09.015.

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                    Kim, Joshua, Glide-Hurst, Carri, Doemer, Anthony, Wen, Ning, Movsas, Benjamin, & Chetty, Indrin J. Implementation of a Novel Algorithm For Generating Synthetic CT Images From Magnetic Resonance Imaging Data Sets for Prostate Cancer Radiation Therapy.  United States.  https://doi.org/10.1016/J.IJROBP.2014.09.015

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                    Kim, Joshua, Glide-Hurst, Carri, Doemer, Anthony, Wen, Ning, Movsas, Benjamin, and Chetty, Indrin J. 2015.  
        "Implementation of a Novel Algorithm For Generating Synthetic CT Images From Magnetic Resonance Imaging Data Sets for Prostate Cancer Radiation Therapy".  United States.  https://doi.org/10.1016/J.IJROBP.2014.09.015.

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@article{osti_22423837,

  title        = {Implementation of a Novel Algorithm For Generating Synthetic CT Images From Magnetic Resonance Imaging Data Sets for Prostate Cancer Radiation Therapy},

  author       = {Kim, Joshua and Glide-Hurst, Carri and Doemer, Anthony and Wen, Ning and Movsas, Benjamin and Chetty, Indrin J.},

  abstractNote = {Purpose: To describe and evaluate a method for generating synthetic computed tomography (synCT) images from magnetic resonance simulation (MR-SIM) data for accurate digitally reconstructed radiograph (DRR) generation and dose calculations in prostate cancer radiation therapy. Methods and Materials: A retrospective evaluation was performed in 9 prostate cancer patients who had undergone MR-SIM in addition to CT simulation (CT-SIM). MR-SIM data were used to generate synCT images by using a novel, voxel-based weighted summation approach. A subset of patients was used for weight optimization, and the number of patients to use during optimization was determined. Hounsfield unit (HU) differences between CT-SIM and synCT images were analyzed via mean absolute error (MAE). Original, CT-based treatment plans were mapped onto synCTs. DRRs were generated, and agreement between CT and synCT-generated DRRs was evaluated via Dice similarity coefficient (DSC). Dose was recalculated, and dose-volume metrics and gamma analysis were used to evaluate resulting treatment plans. Results: Full field-of-view synCT MAE across all patients was 74.3 ± 10.9 HU with differences from CTs of 2.0 ± 8.1 HU and 11.9 ± 46.7 HU for soft tissue structures (prostate, bladder, and rectum) and femoral bones, respectively. Calculated DSCs for anterior-posterior and lateral DRRs were 0.90 ± 0.04 and 0.92 ± 0.05, respectively. Differences in D99%, mean dose, and maximum dose to the clinical target volume from CT-SIM dose calculations were 0.75% ± 0.35%, 0.63% ± 0.34%, and 0.54% ± 0.33%, respectively, for synCT-generated plans. Gamma analysis (2%/2 mm dose difference/distance to agreement) revealed pass rates of 99.9% ± 0.1% (range, 99.7%-100%). Conclusion: Generated synCTs enabled accurate DRR generation and dose computation for prostate MR-only simulation. Dose recalculated on synCTs agreed well with original planning distributions. Further validation using a larger patient cohort is warranted.},

  doi          = {10.1016/J.IJROBP.2014.09.015},

  url          = {https://www.osti.gov/biblio/22423837},
  journal      = {International Journal of Radiation Oncology, Biology and Physics},

  issn         = {0360-3016},

  number       = 1,

  volume       = 91,

  place        = {United States},

  year         = {Thu Jan 01 00:00:00 EST 2015},

  month        = {Thu Jan 01 00:00:00 EST 2015}

}

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