Lauri Koivula1, Mika Kapanen2, Tiina Seppälä3, Juhani Collan3, Jason A Dowling4, Peter B Greer5, Christian Gustafsson6, Adalsteinn Gunnlaugsson7, Lars E Olsson8, Leonard Wee9, Juha Korhonen10. 1. Department of Radiation Oncology, Cancer Center, Helsinki University Central Hospital, Finland; Department of Physics, University of Helsinki, Finland; Medical Imaging and Radiation Therapy, Kymenlaakso Central Hospital, Kymenlaakso Social and Health Services (Carea), Kotka, Finland. Electronic address: lauri.koivula@helsinki.fi. 2. Department of Medical Physics, Medical Imaging Center, Tampere University Hospital, Finland. 3. Department of Radiation Oncology, Cancer Center, Helsinki University Central Hospital, Finland. 4. CSIRO Health and Biosecurity, The Australian e-Health & Research Centre, Herston, Australia. 5. School of Mathematical and Physical Sciences, The University of Newcastle, Australia; Department of Radiation Oncology, Calvary Mater Newcastle Hospital, Australia. 6. Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, Lund, Sweden; Department of Medical Physics, Lund University, Malmö, Sweden. 7. Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, Lund, Sweden. 8. Department of Medical Physics, Lund University, Malmö, Sweden; Department of Translational Sciences, Lund University, Skåne University Hospital, Malmö, Sweden. 9. MAASTRO Clinic, School of Oncology and Developmental Biology, Maastricht University, The Netherlands; Department of Medical Physics, Oncology Services, Vejle Hospital, Denmark. 10. Department of Radiation Oncology, Cancer Center, Helsinki University Central Hospital, Finland; Medical Imaging and Radiation Therapy, Kymenlaakso Central Hospital, Kymenlaakso Social and Health Services (Carea), Kotka, Finland; Department of Radiology, Helsinki University Central Hospital, Finland; Department of Nuclear Medicine, Helsinki University Central Hospital, Finland.
Abstract
BACKGROUND AND PURPOSE: Recent studies have shown that it is possible to conduct entire radiotherapy treatment planning (RTP) workflow using only MR images. This study aims to develop a generalized intensity-based method to generate synthetic CT (sCT) images from standard T2-weighted (T2w) MR images of the pelvis. MATERIALS AND METHODS: This study developed a generalized dual model HU conversion method to convert standard T2w MR image intensity values to synthetic HU values, separately inside and outside of atlas-segmented bone volume contour. The method was developed and evaluated with 20 and 35 prostate cancer patients, respectively. MR images with scanning sequences in clinical use were acquired with four different MR scanners of three vendors. RESULTS: For the generated synthetic CT (sCT) images of the 35 prostate patients, the mean (and maximal) HU differences in soft and bony tissue volumes were 16 ± 6 HUs (34 HUs) and -46 ± 56 HUs (181 HUs), respectively, against the true CT images. The average of the PTV mean dose difference in sCTs compared to those in true CTs was -0.6 ± 0.4% (-1.3%). CONCLUSIONS: The study provides a generalized method for sCT creation from standard T2w images of the pelvis. The method produced clinically acceptable dose calculation results for all the included scanners and MR sequences.
BACKGROUND AND PURPOSE: Recent studies have shown that it is possible to conduct entire radiotherapy treatment planning (RTP) workflow using only MR images. This study aims to develop a generalized intensity-based method to generate synthetic CT (sCT) images from standard T2-weighted (T2w) MR images of the pelvis. MATERIALS AND METHODS: This study developed a generalized dual model HU conversion method to convert standard T2w MR image intensity values to synthetic HU values, separately inside and outside of atlas-segmented bone volume contour. The method was developed and evaluated with 20 and 35 prostate cancerpatients, respectively. MR images with scanning sequences in clinical use were acquired with four different MR scanners of three vendors. RESULTS: For the generated synthetic CT (sCT) images of the 35 prostate patients, the mean (and maximal) HU differences in soft and bony tissue volumes were 16 ± 6 HUs (34 HUs) and -46 ± 56 HUs (181 HUs), respectively, against the true CT images. The average of the PTV mean dose difference in sCTs compared to those in true CTs was -0.6 ± 0.4% (-1.3%). CONCLUSIONS: The study provides a generalized method for sCT creation from standard T2w images of the pelvis. The method produced clinically acceptable dose calculation results for all the included scanners and MR sequences.
Authors: Jae Hyuk Choi; Danny Lee; Laura O'Connor; Stephan Chalup; James S Welsh; Jason Dowling; Peter B Greer Journal: Front Oncol Date: 2019-10-02 Impact factor: 6.244