PURPOSE: A system for digital integration of an open MR scanner (0.23 T, Figure 1) in therapy simulation and 3D radiation treatment planning is described. METHOD: MR images were acquired using the body coil and various positioning and immobilization aids. A gradient echo sequence (TR/TE 320 ms/24 ms) was used to create axial and coronal data sets. Image distortions were measured and corrected using phantom measurements (Figure 2) and specially developed software. RESULTS: Maximal and mean distortions of the MR images could be reduced from 19 mm to 8.2 mm and from 2.7 mm to 0.7 mm, respectively (Figure 3 to 5, Table 1). Coronal MR images were recalculated in fan beam projection for use at the therapy simulator. Tumor and organ contours were transferred from the MR image to the digitally acquired and corrected simulator image using a landmark matching algorithm (Figure 6 and 7). For 3D treatment planning, image fusion of axial MR images with standard CT planning images was performed using a landmark matching algorithm, as well (Figure 8). Representative cases are shown to demonstrate potential applications of the system. CONCLUSION: The described system enables the integration of the imaging information from an open MR system in therapy simulation and 3D treatment planning. The low-field MR scanner is an attractive adjunct for the radio-oncologist because of the open design and the low costs.
PURPOSE: A system for digital integration of an open MR scanner (0.23 T, Figure 1) in therapy simulation and 3D radiation treatment planning is described. METHOD: MR images were acquired using the body coil and various positioning and immobilization aids. A gradient echo sequence (TR/TE 320 ms/24 ms) was used to create axial and coronal data sets. Image distortions were measured and corrected using phantom measurements (Figure 2) and specially developed software. RESULTS: Maximal and mean distortions of the MR images could be reduced from 19 mm to 8.2 mm and from 2.7 mm to 0.7 mm, respectively (Figure 3 to 5, Table 1). Coronal MR images were recalculated in fan beam projection for use at the therapy simulator. Tumor and organ contours were transferred from the MR image to the digitally acquired and corrected simulator image using a landmark matching algorithm (Figure 6 and 7). For 3D treatment planning, image fusion of axial MR images with standard CT planning images was performed using a landmark matching algorithm, as well (Figure 8). Representative cases are shown to demonstrate potential applications of the system. CONCLUSION: The described system enables the integration of the imaging information from an open MR system in therapy simulation and 3D treatment planning. The low-field MR scanner is an attractive adjunct for the radio-oncologist because of the open design and the low costs.
Authors: M Müller-Schimpfle; G Layer; A Köster; G Brix; B Kimmig; H U Kauczor; M Wannenmacher; W Semmler; G van Kaick Journal: J Comput Assist Tomogr Date: 1992 Jan-Feb Impact factor: 1.826
Authors: F Lohr; O Schramm; P Schraube; G Sroka-Perez; S Seeber; G Schlepple; W Schlegel; M Wannenmacher Journal: Radiother Oncol Date: 1997-11 Impact factor: 6.280
Authors: B A Fraass; D L McShan; R F Diaz; R K Ten Haken; A Aisen; S Gebarski; G Glazer; A S Lichter Journal: Int J Radiat Oncol Biol Phys Date: 1987-12 Impact factor: 7.038
Authors: Carri K Glide-Hurst; Ning Wen; David Hearshen; Joshua Kim; Milan Pantelic; Bo Zhao; Tina Mancell; Kenneth Levin; Benjamin Movsas; Indrin J Chetty; M Salim Siddiqui Journal: J Appl Clin Med Phys Date: 2015-03-08 Impact factor: 2.102