title: A dual model HU conversion from MRI intensity values within and outside of bone segment for MRI-based radiotherapy treatment planning of prostate cancer.
abstract: OBJECTIVE
  The lack of electron density information in magnetic resonance images (MRI) poses a major challenge for MRI-based radiotherapy treatment planning (RTP). In this study the authors convert MRI intensity values into Hounsfield units (HUs) in the male pelvis and thus enable accurate MRI-based RTP for prostate cancer patients with varying tissue anatomy and body fat contents.
  
  
  METHODS
  T1/T2*-weighted MRI intensity values and standard computed tomography (CT) image HUs in the male pelvis were analyzed using image data of 10 prostate cancer patients. The collected data were utilized to generate a dual model HU conversion technique from MRI intensity values of the single image set separately within and outside of contoured pelvic bones. Within the bone segment local MRI intensity values were converted to HUs by applying a second-order polynomial model. This model was tuned for each patient by two patient-specific adjustments: MR signal normalization to correct shifts in absolute intensity level and application of a cutoff value to accurately represent low density bony tissue HUs. For soft tissues, such as fat and muscle, located outside of the bone contours, a threshold-based segmentation method without requirements for any patient-specific adjustments was introduced to convert MRI intensity values into HUs. The dual model HU conversion technique was implemented by constructing pseudo-CT images for 10 other prostate cancer patients. The feasibility of these images for RTP was evaluated by comparing HUs in the generated pseudo-CT images with those in standard CT images, and by determining deviations in MRI-based dose distributions compared to those in CT images with 7-field intensity modulated radiation therapy (IMRT) with the anisotropic analytical algorithm and 360° volumetric-modulated arc therapy (VMAT) with the Voxel Monte Carlo algorithm.
  
  
  RESULTS
  The average HU differences between the constructed pseudo-CT images and standard CT images of each test patient ranged from -2 to 5 HUs and from 22 to 78 HUs in soft and bony tissues, respectively. The average local absolute value differences were 11 HUs in soft tissues and 99 HUs in bones. The planning target volume doses (volumes 95%, 50%, 5%) in the pseudo-CT images were within 0.8% compared to those in CT images in all of the 20 treatment plans. The average deviation was 0.3%. With all the test patients over 94% (IMRT) and 92% (VMAT) of dose points within body (lower than 10% of maximum dose suppressed) passed the 1 mm and 1% 2D gamma index criterion. The statistical tests (t- and F-tests) showed significantly improved (p ≤ 0.05) HU and dose calculation accuracies with the soft tissue conversion method instead of homogeneous representation of these tissues in MRI-based RTP images.
  
  
  CONCLUSIONS
  This study indicates that it is possible to construct high quality pseudo-CT images by converting the intensity values of a single MRI series into HUs in the male pelvis, and to use these images for accurate MRI-based prostate RTP dose calculations.
authors.affiliation: Clinical Research Institute Helsinki University Central Hospital Ltd., POB-700, 00029 HUS, Finland and Department of Oncology, Helsinki University Central Hospital, POB-180, 00029 HUS, Finland.
authors.forename: Juha
authors.initials: J
authors.lastname: Korhonen
authors.affiliation: Clinical Research Institute Helsinki University Central Hospital Ltd., POB-700, 00029 HUS, Finland; Department of Oncology, Helsinki University Central Hospital, POB-180, 00029 HUS, Finland; and Department of Medical Physics, Tampere University Hospital, POB-2000, 33521 Tampere, Finland.
authors.forename: Mika
authors.initials: M
authors.lastname: Kapanen
authors.affiliation: Department of Oncology, Helsinki University Central Hospital, POB-180, 00029 HUS, Finland.
authors.forename: Jani
authors.initials: J
authors.lastname: Keyriläinen
authors.affiliation: Department of Oncology, Helsinki University Central Hospital, POB-180, 00029 HUS, Finland.
authors.forename: Tiina
authors.initials: T
authors.lastname: Seppälä
authors.affiliation: Department of Oncology, Helsinki University Central Hospital, POB-180, 00029 HUS, Finland.
authors.forename: Mikko
authors.initials: M
authors.lastname: Tenhunen
mesh_terms: D001842:Bone and Bones / Q000000981:diagnostic imaging / Q000528:radiation effects*; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging / Q000532:radiotherapy*; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D014057:Tomography, X-Ray Computed