title: MRI-alone radiation therapy planning for prostate cancer: Automatic fiducial marker detection.
abstract: OBJECTIVE
  The feasibility of radiation therapy treatment planning using substitute computed tomography (sCT) generated from magnetic resonance images (MRIs) has been demonstrated by a number of research groups. One challenge with an MRI-alone workflow is the accurate identification of intraprostatic gold fiducial markers, which are frequently used for prostate localization prior to each dose delivery fraction. This paper investigates a template-matching approach for the detection of these seeds in MRI.
  
  
  METHODS
  Two different gradient echo T1 and T2* weighted MRI sequences were acquired from fifteen prostate cancer patients and evaluated for seed detection. For training, seed templates from manual contours were selected in a spectral clustering manifold learning framework. This aids in clustering "similar" gold fiducial markers together. The marker with the minimum distance to a cluster centroid was selected as the representative template of that cluster during training. During testing, Gaussian mixture modeling followed by a Markovian model was used in automatic detection of the probable candidates. The probable candidates were rigidly registered to the templates identified from spectral clustering, and a similarity metric is computed for ranking and detection.
  
  
  RESULTS
  A fiducial detection accuracy of 95% was obtained compared to manual observations. Expert radiation therapist observers were able to correctly identify all three implanted seeds on 11 of the 15 scans (the proposed method correctly identified all seeds on 10 of the 15).
  
  
  CONCLUSIONS
  An novel automatic framework for gold fiducial marker detection in MRI is proposed and evaluated with detection accuracies comparable to manual detection. When radiation therapists are unable to determine the seed location in MRI, they refer back to the planning CT (only available in the existing clinical framework); similarly, an automatic quality control is built into the automatic software to ensure that all gold seeds are either correctly detected or a warning is raised for further manual intervention.
authors.affiliation: Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio 44106 and CSIRO Health and Biosecurity, The Australian e-Health & Research Centre, Herston, QLD 4029, Australia.
authors.forename: Soumya
authors.initials: S
authors.lastname: Ghose
authors.affiliation: Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio 44106 and CSIRO Health and Biosecurity, The Australian e-Health & Research Centre, Herston, QLD 4029, Australia.
authors.forename: Jhimli
authors.initials: J
authors.lastname: Mitra
authors.affiliation: CSIRO Health and Biosecurity, The Australian e-Health & Research Centre, Herston, QLD 4029, Australia.
authors.forename: David
authors.initials: D
authors.lastname: Rivest-Hénault
authors.affiliation: CSIRO Health and Biosecurity, The Australian e-Health & Research Centre, Herston, QLD 4029, Australia.
authors.forename: Amir
authors.initials: A
authors.lastname: Fazlollahi
authors.affiliation: School of health sciences, The University of Newcastle, Newcastle, NSW 2308, Australia.
authors.forename: Peter
authors.initials: P
authors.lastname: Stanwell
authors.affiliation: Department of Radiation Oncology, Cavalry Mater Newcastle Hospital, Newcastle, NSW 2298, Australia.
authors.forename: Peter
authors.initials: P
authors.lastname: Pichler
authors.affiliation: School of Mathematical and Physical Sciences, The University of Newcastle, Newcastle, NSW 2308, Australia and Department of Radiation Oncology, Cavalry Mater Newcastle Hospital, Newcastle, NSW 2298, Australia.
authors.forename: Jidi
authors.initials: J
authors.lastname: Sun
authors.affiliation: CSIRO Health and Biosecurity, The Australian e-Health & Research Centre, Herston, QLD 4029, Australia.
authors.forename: Jurgen
authors.initials: J
authors.lastname: Fripp
authors.affiliation: School of Mathematical and Physical Sciences, The University of Newcastle, Newcastle, NSW 2308, Australia and Department of Radiation Oncology, Cavalry Mater Newcastle Hospital, Newcastle, NSW 2298, Australia.
authors.forename: Peter B
authors.initials: PB
authors.lastname: Greer
authors.affiliation: CSIRO Health and Biosecurity, The Australian e-Health & Research Centre, Herston, QLD 4029, Australia.
authors.forename: Jason A
authors.initials: JA
authors.lastname: Dowling
mesh_terms: D000368:Aged; D016000:Cluster Analysis; D005240:Feasibility Studies; D057918:Fiducial Markers; D006046:Gold; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000295:instrumentation / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000295:instrumentation / Q000379:methods*; D008297:Male; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods*; D011467:Prostate / Q000000981:diagnostic imaging / Q000528:radiation effects; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging / Q000532:radiotherapy*; D011880:Radiotherapy Planning, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D061089:Radiotherapy, Image-Guided / Q000295:instrumentation / Q000379:methods*; D014057:Tomography, X-Ray Computed / Q000295:instrumentation / Q000379:methods
chemical_list: D006046:Gold