title: Automatic tracking of arbitrarily shaped implanted markers in kilovoltage projection images: a feasibility study.
abstract: OBJECTIVE
  Certain types of commonly used fiducial markers take on irregular shapes upon implantation in soft tissue. This poses a challenge for methods that assume a predefined shape of markers when automatically tracking such markers in kilovoltage (kV) radiographs. The authors have developed a method of automatically tracking regularly and irregularly shaped markers using kV projection images and assessed its potential for detecting intrafractional target motion during rotational treatment.
  
  
  METHODS
  Template-based matching used a normalized cross-correlation with simplex minimization. Templates were created from computed tomography (CT) images for phantom studies and from end-expiration breath-hold planning CT for patient studies. The kV images were processed using a Sobel filter to enhance marker visibility. To correct for changes in intermarker relative positions between simulation and treatment that can introduce errors in automatic matching, marker offsets in three dimensions were manually determined from an approximately orthogonal pair of kV images. Two studies in anthropomorphic phantom were carried out, one using a gold cylindrical marker representing regular shape, another using a Visicoil marker representing irregular shape. Automatic matching of templates to cone beam CT (CBCT) projection images was performed to known marker positions in phantom. In patient data, automatic matching was compared to manual matching as an approximate ground truth. Positional discrepancy between automatic and manual matching of less than 2 mm was assumed as the criterion for successful tracking. Tracking success rates were examined in kV projection images from 22 CBCT scans of four pancreas, six gastroesophageal junction, and one lung cancer patients. Each patient had at least one irregularly shaped radiopaque marker implanted in or near the tumor. In addition, automatic tracking was tested in intrafraction kV images of three lung cancer patients with irregularly shaped markers during 11 volumetric modulated arc treatments. Purpose-built software developed at our institution was used to create marker templates and track the markers embedded in kV images.
  
  
  RESULTS
  Phantom studies showed mean ± standard deviation measurement uncertainty of automatic registration to be 0.14 ± 0.07 mm and 0.17 ± 0.08 mm for Visicoil and gold cylindrical markers, respectively. The mean success rate of automatic tracking with CBCT projections (11 frames per second, fps) of pancreas, gastroesophageal junction, and lung cancer patients was 100%, 99.1% (range 98%-100%), and 100%, respectively. With intrafraction images (approx. 0.2 fps) of lung cancer patients, the success rate was 98.2% (range 97%-100%), and 94.3% (range 93%-97%) using templates from 1.25 mm and 2.5 mm slice spacing CT scans, respectively. Correction of intermarker relative position was found to improve the success rate in two out of eight patients analyzed.
  
  
  CONCLUSIONS
  The proposed method can track arbitrary marker shapes in kV images using templates generated from a breath-hold CT acquired at simulation. The studies indicate its feasibility for tracking tumor motion during rotational treatment. Investigation of the causes of misregistration suggests that its rate of incidence can be reduced with higher frequency of image acquisition, templates made from smaller CT slice spacing, and correction of changes in intermarker relative positions when they occur.
authors.affiliation: Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York 10065.
authors.forename: Rajesh
authors.initials: R
authors.lastname: Regmi
authors.affiliation: Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York 10065.
authors.forename: D Michael
authors.initials: DM
authors.lastname: Lovelock
authors.affiliation: Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York 10065.
authors.forename: Margie
authors.initials: M
authors.lastname: Hunt
authors.affiliation: Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York 10065.
authors.forename: Pengpeng
authors.initials: P
authors.lastname: Zhang
authors.affiliation: Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York 10065.
authors.forename: Hai
authors.initials: H
authors.lastname: Pham
authors.affiliation: Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York 10065.
authors.forename: Jianping
authors.initials: J
authors.lastname: Xiong
authors.affiliation: Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York 10065.
authors.forename: Ellen D
authors.initials: ED
authors.lastname: Yorke
authors.affiliation: Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, New York 10065.
authors.forename: Karyn A
authors.initials: KA
authors.lastname: Goodman
authors.affiliation: Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, New York 10065.
authors.forename: Andreas
authors.initials: A
authors.lastname: Rimner
authors.affiliation: Ginzton Technology Center, Varian Medical Systems, Palo Alto, California 94304.
authors.forename: Hassan
authors.initials: H
authors.lastname: Mostafavi
authors.affiliation: Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York 10065.
authors.forename: Gig S
authors.initials: GS
authors.lastname: Mageras
mesh_terms: D000465:Algorithms; D062485:Breath Holding; D003198:Computer Simulation; D054893:Cone-Beam Computed Tomography / Q000295:instrumentation* / Q000379:methods*; D004938:Esophageal Neoplasms / Q000000981:diagnostic imaging; D004943:Esophagogastric Junction / Q000000981:diagnostic imaging; D005240:Feasibility Studies; D057918:Fiducial Markers; D006046:Gold; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging; D008954:Models, Biological; D009038:Motion; D010190:Pancreatic Neoplasms / Q000000981:diagnostic imaging; D010363:Pattern Recognition, Automated / Q000379:methods*; D019047:Phantoms, Imaging; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000295:instrumentation* / Q000379:methods*; D012399:Rotation; D012984:Software; D013274:Stomach Neoplasms / Q000000981:diagnostic imaging
chemical_list: D006046:Gold