Literature DB >> 22047394

Automated intraoperative calibration for prostate cancer brachytherapy.

Thomas Kuiran Chen1, Tamas Heffter, Andras Lasso, Csaba Pinter, Purang Abolmaesumi, E Clif Burdette, Gabor Fichtinger.   

Abstract

PURPOSE: Prostate cancer brachytherapy relies on an accurate spatial registration between the implant needles and the TRUS image, called "calibration". The authors propose a new device and a fast, automatic method to calibrate the brachytherapy system in the operating room, with instant error feedback.
METHODS: A device was CAD-designed and precision-engineered, which mechanically couples a calibration phantom with an exact replica of the standard brachytherapy template. From real-time TRUS images acquired from the calibration device and processed by the calibration system, the coordinate transformation between the brachytherapy template and the TRUS images was computed automatically. The system instantly generated a report of the target reconstruction accuracy based on the current calibration outcome.
RESULTS: Four types of validation tests were conducted. First, 50 independent, real-time calibration trials yielded an average of 0.57 ± 0.13 mm line reconstruction error (LRE) relative to ground truth. Second, the averaged LRE was 0.37 ± 0.25 mm relative to ground truth in tests with six different commercial TRUS scanners operating at similar imaging settings. Furthermore, testing with five different commercial stepper systems yielded an average of 0.29 ± 0.16 mm LRE relative to ground truth. Finally, the system achieved an average of 0.56 ± 0.27 mm target registration error (TRE) relative to ground truth in needle insertion tests through the template in a water tank.
CONCLUSIONS: The proposed automatic, intraoperative calibration system for prostate cancer brachytherapy has achieved high accuracy, precision, and robustness.

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Year:  2011        PMID: 22047394     DOI: 10.1118/1.3651690

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  2 in total

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Authors:  Chong Huang; Yu Lin; Lian He; Daniel Irwin; Margaret M Szabunio; Guoqiang Yu
Journal:  Appl Opt       Date:  2015-10-10       Impact factor: 1.980

2.  Stereoscopic augmented reality for laparoscopic surgery.

Authors:  Xin Kang; Mahdi Azizian; Emmanuel Wilson; Kyle Wu; Aaron D Martin; Timothy D Kane; Craig A Peters; Kevin Cleary; Raj Shekhar
Journal:  Surg Endosc       Date:  2014-02-01       Impact factor: 4.584

  2 in total

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