Literature DB >> 15789594

Use and uncertainties of mutual information for computed tomography/ magnetic resonance (CT/MR) registration post permanent implant of the prostate.

Peter L Roberson1, P William McLaughlin, Vrinda Narayana, Sara Troyer, George V Hixson, Marc L Kessler.   

Abstract

Post-implant dosimetric analysis for permanent implant of the prostate benefits from the use of a computed tomography (CT) dataset for optimal identification of the radioactive source (seed) positions and a magnetic resonance (MR) dataset for optimal description of the target and normal tissue volumes. The CT/MR registration process should be fast and sufficiently accurate to yield a reliable dosimetric analysis. Since critical normal tissues typically reside in dose gradient regions, small shifts in the dose distribution could impact the prediction of complication or complication severity. Standard procedures include the use of the seed distribution as fiducial markers (seed match), a time consuming process that relies on the proper identification of signals due to the same seed on both datasets. Mutual information (MI) is more efficient because it uses image data requiring minimal preparation effort. A comparison of MI registration and seed-match registration was performed for twelve patients. MI was applied to a volume limited to the prostate and surrounding structures, excluding most of the pelvic bone structures (margins around the prostate gland were approximately 2 cm right-left, approximately 1 cm anterior-posterior, and approximately 2 cm superior-inferior). Seeds were identified on a 2 mm slice CT dataset using an automatic seed identification procedure on reconstructed three-dimensional data. Seed positions on the 3 mm slice thickness T2 MR data set were identified using a point-and-click method on each image. Seed images were identified on more than one MR slice, and the results used to determine average seed coordinates for MR images and matched seed pairs between CT and MR images. On average, 42% (19%-64%) of the seeds (19-54 seeds) were identified and matched to their CT counterparts. A least-squares method applied to the CT and MR seed coordinates was used to produce the optimum seed-match registration. MI registration and seed match registration angle differences averaged 0.5 degrees, which was not significantly different from zero. Translation differences averaged 0.6 (1.2 standard deviation) mm right-left, -0.5(1.5) mm posterior-anterior, and -1.2(2.0) mm inferior-superior. Registration error estimates were approximately 2 mm for both the MI and seed-match methods. The observed standard deviations in the offset values were consistent with propagation of error. Registration methods as applied here using mutual information and seed matching are consistent, except for a small systematic difference in the inferior-superior axis for a minority of cases (approximately 15%). Cases registered with mutual information and with bony anatomy misregistration of greater than approximately 5 mm should be evaluated for rescan or seed-match registration. The improvement in efficiency of use for the MI registration method is substantial, approximately 30 min compared to several hours using seed match registration.

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Year:  2005        PMID: 15789594     DOI: 10.1118/1.1851920

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


  37 in total

1.  MR image-based synthetic CT for IMRT prostate treatment planning and CBCT image-guided localization.

Authors:  Shupeng Chen; Hong Quan; An Qin; Seonghwan Yee; Di Yan
Journal:  J Appl Clin Med Phys       Date:  2016-05-08       Impact factor: 2.102

2.  Multimodality image registration in the head-and-neck using a deep learning-derived synthetic CT as a bridge.

Authors:  Elizabeth M McKenzie; Anand Santhanam; Dan Ruan; Daniel O'Connor; Minsong Cao; Ke Sheng
Journal:  Med Phys       Date:  2020-01-02       Impact factor: 4.071

Review 3.  Emerging role of MRI in radiation therapy.

Authors:  Hersh Chandarana; Hesheng Wang; R H N Tijssen; Indra J Das
Journal:  J Magn Reson Imaging       Date:  2018-09-08       Impact factor: 4.813

4.  Treatment planning using MRI data: an analysis of the dose calculation accuracy for different treatment regions.

Authors:  Joakim H Jonsson; Magnus G Karlsson; Mikael Karlsson; Tufve Nyholm
Journal:  Radiat Oncol       Date:  2010-06-30       Impact factor: 3.481

5.  Effect of pulse sequence parameter selection on signal strength in positive-contrast MRI markers for MRI-based prostate postimplant assessment.

Authors:  Tze Yee Lim; Rajat J Kudchadker; Jihong Wang; R Jason Stafford; Christopher MacLellan; Arvind Rao; Geoffrey S Ibbott; Steven J Frank
Journal:  Med Phys       Date:  2016-07       Impact factor: 4.071

6.  Penile bulb sparing in prostate cancer radiotherapy : Dose analysis of an in-house MRI system to improve contouring.

Authors:  F Böckelmann; M Hammon; S Lettmaier; R Fietkau; C Bert; F Putz
Journal:  Strahlenther Onkol       Date:  2018-10-12       Impact factor: 3.621

7.  Development of a hybrid magnetic resonance/computed tomography-compatible phantom for magnetic resonance guided radiotherapy.

Authors:  Min-Joo Kim; Seu-Ran Lee; Kyu-Ho Song; Hyeon-Man Baek; Bo-Young Choe; Tae Suk Suh
Journal:  J Radiat Res       Date:  2020-03-23       Impact factor: 2.724

8.  Outcomes After Stereotactic Body Radiotherapy or Radiofrequency Ablation for Hepatocellular Carcinoma.

Authors:  Daniel R Wahl; Matthew H Stenmark; Yebin Tao; Erqi L Pollom; Elaine M Caoili; Theodore S Lawrence; Matthew J Schipper; Mary Feng
Journal:  J Clin Oncol       Date:  2015-11-30       Impact factor: 44.544

9.  Technical Note: Characterization and correction of gradient nonlinearity induced distortion on a 1.0 T open bore MR-SIM.

Authors:  Ryan G Price; Mo Kadbi; Joshua Kim; James Balter; Indrin J Chetty; Carri K Glide-Hurst
Journal:  Med Phys       Date:  2015-10       Impact factor: 4.071

10.  A neurosurgical navigation system based on intraoperative tumour remnant estimation.

Authors:  Jaesung Hong; Yoshihiro Muragaki; Ryoichi Nakamura; Makoto Hashizume; Hiroshi Iseki
Journal:  J Robot Surg       Date:  2007-02-10
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