Literature DB >> 33595863

Technical Note: Patient-morphed mesh-type phantoms to support personalized nuclear medicine dosimetry - a proof of concept study.

Jason S Lewis1,2, Adam L Kesner3, Lukas M Carter3, Juan Camilo Ocampo Ramos3, Wesley E Bolch4.   

Abstract

PURPOSE: Current standard practice for clinical radionuclide dosimetry utilizes reference phantoms, where defined organ dimensions represent population averages for a given sex and age. Greater phantom personalization would support more accurate dose estimations and personalized dosimetry. Tailoring phantoms is traditionally accomplished using operator-intensive organ-level segmentation of anatomic images. Modern mesh phantoms provide enhanced anatomical realism, which has motivated their integration within Monte Carlo codes. Here, we present an automatable strategy for generating patient-specific phantoms/dosimetry using intensity-based deformable image registration between mesh reference phantoms and patient CT images. This work demonstrates a proof-of-concept personalized dosimetry workflow, presented in comparison to the manual segmentation approach.
METHODS: A linear attenuation coefficient phantom was generated by resampling the PSRK-Man reference phantom onto a voxel grid and defining organ regions with corresponding Hounsfield unit (HU) reference values. The HU phantom was co-registered with a patient CT scan using Plastimatch B-spline deformable registration. In parallel, major organs were manually contoured to generate a "ground truth" patient-specific phantom for comparisons. Monte Carlo derived S-values, which support nuclear medicine dosimetry, were calculated using both approaches and compared.
RESULTS: Application of the derived B-spline transform to the polygon vertices comprising the PSRK-Man yielded a deformed variant more closely matching the patient's body contour and most organ volumes as-evaluated by Hausdorff distance and Dice metrics. S-values computed for fluorine-18 for the deformed phantom using the Particle and Heavy Ion Transport code System showed improved agreement with those derived from the patient-specific analog.
CONCLUSIONS: Deformable registration techniques can be used to create a personalized phantom and better support patient-specific dosimetry. This method is shown to be easier and faster than manual segmentation. Our study is limited to a proof-of-concept scope, but demonstrates that integration of personalized phantoms into clinical dosimetry workflows can reasonably be achieved when anatomical images (CT) are available.
© 2021 American Association of Physicists in Medicine.

Entities:  

Keywords:  Monte Carlo simulation; deformable registration; mesh phantoms; personalized dosimetry

Mesh:

Year:  2021        PMID: 33595863      PMCID: PMC8058313          DOI: 10.1002/mp.14784

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


  15 in total

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Authors:  Andriy Fedorov; Reinhard Beichel; Jayashree Kalpathy-Cramer; Julien Finet; Jean-Christophe Fillion-Robin; Sonia Pujol; Christian Bauer; Dominique Jennings; Fiona Fennessy; Milan Sonka; John Buatti; Stephen Aylward; James V Miller; Steve Pieper; Ron Kikinis
Journal:  Magn Reson Imaging       Date:  2012-07-06       Impact factor: 2.546

2.  MIRD pamphlet No. 21: a generalized schema for radiopharmaceutical dosimetry--standardization of nomenclature.

Authors:  Wesley E Bolch; Keith F Eckerman; George Sgouros; Stephen R Thomas
Journal:  J Nucl Med       Date:  2009-03       Impact factor: 10.057

3.  Feasibility of reducing differences in estimated doses in nuclear medicine between a patient-specific and a reference phantom.

Authors:  Alexandra Zvereva; Helmut Schlattl; Maria Zankl; Janine Becker; Nina Petoussi-Henss; Yeon Soo Yeom; Chan Hyeong Kim; Christoph Hoeschen; Katia Parodi
Journal:  Phys Med       Date:  2017-06-16       Impact factor: 2.685

4.  Radiation Dose to Patients from Radiopharmaceuticals: a Compendium of Current Information Related to Frequently Used Substances.

Authors:  S Mattsson; L Johansson; S Leide Svegborn; J Liniecki; D Noßke; K Å Riklund; M Stabin; D Taylor; W Bolch; S Carlsson; K Eckerman; A Giussani; L Söderberg; S Valind
Journal:  Ann ICRP       Date:  2015-07

5.  Technical Note: plastimatch mabs, an open source tool for automatic image segmentation.

Authors:  Paolo Zaffino; Patrik Raudaschl; Karl Fritscher; Gregory C Sharp; Maria Francesca Spadea
Journal:  Med Phys       Date:  2016-09       Impact factor: 4.071

6.  PARaDIM: A PHITS-Based Monte Carlo Tool for Internal Dosimetry with Tetrahedral Mesh Computational Phantoms.

Authors:  Lukas M Carter; Troy M Crawford; Tatsuhiko Sato; Takuya Furuta; Chansoo Choi; Chan Hyeong Kim; Justin L Brown; Wesley E Bolch; Pat B Zanzonico; Jason S Lewis
Journal:  J Nucl Med       Date:  2019-06-14       Impact factor: 10.057

7.  Validation of MRI to TRUS registration for high-dose-rate prostate brachytherapy.

Authors:  Eric Poulin; Karim Boudam; Csaba Pinter; Samuel Kadoury; Andras Lasso; Gabor Fichtinger; Cynthia Ménard
Journal:  Brachytherapy       Date:  2018-01-10       Impact factor: 2.362

8.  The Cancer Imaging Archive (TCIA): maintaining and operating a public information repository.

Authors:  Kenneth Clark; Bruce Vendt; Kirk Smith; John Freymann; Justin Kirby; Paul Koppel; Stephen Moore; Stanley Phillips; David Maffitt; Michael Pringle; Lawrence Tarbox; Fred Prior
Journal:  J Digit Imaging       Date:  2013-12       Impact factor: 4.056

9.  Statistical validation of image segmentation quality based on a spatial overlap index.

Authors:  Kelly H Zou; Simon K Warfield; Aditya Bharatha; Clare M C Tempany; Michael R Kaus; Steven J Haker; William M Wells; Ferenc A Jolesz; Ron Kikinis
Journal:  Acad Radiol       Date:  2004-02       Impact factor: 3.173

10.  Metrics for evaluating 3D medical image segmentation: analysis, selection, and tool.

Authors:  Abdel Aziz Taha; Allan Hanbury
Journal:  BMC Med Imaging       Date:  2015-08-12       Impact factor: 1.930

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  1 in total

Review 1.  An update on computational anthropomorphic anatomical models.

Authors:  Azadeh Akhavanallaf; Hadi Fayad; Yazdan Salimi; Antar Aly; Hassan Kharita; Huda Al Naemi; Habib Zaidi
Journal:  Digit Health       Date:  2022-07-11
  1 in total

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