Construction of patient‐specific computational models for organ dose estimation in radiological imaging. Issue 5 (22nd March 2019)
- Record Type:
- Journal Article
- Title:
- Construction of patient‐specific computational models for organ dose estimation in radiological imaging. Issue 5 (22nd March 2019)
- Main Title:
- Construction of patient‐specific computational models for organ dose estimation in radiological imaging
- Authors:
- Xie, Tianwu
Akhavanallaf, Azadeh
Zaidi, Habib - Abstract:
- Abstract : Purpose: Diagnostic imaging procedures require optimization depending on the medical task at hand, the apparatus being used, and patient physical and anatomical characteristics. The assessment of the radiation dose and associated risks plays a key role in safety and quality management for radiation protection purposes. In this work, we aim at developing a methodology for personalized organ‐level dose assessment in x‐ray computed tomography (CT) imaging. Methods: Regional voxel models representing reference patient‐specific computational phantoms were generated through image segmentation of CT images for four patients. The best‐fitting anthropomorphic phantoms were selected from a previously developed comprehensive phantom library according to patient's anthropometric parameters, then registered to the anatomical masks (skeleton, lung, and body contour) of patients to produce a patient‐specific whole‐body phantom. Well‐established image registration metrics including Jaccard's coefficients for each organ, organ mass, body perimeter, organ‐surface distance, and effective diameter are compared between the reference patient model, registered model, and anchor phantoms. A previously validated Monte Carlo code is utilized to calculate the absorbed dose in target organs along with the effective dose delivered to patients. The calculated absorbed doses from the reference patient models are then compared with the produced personalized model, anchor phantom, and thoseAbstract : Purpose: Diagnostic imaging procedures require optimization depending on the medical task at hand, the apparatus being used, and patient physical and anatomical characteristics. The assessment of the radiation dose and associated risks plays a key role in safety and quality management for radiation protection purposes. In this work, we aim at developing a methodology for personalized organ‐level dose assessment in x‐ray computed tomography (CT) imaging. Methods: Regional voxel models representing reference patient‐specific computational phantoms were generated through image segmentation of CT images for four patients. The best‐fitting anthropomorphic phantoms were selected from a previously developed comprehensive phantom library according to patient's anthropometric parameters, then registered to the anatomical masks (skeleton, lung, and body contour) of patients to produce a patient‐specific whole‐body phantom. Well‐established image registration metrics including Jaccard's coefficients for each organ, organ mass, body perimeter, organ‐surface distance, and effective diameter are compared between the reference patient model, registered model, and anchor phantoms. A previously validated Monte Carlo code is utilized to calculate the absorbed dose in target organs along with the effective dose delivered to patients. The calculated absorbed doses from the reference patient models are then compared with the produced personalized model, anchor phantom, and those reported by commercial dose monitoring systems. Results: The evaluated organ‐surface distance and body effective diameter metrics show a mean absolute difference between patient regional voxel models, serving as reference, and patient‐specific models around 4.4% and 4.5%, respectively. Organ‐level radiation doses of patient‐specific models are in good agreement with those of the corresponding patient regional voxel models with a mean absolute difference of 9.1%. The mean absolute difference of organ doses for the best‐fitting model extracted from the phantom library and Radimetrics™ commercial dose tracking software are 15.5% and 41.1%, respectively. Conclusion: The results suggest that the proposed methodology improves the accuracy of organ‐level dose estimation in CT, especially for extreme cases [high body mass index (BMI) and large skeleton]. Patient‐specific radiation dose calculation and risk assessment can be performed using the proposed methodology for both monitoring of cumulative radiation exposure of patients and epidemiological studies. Further validation using a larger database is warranted. … (more)
- Is Part Of:
- Medical physics. Volume 46:Issue 5(2019)
- Journal:
- Medical physics
- Issue:
- Volume 46:Issue 5(2019)
- Issue Display:
- Volume 46, Issue 5 (2019)
- Year:
- 2019
- Volume:
- 46
- Issue:
- 5
- Issue Sort Value:
- 2019-0046-0005-0000
- Page Start:
- 2403
- Page End:
- 2411
- Publication Date:
- 2019-03-22
- Subjects:
- computational models -- Monte Carlo simulations -- radiation dose -- radiological imaging
Medical physics -- Periodicals
Medical physics
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610.153 - Journal URLs:
- http://scitation.aip.org/content/aapm/journal/medphys ↗
https://aapm.onlinelibrary.wiley.com/journal/24734209 ↗
http://www.aip.org/ ↗ - DOI:
- 10.1002/mp.13471 ↗
- Languages:
- English
- ISSNs:
- 0094-2405
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5531.130000
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British Library HMNTS - ELD Digital store - Ingest File:
- 10242.xml