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Title: SU-F-J-19: Robust Region-Of-Interest (ROI) for Consistent Registration On Deteriorated Surface Images

Abstract

Purpose: For African-American patients receiving breast radiotherapy with a bolus, skin darkening can affect the surface visualization when using optical imaging for daily positioning and gating at deep-inspiration breath holds (DIBH). Our goal is to identify a region-of-interest (ROI) that is robust against deteriorating surface image quality due to skin darkening. Methods: We study four patients whose post-mastectomy surfaces are imaged daily with AlignRT (VisionRT, UK) for DIBH radiotherapy and whose surface image quality is degraded toward the end of treatment. To simulate the effects of skin darkening, surfaces from the first ten fractions of each patient are systematically degraded by 25–35%, 40–50% and 65–75% of the total area of the clinically used ROI-ipsilateral-chestwall. The degraded surfaces are registered to the reference surface in six degrees-of-freedom. To identify a robust ROI, three additional reference ROIs — ROI-chest+abdomen, ROI-bilateral-chest and ROI-extended-ipsilateral-chestwall are created and registered to the degraded surfaces. Differences in registration using these ROIs are compared to that using ROI-ipsilateral-chestwall. Results: For three patients, the deviations in the registrations to ROI-ipsilateral-chestwall are > 2.0, 3.1 and 7.9mm on average for 25–35%, 40–50% and 65–75% degraded surfaces, respectively. Rotational deviations reach 11.1° in pitch. For the last patient, registration is consistentmore » to within 2.6mm even on the 65–75% degraded surfaces, possibly because the surface topography has more distinct features. For ROI-bilateral-chest and ROI-extended-ipsilateral-chest registrations deviate in a similar pattern. However, registration on ROI-chest+abdomen is robust to deteriorating image qualities to within 4.2mm for all four patients. Conclusion: Registration deviations using ROI-ipsilateral-chestwall can reach 9.8mm on the 40–50% degraded surfaces. Caution is required when using AlignRT for patients experiencing skin darkening since the accuracy of AlignRT registration deteriorates. To avoid this inaccuracy, we recommend use of ROI-chest+abdomen, on which registration is consistent within 4.2mm even for highly degraded surfaces.« less

Authors:
; ; ; ;  [1]
  1. The Department of Radiation and Cellular Oncology, The University of Chicago Medicine, Chicago, IL (United States)
Publication Date:
OSTI Identifier:
22632154
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 61 RADIATION PROTECTION AND DOSIMETRY; ACCURACY; BIOMEDICAL RADIOGRAPHY; CHEST; IMAGES; MAMMARY GLANDS; PATIENTS; RADIOTHERAPY; SKIN

Citation Formats

Kang, H, Malin, M, Chmura, S, Hasan, Y, and Al-Hallaq, H. SU-F-J-19: Robust Region-Of-Interest (ROI) for Consistent Registration On Deteriorated Surface Images. United States: N. p., 2016. Web. doi:10.1118/1.4955927.
Kang, H, Malin, M, Chmura, S, Hasan, Y, & Al-Hallaq, H. SU-F-J-19: Robust Region-Of-Interest (ROI) for Consistent Registration On Deteriorated Surface Images. United States. doi:10.1118/1.4955927.
Kang, H, Malin, M, Chmura, S, Hasan, Y, and Al-Hallaq, H. 2016. "SU-F-J-19: Robust Region-Of-Interest (ROI) for Consistent Registration On Deteriorated Surface Images". United States. doi:10.1118/1.4955927.
@article{osti_22632154,
title = {SU-F-J-19: Robust Region-Of-Interest (ROI) for Consistent Registration On Deteriorated Surface Images},
author = {Kang, H and Malin, M and Chmura, S and Hasan, Y and Al-Hallaq, H},
abstractNote = {Purpose: For African-American patients receiving breast radiotherapy with a bolus, skin darkening can affect the surface visualization when using optical imaging for daily positioning and gating at deep-inspiration breath holds (DIBH). Our goal is to identify a region-of-interest (ROI) that is robust against deteriorating surface image quality due to skin darkening. Methods: We study four patients whose post-mastectomy surfaces are imaged daily with AlignRT (VisionRT, UK) for DIBH radiotherapy and whose surface image quality is degraded toward the end of treatment. To simulate the effects of skin darkening, surfaces from the first ten fractions of each patient are systematically degraded by 25–35%, 40–50% and 65–75% of the total area of the clinically used ROI-ipsilateral-chestwall. The degraded surfaces are registered to the reference surface in six degrees-of-freedom. To identify a robust ROI, three additional reference ROIs — ROI-chest+abdomen, ROI-bilateral-chest and ROI-extended-ipsilateral-chestwall are created and registered to the degraded surfaces. Differences in registration using these ROIs are compared to that using ROI-ipsilateral-chestwall. Results: For three patients, the deviations in the registrations to ROI-ipsilateral-chestwall are > 2.0, 3.1 and 7.9mm on average for 25–35%, 40–50% and 65–75% degraded surfaces, respectively. Rotational deviations reach 11.1° in pitch. For the last patient, registration is consistent to within 2.6mm even on the 65–75% degraded surfaces, possibly because the surface topography has more distinct features. For ROI-bilateral-chest and ROI-extended-ipsilateral-chest registrations deviate in a similar pattern. However, registration on ROI-chest+abdomen is robust to deteriorating image qualities to within 4.2mm for all four patients. Conclusion: Registration deviations using ROI-ipsilateral-chestwall can reach 9.8mm on the 40–50% degraded surfaces. Caution is required when using AlignRT for patients experiencing skin darkening since the accuracy of AlignRT registration deteriorates. To avoid this inaccuracy, we recommend use of ROI-chest+abdomen, on which registration is consistent within 4.2mm even for highly degraded surfaces.},
doi = {10.1118/1.4955927},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = 2016,
month = 6
}
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