eISSN: 2081-2841
ISSN: 1689-832X
Journal of Contemporary Brachytherapy
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6/2020
vol. 12
 
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abstract:
Original paper

Automated position and size selection of round applicators for AccuBoost breast brachytherapy

Foster L. West
1, 2
,
Reshma Munbodh
2
,
John C. Patrick
2
,
Mark J. Rivard
2
,
Sean A. Roles
1, 2
,
Ziad H. Saleh
2

1.
Department of Physics, University of Rhode Island, Kingston RI, USA
2.
Department of Radiation Oncology, Rhode Island Hospital, Brown University, Providence RI, USA
J Contemp Brachytherapy 2020; 12, 6: 586–592
Online publish date: 2020/12/18
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Purpose
AccuBoost is a complex non-invasive brachytherapy procedure for breast treatment. This technique requires a radiation oncologist to manually select applicator grid position and size by overlaying transparencies over a mammographic image to encompass surgical clips and resected tumor bed. An algorithm was developed in MATLAB™ to automate the selection of round applicators based on surgical clip position.

Material and methods
A total of 42 mammograms belonging to 10 patients were retrospectively analyzed. Images were pre-processed by masking imprinted localization grid and regions around the grid. A threshold was applied to isolate high-intensity pixels and generate a binary image. A set of morphological operations including region dilation, filling, clearing border structures, and erosion were performed to segment the different regions. A support vector machine classification model was trained to categorize segmented regions as either surgical clips or miscellaneous objects based on different region properties (area, perimeter, eccentricity, circularity, minor axis length, and intensity-derived quantities). Applicator center position was determined by calculating the centroid of detected clips. Size of the applicator was determined with the smallest circle that encompassed all clips with an isotropic 1.0 cm margin.

Results
The clip identification model classified 946 regions, with a sensitivity of 96.6% and a specificity of 98.2%. Applicator position was correctly predicted for 20 of 42 fractions and was within 0.5 cm of physician-selected position for 33 of 42 fractions. Applicator size was correctly predicted for 25 out of 42 fractions.

Conclusions
The proposed algorithm provided a method to quantitatively determine applicator position and size for AccuBoost treatments, and may serve as a tool for independent verifications. The discrepancy between physician-selected and algorithm-predicted determinations of applicator position and size suggests that the methodology may be further improved by considering radiomic features of breast tissue in addition to clip position.

keywords:

non-invasive image-guided breast brachytherapy, AccuBoost, support vector machine

 
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