Evidence map›Paper›PMID 33437307›Full record

ArticleJournal of contemporary brachytherapy2020

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

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

Open access · goldAbstract read
In one paragraph

Article in Journal of contemporary brachytherapy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 81% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Foster L WestDepartment of Physics, University of Rhode Island, Kingston RI, USA.
Reshma MunbodhDepartment of Radiation Oncology, Rhode Island Hospital, Brown University, Providence RI, USA.
John C PatrickDepartment of Radiation Oncology, Rhode Island Hospital, Brown University, Providence RI, USA.
Mark J RivardDepartment of Radiation Oncology, Rhode Island Hospital, Brown University, Providence RI, USA.
Sean A RolesDepartment of Physics, University of Rhode Island, Kingston RI, USA.
Ziad H SalehDepartment of Radiation Oncology, Rhode Island Hospital, Brown University, Providence RI, USA.
Brown University · USProvidence College · USRhode Island Hospital · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeAccuBoost 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

methodsA 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.

resultsThe 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.

conclusionsThe 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.

Indexed as

AccuBoostnon-invasive image-guided breast brachytherapysupport vector machine

Identifiers

PMID33437307
PMCPMC7787202
OpenAlexW3112566800

What OpenQuestion holds

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LicenceCC BY-NC-SA
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.