Evidence map›Paper›PMID 34318581›Full record

ArticleJournal of applied clinical medical physics2021

MRI-TRUS registration methodology for TRUS-guided HDR prostate brachytherapy.

Philip McGeachy, Elizabeth Watt, Siraj Husain, Kevin Martell, Pedro Martinez, Summit Sawhney, Kundan Thind

Open access · goldAbstract read
In one paragraph

Article in Journal of applied clinical medical physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 25% 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

3 citing papers in PubMed, 11 citations in OpenAlex.

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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

7 authors at 1 institution in 2 countries.

Philip McGeachyDepartment of Medical Physics, Tom Baker Cancer Centre, Calgary, AB, Canada.ORCID https://orcid.org/0000-0003-2596-2532
Elizabeth WattDepartment of Medical Physics, Tom Baker Cancer Centre, Calgary, AB, Canada.
Siraj HusainDepartment of Oncology, University of Calgary, Calgary, AB, Canada.
Kevin MartellDepartment of Oncology, University of Calgary, Calgary, AB, Canada.
Pedro MartinezDepartment of Medical Physics, Tom Baker Cancer Centre, Calgary, AB, Canada.
Summit SawhneyDepartment of Radiology and Diagnostic Imaging, University of Calgary, Calgary, AB, Canada.
Kundan ThindDepartment of Medical Physics, Tom Baker Cancer Centre, Calgary, AB, Canada.
University of Calgary · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeHigh-dose-rate (HDR) prostate brachytherapy is an established technique for whole-gland treatment. For transrectal ultrasound (TRUS)-guided HDR prostate brachytherapy, image fusion with a magnetic resonance image (MRI) can be performed to make use of its soft-tissue contrast. The MIM treatment planning system has recently introduced image registration specifically for HDR prostate brachytherapy and has incorporated a Predictive Fusion workflow, which allows clinicians to attempt to compensate for differences in patient positioning between imaging modalities. In this study, we investigate the accuracy of the MIM algorithms for MRI-TRUS fusion, including the Predictive Fusion workflow. MATERIALS AND

methodsA radiation oncologist contoured the prostate gland on both TRUS and MRI. Four registration methodologies to fuse the MRI and the TRUS images were considered: rigid registration (RR), contour-based (CB) deformable registration, Predictive Fusion followed by RR (pfRR), and Predictive Fusion followed by CB deformable registration (pfCB). Registrations were compared using the mean distance to agreement and the Dice similarity coefficient for the prostate as contoured on TRUS and the registered MRI prostate contour.

resultsTwenty patients treated with HDR prostate brachytherapy at our center were included in this retrospective evaluation. For the cohort, mean distance to agreement was 2.1 ± 0.8 mm, 0.60 ± 0.08 mm, 2.0 ± 0.5 mm, and 0.59 ± 0.06 mm for RR, CB, pfRR, and pfCB, respectively. Dice similarity coefficients were 0.80 ± 0.05, 0.93 ± 0.02, 0.81 ± 0.03, and 0.93 ± 0.01 for RR, CB, pfRR, and pfCB, respectively. The inclusion of the Predictive Fusion workflow did not significantly improve the quality of the registration.

conclusionsThe CB deformable registration algorithm in the MIM treatment planning system yielded the best geometric registration indices. MIM offers a commercial platform allowing for easier access and integration into clinical departments with the potential to play an integral role in future focal therapy applications for prostate cancer.

Indexed as

BrachytherapyProstatic NeoplasmsHumansMagnetic Resonance ImagingMaleProstateRetrospective StudiesUltrasonographyHDR brachytherapy, MIM, MRI, prostate cancer, registration, TRUS

Identifiers

PMID34318581
PMCPMC8364261
OpenAlexW3186471769

What OpenQuestion holds

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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.