Evidence map›Paper›PMID 31523238›Full record

ArticleJournal of contemporary brachytherapy2019

Addition of magnetic resonance imaging to real time trans-rectal ultrasound-based treatment planning for prostate implants.

Michael Petronek, Salim Balik, Andrei Purysko, Eric Klein, Jay Ciezki, Allan Wilkinson

Abstract read
In one paragraph

Article in Journal of contemporary brachytherapy, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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.

Michael PetronekDepartment of Radiation Oncology, University of Iowa, Iowa City, Iowa, United States.
Salim BalikDepartment of Radiation Oncology, Cleveland Clinic, Cleveland, Ohio, United States.
Andrei PuryskoDepartment of Diagnostic Radiology, Cleveland Clinic, Cleveland, Ohio, United States.
Eric KleinDepartment of Urology, Cleveland Clinic, Cleveland, Ohio, United States.
Jay CiezkiDepartment of Radiation Oncology, Cleveland Clinic, Cleveland, Ohio, United States.
Allan WilkinsonDepartment of Radiation Oncology, Cleveland Clinic, Cleveland, Ohio, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe greater soft tissue contrast of magnetic resonance imaging (MRI) allows improved accuracy in prostate contouring compared to transrectal ultrasound (TRUS) and helps in identifying specific regions within the prostate. This study attempts to evaluate the potential benefit of MRI-TRUS fusion in treatment planning for more accurate prostate contouring and tumor dose escalation. MATERIAL AND

methods14 patients with previous MRI-guided prostate biopsy and an low-dose-rate (LDR) permanent prostate seed implant have been selected. The prostate and tumor (5 patients) were contoured on the MRI images by a radiologist. The prostate was also contoured on TRUS images during LDR procedure together by a urologist and radiation oncologist. MRI and TRUS images were rigidly fused to compare prostate contours in MRI and TRUS. Prostate was then re-contoured by the radiation oncologist using this fusion. Moreover, V

resultsThe prostate volume was contoured 8 ±10% smaller in TRUS images, compared to MRI images. The mean percent difference in tumor (compared to prostate) V

conclusionsThe MRI-TRUS image fusion is a feasible tool for the visualization of the prostate gland, particularly at the apex and base of the gland. Tumor identification presents the potential for dose escalation using fusion, especially for anteriorly located tumors.

Indexed as

fusionLDRMRIprostateseed implantTRUS

Identifiers

PMID31523238
PMCPMC6737565

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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.