Evidence map›Paper›PMID 24726701›Full record

ArticleMedical dosimetry : official journal of the American Association of Medical Dosimetrists2014

Segmentation precision of abdominal anatomy for MRI-based radiotherapy.

Camille E Noel, Fan Zhu, Andrew Y Lee, Hu Yanle, Parag J Parikh

Abstract read
In one paragraph

Article in Medical dosimetry : official journal of the American Association of Medical Dosimetrists, 2014. 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
–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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

5 authors.

Camille E NoelDepartment of Radiation Oncology, Washington University School of Medicine, St. Louis, MO.
Fan ZhuDepartment of Radiation Oncology, Washington University School of Medicine, St. Louis, MO.
Andrew Y LeeDepartment of Radiation Oncology, Washington University School of Medicine, St. Louis, MO.
Hu YanleDepartment of Radiation Oncology, Washington University School of Medicine, St. Louis, MO.
Parag J ParikhDepartment of Radiation Oncology, Washington University School of Medicine, St. Louis, MO. Electronic address: pparikh@radonc.wustl.edu.

Funding

Washington University Institute of Clinical and Translational SciencesUL1TR000448 · NCATS · WASHINGTON UNIVERSITY · PI EVANOFF, BRADLEY A · 2012 to 2016
$41.4M
Washington University Institute of Clinical and Translational SciencesTL1TR000449 · NCATS · WASHINGTON UNIVERSITY · PI EVANOFF, BRADLEY A · 2012 to 2016
$2.5M
NCATS NIH HHS TL1 TR000449NCATS NIH HHS TL1TR000449NCATS NIH HHS UL1 TR000448NCATS NIH HHS UL1TR000448
6 · The paper itself

Abstract

The limited soft tissue visualization provided by computed tomography, the standard imaging modality for radiotherapy treatment planning and daily localization, has motivated studies on the use of magnetic resonance imaging (MRI) for better characterization of treatment sites, such as the prostate and head and neck. However, no studies have been conducted on MRI-based segmentation for the abdomen, a site that could greatly benefit from enhanced soft tissue targeting. We investigated the interobserver and intraobserver precision in segmentation of abdominal organs on MR images for treatment planning and localization. Manual segmentation of 8 abdominal organs was performed by 3 independent observers on MR images acquired from 14 healthy subjects. Observers repeated segmentation 4 separate times for each image set. Interobserver and intraobserver contouring precision was assessed by computing 3-dimensional overlap (Dice coefficient [DC]) and distance to agreement (Hausdorff distance [HD]) of segmented organs. The mean and standard deviation of intraobserver and interobserver DC and HD values were DC(intraobserver) = 0.89 ± 0.12, HD(intraobserver) = 3.6mm ± 1.5, DC(interobserver) = 0.89 ± 0.15, and HD(interobserver) = 3.2mm ± 1.4. Overall, metrics indicated good interobserver/intraobserver precision (mean DC > 0.7, mean HD < 4mm). Results suggest that MRI offers good segmentation precision for abdominal sites. These findings support the utility of MRI for abdominal planning and localization, as emerging MRI technologies, techniques, and onboard imaging devices are beginning to enable MRI-based radiotherapy.

Indexed as

Magnetic Resonance ImagingRadiotherapy Planning, Computer-AssistedAbdomenAdultFemaleHumansMaleObserver VariationAbdomenIntraobserver interobserver contouring precisionMagnetic resonance imagingTreatment planning

Identifiers

PMID24726701
PMCPMC4211895

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Registered trials

None linked

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.