Evidence map›Paper›PMID 22770690›Full record

ArticleMagnetic resonance imaging2012

3D Slicer as an image computing platform for the Quantitative Imaging Network.

Andriy Fedorov, Reinhard Beichel, Jayashree Kalpathy-Cramer, Julien Finet, Jean-Christophe Fillion-Robin, Sonia Pujol, Christian Bauer, Dominique Jennings, Fiona Fennessy, Milan Sonka and 5 more

3 registry-linked trialsAbstract read
In one paragraph

Article in Magnetic resonance imaging, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 3 registered trials, which are not on this map. Cited by 4,346 papers.

0numbers the graph read from it
0cells of the map it votes in
4,346citing 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.

NCT03831997 unknown statusnot on this mapstarted 2019, after this paper: background citation

The Effect of Dextrose 5% in 0.225% Sodium Chloride (D5 1/4NS) on Postoperative Chronic Subdural Hematoma Size and Recurrence Rate

TypeobservationalSponsorCarilion ClinicRan2019 to 2022Enrolled35ConditionsChronic Subdural HematomaArmsDextrose 5% W/ Sodium Chloride 0.225%
NCT04748016 naunknown statusnot on this mapstarted 2020, after this paper: background citation

Sterilised 3D-PRINTed Bone Models in Addition to Conventional CT Imaging for Operative Visualisation in Complex Intra-articular Fracture Repair - A Multi-centre, Double-blind Randomised Controlled Trial

TypeinterventionalSponsorThe University of Hong KongRan2020 to 2023Enrolled80ConditionsDistal Humerus Fracture, Distal Femur Fracture, Distal Tibia Fracture, Proximal Humeral FractureArms3D printed (3DP) bone models + CT imaging, CT imaging
NCT07783126 not yet recruitingnot on this mapstarted 2026, after this paper: background citation

Deep-learning Prediction of Abdominal Aortic Aneurysm Enlargement in Type II Endoleak After EVAR: Development and Multicenter Validation of an End-to-end Deep-learning Model (the RADAR Study)

TypeobservationalSponsorEnte Ospedaliero Cantonale, BellinzonaRan2026 to 2028Enrolled1,250ConditionsType II Endoleak, Abdominal Aortic Aneurysm EnlargementArmsArtificial intelligence model analyzing preoperative CT angiography
3 · Its place in the literature

Who cites it

4,346 citing papers in PubMed.

  1. Trial
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  7. The Effect of Pessary Insertion on Pelvic Anatomy: A Prospective Observational Study Using Upright MRI.BJOG : an international journal of obstetrics and gynaecology · 2026
    Observational
  8. Article
  9. Article
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  19. Quantitative intraoperative assessment of fronto-orbital advancement and remodelling in craniosynostosis.International journal of computer assisted radiology and surgery · 2026
    Article
  20. Article

4,286 more citing papers are in PubMed but not listed here.

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

15 authors.

Andriy FedorovBrigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA. fedorov@bwh.harvard.edu
Reinhard Beichel
Jayashree Kalpathy-Cramer
Julien Finet
Jean-Christophe Fillion-Robin
Sonia Pujol
Christian Bauer
Dominique Jennings
Fiona Fennessy
Milan Sonka
John Buatti
Stephen Aylward
James V Miller
Steve Pieper
Ron Kikinis

Funding

Washington University ConsoritumU54EB005149 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI JOHNSON, HANS · 2004 to 2013
$39.3M
WHITE MATTER ARCHITECTURE FROM DT-MRIP41RR013218 · NCRR · BRIGHAM AND WOMEN'S HOSPITAL · PI KIKINIS, RON · 1998 to 2011
$30.6M
Image Guided Therapy Center - Ultrasound-based sensor system for the monitoring of COVID-19 patientsP41EB015898 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI TEMPANY, CLARE M · 2012 to 2021
$18.9M
IMAGE GUIDED THERAPY CENTERP41RR019703 · NCRR · BRIGHAM AND WOMEN'S HOSPITAL · PI JOLESZ, FERENC A · 2010 to 2011
$8.6M
Enabling Technologies for MRI-Guided Prostate InterventionsR01CA111288 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI TEMPANY, CLARE M · 2006 to 2015
$7.8M
Graph-Based Medical Image Segmentation in 3D and 4DR01EB004640 · NIBIB · UNIVERSITY OF IOWA · PI BUATTI, JOHN M, SONKA, MILAN · 2006 to 2022
$6.1M
Quantitative Imaging to Assess Response in Cancer Therapy TrialsU01CA140206 · NCI · UNIVERSITY OF IOWA · PI BUATTI, JOHN M, CASAVANT, THOMAS L. · 2010 to 2019
$5.8M
Quantitative MRI of Glioblastoma ResponseU01CA154601 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI KALPATHY-CRAMER, JAYASHREE · 2011 to 2016
$3.4M
Shutter-Speed Model DCE-MRI for Assessment of Response to Cancer TherapyU01CA154602 · NCI · OREGON HEALTH & SCIENCE UNIVERSITY · PI HUANG, WEI, RYAN, CHRISTOPHER WALTER · 2011 to 2015
$2.9M
Quantitiative MRI of prostate cancer as a biomarker and guide for treatmentU01CA151261 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI FENNESSY, FIONA · 2010 to 2014
$1.8M
Clinical Image Retrieval: User needs assessment toolbox development & evaluationR00LM009889 · NLM · MASSACHUSETTS GENERAL HOSPITAL · PI KALPATHY-CRAMER, JAYASHREE · 2011 to 2013
$690k
NCI NIH HHS 1R01CA111288NCI NIH HHS 1U01CA154601-01NCI NIH HHS R01 CA111288NCI NIH HHS U01 CA140206NCI NIH HHS U01-CA140206NCI NIH HHS U01 CA151261NCI NIH HHS U01CA151261NCI NIH HHS U01 CA154601NCI NIH HHS U01 CA154602NCRR NIH HHS P41 RR013218NCRR NIH HHS P41 RR019703NCRR NIH HHS P41RR13218NIBIB NIH HHS P41 EB015898NIBIB NIH HHS P41EB015898NIBIB NIH HHS R01 EB004640NIBIB NIH HHS U54 EB005149NIBIB NIH HHS U54EB005149NLM NIH HHS 4R00LM009889-03NLM NIH HHS R00 LM009889
6 · The paper itself

Abstract

Quantitative analysis has tremendous but mostly unrealized potential in healthcare to support objective and accurate interpretation of the clinical imaging. In 2008, the National Cancer Institute began building the Quantitative Imaging Network (QIN) initiative with the goal of advancing quantitative imaging in the context of personalized therapy and evaluation of treatment response. Computerized analysis is an important component contributing to reproducibility and efficiency of the quantitative imaging techniques. The success of quantitative imaging is contingent on robust analysis methods and software tools to bring these methods from bench to bedside. 3D Slicer is a free open-source software application for medical image computing. As a clinical research tool, 3D Slicer is similar to a radiology workstation that supports versatile visualizations but also provides advanced functionality such as automated segmentation and registration for a variety of application domains. Unlike a typical radiology workstation, 3D Slicer is free and is not tied to specific hardware. As a programming platform, 3D Slicer facilitates translation and evaluation of the new quantitative methods by allowing the biomedical researcher to focus on the implementation of the algorithm and providing abstractions for the common tasks of data communication, visualization and user interface development. Compared to other tools that provide aspects of this functionality, 3D Slicer is fully open source and can be readily extended and redistributed. In addition, 3D Slicer is designed to facilitate the development of new functionality in the form of 3D Slicer extensions. In this paper, we present an overview of 3D Slicer as a platform for prototyping, development and evaluation of image analysis tools for clinical research applications. To illustrate the utility of the platform in the scope of QIN, we discuss several use cases of 3D Slicer by the existing QIN teams, and we elaborate on the future directions that can further facilitate development and validation of imaging biomarkers using 3D Slicer.

Indexed as

AutomationBiomarkersBrain NeoplasmsDatabases, FactualDiagnostic ImagingGlioblastomaHead and Neck NeoplasmsHumansImaging, Three-DimensionalMagnetic Resonance ImagingMaleMedical InformaticsPositron-Emission TomographyProstatic NeoplasmsSoftwareTomography, X-Ray ComputedBiomarkers

Identifiers

PMID22770690
PMCPMC3466397

What OpenQuestion holds

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Read underepoch 390

Registered trials

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.