Evidence map›Paper›PMID 30575051›Full record

ArticleMedical physics2019

The VAMPIRE challenge: A multi-institutional validation study of CT ventilation imaging.

John Kipritidis, Bilal A Tahir, Guillaume Cazoulat, Michael S Hofman, Shankar Siva, Jason Callahan, Nicholas Hardcastle, Tokihiro Yamamoto, Gary E Christensen, Joseph M Reinhardt and 18 more

3 registry-linked trialsAbstract readMulticenter StudyValidation Study
In one paragraph

Article in Medical physics, 2019. 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 54 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
54citing papers in PubMed, 1 pooled it
–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.

NCT02308709 nacompletednot on this map

Novel Lung Functional Imaging for Personalized Radiotherapy

TypeinterventionalSponsorUniversity of California, DavisRan2014 to 2021Enrolled34ConditionsLung CancerArmsVentilation image-guided radiotherapy
NCT02528942 nacompletednot on this map

Early Phase Clinical Trial Incorporating Lung Function Imaging Into Radiation Therapy for Lung Cancer Patients

TypeinterventionalSponsorUniversity of Colorado, DenverRan2016 to 2021Enrolled101ConditionsLung Neoplasms, Lung CancerArmsRadiation therapy
NCT02843568 nacompletednot on this map

Improving Pulmonary Function Following Radiation Therapy

TypeinterventionalSponsorUniversity of Wisconsin, MadisonRan2016 to 2023Enrolled122ConditionsNon-Small Cell Lung CancerArmsLaboratory Biomarker Analysis, Standard fractionation, Stereotactic Body Radiation Therapy (SBRT), Four Dimensional Computed Tomographic Imaging (4DCT)
3 · Its place in the literature

Who cites it

54 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  4. Evaluation of variables predicting PFT changes for lung cancer patients treated on a prospective 4DCT-ventilation functional avoidance clinical trial.Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology · 2023
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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

28 authors.

John KipritidisNorthern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, NSW, Australia.
Bilal A TahirAcademic Unit of Clinical Oncology, University of Sheffield, Sheffield, UK.
Guillaume CazoulatThe University of Texas MD Anderson Cancer Center, Department of Imaging Physics, Houston, TX, USA.
Michael S HofmanPeter MacCallum Cancer Centre, Melbourne, Vic., Australia.
Shankar SivaPeter MacCallum Cancer Centre, Melbourne, Vic., Australia.
Jason CallahanPeter MacCallum Cancer Centre, Melbourne, Vic., Australia.
Nicholas HardcastlePeter MacCallum Cancer Centre, Melbourne, Vic., Australia.
Tokihiro YamamotoUniversity of California Davis School of Medicine, Sacramento, CA, USA.
Gary E ChristensenUniversity of Iowa, Iowa City, IA, USA.
Joseph M ReinhardtUniversity of Iowa, Iowa City, IA, USA.
Noriyuki KadoyaTohoku University Graduate School of Medicine, Sendai, Japan.
Taylor J PattonUniversity of Wisconsin-Madison, Madison, WI, USA.
Sarah E GerardUniversity of Iowa, Iowa City, IA, USA.
Isabella DuarteDuke University Medical Center, Durham, NC, USA.
Ben Archibald-HeerenRadiation Oncology Centres, Sydney Adventist Hospital, Sydney, NSW, Australia.
Mikel ByrneRadiation Oncology Centres, Sydney Adventist Hospital, Sydney, NSW, Australia.
Rick SimsAuckland Radiation Oncology, Auckland, New Zealand.
Scott RamsayAuckland Radiation Oncology, Auckland, New Zealand.
Jeremy T BoothNorthern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, NSW, Australia.
Enid EslickNorthern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, NSW, Australia.
Fiona Hegi-JohnsonSydney Medical School, University of Sydney, Sydney, NSW, Australia.
Henry C WoodruffThe D-Lab: Decision Support for Precision Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands.
Rob H IrelandAcademic Unit of Clinical Oncology, University of Sheffield, Sheffield, UK.
Jim M WildAcademic Radiology, POLARIS, University of Sheffield, Sheffield, UK.
Jing CaiDuke University Medical Center, Durham, NC, USA.
John E BayouthUniversity of Wisconsin-Madison, Madison, WI, USA.
Kristy BrockThe University of Texas MD Anderson Cancer Center, Department of Imaging Physics, Houston, TX, USA.
Paul J KeallSydney Medical School, University of Sydney, Sydney, NSW, Australia.

Funding

Viral VectorP30CA086862 · NCI · UNIVERSITY OF IOWA · PI Douglas Robert Spitz · 2000 to 2026
$70.0M
TREATMENT VERIFICATION AND TREATMENT PLAN REFINEMENTP01CA059827 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI KESSLER, MARC LEWIS, LAWRENCE, THEODORE S · 1993 to 2018
$37.9M
Vector Core-Core 2P30DK054759 · NIDDK · UNIVERSITY OF IOWA · PI Alejandro Antonio Pezzulo · 1998 to 2026
$30.5M
Multi-center Structural & Functional Quantitative CT Pulmonary PhenotypingR01HL112986 · NHLBI · UNIVERSITY OF IOWA · PI HOFFMAN, ERIC ALFRED · 2012 to 2016
$4.6M
Predicting Pulmonary Function Change to Improve Radiation Planning and OutcomeR01CA166703 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI BAYOUTH, JOHN · 2013 to 2017
$1.9M
Regional Lung Mechanics by 3D Image RegistrationR01HL079406 · NHLBI · UNIVERSITY OF IOWA · PI REINHARDT, JOSEPH M · 2006 to 2010
$1.6M
British Heart Foundation SP/14/6/31350Cancer Australia Priority-driven Collaborative Cancer Research Scheme APP1060919Cancer Institute NSW Early Career FellowshipDepartment of Health NIHR-RP-R3-12-027Medical Research Council MR/M008894/1National Institute of Health R01HL079406NCI NIH HHS P01 CA059827NCI NIH HHS R01 CA166703NCI NIH HHS R01CA166703NHLBI NIH HHS R01 HL079406NHLBI NIH HHS R01 HL112986NIDDK NIH HHS P30 DK054759
6 · The paper itself

Abstract

purposeCT ventilation imaging (CTVI) is being used to achieve functional avoidance lung cancer radiation therapy in three clinical trials (NCT02528942, NCT02308709, NCT02843568). To address the need for common CTVI validation tools, we have built the Ventilation And Medical Pulmonary Image Registration Evaluation (VAMPIRE) Dataset, and present the results of the first VAMPIRE Challenge to compare relative ventilation distributions between different CTVI algorithms and other established ventilation imaging modalities.

methodsThe VAMPIRE Dataset includes 50 pairs of 4DCT scans and corresponding clinical or experimental ventilation scans, referred to as reference ventilation images (RefVIs). The dataset includes 25 humans imaged with Galligas 4DPET/CT, 21 humans imaged with DTPA-SPECT, and 4 sheep imaged with Xenon-CT. For the VAMPIRE Challenge, 16 subjects were allocated to a training group (with RefVI provided) and 34 subjects were allocated to a validation group (with RefVI blinded). Seven research groups downloaded the Challenge dataset and uploaded CTVIs based on deformable image registration (DIR) between the 4DCT inhale/exhale phases. Participants used DIR methods broadly classified into B-splines, Free-form, Diffeomorphisms, or Biomechanical modeling, with CT ventilation metrics based on the DIR evaluation of volume change, Hounsfield Unit change, or various hybrid approaches. All CTVIs were evaluated against the corresponding RefVI using the voxel-wise Spearman coefficient

resultsA total of 37 unique combinations of DIR method and CT ventilation metric were either submitted by participants directly or derived from participant-submitted DIR motion fields using the in-house software, VESPIR. The

conclusionsThe VAMPIRE Challenge results demonstrate that the cross-modality correlation between CTVIs and the RefVIs varies not only with the choice of CTVI algorithm but also with the choice of RefVI modality, imaging subject, and the evaluation metric used to compare relative ventilation distributions. This variability may arise from the fact that each of the different CTVI algorithms and RefVI modalities provides a distinct physiologic measurement. Ultimately this variability, coupled with the lack of a "gold standard," highlights the ongoing importance of further validation studies before CTVI can be widely translated from academic centers to the clinic. It is hoped that the information gleaned from the VAMPIRE Challenge can help inform future validation efforts.

Indexed as

AlgorithmsPulmonary VentilationAnimalsFour-Dimensional Computed TomographyHumansImage Processing, Computer-AssistedLung NeoplasmsRadiotherapy DosageRadiotherapy, Intensity-ModulatedRespirationSheepTomography, Emission-Computed, Single-Photon4DCTCT ventilation imagingdeformable image registrationlung cancer

Identifiers

PMID30575051
PMCPMC6605778

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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.