Evidence map›Paper›PMID 30219290›Full record

ArticleAcademic radiology2019

Evaluation of Simulated Lesions as Surrogates to Clinical Lesions for Thoracic CT Volumetry: The Results of an International Challenge.

Marthony Robins, Jayashree Kalpathy-Cramer, Nancy A Obuchowski, Andrew Buckler, Maria Athelogou, Rudresh Jarecha, Nicholas Petrick, Aria Pezeshk, Berkman Sahiner, Ehsan Samei

Open access · greenAbstract readMulticenter Study
In one paragraph

Article in Academic radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.9field-weighted citation impact, top 23% 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

0 citing papers in PubMed, 5 citations in OpenAlex.

No citing paper in PubMed yet.

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

10 authors at 7 institutions in 1 country.

Marthony RobinsCarl E. Ravin Advanced Imaging Laboratories, Medical Physics Graduate Program, Duke University Medical Center, 2424 Erwin Road, Suite 302, Durham, NC 27705. Electronic address: marthony.robins@duke.edu.
Jayashree Kalpathy-CramerMassachusetts General Hospital, Boston, Massachusetts.
Nancy A ObuchowskiCleveland Clinic Foundation, Cleveland, Ohio.
Andrew BucklerElucid Bioimaging Inc., Wenham, Massachusetts.
Maria AthelogouDefiniens AG, München, Germany.
Rudresh JarechaPAREXEL Informatics, Billerica, Massachusetts.
Nicholas PetrickCenter for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland.
Aria PezeshkCenter for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland.
Berkman SahinerCenter for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland.
Ehsan SameiCarl E. Ravin Advanced Imaging Laboratories, Medical Physics Graduate Program, Duke University Medical Center, 2424 Erwin Road, Suite 302, Durham, NC 27705.
United States Food and Drug Administration · USCleveland Clinic · USDuke Medical Center · USDuke University · USElucid Bioimaging · USMassachusetts General Hospital · USPAREXEL International (United States) · US

Funding

Informatics Tools for Optimized Imaging Biomarkers for Cancer Research&DiscoveryU24CA180927 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI KALPATHY-CRAMER, JAYASHREE, ROSEN, BRUCE R · 2014 to 2018
$3.4M
NCI NIH HHS U24 CA180927NHLBI NIH HHS HHSN268201500021CNIBIB NIH HHS HHSN268201300071C
6 · The paper itself

Abstract

RATIONALE AND

objectivesTo evaluate a new approach to establish compliance of segmentation tools with the computed tomography volumetry profile of the Quantitative Imaging Biomarker Alliance (QIBA); and determine the statistical exchangeability between real and simulated lesions through an international challenge. MATERIALS AND

methodsThe study used an anthropomorphic phantom with 16 embedded physical lesions and 30 patient cases from the Reference Image Database to Evaluate Therapy Response with pathologically confirmed malignancies. Hybrid datasets were generated by virtually inserting simulated lesions corresponding to physical lesions into the phantom datasets using one projection-domain-based method (Method 1), two image-domain insertion methods (Methods 2 and 3), and simulated lesions corresponding to real lesions into the Reference Image Database to Evaluate Therapy Response dataset (using Method 2). The volumes of the real and simulated lesions were compared based on bias (measured mean volume differences between physical and virtually inserted lesions in phantoms as quantified by segmentation algorithms), repeatability, reproducibility, equivalence (phantom phase), and overall QIBA compliance (phantom and clinical phase).

resultsFor phantom phase, three of eight groups were fully QIBA compliant, and one was marginally compliant. For compliant groups, the estimated biases were -1.8 ± 1.4%, -2.5 ± 1.1%, -3 ± 1%, -1.8 ± 1.5% (±95% confidence interval). No virtual insertion method showed statistical equivalence to physical insertion in bias equivalence testing using Schuirmann's two one-sided test (±5% equivalence margin). Differences in repeatability and reproducibility across physical and simulated lesions were largely comparable (0.1%-16% and 7%-18% differences, respectively). For clinical phase, 7 of 16 groups were QIBA compliant.

conclusionHybrid datasets yielded conclusions similar to real computed tomography datasets where phantom QIBA compliant was also compliant for hybrid datasets. Some groups deemed compliant for simulated methods, not for physical lesion measurements. The magnitude of this difference was small (<5.4%). While technical performance is not equivalent, they correlate, such that, volumetrically simulated lesions could potentially serve as practical proxies.

Indexed as

AlgorithmsCone-Beam Computed TomographyDatabases, FactualHumansLungLung NeoplasmsPhantoms, ImagingReproducibility of ResultsCTHybrid datasetLung cancerQuantitative imagingSegmentationVolumetry

Identifiers

PMID30219290
PMCPMC6414290
OpenAlexW2890514329

What OpenQuestion holds

Textmetadata
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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.