A template-based approach for the analysis of lung nodules in a volumetric CT phantom study

Gavrielides, Marios A.; Zeng, Rongping; Kinnard, Lisa M.; Myers, Kyle J.; Petrick, Nicholas

doi:10.1117/12.813560

Cited by 10 publications

(8 citation statements)

References 23 publications

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“…A key component in our CT lung phantom project is the ability to calculate the bias produced by software tools that estimate nodule volume from the CT data 13 . This assessment requires an accurate measurement of the true nodule volume.…”

Section: Nodule Measurement Methodsmentioning

confidence: 99%

Micro CT based truth estimation of nodule volume

et al. 2010

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With the advent of high-resolution CT, three-dimensional (3D) methods for nodule volumetry have been introduced, with the hope that such methods will be more accurate and consistent than currently used planar measures of size. However, the error associated with volume estimation methods still needs to be quantified. Volume estimation error is multi-faceted in the sense that there is variability associated with the patient, the software tool and the CT system. A primary goal of our current research efforts is to quantify the various sources of measurement error and, when possible, minimize their effects. In order to assess the bias of an estimate, the actual value, or "truth," must be known. In this work we investigate the reliability of micro CT to determine the "true" volume of synthetic nodules. The advantage of micro CT over other truthing methods is that it can provide both absolute volume and shape information in a single measurement. In the current study we compare micro CT volume truth to weight-density truth for spherical, elliptical, spiculated and lobulated nodules with diameters from 5 to 40 mm, and densities of -630 and +100 HU. The percent differences between micro CT and weight-density volume for -630 HU nodules range from [-21.7%, -0.6%] (mean= -11.9%) and the differences for +100 HU nodules range from [-0.9%, 3.0%] (mean=1.7%).

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Section: Nodule Measurement Methodsmentioning

confidence: 99%

Micro CT based truth estimation of nodule volume

et al. 2010

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“…This makes the data ideal for comparing various size estimation algorithms. The data are also useful for developing new size estimation methods [23] as well as developing appropriate assessment methodologies for comparing algorithms. These as well as various other applications of the phantom data are discussed in more detail in [22].…”

Section: Understanding Performance On Phantomsmentioning

confidence: 99%

Data sets for the qualification of volumetric CT as a quantitative imaging biomarker in lung cancer

Buckler¹,

Schwartz²,

Petrick³

et al. 2010

Opt. Express

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The drug development industry is faced with increasing costs and decreasing success rates. New ways to understand biology as well as the increasing interest in personalized treatments for smaller patient segments requires new capabilities for the rapid assessment of treatment responses. Deployment of qualified imaging biomarkers lags apparent technology capabilities. The lack of consensus methods and qualification evidence needed for large-scale multi-center trials, as well as the standardization that allows them, are widely acknowledged to be the limiting factors. The current fragmentation in imaging vendor offerings, coupled with the independent activities of individual biopharmaceutical companies and their contract research organizations (CROs), may stand in the way of the greater opportunity were these efforts to be drawn together. A preliminary report, "Volumetric CT: a potential biomarker of response," of the Quantitative Imaging Biomarkers Alliance (QIBA) activity was presented at the Medical Imaging Continuum: Path Forward for Advancing the Uses of Medical Imaging in the Development of New Biopharmaceutical Products meeting of the Extended Pharmaceutical Research and Manufacturers of America (PhRMA) Imaging Group sponsored by the Drug Information Agency (DIA) in October 2008. The clinical context in Lung Cancer and a methodology for approaching the qualification of volumetric CT as a biomarker has since been reported [Acad. Radiol. 17, 100-106, 107-115 (2010)]. This report reviews the effort to collect and utilize publicly available data sets to provide a transparent environment in which to pursue the qualification activities in such a way as to allow independent peer review and verification of results. This article focuses specifically on our role as stewards of image sets for developing new tools.

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“…A number of studies examining the effect of such factors on nodule size estimation are summarized in a 2009 review by Gavrielides et al (1) and in subsequent studies (2)(3)(4)(5)(6)(7)(8)(9). In previous work, we developed a template-based matched filter volume estimator (5) and applied it in a number of phantom studies to examine the effect of imaging protocols (5,6,10) and to determine the minimum detectable change in volume (11). The aforementioned studies examined solid nodules for a wide range of radiodensities (-800 to 100HU).…”

Section: Introductionmentioning

confidence: 97%

Volume estimation of multi-density nodules with thoracic CT

Gavrielides

Zeng

et al. 2014

SPIE Proceedings

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The purpose of this work was to quantify the effect of surrounding density on the volumetric assessment of lung nodules in a phantom CT study. Eight synthetic multidensity nodules were manufactured by enclosing spherical cores in larger spheres of double the diameter and with a different uniform density. Different combinations of outer/inner diameters (20/10mm, 10/5mm) and densities (100HU/-630HU, 10HU/-630HU, -630HU/100HU, -630HU/-10HU) were created. The nodules were placed within an anthropomorphic phantom and scanned with a 16-detector row CT scanner. Ten repeat scans were acquired using exposures of 20, 100, and 200mAs, slice collimations of 16x0.75mm and 16x1.5mm, and pitch of 1.2, and were reconstructed with varying slice thicknesses (three for each collimation) using two reconstruction filters (medium and standard). The volumes of the inner nodule cores were estimated from the reconstructed CT data using a matched-filter approach with templates modeling the characteristics of the multi-density objects. Volume estimation of the inner nodule was assessed using percent bias (PB) and the standard deviation of percent error (SPE). The true volumes of the inner nodules were measured using micro CT imaging. Results show PB values ranging from -12.4 to 2.3% and SPE values ranging from 1.8 to 12.8%. This study indicates that the volume of multi-density nodules can be measured with relatively small percent bias (on the order of ±12% or less) when accounting for the properties of surrounding densities.These findings can provide valuable information for Downloaded From: http://proceedings.spiedigitallibrary.org/ on 06/23/2016 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspxunderstanding bias and variability in clinical measurements of nodules that also include local biological changes such as inflammation and necrosis.

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A template-based approach for the analysis of lung nodules in a volumetric CT phantom study

Cited by 10 publications

References 23 publications

Micro CT based truth estimation of nodule volume

Micro CT based truth estimation of nodule volume

Data sets for the qualification of volumetric CT as a quantitative imaging biomarker in lung cancer

Volume estimation of multi-density nodules with thoracic CT

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