Volume error analysis for lung nodules attached to pulmonary vessels in an anthropomorphic thoracic phantom

Kinnard, Lisa M.; Gavrielides, Marios A.; Myers, Kyle J.; Zeng, Rongping; Peregoy, Jennifer; Pritchard, William F.; Karanian, John W.; Petrick, Nicholas

doi:10.1117/12.773039

Cited by 10 publications

(9 citation statements)

References 13 publications

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“…Tissue metabolic rate can be measured with positron emission tomography (PET) using 18 Ffluorodeoxyglucose as a tracer. 18 F-Fluorodeoxyglucose-PET has been a workhorse in diagnosing, staging and monitoring response to therapy for the last 20 years. 18 F-Fluorothymidine is a novel PET tracer, which is a more specific indicator of cellular proliferation.…”

Section: Figurementioning

confidence: 99%

“…18 F-Fluorodeoxyglucose-PET has been a workhorse in diagnosing, staging and monitoring response to therapy for the last 20 years. 18 F-Fluorothymidine is a novel PET tracer, which is a more specific indicator of cellular proliferation. Tumour tissue shows increased vascularity and microvascular permeability.…”

Section: Figurementioning

confidence: 99%

“…Tissue microanatomy can be assessed by density and texture analysis on CT, and by diffusion-weighted imaging (DWI) on MRI. 18 F-Fluorodeoxyglucose (FDG)-PET is used to assess tumour metabolic rate, and 18 F-Fluorothymidine (FLT)-PET can be used to assess cellular proliferation more specifically. Tissue microvasculature can be assessed using various forms of perfusion imaging using dynamic contrast enhancement (DCE).These methods are at present mainly applied in the early stages of clinical development.…”

Section: Figurementioning

confidence: 99%

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The use of tumour volumetrics to assess response to therapy in anticancer clinical trials

Goldmacher¹,

Conklin²

2012

Brit J Clinical Pharma

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Serial evaluations of tumour burden using imaging, mainly computed tomography and magnetic resonance imaging, form the basis for assessing treatment response in many clinical trials of anticancer therapeutics. Traditionally, these evaluations have been based on linear measurements of tumour size. Such measurements have limitations related to variability in technical factors, tumour morphology and reader decisions. Measurements of entire tumour volumes may overcome some of the limitations of linear tumour measurements, improving our ability to detect small changes reliably and increasing statistical power per subject in a trial. Certain technical factors are known to affect the accuracy and precision of volume measurements, and work is in progress to define these factors more thoroughly and to qualify tumour volume as a biomarker for the purposes of drug development.

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Section: Figurementioning

confidence: 99%

Section: Figurementioning

confidence: 99%

Section: Figurementioning

confidence: 99%

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The use of tumour volumetrics to assess response to therapy in anticancer clinical trials

Goldmacher¹,

Conklin²

2012

Brit J Clinical Pharma

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“…Phantom studies have been employed in thoracic CT since the early work of Zerhouni et al (11) to standardize nodule attenuation measurements. Results from studies performed with both phantom (5,(12)(13)(14)(15)(16)(17)(18)(19)(20)(21) and clinical (5,7,8,13,15,17,18,(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33) data on the volumetric assessment of lung nodules with CT will be reviewed and discussed in this article.…”

mentioning

confidence: 99%

Noncalcified Lung Nodules: Volumetric Assessment with Thoracic CT

Gavrielides¹,

Kinnard²,

Myers³

et al. 2009

Radiology

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154

113

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Lung nodule volumetry is used for nodule diagnosis, as well as for monitoring tumor response to therapy. Volume measurement precision and accuracy depend on a number of factors, including image-acquisition and reconstruction parameters, nodule characteristics, and the performance of algorithms for nodule segmentation and volume estimation. The purpose of this article is to provide a review of published studies relevant to the computed tomographic (CT) volumetric analysis of lung nodules. A number of underexamined areas of research regarding volumetric accuracy are identified, including the measurement of nonsolid nodules, the effects of pitch and section overlap, and the effect of respiratory motion. The need for public databases of phantom scans, as well as of clinical data, is discussed. The review points to the need for continued research to examine volumetric accuracy as a function of a multitude of interrelated variables involved in the assessment of lung nodules. Understanding and quantifying the sources of volumetric measurement error in the assessment of lung nodules with CT would be a first step toward the development of methods to minimize that error through system improvements and to correctly account for any remaining error.

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“…These effects must be understood and quantified. A number of technical studies have been performed toward that goal [9-32]. …”

Section: Introductionmentioning

confidence: 99%

Inter-Method Performance Study of Tumor Volumetry Assessment on Computed Tomography Test-Retest Data

Buckler

Danagoulian

Johnson³

et al. 2015

Academic Radiology

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Rationale and objectives Tumor volume change has potential as a biomarker for diagnosis, therapy planning, and treatment response. Precision was evaluated and compared among semi-automated lung tumor volume measurement algorithms from clinical thoracic CT datasets. The results inform approaches and testing requirements for establishing conformance with the Quantitative Imaging Biomarker Alliance (QIBA) CT Volumetry Profile. Materials and Methods Industry and academic groups participated in a challenge study. Intra-algorithm repeatability and inter-algorithm reproducibility were estimated. Relative magnitudes of various sources of variability were estimated using a linear mixed effects model. Segmentation boundaries were compared to provide a basis on which to optimize algorithm performance for developers. Results Intra-algorithm repeatability ranged from 13% (best performing) to 100% (least performing), with most algorithms demonstrating improved repeatability as the tumor size increased. Inter-algorithm reproducibility determined in three partitions and found to be 58% for the four best performing groups, 70% for the set of groups meeting repeatability requirements, and 84% when all groups but the least performer were included. The best performing partition performed markedly better on tumors with equivalent diameters above 40 mm. Larger tumors benefitted by human editing but smaller tumors did not. One-fifth to one-half of the total variability came from sources independent of the algorithms. Segmentation boundaries differed substantially, not just in overall volume but in detail. Conclusions Nine of the twelve participating algorithms pass precision requirements similar to what is indicated in the QIBA Profile, with the caveat that the current study was not designed to explicitly evaluate algorithm Profile conformance. Change in tumor volume can be measured with confidence to within ±14% using any of these nine algorithms on tumor sizes above 10 mm. No partition of the algorithms were able to meet the QIBA requirements for interchangeability down to 10 mm, though the partition comprised of the best performing algorithms did meet this requirement above a tumor size of approximately 40 mm.

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Volume error analysis for lung nodules attached to pulmonary vessels in an anthropomorphic thoracic phantom

Cited by 10 publications

References 13 publications

The use of tumour volumetrics to assess response to therapy in anticancer clinical trials

The use of tumour volumetrics to assess response to therapy in anticancer clinical trials

Noncalcified Lung Nodules: Volumetric Assessment with Thoracic CT

Inter-Method Performance Study of Tumor Volumetry Assessment on Computed Tomography Test-Retest Data

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