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Influences in CT Scan Lung Nodule VolumetryInfluences in CT Scan Lung Nodule Volumetry FREE TO VIEW

Bruno Hochhegger, MD, PhD; Edson Marchiori, MD, PhD; Giordano Rafael Tronco Alves, MD; Marcos Duarte Guimarães, MD, PhD; Klaus Irion, MD, PhD
Author and Funding Information

From the Department of Radiology (Dr Hochhegger), Federal University of Rio de Janeiro; the Department of Radiology (Dr Marchiori), Rio de Janeiro Federal University; the Radiology Division (Dr Alves), Federal University of Santa Maria; the Department of Imaging (Dr Guimarães), Hospital AC Camargo; the Department of Radiology (Dr Irion), Liverpool Heart and Chest Hospital NHS Trust; and Royal Liverpool and Broadgreen University Hospital NHS (Dr Irion).

CORRESPONDENCE TO: Bruno Hochheggar, MD, PhD, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil - Radiology, joao alfredo 558 301, Porto alegre, Porto Alegre 90050230, Brazil; e-mail: brunohochhegger@gmail.com


FINANCIAL/NONFINANCIAL DISCLOSURES: The authors have reported to CHEST that no potential conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.

Reproduction of this article is prohibited without written permission from the American College of Chest Physicians. See online for more details.


Chest. 2014;146(2):e69-e70. doi:10.1378/chest.14-0763
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To the Editor:

We read with great interest the well-written article by Mehta et al1 in CHEST (March 2014), which reported that the addition of nodule volume to existing malignancy prediction models increases the proportion of correctly classified nodules. However, we would like to highlight some aspects regarding lung nodule volumetry.

Lung nodule measurements made with CT imaging are used in clinical practice to assess size changes estimated from serial scans obtained over time to predict the likelihood of malignancy and to monitor the tumor response to treatment.2 Size measurements need to be accurate and consistent to enable the assessment of nodule changes in a short time interval. The precision and accuracy of volume measurements depend on several factors, including the image-acquisition and reconstruction parameters, the nodule characteristics, and the performance of algorithms for nodule segmentation and volume estimation.2-4

Goodman et al3 presented results on the variability of volumetric measurements made with a commercial semiautomated software program (Advantage Lung Analysis; GE Healthcare). The evaluation was performed on 50 nodules across three repeat scans read by three observers. The second and third scans were acquired during two breath holds performed 10 to 20 min after the first scan. Nodule volume was estimated as the average volume measurement of the three observers at the first scan and was used as the baseline truth to measure interobserver variability. This measure of interobserver variability is inherently biased because each observer is compared against a standard that is based, in part, on his/her own contours. Interscan variability was measured as the percentage difference between the average volume measurements and the estimated volume. The results revealed significant interscan variability (on the order of 13%) but minimal interobserver variability. Findings from several other studies have demonstrated differences in the volumetric measurement error, ranging from 10% to 40%, between scans acquired with thin and thick section widths. Even with these limitations, we can generally conclude that section thickness/width is one of the most important CT scan acquisition parameters to control. In a recent article about nodule volumetry with phantom correlation, Xie et al4 reported that the CT scan-derived volume of small nodules is largely underestimated, with considerable variation.

These data highlight the need to standardize all variables in CT scanning to obtain a reliable volumetric assessment of the pulmonary nodule. This standardization is even more important in studies that will use volumetric CT scanning in the follow-up of these nodules.

References

Mehta HJ, Ravenel JG, Shaftman SR, et al. The utility of nodule volume in the context of malignancy prediction for small pulmonary nodules. Chest. 2014;145(3):464-472. [CrossRef] [PubMed]
 
Gavrielides MA, Kinnard LM, Myers KJ, Petrick N. Noncalcified lung nodules: volumetric assessment with thoracic CT. Radiology. 2009;251(1):26-37. [CrossRef] [PubMed]
 
Goodman LR, Gulsun M, Washington L, Nagy PG, Piacsek KL. Inherent variability of CT lung nodule measurements in vivo using semiautomated volumetric measurements. AJR Am J Roentgenol. 2006;186(4):989-994. [CrossRef] [PubMed]
 
Xie X, Willemink MJ, de Jong PA, et al. Small irregular pulmonary nodules in low-dose CT: observer detection sensitivity and volumetry accuracy. AJR Am J Roentgenol. 2014;202(3):W202-W209. [CrossRef] [PubMed]
 

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References

Mehta HJ, Ravenel JG, Shaftman SR, et al. The utility of nodule volume in the context of malignancy prediction for small pulmonary nodules. Chest. 2014;145(3):464-472. [CrossRef] [PubMed]
 
Gavrielides MA, Kinnard LM, Myers KJ, Petrick N. Noncalcified lung nodules: volumetric assessment with thoracic CT. Radiology. 2009;251(1):26-37. [CrossRef] [PubMed]
 
Goodman LR, Gulsun M, Washington L, Nagy PG, Piacsek KL. Inherent variability of CT lung nodule measurements in vivo using semiautomated volumetric measurements. AJR Am J Roentgenol. 2006;186(4):989-994. [CrossRef] [PubMed]
 
Xie X, Willemink MJ, de Jong PA, et al. Small irregular pulmonary nodules in low-dose CT: observer detection sensitivity and volumetry accuracy. AJR Am J Roentgenol. 2014;202(3):W202-W209. [CrossRef] [PubMed]
 
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