Effect of Nodule Characteristics on Variability of Semiautomated Volume Measurements in Pulmonary Nodules Detected in a Lung Cancer Screening Program

Wang, Y.; Klaveren, Rob J. van; Zaag-Loonen, Hester J. van der; Bock, de Truuske; Gietema, Hester A.; Xu, Dong; Leusveld, Anne; Koning, Harry J. de; Scholten, Ernst Th.; Verschakelen, Johny; Prokop, Mathias; Oudkerk, Matthijs

doi:10.1148/radiol.2482070957

Cited by 71 publications

(63 citation statements)

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“…In the NELSON study, slice thickness of 1.0 mm with reconstruction interval of 0.7 mm was used to provide isometric voxels for accurate semi-automated volume measurements. These semi-automated measurements were found to be highly reproducible for the large majority of solid nodules, also in phantom studies [27][28][29], with high reader agreement and volume differences >15% between two readers in only 4% of solid nodules [27][28][29]. Besides, in Lindell's study lung cancer growth curves were plotted and visually evaluated, but growth patterns were not quantified.…”

Section: Discussionmentioning

confidence: 92%

Quantification of growth patterns of screen-detected lung cancers: The NELSON study

et al. 2017

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a b s t r a c tObjectives: Although exponential growth is assumed for lung cancer, this has never been quantified in vivo. Aim of this study was to evaluate and quantify growth patterns of lung cancers detected in the Dutch-Belgian low-dose computed tomography (CT) lung cancer screening trial (NELSON), in order to elucidate the development and progression of early lung cancer. Materials and methods: Solid lung nodules found at ≥3 CT examinations before lung cancer diagnosis were included. Lung cancer volume (V) growth curves were fitted with a single exponential, expressed as V = V 1 exp(t/ ), with t time from baseline (days), V 1 estimated baseline volume (mm 3 ), and estimated time constant. The R 2 coefficient of determination was used to evaluate goodness of fit. Overall volumedoubling time for the individual lung cancer is given by * log(2). Results: Forty-seven lung cancers in 46 participants were included. Forty participants were male (87.0%); mean age was 61.7 years (standard deviation, 6.2 years). Median nodule size at baseline was 99.5 mm 3 (IQR: 46.8-261.8 mm 3 ). Nodules were followed for a median of 770 days (inter-quartile range: 383-1102 days) before lung cancer diagnosis. One cancer (2.1%) was diagnosed after six CT examinations, six cancers (12.8%) were diagnosed after five CTs, 14 (29.8%) after four CTs, and 26 cancers (55.3%) after three CTs. Lung cancer growth could be described by an exponential function with excellent goodness of fit (R 2 0.98). Median overall volume-doubling time was 348 days (inter-quartile range: 222-492 days). Conclusion: This study based on CT lung cancer screening provides in vivo evidence that growth of cancerous small-to-intermediate sized lung nodules detected at low-dose CT lung cancer screening can be described by an exponential function such as volume-doubling time.© 2017 Elsevier B.V. All rights reserved.

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Section: Discussionmentioning

confidence: 92%

Quantification of growth patterns of screen-detected lung cancers: The NELSON study

et al. 2017

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“…Therefore, it is essential to assess the nodule size and growth rate accurately and reproducibly [9,10]. Variability has been found in CT-derived nodule size assessment [11,12]. In view of the current practice of patients frequently undergoing follow-up examinations, sometimes not on the same scanner, reliable inter-and intrascanner reproducibility of nodule volumetry is important.…”

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confidence: 99%

“…These studies generally showed a small margin of variability in nodule volumetry for software from different vendors. On the other hand, in vivo studies have shown that variability can be considerable, with variability up to 25% for 15 to 500 mm 3 nodules [11,[17][18][19]. A study to investigate inter-and intrascanner variability under optimally controlled conditions, yet resembling human lungs, using a more realistic phantom, has not been performed.…”

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Inter- and intrascanner variability of pulmonary nodule volumetry on low-dose 64-row CT: an anthropomorphic phantom study

Xie¹,

Willemink²,

Zhao³

et al. 2013

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Objective: To assess inter-and intrascanner variability in volumetry of solid pulmonary nodules in an anthropomorphic thoracic phantom using low-dose CT. Methods: Five spherical solid artificial nodules [diameters 3, 5, 8, 10 and 12 mm; CT density 1100 Hounsfield units (HU)] were randomly placed inside an anthropomorphic thoracic phantom in different combinations. The phantom was examined on two 64-row multidetector CT (64-MDCT) systems (CT-A and CT-B) from different vendors with a low-dose protocol. Each CT examination was performed three times. The CT examinations were evaluated twice by independent blinded observers. Nodule volume was semi-automatically measured by dedicated software. Interscanner variability was evaluated by Bland-Altman analysis and expressed as 95% confidence interval (CI) of relative differences. Intrascanner variability was expressed as 95% CI of relative variation from the mean.Results: No significant difference in CT-derived volume was found between CT-A and CT-B, except for the 3-mm nodules (p,0.05). The 95% CI of interscanner variability was within 641.6%, 618.2% and 64.9% for 3, 5 and $8 mm nodules, respectively. The 95% CI of intrascanner variability was within 628.6%, 613.4% and 62.6% for 3, 5 and $8 mm nodules, respectively. Conclusion: Different 64-MDCT scanners in low-dose settings yield good agreement in volumetry of artificial pulmonary nodules between 5 mm and 12 mm in diameter. Inter-and intrascanner variability decreases at a larger nodule size to a maximum of 4.9% for $8 mm nodules. Advances in knowledge:The commonly accepted cut-off of 25% to determine nodule growth has the potential to be reduced for $8 mm nodules. This offers the possibility of reducing the interval for repeated CT scans in lung cancer screenings.Lung cancer is the primary cancer in males and the second most common cancer in females worldwide, causing 18% of the total number of deaths [1]. Many lung cancers are found at a relatively late stage, resulting in a 5-year survival of only 15% or less [2]. Low-dose CT is a promising screening method for early detection of lung cancer [3][4][5][6][7]. The first result indicates that CT lung cancer screening can reduce lung cancer-specific mortality [8].

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“…In the main part of this study, we therefore included only solid nodules. For the vast majority of solid nodules, semi-automated measurements were found to be highly reproducible [29]. In 86 % of 4,225 screendetected solid nodules evaluated in the NELSON substudy by Wang et al, double reading obtained complete agreement in volume.…”

Section: Discussionmentioning

confidence: 95%

“…In 86 % of 4,225 screendetected solid nodules evaluated in the NELSON substudy by Wang et al, double reading obtained complete agreement in volume. Volume differences greater than 15 % were found in only 4 % of nodules [29]. When the measured volume differed between the first and second reader, the results from the second reader were used for further analyses.…”

Section: Discussionmentioning

confidence: 99%

The impact of radiologists’ expertise on screen results decisions in a CT lung cancer screening trial

et al. 2014

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Objective To evaluate the impact of radiological expertise on screen result decisions in a CT lung cancer screening trial. Methods In the NELSON lung cancer screening trial, the baseline CT result was based on the largest lung nodule's volume. The protocol allowed radiologists to manually adjust screen results in cases of high suspicion of benign or malignant nodule nature. Participants whose baseline CT result was based on a solid or part-solid nodule were included in this study. Adjustments by radiologists at baseline were evaluated. Histology was the reference for diagnosis or to confirm benignity and stability on subsequent CT examinations. Results A total of 3,318 participants (2,796 male, median age 58.0 years) were included. In 195 participants (5.9 %) the initial baseline screen result was adjusted by the radiologist. Adjustment was downwards from positive or indeterminate to negative in two and 119 participants, respectively, and from positive to indeterminate in 65 participants. None of these nodules turned out to be malignant. In 9/195 participants (4.6 %) the screen result was adjusted upwards from negative to indeterminate or indeterminate to positive; two nodules were malignant. Conclusion In one in 20 cases of baseline lung cancer screening, nodules were reclassified by the radiologist, leading to a reduction of false-positive screen results. Key Points • The NELSON study allowed radiologists to manually adjust the screen result • At baseline, radiologists adjusted the result in about one in 20 cases (95.4 % downwards) • Radiologists' adjustments led to a 22 % reduction of falsepositive screen results • Radiologists' expertise can improve nodule classification in addition to a nodule protocol

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Effect of Nodule Characteristics on Variability of Semiautomated Volume Measurements in Pulmonary Nodules Detected in a Lung Cancer Screening Program

Abstract: Nodule morphology, location, and size influence volume measurement variability, particularly for juxtavascular and irregular nodules.

Cited by 71 publications

References 30 publications

Quantification of growth patterns of screen-detected lung cancers: The NELSON study

Quantification of growth patterns of screen-detected lung cancers: The NELSON study

Inter- and intrascanner variability of pulmonary nodule volumetry on low-dose 64-row CT: an anthropomorphic phantom study

The impact of radiologists’ expertise on screen results decisions in a CT lung cancer screening trial

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