Computer-Aided Volumetry of Pulmonary Nodules Exhibiting Ground-Glass Opacity at MDCT

Department of Diagnostic Radiology, Kumamoto University, Japan.
American Journal of Roentgenology (Impact Factor: 2.73). 02/2010; 194(2):398-406. DOI: 10.2214/AJR.09.2583
Source: PubMed

ABSTRACT The purpose of this study was to investigate the accuracy and reproducibility of results acquired with computer-aided volumetry software during MDCT of pulmonary nodules exhibiting ground-glass opacity.
To evaluate the accuracy of computer-aided volumetry software, we performed thin-section helical CT of a chest phantom that included simulated 3-, 5-, 8-, 10-, and 12-mm-diameter ground-glass opacity nodules with attenuation of -800, -630, and -450 HU. Three radiologists measured the volume of the nodules and calculated the relative volume measurement error, which was defined as follows: (measured nodule volume minus assumed nodule volume / assumed nodule volume) x 100. Two radiologists performed two independent measurements of 59 nodules in humans. Intraobserver and interobserver agreement was evaluated with Bland-Altman methods.
The relative volume measurement error for simulated ground-glass opacity nodules measuring 3 mm ranged from 51.1% to 85.2% and for nodules measuring 5 mm or more in diameter ranged from -4.1% to 7.1%. In the clinical study, for intraobserver agreement, the 95% limits of agreement were -14.9% and -13.7% and -16.6% to 15.7% for observers A and B. For interobserver agreement, these values were -16.3% to 23.7% for nodules 8 mm in diameter or larger.
With computer-aided volumetry of ground-glass opacity nodules, the relative volume measurement error was small for nodules 5 mm in diameter or larger. Intraobserver and interobserver agreement was relatively high for nodules 8 mm in diameter or larger.

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    • "The presented results demonstrated low degree of consensus between the assessing physicians which, according to the authors, could be corrected by using computer-assisted assessment of CT scans [74,75]. With no doubt, results of the increasing number of papers on Computer Aided Diagnosis (CAD) of nodular lesions require that their widespread use should be considered [31,32,37,43,74–76]. According to some researchers, due to the fact that the assessment of screening tests is much work-consuming, the algorithm should be used as the second, independent assessing entity along with the radiologist [31,75]. "
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    ABSTRACT: Background Despite the progress in contemporary medicine comprising diagnostic and therapeutic methods, lung cancer is still one of the biggest health concerns in many countries of the world. The main purpose of the study was to evaluate the detection rate of pulmonary nodules and lung cancer in the initial, helical low-dose CT of the chest as well as the analysis of the relationship between the size and the histopathological character of the detected nodules. Material/Methods We retrospectively evaluated 1999 initial, consecutive results of the CT examinations performed within the framework of early lung cancer detection program initiated in Szczecin. The project enrolled persons of both sexes, aged 55–65 years, with at least 20 pack-years of cigarette smoking or current smokers. The analysis included assessment of the number of positive results and the evaluation of the detected nodules in relationship to their size. All of the nodules were classified into I of VI groups and subsequently compared with histopathological type of the neoplastic and nonneoplastic pulmonary lesions. Results Pulmonary nodules were detected in 921 (46%) subjects. What is more, malignant lesions as well as lung cancer were significantly, more frequently discovered in the group of asymptomatic nodules of the largest dimension exceeding 15 mm. Conclusions The initial, low-dose helical CT of the lungs performed in high risk individuals enables detection of appreciable number of indeterminate pulmonary nodules. In most of the asymptomatic patients with histopathologically proven pulmonary nodules greater than 15 mm, the mentioned lesions are malignant, what warrants further, intensified diagnostics.
    Polish Journal of Radiology 07/2014; 79:210-8. DOI:10.12659/PJR.890103
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    • "The concept of remaining stable over 2 years (doubling time > 730 days) therefore does not apply to pure or partial ground glass nodules which require longer follow-up. In addition, volumetry is not considered to be sufficiently reliable for ground glass nodules [74] [79], despite some encouraging results [80]. A novel, promising approach for mixed nodules would involve measuring the nodule mass, by taking account of volume and density of the two components [81]. "
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    ABSTRACT: Lung nodules are commonly found on computed tomography (CT) and need a standardized approach in order to avoid misdiagnosing lung cancer and delaying surgical excision whilst simultaneously avoiding unnecessary invasive procedures if the lesions prove to be benign. Great advances have been made in the last decade in various areas affecting the management of lung nodules: the understanding of the molecular mechanisms behind carcinogenesis, a new classification of lung adenocarcinoma, new data on lung cancer screening, widespread use of multi-detector row CT and development of volumetric analysis software for nodules. Recent decision-making algorithms are based on the size, density and follow-up of the nodule. The distinction between solid nodules, sub-solid nodules and pure ground glass nodules is fundamental, and has a strong correlation with the histologic spectrum of adenocarcinoma. In the absence of criteria suggesting benign disease, the radiologist's report should offer one of the following two options: follow-up based on the recommendations if the nodule is equivocal, or multidisciplinary discussion to consider invasive management if the nodule is highly suspicious of malignancy. Recent data from this statement are reviewed and practical guidelines are offered based on international expert consensus opinion.
    Diagnostic and interventional imaging 09/2013; 94(11). DOI:10.1016/j.diii.2013.05.007
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    • "Relative attenuation measurement error was not described in that study and we did not include -450 HU nodules which were used as solid nodule surrogates in the study by Oda et al. (8). Our volume measurement error was higher than that reported by Oda et al. (8); however, we only used the semi-automated method without manual editing or manual drawing as we considered them to be impractical and time-consuming in real clinical practice. "
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    ABSTRACT: To compare the segmentation capability of the 2 currently available commercial volumetry software programs with specific segmentation algorithms for pulmonary ground-glass nodules (GGNs) and to assess their measurement accuracy. In this study, 55 patients with 66 GGNs underwent unenhanced low-dose CT. GGN segmentation was performed by using 2 volumetry software programs (LungCARE, Siemens Healthcare; LungVCAR, GE Healthcare). Successful nodule segmentation was assessed visually and morphologic features of GGNs were evaluated to determine factors affecting segmentation by both types of software. In addition, the measurement accuracy of the software programs was investigated by using an anthropomorphic chest phantom containing simulated GGNs. The successful nodule segmentation rate was significantly higher in LungCARE (90.9%) than in LungVCAR (72.7%) (p = 0.012). Vascular attachment was a negatively influencing morphologic feature of nodule segmentation for both software programs. As for measurement accuracy, mean relative volume measurement errors in nodules ≥ 10 mm were 14.89% with LungCARE and 19.96% with LungVCAR. The mean relative attenuation measurement errors in nodules ≥ 10 mm were 3.03% with LungCARE and 5.12% with LungVCAR. LungCARE shows significantly higher segmentation success rates than LungVCAR. Measurement accuracy of volume and attenuation of GGNs is acceptable in GGNs ≥ 10 mm by both software programs.
    Korean journal of radiology: official journal of the Korean Radiological Society 07/2013; 14(4):683-91. DOI:10.3348/kjr.2013.14.4.683 · 1.57 Impact Factor
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