Computer-Aided Differential Diagnosis of the Pulmonary Nodule: Towards an Understanding of the Medical Imaging Basics and Experiences in the Field

Matvey V. Sprindzuk; Kovalev V. Alekseevich; Snezhko E. Vitalévich; Kharuzhyk S. Anatolévich

doi:10.6058/jlc.2009.8.2.78

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Sprindzuk, Alekseevich, Vitalévich, and Anatolévich: Computer-Aided Differential Diagnosis of the Pulmonary Nodule: Towards an Understanding of the Medical Imaging Basics and Experiences in the Field

Original Article

J Lung Cancer 2009;8(2):78-91.

Published online: 10 January 2009

DOI: https://doi.org/10.6058/jlc.2009.8.2.78

Computer-Aided Differential Diagnosis of the Pulmonary Nodule: Towards an Understanding of the Medical Imaging Basics and Experiences in the Field

Matvey V. Sprindzuk, M.D., Kovalev V. Alekseevich, Ph.D., Snezhko E. Vitalévich, Ph.D., Kharuzhyk S. Anatolévich, M.D., Ph.D.

Research Centre for Computer Science and Informational Technologies, National Academy of Science, Minsk, Belarus

Address for correspondence Matvey V. Sprindzuk, M.D. United Institute of Informatics Problems, National Academy of Sciences of Belarus, Surganov str., 6, 220012, Minsk, Belarus Tel: +375-17-274-21-71 Fax: +375-17-331-84-03 E-mail: sprindzuk@yahoo.com

Received 29 September 2009 Revised 22 October 2009 Accepted 11 November 2009

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

In this article, the modern concepts of computer-aided diagnosis (CAD), the methods of pulmonary nodule detection, and facts derived from the literature on the pulmonary nodule differential CAD are compiled in one source and described in some detail. Several issues in lung cancer (LC) epidemiology and early diagnosis are discussed. Analysis of research done so far shows evidence that various CAD systems can be successfully applied to chest radiographs, computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). These modalities can serve as useful potential alternative tools available to practicing medical professionals performing routine diagnostics.

Keywords: Computer-aided diagnosis, Pulmonary nodule, Computed tomography, Magnetic resonance tomography, Positron emission tomography

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Figures and Tables

Fig. 1.

The image from a 61-year-old man. Peripheral cancer of the left lung. MRI of the thoracic cavity (arrows points to the tumor). (A) T2-weighted image in a coronal plane, thickness of a cut – 6 mm; (B) T2-weighted image in a coronal plane, thickness of a cut – 4 mm; (C) T2-weighted image in transversal plane, thickness of a cut-6 mm; (D) T1-weighted image in transversal plane after the intravenous introduction of contrast substance (Omniscan).

Fig. 2.

Lung cancer morbidity and lethality in Belarus, 1998, 2002, 2007 (A: male morbidity, B: male lethality, C: female morbidity, D: female lethality, E: both genders morbidity, F: both genders lethality).

Fig. 3.

Principal causes of solitary pulmonary nodules. Hansen HH. Textbook of lung cancer. 2nd ed. London: Informa Healthcare; 2008 (46).

Fig. 4.

Diagram of the computerized scheme for detection of pulmonary nodules on CT images. Awai K, Murao K, Ozawa A, et al. Radiology 2006;239:276–284 (57).

Fig. 5.

The scheme of pulmonary nodules scoring. Leader JK, Warfel TE, Fuhrman CR, et al. AJR Am J Roentgenol 2005; 185:973–978 (59).

Table 1.

Volume Doubling Time of the SPN

Doubling time (=time required to double in volume):

ㆍ for most malignant nodules: 30∼400 days=26% increase in diameter

∘ ≤30 days: aggressive small cell cancer

∘ ≤90 days: squamous cell carcinoma

∘ ≤120 days: large cell carcinoma

∘ ≤150 days: aggressive adenocarcinoma

∘ ≤180 days: average adenocarcinoma

ㆍ for benign nodules: ＜30 and ＞400 days

∘ Absence of growth over a 2-year period implies a doubling time of ＞730 days

Dä hnert W. Radiology review manual. 6th ed. Philadelphia, PA: Lippincott Williams Wilkins; 2007 (48).

Table 2.

Probability of Malignancy for Indeterminate Solitary Pulmonary Nodule

Characteristic/Feature	Likelihood ratio
Spiculated margin	5.54
Size ＞3 cm	5.23
＞70 years of age	4.16
Malignant growth rate	3.40
Smoker	2.27
Upper lobe location	1.22
Size ＜10 mm	0.52
Smooth margin	0.30
30∼39 years of age	0.24
Never smoked	0.19
20∼29 years of age	0.05
Benign calcification	0.01
Benign growth rate	0.01

Dä hnert W. Radiology review manual. 6th ed. Philadelphia, PA: Lippincott Williams Wilkins; 2007 (48).

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