A Quantitative Method for Estimating Individual Lung Cancer Risk

Rationale and Objectives

Lung cancer is caused primarily by repeated exposure to carcinogenic particulate matter and noxious gasses with high particulate deposition localized to airway bifurcations and the lung periphery. The quantitative measurement and analysis of these sites has the potential to stratify lung cancer risk. The aim of this preliminary study was to assess the performance of a new method for estimating individual lung cancer risk based on the analysis of airway bifurcations on high-resolution (HR) computed tomographic (CT) scanning and spirometry.

Materials and Methods

One hundred eight subjects with spirometry and thin-slice CT data were selected from a CT screening study including 15 patients with early lung cancer and 93 age-matched and pack-year–matched controls. A subset of seven patients with cancer and 72 controls were scanned with 1-mm CT slice thickness, representing an HR case subset. A quantitative lung cancer risk index method was developed on the basis of airway bifurcation x-ray attenuation combined with the ratio of forced expiratory volume in 1 second to forced vital capacity. Cochran-Mantel-Haenszel and conditional logistic regression tests were used to analyze performance.

Results

Cochran-Mantel-Haenszel crude analysis revealed a cancer detection sensitivity and specificity of 67% and 72% for all cases and 100% and 73% for the HR case subset, respectively. Conditional logistic regression showed that a 0.0328 increase in lung cancer risk index was associated with odds ratios of 1.84 (95% confidence interval, 1.18–2.85) for the full data set ( P = .0067) and 2.89 (95% confidence interval, 1.02-8.19) for the HR subset ( P = .0467).

Conclusions

A preliminary evaluation of a new lung cancer risk estimation method based on thin slice CT and spirometry showed a statistically significant association with lung cancer.

Lung cancer is the leading cause of cancer death worldwide and is responsible for >1.3 million deaths each year . In the United States, a 17.3% 5-year survival rate is attributable largely to the high rate of late-stage diagnosis, when treatment options are rarely curative. However, the onset of malignancy generally occurs over decades of life as a result of genetic predisposition to respiratory injury and repeated toxic exposure and damage to lung tissues. Functional declines , structural changes and preneoplastic molecular changes have been documented to occur within the lungs of smokers as cigarette smoke exposure increases. This report provides preliminary evidence that anatomic x-ray attenuation changes also occur, particularly in lung tissues that receive some of the highest levels of toxic exposure.

A large body of environmental health and toxicity research has demonstrated that the deposition of particulate matter is a critical mechanism governing the toxic dose exposure of the lung . Particulate matter, a major source of toxicity in cigarette smoke, is carried through the airways and deposited on the respiratory epithelium on the basis of several fundamental physical forces . This creates “hot spots” in the lung where particulate matter deposition and exposure to noxious gasses are high.

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Materials and methods

Subjects

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Quantitative CT Analysis

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BDI=CFn⋅∑ni=1log(BDi−CDi), B

⋅

∑

log

(

−

)

where i is the index of the n = 5 segmental bifurcations measured.

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Table 1

Scanner Correction Factors Used to Correct for Variation in Acquisition Systems

Scanner Model ∗ Slice Thickness (mm) Correction Control Subjects Patients with Cancer Definition 1.00 0.9676 13 0 Sensation 64 1.00 1.0000 50 1 Volume Zoom 1.00 1.0264 9 6 Volume Zoom 1.25 1.0703 21 8

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Statistical Analysis

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Results

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Table 2

Study Population Characteristics According to Cancer Status

Patients with Cancer Control Subjects Variable ( n = 15) ( n = 93)P Age (y) 59.7 ± 7.3 58.9 ± 7.2 .6680 ∗ Men 13 (86.7%) 79 (84.9%) 1.0000 † Smoking exposure (pack-years) 49.1 ± 25.2 51.9 ± 25.3 .6661 ‡ FEV 1 /FVC 65.1 ± 8.9 71.6 ± 9.5 .0530 ‡ 1-mm slice thickness 7 (46.7%) 72 (77.4%) .0241 †

FEV 1 , forced expiratory volume in 1 second; FVC, forced vital capacity.

Data are expressed as mean ± SD or as number (percentage).

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Table 3

Distribution of Lung Cancer Histologic Types and Stages

Patients with Cancer Lung Cancer Subtype ( n = 15) Stage I Stage II Stage III Stage IV Adenocarcinoma 9 (60%) 6 2 — 1 Squamous cell 2 (13%) 2 — — — Large cell 2 (13%) 1 — 1 — Small cell 2 (13%) — — 2 —

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Discussion

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Conclusion

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Acknowledgments

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Appendix

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References

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A Quantitative Method for Estimating Individual Lung Cancer Risk

Rationale and Objectives

Materials and Methods

Results

Conclusions

Materials and methods

Subjects

Quantitative CT Analysis

Statistical Analysis

Results

Discussion

Conclusion

Acknowledgments

Appendix

References

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