Validity of the assessment of quality of life (AQoL) utility instrument in patients with operable and inoperable lung cancer

There have been few longitudinal studies of quality of life in patients with all stages of lung cancer, particularly those that have included measures of utility. The purpose of this study was to examine the psychometric properties of the Assessment of Quality of Life instrument (AQoL) in patients with lung cancer. The AQoL is a health-related quality of life questionnaire and provides a descriptive system for a multi-attribute utility instrument (MAU), so that scores can be used in cost-utility evaluations. In the present study the reliability (internal consistency) of the AQoL was examined and the concurrent validity was assessed using the Medical Outcomes 36-item Short Form Health Survey (SF-36) as the comparator instrument. The sensitivity to different health states of the AQoL and the responsiveness to change over time was also examined. A prospective, non-experimental cohort study was undertaken. Ninety-two participants with all stages of lung cancer were recruited from a tertiary multi-disciplinary lung cancer clinic. Ninety participants had non-small cell lung cancer (NSCLC) and two had limited stage small cell lung cancer. The AQOL and SF-36 surveys were administered concurrently at baseline. In patients with NSCLC the surveys were then repeated 3 and 6 months later. Correlations between the baseline AQoL summary scales and SF-36 summary scales support the divergent and convergent validity of the AQoL. Reliability was also found to be sufficient (Cronbach's Alpha = 0.76). In addition, in patients with inoperable NSCLC, baseline AQoL scores were found to be predictive of survival at 6 months in Cox proportional hazards multivariate analysis. However, the physical components summary score of the SF-36 was more sensitive to differences in health states between patients with different stages of NSCLC at 6 months of follow-up and more responsive to change over time in both operable and inoperable patients with NSCLC than the AQoL. The findings support the construct validity and reliability of the AQoL in this population. However, there remains some uncertainty about whether the AQoL has sufficient sensitivity to different health states in this population. Further studies using other MAU instruments may determine whether alternative instruments are more sensitive to different health states in individuals with lung cancer.

Discordance between lung function of Chinese university students of 20-year-old established norms

Objective: We examined the validity of the 20-year-old established Asian norms for pulmonary function in a contemporary cohort of Hong Kong Chinese university students. Design and participants: Pulmonary function testing was conducted in university students (n = 805). Setting: A university campus in Hong Kong. Measurements and results: Parameters recorded included gender, age, height, weight, standard lung function variables (ie, FEV1, FVC, and peak expiratory flow rate [PEFR]), and exhaled carbon monoxide (CO) level. Subjects completed a questionnaire on pulmonary health, smoking history, and their dietary and exercise habits within 3 months of the study. Data were compared with the established norms for lung function for Chinese persons from Hong Kong. On average, subjects were taller than those reported in the original cohort, on whom the established norms are based; however, FEV1, FVC, and PEFR were lower. As predicted, the exhaled CO level was higher in smokers. Those who exercised regularly had a higher FEV1 and FVC, and reported fewer respiratory complaints. Conclusions: Our findings support the idea that lung function norms not only differ across ethnic groups, but that they may be susceptible to change over a single generation within an ethnic group living in the same geographic region. Assuming the equivalence of our testing methods and those on which established norms are based, our findings shed further insight into the dynamic nature of lung function, and have implications regarding the definition of normal pulmonary function and its variance over the short term.

Cost-effectiveness analysis of screening for lung cancer with low dose spiral CT (computed tomography) in the Australian setting

Introduction:
Low dose spiral computed tomography (CT) is a sensitive screening tool for lung cancer that is currently being evaluated in both non-randomised studies and randomised controlled trials.
Methods:
We conducted a quantitative decision analysis using a Markov model to determine whether, in the Australian setting, offering spiral CT screening for lung cancer to high risk individuals would be cost-effective compared with current practice. This exploratory analysis was undertaken predominantly from the perspective of the government as third-party funder. In the base-case analysis, the costs and health outcomes (life-years saved and quality-adjusted life years) were calculated in a hypothetical cohort of 10,000 male current smokers for two alternatives: (1) screen for lung cancer with annual CT for 5 years starting at age 60 year and treat those diagnosed with cancer or (2) no screening and treat only those who present with symptomatic cancer.
Results:
For male smokers aged 60–64 years, with an annual incidence of lung cancer of 552 per 100,000, the incremental cost-effectiveness ratio was $57,325 per life-year saved and $105,090 per QALY saved. For females aged 60–64 years with the same annual incidence of lung cancer, the cost-effectiveness ratio was $51,001 per life-year saved and $88,583 per QALY saved. The model was used to examine the relationship between efficacy in terms of the expected reduction in lung cancer mortality at 7 years and cost-effectiveness. In the base-case analysis lung cancer mortality was reduced by 27% and all cause mortality by 2.1%. Changes in the estimated proportion of stage I cancers detected by screening had the greatest impact on the efficacy of the intervention and the cost-effectiveness. The results were also sensitive to assumptions about the test performance characteristics of CT scanning, the proportion of lung cancer cases overdiagnosed by screening, intervention rates for benign disease, the discount rate, the cost of CT, the quality of life in individuals with early stage screen-detected cancer and disutility associated with false positive diagnoses. Given current knowledge and practice, even under favourable assumptions, reductions in lung cancer mortality of less than 20% are unlikely to be cost-effective, using a value of $50,000 per life-year saved as the threshold to define a “cost-effective” intervention.
Conclusion:
The most feasible scenario under which CT screening for lung cancer could be cost-effective would be if very high-risk individuals are targeted and screening is either highly effective or CT screening costs fall substantially.

From lung images to lung models : a review

Automated 3D lung modeling involves analyzing 2D lung images and reconstructing a realistic 3D model of the lung. This paper presents a review of the existing works on automatic formation of 3D lung models from 2D lung images. A common framework for 3D lung modeling is proposed. It consists of eight components: image acquisition, image pre-processing, image segmentation, boundary creation, image recognition, image registration, 3D surface reconstruction, and 3D rendering and visualization. The algorithms used by the existing systems to implement these components are also reviewed.

Automated identification of lung nodules

A system that can automatically detect nodules within lung images may assist expert radiologists in interpreting the abnormal patterns as nodules in 2D CT lung images. A system is presented that can automatically identify nodules of various sizes within lung images. The pattern classification method is employed to develop the proposed system. A random forest ensemble classifier is formed consisting of many weak learners that can grow decision trees. The forest selects the decision that has the most votes. The developed system consists of two random forest classifiers connected in a series fashion. A subset of CT lung images from the LIDC database is employed. It consists of 5721 images to train and test the system. There are 411 images that contained expert- radiologists identified nodules. Training sets consisting of nodule, non-nodule, and false-detection patterns are constructed. A collection of test images are also built. The first classifier is developed to detect all nodules. The second classifier is developed to eliminate the false detections produced by the first classifier. According to the experimental results, a true positive rate of 100%, and false positive rate of 1.4 per lung image are achieved.

A random forest for lung nodule identification

A method is presented for identification of lung nodules. It includes three stages: image acquisition, background removal, and nodule detection. The first stage improves image quality. The second stage extracts long lobe regions. The third stage detects lung nodules. The method is based on the random forest learner. Training set contains nodule, non-nodule, and false-positive patterns. Test set contains randomly selected images. The developed method is compared against the support vector machine. True-positives of 100% and 85.9%, and false-positives of 1.27 and 1.33 per image were achieved by the developed method and the support vector machine, respectively.

Lung nodules detection by ensemble classification

A method is presented that achieves lung nodule detection by classification of nodule and non-nodule patterns. It is based on random forests which are ensemble learners that grow classification trees. Each tree produces a classification decision, and an integrated output is calculated. The performance of the developed method is compared against that of the support vector machine and the decision tree methods. Three experiments are performed using lung scans of 32 patients including thousands of images within which nodule locations are marked by expert radiologists. The classification errors and execution times are presented and discussed. The lowest classification error (2.4%) has been produced by the developed method.

Empirical evaluation of segmentation algorithms for lung modelling

Lung modelling has emerged as a useful method for diagnosing lung diseases. Image segmentation is an important part of lung modelling systems. The ill-defined nature of image segmentation makes automated lung modelling difficult. Also, low resolution of lung images further increases the difficulty of the lung image segmentation. It is therefore important to identify a suitable segmentation algorithm that can enhance lung modelling accuracies. This paper investigates six image segmentation algorithms, used in medical imaging, and also their application to lung modelling. The algorithms are: normalised cuts, graph, region growing, watershed, Markov random field, and mean shift. The performance of the six segmentation algorithms is determined through a set of experiments on realistic 2D CT lung images. An experimental procedure is devised to measure the performance of the tested algorithms. The measured segmentation accuracies as well as execution times of the six algorithms are then compared and discussed.

New system to help detect lung cancer

The article tells about the development of an intelligent system that can improve early detection of lung tissue abnormalities.

Impaired muscle Ca2+ and K+ regulation contribute to poor exercise performance post-lung transplantation

Lung transplant recipients (LTx) exhibit marked peripheral limitations to exercise. We investigated whether skeletal muscle Ca2+ and K+ regulation might be abnormal in eight LTx and eight healthy controls. Peak oxygen consumption and arterialized venous plasma [K+] (where brackets denote concentration) were measured during incremental exercise. Vastus lateralis muscle was biopsied at rest and analyzed for sarcoplasmic reticulum Ca2+ release, Ca2+ uptake, and Ca2+-ATPase activity rates; fiber composition; Na+-K+-ATPase (K+-stimulated 3-O-methylfluorescein phosphatase) activity and content ([3H]ouabain binding sites); as well as for [H+] and H+-buffering capacity. Peak oxygen consumption was 47% less in LTx (P < 0.05). LTx had lower Ca2+ release (34%), Ca2+ uptake (31%), and Ca2+-ATPase activity (25%) than controls (P < 0.05), despite their higher type II fiber proportion (LTx, 75.0 ± 5.8%; controls, 43.5 ± 2.1%). Muscle [H+] was elevated in LTx (P < 0.01), but buffering capacity was similar to controls. Muscle 3-O-methylfluorescein phosphatase activity was 31% higher in LTx (P < 0.05), but [3H]ouabain binding content did not differ significantly. However, during exercise, the rise in plasma [K+]-to-work ratio was 2.6-fold greater in LTx (P < 0.05), indicating impaired K+ regulation. Thus grossly subnormal muscle calcium regulation, with impaired potassium regulation, may contribute to poor muscular performance in LTx.

Automatic detection of lung nodule from computer tomography images

Lung nodule refers to lung tissue abnormalities that may become cancerous. An automated system that detects nodules of common sizes within lung images is developed. It consists of acquisition, pre-processing, background removal, nodule detection, and false positives reduction. The system can assist expert radiologists in their decision making.

A systematic review of the quality of liver biopsy specimens

Characteristics for an optimal liver biopsy specimen were recently defined as 20 to 25 mm long and/or containing more than 11 complete portal tracts (CPTs). A systematic review of percutaneous liver biopsy (PLB) and transjugular liver biopsy (TJLB) series yielded only 32 PLB studies in which these characteristics were evaluated: mean ± SD length, 17.7 ± 5.8 mm and number of CPTs, 7.5 ± 3.4; and 15 TJLB studies: mean ± SD length, 13.5 ± 4.5 mm and number of CPTs, 6.8 ± 2.3. Studies of sampling heterogeneity and intraobserver and interobserver variability also used inadequate specimens by present standards. Only 11 (5.3%) of 207 therapeutic studies for chronic hepatitis B and C documented length and/or number of CPTs. Of the current 12 studies evaluating noninvasive fibrosis tests, only 8 documented length or number of CPTs, and only 1 documented length and number of CPTs. New studies are needed based on adequate liver biopsy samples to provide reliable estimation of grading and staging in chronic liver disease.

Automatic extraction of abnormal regions from lung images

A system that could automatically extract abnormal lung regions may assist expert radiologists in verifying lung tissue abnormalities. This paper presents an automated lung nodule detection system consisting of five components: acquisition, pre-processing, background removal, detection, and false positives reduction. The system employs a combination of an ensemble classification and clustering methods. The performance of the developed system is compared against some existing counterparts. Based 011 the experimental results, the proposed system achieved a sensitivity of 100% and a false-positives/slice of 0.67 for 30 tested CT images.