Automated in vivo quantification of emphysema

Automated lung volumetry from routine thoracic CT scans: how reliable is the result?

RATIONALE AND OBJECTIVES

Today, lung volumes can be easily calculated from chest computed tomography (CT) scans. Modern postprocessing workstations allow automated volume measurement of data sets acquired. However, there are challenges in the use of lung volume as an indicator of pulmonary disease when it is obtained from routine CT. Intra-individual variation and methodologic aspects have to be considered. Our goal was to assess the reliability of volumetric measurements in routine CT lung scans.

MATERIALS AND METHODS

Forty adult cancer patients whose lungs were unaffected by the disease underwent routine chest CT scans in 3-month intervals, resulting in a total number of 302 chest CT scans. Lung volume was calculated by automatic volumetry software. On average of 7.2 CT scans were successfully evaluable per patient (range 2-15). Intra-individual changes were assessed.

RESULTS

In the set of patients investigated, lung volume was approximately normally distributed, with a mean of 5283 cm(3) (standard deviation = 947 cm(3), skewness = -0.34, and curtosis = 0.16). Between different scans in one and the same patient the median intra-individual standard deviation in lung volume was 853 cm(3) (16% of the mean lung volume).

CONCLUSIONS

Automatic lung segmentation of routine chest CT scans allows a technically stable estimation of lung volume. However, substantial intra-individual variations have to be considered. A median intra-individual deviation of 16% in lung volume between different routine scans was found.

Are airflow obstruction and radiographic evidence of emphysema risk factors for lung cancer? A nested case-control study using quantitative emphysema analysis

OBJECTIVES

Several studies have identified airflow obstruction as a risk factor for lung cancer independent of smoking history, but the risk associated with the presence of radiographic evidence of emphysema has not been extensively studied. We proposed to assess this risk using a quantitative volumetric CT scan analysis.

METHODS

Sixty-four cases of lung cancer were identified from a prospective cohort of 1,520 participants enrolled in a spiral CT scan lung cancer screening trial. Each case was matched to six control subjects for age, sex, and smoking history. Quantitative CT scan analysis of emphysema was performed. Spirometric measures were also conducted. Data were analyzed using conditional logistic regression making use of the 1:6 set groups of 64 cases and 377 matched control subjects.

RESULTS

Decreased FEV(1) and FEV(1)/FVC were significantly associated with a diagnosis of lung cancer with ORs of 1.15 (95% CI, 1.00-1.32; P = .046) and 1.29 (95% CI, 1.02-1.62; P = .031), respectively. The quantity of radiographic evidence of emphysema was not found to be a significant risk for lung cancer with OR of 1.042 (95% CI, 0.816-1.329; P = .743). Additionally, there was no significant association between severe emphysema and lung cancer with OR of 1.57 (95% CI, 0.73-3.37).

CONCLUSIONS

We confirm previous observations that airflow obstruction is an independent risk factor for lung cancer. The absence of a clear relationship between radiographic evidence of emphysema and lung cancer using an automated quantitative volumetric analysis may result from different population characteristics than those of prior studies, radiographic evidence of emphysema quantitation methodology, or absence of any relationship between emphysema and lung cancer risk.

Avaliação computacional de enfisema pulmonar em TC: comparação entre um sistema desenvolvido localmente e um sistema de uso livre

OBJETIVO: Apresentar um sistema de visão computacional em imagens de TCAR, desenvolvido localmente e denominado SIStema para a Detecção e a quantificação de Enfisema Pulmonar (SISDEP). Comparar esse sistema a um sistema computacional de acesso livre. MÉTODOS: Foram utilizadas 33 imagens de TCAR de 11 pacientes com DPOC com cortes tomográficos em ápice, hilo e base. O SISDEP foi comparado a Osiris Medical Imaging Software Program quanto à segmentação do parênquima pulmonar; precisão das medidas da área de secção transversal dos pulmões em mm², densidade pulmonar média (DPM), porcentagem da relative area (RA, área relativa) dos voxels com densidade < -950 unidades hounsfield (ra -950), valores de 15º percentil de baixa atenuação (perc15) e visualização das áreas hiperaeradas por máscara colorida. RESULTADOS: Os dois sistemas realizaram uma segmentação pulmonar eficiente; porém o SISDEP o fez de modo automático e mais rápido. Na comparação das medidas de área de secção dos pulmões, DPM, Perc15 e RA -950, houve alta correlação (r² = 0,99; 0,99; 0,99; e 1,00, respectivamente) entre os dois sistemas. A ferramenta de máscara colorida do SISDEP permitiu excelente visualização das áreas hiperaeradas, discriminado-as das áreas normais. CONCLUSÕES: O SISDEP se mostrou eficiente na segmentação dos pulmões e na extração de dados quantitativos da aeração pulmonar com excelente correlação com o sistema Osiris. O SISDEP constitui uma promissora ferramenta computacional para a avaliação diagnóstica e o acompanhamento da evolução do enfisema em imagens de TCAR de pacientes com DPOC.

Lung Density Measurements in Spontaneous Pneumothorax Demonstrate Airtrapping

PURPOSE

Idiopathic spontaneous pneumothorax (SP) is the result of leakage of air from the lung parenchyma through a ruptured visceral pleura into the pleural cavity. This rupture is thought to be caused by an increased pressure difference between parenchymal airspace and pleural cavity. We hypothesize that rather peripheral airway inflammation leads to obstruction with check valve phenomena and by that to airtrapping in the lung parenchyma, which precedes spontaneous pneumothorax.

SETTING

University hospital.

MATERIALS AND METHODS

Forty-one matched healthy volunteers (21 smokers and 20 nonsmokers), and 41 patients with SP (21 patients with and 20 patients without bullae) underwent spirometrically controlled high-resolution CT density measurements with automatic contour tracing at 10% and at 90% of vital capacity.

RESULTS

Patients with SP showed lower mean lung density (MLD) values and higher percentages of Hounsfield units (HU) below - 900 HU (pixel index [PI]) compared to the healthy volunteers on expiratory scans. This enhanced airtrapping phenomenon is seen in both the SP lung (MLD, p = 002; PI, p = 0.01) and the contralateral lung (MLD, p = 0.009; PI, p = 0.05) compared to the control subjects. The difference with control subjects is independent of smoking behavior and bullae.

CONCLUSIONS

Peripheral airway obstruction with airtrapping was found, and it is supposed to play an important role in the pathogenesis of spontaneous pneumothorax.

Automated lung segmentation in X-ray computed tomography: development and evaluation of a heuristic threshold-based scheme

RATIONALE AND OBJECTIVES

To develop and evaluate a reliable, fully-automated lung segmentation scheme for application in X-ray computed tomography.

MATERIALS AND METHODS

The automated scheme was heuristically developed using a slice-based, pixel-value threshold and two sets of classification rules. Features used in the rules include size, circularity, and location. The segmentation scheme operates slice-by-slice and performs three key operations: (1) image preprocessing to remove background pixels, (2) computation and application of a pixel-value threshold to identify lung tissue, and (3) refinement of the initial segmented regions to prune incorrectly detected airways and separate fused right and left lungs.

RESULTS

The performance of the automated segmentation scheme was evaluated using 101 computed tomography cases (91 thick slice, 10 thin slice scans). The 91 thick cases were pre- and post-surgery from 50 patients and were not independent. The automated scheme successfully segmented 94.0% of the 2,969 thick slice images and 97.6% of the 1,161 thin slice images. The mean difference of the total lung volumes calculated by the automated scheme and functional residual capacity plus 60% inspiratory capacity was -24.7 +/- 508.1 mL. The mean differences of the total lung volumes calculated by the automated scheme and an established, commonly used semi-automated scheme were 95.2 +/- 52.5 mL and -27.7 +/- 66.9 mL for the thick and thin slice cases, respectively.

CONCLUSION

This simple, fully-automated lung segmentation scheme provides an objective tool to facilitate lung segmentation from computed tomography scans.

Automated storage and retrieval of thin-section CT images to assist diagnosis: system description and preliminary assessment

A software system and database for computer-aided diagnosis with thin-section computed tomographic (CT) images of the chest was designed and implemented. When presented with an unknown query image, the system uses pattern recognition to retrieve visually similar images with known diagnoses from the database. A preliminary validation trial was conducted with 11 volunteers who were asked to select the best diagnosis for a series of test images, with and without software assistance. The percentage of correct answers increased from 29% to 62% with computer assistance. This finding suggests that this system may be useful for computer-assisted diagnosis.

Relationship between lung function, ventilation-perfusion inequality and extent of emphysema as assessed by high-resolution computed tomography

The development of the high-resolution computed tomography (HRCT) has improved the ability to detect and quantify emphysema in various groups of patients with chronic airflow obstruction (COPD). Significant correlations have previously been found between indices of air flow obstruction, hyperinflation, reduced diffusing capacity for carbon monoxide (DLCO), and the extent of emphysema (emph.%) assessed by HRCT. However, the relationship between emph.% and ventilation-perfusion (V(A)/Q) inequality in COPD is unknown. Twenty COPD patients with a mean forced expiratory volume in 1 s (FEV1) of 38.2 (+/- 15.5)% in percent of predicted value (%P), a mean PaO2 value of 9.6 (+/- 1.3) kPa, and a mean diffusing capacity of 43.6 (+/- 23.0)%P, were subjected to measurements by the multiple elimination inert gas technique (MIGET). The extent of emphysema was determined by HRCT at both full inspiration, emph.I(%) and at full expiration, emph.E(%), with a cut-off limit of -910 Hounsfield Units (HU) using the "Density Mask" method. The ventilation directed towards high V(A)/Q areas was 73 (+/- 10.2)% and the mean ventilation (V-mean) was elevated about three times compared to normal. The mean emph.(I)% and emph.(E) was 45.6 (+/- 16.9) and 32.7 (+/- 190)%, respectively. Significant correlations were shown between the emphysema extent and several lung function parameters, but no correlation was found between the emphysema extent and the V(A)/Q relationships or the blood gas values. Reduced DLCO%P correlated with less high V(A)/Q ventilation (r=0.73, P < 0.05) for the subgroup of COPD patients with DLCO(%P) less than 50% (n=12).

CONCLUSIONS

In COPD patients, suffering from moderate to severe emphysema without severe blood gas impairment, no correlation was shown between the extent of emphysema, as assessed by HRCT, and the severity of ventilation-perfusion inequality. A substantial collateral ventilation in severe emphysema may be a mechanism that prevents a deterioration in V(A)/Q relationships and in blood gas levels.

Prediction of postoperative lung function in patients with lung cancer: comparison of quantitative CT with perfusion scintigraphy

OBJECTIVE

Prediction of postoperative lung function is important in preoperative evaluation of patients with lung cancer. Perfusion scintigraphy is the current method to assess the fractional contribution of lung function of the remaining lung. We developed a quantitative CT method and compared it with perfusion scintigraphy for predictions of postoperative forced expiratory volume in 1 sec (FEV1) in patients with lung cancer.

SUBJECTS AND METHODS

Forty-four patients with lung cancer undergoing lung resection with preoperative CT and perfusion scintigraphy were enrolled. Quantitative CT used a dual threshold (-500 and -910 H) on standard preoperative CT to semiautomatically extract lung volume without emphysema or tumor and atelectasis, which we defined as "functional lung volume." Prediction was calculated from preoperative FEV1 multiplied by the fractional contribution of functional lung volume of the remaining lung by quantitative CT. Perfusion scintigraphy was the standard method. Predictions were correlated with postoperatively measured FEV1.

RESULTS

Both quantitative CT and perfusion scintigraphy predicted postoperative FEV1 well in patients who underwent pneumonectomy (n = 28, r = 0.88 vs r = 0.86) and in lobectomy (n = 16, r = 0.90 vs r = 0.80) (both, p < 0.001). There was good agreement between the two methods by the Bland-Altman method. In the four patients with low measured postoperative FEV1 (<40% predicted normal), quantitative CT had true-positive prediction in four and perfusion scintigraphy, in only two.

CONCLUSION

Given its simplicity, we proposed that quantitative CT be widely used in predicting postoperative FEV1.

Quantitative CT of the lung

Lung disease is a leading cause of morbidity and mortality. HRCT, currently the best test to assess lung involvement in emphysema and interstitial lung disease, relies on abnormalities being detected when there is sufficient morphologic distortion to result in visually identified changes that, for the most part, correlate poorly with conventional lung function tests and outcome. QIA offers a technique to assess both structure and function on a regional and global basis. With the advent of user-friendly software packages, this approach is finding application in clinical practice and in clinical studies of new treatment alternatives for diffuse lung disease

Automated CT image evaluation of the lung: a morphology-based concept

Computed tomography (CT) provides the most reliable method to detect emphysema in vivo. Commonly used methods only calculate the area of low attenuation [pixel index (PI)], while a radiologist considers the bullous morphology of emphysema. The PI is a good, well-known measure of emphysema. But it is not able to detect emphysema in cases in which emphysema and fibrosis occur at the same time. This is because fibrosis leads to a low number of low-attenuation pixels, while emphysema leads to a high number of pixels. The PI takes the average of both and, consequently, may present a result within the normal range.

METHOD

The main focus of this paper is to present a new algorithm of thoracic CT image evaluation based on pulmonary morphology of emphysema. The PI is extended, in that it is enabled to differentiate between small, medium, and large bullae (continuous low-attenuation areas). It is not a texture-based algorithm. The bullae are sorted by size into four size classes: class 1 being within the typical size of lung parenchyma; classes 2-4 presenting small, medium, and large bullae. It is calculated how much area the different classes take up of all low-attenuation pixels. The bullae index (BI) is derived from the percentage of areas covered, respectively, by small, medium, and large bullae. From the relation of the area of bullae belonging to class 4, to that of those belonging to class 2, a measure of the emphysema type (ET)is calculated. It classifies the lung by the type of emphysema in bullous emphysema or small-sized, diffuse emphysema, respectively.

RESULTS

The BI is as reliable as the PI. In cases in which the PI indicates normal values while in fact emphysema is coexisting with fibrosis, the BI, nevertheless, detects the destruction caused by the emphysema. The BI combined with the ET reflects the visual assessment of the radiological expert.

CONCLUSION

The BI is an objective and reliable index in order to quantify emphysematous destruction, hence, avoiding interobserver variance. This is particularly interesting for follow-up. The classification of the ET is a helpful and unique approach to achieving an exact diagnosis of emphysema.

Quantitation of emphysema with three-dimensional CT densitometry: comparison with two-dimensional analysis, visual emphysema scores, and pulmonary function test results

PURPOSE

To compare lung densitometric measurements that use a three-dimensional (3D) reconstruction of the lungs with those obtained from analysis of two-dimensional (2D) computed tomographic (CT) images, visual emphysema scores, and data from pulmonary function tests.

MATERIALS AND METHODS

Thoracic helical CT scans were obtained in 60 adult patients (35 with no visual evidence of emphysema and 25 with emphysema). The lungs were reconstructed as a 3D model on a commercial workstation, with a threshold of -600 HU. By analysis of histograms, the proportions of lung volumes with attenuation values below -950, -910, and -900 HU were measured, in addition to mean lung attenuation. These values were compared with lung densitometric results obtained from 2D CT images, visual emphysema scores, and data from pulmonary function tests.

RESULTS

Quantitation of emphysema with 3D reconstruction was efficient and accurate. Correlation was good among densitometric quantitation with 3D analysis, that obtained with 2D analysis (r = 0.98-0.99), and visual scoring (r = 0.74-0.82). Correlation was reasonable between 3D densitometric quantitation and the diffusing capacity of the lungs for carbon monoxide (DLCO) (r = -0.57 to -0.64), total lung capacity (r = 0.62-0.71), forced expiratory volume in 1 second (FEV1) (r = -0.57 to -0.60), and the ratio of FEV1 to forced vital capacity (FVC) (r = -0.75 to -0.82). The visual CT quantitation of emphysema correlated best with DLCO (r = -0.82) and FEV1/FVC (r = -0.89).

CONCLUSION

Lung densitometry with 3D reconstruction of helical CT data is a fast and accurate method for quantifying emphysema.

Lung volumes before and after lung volume reduction surgery: quantitative CT analysis

The volume and severity of pulmonary emphysema in individual lungs were measured by means of quantitative computed tomography (CT) studies in 28 patients (14 women, 14 men, median age 65 yr) who underwent either bilateral (n = 15) or unilateral (n = 13) lung volume reduction surgery (LVRS). Spirometric, total body plethysmographic, and CT data (at TLC and RV) were correlated before and after LVRS. Lung volumes determined by CT correlated well with volumes obtained by total body plethysmography (p < 0.0001). For individual lungs after LVRS, CT-derived mean lung capacity decreased 13% and residual volume 20% (p < 0.00001 for each), while mean total functional lung volume (TFLV, defined as the volume of lung with CT attenuation greater than -910 Hounsfield units) increased 9% (p < 0.01), and the mean ratio of the air space to tissue space volume (V(AS)/V(TS)) decreased more at RV (23%) than at TLC (14%) (p < 0.0005 for each). In contrast, unilateral LVRS did not affect exhalation from the unoperated lung (2% reduction in RV, p = NS). The magnitude of the postoperative response (CT-derived TLC, RV, TFLV, V(AS)/V(TS)) of each operated lung was comparable for unilateral and bilateral LVRS. Thus, a lung's response to LVRS was independent from that of the contralateral lung. Moreover, postoperative alterations in TFLV and FEV1 correlated significantly (r = 0.80, p < 0.0001), which suggests that the expansion of functioning tissue may contribute to the mechanism by which LVRS palliates airway obstruction.

Method for segmenting chest CT image data using an anatomical model: preliminary results

We present an automated, knowledge-based method for segmenting chest computed tomography (CT) datasets. Anatomical knowledge including expected volume, shape, relative position, and X-ray attenuation of organs provides feature constraints that guide the segmentation process. Knowledge is represented at a high level using an explicit anatomical model. The model is stored in a frame-based semantic network and anatomical variability is incorporated using fuzzy sets. A blackboard architecture permits the data representation and processing algorithms in the model domain to be independent of those in the image domain. Knowledge-constrained segmentation routines extract contiguous three-dimensional (3-D) sets of voxels, and their feature-space representations are posted on the blackboard. An inference engine uses fuzzy logic to match image to model objects based on the feature constraints. Strict separation of model and image domains allows for systematic extension of the knowledge base. In preliminary experiments, the method has been applied to a small number of thoracic CT datasets. Based on subjective visual assessment by experienced thoracic radiologists, basic anatomic structures such as the lungs, central tracheobronchial tree, chest wall, and mediastinum were successfully segmented. To demonstrate the extensibility of the system, knowledge was added to represent the more complex anatomy of lung lesions in contact with vessels or the chest wall. Visual inspection of these segmented lesions was also favorable. These preliminary results suggest that use of expert knowledge provides an increased level of automation compared with low-level segmentation techniques. Moreover, the knowledge-based approach may better discriminate between structures of similar attenuation and anatomic contiguity. Further validation is required.

Evaluation of emphysema in patients with reversible airway obstruction using high-resolution CT

OBJECTIVE

This study was carried out to determine whether asthma affects the development of emphysema.

METHODS

We studied 62 patients with reversible airway obstruction during remission, and evaluated the presence and severity of emphysema using high-resolution CT. The emphysema score (ES) was evaluated with the visual scoring method on CT scans.

RESULTS

Of the 62 patients, 14 were judged to have emphysema. Patients with emphysema were significantly older and more likely to be male than those without emphysema. All patients with emphysema were smokers. There was no significant difference in the duration or severity of asthma between patients with and without emphysema. The 62 patients were divided into three groups according to the ES: 48 patients without emphysema (ES = 0%), 8 patients with mild emphysema (0% < ES < 15%), and 6 patients with more severe emphysema (ES > or = 15%). Highly significant differences between patients without emphysema and those with more severe emphysema were found in FEV1 (p<0.01), FEV1/FVC (p<0.001), diffusing capacity for carbon monoxide (DCO) (p<0.01), and DCO/alveolar volume (p<0.0001).

CONCLUSION

Neither the duration nor the severity of asthma was correlated with the presence of emphysema, while smoking history, sex, and age were strongly correlated. No patients with emphysema were found among the nonsmokers, including those with severe asthma or asthma of long duration. These results suggest that asthma does not lead to emphysema.

CT lung densitometry: dependence of CT number histograms on sample volume and consequences for scan protocol comparability

PURPOSE

Our goals were to determine the dependence of CT number histograms of the lung on section thickness and reconstruction filter and to evaluate the consequences for scan protocol conformity required for universally comparable densitometry of the lungs.

METHOD

The effects of section thickness and reconstruction filter were parameterized with the CT's sample volume [V approximately (section thickness x in-plane resolution2)]. In a study of 31 patients, we determined as a function of V the following CT number histogram parameters: percentiles P(10) and P(90), pixel indexes PI(-905) and PI(-950), and standard deviation.

RESULTS

Patient histogram parameters depended strongly on sample volume. Large differences were found between protocols using 1 and 10 mm sections. For small variations in somewhat larger sample volumes (> 8 mm3), discrepancies were much smaller.

CONCLUSION

To obtain comparable histogram parameters, nearly identical sample volumes (> or = 8 mm3) should be used. When this condition is satisfied, available data suggest that universally comparable densitometry is feasible.

Usual interstitial pneumonia. Quantitative assessment of high-resolution computed tomography findings by computer-assisted texture-based image analysis

RATIONALE AND OBJECTIVES

The authors developed a texture-based pattern recognition and segmentation tool for the quantitation of high-resolution computed tomography (HRCT) findings in usual interstitial pneumonia (UIP).

METHODS

In HRCT images of five patients with UIP and five patients without UIP, 1022 regions of interest (ROIs) of 5 x 5 pixels were classified by the examiner to be normal, emphysematous, ground-glass lesion, intralobular fibrosis, vessel, or bronchus section. The classes and the texture parameters calculated in the ROIs were the basis for the decision rule, using a multivariate discrimination analysis. The classification was compared with the examiner's diagnosis in 1889 new randomly selected ROIs.

RESULTS

Depending on the structure, the sensitivity (the probability that a structure would be recognized correctly) was 68.7% to 80.7%. If the system classified a structure as normal, ground glass or fibrotic region, this was correct in 77.3% to 88.1%. However, the system's diagnosis of a bronchus section was correct in only 16.2%. The overall accuracy was 70.7%.

CONCLUSIONS

Texture-based segmentation may be a valuable tool to aid the quantitative assessment of parenchymal disease in HRCT images.

Quantification of pulmonary emphysema from lung computed tomography images

A texture-based adaptive multiple feature method (AMFM) for evaluating pulmonary parenchyma from computed tomography (CT) images is described. This method incorporates multiple statistical and fractal texture features. The AMFM was compared to two previously published methods, namely, mean lung density (MLD) and the lowest fifth percentile of the histogram (HIST). First, the ability of these methods to detect subtle differences in ventral-dorsal lung density gradient in the prone normal lung was studied. Second, their abilities to differentiate between normal and emphysematous whole lung slices were compared. Finally, regional analyses comparing normal and emphysematous regions were performed by dividing the lungs. In the CT slices into six equal regions, ventral to dorsal, and analyzing each region separately. The results demonstrated that the AMFM could separate the ventral from the dorsal one-third of the normal prone lung with 89.8% accuracy, compared to an accuracy of 74.6% with the MLD and 64.4% with the HIST methods. The normal and emphysematous slices were separated on a global basis with 100.0% accuracy using the AMFM as compared to an accuracy of 94.7% and 97.4% using the MLD and HIST methods, respectively. The regional normal and emphysematous tissues were discriminated with an average accuracy of 97.9%, 89.9%, and 99.1% with the AMFM, MLD, and HIST methods, respectively. The three methods and the pulmonary function tests in the normal and emphysema groups were poorly correlated. Quantitative texture analysis using adaptive multiple features holds promise for the objective noninvasive evaluation of the pulmonary parenchyma.

Assessment of the progression of emphysema by quantitative analysis of spirometrically gated computed tomography images

RATIONALE AND OBJECTIVES

The authors assessed the progression of pulmonary emphysema by means of quantitative analysis of computed tomography images.

METHODS

Twenty-three patients suffering from emphysema due to an alpha 1-antitrypsin deficiency, aged 45 +/- 7 years and exsmokers, were scanned twice with a 1-year time interval. At 90% of the vital lung capacity, slices with a thickness of 1.5 mm were acquired at the level of the carina and 5 cm above the carina; slices with a thickness of 1 cm were acquired 5 cm below the carina. The entire lung was scanned spirally at a respiratory status, corresponding with 75% of the total lung capacity at baseline. The mean lung densities (MLD) were calculated in an objective manner with new analytic software featuring automated detection of the lung contours.

RESULTS

Mean lung densities decreased by 14.2 +/- 12.0 Hounsfield units (HU; P < 0.001) above the carina, by 18.1 +/- 14.4 HU (P < 0.001) at the carina level, by 23.6 +/- 15.0 HU (P < 0.001) below the carina, and by 12.8 +/- 22.2 HU (P < 0.01) for the entire lung. The decrease in MLD was most obvious in the lower lung lobes. For the same patient group, the annual decrease in the forced expiratory volume (FEV1) and the carbon monoxide-diffusion were 120 +/- 190 mL (P < 0.01) and 10 +/- 70 mmol/kg/minute ( P < 0.2), respectively. No significant correlation was found between the decrease in MLD and the decrease in FEV1.

CONCLUSIONS

Progression of emphysema can be assessed in an objective manner based on the mean lung density (MLD), measured from computed tomography volume scans as well as from single-slice scans. Mean lung density has proved to be more sensitive than FEV1 and carbon monoxide-diffusion.

CT densitometry of the lungs: scanner performance

OBJECTIVE

Our goal was to establish the reproducibility and accuracy of the CT scanner in densitometry of the lungs.

MATERIALS AND METHODS

Scanner stability was assessed by analysis of daily quality checks. Studies using a humanoid phantom and polyethylene foams for lung were performed to measure reproducibility and accuracy. The dependence of the CT-estimated density on reconstruction filter, zoom factor, slice thickness, table height, data truncation, and objects outside the scan field was determined.

RESULTS

Stability of the system at air density was within approximately 1 HU and at water density within approximately 2 HU. Reproducibility and accuracy for densities found for lung were within 2-3%. Dependence on the acquisition and reconstruction parameters was neglible, with the exceptions of the ultra high resolution reconstruction algorithm in the case of emphysema, and objects outside the scan field.

CONCLUSION

The performance of the CT scanner tested is quite adequate for densitometry of the lungs.

Macroscopic assessment of pulmonary emphysema by image analysis

AIMS

To propose a computerised image analysis based method for measuring, on paper mounted lung sections, the area macroscopically occupied by emphysema.

METHODS

The study was based on the assessment of 69 lung sections prepared following a modified Gough-Wentworth technique. The results obtained from image analysis, point counting, and panel grading methods were compared, as was the repeatability of image analysis and panel grading.

RESULTS

The results from image analysis and from point counting were not significantly different (p = 0.609) and significant quadratic regressions (r = 0.96, p < 0.001) were found between measurements from image analysis and from panel grading, the computerised technique being shown to be the most reproducible.

CONCLUSIONS

Image analysis is a valuable and reproducible method to measure the area of lung macroscopically involved by emphysema.

Regional ventilatory evaluation using dynamic SPET imaging of xenon-133 washout in obstructive lung disease: an initial study

Regional ventilatory abnormalities in obstructive lung disease were evaluated by dynamic single-photon emission tomography (SPET) of pulmonary washout of xenon-133 (133Xe) gas. The subjects included seven healthy volunteers. 17 patients with obstructive lung disease, and seven patients with restrictive lung disease. Following 6 min of inhalation of 133Xe gas (60-72 MBq/l), equilibrium and subsequent washout SPET images during spontaneous breathing were sequentially acquired every 30 s for 6-7 min, using a triple-head SPET system with the return mode of continuous repetitive rotating acquisition. A gravity-induced gradient of ventilation was demonstrated in the volunteers' lungs. Compared with the normal subjects, all the patients with obstructive disease showed abnormal 133Xe retention on the washout SPET images, with or without abnormalities on chest X-ray computed tomography, whereas the patients with restrictive disease did not show any significant delays in washout. This modality may assist in the evaluation of the three-dimensional dynamic process of ventilatory abnormalities in obstructive lung disease.