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J Thorac Cardiovasc Surg 2006;131:994-1001
© 2006 The American Association for Thoracic Surgery

General Thoracic Surgery

Breath-hold single-photon emission tomography and computed tomography for predicting residual pulmonary function in patients with lung cancer

Manabu Sudoh, MD a , Kazuhiro Ueda, MD a , * , Yoshikazu Kaneda, MD a , Jinbo Mitsutaka, MD a , Tao-Sheng Li, MD a , Kazuyoshi Suga, MD b , Yasuhiko Kawakami, MD b , Kimikazu Hamano, MD a

a Division of Thoracic Surgery, Department of Medical Bioregulation, Yamaguchi University School of Medicine, Yamaguchi, Japan
b Division of Radiology, Department of Radiopathology and Science, Yamaguchi University School of Medicine, Yamaguchi, Japan

Received for publication July 26, 2005; revisions received November 20, 2005; accepted for publication December 22, 2005.

* Address for reprints: Kazuhiro Ueda, MD, Division of Thoracic Surgery, Department of Medical Bioregulation, Yamaguchi University School of Medicine, 1-1-1 Minami-Kogushi, Ube, Yamaguchi, 755-8505, Japan (Email: kaueda{at}c-able.ne.jp).


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
OBJECTIVE: We sought to evaluate the utility of integrated breath-hold single-photon emission tomography and computed tomography imaging compared with that of simple calculation with the lung segment–counting technique for predicting residual pulmonary function in patients undergoing surgical intervention for lung cancer.

METHODS: A prospective series of 22 patients undergoing anatomic lung resection for cancer were enrolled in this study. Postoperative residual forced expiratory volume in 1 second was predicted by measuring the radioactivity counts of the affected lobes or segments to be resected within the entire lungs by placement of regions of interest on single-photon emission tomography and computed tomography images. Residual forced expiratory volume in 1 second was also estimated by using the segment-counting technique.

RESULTS: Both predicted values agreed well with postoperative forced expiratory volume in 1 second. Although the residual forced expiratory volume in 1 second predicted by means of single-photon emission tomography and computed tomography correlated well with that predicted by using segment counting, the values were significantly underestimated by the segment-counting technique in 4 outliers with severe emphysema. There were 2 patients with borderline pulmonary functional reserve whose residual forced expiratory volume in 1 second values were predicted more accurately by means of single-photon emission tomography and computed tomography than by using segment counting.

CONCLUSION: Integrated breath-hold single-photon emission tomography and computed tomography images allow the accurate prediction of postoperative pulmonary function but without statistical superiority over the simple segment-counting technique. Further study of the usefulness of single-photon emission tomography and computed tomography in patients with severe emphysema and borderline lung function should prove valuable because the segment-counting technique underestimates pulmonary functional reserve in these patients.

Abbreviations and Acronyms CT = computed tomography; 3D = Three-dimensional; FEV1 = forced expiratory volume in 1 second; FEV1ppo = predicted postoperative forced expiratory volume in 1 second; HU = Hounsfield units; LAA = low-attenuation area; ROI = region of interest; SPET = single-photon emission tomography


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 

Figure 1
M. Sudoh, J. Mitsutaka, K. Hamano, K. Ueda, Y. Kaneda (left to right)


For patients with primary lung cancer, surgical resection remains the only potentially curative option. However, chronic underlying lung diseases often limit operability. Because predicted pulmonary functional reserve is the most important determinant for the decision to perform pulmonary resection, 1-3 Go extensive effort has been made to accurately predict postoperative pulmonary function by using various diagnostic modalities. The simple lung segment–counting technique is widely used to estimate postoperative pulmonary function by counting the number of functioning segments that will be reserved and the number of those that will be resected. 4 Go However, this will provide an accurate prediction only if all the functioning segments are functioning equally preoperatively and postoperatively. For patients with heterogeneous lung diseases, Tc-99m–macroaggregated albumin perfusion single-photon emission tomography (SPET) has been widely used to evaluate regional lung function. 5-8 Go However, in standard non–breath-hold SPET, respiratory lung motion and cyclically varying lung volume changes during image acquisition degrade image sharpness and complicate accurate identification of the areas corresponding with the lobes or segments to be resected.

At our institute, to solve these problems on standard perfusion SPET, we have recently introduced breath-hold perfusion SPET images acquired with a triple-headed SPET system and a laser-light respiratory tracking device. 9-11 Go These images are also used for obtaining reliable integrated images with routine breath-hold computed tomography (CT) images. 10,11 Go We expect that these SPET and integrated images will help to predict postoperative pulmonary function by providing accurate assessment of perfusion impairment and correlation with lung anatomy and might be superior to the simple segment-counting technique for this prediction. We conducted this study to evaluate the feasibility of using these images to predict postoperative pulmonary function in patients with lung cancer by comparing them with the simple lung segment–counting technique.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Study Subjects
The subjects of this prospective study were 22 patients who underwent anatomic lung resection for cancer. All patients underwent a pulmonary function test, thin-slice high-resolution CT, and breath-hold perfusion SPET studies. The patients' characteristics are shown in Table 1. Nineteen patients had peripheral-type tumors, and 3 had central-type tumors. The CT images showed varying degrees of focal low-attenuation areas (LAAs) representative of emphysematous changes with or without bullae in all 22 patients. The number of resected subsegments was 10.5 ± 4.3 for lobectomy and 6.0 ± 2.5 for segmentectomy. All patients were informed about the research protocol, which was approved by our institutional review board.


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  		TABLE 1. Patient characteristics *
 
Breath-hold Perfusion SPET
Breath-hold perfusion SPET images were obtained by using a triple-headed SPET unit (GCA 9300 A/PI; Toshiba Medical System, Tokyo, Japan) and a laser-light respiratory tracking device (AZ-733; Anzai Sogyo Co, Osaka, Japan). Each patient was placed in the supine position, as in CT scanning, and a laser-light reflex plate was attached to the thoracic or abdominal wall to show the maximum respiratory movement. The laser-light reflex system was connected to a physiologic respiratory tracking device, which was used to monitor respiratory motion on the time-distance curves. We then gave each patient an intravenous injection of 259 MBq (7 mCi) of macroaggregated albumin. Breath-hold image acquisition was intermittently repeated until 5 adequate projection data sets with the same respiratory dimension could be obtained. The maximum difference in respiratory dimension among the 5 projection data sets was only 2.2 ± 0.5 mm on average (range, 1.1-4.3 mm) in all patients. The total examination time for breath-hold SPET imaging ranged from 2 to 6 minutes (mean, 3.5 ± 1.6 minutes). Subsequently, standard non–breath-hold SPET images during rest breathing were acquired by using a step-and-shoot mode.

On the image workstation (GCA 9300 A/DI; Toshiba Medical System, Shibaura, Japan), breath-hold SPET images were reconstructed from every 4° projection of the 5 data sets. Standard non–breath-hold SPET images were reconstructed from every 6° projection. The lung contour was drawn at a threshold of 20% of the maximum radioactivity of the lungs in each patient.

CT Scan and Emphysema Index
CT scans were performed with a 4-detector-row CT scanner (Siemens Volume Zoom; Siemens-Asahi Medical Ltd, Tokyo, Japan). With the patient in the supine position, 3-mm-thick, high-resolution CT images covering the entire lung were obtained in a 512 x 512 matrix during deep inspiratory breath-hold by using 3-mm collimation, with a scan time of 1.0 seconds at 120 to 130 kVp and 220 to 230 mA. Transaxial CT images were reconstructed with the lung algorithm.

To evaluate the distribution and extent of emphysematous lung areas in each patient, we created volume-rendering 3-dimensional (3D) images of lung-volume, LAA, and density-masked images, which highlighted the lung areas with attenuation values of less than –910 Hounsfield units (HU), which were representative of emphysematous areas, by using imaging software (M900 QUADRA; Zio Soft K.K., Osaka, Japan). Threshold limits of –600 to –1024 HU were applied to segment the entire lungs and to exclude soft tissues surrounding the lung and the large vessels within the lung. On 3D LAA and density-masked images, emphysematous areas were visualized as red colors (Figure 1). 3D lung volume images represent lung contours and volumes. By using 3D LAA and lung volume images, the area of emphysema was quantified by using the emphysema index: percentage of the number of voxels with attenuation values of less than –910 HU to the total number of voxels in the entire lungs. 12-16 Go


Figure 1
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  		Figure 1. A, Three-dimensional (3D) lung volume and low-attenuation area (LAA) images (top left), density-masked computed tomographic (CT) image of the lung plane (bottom left), and breath-hold and standard non–breath-hold perfusion single-photon emission CT (SPET) images (right) in a 77-year-old man with adenocarcinoma in the right lower lobe and diffuse emphysema. The red areas on 3D LAA and density-masked CT images represent the distribution of emphysematous areas with CT attenuation values of less than –910 HU. The 3D LAA and density-masked CT images (left) clearly show that this patient has a moderate extent of focal emphysema, with an emphysema index of 18.2%, and a forced expiratory volume in 1 second (FEV 1 ) of 2.64 L. Although heterogeneous perfusion defects were seen on breath-hold and non–breath-hold images at the same transaxial lung plane as in the CT image and in the coronal dorsal lung plane, some defects were more distinct on the breath-hold images (right, arrows). Breath-hold SPET images showed extended perfusion defects at normal lung areas without LAAs. B, Image set of transaxial breath-hold SPET, SPET/CT integrated, and CT images. For regions of interest (ROI) placement (red solid lines) to predict postoperative FEV1 after right middle and lower lobectomy, individual lung lobe borders could be outlined comprehensively by referring to the integrated images, although the borders were unclear on SPET images alone. In this patient the predicted FEV1 of 1.96 L provided on the basis of integrated images was correlated better with the postoperative actual FEV1 of 1.98 L than the predicted value of 1.63 L determined by means of lung segment counting.

 
Integrated Breath-hold Perfusion SPET/CT Images
For the image integration of breath-hold SPET and CT images, DICOM data were electronically transferred to the teleradiologic workstation monitor (GMS 5500 A/DI, Toshiba Medical) and reformatted to a 168 x 168 matrix. Image integration was done with fully automated 3D multi-image registration software (automatic registration tool, Toshiba Medical). 10,11 Go The automated image integration was performed by definition of body contour and clustering of the voxels inside the body contour into a set of connected components by using a rigid body transformation technique. CT images were presented on a gray scale and SPET images were presented on a color scale to distinguish CT from SPET information on integrated images. The gray and color scales could be freely changed for adequate observations. The image integration process was completed within 1 to 2.5 minutes.

Image Interpretation and Data Analysis
Two independent observers (Y.K. and K.S.) with more than 6 years' experience in chest nuclear medicine counted the numbers of defects in all patients to compare the detectability of perfusion defects between breath-hold and standard non–breath-hold SPET images. Only well-defined defects were counted, and if there was inconsistency between the 2 observers, it was judged as a negative defect. For quantitative analysis, regions of interest (ROIs) were manually placed over relatively small defects and the surrounding normal areas, and the lesion–to–normal lung count ratios were calculated on the basis of the mean radioactivity per pixel for each ROI. The sizes of these ROIs ranged from 12 to 34 pixels (mean, 28 ± 14 pixels).

ROIs were placed over the lung areas to be resected by referring to integrated images to evaluate the contribution of integrated breath-hold SPET/CT images in the prediction of postoperative pulmonary function (Figure 1). Postoperative pulmonary function was predicted by using the following equation:


Formula

Postoperative pulmonary function was also predicted by means of a simple calculation with lung subsegment counting, as described by Nakahara and colleagues, 4 Go as follows: Formula where n is the number of obstructed subsegments, and b is the total number of removed subsegments. The total number of pulmonary subsegments was 42, with 10 each in the left upper lobe and left lower lobe, 6 in the right upper lobe, 4 in the right middle lobe, and 12 in the right lower lobe. The n value was calculated from the findings of preoperative fiberbronchoscopy or CT. The FEV1ppo values were compared with actual postoperative values measured 3 to 4 months after the operation.

Statistical Analysis
The unpaired Student t test was used to test relations between categoric variables and numeric variables, and simple regression analysis was used to test relations between numeric variables.


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
Breath-hold SPET images enhanced perfusion defect clarity and detected 46 (26%) additional defects (221 vs 175) compared with standard non–breath-hold images. The lesion-to-normal lung count ratios in the total 81 perfusion defects on breath-hold images were significantly lower than those on standard images (0.22 ± 0.16 vs 0.28 ± 0.19, P < .001).

The use of SPET/CT integrated images allowed comprehensive ROI placement over the lung areas to be resected in all patients (Figures 1-3).Go Go The FEV1ppo estimated on the basis of integrated images was 1.66 ± 0.5 L, and the linear correlation coefficient with postoperative actual FEV1 was 0.914 (P < .0001, Table 2). The FEV1ppo estimated by means of segment counting was 1.59 ± 0.5 L, and the linear correlation coefficient with postoperative FEV1 was 0.911 (P < .0001, Table 2). Both the FEV1ppo estimated on the basis of integrated images and the FEV1ppo estimated by means of segment counting were significantly lower than postoperative actual FEV1 (1.83 ± 0.6 L, both P < .01). The FEV1ppo values estimated on the basis of integrated images and segment counting were well correlated (correlation coefficient = 0.962, Table 2), with the exception of 4 outliers, which had differences of more than 10% of FEV1ppo estimated by means of segment counting (Figure 4). In these outliers FEV1ppo estimated on the basis of integrated images (1.64 ± 0.6 L) agreed well with postoperative actual FEV1 (1.68 ± 0.4 L), although the values were underestimated by using the segment-counting technique (1.35 ± 0.5 L). In these outliers the area of emphysema on density-masked CT images was significantly higher than that in the remaining 18 patients (26% ± 6.3% vs 8% ± 6.1%, P < .001). There were 2 patients with borderline operative pulmonary function as a result of emphysema. Initially, we planned to perform a left upper lobectomy in both patients to resect the primary tumor. In one patient the FEV1ppo values as estimated on the basis of segment counting and integrated images were 0.69 L and 0.76 L, respectively. Postoperatively, this patient recovered without any cardiopulmonary complications, and the FEV1ppo as estimated on the basis of integrated images was closer to the measured value (1.19 L) than the FEV1ppo as estimated by means of segment counting (Figure 2). In the other patient the FEV1ppo values as estimated on the basis of segment counting and integrated images were 0.74 L and 0.62 L, respectively. On the basis of the limited FEV1ppo as estimated on the basis of integrated images, we recommended to the patient that he undergo resection of the left upper segment (S1+2 and S3). By preserving the left lingular segment, the FEV1ppo values as estimated on the basis of segment counting and integrated images were 0.82 L and 0.74 L, respectively. Postoperatively, the patient remained free of cardiopulmonary complications, and the actual FEV1 (0.71 L) correlated well with the FEV1ppo as estimated on the basis of integrated images (Figure 3).


Figure 2
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  		Figure 2. Three-dimensional (3D) lung volume and low-attenuation area (LAA) images (top left), density-masked computed tomographic (CT) image at the lung plane with primary lung cancer (top left, red line; bottom left), and image set of transaxial breath-hold perfusion single-photon emission CT (SPET), SPET/CT integrated, and CT images (right) in a 69-year-old man with adenocarcinoma in the left upper lobe. The 3D LAA and density-masked CT images clearly show that this patient has severe diffuse emphysema, with an emphysema index of 28.7% and an FEV1 of 0.91 L. The integrated images provided accurate ROI placement (red solid lines) for predicting the postoperative FEV1 after left upper lobectomy. The predicted FEV1 value of 0.76 L determined on the basis of the integrated images was marginal for lobectomy and correlated better with the postoperative actual FEV1 of 1.19 L than the significantly underestimated predicted value of 0.69 L determined by means of lung segment counting.

 

Figure 3
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  		Figure 3. Three-dimensional (3D) lung volume and low-attenuation area (LAA) images (left; top), density-masked computed tomographic (CT) image at the lung plane with primary lung cancer (top left, red line; bottom left), and image set of transaxial breath-hold perfusion single-photon emission CT (SPET), SPET/CT integrated, and CT images (right) in a 68-year-old man with adenocarcinoma in left upper lobe. The 3D LAA and density-masked CT images clearly show that this patient has bullous emphysema, with an emphysema index of 15.2% and an FEV1 of 0.97 L. The predicted residual FEV1 values after left upper lobectomy on the basis of lung segment counting and integrated images were 0.71 L and 0.62 L, respectively. Based on the marginal FEV1 predicted on the basis of integrated images, this patient was recommended to undergo resection of the left upper segment (S1+2 and S3). By preserving the left lingular segment, the residual FEV1 values predicted by means of lung segment counting and integrated images were 0.82 L and 0.74 L, respectively. The predicted FEV1 determined on the basis of integrated images correlated better with the postoperative actual FEV1 of 0.71 L than the predicted value provided by means of lung segment counting.

 

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  		TABLE 2. The linear correlation coefficient for the variables shown
 

Figure 4
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  		Figure 4. Linear dependence between the postoperative predicted forced expiratory volume in 1 second (FEV1ppo) estimated on the basis of single-photon emission tomography and computed tomography (SPET/CT) integrated images and the FEV1ppo estimated by means of the segment-counting method. Both values were closely dependent (correlation coefficient = 0.962) in all patients, except for 4 outliers (filled circles) whose residual pulmonary function was underestimated by means of the segment-counting method. The solid line expresses y = x, and the dotted lines express y = 0.9 x and y = 1.1 x.

 

   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
Although perfusion SPET is widely used to evaluate functional reserve after pulmonary resection, 5-8 Go it has some limitations. Respiratory motion during image acquisition degrades image clarity and compromises the detection of ill-defined perfusion defects. Moreover, there is no detailed anatomic landmarks on SPET images, resulting in large interobserver variability in estimating the functional contribution of specific lung areas. Conversely, the present breath-hold SPET images and integrated images with CT are refined images that have been developed to solve these problems. In the present study breath-hold SPET images enhanced the image clarity of perfusion defects and detected defects more sensitively than standard non–breath-hold images. The reliable integrated images with CT images allowed accurate outlining of the lung lobes and segments to be resected for ROI analysis. Although the superiority of these integrated images over the simple segment-counting technique in predicting postoperative FEV1 did not reach significance in this study, we were able to use these images to accurately predict the values in 4 outliers with severe emphysema. In these outliers the segment-counting technique significantly underestimated the values. These integrated images might especially contribute to accurate prediction of postoperative pulmonary function in patients with severe emphysema.

To date, pulmonary perfusion SPET/CT integrated images have not been widely used because of the difficulty in obtaining reliable image integration. However, the present breath-hold SPET images can provide reliable integrated images with CT images at the same deep inspiratory phase. In our preliminary study the integrated images of the same respiratory-phase SPET and CT images have allowed comprehensive outlining of the lung lobes to be resected, yielding a better prediction of postoperative pulmonary function compared with SPET images alone, with excellent interobserver reproducibility. 11 Go In the present study the deep respiratory breath-hold SPET/CT integrated images also allowed us to accurately outline the areas to be resected, even in patients undergoing segmental lung resection. With the increasing incidence of peripheral small adenocarcinoma, segmentectomy might become the treatment of choice. 17-21 Go We expect that the present integrated images will become a more attractive tool for identifying pulmonary functional reserve in patients undergoing this type of operation for limited function.

The area of emphysema quantified by means of CT, but not preoperative FEV1, was significantly associated with the discrepancy between FEV1ppo estimated on the basis of integrated images and FEV1ppo estimated by means of segment counting. This might assist in the selection of patients who should be considered for integrated images by providing an accurate prediction of postoperative respiratory function. Because FEV1 of less than 700 mL is reported to be associated with a significantly higher mortality risk, 1-3 Go the minimal disagreement between the 2 predicted values is critical for the determination of operability in patients with borderline function. In our series there were 2 patients with borderline function caused by severe emphysema. SPET/CT integrated images helped to verify operability in one patient with an FEV1ppo of less than 700 mL as estimated by means of segment counting (Figure 2). These integrated images also suggested that the change in the operative method was appropriate in the other patient with an FEV1ppo of more than 700 mL as estimated by means of segment counting (Figure 3). Integrated images contributed greatly to predict postoperative functional reserve more accurately than segment counting in both these patients, who recovered postoperatively without any cardiopulmonary complications. Thus in patients with severe emphysema and borderline function, assessment of perfusion impairment with integrated images appears indispensable for determining operability.

Breath-hold perfusion SPET images showed more extended perfusion defects compared with LAAs depicted by using density-masked CT in our patients, with occasional perfusion defects at normal lung areas without LAAs (Figure 1). The superiority of perfusion SPET in detection of emphysematous lungs was also demonstrated by a previous animal study. 22 Go Perfusion defects at normal lung areas on CT images were also documented in patients with pulmonary emphysema in previous clinical studies by us and others. 23-26 Go Smoking-induced mild inflammatory changes in airways, alveolar destruction, or both are not well identified on CT images because of the limitation of spatial resolution. Even in cases without focal alveolar destruction LAAs, smoking-induced airflow obstruction in central-peripheral airways should impair regional perfusion considerably. Breath-hold perfusion SPET images, which enhance the detectability of perfusion defects, seem to further facilitate the advantage of SPET study in the detection of smoking-induced lung pathology.

Regardless of the good correlation between FEV1ppo values estimated on the basis of SPET/CT integrated images and values measured postoperatively in our patients, the predicted FEV1 values were significantly lower than postoperative FEV1 values. Postoperative pulmonary function can be underestimated because pulmonary resection itself sometimes results in improved residual lung function in patients with emphysema. Relief of airflow obstruction, improved respiratory muscle function and elimination of dead space ventilation in ventilated but unperfused areas, and improved cardiovascular hemodynamics might all contribute to this unexpected improvement. 16,27-29 Go Some mathematic correction with variables such as the area of emphysema might be required for obtaining more accurate prediction. Further study on a larger patient population is warranted to solve this issue.

In the present study we focused on the estimation of FEV1ppo because residual FEV1 is the most relevant indicator of morbidity and mortality after major pulmonary resection among all pulmonary functional variables. Likely to the estimation of residual FEV1, both the segment-counting technique and integrated images accurately estimated postoperative vital capacity (r = 0.879 for segment counting and r = 0.863 for integrated images) and postoperative diffusing capacity for carbon monoxide (r = 0.961 for segment counting and r = 0.960 for integrated images). In contrast, unlikely to the estimation of residual FEV1, postoperatively measured vital capacity and diffusing capacity for carbon monoxide were not significantly better than the estimated residual values (all P > .05, paired t test). These results might support the notion that residual FEV1 values are likely to be affected by a volume-reduction effect compared with vital capacity and diffusing capacity, especially for patients with emphysema.

In summary, breath-hold perfusion SPET images enhanced perfusion defect clarity and detected perfusion defects more sensitively than standard images and also provided reliable integrated images with the same respiratory-phase CT images. The reliable SPET/CT integrated images helped to accurately outline the lung lobes or segments to be resected for ROI analysis. Although the superiority of this method over simple lung segment counting for prediction of postoperative pulmonary function was not demonstrated statistically in this study population, our results indicate that patients with severe emphysema and borderline pulmonary function should be evaluated with SPET/CT integrated images for accurate prediction of postoperative pulmonary function because the simple segment-counting technique appears to inherently underestimate functional reserve in these patients.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

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K. Ueda, M. Jinbo, T.-S. Li, T. Yagi, K. Suga, and K. Hamano
Computed Tomography-Diagnosed Emphysema, Not Airway Obstruction, Is Associated with the Prognostic Outcome of Early-Stage Lung Cancer.
Clin. Cancer Res., November 15, 2006; 12(22): 6730 - 6736.
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