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(Radiology. 1999;212:561-566.)
© RSNA, 1999

Thoracic Imaging

Small Pulmonary Nodules: Evaluation with Repeat CT-Preliminary Experience1

David F. Yankelevitz, MD, Rajiv Gupta, PhD, Binsheng Zhao, DSc and Claudia I. Henschke, PhD, MD

1 From the Department of Radiology, the New York Hospital–Cornell University Medical Center, 525 E 68th St, New York, NY 10021. Received March 19, 1998; revision requested May 19; final revision received October 25; accepted March 16, 1999. Supported in part by National Institutes of Health grant R01-CA-63393 and General Electric Corporate Research and Development. Address reprint requests to D.F.Y. (e-mail: dyankele@mail.med.cornell.edu).


   Abstract
TOP
 Abstract
Introduction
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
PURPOSE: To assess the use of early repeat computed tomography (CT) of solitary pulmonary nodules to determine nodule growth.

MATERIALS AND METHODS: The authors performed repeat CT of nodule phantoms to assess the accuracy of their measurement technique. They then used this technique to assess nodule growth (nine malignant, six benign) in 15 patients (nine men, six women; age range, 60–79 years; average age, 66 years) who underwent repeat CT as part of their routine clinical protocol. The final diagnosis was established with surgical resection or follow-up for more than 2 years after an indeterminate biopsy.

RESULTS: Results of phantom experiments revealed that the method used to determine area change is sensitive enough to help detect nodule growth if one pixel is added around the entire circumference of a nodule. With use of standard exponential growth curves and known tumor growth rates, malignant growth could be detected in vivo within 30 days. All 15 in vivo nodules were correctly classified with early repeat CT.

CONCLUSION: Preliminary experience with early repeat CT suggests that a single repeat CT scan obtained 30 days after the first scan can depict growth in most malignant tumors as small as 5 mm.

Index terms: Lung neoplasms, CT, 60.12118 • Lung neoplasms, diagnosis, 60.31, 60.32


   Introduction
TOP
 Abstract
 Introduction
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
The solitary pulmonary nodule is a common and challenging problem. In the United States, more than 150,000 new solitary pulmonary nodules are detected each year; one to two nodules are found on every 1,000 chest radiographs (1–3). With the introduction and continual improvement of computed tomography (CT) since the 1970s, the rate of detection of these nodules has increased. Once discovered, such nodules almost always lead to further diagnostic studies because a high percentage are malignant (2,3). Although the rate of benignity among resected nodules has decreased, it remains high—between 20% and 40% (4).

Small pulmonary nodules (those less than 1 cm in diameter) present an even greater diagnostic challenge because the accuracy of available diagnostic procedures is considerably decreased owing to their size. Given the virulence of lung cancer, the natural tendency is to err on the side of overdiagnosis, even for these small nodules. This explains, in part, the continued high rate of resection of benign nodules.

A key issue in patient treatment is balancing the trade-off between early versus unnecessary resection. Currently, only two radiologic criteria are widely accepted as proof of benignity: (a) nodule calcification in a benign pattern and (b) lack of growth (2). Curiously, although these two criteria were initially described at approximately the same time in the 1950s (5–8), most research to date, including a multicenter study involving CT densitometry and anthropomorphic phantoms (9), has dealt almost exclusively with obtaining additional information regarding calcification. To our knowledge, virtually no work has been done on refining measurement of growth. This is particularly puzzling because growth is a salient feature of malignancy.

In this study, we focused on rapid assessment of nodule growth, particularly of small pulmonary nodules, with repeat CT. We call this method early repeat CT. The feasibility of early repeat CT depends on (a) the expected nodule growth within a clinically acceptable delay between the initial and repeat scans and (b) the accuracy of the measurement technique. The growth observed with early repeat CT, or the lack of it, can be correlated with malignancy status.

The present study was conducted to assess the use of early repeat CT in determining pulmonary nodule growth. This study consisted of two parts. In the first part, we sought to demonstrate that there is a reliable way of measuring changes in small pulmonary nodules during a short follow-up period. This was achieved by using both theoretical considerations and in vitro experiments on nodule phantoms of known sizes. The second part consisted of actual clinical cases in which repeat CT data were available.


   MATERIALS AND METHODS
TOP
 Abstract
 Introduction
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 References
 
Theoretical Growth Projections
To estimate tumor growth, we calculated the expected growth of nodules with different diameters by using an exponential growth model. Assuming the nodules were spherical and initially of diameters of 5, 10, 15, and 20 mm, we calculated the new diameters within 1–4 weeks by using doubling times of 30, 90, 120, 150, and 180 days (Table 1). These doubling times roughly correspond to those of a very aggressive small cell carcinoma (30-day doubling time), a squamous cell carcinoma (90-day doubling time), a large cell carcinoma (120-day doubling time), and an aggressive and average adenocarcinoma (150- and 180-day doubling time, respectively) (10).


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  		TABLE 1. Expected Nodule Diameter at Early Repeat CT based on Interval between Initial and Repeat CT, Initial Nodule Diameter, and Tumor Doubling Time
 
As shown in Table 1, a nodule with a diameter of 5 mm and a doubling time of 30 days would reach a diameter of 5.57 mm after 14 days, 5.88 mm after 21 days, and 6.20 mm after 28 days. All of these diameter changes are greater than the CT resolution of 0.3 mm in the x and y planes. A larger nodule with a diameter of 10 mm and the same doubling time would reach a diameter of 10.55 mm after 7 days so that early repeat CT performed after 7 days could depict this change. Conversely, the same 10-mm-diameter nodule would have a barely discernible diameter change after 28 days if it had a doubling time of 180 days.

The data in Table 1 demonstrate that even the slowest growing 10-, 15-, and 20-mm-diameter nodules would register a measurable increase within 28 days for all listed growth rates. Thus, theoretically, repeat CT performed after 28 days would depict growth in these nodules. Nodules with a diameter of 5 mm would also demonstrate measurable growth within 28 days, except at the slowest growth rates of 150 and 180 days, at which the growth would be below the detection threshold. If a repeat scan were obtained after another 28 days, however, even such slowly growing nodules could be recognized.

Minimum Detectable Change
Nodule growth can be assessed on individual CT sections or on the whole volumetric stack. Our primary concern in this study was to determine the minimum detectable area change on individual CT sections because these are readily available for in vivo nodules and clinicians are used to analyzing nodules on a section-by-section basis.

To assess the area growth metric, we constructed CT phantoms by using polycarbonate rods with base diameters of 3.17, 4.78, 6.24, 9.79, and 12.80 mm. The rod diameters were incrementally increased by winding different numbers of turns of transparent adhesive tape around them, with each turn increasing the diameter by 0.1 mm. A total of 10 turns were applied to each rod. The rods were scanned with a CT HiSpeed Advantage (GE Medical Systems, Milwaukee, Wis) scanner by using a standard imaging protocol (1-mm collimation, spiral mode with a pitch of 1:1, and 9.6-cm field of view) (Fig 1).



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  		Figure 1. Ten cross-sectional CT scans of five polycarbonate rods with diameters of 3.17, 4.78, 6.24, 9.79, and 12.80 mm. The diameter of each group of rods increases from left to right and top to bottom in increments of 0.1 mm. The overall diameter change is about 1 mm between the smallest set of rods (top left) and the largest set of rods (bottom right).

 
Each rod was then precisely measured with a micrometer (accuracy greater than 10 µm) to determine the actual area considered to have the true measurement. To determine the accuracy of the CT scanner, we measured the area of the rod phantom on the acquired image. The area was determined by segmenting its boundary with the k-means segmentation algorithm (11,12). The area was calculated by multiplying the number of pixels within the nodule boundary by the pixel size. The scans were analyzed with software that we developed on an Indy workstation (Silicon Graphics, Mountain View, Calif).

We used the k-means algorithm, which minimizes the sum of the Euclidean distances from all pixels in a cluster to the cluster center, because it is effective when there are marked differences between the structures being segmented—in this case between the rods and the surrounding air.

In Vivo Experiments
For the in vivo assessment of early repeat CT, we evaluated the nodule growth in 15 patients (nine men, six women; age range, 60–79 years; average age, 66 years) who underwent repeat CT during the course of their routine clinical work-up. According to routine clinical practice at our institution, biopsy was recommended for all nodules that demonstrated growth within the malignant range (Table 1); follow-up was recommended for all other nodules. Thus, except for those cases in which the second scan was obtained at biopsy, our recommendations were made before knowing the true status of the nodule. The actual malignancy status of the nodule was determined with resection or biopsy or after sufficient follow-up (minimum, 2 years) to ensure nodule stability, which is indicative of benignity.

Thin-section CT scans of the nodules were obtained, and the images from repeat CT were reconstructed at 0.5-mm intervals on the z axis to maximize the comparability of the repeat and initial images. The image from the initial scan with the maximal area was compared with the image from the repeat scan with the maximal area. This comparison was done by displaying the two image sets side by side.

Once the nodule was segmented, the area could be readily calculated. Because there are marked differences between the attenuation (in Hounsfield units) of the nodule and that of the surrounding lung tissue, which is predominantly air, we again used the k-means algorithm for the segmentation of the nodule. Because this segmentation algorithm requires a predefined number of clusters, we compared the results obtained by using different numbers of clusters and found that 18 clusters were optimal for the segmentation of these nodules. Two experienced chest radiologists (D.F.Y., C.I.H.) also carefully compared each segmented nodule with the original CT scans to ensure that the nodule had been correctly and consistently identified with the segmentation procedure.

We used the calculated nodule area to determine nodule diameter. The exponential growth model was used to calculate the doubling time for each nodule and the projected area and corresponding diameter if the repeat scan had been obtained after 30 days. We also compared our calculated diameter with that obtained from the pathologic specimen for all resected nodules.


   RESULTS
TOP
 Abstract
 Introduction
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 References
 
Minimum Detectable Change
Figure 1 shows that even a change of about 100 µm all around the simulated nodules, although only faintly perceptible to the human eye, can be measured on CT scans. Larger changes, those on the order of one pixel dimension (about 300 µm), are both visually discernible and quantitatively measurable. In addition, a measurement of this amount of change, that is, one pixel dimension all around the nodule, is robust in the sense that it is unlikely to be confused with other effects such as partial volume effects, detector quantum noise, and misregistration.

Table 2 shows the actual and measured areas and the corresponding changes from the base values for the various nodule phantoms shown in Figure 1. As mentioned earlier, the actual area was computed from the diameter of the rod phantom. The change in area (in square millimeters) from the base value is shown in column 3. The nodule area was also estimated from the acquired image. The image was segmented, and the number of pixels within the nodule were counted. The change in measured area (in number of pixels) from the base value also is shown. As can be seen in Table 2, even for the smallest change in area, the corresponding change in the image area is measurable.


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  		TABLE 2. Comparison of Actual and Measured Areas of Rod Phantoms
 
Figure 2 shows the plot of the actual area change for the phantoms on the x axis and the corresponding measured change on the y axis. This graph demonstrates the linear relationship between the actual and measured change. In addition, even the smallest increment in the diameter is discernible on the image. Thus, the results shown in Table 2 demonstrate that we are able to discern change as small as a third of a pixel, provided it occurs around the entire circumference of the nodule. In other words, for a nodule with diameter D, a change of {pi}D times the pixel size is detectable. Thus, an area change of 9 mm or 12% (assuming a pixel size of 0.3 mm) can be detected in a nodule with a diameter of 10 mm.



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  		Figure 2. Graph shows actual versus measured change in the cross-sectional area of polycarbonate rod phantoms.

 
Validation of Early Repeat CT with in Vivo Nodules
Table 3 gives the intervals between acquisitions of the two CT scans, the nodule areas obtained at each time, and the final diagnosis for malignant nodules (nine malignant, six benign). All nine malignant nodules had growth well above the minimal detectable change. In addition, their growth rates correlated with the generally accepted growth rates for this type of malignancy. With use of the projected growth in 30 days, all of these nodules could have been detected with repeat CT after 30 days. Although the repeat CT scan obtained in case 9 does not qualify as "early," it does demonstrate rapid growth and, as can be seen from the projected 30-day growth, the change at that time was well within the limits of growth detection. Because all of these cases were treated according to current clinical practice, we did not control the scheduling of repeat scans.


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  		TABLE 3. Results of in Vivo Studies of Malignant Nodules with Early Repeat CT
 
Table 4 gives the same information for benign nodules. Cases 10–12, 14, and 15 are nodules that have now been followed-up for more than 2 years and have shown no growth. In case 10, biopsy of the nodule was performed; no malignant cells were found. In case 11, biopsy of the nodule was performed twice within a 3-year period, and the lesion did not demonstrate malignant cells. At all of these biopsies, the needle tip was confirmed to be in the lesion. In cases 10 and 11, repeat CT added substantial confidence, so that surgical resection was avoided for these benign nodules. Cases 11 and 15 demonstrated a decrease in size, as represented by negative growth rates. Thus, a negative growth rate is also within the limits of variation in our current technique.


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  		TABLE 4. Stability of Early Repeat CT in Benign Nodules
 
Early repeat CT depicted nodule growth within 6 weeks in the six patients who underwent repeat CT within that time. Early repeat CT depicted growth even for the smallest nodule (case 6 in Table 3 and Fig 3). Conversely, the increase in the area of the six benign nodules, even over long periods, was minimal and well below the CT detection limit.



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  		Figure 3a. Case 6. (a) Initial axial CT scan of the right upper lobe of the lung (nodule diameter, 3.6 mm) and (b) early repeat axial CT scan of the right upper lobe obtained 44 days later (nodule diameter, 4.3 mm) showing the selected region of interest (top), and the corresponding k-means classification of the region of interest (bottom left) and resultant segmented nodule (bottom right). The nodule was confirmed at pathologic evaluation to be an adenocarcinoma in the right upper lobe.

 


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  		Figure 3b. Case 6. (a) Initial axial CT scan of the right upper lobe of the lung (nodule diameter, 3.6 mm) and (b) early repeat axial CT scan of the right upper lobe obtained 44 days later (nodule diameter, 4.3 mm) showing the selected region of interest (top), and the corresponding k-means classification of the region of interest (bottom left) and resultant segmented nodule (bottom right). The nodule was confirmed at pathologic evaluation to be an adenocarcinoma in the right upper lobe.

 

   DISCUSSION
TOP
 Abstract
 Introduction
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
References
 
The results of our experiments with phantoms and in vivo nodules show that early repeat CT can depict change within 30 days for malignancies that double within 30–180 days and are larger than 5 mm at initial presentation. To our knowledge, no study has documented a deleterious effect to the final outcome of the patient by observing a nodule for less than one doubling time before surgery. Although the policy of "watchful waiting" has come under scrutiny in the past, leading authorities in the field now advocate that "under certain circumstances, a decision to observe the nodule for a period of time with serial chest films may be appropriate, but this must be a considered approach and not a `default' position" (2,13). Herein, we present one such approach, in which we established the usefulness of early repeat CT by demonstrating that growth in a nodule can be reliably detected with repeat CT performed within a clinically acceptable interval.

Early repeat CT also supplements information from the biopsy procedure by enabling direct confirmation of the presence or absence of growth. This is important because the accuracy of CT-guided needle biopsy in these small nodules is questionable (14). Needless to say, early repeat CT can be performed as part of the percutaneous CT-guided biopsy procedure. Our preliminary experience has shown that early repeat CT is highly desirable for determining the appropriate management actions when the biopsy result is indeterminate—allowing for confident continued observation when scans demonstrate lack of growth or suggesting further action when the malignant growth rate is determined. Thus, early repeat CT may be combined with a decision theoretical approach that enables determination of the probability of malignancy based on the initial CT findings. Results of early repeat CT can then be used to modify the baseline probability.

Gurney and colleagues (15,16) recommended using the Bayes theorem, which allows for the incorporation of likelihood ratios of various test results or clinical findings in determining the probability of malignancy of a given nodule. On the basis of a large literature survey, Gurney (15) found that the most important radiologic characteristics of malignant nodules were cavity wall thickness, spiculated edge, and nodule diameter greater than 3 cm; important characteristics for benignity were benign growth rate and benign pattern of calcification. As Swensen (17) noted, however, it is difficult to fully incorporate the combined information of many variables by using the Bayes theorem, and other techniques may be even more appropriate.

Additional advantages of early repeat CT include its potential for widespread availability and the fact that it does not require the specialized skills needed for accurate and safe percutaneous needle biopsy procedures or other more invasive diagnostic studies. In addition, early repeat CT entails a much lower cost.

In all of our in vivo studies, we relied on images that were obtained as part of routine clinical management. Repeat scans were typically obtained before biopsy. The routine clinical use of early repeat CT, however, would require a well-defined protocol for follow-up scanning. Ideally, this protocol would take into account the probability of malignancy based on both the patient's clinical characteristics and the nodule's initial morphologic features, as well as the parameters that describe the capabilities of the CT scanner. This task is complicated, because a complex interaction between these parameters determines when growth will become discernible. These parameters include (a) the initial size of the small pulmonary nodule, (b) the resolution of the imaging technique, (c) the measurement parameter used to assess growth, and (d) the doubling time of the tumor.

Any prespecified interval between initial and repeat CT (eg, 30 days) would enable only tumors growing faster than a certain rate to be reliably diagnosed. Thus, a single repeat scan might not depict the slower-growing tumors, and additional CT scans might be required. The scheduling function to determine when to obtain these additional repeat scans is a topic of current research.

Because volume changes as a function of the cube of the diameter, the proportional change in the nodule volume is much greater than the proportional change in the nodule diameter. Because the precision of these volume measurements is on the same order as that of diameter measurements, an increase in the nodule volume can be detected even earlier. For example, a 10-mm-diameter nodule with a doubling time of 30 days would show an increase of 1 mm in 12.4 days (a 10% increase), whereas the corresponding volume increase (33%) would be much larger. The larger the initial diameter, the greater the corresponding change in volume. Thus, determination of nodule volume directly from three-dimensional images is preferable.

Our current software implementation allows us to measure area change at the maximum cross section to assess growth as well as volumetric change in the overall nodule size. To analyze the capabilities of volumetric early repeat CT, we are currently gathering such volumetric data from appropriate clinical cases.


   Footnotes
 
Author contributions: Guarantors of integrity of entire study, all authors; study concepts and design, all authors; definition of intellectual content, all authors; literature research, all authors; clinical studies, D.F.Y., C.I.H.; data acquisition and analysis, all authors; statistical analysis, C.I.H.; manuscript preparation, editing, and review, all authors.


   References
TOP
 Abstract
 Introduction
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 

  1. Lillington GA, Caskey CC. Evaluation and management of solitary and multiple pulmonary nodules. Clin Chest Med 1993; 14:111-119.[Medline]
  2. Lillington GA. Management of solitary pulmonary nodules. Postgrad Med 1997; 101:145-150.
  3. Viggiano RW, Swensen SJ, Rosenow EC. Evaluation and management of solitary and multiple pulmonary nodules. Clin Chest Med 1992; 13:83-95.[Medline]
  4. Midthun DE, Swensen SJ, Jett JR. Clinical strategies for solitary pulmonary nodule. Annu Rev Med 1992; 43:195-208.[Medline]
  5. Hood RT, Jr, Good CA, Clagett OT, McDonald JR. Solitary circumscribed lesions of the lung. JAMA 1953; 152:1185-1191.
  6. Good CA, Hood RT, Jr, McDonald JR. Significance of a solitary mass in the lung. AJR 1953; 70:543-554.
  7. Good CA. Management of patient with solitary mass in lung. Chicago Med Soc Bull 1953; 55:893-896.
  8. Good CA, Wilson TW. The solitary circumscribed pulmonary nodule. JAMA 1958; 166:210-215.
  9. Zerhouni EA, Stitik FP, Siegelman SS, et al. CT of the pulmonary nodule: a cooperative study. Radiology 1986; 160:319-327.[Abstract/Free Full Text]
  10. Geddes DM. The natural history of lung cancer: a review based on rates of tumor growth. Br J Dis Chest 1979; 73:1-17.[Medline]
  11. Russ JC. The image processing handbook 2nd ed. Boca Raton, Fla: CRC, 1995.
  12. Haralick RM, Shapiro LB. Survey-image segmentation techniques. Comp Vis Graphics Imaging Processing 1985; 29:100-132.
  13. Cumming SR, Lillington GA, Richard RJ. Managing solitary pulmonary nodules: the choice of strategy is a "close call.". Am Rev Respir Dis 1986; 134:453-460.[Medline]
  14. Yankelevitz DF, Henschke CI, Koizumi J, Altorki N, Libby D. CT-guided transthoracic needle biopsy of small solitary pulmonary nodules. Clin Imaging 1997; 21:107-110.[Medline]
  15. Gurney JW. Determining the likelihood of malignancy in solitary pulmonary nodules with Bayesian analysis. I. Theory. Radiology 1993; 186:405-413.[Abstract/Free Full Text]
  16. Gurney JW, Lyddon DM, McKay JA. Determining the likelihood of malignancy in solitary pulmonary nodules with Bayesian analysis. II. Application. Radiology 1993; 186:415-422.[Abstract/Free Full Text]
  17. Swensen SJ. The probability of malignancy in solitary pulmonary nodules: application to small radiologically indeterminate nodules. Arch Intern Med 1997; 157:849-855.[Abstract]



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Solitary Pulmonary Nodules: Dynamic Contrast-enhanced MR Imaging--Perfusion Differences in Malignant and Benign Lesions
Radiology, August 1, 2004; 232(2): 544 - 553.
[Abstract] [Full Text] [PDF]

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S. G. Jennings, H. T. Winer-Muram, R. D. Tarver, and M. O. Farber
Lung Tumor Growth: Assessment with CT--Comparison of Diameter and Cross-sectional Area with Volume Measurements
Radiology, June 1, 2004; 231(3): 866 - 871.
[Abstract] [Full Text] [PDF]

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W. J. Kostis, D. F. Yankelevitz, A. P. Reeves, S. C. Fluture, and C. I. Henschke
Small Pulmonary Nodules: Reproducibility of Three-dimensional Volumetric Measurement and Estimation of Time to Follow-up CT
Radiology, May 1, 2004; 231(2): 446 - 452.
[Abstract] [Full Text] [PDF]

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M.-P. Revel, C. Lefort, A. Bissery, M. Bienvenu, L. Aycard, G. Chatellier, and G. Frija
Pulmonary Nodules: Preliminary Experience with Three-dimensional Evaluation
Radiology, May 1, 2004; 231(2): 459 - 466.
[Abstract] [Full Text] [PDF]

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 J. Thorac. Cardiovasc. Surg.Home page
H. Nomori, T. Ohtsuka, T. Naruke, and K. Suemasu
Histogram analysis of computed tomography numbers of clinical T1 N0 M0 lung adenocarcinoma, with special reference to lymph node metastasis and tumor invasiveness
J. Thorac. Cardiovasc. Surg., November 1, 2003; 126(5): 1584 - 1589.
[Abstract] [Full Text] [PDF]

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H. T. Winer-Muram, S. G. Jennings, C. A. Meyer, Y. Liang, A. M. Aisen, R. D. Tarver, and R. C. McGarry
Effect of Varying CT Section Width on Volumetric Measurement of Lung Tumors and Application of Compensatory Equations
Radiology, October 1, 2003; 229(1): 184 - 194.
[Abstract] [Full Text] [PDF]

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J. P. Ko, H. Rusinek, E. L. Jacobs, J. S. Babb, M. Betke, G. McGuinness, and D. P. Naidich
Small Pulmonary Nodules: Volume Measurement at Chest CT--Phantom Study
Radiology, September 1, 2003; 228(3): 864 - 870.
[Abstract] [Full Text] [PDF]

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 ChestHome page
J. P. Wisnivesky, A. I. Mushlin, N. Sicherman, and C. Henschke
The Cost-Effectiveness of Low-Dose CT Screening for Lung Cancer: Preliminary Results of Baseline Screening
Chest, August 1, 2003; 124(2): 614 - 621.
[Abstract] [Full Text] [PDF]

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 NEJMHome page
D. Ost, A. M. Fein, and S. H. Feinsilver
The Solitary Pulmonary Nodule
N. Engl. J. Med., June 19, 2003; 348(25): 2535 - 2542.
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 Am. J. Roentgenol.Home page
Y. Ohno, H. Hatabu, D. Takenaka, T. Higashino, H. Watanabe, C. Ohbayashi, and K. Sugimura
CT-Guided Transthoracic Needle Aspiration Biopsy of Small (<= 20 mm) Solitary Pulmonary Nodules
Am. J. Roentgenol., June 1, 2003; 180(6): 1665 - 1669.
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 Am. J. Roentgenol.Home page
S. Takashima, S. Sone, F. Li, Y. Maruyama, M. Hasegawa, and M. Kadoya
Indeterminate Solitary Pulmonary Nodules Revealed at Population-Based CT Screening of the Lung: Using First Follow-Up Diagnostic CT to Differentiate Benign and Malignant Lesions
Am. J. Roentgenol., May 1, 2003; 180(5): 1255 - 1263.
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 Am. J. Roentgenol.Home page
S. Takashima, Y. Maruyama, M. Hasegawa, T. Yamanda, T. Honda, M. Kadoya, and S. Sone
CT Findings and Progression of Small Peripheral Lung Neoplasms Having a Replacement Growth Pattern
Am. J. Roentgenol., March 1, 2003; 180(3): 817 - 826.
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 RadiologyHome page
M. S. Benjamin, E. A. Drucker, T. C. McLoud, and J.-A. O. Shepard
Small Pulmonary Nodules: Detection at Chest CT and Outcome
Radiology, February 1, 2003; 226(2): 489 - 493.
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 Eur Respir JHome page
C.I. Henschke, D.F. Yankelevitz, D.I. McCauley, D.M. Libby, M.W. Pasmantier, and J.P. Smith
Guidelines for the use of spiral computed tomography in screening for lung cancer
Eur. Respir. J., January 1, 2003; 21(39_suppl): 45S - 51s.
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S. G. Armato III, F. Li, M. L. Giger, H. MacMahon, S. Sone, and K. Doi
Lung Cancer: Performance of Automated Lung Nodule Detection Applied to Cancers Missed in a CT Screening Program
Radiology, December 1, 2002; 225(3): 685 - 692.
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 Ann. Thorac. Surg.Home page
K. Suzuki, H. Asamura, M. Kusumoto, H. Kondo, and R. Tsuchiya
"Early" peripheral lung cancer: prognostic significance of ground glass opacity on thin-section computed tomographic scan
Ann. Thorac. Surg., November 1, 2002; 74(5): 1635 - 1639.
[Abstract] [Full Text] [PDF]
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