HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Abstract Figures Only Full Text (PDF) All Versions of this Article: 2211001585v1 221/2/531    most recent Submit a response Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Hopper, K. D. Articles by Mahraj, R. Search for Related Content PubMed PubMed Citation Articles by Hopper, K. D. Articles by Mahraj, R.

Transbronchial Biopsy with Virtual CT Bronchoscopy and Nodal Highlighting¹

¹ From the Departments of Radiology (K.D.H., R.M.), Medicine (T.A.L., K.G., J.L.S., R.B.), and Health Evaluation Sciences (D.T.M.), Penn State University, PO Box 850, Hershey, PA 17033. Received September 27, 2000; revision requested November 14; revision received January 23, 2001; accepted March 2. Address correspondence to K.D.H. (e-mail: khopper@psu.edu).

	ABSTRACT

TOP ABSTRACT INTRODUCTION Materials and Methods Results Discussion REFERENCES

 
Transbronchial biopsy to sample lymph nodes and tumors that are not visible at endoscopy has a poor (<50%) success rate. These nodes can be highlighted easily at virtual computed tomographic (CT) bronchoscopy to provide a guide. This study was performed to evaluate if the addition of this information to the bronchoscopist improved the success rate of transbronchial biopsy of subcarinal and aortopulmonary lymph nodes. The addition of virtual CT bronchoscopy with lymph node highlighting significantly (P < .5) increased biopsy success rates for pretracheal, hilar, and high pretracheal adenopathy.

Index terms: Bronchi, CT, 671.12117, 671.12118 • Computed tomography (CT), three-dimensional, 671.12117, 671.12118

	INTRODUCTION

TOP ABSTRACT INTRODUCTION Materials and Methods Results Discussion REFERENCES

 
Creation of endoscopic views with computed tomography (CT) has become possible with technologic advances in both the acquisition and display of CT data. With the introduction of helical CT scanners, the ability to acquire a large volume of data in a short time with little breathing artifact has been realized. An entire section of the body can now be scanned with little or no patient movement, and sections can be reconstructed with as much overlap as desired. A single helical CT study for virtual reality can easily contain 150–250 individual CT sections, making the use of high-end display systems critical.

Few investigators (1–9), however, have applied this technology to the airway, especially as a direct adjunct to bronchoscopy. The limited efforts with virtual CT bronchoscopy to date are in delineating endobronchial pathologic sites rather than demonstrating to the bronchoscopist what he otherwise cannot see. However, virtual reality can literally combine a patient’s chest CT scan with his or her bronchoscopic image. Viewing of the virtual CT bronchoscopic findings prior to actual endoscopy and especially transbronchial biopsy could show the pulmonologist the diseased anatomy and the exact location of hidden masses and lymph nodes. The purpose of this study was to determine whether virtual CT bronchoscopy with nodal highlighting could help selection of a site for transbronchial biopsy of lymph nodes that are not visible at bronchial endoscopy.

	Materials and Methods

TOP ABSTRACT INTRODUCTION Materials and Methods Results Discussion REFERENCES

 
A senior radiology investigator (K.D.H.), experienced in virtual CT bronchoscopy, selected 35 sites of adenopathy depicted on CT scans obtained in 14 patients (eight men and six women; age range, 38–79 years; mean age, 58.6 years). The sites were chosen to provide a spectrum of anatomic sites (seven aortopulmonary window, nine pretracheal, six subcarinal, 10 hilar, and three high pretracheal). The transition from pretracheal to high pretracheal adenopathy was 3.0 cm above the carina. The lymph nodes were selected to provide a representation of sizes (<1.5 cm, seven; 1.5–3.0 cm, 13; >3 cm, 15). The study population was limited to patients with normal bronchi and mucosa depicted at actual bronchoscopy and to patients with extrabronchial lymphadenopathy, because these are the patients for whom the results would be clinically relevant.

Each patient selected for the study underwent repeat CT (PQ5000; Marconi Medical Systems, Highland Heights, Ohio). Informed consent was obtained, and the study was performed under the auspices of our institutional human use committee. The patients underwent nonenhanced helical CT of the tracheobronchial tree from 3 mm above the aortic arch to the top of the right hemidiaphragm (3.0-mm section thickness, pitch of 2.0, reconstructed section overlap of 50%, 175 mAs).

The CT data for each study were loaded onto a workstation (Voxel Q; Marconi Medical Systems). By using the editing software, the selected lymph nodes were then highlighted on all the transverse images that displayed them. This highlighting process required 3–4 minutes by the investigator. A virtual reality fly-through of the airways was then produced by the same experienced imager. The volumetric reconstruction technique was based on x-ray attenuation values to reconstruct the mucosal (inner luminal layer of two to three voxels) as one structure, the bronchial wall as a second, and the highlighted lymph node as a third. Colors were assigned and attenuation settings were adjusted for each of the three tissue classes to maximize mucosal detail, provide depth perception, mimic the bronchial tree as seen during actual bronchoscopy, and make highlighted lymph nodes easily visible through the bronchial walls.

For each nodal site studied, two separate virtual CT bronchoscopic cine images were acquired, one without nodal highlighting and a second with and without nodal highlighting. Creation of the virtual CT bronchoscopic images required an average 8–10 minutes of the investigator’s time. The virtual cine image of each of the 35 sites without lymph node highlighting was used as a control to determine where each pulmonologist would perform a biopsy of that site during actual bronchoscopy. This allowed evaluation of whether viewing of a virtual cine image with lymph node highlighting prior to actual bronchoscopy would improve localization for transbronchial biopsy. Key images (every 6th to 10th frame) from the virtual cine image without lymph node highlighting were obtained.

Three pulmonologists (T.A.L., K.G., J.L.S.) separately reviewed each of the 70 cine images (35 of sites without lymph node highlighting and, during another reading session, 35 both with and without lymph node highlighting) along with the original transverse CT study with the targeted lymph node circled in red. Each reviewer was blinded to the other reviewers’ findings. This study design allowed the virtual cine image of each of the 35 sites without lymph node highlighting to be directly compared with the virtual cine image with lymph node highlighting and allowed each site to serve as its own normal control. After they reviewed each virtual cine image, the pulmonologists were provided with the key images from the nonhighlighted cine images and asked to mark on the most appropriate image the exact location they would select to perform transbronchial biopsy of that particular lymph node. The order of the case review was randomized, all patient identification was removed from all studies, and the patient’s highlighted cine image was reviewed in a different review session from that in which the nonhighlighted cine image was reviewed. A total of five review sessions were spaced over a 3-month period, with approximately 14 cases reviewed per session.

The distance from the marked biopsy site to the nearest edge and to the center of the targeted pathologic site was determined by the same radiology investigator (K.D.H.) who selected the sites, marked the targeted lymph nodes, and created the cine images. A successful biopsy site choice was considered the choice of a biopsy site that overlay any portion of the lymph node. The distance from the marked biopsy site to the center 75% of the lymph node was also measured, as was the distance to the nodal center. The distances from the site selected by the pulmonologists for potential transbronchial biopsy to the edge and center of the actual nodal site was determined both with and without lymph node highlighting for the overall data, specific pathologic sites, and between and within individual pulmonologists. Neither the depth of the biopsy site nor the number of passes required for successful biopsy could be assessed because actual biopsies were not performed. However, the lymph nodes or tumors selected for this study were all adjacent to the bronchial wall and would have been within easy reach of a transbronchial biopsy needle with use of a biopsy depth of at least 5 mm.

The difference in accuracy of choice of lymph node biopsy site with and that without highlighting was assessed by means of three parallel analyses. In the first analysis, the McNemar test was used to assess the effect of highlighting on the basis of a general measure of accuracy, whether or not the biopsy site was within the intended node. In the second analysis, the McNemar test was used to assess the effect of highlighting on the basis of a more restrictive measure of accuracy, whether or not the biopsy was within the middle 75% of the intended node. In the third analysis, repeated measures analysis of variance was used to compare both with and without highlighting the physical distance from the biopsy site to the isocenter of the node. All analyses were performed with a statistical software system (SAS, version 8; SAS Institute, Cary, NC). Analyses included differences between nodal sites and sizes and the three pulmonologists.

	Results

TOP ABSTRACT INTRODUCTION Materials and Methods Results Discussion REFERENCES

 
Virtual CT bronchoscopy with lymph node highlighting added little to the choice of a biopsy site of subcarinal adenopathy (Fig 1). The three pulmonologists would have successfully chosen the biopsy sites in 94% of these lymph nodes whether virtual CT bronchoscopic images were highlighted or not. While virtual CT bronchoscopy with highlighting allowed the pulmonologist to successfully place the biopsy site in the center 75% of subcarinal lymph nodes a greater proportion of the time (with highlighting, 78% [14 of 18]; without highlighting, 61% [11 of 18]), this increase was not statistically significant (P = .4). All percentages provided in Results represent an average among the three pulmonologists.

View larger version (191K): [in this window] [in a new window] [Download PPT slide]   Figure 1a. (a) Transverse CT scan shows a highlighted (in purple) 2-cm-diameter subcarinal lymph node in a 75-year-old woman with lymphoma. (b) Virtual CT bronchoscopic image shows the locations of the biopsy sites chosen by the three pulmonologists (1, 2, 3) without (X) and with () lymph node highlighting. Without the lymph node highlighted, pulmonologist 2 missed the lymph node posteriorly; pulmonologist 3, by going through the apex of the carina, would have had to perform the biopsy at a depth of at least 9 mm to reach the proximal edge of the lymph node. Only pulmonologist 1 would have successfully sampled the lymph node at biopsy. With the lymph node highlighted, all three pulmonologists picked better locations to perform biopsy.

View larger version (137K): [in this window] [in a new window] [Download PPT slide]   Figure 1b. (a) Transverse CT scan shows a highlighted (in purple) 2-cm-diameter subcarinal lymph node in a 75-year-old woman with lymphoma. (b) Virtual CT bronchoscopic image shows the locations of the biopsy sites chosen by the three pulmonologists (1, 2, 3) without (X) and with () lymph node highlighting. Without the lymph node highlighted, pulmonologist 2 missed the lymph node posteriorly; pulmonologist 3, by going through the apex of the carina, would have had to perform the biopsy at a depth of at least 9 mm to reach the proximal edge of the lymph node. Only pulmonologist 1 would have successfully sampled the lymph node at biopsy. With the lymph node highlighted, all three pulmonologists picked better locations to perform biopsy.

For pretracheal, hilar, and high pretracheal adenopathy, the addition of virtual CT bronchoscopy with lymph node highlighting significantly increased the successful choice of a biopsy site (Table). For instance, the successful choice of a biopsy site for hilar adenopathy increased from 37% (11 of 30) to 83% (25 of 30) (P = .001) and for pretracheal nodes increased from 59% (16 of 27) to 85% (23 of 27) (P = .07). For the three high pretracheal lymph nodes (Fig 2), the percentage increased from 11% (one of nine) to 78% (seven of nine) (P = .07). The data for successful choice of a biopsy site in the central 75% of the lymph node in these anatomic sites and the P values improved in a similar fashion (Table). Overall for all 105 measurements (35 nodal sites x 3 pulmonologists), the addition of virtual CT bronchoscopy with lymph node highlighting increased the successful choice of a biopsy site from 55% (58 of 105) to 83% (87 of 105) (P < .001). For choice of a biopsy site in the central 75% of the lymph node, the percentage increase increased from 41% (43 of 105) to 70% (74 of 105) (P < .001).

View larger version (174K): [in this window] [in a new window] [Download PPT slide]   Figure 2a. (a) Transverse CT scan shows a highlighted (in blue) 2.9-cm-diameter high right paratracheal lymph node in a 56-year-old woman with lymphoma. (b) Virtual CT bronchoscopic image shows the locations of the biopsy sites chosen by the three pulmonologists (1, 2, 3) without (X) and with () the lymph node highlighted. Without the lymph node highlighted, all three pulmonologists missed the lymph node. With the lymph node highlighted, all three pulmonologists successfully picked locations to perform biopsy.

View larger version (112K): [in this window] [in a new window] [Download PPT slide]   Figure 2b. (a) Transverse CT scan shows a highlighted (in blue) 2.9-cm-diameter high right paratracheal lymph node in a 56-year-old woman with lymphoma. (b) Virtual CT bronchoscopic image shows the locations of the biopsy sites chosen by the three pulmonologists (1, 2, 3) without (X) and with () the lymph node highlighted. Without the lymph node highlighted, all three pulmonologists missed the lymph node. With the lymph node highlighted, all three pulmonologists successfully picked locations to perform biopsy.

There was also little variation in the data between lymph nodes of various sizes. Of the seven lymph nodes smaller than 1.5 cm, the successful choice of biopsy site was increased by the addition of virtual CT bronchoscopy with lymph node highlighting; the percentage increased from 52% (11 of 21) to 86% (18 of 21) (P < .4). The percentage of successful choices of biopsy sites increased from 49% (19 of 39) to 82% (32 of 39) (P = .002) for 1.5–3.0-cm-diameter lymph nodes and increased from 62% (28 of 45) to 82% (37 of 45) (P = .04) for lymph nodes larger than 3.0 cm.

The mean distance from the selected biopsy site to the center of the targeted lymph node was 1.41 cm when virtual CT bronchoscopy with lymph node highlighting was not provided versus 0.88 cm (P = .005) when it was. The mean percentage relative distance to the center of the lymph node as a function of size (distance to center divided by lymph node radius x 100%) was 122% with lymph node highlighting versus 81% without (P = .003).

Although the overall effect of node highlighting on successful choice of biopsy site across all anatomic sites was significant, the results were not definitive for individual sites except in the hilar region. This was partly due to a lack of statistical power owing to small samples (the hilar region had the largest sample) and partly because the effect was larger in the hilar region. The high pretracheal region also exhibited a large effect (78% vs 11%), but the sample was only nine high pretracheal lymph nodes. On the basis of our data, a sample of 15 high pretracheal lymph nodes provided 80% power for detecting an effect of highlighting. The pretracheal region exhibited a moderate effect (85% vs 59%). On the basis of our data, a sample size of 59 in the pretracheal region would provide 80% power for detecting an effect of highlighting. On the other hand, the aortopulmonary window region exhibited a very modest effect (71% vs 62%). On the basis of our data, a sample size of 389 would be required in the aortopulmonary window region to detect an 80% effect of highlighting.

	Discussion

TOP ABSTRACT INTRODUCTION Materials and Methods Results Discussion REFERENCES

 
While the false-positive rate for bronchoscopic needle biopsy is very low (0.8%), the false-negative rate is much worse (10,11). For endoscopically visible tumors, an accurate histologic diagnosis can be made in up to 94% of cases (10,11). However, for lesions that are not visible or that are more peripheral, an accurate histologic diagnosis is made on the basis of only transbronchial biopsy in approximately 50% of cases (12,13). This is a special problem in lung cancer at an advanced stage because patients must undergo staging thoracotomy or a Chamberlain procedure to diagnose the tumor. This causes a delay in initiation of chemotherapy while the patient is scheduled for the thoracotomy procedure and heals. The delay is an even greater problem for patients with T1 lung cancer with mediastinal adenopathy (21%), because they are forced to undergo either a staging thoracotomy or Chamberlain procedure prior to resection of their primary lung cancer (14). This low percentage for biopsy success is not surprising, especially when the mucosa and airways appear normal, as the pulmonologist is forced to literally guess where to make his biopsy attempt.

Unlike in the colon, where virtual reality has found its greatest potential application in detecting intraluminal polyps, the need in the bronchi is different. An intraluminal pathologic site is easily visualized at transverse CT with the backdrop of normally air-filled airways. However, it seems plausible from the poor results of transbronchial biopsy that when tumor does not extend into the airway or when tissue from lymph nodes is required, virtual CT bronchoscopy may assist the pulmonologist in directing his biopsy attempts through normal mucosa. In this role, the requirements for image optimization and delineation of mucosal or anatomic detail are far greater for virtual CT bronchoscopy than virtual CT elsewhere in the body. To perform aggressive transbronchial biopsy through normal appearing mucosa, maximum detail of the mucosal surface, tracheal rings, and bronchial origins will be required at virtual CT bronchoscopy.

Helical CT offers unique advantages for virtual reality imaging. A characteristic of helical CT is its improved z-axis resolution (into the gantry and parallel to the long axis of the patient) (15,16). This is very important in any three-dimensional CT application because the section thickness is several times larger than the pixel size. Even with helical CT, the z axis is responsible for major partial volume averaging artifacts, which justifies the use of volume rendering in critical clinical applications like virtual endoscopy or CT angiography. Helical CT also eliminates section-to-section (breath-to-breath) misregistration. Last, helical CT allows unlimited overlapping of reconstructed sections with no additional radiation versus nonoverlapped consecutive conventional CT.

There are two display methods currently being used for virtual CT: shaded surface and volumetric. Shaded surface display in the tracheal bronchial tree shows only the inside surface of the airways by using a selected attenuation coefficient threshold. This technique is fast and simple to use but does not allow viewing of anatomic detail underneath the surface. In addition, the optimal single attenuation coefficient for differentiating wall from lumen varies between patients and pathologic findings, which further decreases detail. Because it only evaluates a surface, surface rendering cannot be used to display extraluminal lesions. Last, surface rendering is sensitive to artifact and noise. As a result, surface rendering—with its ubiquitous volume averaging, variability, absence or exaggeration of detail, and inability to see beyond the mucosa—is undesirable for use in virtual CT of the airway (17,18).

A different rendering technique is required to view anatomic detail beneath the surface: compositing (or volumetric). With this technique, the entire imaged volume is subdivided into tissue classes based on the attenuation coefficient of each voxel. Each of the defined tissues can have different attenuations and intensities. This not only improves the detail of the luminal surface, it allows extraluminal structures, such as lymph nodes, to be treated as a separate tissue class and to be highlighted. By adjusting the luminal wall attenuation, extraluminal structures can be made visible from inside the lumen (19–23). The use of volumetric rendering also allows the use of realistic colors, which we believe increases the viewer’s depth perception and the conspicuity of small abnormalities.

Our conclusion from our previous work (24–26) is that the most important variable by far is the use of the thinnest section thickness possible. Our data also show that a section reconstruction overlap of at least 50% is necessary for the best quality images but that the milliampere setting has little impact on image quality.

There is an important deficiency with this study. Specifically, the assumption was made that a biopsy site selected by a pulmonologist on the basis of virtual CT findings without lymph node highlighting would be the same site he or she would select during actual bronchoscopy. While the display of a particular patient’s airways is similar between virtual CT bronchoscopy and actual bronchoscopy, it is certainly not the same. However, this type of study is useful in that it carried no risk to the patient by selecting the wrong transbronchial biopsy site by using an unproven technique. In addition, this study design allowed an assessment of whether virtual CT with lymph node highlighting can potentially improve the rate of successful diagnoses from transbronchial biopsy. The data in this study indicate that a clinical study would be appropriate of patients with similar nodal sites who are randomly placed into two groups to undergo transbronchial biopsy with or without the addition of virtual CT with lymph node highlighting.

In conclusion, virtual CT holds great promise in many areas of the body. With volumetric rendering, virtual CT bronchoscopy can play a major role in patients with mediastinal or hilar tumor and lymphadenopathy. While endobronchial lesions can be easily localized, virtual CT bronchoscopy offers little advantage over actual bronchoscopy except that the airway distal to the tumor can be evaluated. However, the majority of mediastinal tumors and lymph nodes do not affect the mucosa nor distort the airways. In these patients, virtual CT bronchoscopy can play an important role. By helping the bronchoscopist to localize lesions chosen from the transverse CT images, virtual CT bronchoscopy can guide biopsy of the ideal site and allow more aggressive biopsy of lesions that are in a difficult position while decreasing potential complications. An additional application for this technique could be to direct the bronchoscopist to the appropriate subsegmental airway to reach an endobronchial lesion distal to the field of view of the bronchoscope.

To our knowledge, this is the first published study to quantify the specific value of virtual CT bronchoscopy in aiding pulmonologists during transbronchial biopsy. The results of this study suggest that when a pulmonologist first views a virtual CT bronchoscopic image with the extrabronchial pathologic site highlighted, their accuracy in performing transbronchial biopsy is increased. These data also indicate the need for a clinical study to confirm these results. Virtual CT bronchoscopy with the targeted lymph node highlighted is simple, quickly performed, and a useful adjunct to improve the accuracy of transbronchial biopsy of lymph nodes and tumors that are not visible at bronchial endoscopy.

	FOOTNOTES

 
Author contributions: Guarantor of integrity of entire study, K.D.H.; study concepts and design, K.D.H.; literature research, K.D.H.; clinical studies, K.D.H., K.G., T.A.L., R.B., J.L.S., R.M.; data acquisition, K.D.H., T.A.L., J.L.S., R.B., D.T.M., R.M.; data analysis/interpretation, D.T.M., K.D.H.; statistical analysis, D.T.M.; manuscript preparation, K.D.H., T.A.L., J.L.S., R.B., D.T.M., R.M.; manuscript definition of intellectual content, K.D.H.; manuscript editing, K.G., K.D.H.; manuscript revision/review, all authors; manuscript final version approval, K.D.H., T.A.L., J.L.S., R.B., D.T.M., R.M.

	REFERENCES

TOP ABSTRACT INTRODUCTION Materials and Methods Results Discussion REFERENCES

 

1. Vining DJ, Liu K, Choplin RH, Haponik EF. Virtual bronchoscopy: relationships of virtual reality endobronchial simulations to actual bronchoscopic findings. Chest 1996; 109:549-553.
2. Gruden JF, Harkin TJ, Addrizzo-Harris DJ, McGuinness G, Bhalla M, Naidich DP. Three-dimensional virtual bronshocsopy: correlation to fiberoptic bronchoscopy in normal and diseased airways (abstr). Radiology 1996; 201(P):435.
3. McAdams HP, Erasmus JJ, Shahdi R, Argiro V, Tapson V, Kussin P. Virtual bronchoscopy: principles, pitfalls, and clinical applications (abstr). Radiology 1996; 201(P):480.
4. Mimura F, Kono M, Kusumoto M, Itouji E, Kimura K, Motoyama A. Role of 3D reconstruction spiral CT to evaluate tracheobronchial mucosa irregularity (abstr). Radiology 1996; 201(P):486.
5. Ferretti GR, Vining DJ, Knoplioch J, Coulomb M. Tracheobronchial tree: three-dimensional spiral CT with bronchoscopic perspective. J Comput Assist Tomogr 1996; 20:777-781.
6. Chin RJ, Yang GZ, Congleton J, Mellor J, Geddes DM, Hansell DM. Three-dimensional computed tomography bronchoscopy using clinical datasets: a comparison with fiberoptic bronchoscopy. Clin Radiol 1997; 52:830-836.
7. Salvolini L, Gasparini S, Baldelli S, Bichi Secchi E, Amici F. Virtual bronchoscopy: the correlation between endoscopic simulation and bronchoscopic findings. Radiol Med 1997; 94:454-462.
8. Hopper KD, Mahraj RP, Gleeson K, Iyriboz TA, Stauffer JL. CT virtual bronchoscopy in patients with non-endoscopically visible tumor/adenopathy (abstr). Radiology 1997; 205(P):672.
9. McAdams HP, Goodman PC, Kussin P. Virtual bronchoscopy for directing transbronchial needle aspiration of hilar and mediastinal lymph nodes: a pilot study. AJR Am J Roentgenol 1998; 170:1361- 1364.
10. Kvale PA, Bode FR, Kini S. Diagnostic accuracy in lung cancer: comparison of techniques used in association with flexible fiberoptic bronchoscopy. Chest 1976; 69:752-757.
11. Martini N, McCormack PM. Assessment of endoscopically visible carcinomas. Chest 1978; 73:718-720.
12. Zavala DC. Diagnostic fiberoptic bronchoscopy: techniques and results of biopsy in 600 patients. Chest 1975; 68:12-19.
13. Lam WK, So SY, Hsu C, et al. Fiberoptic bronchoscopy in the diagnosis of bronchial cancer: comparison of washings, brushings and biopsies in central and peripheral tumours. Clin Oncol 1983; 9:35-42.
14. Seely JM, Mayo JR, Miller RR, Müller NL. T1 lung cancer: prevalence of mediastinal nodal metastases and diagnostic accuracy of CT. Radiology 1993; 186:129-132.
15. Kalender WA, Polacin A, Süss C. A comparison of conventional and spiral CT: an experimental study on the detection of spherical lesions. J Comput Assist Tomogr 1994; 18:167-176.
16. Kasales CJ, Hopper KD, Ariola DN, et al. Reconstructed helical CT scan: improvement in z-axis resolution compared with overlapped and nonoverlapped conventional CT scans. AJR Am J Roentgenol 1995; 164:1281-1284.
17. Fleiter T, Merkle EM, Aschoff AJ, et al. Comparison of real-time virtual and fiberoptic bronchoscopy in patients with bronchial carcinoma: opportunities and limitations. AJR Am J Roentgenol 1997; 169:1591-1595.
18. Higgins WE, Ramaswamy K, Swift RD, McLennan G, Hoffman EA. Virtual bronchoscopy for three-dimensional pulmonary image assessment: state of the art and future needs. RadioGraphics 1998; 18:761-778.
19. Fishman EK, Magid D, Ney DR, et al. Three-dimensional imaging. Radiology 1991; 181:321-337.
20. Fishman EK, Ney DR. Advanced computer applications in radiology: clinical applications. RadioGraphics 1993; 13:463-475.
21. Drebin RA, Carpenter L, Hanrahan P. Volume rendering. Comput Graphics 1988; 22:65-74.
22. Levoy M. Display of surfaces from volume data. IEEE Comput Graph Appl 1988; 8:29-37.
23. Hopper KD, Iyriboz AT, Wise SW, Neuman JD, Mauger DT, Kasales CJ. Mucosal detail at CT virtual reality: surface versus volume rendering. Radiology 2000; 214:517-522.
24. Hopper KD, Iyriboz TA, Mahraj RP, et al. CT bronchoscopy: optimization of imaging parameters. Radiology 1998; 209:872-877.
25. Summers RM, Shaw DJ, Shelhamer JH. CT virtual bronchoscopy of simulated endobronchial lesions: effect of scanning, reconstruction, and display settings and potential pitfalls. AJR Am J Roentgenol 1998; 170:947-950.
26. Hopper KD. CT bronchoscopy. Semin Ultrasound CT MR 1999; 20:10-15.

This article has been cited by other articles:

				G. M. Weiner, K. Schulze, B. Geiger, H. Ebhardt, K.-J. Wolf, and T. Albrecht CT Bronchoscopic Simulation for Guiding Transbronchial Needle Aspiration of Extramural Mediastinal and Hilar Lesions: Initial Clinical Results Radiology, March 1, 2009; 250(3): 923 - 931. [Abstract] [Full Text] [PDF]

				S. A. Merritt, J. D. Gibbs, K.-C. Yu, V. Patel, L. Rai, D. C. Cornish, R. Bascom, and W. E. Higgins Image-Guided Bronchoscopy for Peripheral Lung Lesions: A Phantom Study Chest, November 1, 2008; 134(5): 1017 - 1026. [Abstract] [Full Text] [PDF]

				M. Y. Dolina, D. C. Cornish, S. A. Merritt, L. Rai, R. Mahraj, W. E. Higgins, and R. Bascom Interbronchoscopist Variability in Endobronchial Path Selection: A Simulation Study Chest, April 1, 2008; 133(4): 897 - 905. [Abstract] [Full Text] [PDF]

				F. Asano, Y. Matsuno, N. Shinagawa, K. Yamazaki, T. Suzuki, T. Ishida, and H. Moriya A virtual bronchoscopic navigation system for pulmonary peripheral lesions. Chest, August 1, 2006; 130(2): 559 - 566. [Abstract] [Full Text] [PDF]

				Fluoroscopy-assisted thoracoscopic resection of pulmonary nodules after computed tomography-guided bronchoscopic metallic coil marking. J. Thorac. Cardiovasc. Surg., March 1, 2006; 131(3): 704 - 710.

				H. Asahina, K. Yamazaki, Y. Onodera, E. Kikuchi, N. Shinagawa, F. Asano, and M. Nishimura Transbronchial Biopsy Using Endobronchial Ultrasonography With a Guide Sheath and Virtual Bronchoscopic Navigation Chest, September 1, 2005; 128(3): 1761 - 1765. [Abstract] [Full Text] [PDF]

				C. M. Jones and T. Athanasiou Is Virtual Bronchoscopy an Efficient Diagnostic Tool for the Thoracic Surgeon? Ann. Thorac. Surg., January 1, 2005; 79(1): 365 - 374. [Abstract] [Full Text] [PDF]

				Y. Onodera, T. Omatsu, S. Takeuchi, N. Shinagawa, K. Yamazaki, T. Nishioka, and K. Miyasaka Enhanced Virtual Bronchoscopy Using the Pulmonary Artery: Improvement in Route Mapping for Ultraselective Transbronchial Lung Biopsy Am. J. Roentgenol., October 1, 2004; 183(4): 1103 - 1110. [Abstract] [Full Text] [PDF]

				W. De Wever, V. Vandecaveye, S. Lanciotti, and J.A. Verschakelen Multidetector CT-generated virtual bronchoscopy: an illustrated review of the potential clinical indications Eur. Respir. J., May 1, 2004; 23(5): 776 - 782. [Abstract] [Full Text] [PDF]

				N. Shinagawa, K. Yamazaki, Y. Onodera, K. Miyasaka, E. Kikuchi, H. Dosaka-Akita, and M. Nishimura CT-Guided Transbronchial Biopsy Using an Ultrathin Bronchoscope With Virtual Bronchoscopic Navigation Chest, March 1, 2004; 125(3): 1138 - 1143. [Abstract] [Full Text] [PDF]

				H. Hoppe, H.-P. Dinkel, B. Walder, G. von Allmen, M. Gugger, and P. Vock Grading Airway Stenosis Down to the Segmental Level Using Virtual Bronchoscopy Chest, February 1, 2004; 125(2): 704 - 711. [Abstract] [Full Text] [PDF]

This Article Abstract Figures Only Full Text (PDF) All Versions of this Article: 2211001585v1 221/2/531    most recent Submit a response Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Hopper, K. D. Articles by Mahraj, R. Search for Related Content PubMed PubMed Citation Articles by Hopper, K. D. Articles by Mahraj, R.