Original Article
Management of Lung Nodules Detected by Volume CT Scanning
N Engl J Med 2009; 361:2221-2229December 3, 2009
- Abstract
Background
The use of multidetector computed tomography (CT) in lung-cancer screening trials involving subjects with an increased risk of lung cancer has highlighted the problem for the clinician of deciding on the best course of action when noncalcified pulmonary nodules are detected by CT.
Methods
A total of 7557 participants underwent CT screening in years 1, 2, and 4 of a randomized trial of lung-cancer screening. We used software to evaluate a noncalcified nodule according to its volume or volume-doubling time. Growth was defined as an increase in volume of at least 25% between two scans. The first-round screening test was considered to be negative if the volume of a nodule was less than 50 mm3, if it was 50 to 500 mm3 but had not grown by the time of the 3-month follow-up CT, or if, in the case of those that had grown, the volume-doubling time was 400 days or more.
Results
In the first and second rounds of screening, 2.6% and 1.8% of the participants, respectively, had a positive test result. In round one, the sensitivity of the screen was 94.6% (95% confidence interval [CI], 86.5 to 98.0) and the negative predictive value 99.9% (95% CI, 99.9 to 100.0). In the 7361 subjects with a negative screening result in round one, 20 lung cancers were detected after 2 years of follow-up.
Conclusions
Among subjects at high risk for lung cancer who were screened in three rounds of CT scanning and in whom noncalcified pulmonary nodules were evaluated according to volume and volume-doubling time, the chances of finding lung cancer 1 and 2 years after a negative first-round test were 1 in 1000 and 3 in 1000, respectively. (Current Controlled Trials number, ISRCTN63545820.)
Media in This Article
Figure 1
Results of the First Round of Screening.Figure 2
Results of the Second Round of Screening.Article Activity
- Article
The use of multidetector computed tomography (CT) has increased the chance of finding noncalcified pulmonary nodules,1,2 and as a result, clinicians often face the problem of deciding on the best course of action with respect to such nodules when they are found in asymptomatic subjects who have an increased risk for lung cancer.3 This difficulty is especially evident in CT-based screening programs for lung cancer. The current practice is to refer participants in these programs for additional diagnostic evaluation if they have a noncalcified nodule that is larger than 5 mm in diameter.4-9 In designing the Dutch–Belgian randomized lung cancer screening trial (Nederlands-Leuvens Longkanker Screenings Onderzoek [NELSON]), we adopted a strategy that was meant to provide an inexpensive and simple follow-up process without increasing the false negative rate of the screening test.10 The strategy entailed the use of the volume and volume-doubling time of a noncalcified nodule as the main criteria for deciding on further action. In this article, we report an evaluation of this strategy, which involved the tracking of individual nodules and the collection of 2-year follow-up data from the screened population of the NELSON trial.
Methods
Participants
We randomly assigned eligible participants in NELSON, who were recruited as described previously,11 to undergo CT screening at baseline (first round), 1 year later (second round), and 3 years later (third round, 2 years after the second round), or no screening. The purpose of the trial is to determine whether at 10 years after randomization CT screening will have reduced mortality from lung cancer by at least 25%. The trial was approved by the Dutch Minister of Health and the ethics board at each participating center. All participants gave written informed consent.
Screening Strategy
A 16-detector CT scanner (Somatom Sensation 16, Siemens Medical Solutions or, at the screening site in Utrecht, 1x Mx8000 IDT or Brilliance-16P, Philips Medical Systems) was used at each of the screening sites. Data sets were derived from images of the lung with a thickness of 1 mm that were reconstructed at overlapping 0.7-mm intervals. Isotropic data sets allowed for volume measurements with good reproducibility, even in the case of small lesions.12 Data acquisition and scanning conditions were standard across screening sites and were the same for all rounds of screening.10 At each site, CT data were analyzed on one type of digital workstation (Leonardo, Siemens Medical Solutions) with the use of software for semiautomated volume measurements (LungCare, version Somaris/5 VA70C-W, Siemens Medical Solutions).13,14 In the case of inappropriate segmentation (i.e., nodules that were attached to a fissure or to a vessel), the radiologist was allowed to enter manual measurements, which overruled the automatically generated volumes. Data generated by the LungCare software were uploaded into the NELSON Management System, which automatically detected whether a nodule was new or had been present previously and which calculated the percentage change in volume and the volume-doubling time in days (Fig. 1 in the Supplementary Appendix, available with the full text of this article at NEJM.org).
A nodule was classified as noncalcified if it did not meet previously specified criteria for a benign lesion.4 For solid pleural-based and nonsolid pulmonary nodules, the diameter was determined manually, and the volume-doubling time was calculated as described previously10 (Fig. 1 in the Supplementary Appendix). In the case of pleural-based nodules, the diameter was measured at a point perpendicular to the costal pleura. In the case of partially solid lesions, only the volume of the solid region was used. The diameter was defined as the average of the maximum length and width of the nodule. Growth was defined as a change in volume of at least 25% between the first and second scans or between the second and third scans. The 25% threshold was based on three zero-change data sets in which the variation in volume of individual nodules was assessed between two low-dose CT scans. After the first of these scans, the patient returned to the examining table for the second scan to simulate the condition of a repeat examination for the follow-up of a pulmonary nodule. In these studies, the volume measurement error varied between 20% and 25%.12,14,15 Growing nodules were classified into three growth categories according to their volume-doubling time (<400, 400 to 600, and >600 days).
CT scans were independently read by first and second readers. The experience of the 13 first readers ranged from none to more than 20 years of experience reading thoracic CT scans (median, 6 years); both second readers had 6 years of experience. The second readers matched the nodules they had identified with nodules identified by the first readers according to location and size and compared their results with those of the first readers. If the results were discrepant, the readers reevaluated the scan to reach a consensus. If no consensus was reached, a third radiologist arbitrated the results.
First-Round (Baseline) Scan
A test was considered to be positive if on the CT scan any noncalcified nodule had a solid component that was more than 500 mm3 (>9.8 mm in diameter) and was considered to be indeterminate if the volume of the largest solid nodule or of the solid component of a partially solid nodule was 50 to 500 mm3 (4.6 to 9.8 mm in diameter) or if the diameter of a nonsolid nodule was greater than 8 mm.10 In subjects with an indeterminate result, a follow-up scan was obtained 3 months after the baseline scan to assess the growth of the lesion. If at that time the lesion had a volume-doubling time of less than 400 days, the final result was declared to be positive; otherwise, it was considered to be negative. Subjects with positive screening tests were referred to a chest physician for workup and diagnosis. If lung cancer was diagnosed, the participant was treated for the disease and left the screening trial; if no lung cancer was found, the regular second-round CT scan was scheduled for 12 months after the baseline scan.
Second-Round Scan
When one or more new nodules were found on the second-round scan, the interpretation (positive or negative result) was based on the size of the nodule, as it had been in round one; if the result was indeterminate, a follow-up scan was obtained 6 weeks later.10 In the case of nodules that had been detected previously, the second-round result was based on the volume-doubling time. If there was no growth, or if the volume-doubling time was more than 600 days, the screen was classified as negative. If the volume-doubling time was less than 400 days, or if a new solid component had emerged in a previously nonsolid nodule, the scan was considered to be positive. When the volume-doubling time was 400 to 600 days, the test result was considered to be indeterminate and a follow-up scan was obtained 1 year after the second-round scan. At that time, if the volume-doubling time was less than 400 days, the final result was considered to be positive; otherwise it was considered to be negative. If both new and existing nodules were present, the nodule with the largest volume or fastest growth determined the result. All participants with a negative second-round test result were invited to undergo the third round of screening 2 years after the second round. A cancer detected on screening was classified as a first-round or second-round cancer if it was diagnosed after a workup during the first year after a positive first-round or second-round screen, respectively. Lung cancers that were detected during the first year after a negative first-round or second-round screening test were classified as interval cancers. They were identified through linkage with the national pathology database, information from participants and general practitioners, and, in the case of round-one interval cancers, linkage with the National Cancer Registry. The workup, staging, and treatment were standard across all screening sites and were performed according to published guidelines.10,16,17
All the authors contributed to the data collection and the decision to submit the manuscript for publication, and all the authors vouch for the accuracy and completeness of the data.
Statistical Analysis
The diagnostic sensitivity was defined as the ratio between the number of true positive results (participants who were diagnosed with lung cancer during the first year after a positive screening test) and the number of true positive results plus the number of false negative results (interval cancers detected during the same time period). Diagnostic sensitivity, specificity, positive predictive value, and negative predictive value were calculated at the participant level, and 95% confidence intervals were determined with the use of SPSS software, version 15.0 (SPSS). The standard for a negative baseline or second-round test result was based on the retrospective information that lung cancer was absent 2 years after the first round of screening and 1 year after the second round. Normally distributed data are shown as means ±SD. P values of less than 0.05 were considered to indicate statistical significance.
Results
First Round
The mean (±SD) age of the screened participants was 59±6 years, and the mean number of pack-years smoked was 42±19; a total of 16% of the participants were women. The first round of screening was conducted from April 2004 through December 2006 (Fig. 2 in the Supplementary Appendix). Of the 7557 participants, 50.5% had a total of 8623 noncalcified pulmonary nodules, of which 98.0% were solid. Automated volumetric data were manually adjusted in the case of 6.3% of the nodules. The screening results were determined to be negative in 5987 participants (79.2%), indeterminate in 1451 (19.2%), and positive in 119 (1.6%) (Figure 1Figure 1
Results of the First Round of Screening.). A total of 1536 follow-up scans were obtained 100±19 days, on average, after the baseline scan in participants with an indeterminate result. Including the outcome of these follow-up scans, the results from round one of the screening were negative in 7361 participants (97.4%) and positive in 196 (2.6%).Of the 196 participants with a positive scan, 177 were referred for workup; 19 were not referred (9 because of a decision by the tumor board, 3 because of an administrative error, and 7 because they were already receiving treatment from another specialist). Lung cancer was diagnosed in 70 of the 177 participants who had a positive scan (39.5%); the diagnosis was made mainly by means of an invasive procedure (85.7%). These 70 participants had 72 lung cancers, of which 46 (63.9%) were classified as pathological stage I. In three subjects, no tissue for a histologic diagnosis could be obtained. These subjects received high-dose radiotherapy because the lesions were growing and were assessed as positive on a positron-emission tomographic (PET) scan. Of the remaining 107 subjects with a positive scan, 100 had benign disease and 7 had metastases from another cancer. In round one, the proportion of invasive procedures that revealed benign disease was 27.2%.
The lung-cancer detection rate in round one was 0.9% (70 of 7557 subjects). There were four interval cancers, all of which were stage IV adenocarcinomas; three of these were new noncalcified nodules, and one, which had been seen in the first round, had a volume-doubling time of more than 600 days at the 3-month follow-up. The sensitivity of round-one screening was 94.6% (95% confidence interval [CI], 86.5 to 98.0), the specificity 98.3% (95% CI, 98.0 to 98.6), the positive predictive value 35.7% (95% CI, 29.3 to 42.7), and the negative predictive value 99.9% (95% CI, 99.9 to 100.0). Thus, in a subject with a positive CT screening test, the probability that the lesion would be malignant was 36%; with a negative screening test, the probability that a participant would not have lung cancer was 99.9%.
Among the 7361 negative CT scans in round one, 20 lung cancers were detected during the 2 years of follow-up: 3 were round-one interval cancers, and 17 were detected in the round-two screening. On the basis of this information, the negative predictive value was 99.7% (95% CI, 99.6 to 99.8). All 126 participants with a positive screening result at round one but with a negative workup returned to the screening program. After a mean follow-up of 785±263 days, 10 of these 126 subjects received the diagnosis of pulmonary adenocarcinoma, which appeared to have originated from a suspicious nodule that was detected in round one (Table 1 in the Supplementary Appendix).
Second Round
In accordance with the trial's protocol, all the participants in the first round of screening, except those in whom lung cancer had been diagnosed, were invited to undergo screening in the second round,12 which was conducted from April 2005 through April 2008. A total of 7289 participants underwent screening 384±59 days after the round-one screening (Fig. 1 in the Supplementary Appendix). In 1588 (21.8%) of these participants, a total of 2320 new nodules were detected, 29.2% of which had a volume of less than 15 mm3 or had been missed in round one. Automated volumetric data were manually adjusted in the case of 5.4% of the new nodules and 1.9% of previously existing nodules. The second-round screening result was negative in 6719 participants (92.2%), indeterminate in 480 (6.6%), and positive in 90 (1.2%) (Figure 2Figure 2
Results of the Second Round of Screening.). Among participants with an indeterminate result, 276 had a follow-up scan 77±36 days after the second-round screening and 231 had a follow-up scan 364±36 days after the second-round screening. The follow-up scans were positive in 38 subjects, and when the results of these positive follow-up scans were added to the results of the 90 positive screening scans, there were 128 subjects (1.8%) with positive second-round scans. Of these 128 participants, 1 patient died as a result of a metastatic colon carcinoma and 118 were referred for workup; 54 of the 118 who were referred for workup (45.8%) received the diagnosis of lung cancer, mainly after undergoing an invasive procedure (88.9%). The nine participants who were not referred for workup (four because of a decision by the tumor board, four because of an administrative error, and one because the patient was already receiving treatment from another specialist) were invited to participate in the third round of screening 2 years later. In one of these nine, lung cancer was found 23 months after the first detection of the nodule in a nodule that had not been seen previously. Of the remaining 64 subjects with a positive scan, 62 had benign disease and 2 had another cancer (1 a thymoma and 1 lymphoma).There were two subjects with suspicious lesions from whom no tissue could be obtained for histologic diagnosis. These subjects were treated with high-dose radiotherapy because the lesions were new and growing and were positive on a PET scan. The 54 participants with lung cancer had 57 cancerous nodules, 42 of which (73.7%) were classified as pathological stage I, including 3 that were synchronous double tumors. The lung-cancer detection rate was 0.5% (40 of 7289) during the first year after the second-round screening and 0.8% (57 of 7289) for the entire 2-year period after the second and third rounds of screening. One stage IV small-cell and one stage IV large-cell interval carcinoma, both of which were present in nodules that had been absent at the time of the second-round screening, were diagnosed during the first year after the second-round screening. The sensitivity of the second-round screening was 96.4% (95% CI, 86.8 to 99.1), the specificity was 99.0% (95% CI, 98.7 to 99.2), the positive predictive value was 42.2% (95% CI, 33.9 to 50.9), and the negative predictive value was 99.9% (95% CI, 99.9 to 100.0).
Additional Diagnostic Investigations
The recall rates for CT scans among participants with indeterminate test results were 19.0% and 3.8% in rounds one and two, respectively (Table 2 in the Supplementary Appendix). No diagnostic PET or PET–CT scanning was performed in participants with positive test results, and fine-needle biopsy procedures were performed in less than 1% of the subjects. The rate of invasive diagnostic procedures was 1.2% in round one and 0.8% in round two.
Discussion
In a population that was at an increased risk for lung cancer, our strategy of screening for lung cancer with the use of volume CT diminished the need for follow-up evaluation in participants with an indeterminate test result. This strategy was especially useful during the second-round screening. It reduced the number of follow-up examinations in participants with a positive test result without reducing the overall sensitivity of the technique, as compared with that reported in the literature.4-8,18-23 This report concerns itself only with how to deal with an abnormality that has been detected on a CT scan in this population; it does not address the usefulness of screening for lung cancer with the use of CT scanning.
The rate of interval cancers that were found in participants in our trial was similar to that found in participants in other trials.20 The proportion of early (stage I) lung cancers detected in round one (63.9%) was similar to that found in other randomized trials,18,19,23 but lower than that found in nonrandomized trials (e.g., the proportion in the International Early Lung Cancer Action Program [I-ELCAP] was 86%, and the proportion in a trial performed at the Mayo Clinic was 75%).6,7,20 The lung-cancer detection rate in round one in I-ELCAP was higher than that in NELSON (1.3% vs. 0.9%),7 despite similar median ages of the participants and a higher number of pack-years smoked by participants in NELSON. The discrepancy was probably due to the fact that the proportion of women, who tend to have slow-growing cancers,24,25 was higher in I-ELCAP than in NELSON. Moreover, in I-ELCAP surgeons removed any nonsolid nodule that was larger than 8 mm, instead of waiting for the nodule to grow before removing it, as was done in NELSON. In our trial of subjects who had an increased risk of lung cancer, we found that the chances of finding lung cancer on a CT scan at 3 months, 1 year, and 2 years after a negative first-round test were 0, 1 in 1000, and 3 in 1000, respectively.
In round one, the proportion of invasive procedures that revealed benign disease was 27.2%, which is similar to that found in other trials.5,6,19,21,22,26-30 The advantages of volumetric measurements become fully apparent when a volumetric comparison can be made with a previous indeterminate CT scan. Because there were no comparative CT scans available at round one, the first-round recall rate was almost as high as that in other trials (Table 2 in the Supplementary Appendix). The LungCare software version that we used is not proprietary and can be used with any CT data set, regardless of the CT system, for evaluation of solid nodules and the solid component of partially solid noncalcified nodules smaller than 500 mm3. With manual correction, the mean relative deviation from the true lesion volume was only −0.3±6.5% for these types of lesions.13
As an absolute standard for negative test results, we used the absence of lung cancer after 2 years of follow-up, a period that is considered to be sufficient for concluding that a nodule is benign.2 The 400-day threshold for volume-doubling time that we used was based on current opinion that lung cancers with a volume-doubling time of 400 days or more are overdiagnosed cases.24,31 A volume-doubling time of 500 days is regarded as the upper limit for lung cancer, even though some tumors may grow more slowly 32-34; our upper limit was set at 600 days. If a lower upper limit had been used, the rate of false negatives would have increased, but the rate of false positives would have decreased. Therefore, the ranges for volume-doubling time that we used are not definite and could be improved. Finally, before we can make clinically directive recommendations, our strategy requires validation in an independent study.
Supported by Zorg Onderzoek Nederland-Medische Wetenschappen, KWF Kankerbestrijding, Stichting Centraal Fonds Reserves van Voormalig Vrijwillige Ziekenfondsverzekeringen, G. Ph. Verhagen Foundation, Rotterdam Oncologic Thoracic Study Group, Erasmus Trust Fund, Foundation against Cancer, Flemish League against Cancer, and Lokaal Gezondheids Overleg (LOGO) Leuven and Hageland. Roche Diagnostics provided an unrestricted research grant. Siemens Germany provided four digital workstations and accompanying software but had no other role in the study.
Dr. van Klaveren reports receiving advisory board fees, lecture fees, and grant support from Eli Lilly, Roche Pharmaceuticals, and Roche Diagnostics; Dr. Weenink, lecture fees from Mundipharma; and Dr. Lammers, lecture fees from Novartis and grant support from a public–private partnership (Utrecht University, GlaxoSmithKline, Nycomed, and AstraZeneca). No other potential conflict of interest relevant to this article was reported.
We thank Ton de Jongh, ARTEX, Capelle aan den IJssel, the Netherlands, for developing and maintaining the NELSON database and management system (Nelson Management System); the representatives of the municipal health services (Gemeentelijke Geneeskundige en Gezondsheidsdienst [GGD]) for providing the addresses of the participants from the population registries: J. Toet, M.Sc. and E.J.C. van Ameijden, Ph.D. (GGD Utrecht), J.M. ten Brinke, M.Sc. (GGD Amstelland de Meerlanden), A.E.M. Grotenhuis and W. Nijbroek, M.Sc. (GGD Kennemerland), E. Tromp, Ph.D. (GGD Midden Nederland), N. de Vos, M.Sc. (GGD Eemland), J. Broer, M.D., Ph.D. (GGD Groningen), C.A. Bos, M.A., M.Sc. (GGD Drenthe), LOGO Leuven and Hageland, Belgium; and Marielle Caspari, M.D. (the Dutch national pathology database), Roel Faber, Frank Santegoets, Suzie Otto, M.D., Ph.D., Jacque Fracheboud, M.D., Eleonora Baecke, M.D., Linda van Dongen, Marianne Quak and Anne Koch (Erasmus Medical Center); Hester van der Zaag, Ph.D., Wouter de Jongh, M.D., Ph.D., Ria Ziengs, Wim Tukker (University Medical Center Groningen); Anneke Hamersma, Saskia van der Vorst, (University Medical Center Utrecht); L.P. Driessen, M.D., Wauter de Monyé, M.D., Ph.D., Henk Pruiksma (Kennermer Gasthuis Haarlem); Feng Cheng, M.D., Walter de Wever, M.D., Ph.D., Walter Coudijzer, Paul De Leyn M.D., Ph.D., Erik Verbeken, M.D., Ph.D., Liesbet Peeters and Beatrijs Anrijs (University Hospital Gasthuisberg Leuven, Belgium).
Source Information
From the Departments of Pulmonology (R.J.K., R.V., C.A.I., S.W., C.A.) and Public Health (C.A.I., K.A.M.B., C.A., H.J.K.), Erasmus Medical Center, Rotterdam; the Departments of Radiology (M.O., D.M.X., Y.W., Y.Z., P.O.), Epidemiology (G.H.B.), Pulmonology (H.J.M.G.), and Pathology (W.T.), University Medical Center, Groningen; the Departments of Radiology, (M.P., H.A.G., B.-J.H., W.M.), Pulmonology (J.-W.J.L.), and Pathology (A.V.), University Medical Center, Utrecht; the Departments of Radiology (E.T.S.), Pulmonology (C.W.), and Pathology (D.W.), Kennemer Gasthuis, Haarlem; and the Department of Pathology, Free University Medical Center Amsterdam, Amsterdam (E.T.) — all in the Netherlands; and the Departments of Pulmonology (K.N.) and Radiology (J.V.), University Hospital Gasthuisberg Leuven, Leuven, Belgium.
Address reprint requests to Dr. van Klaveren at the Department of Pulmonology, Erasmus Medical Center, 3000 CA Rotterdam, the Netherlands, or at r.j.vanklaveren@erasmusmc.nl.
- References
References
1
Fischbach F ,Knollmann F ,Griesshaber V ,Freund T ,Akkol E ,Felix R . Detection of pulmonary nodules by multislice computed tomography: improved detection rate with reduced slice thickness. Eur Radiol 2003;13:2378-2383
CrossRef | Web of Science | Medline2
MacMahon H ,Austin JH ,Gamsu G , et al. Guidelines for management of small pulmonary nodules detected on CT scans: a statement from the Fleischner Society. Radiology 2005;237:395-400
CrossRef | Web of Science | Medline3
van Klaveren RJ ,de Koning HJ ,Mulshine J ,Hirsch FR . Lung cancer screening by spiral CT: what is the optimal target population for screening trials? Lung Cancer 2002;38:243-252
CrossRef | Web of Science | Medline4
Henschke CI ,McCauley DI ,Yankelevitz DF , et al. Early Lung Cancer Action Project: overall design and findings from baseline screening. Lancet 1999;354:99-105
CrossRef | Web of Science | Medline5
Pastorino U ,Bellomi M ,Landoni C , et al. Early lung-cancer detection with spiral CT and positron emission tomography in heavy smokers: 2-year results. Lancet 2003;362:593-597
CrossRef | Web of Science | Medline6
Swensen SJ ,Jett JR ,Hartman TE , et al. CT screening for lung cancer: five-year prospective experience. Radiology 2005;235:259-265
CrossRef | Web of Science | Medline7
The International Early Lung Cancer Action Program Investigators
Full Text | Web of Science | Medline8
Sone S ,Nakayama T ,Honda T , et al. Long-term follow-up study of a population-based 1996-1998 mass screening programme for lung cancer using mobile low-dose spiral computed tomography. Lung Cancer 2007;58:329-341
CrossRef | Web of Science | Medline9
National Lung Screening Trial. Bethesda, MD: National Cancer Institute. (Accessed November 6, 2009, at http://www.nci.nih.gov/NLST.)
10
Xu DM ,Gietema HA ,de Koning H , et al. Nodule management protocol of the NELSON randomised lung cancer screening trial. Lung Cancer 2006;54:177-184
CrossRef | Web of Science | Medline11
Van Iersel CA ,de Koning HJ ,Draisma G , et al. Risk-based selection from the general population in a screening trial: selection criteria, recruitment and power for the Dutch-Belgian randomised lung cancer multi-slice CT screening trial (NELSON). Int J Cancer 2007;120:868-874
CrossRef | Web of Science | Medline12
Gietema HA ,Schaefer-Prokop CM ,Mali WP ,Groenewegen G ,Prokop M . Pulmonary nodules: interscan variability of semi-automated volume measurement with multisection CT -- influence of inspiration level, nodule size and segmentation performance. Radiology 2007;245:888-894
CrossRef | Web of Science | Medline13
Bolte H ,Riedel C ,Muller-Hulsbeck S , et al. Precision of computer-aided volumetry of artificial small solid pulmonary nodules in ex vivo porcine lungs. Br J Radiol 2007;80:414-421
CrossRef | Web of Science | Medline14
Wormanns D ,Kohl G ,Klotz E , et al. Volumetric measurement of pulmonary nodules at multi-row detector CT: in vivo reproducibility. Eur Radiol 2004;14:86-92
CrossRef | Web of Science | Medline15
Goodman LR ,Gulsun M ,Washington L ,Nagy PG ,Piacsek KL . Inherent variability of CT lung nodule measurements in vivo using semi-automated volumetric measurements. AJR Am J Roentgenol 2006;186:989-994
CrossRef | Web of Science | Medline16
Mountain CF . Revisions in the International System for Staging Lung Cancer. Chest 1997;111:1710-1717
CrossRef | Web of Science | Medline17
CBO guideline — non-small cell lung cancer: staging and treatment. Alphen aan de Rijn, the Netherlands: Van Zuiden Communications BV, 2004.
18
Blanchon T ,Brechot JM ,Grenier PA , et al. Baseline results of the Depiscan study: a French randomized pilot trial of lung cancer screening comparing low dose CT scan (LDCT) and chest X-ray (CXR). Lung Cancer 2007;58:50-58
CrossRef | Web of Science | Medline19
Infante M ,Lutman FR ,Cavuto S , et al. Lung cancer screening with spiral CT: baseline results of the randomized DANTE trial. Lung Cancer 2008;59:355-363
CrossRef | Web of Science | Medline20
Black WC . Computed tomography screening for lung cancer: review of screening principles and update on current status. Cancer 2007;110:2370-2384
CrossRef | Web of Science | Medline21
Wilson DO ,Weissfeld JL ,Fuhrman CR , et al. The Pittsburgh Lung Cancer Screening Study (PLuSS): outcomes within 3 years of a first CT scan. Am J Respir Crit Care Med 2008;178:956-961
CrossRef | Web of Science | Medline22
Veronesi G ,Bellomi M ,Veronesi U , et al. Role of positron emission tomography scanning in the management of lung nodules detected at baseline computed tomography screening. Ann Thorac Surg 2007;84:959-966
CrossRef | Web of Science | Medline23
Lopes Pegna A ,Picozzi G ,Mascalchi M , et al. Design, recruitment and baseline results of the ITALUNG trial for lung cancer screening with low-dose CT. Lung Cancer 2009;64:34-40
CrossRef | Web of Science | Medline24
Lindell RM ,Hartman TE ,Swensen SJ , et al. Five-year lung cancer screening experience: CT appearance, growth rate, location and histologic features of 61 lung cancers. Radiology 2007;242:555-562
CrossRef | Web of Science | Medline25
International Early Lung Cancer Action Program investigators
CrossRef | Web of Science26
Gohagan J ,Marcus P ,Fagerstrom R , et al. Baseline findings of a randomized feasibility trial of lung cancer screening with spiral CT scan vs chest radiograph: the Lung Screening Study of the National Cancer Institute. Chest 2004;126:114-121
CrossRef | Web of Science | Medline27
Gohagan JK ,Marcus PM ,Fagerstrom RM , et al. Final results of the Lung Screening Study, a randomized feasibility study of spiral CT versus chest X-ray screening for lung cancer. Lung Cancer 2005;47:9-15
CrossRef | Web of Science | Medline28
Menezes RJ, Roberts HC, Paul NS, et al. Lung cancer screening using low-dose computed tomography in at-risk individuals: the Toronto experience. Lung Cancer 2009 May 6 (Epub ahead of print).
29
Veronesi G ,Bellomi M ,Mulshine JL , et al. Lung cancer screening with low-dose computed tomography: a non-invasive diagnostic protocol for baseline nodules. Lung Cancer 2008;61:340-349
CrossRef | Web of Science | Medline30
Veronesi G ,Bellomi M ,Scanagatta P , et al. Difficulties encountered managing nodules detected during a computed tomography lung cancer screening program. J Thorac Cardiovasc Surg 2008;136:611-617
CrossRef | Web of Science | Medline31
Yankelevitz DF ,Kostis WJ ,Henschke CI , et al. Overdiagnosis in chest radiographic screening for lung carcinoma: frequency. Cancer 2003;97:1271-1275
CrossRef | Web of Science | Medline32
Revel MP ,Merlin A ,Peyrard S , et al. Software volumetric evaluation of doubling times for differentiating benign versus malignant pulmonary nodules. AJR Am J Roentgenol 2006;187:135-142
CrossRef | Web of Science | Medline33
Winer-Muram HT ,Jennings SG ,Tarver RD , et al. Volumetric growth rate of stage I lung cancer prior to treatment: serial CT scanning. Radiology 2002;223:798-805
CrossRef | Web of Science | Medline34
Lindell RM, Hartman TE, Swensen SJ, Jett JR, Midthun DE, Mandrekar JN. 5-Year lung cancer screening experience: growth curves of 18 lung cancers compared to histological type, CT attenuation, stage, survival and size. Chest 2009 July 6 (Epub ahead of print).
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William Krimsky, Luis M. Seijo. (2012) Bronchoscopy and the peripheral nodule in the age of lung cancer screening and targeted therapies. Current Respiratory Care Reports
CrossRef3
Alexander Sasha Krupnick, Vanessa K Tidwell, John A Engelbach, Vamsi V Alli, Arye Nehorai, Ming You, Haris G Vikis, Andrew E Gelman, Daniel Kreisel, Joel R Garbow. (2012) Quantitative monitoring of mouse lung tumors by magnetic resonance imaging. Nature Protocols 7:1, 128-142
CrossRef4
Ingrid Broodman, Dominique de Costa, Christoph Stingl, Lennard J. M. Dekker, Martijn M. VanDuijn, Jan Lindemans, Rob J. van Klaveren, Theo M. Luider. (2012) Mass spectrometry analyses of κ and λ fractions result in increased number of complementarity-determining region identifications. PROTEOMICS 12:2, 183-191
CrossRef5
John K. Field, Robert A. Smith, Denise R. Aberle, Matthijs Oudkerk, David R. Baldwin, David Yankelevitz, Jesper Holst Pedersen, Scott James Swanson, William D. Travis, Ignacio I. Wisbuba, Masayuki Noguchi, Jim L. Mulshine. (2012) International Association for the Study of Lung Cancer Computed Tomography Screening Workshop 2011 Report. Journal of Thoracic Oncology 7:1, 10-19
CrossRef6
Yoshiki Kawata, Noboru Niki, Hironobu Ohmatsu, Masahiko Kusumoto, Takaaki Tsuchida, Kenji Eguchi, Masahiro Kaneko, Noriyuki Moriyama. (2012) Quantitative classification based on CT histogram analysis of non-small cell lung cancer: Correlation with histopathological characteristics and recurrence-free survival. Medical Physics 39:2, 988
CrossRef7
R. Rajani, R. L. Brum, R. Preston, G. Carr-White, D. S. Berman. (2011) Coronary computed tomography angiography for the evaluation of patients with acute chest pain. International Journal of Clinical Practice 65:12, 1267-1273
CrossRef8
Arjun Nair, David M. Hansell. (2011) European and North American lung cancer screening experience and implications for pulmonary nodule management. European Radiology 21:12, 2445-2454
CrossRef9
David E. Midthun. (2011) Screening for Lung Cancer. Clinics in Chest Medicine 32:4, 659-668
CrossRef10
J.-C. Dalphin. (2011) Quels sont les objectifs du suivi post-professionnel, les bénéfices attendus et les risques possibles ? Objectifs médicaux en termes de morbidité, mortalité et qualité de vie. Revue des Maladies Respiratoires 28:10, 1230-1240
CrossRef11
Mingzhu Liang, Xueguo Liu, Weidong Li, Kunwei Li, Xiangmeng Chen, Guojie Wang, Kai Chen, Jinxin Zhang. (2011) Evaluating the growth of pulmonary nodular ground-glass opacity on CT: Comparison of volume rendering and thin slice images. Journal of Huazhong University of Science and Technology [Medical Sciences] 31:6, 846-851
CrossRef12
Stephen G Spiro, Neal Navani. (2011) Screening for lung cancer: Is this the way forward?. Respirologyno-no
CrossRef13
Carlijn M. van der Aalst, Harry J. de Koning, Karien A.M. van den Bergh, Marc C. Willemsen, Rob J. van Klaveren. (2011) The effectiveness of a computer-tailored smoking cessation intervention for participants in lung cancer screening: A randomised controlled trial. Lung Cancer
CrossRef14
Peter Goldstraw, David Ball, James R Jett, Thierry Le Chevalier, Eric Lim, Andrew G Nicholson, Frances A Shepherd. (2011) Non-small-cell lung cancer. The Lancet 378:9804, 1727-1740
CrossRef15
Claudia I. Henschke, David F. Yankelevitz, Anthony P. Reeves, Matthew D. Cham. (2011) Image Analysis of Small Pulmonary Nodules Identified by Computed Tomography. Mount Sinai Journal of Medicine: A Journal of Translational and Personalized Medicine 78:6, 882-893
CrossRef16
Susan C. vanʼt Westeinde, Harry J. de Koning, Frederik B. Thunnissen, Matthijs Oudkerk, Harry J. M. Groen, Jan-Willem J. Lammers, Carla Weenink, Rene Vernhout, Kristiaan Nackaerts, Willem Mali, Rob J. van Klaveren. (2011) The Role of the (18)F-Fluorodeoxyglucose-Positron Emission Tomography Scan in the Nederlands Leuvens Longkanker Screenings Onderzoek Lung Cancer Screening Trial. Journal of Thoracic Oncology 6:10, 1704-1712
CrossRef17
Christoph Kneip, Bernd Schmidt, Anke Seegebarth, Sabine Weickmann, Michael Fleischhacker, Volker Liebenberg, John K. Field, Dimo Dietrich. (2011) SHOX2 DNA Methylation Is a Biomarker for the Diagnosis of Lung Cancer in Plasma. Journal of Thoracic Oncology 6:10, 1632-1638
CrossRef18
Rob J. van Klaveren. (2011) Lung cancer screening. European Journal of Cancer 47, S147-S155
CrossRef19
G. Ferretti, D. Moro-Sibilot, C. Brambilla. (2011) Dépistage scannographique du cancer bronchique. Revue des Maladies Respiratoires Actualités 3:4, 388-390
CrossRef20
The National Lung Screening Trial Research Team . (2011) Reduced Lung-Cancer Mortality with Low-Dose Computed Tomographic Screening. New England Journal of Medicine 365:5, 395-409
Full Text21
Robert J. Korst, Benjamin E. Lee, Glenn A. Krinsky, John R. Rutledge. (2011) The utility of automated volumetric growth analysis in a dedicated pulmonary nodule clinic. The Journal of Thoracic and Cardiovascular Surgery 142:2, 372-377
CrossRef22
Jeremy Force, Arun Rajan, Eva Dombi, Seth M. Steinberg, Giuseppe Giaccone. (2011) Assessment of Objective Responses Using Volumetric Evaluation in Advanced Thymic Malignancies and Metastatic Non-small Cell Lung Cancer. Journal of Thoracic Oncology 6:7, 1267-1273
CrossRef23
Mizuki Nishino, David M. Jackman, Hiroto Hatabu, Pasi A. Jänne, Bruce E. Johnson, Annick D. Van den Abbeele. (2011) Imaging of Lung Cancer in the Era of Molecular Medicine. Academic Radiology 18:4, 424-436
CrossRef24
James L. Mulshine, Rob J. van Klaveren. (2011) Lung cancer screening: What is the benefit and what do we do about it?. Lung Cancer 71:3, 247-248
CrossRef25
Maurizio Infante, Giuseppe Chiesa, Daniel Solomon, Emanuela Morenghi, Eliseo Passera, Fabio Romano Lutman, Edoardo Bottoni, Umberto Cariboni, Valentina Errico, Emanuele Voulaz, Giorgio Ferraroli, Alberto Testori, Francesco Inzirillo, Maurizio Chiarenza, Massimo Roncalli, Silvio Cavuto, Arturo Chiti, Marco Alloisio, Gianluigi Ravasi. (2011) Surgical Procedures in the DANTE Trial, A Randomized Study of Lung Cancer Early Detection with Spiral Computed Tomography. Journal of Thoracic Oncology 6:2, 327-335
CrossRef26
William D. Travis, Elisabeth Brambilla, Masayuki Noguchi, Andrew G. Nicholson, Kim R. Geisinger, Yasushi Yatabe, David G. Beer, Charles A. Powell, Gregory J. Riely, Paul E. Van Schil, Kavita Garg, John H. M. Austin, Hisao Asamura, Valerie W. Rusch, Fred R. Hirsch, Giorgio Scagliotti, Tetsuya Mitsudomi, Rudolf M. Huber, Yuichi Ishikawa, James Jett, Montserrat Sanchez-Cespedes, Jean-Paul Sculier, Takashi Takahashi, Masahiro Tsuboi, Johan Vansteenkiste, Ignacio Wistuba, Pan-Chyr Yang, Denise Aberle, Christian Brambilla, Douglas Flieder, Wilbur Franklin, Adi Gazdar, Michael Gould, Philip Hasleton, Douglas Henderson, Bruce Johnson, David Johnson, Keith Kerr, Keiko Kuriyama, Jin Soo Lee, Vincent A. Miller, Iver Petersen, Victor Roggli, Rafael Rosell, Nagahiro Saijo, Erik Thunnissen, Ming Tsao, David Yankelewitz. (2011) International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society International Multidisciplinary Classification of Lung Adenocarcinoma. Journal of Thoracic Oncology 6:2, 244-285
CrossRef27
Sandra C. Tomaszek, Dennis A. Wigle. (2011) Pretreatment Assessment for the Optimal Management of Early-Stage Lung Cancer. The Cancer Journal 17:1, 11-17
CrossRef28
Jin Mo Goo. (2011) A Computer-Aided Diagnosis for Evaluating Lung Nodules on Chest CT: the Current Status and Perspective. Korean Journal of Radiology 12:2, 145
CrossRef29
C. Bendtsen, M. Kietzmann, R. Korn, P. D. Mozley, G. Schmidt, G. Binnig. (2011) X-Ray Computed Tomography: Semiautomated Volumetric Analysis of Late-Stage Lung Tumors as a Basis for Response Assessments. International Journal of Biomedical Imaging 2011, 1-11
CrossRef30
J. Clay Callison, Ronald C. Walker, Pierre P. Massion. (2011) Somatostatin Receptors in Lung Cancer: From Function to Molecular Imaging and Therapeutics. Journal of Lung Cancer 10:2, 69
CrossRef31
Hemant K Roy, Thomas Hensing, Vadim Backman. (2011) Nanocytology for field carcinogenesis detection: novel paradigm for lung cancer risk stratification. Future Oncology 7:1, 1-3
CrossRef32
Susan C. van't Westeinde, Rob J. van Klaveren. (2011) Screening and Early Detection of Lung Cancer. The Cancer Journal 17:1, 3-10
CrossRef33
L.T. Tanoue. (2011) Management of Lung Nodules Detected by Volume CT Scanning. Yearbook of Pulmonary Disease 2011, 78-79
CrossRef34
Jessica C. Sieren, Yoshiharu Ohno, Hisanobu Koyama, Kazuro Sugimura, Geoffrey McLennan. (2010) Recent technological and application developments in computed tomography and magnetic resonance imaging for improved pulmonary nodule detection and lung cancer staging. Journal of Magnetic Resonance Imaging 32:6, 1353-1369
CrossRef35
Karien A.M. van den Bergh, Marie-Louise Essink-Bot, Rob J. van Klaveren, Harry J. de Koning. (2010) Informed decision making does not affect health-related quality of life in lung cancer screening (NELSON trial). European Journal of Cancer 46:18, 3300-3306
CrossRef36
M. J. A. Gondrie, W. P. Th. M. Mali, C. F. M. Buckens, P. C. A. Jacobs, D. E. Grobbee, Y Graaf. (2010) The PROgnostic Value of unrequested Information in Diagnostic Imaging (PROVIDI) Study: rationale and design. European Journal of Epidemiology 25:10, 751-758
CrossRef37
Concetta De Cicco, Massimo Bellomi. (2010) Reply. The Annals of Thoracic Surgery 90:4, 1398-1399
CrossRef38
Celine Mascaux, Nir Peled, Kavita Garg, Yasufumi Kato, Murry W Wynes, Fred R Hirsch. (2010) Early detection and screening of lung cancer. Expert Review of Molecular Diagnostics 10:6, 799-815
CrossRef39
P. D. Mozley, L. H. Schwartz, C. Bendtsen, B. Zhao, N. Petrick, A. J. Buckler. (2010) Change in lung tumor volume as a biomarker of treatment response: a critical review of the evidence. Annals of Oncology 21:9, 1751-1755
CrossRef40
Maurizio V Infante, Jesper H Pedersen. (2010) Screening for lung cancer: are we there yet?. Current Opinion in Pulmonary Medicine 16:4, 301-306
CrossRef41
Peter J. Mazzone. (2010) Lung Cancer Screening: An Update, Discussion, and Look Ahead. Current Oncology Reports 12:4, 226-234
CrossRef42
U Pastorino. (2010) Lung cancer screening. British Journal of Cancer 102:12, 1681-1686
CrossRef43
(2010) Management of Lung Nodules Detected by Volume CT Scanning. New England Journal of Medicine 362:8, 757-759
Full Text44
Mulshine, James L., Jablons, David M., . (2009) Volume CT for Diagnosis of Nodules Found in Lung-Cancer Screening. New England Journal of Medicine 361:23, 2281-2282
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