Volume and Mass Doubling Times of Persistent Pulmonary Subsolid Nodules Detected in Patients without Known Malignancy 1

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1 Note: This copy is for your personal non-commercial use only. To order presentation-ready copies for distribution to your colleagues or clients, contact us at Original Research n Thoracic Imaging Yong Sub Song, MD Chang Min Park, MD Sang Joon Park, PhD Sang Min Lee, MD Yoon Kyung Jeon, MD Jin Mo Goo, MD Volume and Mass Doubling Times of Persistent Pulmonary Subsolid Nodules Detected in Patients without Known Malignancy 1 Purpose: Materials and Methods: To evaluate volume doubling time (VDT) and mass doubling time (MDT) of persistent pulmonary subsolid nodules (SSNs) followed-up with low-dose (LD) computed tomography (CT) in patients without a history of malignancy. This retrospective institutional review board approved study, with waiver of patient informed consent, included 97 SSNs in 97 patients (45 men, 52 women; median age, 58 years; range, years) in whom at least two LD CT scans were obtained, with 3-month or longer follow-up interval and median follow-up of 633 days. SSNs were categorized into pure ground-glass nodules (GGNs) (group A), part-solid GGNs with solid components of 5 mm or smaller (group B), and part-solid GGNs with solid components larger than 5 mm (group C). Three-dimensional manual segmentation for all SSNs was performed on initial and latest follow-up LD CT scans; subsequently, VDTs and MDTs were calculated and were compared among groups by using Kruskal-Wallis test, followed by the Dunn procedure with Bonferroni correction for volume-growing SSNs and mass-growing SSNs. 1 From the Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center, 101 Daehangno, Jongno-gu, Seoul , Korea (Y.S.S., C.M.P., S.J.P., S.M.L., J.M.G.); Cancer Research Institute, Seoul National University, Seoul, Korea (C.M.P., S.J.P., J.M.G.); and Department of Pathology, Seoul National University College of Medicine, Seoul, Korea (Y.K.J.). Received October 4, 2013; revision requested December 9; final revision received March 7, 2014; accepted March 21; final version accepted April 18. Supported by a research grant from the Korean Foundation for Cancer Research (grant CB ) and the Seoul National University College of Medicine Research Fund Address correspondence to C.M.P. ( cmpark@radiol.snu.ac.kr). q RSNA, 2014 Results: Conclusion: Volume growth was thus: 12 of 63 SSNs (19%), group A; nine of 23 SSNs (39%), group B; and eight of 11 SSNs (73%), group C. Median VDT was thus: days (range, days), group A; days (range, days), group B; and days (range, days), group C. Mass growth was thus: 17 of 63 SSNs (27%), group A; 11 of 23 SSNs (48%), group B; and nine of 11 SSNs (82%), group C. Median MDT was days (range, days) for group A, days (range, days) for group B, and days (range, days) for group C. Median VDTs and MDTs of groups A and B were significantly longer than those of group C (P,.01). Pure GGNs and part-solid GGNs with solid components of 5 mm or smaller show significantly longer VDTs and MDTs than do part-solid GGNs with solid components larger than 5 mm. q RSNA, 2014 Online supplemental material is available for this article. 276 radiology.rsna.org n Radiology: Volume 273: Number 1 October 2014

2 Persistent pulmonary subsolid nodules (SSNs) have been shown in previous studies to pathologically correspond to pulmonary adenocarcinomas and their preinvasive lesions Advances in Knowledge nn Median volume doubling times (VDTs) were days (range, days) for pure ground-glass nodules (GGNs), days (range, days) for part-solid GGNs with solid components of 5 mm or smaller, and days (range, days) for part-solid GGNs with solid components larger than 5 mm (pure GGNs vs part-solid GGNs with solid components 5 mm, P =.153; pure GGNs vs part-solid GGNs with solid components.5 mm, P,.001; part-solid GGNs with solid components 5 mm vs part-solid GGNs with solid components.5 mm, P =.006). nn As for mass growth of subsolid nodules, median mass doubling times (MDTs) were days (range, days) for pure GGNs, days (range, days) for part-solid GGNs with solid components of 5 mm or smaller, and days (range, days) for part-solid GGNs with solid components larger than 5 mm (pure GGNs vs part-solid GGNs with solid components 5 mm, P =.357; pure GGNs vs part-solid GGNs with solid components.5 mm, P,.001; part-solid GGNs with solid components 5 mm vs part-solid GGNs with solid components.5 mm, P =.003). nn VDTs and MDTs of pure GGNs and part-solid GGNs with solid components of 5 mm or smaller are significantly longer than those for part-solid GGNs with solid components larger than 5 mm (P,.001 and P =.006, respectively, for VDTs; P,.001 and P =.003, respectively, for MDTs). (1 6). With the new Fleischner Society guidelines (1), these SSNs are classified in three subgroups according to the presence and size of their internal solid components, and different management strategies are recommended for each subgroup. These recommendations are based on the current knowledge that SSNs with larger solid components are more closely associated with a higher probability of malignancy (1 10). The interval growth (size increase or development of internal solid components) of SSNs over follow-ups is considered an important clue in the differentiation of clinically relevant malignant SSNs from benign SSNs (7,11). However, multiple computed tomographic (CT) scans over long-term follow-ups are often required to identify visually detectable growth in these lesions, as SSNs are known to exhibit very indolent growth features (7,12 17). Thus, there is a clear clinical need to measure the growth rate of SSNs in an accurate, reproducible, and sensitive manner to optimize the follow-up strategies for SSNs, such as their follow-up intervals and follow-up periods. In this context, three-dimensional volumetry has been reported to have the potential to reflect the true growth rate of SSNs with acceptable reproducibility (18 20). Furthermore, mass measurement has recently been noticed as a promising tool for the evaluation of the growth rate of SSNs. Indeed, mass measurements may simultaneously reflect the volume and density of SSNs with potentially superior reproducibility to three-dimensional volumetry (20). To our knowledge, however, there have been no prior studies that have included evaluation of the growth rate of each SSN subgroup according to the new Fleischner Society guidelines (1) or studies that have included evaluation of the growth rate of SSNs with the use Implication for Patient Care nn Pure GGNs and part-solid GGNs with solid components of 5 mm or smaller may be followed up with surveillance CT examinations with intervals of 2 years. of mass measurements. Therefore, the purpose of our study was to evaluate the volume doubling time (VDT) and mass doubling time (MDT) of persistent SSNs that were followed-up with low-dose (LD) CT in patients without a history of malignancy. Materials and Methods The institutional review board of Seoul National University Hospital approved this retrospective study, with a waiver of the requirement for patient informed consent. Patient Selection From January 2005 to December 2012, nonenhanced thin-section (thickness of 1 mm) LD CT scans in patients were obtained at our hospital. Among the patients, 9782 patients had at least one follow-up LD CT scan. Subsequently, one radiologist (Y.S.S., with 3 years of experience in chest CT) searched the electronic medical records and the radiology information systems of our hospital and selected all LD CT scans for which the radiologic reports included the Published online before print /radiol Content codes: Radiology 2014; 273: Abbreviations: AAH = adenomatous hyperplasia AIS = adenocarcinoma in situ GGN = ground-glass nodule LD = low dose MDT = mass doubling time MIA = minimally invasive adenocarcinoma SSN = subsolid nodule VDT = volume doubling time Author contributions: Guarantor of integrity of entire study, C.M.P.; study concepts/study design or data acquisition or data analysis/interpretation, all authors; manuscript drafting or manuscript revision for important intellectual content, all authors; approval of final version of submitted manuscript, all authors; literature research, Y.S.S., C.M.P., S.J.P., S.M.L., J.M.G.; clinical studies, Y.S.S., C.M.P., S.M.L., Y.K.J., J.M.G.; experimental studies, Y.S.S., S.J.P.; statistical analysis, Y.S.S.; and manuscript editing, Y.S.S., C.M.P., S.J.P., S.M.L. See also the article by Chae et all in this issue. Conflicts of interest are listed at the end of this article. Radiology: Volume 273: Number 1 October 2014 n radiology.rsna.org 277

3 descriptive words referring to SSNs (ie, ground-glass nodules, GGNs, ground-glass opacity nodules, GGO nodules, nonsolid nodules, subsolid nodules, part-solid nodules, or partly solid nodules ). The search yielded a total of 1875 LD CT scans in 584 patients, for which two radiologists (C.M.P. and Y.S.S., with 14 and 3 years of experience in chest CT, respectively) reviewed all LD CT images in consensus. Thereafter, our study population was selected according to the following criteria: (a) confirmation of persistent SSNs on follow-up LD CT scans, (b) follow-up interval of 3 months or longer, (c) SSNs larger than 5 mm and 3 cm or smaller in diameter on the initial LD CT scan, and (d) no history of previous or concurrent malignancy. Twelve patients with multiple SSNs and 85 patients with solitary SSNs met all four of these criteria. In the 12 patients with multiple SSNs, we selected one dominant nodule according to the following criteria: (a) the part-solid ground-glass nodule (GGN) with the largest solid component when there were at least two part-solid GGNs and (b) the pure GGN with the largest diameter when there were no part-solid GGNs. Finally, 97 SSNs in 97 patients (45 men and 52 women; median age, 58 years; range, years) with 3-month or longer follow-up intervals (median, 633 days; range, days) were included in this study. There were no patients with immunosuppression or known infections. One thoracic radiologist (C.M.P.) measured the diameters of entire nodules and internal solid components of all 97 SSNs on axial images of the initial LD CT scans and classified them as pure GGNs (group A, n = 63), partsolid GGNs with solid components of 5 mm or smaller (group B, n = 23; median solid component size, 3.2 mm; range, mm), or part-solid GGNs with solid components larger than 5 mm (group C, n = 11; median solid component size, 9.0 mm; range, mm). The median diameter of the 97 SSNs was 9.4 mm (range, mm). Table 1 summarizes Table 1 Demographic and Pathologic Characteristics of 97 SSNs Characteristic Group A (n = 63) Group B (n = 23) Group C (n = 11) P Value Sex.198* No. male No. female Median age (y) 58 (37 77) 57 (47 72) 68 (54 87).008 Median nodule diameter (mm) 8.3 ( ) 11.1 ( ) 18.8 ( ),.001 Median follow-up interval (d) 742 ( ) 368 ( ) 385 ( ).006 Pathologic results.032 No. unknown 49 (78) 13 (57) 6 (55)... No. with AAH 3 (5) 0 (0) 0 (0)... No. with AIS 8 (13) 7 (30) 1 (9)... No. with MIA 1 (2) 1 (4) 1 (9)... No. with invasive adenocarcinoma 2 (3) 2 (9) 3 (27)... Note. AAH = atypical adenomatous hyperplasia, AIS = adenocarcinoma in situ, group A = pure GGN, group B = part-solid GGN with solid component of 5 mm or smaller, group C = part-solid GGN with solid component larger than 5 mm, MIA = minimally invasive adenocarcinoma. * Calculated with the Pearson x 2 test. Numbers in parentheses are ranges. Calculated with the Kruskal-Wallis test. Calculated with the Fisher s exact test. Numbers in parentheses are percentages. the clinical and pathologic characteristics of the three groups (groups A C). The median diameter of group C was significantly larger than that of group A or B (P,.01, Kruskal-Wallis test followed by the Dunn procedure with Bonferroni correction). For interobserver agreement in terms of nodule classification and the diameter of entire nodules and internal solid components, another thoracic radiologist (S.M.L., with 8 years of experience in chest CT) independently measured the diameter of entire nodules and solid components of all 97 SSNs. Among the 97 SSNs, 29 were pathologically confirmed with surgical resection, and their pathologic diagnosis included AAH (n = 3), AIS (n = 16), MIA (n = 3), and invasive adenocarcinoma (n = 7) (Fig 1). One pathologist (Y.K.J., with 14 years of experience in lung cancer) performed pathologic evaluation in all 29 cases and confirmed their diagnoses. Table 2 summarizes the clinical characteristics of the 29 patients with pathologically confirmed SSNs. Among the 29 patients with pathologically confirmed SSNs, five patients were current smokers, and the remaining 24 patients were never smokers. In addition, among the 97 SSNs included in our study, 17 were identical to those in the study population of our previous report (21). CT Examination LD CT scans were obtained by using a 16 detector row CT scanner (Sensation-16; Siemens Medical Systems, Erlangen, Germany) (hereafter referred to as scanner 1) or a 64 detector row CT scanner (Brilliance-64; Philips Medical Systems, Best, the Netherlands) (hereafter referred to as scanner 2). Among 97 patients, 40 patients underwent initial and latest LD CT scanning by using scanner 1, 24 underwent initial and latest LD CT scanning by using scanner 2, and the remaining 33 underwent initial LD CT scanning by using scanner 1 and latest LD CT scanning by using scanner 2 (or vice versa). All LD CT scans were obtained in full inspiration without intravenous contrast material. Scanning 278 radiology.rsna.org n Radiology: Volume 273: Number 1 October 2014

4 parameters for each CT scanner were thus: For scanner 1, detector collimation was 0.75 mm; beam pitch, 1.0; reconstruction thickness, 1.0 mm; reconstruction interval, 1.0 mm; rotation time, 0.5 second; tube voltage, 120 kvp; tube current, 30 effective Figure 1 mas; and reconstruction kernel, B60f sharp algorithm. For scanner 2, detector collimation was mm; beam pitch, 1.014; reconstruction thickness, 1.0 mm; reconstruction interval, 1.0 mm; rotation time, 0.75 second; tube voltage, 120 kvp; tube current, 40 effective mas; and reconstruction kernel, YC kernel. Nodule Segmentation One chest radiologist (S.M.L. with 8 years of experience in chest CT) performed three-dimensional manual segmentation of each SSN to measure volume and mass. Manual segmentation was performed by electronically outlining SSNs on all axial LD CT images by using in-house software (Fig 2). All segmentations were performed under a lung window setting at a width of 1500 HU and a level of 2700 HU. When manual segmentation was finished, the software calculated the volume and mass of the segmented SSNs. Mass was calculated according to the following equation, as previously adopted (20,22,23): M = V [(A mean ) 0.001], where M is mass in milligrams per milliliter, V is volume, and A mean is mean attenuation in Hounsfield units. Further detailed information in regard to our in-house software program is provided in Appendix E1 (online). Figure 1: Flowchart of the study population. Except where there is a measurement in millimeters, numbers in parentheses are the numbers of patients. GGO = ground-glass opacity. Nodule Growth Analysis A three-step approach was used to evaluate the VDT and MDT of SSNs: First, intraobserver variability of volume and mass measurements was assessed. For intraobserver variability, all 97 SSNs were classified in two groups according to the maximum Table 2 Demographic Characteristics of 29 Pathologically Confirmed SSNs Characteristic AAH (n = 3) AIS (n = 16) MIA (n = 3) Invasive Adenocarcinoma (n = 7) P Value Sex.593* No. male No. female Median age (y) 58 (46 59) 57 (49 75) 62 (56 67) 60 (46 87).49 Median nodule diameter (mm) 8.1 ( ) 11.3 ( ) 14.7 ( ) 19.3 ( ).094 Median follow-up interval (d) 290 ( ) 519 ( ) 747 ( ) 363 ( ).601 Median VDT (d) Nonmeasurable ( ) ( ) ( ).382 Median MDT (d) Nonmeasurable ( ) ( ) ( ).476 * Calculated with the Fisher exact test. Numbers in parentheses are ranges. Calculated with the Kruskal-Wallis test. Doubling time was calculated by using the Schwartz formula. Numbers in parentheses are ranges. Radiology: Volume 273: Number 1 October 2014 n radiology.rsna.org 279

5 Figure 2 Figure 2: In-house volumetry software program for volume and mass growth rate measurement. This software program provides two screens of loaded CT images with or without magnification. (a) Larger screen shows a loaded axial CT image without magnification. The area within the purple square is selected for magnification. (b) Smaller screen shows an image of the area within the purple square selected on the larger screen at four times the magnification. Manual segmentation (shown as the polymorphic yellow line; the small yellow square on the yellow line indicates the starting point) was performed on this magnified image. The yellow number on the image indicates the current image number of the CT image stack. diameter (SSNs 10 mm, n = 53; SSNs. 10 mm, n = 44) on their initial LD CT images. Subsequently, 15 SSNs (12 pure GGNs and three part-solid GGNs) of 10 mm or smaller (median, 7.6 mm; range, mm) and 15 SSNs (three pure GGNs and 12 partsolid GGNs) larger than 10 mm (median, 14.8 mm; range, mm) were randomly selected. Sample size calculation in this variability test was based on the ability to detect a concordance correlation coefficient between the first and second measurements of at least 0.75 (probability of type I error =.01, power = 0.99). One observer (S.M.L.) performed manual segmentation of the 30 SSNs on the initial LD CT scans and repeated the manual segmentation after an interval of 2 months. A 95% confidence interval for the limits of agreement was calculated by using Bland-Altman analysis and was expressed as percentages to determine volume and mass measurement variability. Second, interval volume and mass growth of SSNs were determined. Two months after the variability test, the same observer performed manual segmentation of all 97 SSNs on the initial LD CT scans. After another 2 months, the same observer performed manual segmentation of these SSNs on the latest follow-up LD CT scans; subsequently, relative volume and mass changes from those measured on the initial LD CT scans were calculated. A nodule was designated as a growing nodule when the relative volume or mass changes exceeded the upper limit of the 95% confidence interval for the limits of agreement determined by the variability test (24). Third, VDTs and MDTs were calculated for volume- and mass-growing nodules by using an equation based on a modified Schwartz formula (25) of an exponential growth model thus: DT = [log2 T]/[log (X f /X i )], where DT is doubling time, X f and X i are the final and initial volumes (or mass), respectively, and T is the interval between the two LD CT scans. Statistical Analysis Statistical analyses were performed with use of software (XLSTAT, version , Addinsoft, Paris, France; and MedCalc, version , Med- Calc Software, Mariakerke, Belgium) by one author (Y.S.S.). Results with P values of less than.05 were considered to indicate a significant difference. In this study, nonparametric tests were used, as the numerical data sets were not normally distributed. VDTs and MDTs of SSNs were compared among groups A, B, and C by using the Kruskal-Wallis test, followed by the Dunn procedure with Bonferroni correction, accounting for the number of pairwise comparisons among the three groups in regard to volumegrowing SSNs and mass-growing SSNs. A pairwise comparison between VDTs and MDTs of SSNs that were determined to grow in both volume and mass was performed by using the Wilcoxon signed-rank test. For pathologically confirmed nodules, the VDTs of volume-growing 280 radiology.rsna.org n Radiology: Volume 273: Number 1 October 2014

6 Figure 3 Figure 3: Box plot shows median VDTs for group A (pure GGNs), group B (part-solid GGNs with solid components 5 mm), and group C (part-solid GGNs with solid components. 5 mm). The median VDT of group C was significantly shorter than those of the other two groups. The upper and lower ends of the whiskers, upper and lower hinges of the boxes, the horizontal lines across each box, and circles represent upper and lower extremes, upper [75th] and lower [25th] quartiles, medians, and data outliers, respectively. = P,.01. nodules and MDTs of mass-growing nodules were compared by using the Kruskal-Wallis test, followed by the Dunn procedure with Bonferroni correction, accounting for the number of pairwise comparisons among the pathologic groups. Interobserver agreement for SSN classification was investigated by using a weighted k statistic. A k value of less than zero indicates poor agreement; k value of , slight agreement; k value of , fair agreement; k value of , moderate agreement; k value of , substantial agreement; and k value of , almost perfect agreement (26). Interobserver measurement agreement for the diameter of entire nodules and internal solid components was assessed by using linear regression analysis. Results SSNs showed increases in volume and mass over follow-ups by a median of 14.0% (mean, 22.1%; range,221.1% to 134.8%) and 14.3% (mean, 27.7%; range,215.1% to 185.8%), respectively. The intraobserver variability test revealed that the 95% confidence interval for the limits of agreement was 227.3% to 29.5% (mean, 1.1%) for volume measurements and 219.0% to 20.6% (mean, 0.8%) for mass measurements. Therefore, our study designated SSNs as growing nodules when their relative volume or mass changes exceeded 29.5% of the initial volume or 20.6% of the initial mass on follow-up CT scans. As for the volume growth of SSNs, 12 of 63 SSNs (19%) showed significant interval growth in group A, nine of 23 (39%) showed significant growth in group B, and eight of 11 (73%) showed significant growth in group C. The median VDT of all 29 volume-growing SSNs was days (mean, days; range, days). The median VDT of volume-growing nodules in group A was days (mean, days; range, days), that in group B was days (mean, days; range, days), and that in group C was days (mean, days; range, days). Overall Kruskal- Wallis test among the three groups showed significant differences between them (P,.001). The median VDTs of volume-growing SSNs in groups A and B were significantly longer than in group C (group A vs group B, P =.153; group A vs group C, P,.001; group B vs group C, P = 0.006) (Fig 3). As for mass growth, 17 of 63 nodules (27%) showed significant interval growth in group A, 11 of 23 (48%) showed significant interval growth in group B, and nine of 11 (82%) showed significant interval growth in group C. Mass growth was observed in all 29 volume-growing SSNs. The median MDT of all 37 mass-growing nodules was days (mean, days; range, days). The median MDT of mass-growing nodules in group A was days (mean, days; range, days), that in group B was days (mean, days; range, days), and that in group C was days (mean, days; range, days). Overall Kruskal-Wallis test among the three groups showed significant differences between them (P,.001). The median MDTs of mass-growing nodules in groups A and B were significantly longer than that in group C (group A vs group B, P =.357; group A vs group C, P,.001; group B vs group C, P =.003) (Fig 4). For nodules that were determined to grow in both volume and mass, the median MDT was shorter than the median VDT ( and days for MDT and VDT, respectively); however, the differences were not significant (P =.098). Table 3 summarizes the pathologic distribution of volume- and massgrowing nodules. Among 29 pathologically confirmed SSNs, volume growth was observed in 15 nodules (nine of 16 with AIS, three of three with MIA, and three of seven with invasive adenocarcinomas) and mass growth was observed in 16 nodules (nine of 16 with AIS, three of three with MIA, and four of seven with invasive adenocarcinoma). There were no cases of volume-growing or massgrowing AAH. The median VDT was days (mean, days; range, days) for AIS, Radiology: Volume 273: Number 1 October 2014 n radiology.rsna.org 281

7 Figure 4 agreement (k = 0.822; 95% confidence interval: 0.727, 0.917). Linear regression analysis for the diameters of entire nodules and internal solid components was y = x (R 2 = , P,.001) and y = x (R 2 = , P,.001), respectively. Table 3 Figure 4: Box plot shows median MDTs for group A (pure GGNs), group B (part-solid GGNs with solid components 5 mm), and group C (part-solid GGNs with solid components. 5 mm). The median MDT of group C was significantly shorter than those of the other two groups. Keys are the same as on Figure 3. Pathologic Results of Volume- and Mass-growing SSNs Pathologic Result Group A Group B Group C Volume-growing nodule Unresected 6 (50) 4 (44) 4 (50) AAH 0 (0) 0 (0) 0 (0) AIS 5 (42) 3 (33) 1 (12) MIA 1 (8) 1 (11) 1 (12) Invasive adenocarcinoma 0 (0) 1 (11) 2 (25) Mass-growing nodule Unresected 10 (59) 6 (55) 5 (6) AAH 0 (0) 0 (0) 0 (0) AIS 5 (29) 3 (27) 1 (11) MIA 1 (6) 1 (9) 1 (11) Invasive adenocarcinoma 1 (6) 1 (9) 2 (22) Note. Group A = pure GGN, group B = part-solid GGN with solid component of 5 mm or smaller, group C = part-solid GGN with solid component larger than 5 mm. For the volume-growing nodule, group A included 12 nodules, group B included nine nodules, and group C included eight nodules. For the mass-growing nodule, group A included 17 nodules, group B included 11 nodules, and group C included nine nodules. Numbers in parentheses are percentages days (mean, days; range, days) for MIA, and days (mean, days; range, days) for invasive adenocarcinoma. The median MDT was days (mean, days; range, days) for AIS, days (mean, days; range, days) for MIA, and days (mean, days; range, days) for invasive adenocarcinoma. The differences in median VDT and MDT among AIS, MIA, and invasive adenocarcinoma were not significant (P =.382 and.476 for VDT and MDT, respectively). Interobserver agreement for SSN classification showed substantial Discussion We found that growing SSNs in group A (pure GGNs) and group B (part-solid GGNs with solid components 5 mm) had significantly longer VDTs and MDTs than those of group C (part-solid GGNs with solid components. 5 mm). The median VDT and MDT of growing SSNs in group B were also shorter than those in group A; however, those differences were not significant. Our findings suggest that group B may have a more indolent growth potential than group C and that it may be reasonable for SSNs in group B to be managed in a more conservative manner than group C. We believe that our results can provide additional background to the newly published Fleischner Society guidelines (1), which include a recommendation of surgical resection for persistent partsolid GGNs with solid components larger than 5 mm and which also suggest that part-solid GGNs with solid components of 5 mm or smaller may be conservatively monitored without immediate resection. In our study, patients with a history of lung cancer or extrathoracic malignancies were excluded, as these are potential risk factors for the rapid growth of SSNs (13,27). Although several instances of pulmonary metastases (including melanoma or adenoid cystic carcinoma) appearing as SSNs have been reported and have showed a substantially rapid growth rate, in fact, it is quite rare for metastases from extrathoracic malignancies to manifest as SSNs (28,29). Previous studies have reported the VDTs of SSNs by using two- or threedimensional volumetry with a modified Schwartz equation (12,19). Hasegawa et al (12) used two-dimensional volumetry and reported the VDT of radiology.rsna.org n Radiology: Volume 273: Number 1 October 2014

8 primary lung cancers, including 38 SSNs. They reported that the mean VDT of lung cancers appearing as partsolid GGNs was significantly shorter than that of pure GGNs (457 days vs 813 days 6 375, respectively). Oda et al (19) also calculated the VDT of 47 pathologically confirmed SSNs by using three-dimensional volumetry software. In their study, the mean VDT of part-solid GGNs was also significantly shorter than that of pure GGNs (276.9 days vs days , respectively). Our results are consistent with data in these previous studies and show that the median VDT of part-solid GGNs (groups B and C) was shorter than that of pure GGNs (group A); however, the differences between group A and group B were not significant. Our results also showed that median growth rates of groups A and B were longer than 1000 days. At present, Fleischner Society guidelines suggest that these SSNs may be conservatively managed with annual CT examinations (1); however, our results indicate that SSNs in groups A and B may be even more conservatively followed up with biennial CT examinations. It is notable that the median VDTs of our study were significantly longer than those of previous studies, which can most likely be attributed to the differences in our study populations. Investigators in previous studies (12,19) calculated the VDTs of only pathologically proven lung cancers, which may have a more aggressive growth feature than the SSNs that are followed up, while our study may have included more indolent SSNs, as we included only SSNs with 3 months or longer of follow-up. In addition, in our study, 68 of a total of 97 SSNs were not resected. Therefore, SSNs with a high suspicion of malignancy on an initial CT scan (such as part-solid GGNs with large solid components) may have been promptly resected without follow-up and subsequently excluded in our study, potentially leading to underestimation of the growth rates of SSNs (particularly group C). However, we believe that our study population can be more suitable for the investigation of the true growth rate of SSNs that are followed up with surveillance CT examinations in daily clinical practice. As for pathologically confirmed SSNs, Oda et al (19) reported that the mean VDT of AAH was days , that of bronchioloalveolar carcinoma was days , and that of adenocarcinoma was days The median VDTs of AIS, MIA, and invasive adenocarcinoma (1240.3, , and days, respectively) in our study were substantially longer than their results. We believe that this may also be due to the fact that we may have included more indolent SSNs, as we excluded SSNs with shorter than 3 months of follow-up. In fact, the median follow-up period prior to surgical resection for each pathologic group of our study (519 days for AIS, 747 days for MIA, and 363 days for invasive adenocarcinoma) was substantially longer than those of the study by Oda et al (123.9 days for bronchioloalveolar carcinoma and 85.9 days for adenocarcinoma) (19). Additional prospective studies with a larger study population are warranted to better assess the actual growth rates of those pathologic findings. To our knowledge, our study is the first study to have included calculation of the MDT of SSNs. We found that median MDTs of each subgroup were shorter than the median VDTs, although a pairwise comparison between MDTs and VDTs did not reach significance. In addition, mass-growing nodules were more numerous than volume-growing nodules, which allowed us to calculate the growth rate of an additional eight SSNs that seemed to be stable in terms of volume measurements. This factor suggests that mass measurements may be more sensitive for the detection of the growth of SSNs, as the mass simultaneously reflects changes in both the attenuation and volume of SSNs. Mass measurement was also shown to be more reproducible than volume measurements in SSNs. De Hoop et al (20) also reported that the mass measurement variability of SSNs was significantly smaller than volume measurement variability, which was reproduced in our study. Several limitations of our study should be mentioned. First, our study was of a retrospective design, and there may have been unavoidable bias. Second, there was a relatively small number of growing nodules for the calculation of VDT and MDT. Third, we did not cover other potential risk factors for the rapid growth of SSNs (such as initial nodule diameter and history of previous or concurrent lung cancer), as they were beyond the scope of our study. We believe, however, that future studies are warranted to evaluate these potential risk factors. Fourth, LD CT scans were obtained by using two different CT scanners, which may have affected the results. Fifth, volume and mass measurements were derived from the results of manual segmentation by one radiologist, which can be significantly influenced by observers subjective trend. Manual segmentation may be the standard for lesion segmentation of pulmonary SSNs; however, we believe that an accurate and reproducible automatic nodule segmentation method should be further developed for SSNs. Sixth, we did not evaluate interobserver variability for volume and mass measurements. However, de Hoop et al (20) showed that interobserver variability for volume and mass measurement of SSNs was greater than intraobserver variability. Thus, some proportion of the growing SSNs in our study might have been designated as stable SSNs if we adopted interobserver variability as a threshold for nodule growth. Seventh, we used a modified Schwartz formula that supposes the consistent exponential growth of a tumor, which is not always the case (25,30). In conclusion, pure GGNs and partsolid GGNs with solid components of 5 mm or smaller show significantly longer VDTs and MDTs than part-solid GGNs with solid components larger than 5 mm. Disclosures of Conflicts of Interest: Y.S.S. disclosed no relevant relationships. C.M.P. disclosed no relevant relationships. S.J.P. disclosed no relevant relationships. S.M.L. disclosed no relevant relationships. Y.K.J. disclosed no relevant relationships. J.M.G. disclosed no relevant relationships. 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9 References 1. Naidich DP, Bankier AA, MacMahon H, et al. Recommendations for the management of subsolid pulmonary nodules detected at CT: a statement from the Fleischner Society. Radiology 2013;266(1): Travis WD, Brambilla E, Noguchi M, et al. International association for the study of lung cancer/american thoracic society/european respiratory society international multidisciplinary classification of lung adenocarcinoma. J Thorac Oncol 2011;6(2): Godoy MC, Naidich DP. Subsolid pulmonary nodules and the spectrum of peripheral adenocarcinomas of the lung: recommended interim guidelines for assessment and management. Radiology 2009;253(3): Park CM, Goo JM, Lee HJ, Lee CH, Chun EJ, Im JG. Nodular ground-glass opacity at thin-section CT: histologic correlation and evaluation of change at follow-up. Radio- Graphics 2007;27(2): Kim HY, Shim YM, Lee KS, Han J, Yi CA, Kim YK. Persistent pulmonary nodular ground-glass opacity at thin-section CT: histopathologic comparisons. Radiology 2007;245(1): Henschke CI, Yankelevitz DF, Mirtcheva R, et al. CT screening for lung cancer: frequency and significance of part-solid and nonsolid nodules. AJR Am J Roentgenol 2002;178(5): Aoki T, Nakata H, Watanabe H, et al. Evolution of peripheral lung adenocarcinomas: CT findings correlated with histology and tumor doubling time. AJR Am J Roentgenol 2000;174(3): Lee HJ, Goo JM, Lee CH, Yoo CG, Kim YT, Im JG. Nodular ground-glass opacities on thin-section CT: size change during follow-up and pathological results. Korean J Radiol 2007;8(1): Aoki T, Tomoda Y, Watanabe H, et al. Peripheral lung adenocarcinoma: correlation of thin-section CT findings with histologic prognostic factors and survival. Radiology 2001;220(3): Ohde Y, Nagai K, Yoshida J, et al. The proportion of consolidation to ground-glass opacity on high resolution CT is a good predictor for distinguishing the population of non-invasive peripheral adenocarcinoma. Lung Cancer 2003;42(3): Kakinuma R, Ohmatsu H, Kaneko M, et al. Progression of focal pure ground-glass opacity detected by low-dose helical computed tomography screening for lung cancer. J Comput Assist Tomogr 2004;28(1): Hasegawa M, Sone S, Takashima S, et al. Growth rate of small lung cancers detected on mass CT screening. Br J Radiol 2000;73(876): Matsuguma H, Mori K, Nakahara R, et al. Characteristics of subsolid pulmonary nodules showing growth during follow-up with CT scanning. Chest 2013;143(2): Chang B, Hwang JH, Choi YH, et al. Natural history of pure ground-glass opacity lung nodules detected by low-dose CT scan. Chest 2013;143(1): Takahashi S, Tanaka N, Okimoto T, et al. Long term follow-up for small pure groundglass nodules: implications of determining an optimum follow-up period and high-resolution CT findings to predict the growth of nodules. Jpn J Radiol 2012;30(3): Takashima S, Sone S, Li F, Maruyama Y, Hasegawa M, Kadoya M. 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. AJR Am J Roentgenol 2003;180(5): Henschke CI, Yankelevitz DF, Yip R, et al. Lung cancers diagnosed at annual CT screening: volume doubling times. Radiology 2012;263(2): Oda S, Awai K, Murao K, et al. Computeraided volumetry of pulmonary nodules exhibiting ground-glass opacity at MDCT. AJR Am J Roentgenol 2010;194(2): Oda S, Awai K, Murao K, et al. Volumedoubling time of pulmonary nodules with ground glass opacity at multidetector CT: assessment with computer-aided three-dimensional volumetry. Acad Radiol 2011;18(1): de Hoop B, Gietema H, van de Vorst S, Murphy K, van Klaveren RJ, Prokop M. Pulmonary ground-glass nodules: increase in mass as an early indicator of growth. Radiology 2010;255(1): Lee SM, Park, CM, Goo JM, Lee HJ, Wi JY, Kang CH. Invasive pulmonary adenocarcinomas versus preinvasive lesions appearing as ground-glass nodules: differentiation by using CT features. Radiology 2013;268(1): Mull RT. Mass estimates by computed tomography: physical density from CT numbers. AJR Am J Roentgenol 1984;143(5): Kim H, Park CM, Woo S, et al. Pure and part-solid pulmonary ground-glass nodules: measurement variability of volume and mass in nodules with a solid portion less than or equal to 5 mm. Radiology 2013;269(2): Park CM, Goo JM, Lee HJ, Kim KG, Kang MJ, Shin YH. Persistent pure ground-glass nodules in the lung: interscan variability of semiautomated volume and attenuation measurements. AJR Am J Roentgenol 2010;195(6):W408 W Schwartz M. A biomathematical approach to clinical tumor growth. Cancer 1961;14: Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics 1977;33(1): Hiramatsu M, Inagaki T, Inagaki T, et al. Pulmonary ground-glass opacity (GGO) lesions: large size and a history of lung cancer are risk factors for growth. J Thorac Oncol 2008;3(11): Kang MJ, Kim MA, Park CM, Lee CH, Goo JM, Lee HJ. Ground-glass nodules found in two patients with malignant melanomas: different growth rate and different histology. Clin Imaging 2010;34(5): Park CM, Goo JM, Kim TJ, et al. Pulmonary nodular ground-glass opacities in patients with extrapulmonary cancers: what is their clinical significance and how can we determine whether they are malignant or benign lesions? Chest 2008;133(6): 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 histologic type, CT attenuation, stage, survival, and size. Chest 2009;136(6): radiology.rsna.org n Radiology: Volume 273: Number 1 October 2014