Abstract
Aim: To assess the correlation between advanced non-small cell lung cancer (NSCLC) with or without pulmonary lymphangitic carcinomatosis (PLC) and fluorodeoxyglucose (FDG) uptake and its effect on survival outcomes. Patients and Methods: We retrospectively reviewed 157 patients with NSCLC. The mean and maximum standardized uptake values (SUVmean and SUVmax, respectively), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were evaluated for their effect on overall survival (OS) and progression-free survival (PFS). Results: The PLC group included 55 patients and the non-PLC group included 102 patients. The SUVmean, SUVmax, MTV and TLG values were lower in the non-PLC group. In the PLC group, primary lung tumor TLG was a significant predictor of PFS, while whole-body TLG was found to be a significant predictor in non-PLC patients. Conclusion: Primary lung tumor TLG was a good predictor in PLC patients. Whole-body TLG could be a useful predictor only in patients without PLC.
Pulmonary lymphangitic carcinomatosis (PLC) is defined as the dissemination of cancer into the lymphatic system in the lung. It is caused by cancer spreading from the pulmonary circulation into the interstitium of lung (1, 2). The invasion may be antegrade, spreading directly from the axial lymph node into the lung parenchyma, or retrograde, spreading from the lung periphery into the hilar lymph node (3). PLC may be localized to small areas of the lung or may be diffuse over larger areas and is often associated with advanced non-small cell lung cancer (NSCLC) (4).
The characteristic clinical diagnostic computed tomography (CT) features of PLC, which correlate with histopathologic findings, are an uneven thickening of the interstitial septa and bronchovascular bundles (5-7). The majority of studies using fluorodeoxyglucose-positron emission tomography (FDG-PET) in lung cancer patients have evaluated tumors and metastases based on the extent of FDG uptake, which correlates with tumor cell metabolism, measured by glucose uptake. High uptake reflects a high metabolic rate and increased tumor cell aggression. The degree of FDG uptake in tumors as seen on PET, which is determined by the mean standardized uptake value (SUVmean), maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV) and total lesion glycolysis (TLG), is useful for predicting overall survival (OS) and progression-free survival (PFS) in lung cancer patients (8-11). However, the interpretation of these FDG uptake parameters in PLC has not been fully established. To our knowledge, 3 small case series have investigated the use of PET/CT for the detection of PLC (12-14), whereas no previous reports describing the differences in TLG uptake between PLC-positive and PLC-negative cases exist.
The purpose of this study was to assess the correlation between advanced NSCLC with or without PLC and FDG-PET/CT uptake and to evaluate its effect on survival outcomes.
Patients and Methods
Patient population. We retrospectively reviewed the medical charts of all patients with histopathologically confirmed NSCLC who underwent FDG-PET/CT at our institution, prior to lung cancer treatment, between January 2007 and December 2012. The histopathological confirmation of diagnosis was made using body fluid cytology, CT-guided biopsy or operative specimens. The median follow-up period was 13.5 months; all patients were followed up until the end of study on 31 December 2013. The inclusion criteria were as follows: (i) no known history of cancer, (ii) lung cancer that was staged using the American Joint Cancer Committee (AJCC) 2002/2010 criteria (5-7), (iii) the patient was evaluated according to institutional guidelines and (iv) the patient received subsequent clinical follow-up at our institution. The pretreatment work-up consisted of Eastern Cooperative Oncology Group (ECOG) performance status evaluation, clinical and physical examination, complete blood counts and biochemistry tests. The imaging studies included chest CT, chest radiography, brain magnetic resonance imaging (MRI)/CT and bone scintigraphy. Exclusion criteria were as follows: (i) no histopathologically confirmed NSCLC, (ii) a diagnosis of small cell carcinoma or bronchial adenoma, (iii) no FDG-PET/CT imaging prior to therapy, (iv) a history of cancer, (v) lung cancer not staged according to AJCC 2002/2010 criteria, (vi) lung cancer that was not diagnosed according to institutional guidelines, (vii) no subsequent clinical follow-up at our institution, (viii) administration of a steroid before the FDG-PET/CT examination and (ix) active tuberculosis, interstitial lung disease, pulmonary edema, opportunistic infection, radiation fibrosis and autoimmune disease/drug-induced lung disease.
Image analyses. CT scans were obtained according to the manufacturers' protocol using a General Electric HighSpeed or LightSpeed scanner (General Electric Medical Systems, Milwaukee, WI, USA). Intravenous contrast agent (100 ml) containing 300 mg/ml ioxilan was administered at a rate of 2 ml/s. Mediastinal (window width=350 Hounsfield units (HU), window level=40 HU) and lung (window width=1,500 HU, window level=2,600 HU) CT scans were obtained using a picture archiving and communication system (PACS). We retrospectively determined the presence of septal lines, bronchovascular thickening, ground-glass opacities, pulmonary nodules, lymphadenopathy and pleural effusions.
On chest CT images, if a primary lung cancer was noted, PLC was identified as uneven thickening of bronchovascular bundles, broad interstitial septal lines and a polygonal pattern in the interstitium. PLC was defined as diffuse if areas of the whole lung were involved and focal if localized to an interstitial line of one lung lobe. Other associated findings, such as lymphadenopathy, pleural effusion and nodules were also recorded (15). Two radiologists with 10 and 8 years of experience, respectively, independently assessed the images to diagnose PLC. Disagreements were resolved by discussion to reach a consensus interpretation.
Analysis of tumor volume in FDG-PET/CT. We used Volume Viewer software on a GE Advantage Workstation 4.4 (GE Healthcare, Milwaukee, WI, USA) to measure the tumor volume, which delineated the volume of interest using an automated SUV to provide an isocontour threshold. PET/CT parameters SUVmax, SUVmean and MTV were recorded. MTV was defined as the total computed tumor volume greater than the threshold SUV baseline as compared with the mediastinal background. SUVmean values plus 2 standard deviations are shown. The TLG was calculated from the product of MTV and SUVmean. These PET parameters were examined for normality and skewness, while log-squared transformation was applied to the skewed variables SUVmax, MTV and TLG (16-18).
Patients' clinicopathological characteristics.
The study was approved by the Human Research Ethics Committee of our institution (Buddhist Tzu Chi General Hospital, Dalin; B10201023), with the need for informed consent being waived because of the retrospective nature of the study.
Statistical analyses. PFS was defined as the period extending from the date of FDG-PET imaging until disease recurrence or final follow-up and OS was defined as the period extending from the date of FDG-PET imaging until death or final follow-up.
For SUVmean, SUVmax, MTV and TLG, we selected cut-off values that maximized the profile partial likelihood in the Cox regression model. These were treated as binary explanatory variables, with their cut-off values determining positive or negative results. Patients were classified into low/high PET volume parameter groups for the whole-body and primary lung tumor, as described in previous volume parameter studies (19, 20). Accordingly, the cut-off values for the primary lung tumor were determined as 21.60 for SUVmean, 31.25 for SUVmax, 47.00 for MTV, and 330.00 for TLG. Those for the whole-body were determined as 22.00 for SUVmean, 41.25 for SUVmax, 30.82 for MTV and 383.29 for TLG.
Clinical factors and positron emission tomography data associated with and without pulmonary lymphangitic carcinomatosis in advanced non-small cell lung cancer patients.
Tumor size and histology associated with fluorodeoxyglucose (FDG) uptake in advanced non-small cell lung cancer patients.
Predictions of OS and PFS based on clinical factors and PET measurements in NSCLC patients with and without pulmonary lymphangitic carcinomatosis.
OS and PFS were calculated using the Kaplan-Meier method and groups were compared using the log-rank test. A multivariate analysis was performed using the Cox proportional hazards model to assess joint effects of the following variables on OS and PFS: age, sex, ECOG performance status, histology, treatment modality, SUVmean, SUVmax, MTV and TLG (relating to the primary tumor).
Results
Patients' characteristics. A total of 346 patients with histopathologically confirmed NSCLC were identified. A total of 157 patients met the inclusion criteria. The clinicopathological characteristics of patients are listed in Table I.
FDG-PET uptake in patients with and without PLC. Associations of PLC with clinical factors or PET measurements are shown in Table II and Table III. No clinical factors were significantly different between PLC and non-PLC groups. PET measurements were lower in the non-PLC group than in the PLC group, although only primary lung tumor TLG and whole-body TLG were significantly different between the groups with or without PLC (p=0.04 and p=0.01, respectively). In addition, tumor differentiation status and size were not significantly associated in between the groups with or without PLC. Survival analysis showed that the non-PLC group had longer median PFS and OS compared to the PLC group (p=0.03 and p=0.05, respectively).
Prognostic value of clinical factors and FDG uptake on survival. Clinical factors, such as age (>65 vs. <65 years) and treatment modality (chemotherapy vs. radiation/chemoradiation), were significantly associated with OS or PFS in the PLC and non-PLC groups (Table IV).
In patients with PLC, whole-body scan values of SUVmean, SUVmax and MTV were not significant prognostic factors. In contrast, in these patients, whole-body TLG and primary lung tumor TLG were significant prognostic factors for PFS. In patients without PLC, only whole lung TLG was a significant prognostic factor for PFS and OS, whereas whole-body SUVmax was a significant prognostic factor for PFS (Table V).
According to Kaplan-Meier estimates, in the PLC group, primary lung tumor TLG was significantly associated with PFS but not OS. In contrast, in the PLC group, whole-body TLG was not associated with survival (Figure 1). In the non-PLC group, primary lung tumor TLG was not associated with PFS or OS; however, whole-body TLG was significantly associated with both PFS and OS (Figure 2).
Discussion
Various neoplasms can cause PLC, although the most common cause is lung cancer (20, 21). PLC is associated with the movement of tumor emboli into the adjacent vessels or lymphatics. The engorgement of the lymphatics may compress the adjacent pulmonary vessels and blockage of the lymphatic system can cause the lymphatic bed surrounding the alveoli to become stiff, increasing the workload of the lungs and the breathing rate, which can lead to profound dyspnea in NSCLC patients with PLC. It is believed that tumor emboli account for the poor prognosis in advanced NSCLC patients with PLC (22, 23).
Association between OS and PFS in the PLC and non-PLC groups analyzed by Cox regression analysis.
Kaplan–Meier estimates of OS and PFS for the PLC group. (a) OS in the PLC group did not correlate with primary lung TLG (log rank test, p=0.41) (b) PFS in the PLC group correlated with primary lung TLG (log-rank test, p=0.04). (c) OS in the PLC group did not correlate with whole-body TLG (log-rank test, p=0.92). (d) PFS in the PLC group did not correlate with whole body TLG (log-rank test, p=0.51). OS, Overall survival; PFS, progression free survival; PLC, pulmonary lymphangitic carcinomatosis; TLG, total lesion glycolysis.
The current study showed that increased diffuse FDG uptake in the lungs correlated with the CT pattern of PLC, that was concordant with previous studies (12-14). For example, Digumarthy et al. showed that the FDG uptake pattern in 7 patients with PLC was the same as that on chest CT (14).
To our knowledge, there have been no prior publications reporting MTV, TLG or SUVmax in advanced NSCLC patients with PLC. Although Prakash et al. reported that the SUVmean in patients with PLC was significantly greater than that in patients without PLC (12), the authors analyzed SUVmean alone. Recent studies have demonstrated that MTV, TLG and SUVmax are significantly better predictors than SUVmean (24-26). In the current study, FDG uptake values (SUVmean, SUVmax, MTV and TLG) were lower in patients without PLC. In addition, there was a significant difference in primary lung tumor and whole-body TLG between patients with or without PLC. Primary lung tumor TLG was a predictor of PFS in patients with PLC, whereas whole-body TLG was a predictor of PFS and OS in patients without PLC.
Prognostic factors of lung cancer have been studied extensively, including clinical factors, such as tumor stage, age, treatment and ECOG performance status (27-29). In the current study, clinical factors, such as age and treatment modality, were significantly associated with OS or PFS in both the PLC and non-PLC groups. However, treatment modality was the only significant predictor of OS among patients with PLC.
This study has several limitations. First, we used a percentage threshold (i.e. 50% of SUVmax) to compute the tumor volume; we compared the value with the background of fused CT images, irrespective of whether any adjustment of the threshold was needed (30, 31). The choice of this threshold influences the tumor volume measurements; however, there is no consensus on how to delineate tumor volume and, thus, validation of this method is needed for future studies. Second, inflammation, especially in granulomatous changes, could also affect FDG uptake in the lung. However, to minimize this, we excluded any patients with active tuberculosis, interstitial lung disease, pulmonary edema, opportunistic infection, radiation fibrosis or drug-induced lung disease. Third, this was a retrospective study with a limited number of patients. A further large, prospective, randomized, multicenter study is needed to validate the findings of this report.
Kaplan–Meier estimates of OS and PFS for the non-PLC group. (a) OS in the non-PLC group did not correlate with primary lung TLG (log rank test, p=0.35). (b) PFS in the non-PLC group did not correlate with primary lung TLG (log rank test, p=0.19). (c) OS in the non-PLC group correlated with whole lung TLG (log-rank test, p=0.01). (d) PFS in the non-PLC group correlated with whole lung TLG (log-rank test, p=0.03). OS, Overall survival; PFS, progression free survival; PLC, pulmonary lymphangitic carcinomatosis; TLG, total lesion glycolysis.
Conclusion
In conclusion, the data suggest that an assessment of primary lung tumor TLG would be useful for predicting among patients with PLC. However, whole-body TLG could be useful for predicting only in patients without PLC. The different risk group (PLC or non-PLC) should be having a different predicting tool.
Acknowledgements
This study was performed at the Taichung Tzu Chi Hospital, Taiwan, ROC. The Authors thank the Department of Nuclear Medicine and the Cancer Center for their technical help and general support. This work was in part supported by grant MOST 103-2314-B-371-004-MY3.
- Received June 14, 2016.
- Revision received July 4, 2016.
- Accepted July 5, 2016.
- Copyright© 2016 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved
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