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FDG-PET/CT tumor to liver SUV ratio (TLR), tumor SUVmax, and tumor size: can this help in differentiating squamous cell carcinoma from adenocarcinoma of the lung?
Egyptian Journal of Radiology and Nuclear Medicine volume 53, Article number: 103 (2022)
PET/CT plays an essential role in the diagnosis, staging, and follow-up of lung cancer. We aimed to assess the ability of PET/CT to differentiate between adenocarcinomas (AC) and squamous cell carcinomas (SCC) of the lung using tumor size, tumor maximum standardized uptake value (SUVmax), lymph nodes SUVmax, and tumor to liver SUV ratio (TLR).
A total of 60 patients pathologically proved to have non-small cell lung cancer either AC or SCC were retrospectively evaluated. The mean tumor size, SUVmax of the tumor, and TLR were significantly higher in SCC lesions compared to AC lesions. The mean SCC tumoral size was 7.96 ± 2.18 cm compared to 5.66 ± 2.57 cm in AC lesions (P = 0.008). The mean tumor SUVmax in SCC lesions was 18.95 ± 8.3 compared to 12.4 ± 7.55 in AC lesions (P = 0.04). While the mean TLR of SCC lesions was 10.32 ± 4.03 compared to 7.36 ± 4.61 in AC lesions (P = 0.028). All three parameters showed the same sensitivity (75%), while TLR showed the highest specificity (77.78%) followed by tumor size (76.47%) and then SUVmax of the tumor (72.22%).
SCC of the lung has a higher mean tumor size, SUVmax of the tumor, and TLR as compared to AC which can be helpful tools in differentiation between them using PET/CT.
Lung cancer is considered one of the commonest cancer in the world characterized by its high mortality rates worldwide [1, 2]. Pathologically, bronchogenic carcinoma has two major types namely; non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) with NSCLC being the commonest type representing 86% of cases. NSCLC is further subdivided into three main subtypes with adenocarcinoma (AC) that comes with the highest incidence (60%) followed by squamous cell carcinoma (SCC) (20%) and lastly large-cell carcinoma (3%) .
The integration of Fluoro-deoxyglucose positron emission tomography (FDG-PET) and computed tomography (CT) plays an essential role in the diagnosis and staging which reflects on the treatment strategy and follow-up of patients with bronchogenic carcinoma. PET/CT is a well-established radiological modality with high diagnostic accuracy in metastases detection compared to usual CT. Also, it has been reported that up to 10% of patients with bronchogenic carcinoma are found to have metastases on PET/CT that were not detected on CT with subsequent different patients’ staging . The high accuracy of PET/CT in tumor staging makes it important for the treatment strategy either surgical treatment or radiotherapy or chemotherapy. Also, it becomes essential during the follow-up to detect recurrence. PET/CT shows a higher ability to evaluate the early response to the treatment as chemotherapy by its ability to detect the metabolic response even before the size change .
SUVmax is a PET semi-quantitative index that is calculated easily and considered a reflection of the lesion metabolic activity. It is a well-known parameter used to differentiate malignant from benign lesions .
It is important to differentiate AC from SCC of the lung because this affects the management strategy of the patients and changes the choice of treatment type. For example, Pemetrexed is known to have more effect during the treatment of patients with advanced lung AC rather than SCC. Also, Bevacizumab used in the treatment of patients with AC is considered contraindicated in patients with SCC .
The most standard way of differentiating the different types of bronchogenic carcinoma is tissue biopsy. In cases of peripheral tumors, CT-guided biopsy is the method of choice but it carries a risk of pneumothorax and pleural effusion/hemorrhage . However, in cases with central masses, it is recommended for the biopsy to be taken trans-bronchial, but this carries the risk of hemorrhage secondary to vascular/tissue injury especially if close to the mediastinal structure .
Because of biopsy complications, it is important to search for other non-invasive modalities to differentiate the different pathological types of lung cancer to avoid such complications and decrease the incidence of patient morbidity and mortality secondary to biopsy. Recent research is now directed to the use of PET/CT not only in the diagnosis, staging, and follow-up of patients but also to differentiate between different histological subtypes and also with different tumor grades [9,10,11,12,13,14].
In this study, we tried to assess the ability of PET/CT as a non-invasive radiological modality that can be used to differentiate AC from SCC by comparing the tumor size, tumor SUVmax, and lymph nodes SUVmax, and tumor to liver SUVmax ratio (TLR).
After ethical approval from our institutional ethical committee, 60 patients with pathologically proved NSCLC were included in this retrospective study who came in the period from April 2018 to December 2020 to do PET/CT in Radiology Department-Ain Shams University after a referral from the chest/radiotherapy team for staging aiming to start the adequate therapy or to proceed with surgery if indicated. The patient's privacy and data confidentiality were guaranteed during the whole study. All patients were subjected to post-contrast CT followed by PET scanning in the same session.
We included any patient with biopsy proved AC or SCC before starting any type of treatment related to lung cancer. No age or sex predilection. We excluded any patients with unavailable pathological data or cases with other pathological types rather than SCC or AC. Also, patients who came for follow-up studies after the start of treatment were excluded to avoid the effect of treatment on the tumor size and metabolic activity.
Scans were scheduled at least one month after any tumoral/nodal biopsy to avoid false-positive results. All patients were instructed to avoid vigorous exercise for several days before scanning, to fast except water for 4–6 h at least before the examination. Recent serum creatinine was requested and confirmed to be within normal before the study. Also, in cases with diabetes adequate control of the blood glucose level was required before the date of imaging with serum glucose levels were measured to ensure adequate glucose level (Fasting blood glucose level < 150 mg/dl).
Venous access was needed with the insertion of a cannula inside the antecubital vein was preferable at the contralateral tumor side. The patients were kept in a controlled warm temperature room to decrease the FDG uptake by the brown fat.
We used a Discovery IQ 5 ring machine class I IPX0 with 16 slices CT, GE (General Electric Company, Milwaukee, Wisconsin, USA, 2016). 10–20 mCi were injected 45–60 min before the exam and the patients were asked to rest in a quiet place without vigorous activity and trying to avoid even talking as minimal as they can.
All patients were placed in a supine position with elevated arms for imaging acquisition starting from the skull vault down to the upper thigh level. We started with post-contrast CT followed by PET imaging using the same scan area.
125 mL of a low-osmolarity contrast medium was used for CT imaging (Optiray 350) at a rate of 4 mL/s by using an injector. The scanning parameters were 110 mA, 110 kV, 0.5 s tube rotation time, and 3.3 mm section thickness. This was followed immediately by PET scanning using the same field of view with six to seven-bed positions planned in the three-dimensional acquisition mode. Three to five minutes were consumed for each acquisition at each bed position.
The patients were asked to avoid children for at least 24 h after the study, drink plenty of amounts of water, and stop lactation for 24 h.
All images including PET and CT images were transferred to a specific workstation where PET/CT fused images could be done. Multi-planar reformatted images (MPR) were done for both PET and CT images. PET/CT images were interpreted via an experienced specialized radiologist in PET/CT fields for at least five years blinded to the pathological types of the cases.
The size of the tumor was measured as the maximum diameter of the lesion measured in the contrast-enhanced CT images. SUVmax of the tumor was measured by placing the region of interest (ROI) around the primary tumor that has avid FDG uptake. SUVmax of the LN was measured by placing the ROI around the lymph node that has avid FDG uptake. SUVmax of the liver was measured by placing the ROI at the liver. TLR was calculated by dividing the SUVmax of the tumor by the SUV of the liver.
Statistical analysis of data
The analysis of data was done using IBM SPSS statistics (V. 24.0, IBM Corp., USA, 2016). Wilcoxon–Mann–Whitney test was used to compare the means of quantitative variables for two independent groups. The Chi-square test was used to compare the two independent groups regarding qualitative data. Spearman correlation coefficient was used to determine the correlation between quantitative variables. Receiver operating characteristics (ROC) and area under the curve (AUC) were used to determine the ability of a quantitative variable to differentiate between two independent groups with a determination of the cut-off with the best sensitivity and specificity.
This was a retrospective study conducted over 60 patients with a mean age of 56.9 ± 11.5 years. 50 patients were males representing 83.3% with a mean age of 56.28 ± 11.54 years while the rest 10 patients representing 16.7% were females with a mean age of 60 years ± 12.27 years. 36 patients (60%) were diagnosed by a biopsy to have AC while the rest 24 patients (40%) were diagnosed with SCC.
We found no significant relationship between the histopathology of the tumor and the age or the sex of the patients (P value = 0.55 and 0.32, respectively) (Table 1).
As regards the bronchogenic carcinoma tumoral mass size, the mean tumor size was 6.58 ± 2.65 cm in all our cases. The tumoral mass size showed a statistical significance higher difference between the patients with SCC measuring 7.96 ± 2.18 cm compared to the size in patients with AC measuring 5.66 ± 2.57 cm with a calculated P value = 0.008 (Tables 1, 2) (Fig. 1). There was no significant relationship between the size of the tumor and the age or sex of the patients (P value = 0.27 and 0.53, respectively) (Table 1).
The mean SUVmax of the tumor between our 60 patients was 15.02 ± 8.4 (range: 2–32.8). The mean SUVmax of AC lesions was 12.4 ± 7.55 (range: 2–32.8), while the mean SUVmax of SCC lesions was 18.95 ± 8.3 (range: 3.7–30.77). The mean SUVmax of lesions in patients with SCC was significantly higher than that of patients with AC using the Wilcoxon–Mann–Whitney test (P value = 0.04) (Tables 1, 3) (Figs. 2, 3, 4). There was no statistically significant difference found between the SUVmax of the tumor and the sex of the patients (P value = 0.16). Also, we found no significant relationship between the SUVmax of the lesion and the age of the patients (P value = 0.87) (Table 1).
Between the 60 patients, 45 patients showed positive metastatic lymphadenopathies with no statistically significant difference between the AC and SCC in lymph nodes SUVmax (P value = 0.53). While we found a highly significant correlation between the SUVmax of the LN and the SUVmax of the tumor and only a significant correlation with the TLR (Table 1) (Figs. 5, 6).
Lastly, the SUVmax of the tumor was divided by the SUV of the liver to calculate the tumor to liver ratio (TLR). The mean TLR of the 60 patients was 8.54 ± 4.56 (range 1.43–21.5). The mean TLR of AC patients was 7.36 ± 4.61 (range 1.43–21.5) while it was 10.32 ± 4.03 (range 2.68–16.69) for SCC patients. A statistically significant difference was found between patients with AC and SCC as regards the TLR (P value = 0.028) with TLR tended to be higher in patients with SCC (Tables 1, 4) (Figs. 3, 4, 5, 6, 7). A significant relation was found between TLR and SUVmax of the tumor (P value = 0.000). No significant relation was found between the TLR and the size of the lesion (P value = 0.66) (Table 1).
The best cut-off value in our study regarding the tumor mass size was 7.55 cm with 75% sensitivity, 76.5% specificity, and area under curve = 0.794 (Table 5) (Fig. 1). while for SUVmax was 15.45 with 75% sensitivity, 72.2% specificity, and 73.3% accuracy, and area under curve = 0.72 (Table 5) (Fig. 2). The best cut-off value of TLR to be used as a differentiation between the AC and SCC was 9.49 with 75% sensitivity, 77.8% specificity, and 76.67% accuracy, and area under curve = 0.741 (Table 5) (Fig. 7).
In this study, we tried to differentiate between AC and SCC of the lung using PET/CT parameters. We found a statistically significant difference between the SCC and AC regarding the tumor size, SUVmax of the tumor, and the TLR with these parameters are higher among patients with SCC.
We studied 60 patients who were pathologically proven to have either lung SCC or AC which are considered the most common pathological types. The number of patients with AC was larger than patients with SCC at 60% and 40%, respectively. This is consistent with the international epidemiology of lung cancer and the switch that happened after 1990 with lung AC becoming the first type of lung cancer representing 60% of all types followed by SCC representing 20% . Karam et al. , Kim et al. , and Wang et al.  also included patients with only pathologically proven AC and SCC during their research and found that the AC patients are more than SCC patients; AC patients in their sample represented 60.2%, 56.3%, and 66.4%, respectively, which is very close to our patient sample. However, Lu et al.  and Sunnetcioglu et al.  included patients with other pathological types such as bronchoalveolar carcinoma and small cell lung cancer.
A significant correlation was found between the size of the tumor measured on contrast-enhanced CT images and the pathological type of the tumor with SCC masses showed higher sizes compared to the AC masses with P value = 0.008. This is also in keeping with previous studies that found a larger size of SCC tumor [12, 14, 17].
Multiple previous studies found a significant correlation between the pathological type of the NSCLC and SUVmax of the tumoral lesions with SCC lesions showed higher SUVmax compared to AC [12,13,14,15,16,17]. This is in agreement with our result and this can be explained by the higher size of the SCC tumors as shown in our study and subsequently containing a larger number of malignant cells leading to increased metabolic activity compared to AC tumors which reflects the FDG uptake and SUVmax.
De Geus et al.  found a significant difference between the SUVmax of SCC compared to AC and large cell carcinoma yet there was no significant difference found between AC and large cell carcinoma. Lu et al.  found a statistically significant difference between the SUVmax of SCC, AC, and bronchoalveolar carcinoma. Multiple studies also found a correlation between the SUVmax and the degree of differentiation of the tumor [9, 17].
Regarding the SUVmax of the lymph nodes, no significant difference was found between the SUVmax of the lymph nodes of AC patients and SCC patients and no significant correlation between the SUVmax of the lymph nodes and the size of the tumor; however, we found a highly significant correlation between the SUVmax of the LN and SUVmax of the tumor. Wang et al.  also found no difference between AC and SCC as regards the metastatic lymph nodes SUVmax. Nambu et al.  and Li et al.  reported that tumor with higher SUVmax has a higher risk of lymph nodes metastases.
In the current study, we tried to make a normalization for the SUVmax of the tumor by dividing it by the SUVmax of the liver trying to eliminate the effects of other parameters that may affect the accuracy of the SUVmax such as the dose of FDG, the weight of the patient, the time gap between the injection and the acquisition and lastly the patients’ glucose level. Multiple previous types of research used the liver as a parameter for normalization [17, 22]. TLR showed a significant difference between patients with AC and patients with SCC being higher in patients with SCC and this is consistent with Duan et al.  who concluded that TLR is one of the parameters which can be used to differentiate between SCC and AC and also showed a significant correlation with the tumor differentiation.
To our knowledge, no previous studies tried to calculate the cut-off values of SUVmax of the tumor, size of the tumor, and TLR which can be used to differentiate between the SCC and AC. However, all these parameters showed the same sensitivity (75%), and TLR showed the highest specificity 77.78% compared to 76.47% for tumor size and 72.22% for SUVmax.
Shao et al.  tried to use PET/CT to predict the different pathological subtypes and growth patterns of early adenocarcinoma. They found higher SUVmax in cases with invasive adenocarcinoma compared to adenocarcinoma in situ and minimally invasive adenocarcinoma with median SUVmax = 2.0 which was the optimal cutoff value with P value = 0.008. Also, they found a SUVmax of 1.4 was the optimal cutoff value for differentiating the growth pattern of adenocarcinoma.
Liu et al.  tried to use SUVmax to differentiate between the synchronous multiple primary lung tumors and the lung metastases and they found SUVmax of 1.7 the best cut-off value with 62.7% sensitivity and 82.6% specificity.
Limitations The current study tried to differentiate between the two commonest pathological subtypes of lung cancers. So, further studies can be conducted on more pathological types. Also, bigger sample size and multicentric studies are needed to obtain more accurate results. Finally, the degree of tumor differentiation is better to be added in comparison.
PET/CT is the gold standard for lung tumor staging with tumor SUVmax, TLR, and tumor size can be used as non-invasive quantitative differentiation parameters between SCC and AC being higher among SCC. With more advances in PET/CT, biopsy hazards are expected to be avoided.
Availability of data and materials
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Fluoro-deoxyglucose positron emission tomography
Positive likelihood ratio
Negative likelihood ratio
Negative predictive value
Non-small cell lung cancer
Positive predictive value
- ROC curve:
Receiver operating characteristic curve
Squamous cell carcinoma
Small cell lung cancer
Statistical package forth social sciences
- SUVmax :
Maximum standardized uptake value
Volpi S, Ali JM, Tasker A et al (2018) The role of positron emission tomography in the diagnosis, staging, and response assessment of non-small cell lung cancer. Ann Transl Med 6(5):95–103. https://doi.org/10.21037/atm.2018.01.25
Siegel R, Ma J, Zou Z et al (2014) Cancer statistics, 2014. CA Cancer J Clin 64(1):9–29. https://doi.org/10.3322/caac.21208
Barta JA, Powell CA, Wisnivesky JP (2019) Global epidemiology of lung cancer. Ann Glob Health 85(1):1–16. https://doi.org/10.5334/aogh.2419
Messerli M, Kotasidis F, Burger IA et al (2019) Impact of different image reconstructions on PET quantification in non-small cell lung cancer: a comparison of adenocarcinoma and squamous cell carcinoma. Br J Radiol 92(1069):20180792. https://doi.org/10.1259/bjr.20180792
Choi EK, Park HL, Yoo IR et al (2020) The clinical value of F-18 FDG PET/CT in differentiating malignant from benign lesions in pneumoconiosis patients. Eur Radiol 30:442–451. https://doi.org/10.1007/s00330-019-06342-1
Travis WD, Brambilla E, Noguchi M et al (2011) The new IASLC/ATS/ERS international multidisciplinary lung adenocarcinoma classification. J Thoracic Oncol 6(2):244–285. https://doi.org/10.1097/jto.0b013e318206a221
Lang D, Reinelt V, Horner A et al (2018) Complications of CT-guided transthoracic lung biopsy: a short report on current literature and a case of systemic air embolism. Wien Klin Wochenschr 130:288–292
Hetzel J, Eberhardt R, Petermann C et al (2019) Bleeding risk of transbronchial cryobiopsy compared to transbronchial forceps biopsy in interstitial lung disease—a prospective, randomized, multicentre cross-over trial. Respir Res 20:140. https://doi.org/10.1186/s12931-019-1091-1
Zhu SH, Zhang Y, Yu YH et al (2013) FDG PET-CT in non-small cell lung cancer: the relationship between primary tumor FDG uptake and extensional or metastatic potential. Asian Pac J Cancer Prev 14(5):2925–2929. https://doi.org/10.7314/APJCP.2013.14.5.2925
Sim YT, Goh YG, Dempsey MF et al (2013) PET–CT evaluation of solitary pulmonary nodules: correlation with maximum standardized uptake value and pathology. Lung 191:625–632. https://doi.org/10.1007/s00408-013-9500-6
Yu J, Zhu H, Fu Z et al (2016) Prognostic value of the standardized uptake value maximum change calculated by dual-time-point 18F-Fluorodeoxyglucose positron emission tomography imaging in patients with advanced non-small-cell lung cancer. Onco Targets Ther 9:2993–2999. https://doi.org/10.2147/OTT.S104919
Karam MB, Doroudinia A, Behzadi B et al (2018) Correlation of quantified metabolic activity in non-small cell lung cancer with tumor size and tumor pathological characteristics. Medicine 97(32):e11628. https://doi.org/10.1097/MD.0000000000011628
Kim DH, Jung JH, Son SH et al (2015) Prognostic significance of intratumoral metabolic heterogeneity on 18F-FDG PET/CT in pathological N0 non-small cell lung cancer. Clin Nucl Med 40(9):708–714. https://doi.org/10.1097/RLU.0000000000000867
Wang Y, Ma S, Dong M et al (2015) Evaluation of the factors affecting the maximum standardized uptake value of metastatic lymph nodes in different histological types of non-small cell lung cancer on PET-CT. BMC Pulm Med 15:20. https://doi.org/10.1186/s12890-015-0014-2
Lu P, Yu L, Li Y et al (2010) A correlation study between maximum standardized uptake values and pathology and clinical staging in non-small cell lung cancer. Nucl Med Commun 31:646–651. https://doi.org/10.1097/MNM.0b013e328339bddb
Sunnetcioglu A, Arisoy A, Demir Y et al (2015) Association between the standardized uptake value of 18F-FDG PET/CT and demographic, clinical, pathological, radiological factors in lung cancer. Int J Clin Exp Med 8:15794–15800
Duan X, Wang W, Li M et al (2015) Predictive significance of standardized uptake value parameters of FDG-PET in patients with non-small lung carcinoma. Braz J Med Biol Res 48:267–272. https://doi.org/10.1590/1414-431X20144137
De Geus-Oei LF, van Krieken JH, Aliredjo RP et al (2007) Biological correlates of FDG uptake in non-small cell lung cancer. Lung Cancer 55:79–87. https://doi.org/10.1016/j.lungcan.2006.08.018
Lin M, Wu M, Brennan S et al (2014) Absence of a relationship between tumor 18f-fluorodeoxyglucose standardized uptake value and survival in patients treated with definitive radiotherapy for non-small lung cancer. J Thorac Oncol 9:377–382. https://doi.org/10.1097/JTO.0000000000000096
Nambu A, Kato S, Sato Y et al (2009) Relationship between maximum standardized uptake value (SUVmax) of lung cancer and lymph node metastases on FDG-PET. Ann Nucl Med 23:269–275. https://doi.org/10.1007/s12149-009-0237-5
Li M, Wu N, Zheng R et al (2013) Primary tumor PET/CT (18F)FDG uptake is an independent predictive for regional lymph node metastasis in patients with non-small cell lung cancer. Cancer Imaging 12:566–572. https://doi.org/10.1102/1470-7330.2012.0040
Hofheinz F, Butof R, Apostolova I et al (2016) An investigation of the relation between the tumor-to-liver ratio (TLR) and tumor-to-blood standard uptake ratio (SUR) in oncological FDG PET. EJMMI Res 6:1–9. https://doi.org/10.1186/s13550-016-0174-y
Shao X, Niu R, Jiang Z et al (2020) Role of PET/CT in management of early adenocarcinoma. AJR 214(2):437–445. https://doi.org/10.2214/AJR.19.21585
Liu Y, Tang Y, Xue Z et al (2020) SUVmax ratio on PET/CT may differentiate between lung metastases and synchronous multiple primary lung cancer. Acad Radiol 27(5):618–623. https://doi.org/10.1016/j.acra.2019.07.001
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Ethics approval and consent to participate were taken from our institute ethical committee (Faculty of Medicine-Ain shams university) with written informed consents were waived being a retrospective study.
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The written informed consents were waived being a retrospective study.
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Salem, A.M.A., Hussein, L.H. & Osman, A.M. FDG-PET/CT tumor to liver SUV ratio (TLR), tumor SUVmax, and tumor size: can this help in differentiating squamous cell carcinoma from adenocarcinoma of the lung?. Egypt J Radiol Nucl Med 53, 103 (2022). https://doi.org/10.1186/s43055-022-00782-4
- Squamous cell carcinoma