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The prognostic value of multidetector CT features in predicting overall survival outcomes in patients with pancreatic neuroendocrine tumors
European Journal of Radiology 124 (2020) 108847
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European Journal of Radiology journal homepage: www.elsevier.com/locate/ejrad
Research article
The prognostic value of multidetector CT features in predicting overall survival outcomes in patients with pancreatic neuroendocrine tumors
T
Bo Yanga,b,1, Hai-Yan Chena,1, Xue-Yan Zhanga,c, Yao Pana, Yuan-Fei Lua, Ri-Sheng Yua,* a
Department of Radiology, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China Department of Radiology, Zhejiang Prison Center Hospital (Zhejiang Youth Hospital), Hangzhou, China c Department of Radiology, Institute of Occupational Diseases, Zhejiang Academy of Medical Sciences, Hangzhou, China b
A R T I C LE I N FO
A B S T R A C T
Keywords: Neuroendocrine tumors Pancreas Computed tomography Survival analysis
Purpose: To assess the prognostic value of multidetector CT in predicting overall survival outcomes in patients with pancreatic neuroendocrine tumors (PNETs). Method: Seventy-one patients pathologically diagnosed with PNETs were retrospectively included. The clinical and imaging information was evaluated by two radiologists. The difference between well-differentiated and poorly differentiated PNETs was analyzed. Cox proportional hazards models were created to determine the risk factors for overall survival. Kaplan-Meier survival analyses with log-rank tests were used among different subgroups of patients with PNETs. Results: In the whole cohort, the median survival was 36 months, and the 5-year survival rate was 84.8 %. Patients with poorly differentiated PNETs were more likely to present with symptoms, abnormal tumor markers, larger diameters, irregular shapes, ill-defined margins, invasion into nearby tissues, liver and lymph node metastases, and lower enhancement ratio than those with well-differentiated PNETs (P < 0.05). In the multivariate analysis, lymph node metastases (hazard ratio: 21.52, P = 0.009) and a portal enhancement ratio less than 1.02 (hazard ratio: 30.89, P = 0.024) were significant factors for overall survival. Overall survival decreased with an ill-defined margin, irregular shape, poor differentiation, grade 3 disease, nonfunctional status, abnormal tumor marker levels, invasion into nearby tissues, lymph node and liver metastases, and lower enhancement ratio (logrank P < 0.05). Conclusions: Poorly differentiated PNETs were more aggressiveness than well-differentiated PNETs. Lymph node metastases and a portal enhancement ratio < 1.02 were independent prognostic factors for worse overall survival outcomes in patients with PNETs.
1. Introduction Pancreatic neuroendocrine tumors (PNETs) are considered the second most common malignancy of the pancreas, accounting for up to 1–3 % of all pancreatic cancers [1,2]. PNETs are a group of heterogeneous lesions with diverse radiological, pathological and clinical features, stemming from neuroendocrine cells or the islets of Langerhans of the pancreas [1]. Because of their ability to secrete hormones, PNETs are stratified into functional PNETs or nonfunctional PNETs [3]. According to the 2017 WHO classification, PNETs can be divided into well-differentiated and poorly differentiated PNETs (also named as
neuroendocrine carcinomas), and the former is further subdivided into grade 1 (G1), grade 2 (G2) and well-differentiated grade 3 (G3) [4]. These two groups of tumors range from indolent to highly aggressive in nature, resulting in many differences in imaging and clinical presentation, survival outcomes, and genetic underpinnings [5]. In a larger clinical population study of NETs, the median five-year overall survival (OS) rate varied with grade, age, stage, primary location, and diagnostic time [2]. PNETs stage is determined by tumor diameter, local invasion, and lymph node and distant metastases, which can be measured through multidetector CT [6]. The sensitivity and specificity of CT in detecting PNETs in patients are 61–93 % and
Abbreviations: PNETs, pancreatic neuroendocrine tumors; G1/2/3, grade 1/2/3; ROC, receiver operating characteristic; HR, hazard ratio; CI, confidence interval; AUC, area under the curve ⁎ Corresponding author at: Department of Radiology, Second Affiliated Hospital, Zhejiang University School of Medicine. Jiefang Road 88#, Hangzhou, 310009, China. E-mail address: [email protected] (R.-S. Yu). 1 Bo Yang and Hai-Yan Chen contributed equally and should be considered as co-first authors. https://doi.org/10.1016/j.ejrad.2020.108847 Received 17 September 2019; Received in revised form 3 December 2019; Accepted 18 January 2020 0720-048X/ © 2020 Published by Elsevier B.V.
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64 (Siemens Medical Systems, Erlangen, Germany, n = 41) and TOSHIBA Aquilion 16 (Toshiba Medical Systems Corporation, Tochigi ken, Japan, n = 30). Patients initially underwent plain CT scans; then, nonionic contrast medium (iopromide; Ultravist 370, Bayer Schering Pharma, Berlin, Germany) was intravenously injected at a rate of 3 mL/ s. Arterial phase and portal venous phase images were acquired at 25−35 s and 60 s, respectively. Other parameters were as follows: voltage: 120 kV; maximum tube current: 250 mAs and 150–350 mAs for the arterial phase and portal venous phase, respectively; slice thickness: 3 mm; slice collimation: 0.6 mm; and field of view (FOV): 380 × 380.
71–100 %, respectively [7]. According to previous studies, the typical performance of CT in identifying PNETs relies on a well-demarcated margin, hypervascular enhanced or delayed rim enhancement pattern, lack of dilation of the pancreatic duct and the presence of a hemorrhage or calcifications [8–10]. Some tend to evaluate prognostic factors through clinical evaluations, while others try to use imaging features to predict the outcomes [11]. However, few studies have focused on the CT features associated with survival outcomes or recurrence-free survival, and the results in the existing literature vary [11–14]. The recurrence-free survival of patients with PNETs in our study was very rare, and thus, firm conclusions could not be drawn. Hence, our study aimed to assess only the prognostic value of multidetector CT in predicting OS outcomes in patients with PNETs.
2.3. Imaging analysis The imaging features were assessed by two radiologists (with 8 and 6 years of experience in abdominal radiology) who were blinded to the pathological outcomes. Disagreements were settled by consensus after consulting a third radiologist with 31 years of experience in pancreatic radiology. Clinical characteristics such as age, sex, presence of symptoms related to PNETs, tumor marker levels (carbohydrate antigen (CA) 19-9, carcinoembryonic antigen (CEA), CA 125), functional tumor status and survival outcomes were included. OS was defined from the date of biopsy or surgery to the date of patient's death. The data were censored if the patient was alive at the end of the follow-up period (June 1, 2019) or if the patient was lost to follow up without reason. General imaging features such as location (head/neck vs body/tail), maximum diameter on the axial images, shape (round vs irregular), the presence of calcifications or cystic degeneration, tumor margin (well-defined vs ill-defined), enhancement intensity, dilation of the pancreatic duct (≥3 mm [15]), pancreatic atrophy and pancreatitis were collected. Enhancement intensity was expressed by the plain/arterial/portal enhancement ratio. For example, the arterial enhancement ratio was defined as the HU of the lesion/HU of the nearby pancreatic parenchyma measured on the arterial phase, and the plain and portal enhancement ratios had similar definitions [11], and the equation of each phase of contrast was HU of the lesion as follows: enhancement ratio = HU of the banckground pancreas . The imaging features that conveyed aggressive behavior such as invasion into the nearby tissues, lymph node metastases (short axis larger than 10 mm or necrosis of any size [16,17]) and liver metastases (multiple peripheral enhanced or hypervascular enhanced nodules [18]) were also collected.
2. Materials and methods 2.1. Study population Our institutional review board has approved this retrospective study, and the requirement for informed consent was waived. Patients pathologically diagnosed with PNETs at The Second Affiliated Hospital of Zhejiang University School of Medicine from January 1, 2012 up to June 1, 2019, were retrospectively evaluated. The inclusion criteria were as follows: 1) with detailed pathological and follow up information; 2) dynamic enhanced multidetector CT within 2 months prior to surgery or biopsy; 3) no local treatment or chemotherapy before the operation. The exclusion criteria were as follows: 1) severe pancreatic atrophy when measured in CT Hounsfield units (HU) due to a lack of a region of interest (n = 3); 2) invisible lesions (n = 9); 3) no integrated imaging data (n = 6); 4) survival data was incomplete (n = 4). Finally, we included 71 patients in our study (Fig. 1). Five patients had multiple PNETs, and the largest lesion was selected for further evaluation. Every sample was reviewed separately by two pathologists, and the Ki67 index value of 50 % was used to distinguish well-differentiated from poorly differentiated PNETs [7]. Well-differentiated PNETs were defined as those with a Ki67 index < 50 %, while poorly differentiated PNETs were defined as those with a Ki67 index > 50 %. 2.2. Image acquisition
2.4. Statistical analysis Before the examination, all patients were asked to abstain from solid food for 4−6 h. Two kinds of CT scanners were used: Siemens Emotion
Quantitative data are manifested as the mean ± standard deviation
Fig. 1. Flow chart depicting the selection of patients with PNETs. 2
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% vs 18 %), ill-defined margin (70 % vs 11.5 %), invasion into nearby tissues (70 % vs 9.8 %), liver metastases (60 % vs 8.2 %), lymph node metastases (30 % vs 4.9 %), a lower arterial enhancement ratio (0.71 vs 1.20), and a lower portal enhancement ratio (0.76 vs 1.24) than those with well-differentiated PNETs. These differences were statistically significant (P < 0.05). All functional tumors were well-differentiated PNETs. There was no significant difference in sex, age, location, calcification, texture, pancreatic atrophy, pancreatitis, pancreatic duct dilation or plain ratio between patients with well-differentiated PNETs and those with poorly differentiated PNETs (P ≥ 0.05) (Fig. 2).
or median (25–75 th percentile) based on their distribution, and qualitative data are expressed as frequencies (percentages). Student’s t-tests or Mann-Whitney U tests were used for continuous variables, while Fisher’s exact tests or χ2 tests were used to compare categorical data between well-differentiated PNETs and poorly differentiated PNETs. Quantitative variables were dichotomized for Cox regression analysis, and receiver operating characteristic (ROC) curves were created to determine the best cutoff values. Thus, a univariate Cox proportional hazard model was created to identify the risk factors for prognosis. The factors with a p value < 0.1 were included in the multivariate Cox regression analysis to determine the final independent prognostic risk factors. A Kaplan-Meier survival analysis with the log-rank test was used to analyze the survival outcomes among different subgroups. P < 0.05 was considered statistically significant. ROC curves were created by Medcalc software V.18 (Mariakerke, Belgium), while other analyses were performed by Stata 14.0 (Stata Corporation, College Station, Texas, USA).
3.2. Univariate and multivariate Cox regression analysis of the study population Before the univariate Cox analysis, quantitative variables, including age, diameter, plain ratio, arterial enhancement ratio and portal enhancement ratio, were dichotomized; the area under the curve (AUC), 95 % confidence interval (CI), best cutoff values, sensitivity and specificity are shown in Table 2. Furthermore, a univariate Cox analysis was performed, and the results summarized in Table 3. Abnormal tumor marker levels (hazard ratio (HR): 13.0), poorly differentiated PNETs (HR: 24.85), diameter larger than 25.9 mm (HR: 13.1), irregular shape (HR: 8.15), ill-defined margin (HR: 11.53), invasion into nearby tissues (HR: 5.23), lymph node metastases (HR: 7.78), liver metastases (HR: 17.17), arterial enhancement ratio < 0.84 (HR: 9.31), and portal enhancement ratio < 1.02 (HR: 17.14) were factors that might impact survival outcomes. We then entered these variables along with those with P < 0.10 into the multivariate Cox regression analysis. The results are presented in Table 4 and suggest that lymph node metastases (HR: 21.52) and a portal enhancement ratio < 1.02 (HR: 30.89) were independent prognostic factors related to poor outcomes.
3. Results 3.1. Comparison of clinical and imaging features between welldifferentiated PNETs and poorly differentiated PNETs The whole population and subgroup information are summarized in Table 1. A total of 71 patients were included, with an average age of 52.34 ± 13.10, and 50.7 % of the patients were female. A total of 66.2 % of the patients presented with symptoms; all of the functional lesions were insulinomas, and the chief complaint was hypoglycemia. According to the 2017 WHO classification, 61 of these tumors were welldifferentiated PNETs, and 10 were poorly differentiated PNETs. Patients with poorly differentiated PNETs were more likely to present with symptoms (100 % vs 60.7 %), elevated tumor marker levels (50 % vs 11.5 %), larger diameter (40.0 mm vs 23.4 mm), irregular shape (80
Table 1 The baseline demographic and general radiologic characteristics of all patients in the study and a comparison between well-differentiated PNETs and poorly differentiated PNETs.
Gender Male Female Age Median survival time(m) Symptoms Tumor marker Functional Location Head/neck Body/tail Diameter(mm) Shape Round Irregular Margin Well-defined Ill-defined Calcification Texture Solid Cystic degeneration Pancreatic atrophy Pancreatic duct dilation Pancreatitis Invasion of nearby tissues Liver metastases Lymph node metastases Plain ratio Artery enhancement ratio Portal enhancement ratio
Total (n = 71)
Well-differentiated (n = 61)
Poorly differentiated (n = 10)
35(49.3) 36(50.7) 52.34 ± 13.10 36 47(66.2) 12(16.9) 20(28.2)
29(47.5) 32(52.5) 51.64 ± 13.23 43 37(60.7) 7(11.5) 20(32.8)
6(60) 4(40) 56.60 ± 12.05 9.5 10(100) 5(50) 0(0)
35(49.3) 36(50.7) 24.4(12.4–48.7)
31(50.8) 30(49.2) 23.4(11.8–40.95)
4(40) 6(60) 40.0(25.45–60.9)
52(73.2) 19(26.8)
50(82) 11(18)
2(20) 8(80)
57(80.3) 14(19.7) 15(21.1)
54(88.5) 7(11.5) 15(24.6)
3(30) 7(70) 0(0)
44(62) 27(38) 7(9.9) 7(9.9) 3(4.2) 13(18.3) 11(15.5) 6(8.5) 0.86(0.74–1.0) 1.13 ± 0.51 1.17 ± 0.44
39(63.9) 22(36.1) 5(8.2) 7(11.5) 1(1.6) 6(9.8) 5(8.2) 3(4.9) 0.85(0.76-0.97) 1.20 ± 0.50 1.24 ± 0.44
5(50) 5(50) 2(20) 0(0) 2(20) 7(70) 6(60) 3(30) 0.96(0.73–1.19) 0.71 ± 0.31 0.76 ± 0.17
P-value 0.349
0.27 < 0.001 0.011 0.01 0.028 0.386
0.036 < 0.001
< 0.001
3
0.077 0.4
0.254 0.328 0.05 < 0.001 0.001 0.033 0.432 0.004 ＜0.001
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Fig. 2. (a–c): A 50-year-old female with a well-differentiated PNET within the tail of the pancreas. 2(a). A plain CT scan shows a slightly hypodense nodule with a round shape (white arrow). 2(b–c). The arterial and portal phase present a well-defined lesion (white arrow) with obvious enhancement compared to the pancreatic parenchyma. (d–f): A 38-year-old male with a poorly differentiated G3 PNET within the tail of the pancreas. 2(d). A plain CT scan presents with a slightly hypodense lesion with an irregular shape (white arrow). 2(e–f). The arterial and portal phases show a lesion with obvious hypoenhancement compared to the adjacent pancreas that involves the hilum of the spleen, resulting in infarction in the distal spleen (white arrow). There is also a large metastatic lymph node with a hypoenhanced appearance between the pancreas and left kidney (white arrowhead). Table 2 ROC analysis for cutoff values of age, diameter, plain ratio, artery and portal enhancement ratio in differentiating patients with PNETs. Variables
AUC* (95%CI*)
Cutoff
Sensitivity (%)
Specificity (%)
Age (years) Diameter(mm) Plain ratio Artery enhancement ratio Portal enhancement ratio
0.557 0.779 0.518 0.764 0.852
> 56 ＞25.9 < 0.84 ＜0.84 ＜1.02
60 90 60 73.8 68.9
60.7 63.9 59 90 100
(0.435-0.675) (0.664-0.869) (0.396-0.638) (0.648-0.857) (0.748-0.925)
* AUC: area under the curve; 95 %CI: 95 % confidence interval.
ratio less than 1.02 were strong independent prognostic factors for worse outcomes in the multivariate Cox regression analysis, according to our study. Moreover, poorly differentiated PNETs were more aggressive and were more prone to result in invasion into nearby tissues and lymph node and hepatic metastases than low-grade PNETs; these factors caused a short median survival rate. Grade and differentiation are often confused. Grade is mostly discussed and could be an indicator of the aggressive behavior of PNETs. However, differentiation is pertinent for the morphological conformity in the neuroendocrine cells of PNETs, which may more truly reflect biological behavior than grade [5]. The treatment for PNETs also differs. Surgery is always the top choice, although platinum-based regimens are now the cornerstone of medical treatment for patients with poorly differentiated PNETs who are not fit for operation [19,20]. As mentioned above, 60 % of patients with poorly differentiated PNETs already developed liver metastases at the initial diagnosis. Halfdanarson et al. [21] found that 60.2 % of patients had metastatic lesions and 20.7 % had regionally advanced neoplasms at the time of diagnosis. Furthermore, tumors with a diameter > 30 mm, an ill-defined margin, low enhancement, extrapancreatic and vascular invasion, and distant and lymph node metastases were significantly related to poor differentiation and a high tumor grade [22,23], which is similar to our results. The most compelling finding of our study is that a portal
3.3. Survival analysis of the study population The median survival time was 36 months (ranging from 1 to 90 months) for all patients, 43 months (ranging from 6 to 90 months) for patients with well-differentiated PNETs, and 9.5 months (ranging from 1 to 48 months) for patients with poorly differentiated PNETs. The 5year survival rate was 84.8 % for the entire cohort, 95.1 % for patients with well-differentiated PNETs, 100 % for patients with G1 PNETs, and 16.7 % for patients with poorly differentiated PNETs. Furthermore, the Kaplan-Meier curves demonstrated that an ill-defined margin, irregular shape, poorly differentiated PNET, G3 tumor, nonfunctional status, and elevated tumor marker levels were associated with poor survival rates (log-rank P < 0.05) (Fig. 3). Moreover, aggressive behavior, such as invasion into nearby tissues and lymph node and liver metastases, and a low enhancement ratio, such as an arterial enhancement ratio < 0.84 and a portal enhancement ratio < 1.02 (log-rank P < 0.05) were also related to poor outcomes (Fig. 4).
4. Discussion Our study not only compared the imaging findings between welldifferentiated PNETs and poorly differentiated PNETs but also found positive prognostic variables that could predict the survival outcomes of patients with PNETs. Lymph node metastases and a portal enhancement 4
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Table 3 Univariate Cox regression analyses in patients with PNETs. Variables
Univariate analyses HR (95 %CI)
Age (years) ≤56 ＞56 Gender Female Male Symptom None Abnormal Tumor marker Normal Abnormal Group Well-differentiated Poorly differentiated Diameter (mm) ≤25.9 ＞25.9 Location Head/neck Body/tail Invasion of nearby tissues None Abnormal Lymph node metastases None Abnormal
Variables P value
1.00 2.21 (0.62, 7.85)
0.22
1.00 1.64 (0.46, 5.81)
0.45
1.00 2.21 (0.47, 10.43)
0.32
1.00 13.0 (3.50, 48.22)
＜0.001
1.00 24.85 (6.26, 98.64)
＜0.001
1.00 13.1 (1.66, 103.56)
0.02
1.00 2.56 (0.66, 9.95)
0.18
1.00 5.23 (1.51, 18.19)
0.009
1.00 7.78 (1.99, 30.48)
0.003
Shape Round Irregular Margin Well-defined Ill-defined Pancreatitis Normal Abnormal Texture Solid Cystic degeneration Liver metastases None Abnormal Plain ratio ≥ 0.84 < 0.84 Artery enhancement ratio ≥0.84 < 0.84 Portal enhancement ratio ≥1.02 < 1.02
Univariate analyses HR (95 %CI)
P value
1.00 8.15 (2.09, 31.84)
0.003
1.00 11.53 (2.97, 44.71)
＜0.001
1.00 2.69 (0.34, 21.33)
0.35
1.00 1.61 (0.47, 5.57)
0.45
1.00 17.17 (4.41, 66.89)
＜0.001
1.00 1.78 (0.50, 6.30)
0.37
1.00 9.31 (1.97, 44.05)
0.005
1.00 17.14 (2.16, 135.95)
0.007
HR: Hazard ratio; 95 %CI: 95 % confidence interval.
enhancement ratio less than 1.02 was correlated with poor survival outcomes in patients with PNETs. Our result is consistent with Kim’s finding that a portal enhancement ratio ≤1.1 was an independent prognostic variable for predicting worse overall survival and recurrence-free survival in patients with PNETs [11]. The enhancement patterns of PNETs have been well explored for differentiating between low and high-grade PNETs or differentiating PNETs from other pancreatic cancers [15,23,24]. The progression towards malignancy has
Table 4 Multivariate forward stepwise logistic regression analysis. Variables
HR (95 % CI)
P value
Lymph node metastases Portal enhancement ratio < 1.02
21.52 (2.15–215.13) 30.89 (1.56–610.40)
0.009 0.024
HR: Hazard ratio; 95 % CI: 95 % confidence interval.
Fig. 3. Survival analyses of different groups of patients with PNETs subdivided by (a) margin, (b) shape, (c) differentiation, (d) grade, (e) functional status, and (f) tumor marker levels. 5
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Fig. 4. Survival analyses of different groups of patients with PNETs subdivided by (a) invasion into nearby tissue, (b) lymph node metastases, (c) liver metastases, (d) portal enhancement ratio, (e) arterial enhancement ratio, and (f) overall survival.
[28] reviewed 78 patients with PNETs with 15 years of follow-up and found that the 5-years overall survival for G1 was 87.2 %, that for G2 was 73.9 %, and that for G3 was 21.7 % according to the 2010 WHO classification. The differences between our results and theirs may be due to differences in the follow-up duration. This study had a few limitations. First, this study included data from different CT machines and parameters due to the retrospective study design and long follow-up period, which may introduce confounding bias in the research. Second, we included several patients who underwent biopsy, which may have introduced some potential bias. However, the Ki67 index is the only count possible with biopsy samples that can ensure high consistency with primary lesions [29,30]. Third, we did not measure interobserver agreement because of the consensus was settled by a third radiologist. Furthermore, disagreements were uncommon due to the rich experience of the initial two radiologists in abdominal radiology. Fourth, other factors, such as systemic therapy, chemotherapy and quality and method of surgery, were not available for our study, which could introduce some bias. Finally, the quantitative factors were dichotomized, which may cause a loss of information during statistical analysis. In conclusion, lymph node metastases and a portal enhancement ratio < 1.02 were independent prognostic factors for worse overall survival outcomes in patients with PNETs. A reduced overall survival was associated with an ill-defined margin, irregular shape, poorly differentiated tumor, G3 grade, nonfunctional status, abnormal tumor marker levels, invasion into nearby tissues, lymph node and liver metastases, and lower enhancement ratio. Patients with poorly differentiated PNETs presented with more aggressive behavior and had noticeably worse survival rates than patients with well-differentiated PNETs.
been related to disorganized vessel structure and vessel dysfunction, and a lower microvessel density and a hypodense appearance may be signs of worse prognosis in patients with PNETs [24]. Furthermore, hypoenhanced PNETs have higher probabilities of synchronous liver and lymph node metastases than hyperenhanced PNETs [25]. Another study also found that the enhancement pattern on CT was pertinent for evaluating vascularity by light microscopy; lower enhancement ratio of PNETs were more likely to be poorly differentiated tumors, and patients with these tumors had worse overall survival rates [12]. A lower microvessel density was a disadvantageous prognostic variable, which was also reflected in our study. Patients with lesions with an arterial enhancement ratio < 0.84 or a portal enhancement ratio < 1.02 had worse survival probabilities than those with hypervascular tumors, which present with a hyperenhanced appearance since these tumors are derived from islet cells with high vascularization [24]. The other finding worth discussing was the association between lymph node metastases and survival outcomes. In our study, lymph node metastases were an independent risk factor for poor outcomes in the multivariable analysis. Huang et al. [26] found that the presence of lymph node and distant metastases was an independent predictor of poor prognosis. The survival time decreased significantly as the number of metastatic sites increased [27]. Kim et al. [11] suggested that both the portal enhancement ratio (≤1.1) and hepatic metastases were prognostic factors for overall survival. However, even though patients with liver metastases had a poor survival rate, these metastases were not an independent factor for overall survival in our study. Further studies that include more cases are needed to further illuminate this relationship. Patients with poorly differentiated PNETs had noticeably worse survival rates than patients with well-differentiated PNETs, with median survival times of 9.5 and 43 months and 5-year survival rates of 16.7 % and 95.1 %, respectively. Another study with 161 patients found that the median overall survival was 48.4 months among all grades of PNETs, which may be due to high proportions rate of G1 and G2 (91.9 %) [11]. Moreover, according to our study, patients with aggressive tumor behavior, such as invasion into nearby tissues and lymph node and liver metastases, were also associated with a worse prognosis. However, patients with low tumor grades, especially G1, had excellent 5-year survival rates, which could reach as high as 100 %. Ye L et al.
Declaration of Competing Interest None. Acknowledgements None. 6
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[1] M. Cives, J.R. Strosberg, Gastroenteropancreatic neuroendocrine tumors, CA Cancer J. Clin. 68 (6) (2018) 471–487. [2] A. Dasari, C. Shen, D. Halperin, et al., Trends in the incidence, prevalence, and survival outcomes in patients with neuroendocrine tumors in the United States, JAMA Oncol. 3 (10) (2017) 1335–1342. [3] J. Wu, C. Sun, E. Li, et al., Non-functional pancreatic neuroendocrine tumours: emerging trends in incidence and mortality, BMC Cancer 19 (1) (2019) 334. [4] R.V. Lloyd, R.Y. Osamura, G, K, J R, WHO Classification of Tumours of Endocrine Organs. WHO/ IARC Classification of Tumours, 4th ed., IARC Press, Lyon, France, 2017, p. 10. [5] A.D. Singhi, D.S. Klimstra, Well-differentiated pancreatic neuroendocrine tumours (PanNETs) and poorly differentiated pancreatic neuroendocrine carcinomas (PanNECs): concepts, issues and a practical diagnostic approach to high-grade (G3) cases, Histopathology 72 (1) (2018) 168–177. [6] J.H. Kim, H.W. Eun, Y.J. Kim, J.M. Lee, J.K. Han, B.I. Choi, Pancreatic neuroendocrine tumour (PNET): staging accuracy of MDCT and its diagnostic performance for the differentiation of PNET with uncommon CT findings from pancreatic adenocarcinoma, Eur. Radiol. 26 (5) (2016) 1338–1347. [7] A. Sundin, R. Arnold, E. Baudin, et al., ENETS consensus guidelines for the standards of care in neuroendocrine tumors: radiological, nuclear medicine & hybrid imaging, Neuroendocrinology 105 (3) (2017) 212–244. [8] C. Dromain, D. Deandreis, J.Y. Scoazec, et al., Imaging of neuroendocrine tumors of the pancreas, Diagn. Interv. Imaging 97 (12) (2016) 1241–1257. [9] K. Takumi, Y. Fukukura, M. Higashi, et al., Pancreatic neuroendocrine tumors: correlation between the contrast-enhanced computed tomography features and the pathological tumor grade, Eur. J. Radiol. 84 (8) (2015) 1436–1443. [10] G.A. Zamboni, M.C. Ambrosetti, C. Zivelonghi, et al., Solid non-functioning endocrine tumors of the pancreas: correlating computed tomography and pathology, HPB (Oxford) 19 (11) (2017) 986–991. [11] D.W. Kim, H.J. Kim, K.W. Kim, et al., Prognostic value of CT findings to predict survival outcomes in patients with pancreatic neuroendocrine neoplasms: a single institutional study of 161 patients, Eur. Radiol. 26 (5) (2016) 1320–1329. [12] M. Rodallec, V. Vilgrain, A. Couvelard, et al., Endocrine pancreatic tumours and helical CT: contrast enhancement is correlated with microvascular density, histoprognostic factors and survival, Pancreatology 6 (1–2) (2006) 77–85. [13] A. Gallotti, R.P. Johnston, P.A. Bonaffini, et al., Incidental neuroendocrine tumors of the pancreas: MDCT findings and features of malignancy, AJR Am. J. Roentgenol. 200 (2) (2013) 355–362. [14] C. Kim, J.H. Byun, S.M. Hong, et al., A comparison of enhancement patterns on dynamic enhanced CT and survival between patients with pancreatic neuroendocrine tumors with and without intratumoral fibrosis, Abdom. Radiol. 42 (12) (2017) 2835–2842. [15] S.K. Jeon, J.M. Lee, I. Joo, et al., Nonhypervascular pancreatic neuroendocrine tumors: differential diagnosis from pancreatic ductal adenocarcinomas at MR imaging-retrospective cross-sectional study, Radiology 284 (1) (2017) 77–87.
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Contents lists available at ScienceDirect
European Journal of Radiology journal homepage: www.elsevier.com/locate/ejrad
Research article
The prognostic value of multidetector CT features in predicting overall survival outcomes in patients with pancreatic neuroendocrine tumors
T
Bo Yanga,b,1, Hai-Yan Chena,1, Xue-Yan Zhanga,c, Yao Pana, Yuan-Fei Lua, Ri-Sheng Yua,* a
Department of Radiology, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China Department of Radiology, Zhejiang Prison Center Hospital (Zhejiang Youth Hospital), Hangzhou, China c Department of Radiology, Institute of Occupational Diseases, Zhejiang Academy of Medical Sciences, Hangzhou, China b
A R T I C LE I N FO
A B S T R A C T
Keywords: Neuroendocrine tumors Pancreas Computed tomography Survival analysis
Purpose: To assess the prognostic value of multidetector CT in predicting overall survival outcomes in patients with pancreatic neuroendocrine tumors (PNETs). Method: Seventy-one patients pathologically diagnosed with PNETs were retrospectively included. The clinical and imaging information was evaluated by two radiologists. The difference between well-differentiated and poorly differentiated PNETs was analyzed. Cox proportional hazards models were created to determine the risk factors for overall survival. Kaplan-Meier survival analyses with log-rank tests were used among different subgroups of patients with PNETs. Results: In the whole cohort, the median survival was 36 months, and the 5-year survival rate was 84.8 %. Patients with poorly differentiated PNETs were more likely to present with symptoms, abnormal tumor markers, larger diameters, irregular shapes, ill-defined margins, invasion into nearby tissues, liver and lymph node metastases, and lower enhancement ratio than those with well-differentiated PNETs (P < 0.05). In the multivariate analysis, lymph node metastases (hazard ratio: 21.52, P = 0.009) and a portal enhancement ratio less than 1.02 (hazard ratio: 30.89, P = 0.024) were significant factors for overall survival. Overall survival decreased with an ill-defined margin, irregular shape, poor differentiation, grade 3 disease, nonfunctional status, abnormal tumor marker levels, invasion into nearby tissues, lymph node and liver metastases, and lower enhancement ratio (logrank P < 0.05). Conclusions: Poorly differentiated PNETs were more aggressiveness than well-differentiated PNETs. Lymph node metastases and a portal enhancement ratio < 1.02 were independent prognostic factors for worse overall survival outcomes in patients with PNETs.
1. Introduction Pancreatic neuroendocrine tumors (PNETs) are considered the second most common malignancy of the pancreas, accounting for up to 1–3 % of all pancreatic cancers [1,2]. PNETs are a group of heterogeneous lesions with diverse radiological, pathological and clinical features, stemming from neuroendocrine cells or the islets of Langerhans of the pancreas [1]. Because of their ability to secrete hormones, PNETs are stratified into functional PNETs or nonfunctional PNETs [3]. According to the 2017 WHO classification, PNETs can be divided into well-differentiated and poorly differentiated PNETs (also named as
neuroendocrine carcinomas), and the former is further subdivided into grade 1 (G1), grade 2 (G2) and well-differentiated grade 3 (G3) [4]. These two groups of tumors range from indolent to highly aggressive in nature, resulting in many differences in imaging and clinical presentation, survival outcomes, and genetic underpinnings [5]. In a larger clinical population study of NETs, the median five-year overall survival (OS) rate varied with grade, age, stage, primary location, and diagnostic time [2]. PNETs stage is determined by tumor diameter, local invasion, and lymph node and distant metastases, which can be measured through multidetector CT [6]. The sensitivity and specificity of CT in detecting PNETs in patients are 61–93 % and
Abbreviations: PNETs, pancreatic neuroendocrine tumors; G1/2/3, grade 1/2/3; ROC, receiver operating characteristic; HR, hazard ratio; CI, confidence interval; AUC, area under the curve ⁎ Corresponding author at: Department of Radiology, Second Affiliated Hospital, Zhejiang University School of Medicine. Jiefang Road 88#, Hangzhou, 310009, China. E-mail address: [email protected] (R.-S. Yu). 1 Bo Yang and Hai-Yan Chen contributed equally and should be considered as co-first authors. https://doi.org/10.1016/j.ejrad.2020.108847 Received 17 September 2019; Received in revised form 3 December 2019; Accepted 18 January 2020 0720-048X/ © 2020 Published by Elsevier B.V.
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64 (Siemens Medical Systems, Erlangen, Germany, n = 41) and TOSHIBA Aquilion 16 (Toshiba Medical Systems Corporation, Tochigi ken, Japan, n = 30). Patients initially underwent plain CT scans; then, nonionic contrast medium (iopromide; Ultravist 370, Bayer Schering Pharma, Berlin, Germany) was intravenously injected at a rate of 3 mL/ s. Arterial phase and portal venous phase images were acquired at 25−35 s and 60 s, respectively. Other parameters were as follows: voltage: 120 kV; maximum tube current: 250 mAs and 150–350 mAs for the arterial phase and portal venous phase, respectively; slice thickness: 3 mm; slice collimation: 0.6 mm; and field of view (FOV): 380 × 380.
71–100 %, respectively [7]. According to previous studies, the typical performance of CT in identifying PNETs relies on a well-demarcated margin, hypervascular enhanced or delayed rim enhancement pattern, lack of dilation of the pancreatic duct and the presence of a hemorrhage or calcifications [8–10]. Some tend to evaluate prognostic factors through clinical evaluations, while others try to use imaging features to predict the outcomes [11]. However, few studies have focused on the CT features associated with survival outcomes or recurrence-free survival, and the results in the existing literature vary [11–14]. The recurrence-free survival of patients with PNETs in our study was very rare, and thus, firm conclusions could not be drawn. Hence, our study aimed to assess only the prognostic value of multidetector CT in predicting OS outcomes in patients with PNETs.
2.3. Imaging analysis The imaging features were assessed by two radiologists (with 8 and 6 years of experience in abdominal radiology) who were blinded to the pathological outcomes. Disagreements were settled by consensus after consulting a third radiologist with 31 years of experience in pancreatic radiology. Clinical characteristics such as age, sex, presence of symptoms related to PNETs, tumor marker levels (carbohydrate antigen (CA) 19-9, carcinoembryonic antigen (CEA), CA 125), functional tumor status and survival outcomes were included. OS was defined from the date of biopsy or surgery to the date of patient's death. The data were censored if the patient was alive at the end of the follow-up period (June 1, 2019) or if the patient was lost to follow up without reason. General imaging features such as location (head/neck vs body/tail), maximum diameter on the axial images, shape (round vs irregular), the presence of calcifications or cystic degeneration, tumor margin (well-defined vs ill-defined), enhancement intensity, dilation of the pancreatic duct (≥3 mm [15]), pancreatic atrophy and pancreatitis were collected. Enhancement intensity was expressed by the plain/arterial/portal enhancement ratio. For example, the arterial enhancement ratio was defined as the HU of the lesion/HU of the nearby pancreatic parenchyma measured on the arterial phase, and the plain and portal enhancement ratios had similar definitions [11], and the equation of each phase of contrast was HU of the lesion as follows: enhancement ratio = HU of the banckground pancreas . The imaging features that conveyed aggressive behavior such as invasion into the nearby tissues, lymph node metastases (short axis larger than 10 mm or necrosis of any size [16,17]) and liver metastases (multiple peripheral enhanced or hypervascular enhanced nodules [18]) were also collected.
2. Materials and methods 2.1. Study population Our institutional review board has approved this retrospective study, and the requirement for informed consent was waived. Patients pathologically diagnosed with PNETs at The Second Affiliated Hospital of Zhejiang University School of Medicine from January 1, 2012 up to June 1, 2019, were retrospectively evaluated. The inclusion criteria were as follows: 1) with detailed pathological and follow up information; 2) dynamic enhanced multidetector CT within 2 months prior to surgery or biopsy; 3) no local treatment or chemotherapy before the operation. The exclusion criteria were as follows: 1) severe pancreatic atrophy when measured in CT Hounsfield units (HU) due to a lack of a region of interest (n = 3); 2) invisible lesions (n = 9); 3) no integrated imaging data (n = 6); 4) survival data was incomplete (n = 4). Finally, we included 71 patients in our study (Fig. 1). Five patients had multiple PNETs, and the largest lesion was selected for further evaluation. Every sample was reviewed separately by two pathologists, and the Ki67 index value of 50 % was used to distinguish well-differentiated from poorly differentiated PNETs [7]. Well-differentiated PNETs were defined as those with a Ki67 index < 50 %, while poorly differentiated PNETs were defined as those with a Ki67 index > 50 %. 2.2. Image acquisition
2.4. Statistical analysis Before the examination, all patients were asked to abstain from solid food for 4−6 h. Two kinds of CT scanners were used: Siemens Emotion
Quantitative data are manifested as the mean ± standard deviation
Fig. 1. Flow chart depicting the selection of patients with PNETs. 2
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% vs 18 %), ill-defined margin (70 % vs 11.5 %), invasion into nearby tissues (70 % vs 9.8 %), liver metastases (60 % vs 8.2 %), lymph node metastases (30 % vs 4.9 %), a lower arterial enhancement ratio (0.71 vs 1.20), and a lower portal enhancement ratio (0.76 vs 1.24) than those with well-differentiated PNETs. These differences were statistically significant (P < 0.05). All functional tumors were well-differentiated PNETs. There was no significant difference in sex, age, location, calcification, texture, pancreatic atrophy, pancreatitis, pancreatic duct dilation or plain ratio between patients with well-differentiated PNETs and those with poorly differentiated PNETs (P ≥ 0.05) (Fig. 2).
or median (25–75 th percentile) based on their distribution, and qualitative data are expressed as frequencies (percentages). Student’s t-tests or Mann-Whitney U tests were used for continuous variables, while Fisher’s exact tests or χ2 tests were used to compare categorical data between well-differentiated PNETs and poorly differentiated PNETs. Quantitative variables were dichotomized for Cox regression analysis, and receiver operating characteristic (ROC) curves were created to determine the best cutoff values. Thus, a univariate Cox proportional hazard model was created to identify the risk factors for prognosis. The factors with a p value < 0.1 were included in the multivariate Cox regression analysis to determine the final independent prognostic risk factors. A Kaplan-Meier survival analysis with the log-rank test was used to analyze the survival outcomes among different subgroups. P < 0.05 was considered statistically significant. ROC curves were created by Medcalc software V.18 (Mariakerke, Belgium), while other analyses were performed by Stata 14.0 (Stata Corporation, College Station, Texas, USA).
3.2. Univariate and multivariate Cox regression analysis of the study population Before the univariate Cox analysis, quantitative variables, including age, diameter, plain ratio, arterial enhancement ratio and portal enhancement ratio, were dichotomized; the area under the curve (AUC), 95 % confidence interval (CI), best cutoff values, sensitivity and specificity are shown in Table 2. Furthermore, a univariate Cox analysis was performed, and the results summarized in Table 3. Abnormal tumor marker levels (hazard ratio (HR): 13.0), poorly differentiated PNETs (HR: 24.85), diameter larger than 25.9 mm (HR: 13.1), irregular shape (HR: 8.15), ill-defined margin (HR: 11.53), invasion into nearby tissues (HR: 5.23), lymph node metastases (HR: 7.78), liver metastases (HR: 17.17), arterial enhancement ratio < 0.84 (HR: 9.31), and portal enhancement ratio < 1.02 (HR: 17.14) were factors that might impact survival outcomes. We then entered these variables along with those with P < 0.10 into the multivariate Cox regression analysis. The results are presented in Table 4 and suggest that lymph node metastases (HR: 21.52) and a portal enhancement ratio < 1.02 (HR: 30.89) were independent prognostic factors related to poor outcomes.
3. Results 3.1. Comparison of clinical and imaging features between welldifferentiated PNETs and poorly differentiated PNETs The whole population and subgroup information are summarized in Table 1. A total of 71 patients were included, with an average age of 52.34 ± 13.10, and 50.7 % of the patients were female. A total of 66.2 % of the patients presented with symptoms; all of the functional lesions were insulinomas, and the chief complaint was hypoglycemia. According to the 2017 WHO classification, 61 of these tumors were welldifferentiated PNETs, and 10 were poorly differentiated PNETs. Patients with poorly differentiated PNETs were more likely to present with symptoms (100 % vs 60.7 %), elevated tumor marker levels (50 % vs 11.5 %), larger diameter (40.0 mm vs 23.4 mm), irregular shape (80
Table 1 The baseline demographic and general radiologic characteristics of all patients in the study and a comparison between well-differentiated PNETs and poorly differentiated PNETs.
Gender Male Female Age Median survival time(m) Symptoms Tumor marker Functional Location Head/neck Body/tail Diameter(mm) Shape Round Irregular Margin Well-defined Ill-defined Calcification Texture Solid Cystic degeneration Pancreatic atrophy Pancreatic duct dilation Pancreatitis Invasion of nearby tissues Liver metastases Lymph node metastases Plain ratio Artery enhancement ratio Portal enhancement ratio
Total (n = 71)
Well-differentiated (n = 61)
Poorly differentiated (n = 10)
35(49.3) 36(50.7) 52.34 ± 13.10 36 47(66.2) 12(16.9) 20(28.2)
29(47.5) 32(52.5) 51.64 ± 13.23 43 37(60.7) 7(11.5) 20(32.8)
6(60) 4(40) 56.60 ± 12.05 9.5 10(100) 5(50) 0(0)
35(49.3) 36(50.7) 24.4(12.4–48.7)
31(50.8) 30(49.2) 23.4(11.8–40.95)
4(40) 6(60) 40.0(25.45–60.9)
52(73.2) 19(26.8)
50(82) 11(18)
2(20) 8(80)
57(80.3) 14(19.7) 15(21.1)
54(88.5) 7(11.5) 15(24.6)
3(30) 7(70) 0(0)
44(62) 27(38) 7(9.9) 7(9.9) 3(4.2) 13(18.3) 11(15.5) 6(8.5) 0.86(0.74–1.0) 1.13 ± 0.51 1.17 ± 0.44
39(63.9) 22(36.1) 5(8.2) 7(11.5) 1(1.6) 6(9.8) 5(8.2) 3(4.9) 0.85(0.76-0.97) 1.20 ± 0.50 1.24 ± 0.44
5(50) 5(50) 2(20) 0(0) 2(20) 7(70) 6(60) 3(30) 0.96(0.73–1.19) 0.71 ± 0.31 0.76 ± 0.17
P-value 0.349
0.27 < 0.001 0.011 0.01 0.028 0.386
0.036 < 0.001
< 0.001
3
0.077 0.4
0.254 0.328 0.05 < 0.001 0.001 0.033 0.432 0.004 ＜0.001
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Fig. 2. (a–c): A 50-year-old female with a well-differentiated PNET within the tail of the pancreas. 2(a). A plain CT scan shows a slightly hypodense nodule with a round shape (white arrow). 2(b–c). The arterial and portal phase present a well-defined lesion (white arrow) with obvious enhancement compared to the pancreatic parenchyma. (d–f): A 38-year-old male with a poorly differentiated G3 PNET within the tail of the pancreas. 2(d). A plain CT scan presents with a slightly hypodense lesion with an irregular shape (white arrow). 2(e–f). The arterial and portal phases show a lesion with obvious hypoenhancement compared to the adjacent pancreas that involves the hilum of the spleen, resulting in infarction in the distal spleen (white arrow). There is also a large metastatic lymph node with a hypoenhanced appearance between the pancreas and left kidney (white arrowhead). Table 2 ROC analysis for cutoff values of age, diameter, plain ratio, artery and portal enhancement ratio in differentiating patients with PNETs. Variables
AUC* (95%CI*)
Cutoff
Sensitivity (%)
Specificity (%)
Age (years) Diameter(mm) Plain ratio Artery enhancement ratio Portal enhancement ratio
0.557 0.779 0.518 0.764 0.852
> 56 ＞25.9 < 0.84 ＜0.84 ＜1.02
60 90 60 73.8 68.9
60.7 63.9 59 90 100
(0.435-0.675) (0.664-0.869) (0.396-0.638) (0.648-0.857) (0.748-0.925)
* AUC: area under the curve; 95 %CI: 95 % confidence interval.
ratio less than 1.02 were strong independent prognostic factors for worse outcomes in the multivariate Cox regression analysis, according to our study. Moreover, poorly differentiated PNETs were more aggressive and were more prone to result in invasion into nearby tissues and lymph node and hepatic metastases than low-grade PNETs; these factors caused a short median survival rate. Grade and differentiation are often confused. Grade is mostly discussed and could be an indicator of the aggressive behavior of PNETs. However, differentiation is pertinent for the morphological conformity in the neuroendocrine cells of PNETs, which may more truly reflect biological behavior than grade [5]. The treatment for PNETs also differs. Surgery is always the top choice, although platinum-based regimens are now the cornerstone of medical treatment for patients with poorly differentiated PNETs who are not fit for operation [19,20]. As mentioned above, 60 % of patients with poorly differentiated PNETs already developed liver metastases at the initial diagnosis. Halfdanarson et al. [21] found that 60.2 % of patients had metastatic lesions and 20.7 % had regionally advanced neoplasms at the time of diagnosis. Furthermore, tumors with a diameter > 30 mm, an ill-defined margin, low enhancement, extrapancreatic and vascular invasion, and distant and lymph node metastases were significantly related to poor differentiation and a high tumor grade [22,23], which is similar to our results. The most compelling finding of our study is that a portal
3.3. Survival analysis of the study population The median survival time was 36 months (ranging from 1 to 90 months) for all patients, 43 months (ranging from 6 to 90 months) for patients with well-differentiated PNETs, and 9.5 months (ranging from 1 to 48 months) for patients with poorly differentiated PNETs. The 5year survival rate was 84.8 % for the entire cohort, 95.1 % for patients with well-differentiated PNETs, 100 % for patients with G1 PNETs, and 16.7 % for patients with poorly differentiated PNETs. Furthermore, the Kaplan-Meier curves demonstrated that an ill-defined margin, irregular shape, poorly differentiated PNET, G3 tumor, nonfunctional status, and elevated tumor marker levels were associated with poor survival rates (log-rank P < 0.05) (Fig. 3). Moreover, aggressive behavior, such as invasion into nearby tissues and lymph node and liver metastases, and a low enhancement ratio, such as an arterial enhancement ratio < 0.84 and a portal enhancement ratio < 1.02 (log-rank P < 0.05) were also related to poor outcomes (Fig. 4).
4. Discussion Our study not only compared the imaging findings between welldifferentiated PNETs and poorly differentiated PNETs but also found positive prognostic variables that could predict the survival outcomes of patients with PNETs. Lymph node metastases and a portal enhancement 4
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Table 3 Univariate Cox regression analyses in patients with PNETs. Variables
Univariate analyses HR (95 %CI)
Age (years) ≤56 ＞56 Gender Female Male Symptom None Abnormal Tumor marker Normal Abnormal Group Well-differentiated Poorly differentiated Diameter (mm) ≤25.9 ＞25.9 Location Head/neck Body/tail Invasion of nearby tissues None Abnormal Lymph node metastases None Abnormal
Variables P value
1.00 2.21 (0.62, 7.85)
0.22
1.00 1.64 (0.46, 5.81)
0.45
1.00 2.21 (0.47, 10.43)
0.32
1.00 13.0 (3.50, 48.22)
＜0.001
1.00 24.85 (6.26, 98.64)
＜0.001
1.00 13.1 (1.66, 103.56)
0.02
1.00 2.56 (0.66, 9.95)
0.18
1.00 5.23 (1.51, 18.19)
0.009
1.00 7.78 (1.99, 30.48)
0.003
Shape Round Irregular Margin Well-defined Ill-defined Pancreatitis Normal Abnormal Texture Solid Cystic degeneration Liver metastases None Abnormal Plain ratio ≥ 0.84 < 0.84 Artery enhancement ratio ≥0.84 < 0.84 Portal enhancement ratio ≥1.02 < 1.02
Univariate analyses HR (95 %CI)
P value
1.00 8.15 (2.09, 31.84)
0.003
1.00 11.53 (2.97, 44.71)
＜0.001
1.00 2.69 (0.34, 21.33)
0.35
1.00 1.61 (0.47, 5.57)
0.45
1.00 17.17 (4.41, 66.89)
＜0.001
1.00 1.78 (0.50, 6.30)
0.37
1.00 9.31 (1.97, 44.05)
0.005
1.00 17.14 (2.16, 135.95)
0.007
HR: Hazard ratio; 95 %CI: 95 % confidence interval.
enhancement ratio less than 1.02 was correlated with poor survival outcomes in patients with PNETs. Our result is consistent with Kim’s finding that a portal enhancement ratio ≤1.1 was an independent prognostic variable for predicting worse overall survival and recurrence-free survival in patients with PNETs [11]. The enhancement patterns of PNETs have been well explored for differentiating between low and high-grade PNETs or differentiating PNETs from other pancreatic cancers [15,23,24]. The progression towards malignancy has
Table 4 Multivariate forward stepwise logistic regression analysis. Variables
HR (95 % CI)
P value
Lymph node metastases Portal enhancement ratio < 1.02
21.52 (2.15–215.13) 30.89 (1.56–610.40)
0.009 0.024
HR: Hazard ratio; 95 % CI: 95 % confidence interval.
Fig. 3. Survival analyses of different groups of patients with PNETs subdivided by (a) margin, (b) shape, (c) differentiation, (d) grade, (e) functional status, and (f) tumor marker levels. 5
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Fig. 4. Survival analyses of different groups of patients with PNETs subdivided by (a) invasion into nearby tissue, (b) lymph node metastases, (c) liver metastases, (d) portal enhancement ratio, (e) arterial enhancement ratio, and (f) overall survival.
[28] reviewed 78 patients with PNETs with 15 years of follow-up and found that the 5-years overall survival for G1 was 87.2 %, that for G2 was 73.9 %, and that for G3 was 21.7 % according to the 2010 WHO classification. The differences between our results and theirs may be due to differences in the follow-up duration. This study had a few limitations. First, this study included data from different CT machines and parameters due to the retrospective study design and long follow-up period, which may introduce confounding bias in the research. Second, we included several patients who underwent biopsy, which may have introduced some potential bias. However, the Ki67 index is the only count possible with biopsy samples that can ensure high consistency with primary lesions [29,30]. Third, we did not measure interobserver agreement because of the consensus was settled by a third radiologist. Furthermore, disagreements were uncommon due to the rich experience of the initial two radiologists in abdominal radiology. Fourth, other factors, such as systemic therapy, chemotherapy and quality and method of surgery, were not available for our study, which could introduce some bias. Finally, the quantitative factors were dichotomized, which may cause a loss of information during statistical analysis. In conclusion, lymph node metastases and a portal enhancement ratio < 1.02 were independent prognostic factors for worse overall survival outcomes in patients with PNETs. A reduced overall survival was associated with an ill-defined margin, irregular shape, poorly differentiated tumor, G3 grade, nonfunctional status, abnormal tumor marker levels, invasion into nearby tissues, lymph node and liver metastases, and lower enhancement ratio. Patients with poorly differentiated PNETs presented with more aggressive behavior and had noticeably worse survival rates than patients with well-differentiated PNETs.
been related to disorganized vessel structure and vessel dysfunction, and a lower microvessel density and a hypodense appearance may be signs of worse prognosis in patients with PNETs [24]. Furthermore, hypoenhanced PNETs have higher probabilities of synchronous liver and lymph node metastases than hyperenhanced PNETs [25]. Another study also found that the enhancement pattern on CT was pertinent for evaluating vascularity by light microscopy; lower enhancement ratio of PNETs were more likely to be poorly differentiated tumors, and patients with these tumors had worse overall survival rates [12]. A lower microvessel density was a disadvantageous prognostic variable, which was also reflected in our study. Patients with lesions with an arterial enhancement ratio < 0.84 or a portal enhancement ratio < 1.02 had worse survival probabilities than those with hypervascular tumors, which present with a hyperenhanced appearance since these tumors are derived from islet cells with high vascularization [24]. The other finding worth discussing was the association between lymph node metastases and survival outcomes. In our study, lymph node metastases were an independent risk factor for poor outcomes in the multivariable analysis. Huang et al. [26] found that the presence of lymph node and distant metastases was an independent predictor of poor prognosis. The survival time decreased significantly as the number of metastatic sites increased [27]. Kim et al. [11] suggested that both the portal enhancement ratio (≤1.1) and hepatic metastases were prognostic factors for overall survival. However, even though patients with liver metastases had a poor survival rate, these metastases were not an independent factor for overall survival in our study. Further studies that include more cases are needed to further illuminate this relationship. Patients with poorly differentiated PNETs had noticeably worse survival rates than patients with well-differentiated PNETs, with median survival times of 9.5 and 43 months and 5-year survival rates of 16.7 % and 95.1 %, respectively. Another study with 161 patients found that the median overall survival was 48.4 months among all grades of PNETs, which may be due to high proportions rate of G1 and G2 (91.9 %) [11]. Moreover, according to our study, patients with aggressive tumor behavior, such as invasion into nearby tissues and lymph node and liver metastases, were also associated with a worse prognosis. However, patients with low tumor grades, especially G1, had excellent 5-year survival rates, which could reach as high as 100 %. Ye L et al.
Declaration of Competing Interest None. Acknowledgements None. 6
European Journal of Radiology 124 (2020) 108847
B. Yang, et al.
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