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European Journal of Gynaecological Oncology  2020, Vol. 41 Issue (3): 408-414    DOI: 10.31083/j.ejgo.2020.03.5312
Original Research Previous articles | Next articles
Sentinel lymph node mapping with carbon nanoparticles in endometrial cancer
J.Y. Chen1, Z.Q. Wang1, S.C. Liang1, H.Y. Hou1, D.B. Chen1, J.L. Wang1()
1Gynecology Department. Peking University people’s Hospital, Beijing, China
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Aim: A retrospective study was conducted to explore the value of sentinel lymph node (SLN) mapping with carbon nanoparticles (CNP) in endometrial cancer patients. Methods: Seventy-six endometrial cancer patients who underwent sentinel lymph node mapping with or without systemic pelvic lymphadenectomy were involved in this study. All patients received cervical injection of carbon nanoparticles. The detection frequency for sentinel lymph nodes was calculated for all 76 patients, while the sensitivity and negative predictive value for metastasis were calculated for patients who underwent additional systemic pelvic lymphadenectomy (n=43). Clinical factors associated with sentinel lymph node detection were also evaluated. Results: The overall and bilateral detection frequencies were 71.1% (54/76) and 61.1% (33/54), respectively. A total of 291 sentinel lymph nodes were removed from 54 patients, with the median number removed per patient being 4 (range 3-7). sentinel lymph nodes were mostly located in the external lilac (45.7%) and obturator (41.2%) regions. Fifteen positive lymph nodes including 6 positive sentinel lymph nodes were found in 5 patients. Two of the five patients failed sentinel lymph node mapping but showed positive lymph nodes after systemic pelvic lymphadenectomy. The sensitivity and negative predictive value of sentinel lymph node mapping were therefore both 100%. Conclusion: The detection frequency of sentinel lymph node mapping with carbon nanoparticles in endometrial cancer patients was not as high as for some other cancer types. However, the accuracy of this method was high despite the relatively low detection frequency. More research is needed to improve sentinel lymph node mapping in endometrial cancer patients.

Key words:  Sentinel lymph node      Endometrial cancer      Carbon nanoparticles     
Submitted:  30 June 2019      Accepted:  19 September 2019      Published:  15 June 2020     
Fund: 2015BAI13B06/National Key Technology Research and Development Program of the Ministry of Science and Technology of China
*Corresponding Author(s):  J.L. Wang     E-mail:

Cite this article: 

J.Y. Chen, Z.Q. Wang, S.C. Liang, H.Y. Hou, D.B. Chen, J.L. Wang. Sentinel lymph node mapping with carbon nanoparticles in endometrial cancer. European Journal of Gynaecological Oncology, 2020, 41(3): 408-414.

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Figure 1.   - The black-stained SLNs with CNP injection (as indicated by the black arrows). a. The CNP-labeled lymph nodes between external and internal lilac artery. b. The CNP-labeled lymph nodes that were resected separately.

Table 1  - Clinical characteristics of patients
Total (n, %)
Pathology type
Atypical hyperplasia 4 (5.3%)
Endometrioid 67 (88.2%)
Mucinous 2 (2.6%)
Serous 2 (2.6%)
Mixed 1 (1.3%)
Grade of endometrioid cancer
1 29 (38.2%)
2 26 (34.2%)
3 12 (15.8%)
FIGO stage
0 [atypical hyperplasia] 4 (5.3%)
I 62 (81.6%)
II 1 (1.3%)
III 8 (10.5%)
IV 1 (1.3%)
Present 3 (3.9%)
Absent 73 (96.1%)
Myometrial invasion
< 50% 67 (88.2%)
> 50% 9 (11.8%)
Parametrial involvement
Present 10 (13.2%)
Absent 66 (86.8%)
Surgery (*TLH + BSO +)
SLNB 33 (43.4%)
SLNB + PLND 9 (11.8%)
SLNB + PLND + PALND 34 (44.7%)
Table 2  - Detection rate and accuracy
Detection rate
Overall 71.1% (54/76)
Bilateral 61.1% (33/54)
Unilateral 38.9% (21/54)
Number of SLNs
Total 291.0
Median 4.0 (3.0~7.0)
Number of PLNs
Total 1184.0
Median 27.0 (19.0~35.0)
Number of Positive Nodes
Total 16.0
SLNs 6.0
non-SLNs 10.0
Accuracy PLNs (Cases)
SLNs + 3 0
(Cases) 0 25
S 100.0%
NPV 100.0%
Table 3  - The characteristics of the 5 patients with nodal metastasis
Characteristics Case 1 Case 2 Case 3 Case 4 Case 5
Age, y 57 54 64 75 78
Pathology type Endometrioid Endometrioid Endometrioid Serous Serous
Grade 3 3 3 3 3
LVSI Yes Yes No Yes No
Deep myometrial invasion Yes Yes Yes Yes No
Parametiral involvement No No No No No
SLNB* Yes Yes Yes Yes Yes
PLND* Yes Yes Yes Yes Yes
PALND* Yes No Yes Yes Yes
Number of SLNs 8 0 0 3 4
Number of positive SLNs 2 0 0 1 3
Number of positive non-SLNs 5 2 2 0 0
Table 4  - The distribution of SLNs (Total number = 291.0)
Region Number (n, %)
External iliac 133.0 (45.7)
Obturator 120.0 (41.2)
Common iliac 19.0 (6.5)
Internal lilac 8.0 (2.7)
Inguinal 2.0 (0.7)
sacro anterior 3.0 (1.0)
para-aortic 3.0 (1.0)
inferior vena cava 3.0 (1.0)
Table 5  - The relevant factors might affect the success rate of SLN mapping
Detected Cases (n)
Fail detection
*Detection rate (%) Confidence Intervals (95%) P value
Successful Fail Lower Upper
Pathology Type 0.284 7.804 1.000
Endometriod 47 20 70.1
Non-endometriod 7 2 77.8
FIGO Stage 0.142 2.228 0.462
0 / I 48 18 72.7
II / III / IV 6 4 60.0
BMI* 0.368 2.882 0.956
< 24.0 45 14 76.3
≥ 24.0 9 8 52.9
LVSI* 0.220 4.036 1.000
Present 7 3 70.0
Absent 47 19 71.2
Deep Myometrial Invasion 0.284 7.804 1.000
Present 7 2 77.8
Absent 47 20 70.1
Parametrial Extension 0.992 1.130 0.552
Present 3 0 100.0
Absent 51 22 69.9
Surgical cases 0.396 2.989 0.870
≤ 30 21 9 70.0
>30 33 13 71.7
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