Imaging evaluation of para-aortic lymph nodes in cervical cancer

Abstract

Background

In recent years, much literature has reported the diagnostic value of computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET)-CT in para-aortic lymph node metastasis of cervical cancer.

Purpose

To compare and analyze the para-aortic lymph node presentations found in cervical cancer on different images in order to determine the best precise imaging method for identifying metastatic lymph nodes.

Material and Methods

PubMed, Web of Science, MEDLINE, and other databases were searched for the non-invasive detection of metastatic lymph nodes for a comprehensive comparison.

Results

Positive lymph nodes on CT are significantly related to the following factors: short axis ≥10 mm; and round or central necrosis. Positive lymph nodes on MRI are significantly related to the following factors: short axis ≥8 mm; inhomogeneous signal intensity; morphology: round, irregular edge, extracapsular invasion, central necrosis, loss of lymph node structure, burrs, or lobes; and ADC value decreases, combined with local actuality. On PET-CT examination, when the short axis of the lymph node is >5 mm, the SUV is >2.5, or the FDG uptake is greater than that of the surrounding tissue, it is a metastatic lymph node.

Conclusion

In conclusion, different imaging techniques show metastatic lymph nodes in different ways. Combining the patient's medical history with the symptoms of the aforementioned lymph nodes, together with one or more imaging techniques, is important to diagnose para-aortic lymph nodes in cervical cancer.

Keywords

Cervical cancer computed tomography magnetic resonance imaging positron emission tomography para-aortic lymph node

Background

Cervical cancer is one of the most common gynecological malignant tumors in the world, ranking fourth after breast, colorectal, and lung cancers. GLOBOCAN 2020 estimates that there are approximately 604,000 new cases of cervical cancer worldwide and 342,000 deaths annually. Most new cases and deaths (approximately 85% and 90%, respectively) occur in low- and middle-income countries, and it is the third most common cancer in women (1). In China, there were an estimated 110,000 new cases and 59,000 deaths in 2020 (2).

The International Federation of Gynaecology and Obstetrics (FIGO) is the worldwide recognized system for the staging and treatment of cervical cancer. In the 2018 FIGO systematic staging, imaging and pathological assessments were included. Cervical cancer undergoes strict clinical staging based on a gynecological examination and newly added stage IIIC1 tumors with pelvic lymph node involvement and IIIC2 tumors with para-aortic lymph node (PALN) involvement (3). PALN metastasis is a poor prognostic factor for cervical cancer (4). For patients without PALN metastases, the median survival time was 76.9 months, while the median survival time for patients with positive PALN was 21 months (5). Patients with the para-aortic node-positive disease had poor survival compared with patients with para-aortic node-negative disease. PALN status at initial assessment is a major prognostic factor and a critical point in treatment strategy because it defines the extent of the radiation field. Despite the continuous improvement of methodology, lymph node size is still an important indicator for an imaging diagnosis of metastatic lymph nodes. Morphology, density, signal, enhancement features, ADC value, SUV value, and radiomics have been continuously applied in the diagnosis of metastatic lymph nodes. But there is no broad consensus. None of the currently available imaging modalities has proven sensitive enough to detect para-aortic metastases in patients with locally advanced cancer. PALNs must always be evaluated in patients with locally advanced cervical cancer with positive pelvic lymph nodes, tumors >2 cm, or common iliac lymph node metastases (6).

Imaging modalities used to evaluate PALNs in cervical cancer include computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET) (7). MRI and CT have been widely used for the detection of lymph node metastases, mostly based on the assessment of lymph node size and/or morphological information. Diffusion-weighted imaging (DWI) in MRI is a non-invasive functional imaging technique that provides structural information by obtaining the diffusion properties of tissue through the apparent diffusion coefficient (ADC). PET-CT can non-invasively assess metastatic lymph nodes with metabolic activity not compromised by using morphologic size criteria (8). In recent years, many studies have described the usefulness of different imaging modalities in differentiating metastatic and non-metastatic lymph nodes. The aim of the present article was to summarize the imaging manifestations of PALN metastasis in cervical cancer through this literature.

Material and Methods

Document retrieval

This article searched PubMed, Web of Science, MEDLINE, and other databases for relevant studies using the terms (“cervical cancer,” “para-aortic lymph nodes,” “computed tomography” or “CT,” “magnetic resonance imaging” or “MRI,” “positron emission tomography” or “PET,” “diffusion-weighted imaging” or “DWI”). The flow chart of the retrieval process is shown in Fig. 1.

Fig. 1.

The flow chart of the article screening procedure.

Inclusion and exclusion criteria

The inclusion criteria were as follows: (i) human body research; (ii) available data (sensitivity, specificity, and accuracy); (iii) clear diagnostic criteria; and (iv) lymph nodes metastasis confirmed by surgery or biopsy. The exclusion criteria were as follows: (i) animal experiment; (ii) poor adaptability of reported data; and (iii) lack of evidence confirmed by pathological examination.

Data extraction

The authors independently reviewed the retrieved papers. The key information of each qualified paper was extracted according to the above inclusion and exclusion criteria (e.g. study design, FIGO stage, first author name, year of publication, lymph node size, morphology, density, signal, enhancement characteristics, ADC value, SUV value, etc.).

Results

After careful review, a total of 33 papers were included in this study. Of these, nine papers reported CT findings, 12 studies reported MRI findings, and 12 studies reported PET or PET/CT findings.

Radiographic findings of abdominal lymph node metastasis

In the abdomen, the upper limit of the maximum short-axis diameter of normal lymph nodes is in the range of 6–10 mm (9,10). The maximum axial diameter of a normal retroperitoneal abdominal lymph node is 10 mm (11). Koh et al. (12) recommended a size threshold of 10 mm for abdominal retroperitoneal lymph nodes. However, the size criteria applied may vary from cancer to cancer. For example, in testicular cancer, 8 mm of the retroperitoneal abdominal lymph node is considered “suspicious” (13). There are studies on PALNs of patients with pancreatic cancer. When lymph nodes with a diameter ≥10 mm are considered metastatic lymph nodes, the accuracy of CT diagnosis is 72.5%, and that of MRI diagnosis is 88.4%. When FDG uptake exceeds that of adjacent normal tissues, it is considered to be metastatic lymph nodes. The diagnostic accuracy of PET-CT was 90% (14). In general, there are differences in the imaging diagnosis of abdominal lymph nodes in different cancers reported in the literature.

CT

CT, which uses precisely collimated X-ray beams, gamma rays, ultrasonic waves, and so on, together with a highly sensitive detector, makes a cross-sectional scan around a certain part of the human body one by one. It has the characteristics of fast scanning time and clear images and can be used for the inspection of various diseases. CT is also widely used for the initial diagnosis of lymph node metastasis and distant spread. Lymph node size is widely used to differentiate between metastatic and non-metastatic lymph nodes. The following criteria for the diagnosis of metastasis in pelvic nodes were used: short axis >10 mm and the presence of central necrosis regardless of nodal size. Sensitivity, specificity, positive and negative predictive values, and accuracy of helical CT imaging in the diagnosis of lymph node metastasis on a hemipelvis basis was 64.7%, 96.6%, 84.6%, 90.5%, and 89.5% (15). The size of pelvic lymph nodes on CT is summarized in Table 1.

Table 1.

CT detection of pelvic lymph node metastasis in patients with cervical cancer.

Researchers	Diameter (mm)	Additional items	Sensitivity (%)	Specificity (%)	Accuracy (%)
Yang et al. (15)	10	Central necrosis	64.7	96.6	89.5
Jung et al. (40)	10	-	51.4	81.9	80.3
Louis et al. (41)	15	-	100	75	85

CT, computed tomography.

For PALNs in cervical cancer, it was reported in the literature that the positive rate of lymph node metastasis in the group with minimum axial diameter ≥1.0 cm (83.33%) was significantly higher than that in the group with 0.5 cm ≤ MAD (minimum axial diameter) < 1.0 cm (26.82%). The cutoff value of the smallest axial diameter in determining lymph node metastasis is 1.0 cm (16). The study also yielded an area under the receiver operating characteristic (ROC) curve for the smallest axial diameter of lymph nodes on CT scan of 0.782 (95% confidence interval [CI] = 0.706–0.859). The Youden index was the largest when the smallest axial diameter was 1.0 cm. Other studies have shown that if the short axis is >10 mm, para-aortic lymphadenopathy is considered to be enlarged, with a sensitivity and specificity of 80% and 92%, respectively (17). When the lymph node diameter was >1 cm, the sensitivity and specificity of CT for PALN involvement were 67% and 92%, respectively (18). The shape of the lymph nodes may also be a useful diagnostic feature. Normal lymph nodes have a fat hilum, which is an oblong bean-like structure (19). In a study of patients with gastric cancer, Fukuya et al. found that lymph nodes with higher short-to-long axis ratios (rounder than ovals) were more likely to be malignant (20). It can be seen that CT mainly depends on the morphological and size criteria for distinguishing benign and malignant lymph nodes. The size of PALNs in CT is summarized in Table 2. Positive lymph nodes in CT are significantly related to the following factors: (i) short axis ≥10 mm; and (ii) round or central necrosis.

Table 2.

CT detection of para-aortic lymph node metastasis in patients with cervical cancer.

Researchers	Diameter (mm)	Sensitivity (%)	Specificity (%)	Accuracy (%)
Dean et al. (18)	10	67	92	85
Li et al. (16)	10	66	80	72
Louis et al. (41)	15	67	100	90

CT, computed tomography.

MRI

MRI is a type of imaging equipment used for medical examinations made using the phenomenon of nuclear magnetic resonance. High-contrast resolution images of tissues are obtained by strong magnets with phased array coils (21). The only generally accepted criterion for diagnosing metastatic lymph nodes in MRI is lymph node size, but considering that metastatic lymph nodes, hyperplastic lymph nodes, and normal lymph nodes may overlap, the shape and signal characteristics of the lymph nodes should be evaluated in the diagnosis. For pelvic lymph nodes in cervical cancer, the MRI findings of pelvic lymph nodes are summarized in Table 3.

Table 3.

MRI detection of pelvic lymph node metastasis in patients with cervical cancer.

Stratification	Subgroups	Sensitivity (%)	Specificity (%)	Accuracy (%)
Diameter (mm)	8 (23)	67	84	81
	8.8 (42)	55	84	74
	10 (40)	24.3	96.3	84.6
ADC (×10⁻³mm²/s)	0.72 (b value of 0 and 800 s/mm²) (43)	83.1	89.6	83.7
	0.712 (b value of 0 and 1000 s/mm²) (42)	86	80	82
	1.159 (b value of 0 and 800 s/mm²) (44)	83.3	74.7	78.4

ADC, apparent diffusion coefficient; MRI, magnetic resonance imaging.

The sensitivity and positive predictive value of lymph nodes were significantly improved when the short-axis diameter of the lymph nodes was >9 mm, with lobulated or needle-like margins (22). Other studies have concluded that when the short diameter of the lymph node is >8 mm, the sensitivity is 60%, the specificity is 73%, and the accuracy is 70% (23). In the study by DEZEN et al., 90.5% of lymph nodes were found to be metastatic lymph nodes on histological analysis when the short diameter of the lymph nodes was >10 mm. The correlation between T2 low signal and lymph node metastasis was 81.0%; the correlation between round shape and lymph node metastasis was 78.6%; the correlation between heterogeneous appearance and lymph node metastasis was 69%; the correlation between necrosis and lymph node metastasis was 47.6%; and the association of irregularly demarcated lymph node metastasis was 40.5% (24).

DWI is a magnetic resonance technique and a non-invasive functional imaging modality. DWI enables a quantitative assessment of diffusion properties based on the calculated apparent diffusion coefficient (ADC), which is a function of the exponential decrease in tissue signal intensity with increasing diffusion weighting (b-value). Cervical cancer tissue usually shows the high signal intensity of the primary tumor and metastatic lymph nodes on high b-value DWI, and corresponding low signal intensity on the ADC map (25). Recently, many studies have described the effectiveness of DWI and ADC values in differentiating metastatic and non-metastatic lymph nodes. When the short-axis diameter of the lymph nodes is <20 mm, the ADC value of the metastatic lymph node (0.86 ± 0.36) × 10⁻³mm²/s is significantly lower than that of the non-metastatic lymph node (1.12 ± 0.34) × 10⁻³mm²/s. Thus, ADC values are valuable in distinguishing metastatic and non-metastatic lymph nodes (26). Lin et al. introduced the concept of relative ADC values because of the lack of absolute cutoff values for ADC values when distinguishing between metastatic and non-metastatic lymph nodes. The theory is based on the assumption that lymph nodes in the invaded region exhibit similar cellular structures and/or features of primary tumor microstructures with similar ADC values. In Lin et al.’s study, the ADC value of the metastatic lymph nodes was higher than that of benign nodes, albeit not significantly. They thus propose the use of the relative ADC criterion. The relative ADC values between tumor and nodes were significantly lower in metastatic lymph nodes than in benign nodes (0.06 × 10⁻³ and 0.21 × 10⁻³) (27). MRI findings of PALNs are summarized in Table 4. Positive lymph nodes in MRI are significantly related to the following factors: (i) short axis ≥8 mm; (ii) inhomogeneous signal intensity; (iii) morphology: round, irregular margins, extracapsular invasion, central necrosis, lymph nodes loss of structure, burrs, or lobes; and (iv) ADC value decreased, combined with local actuality.

Table 4.

MRI detection of para-aortic lymph node metastasis in patients with cervical cancer.

Stratification	Subgroups	Sensitivity (%)	Specificity (%)	Accuracy (%)
Diameter (mm)	8 (23)	60	73	70
	9 (22)	33.3	97.4	91.4
	10 (24)	-	-	90.5
ADC (×10⁻³mm²/s)	0.862 (b value of 0 and 1000 s/mm²) (45)	87	80	81
	0.881 (b value of 0 and 1000 s/mm²) (46)	95.7	96.5	96.3
	1.149 (b value of 0 and 800 s/mm²) (47)	83	98	94

ADC, apparent diffusion coefficient; MRI, magnetic resonance imaging.

PET-CT

PET-CT combines two imaging techniques to simultaneously visualize morphological and metabolic tumor features, allowing co-registration of structural and functional data in fused images. 18F-FDG PET is a functional method based on increased glucose metabolism in cancer cells, independent of lymph node size. For the detection of lymph node metastases, FDG PET-CT, although slightly inferior to sentinel lymph node biopsy (SLN) (28 –30), appears to be superior to conventional MRI, CT, and ultrasound, making it a very attractive non-invasive imaging method, especially in patients at high risk of metastatic disease (28,31,32), PET-CT can often detect micrometastatic lymph nodes with sizes in the range of 5–9 mm, which cannot be diagnosed by MRI or CT (33). In general, the criterion for lymph node involvement on FDG imaging is that a node with greater FDG uptake than the surrounding tissue or an SUV >2.5 is defined as a positive node, regardless of its size (34). PET-CT has been proved to be valuable for lymph node staging in patients with cervical cancer. A short-axis diameter >0.5 cm is the size threshold for accurately describing the size of metastatic lymph nodes. When the node size is <5 mm, its accuracy is reduced (35). In conclusion, we believe that in the PET-CT examination, when the short axis of the lymph node is >5 mm, the SUV is >2.5, or the FDG uptake is greater than that of the surrounding tissue, it is a metastatic lymph node.

Discussion

In a review of the literature, we found that the sensitivity and specificity of PET-CT were 73%–81% and 93%–98%, respectively. The sensitivity and specificity of MRI were 54% and 94%, and that of CT were 68% and 90%, respectively (32,36). CT and MRI have similar sensitivities and specificities for the evaluation of lymph nodes. The evaluation is mainly based on the size of the lymph nodes, combined with the morphology, density, signal, and enhancement characteristics of the lymph nodes. Of course, the size criteria of lymph nodes and the conventional imaging features of CT and MRI imaging have proven to have limited diagnostic accuracy. When MRI is used in combination with DWI, its sensitivity is greatly improved. Lin et al. found that the method combining lymph node size and ADC value had better sensitivity (25% vs. 83%) and similar specificity (98% vs. 99%) compared to conventional MRI (27). PET-CT is a functional approach based on increased glucose metabolism in cancer cells, independent of lymph node size. PET-CT can detect micrometastatic lymph nodes, which is the main advantage of CT and MRI in distinguishing metastatic lymph nodes. Studies have found that there is a significant negative correlation between SUV and ADC. Both PET-CT and MRI have advantages in the diagnosis of positive PALNs. Can the detection of PALNs in cervical cancer be improved by combining MRI and PET-CT? The study by Montiel et al. found that FDG-PET combined with MRI can improve the detection of PALN metastasis (23).

In this paper, the ADC value was selected as the standard for metastatic lymph nodes in MRI, and the SUV value was selected as the standard for positive lymph nodes in PET-CT. However, in Kazuhiro et al.’s study, the above values were not used to distinguish positive lymph nodes. They compared the focal abnormal signal signatures on DWI with those on enhanced T1-weighted (T1W) and T2-weighted (T2W) imaging nodes as criteria for metastatic nodes. They argue that quantifying ADC values is currently controversial. Again, they suggested that the SUV value might be of little help in differentiating metastatic lymph nodes, and instead use PET-CT to extract more tracers from lymph nodes as a criterion for positive lymph nodes (37,38). Of course, whether CT, MRI, or PET-CT, they are not as good as surgical staging. Staging of PALNs using PET-CT is an alternative to surgery in locally advanced diseases (39).

In the literature reviewed so far, there are few summaries of the imaging manifestations of metastatic lymph nodes adjacent to the abdominal aorta in cervical cancer, and most of them focus on the analysis of the sensitivity and specificity of imaging. By reading the positive lymph nodes in various kinds of literature, this paper summarizes the criteria for the manifestations of para-aortic metastatic lymph nodes in different imaging examinations of cervical cancer.

The present study has some limitations. These include the following: (i) only a limited number of literary studies can be included. This is because patients with locally advanced cervical cancer generally do not undergo surgery, and mostly use radiotherapy and chemotherapy, so the pathological specimens that can be collected are limited; (ii) in the included studies, compared with pelvic lymph nodes, the number of cases of abdominal aortic lymph node metastasis was less; (iii) for MRI, the threshold of ADC is affected by many factors, and the criteria for positive lymph nodes should be reasonably designed in combination with local institutions.

Conclusion

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Guangdong Medical Research Fund (Project No. B2021114).

ORCID iD

Yufang Zuo

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