Validity of CT/MRI in Cervical Lymph Nodes with Oral Squamous Cell Carcinoma in a Select Kenyan Population

Abstract

Objectives: Accurate assessment of neck lymphadenopathy is crucial in Oral Squamous Cell Carcinoma (OSCC) due to its prognostic significance. This study aimed to evaluate the reliability and validity of radiological tools using histopathology as a reference for assessing cervical lymph nodes in these patients. Methods: A cross-sectional study was conducted involving 30 patients with OSCC, selected through purposive sampling, who underwent neck dissection at Kenyatta National Hospital between February and June 2023. Data from radiological (preoperative) and histopathological (postoperative) assessment of cervical lymph nodes was collected. The agreement, sensitivity, and specificity of different radiological examinations were evaluated. Results: Radiological and pathological nodal categories showed a consensus (κ = 0.629, p = 0.009), reporting CT scan sensitivity was 83.3% (51.6 - 97.9) and MRI sensitivity was 100% (39.8 - 100). Specificity for CT scan was 44.4% (13.7 - 78.8), while specificity for MRI was 60% (14.7 - 94.7). The positive predictive values for CT scan and MRI were 66.7% (51.4 - 79.1) each while the negative predictive values were 66.7% (40.6 - 85.4) and 100%, respectively. Conclusions: The radiological diagnostic tools demonstrated varying levels of reliability, with MRI showing higher validity than CT scan in the assessment of cervical lymph nodes in OSCC patients.

Share and Cite:

Makokha, R. , Butt, F. , Olabu, B. , Dimba, E. and Guthua, S. (2026) Validity of CT/MRI in Cervical Lymph Nodes with Oral Squamous Cell Carcinoma in a Select Kenyan Population. Open Journal of Stomatology, 16, 17-34. doi: 10.4236/ojst.2026.162003.

1. Introduction

Oral squamous cell carcinoma (OSCC) ranks as the fifteenth most common malignancy affecting both males and females worldwide with 300,000 new cases recorded every year [1]. The prognosis of patients with lymph node involvement markedly decreases by 50% affecting both recurrence of disease and poor chances of survival [2]. Twenty-three percent (23%) of lymph node metastases have been identified in OSCC, even at early stages of the disease [3].

Techniques utilized to detect the spread of lymph node metastasis include clinical and radiographic imaging (CT, MRI, US, and PET/CT scans). While each diagnostic imaging method has not been thoroughly examined, their use in preoperative evaluation remains under-researched, limiting their predictive reliability [4]-[6]. The meta-analysis published reports on the validity of each imaging modality, but the studies lacked refinement due to the inclusion of dissection slides or individual patient data. Comparing each lymph node region clinically and radiologically can improve both prognosis and treatment planning [7].

According to Bae et al. (2020), CT scans and MRI are less effective at detecting cervical lymph node metastasis [8]. This is demonstrated after therapeutic neck dissection, where some clinically N+ patients end up as N0 on histopathology. Similarly, after elective neck dissection, some clinically N0 patients end up as N+ on histopathology [9]. The decision as to whether or not to perform elective neck dissection on clinically N0 necks is a delicate balance. On one hand, there is the risk of unnecessary morbidity associated with neck dissection (e.g., numbness, lymphedema and limited shoulder movements) [10]. On the other hand, there is a risk of occult metastasis and subsequent recurrence if not dissected [11]. Some studies found that CT scans effectively estimate lymph node volume, with a sensitivity of 81.8%, specificity of 100%, and accuracy of 97.7%. However, sensitivity may appear lower because most lymph nodes studied were benign on histopathology [12] [13]. Accurate preoperative lymph node evaluation is essential for staging and prognosis, requiring sensitive and specific investigative techniques.

There are limited studies that evaluate the reliability of radiological diagnostic tools with histopathology as the reference for assessment of cervical lymph nodes in patients with OSCC. Therefore, this study assessed the accuracy of CT and MRI in detecting cervical nodes among patients with oral squamous cell carcinoma, using histopathology as the reference standard, within a specific Kenyan population.

2. Materials and Methods

This cross-sectional study took place at Kenyatta National Hospital (KNH), Kenya’s largest referral and teaching hospital. Patients were purposively selected between February and June 2023. Inclusion criteria included patients to have neck dissection as treatment during resection of the OSCC, along with preoperative neck imaging (CT or MRI). Participants were recruited into the study after providing written consent. Exclusion criteria included recurrent disease, prior neck treatment (surgery, radiotherapy, chemotherapy), or lymphadenopathy due to other causes such as HIV. Data on the sociodemographic variables (age, sex) and clinical characteristics (type of radiological imaging, primary tumor site, primary tumor categorization-T) was collected. Primary tumor (T) categorization was according to the Eighth Edition AJCC Cancer Staging [14].

CT and MRI images and reports were reviewed before surgery. Both the size and morphology of the node were taken into consideration for scoring as per Yoon et al. Suspicious nodes were defined by diameters over 9mm, abnormal hilar structure, or evidence of extra-nodal extension [15].

The cervical lymph nodes were sent to an oral pathologist for histological assessment, processed, stained with H&E, and examined under light microscopy. The lymph nodes were categorized as positive if tumour cells were observed on histologic examination. The patients’ nodes were subsequently categorized (pN) according to the Eighth Edition AJCC Cancer Staging [14]. Information regarding the number of patients with abnormal (metastatic) lymph nodes, their pathological nodal classification, and specific characteristics of the metastatic lymph nodes was systematically recorded on data sheets and subsequently transferred to an MS Excel spreadsheet. This data from patients was recorded on data sheets and entered into an MS Excel file.

The statistical analyses were conducted with SPSS version 25 software. For descriptive statistics, median and IQR were used to describe continuous variables, while proportions were used to describe categorical variables. Cohen’s Kappa was used to determine the level of agreement between clinical (radiological) and pathological nodal categorization and interpreted according to Landis and Koch [16]. Quantitative variables are reported using averages and standard deviations, while qualitative variables are described by frequencies and percentages. Sensitivity, specificity, and predictive values for radiological imaging were calculated against histopathology, with a 95% confidence interval. The association between Primary Tumor Categories (T) and Nodal spread (N) was analyzed by calculating Odds ratios (OR).

The study was reviewed and approved by the KNH-UON Ethics and Research Committee (reference number KNH-ERC/A/84). It was conducted in accordance with the principles of the Declaration of Helsinki of 1975 (available online: https://www.wma.net/what-we-do/medical-ethics/declaration-of-helsinki/, accessed on 27 March 2020), revised in 2013 [17].

3. Results

From February to June 2023, 30 patients were diagnosed with OSCC and all met the inclusion criteria for neck dissection surgery. The age ranged from 15 - 77 years ( x ¯ = 58.1 yrs ± 12.5 SD) with a median age of 60.5 years (interquartile range: 52 - 66). The sociodemographic and clinical characteristics are summarized in Table 1.

Table 1. Sociodemographic and clinical characteristics of patients with OSCC undergoing neck dissection (N = 30).

Characteristics

Number of patientsn (%)

Sex

Male

16 (53.3)

Female

14 (46.7)

Age (years)

≤40

1 (3.3)

41 - 50

6 (20)

51 - 60

8 (26.7)

61 - 70

11 (36.7)

>70

4 (13.3)

Evaluation of the site of primary lesion showed that 28 (93.4%) were in the oral cavity, 1 (3.3%) affected both oral cavity and oropharynx while 1 (3.3%) was in the oropharynx. Within the sub-sites majority 13 (28.9%) of the patients had a tumor in the anterior tongue, followed by 7 (15.6%) for both the floor of the mouth and buccal mucosa. The evaluation of histological diagnosis showed that 18 (60.0%) were well differentiated, 8 (26.7%) moderately differentiated and 4 (13.3%) poorly differentiated SCC. The site of the primary lesion, sub-sites, histological diagnosis and histological grading are summarized in Table 2.

Table 2. Anatomical and histological grade of OSCC.

Characteristics

n

%

Site of Primary Lesion

Oral Cavity

28

93.4

Oral Cavity & Oropharynx

1

3.3

Oropharynx

1

3.3

Total

30

100.0

Sub sites

Mucosal lips

3

6.7

Anterior tongue

13

28.9

Floor of the mouth

7

15.6

Buccal mucosa

7

15.6

Mandibular alveolar ridge

3

6.7

Maxillary alveolar ridge

1

2.2

Hard palate

3

6.7

Retro molar trigone

2

4.4

Base of the tongue

2

4.4

Tonsillar complex

2

4.4

Soft palate

2

4.4

Total

45

100.0

Histological Diagnosis

OSCC

29

96.7

OPSC

1

3.3

Total

30

100.0

Histological Grading

Well differentiated

18

60.0

Moderately differentiated

8

26.7

Poorly differentiated

4

13.3

Total

30

100.0

3.1. Radiological Assessment of Cervical Lymph Nodes in OSCC/OPSCC

Reviewing patient records revealed that 22 patients (73.3%) had CT scans, while 8 (26.7%) underwent MRI. Among 30 patients, 21 (70.0%) had suspicious nodes; 9 (30.0%) did not. Out of 21 patients with suspected lymph nodes, Level I involvement was found in 18 cases (85.7%), while Level II was seen in 10 cases (47.6%), and Level III appeared in just 2 cases (9.5%). In 8 patients (38.1%), suspicious nodes were present across multiple cervical levels. Characterization of the radiological features of the 38 suspicious nodes showed 28 (73.6%) nodes had diameters greater than 9 mm, 2 (5.3%) nodes had a round shape, 6 (15.8%) nodes had abnormal hilum architecture, and 2 (5.3%) nodes were matted. The lymph node size ranged from 0.0 - 62 mm with a mean size of 12.7 mm (±13.3 SD), a median of 11.5 mm and a mode of 0.0 mm. Some of the patients exhibited more than one evaluation criterion. The radiological nodal categorization had 9 (30.0%) patients with cN0 followed by 8 (26.7%) and 7 (23.3%) patients with cN2b and cN1 respectively in Table 3. The radiological features of the patients are summarized in while the distributions of suspicious nodes by levels are summarized in Figure 1. The histological nodal classification indicated that 14 (46.7%) patients were categorized as pN0, while 6 (20.0%) patients were classified as pN3b. Additionally, 3 (10.0%) patients each were staged as pN1, pN2b, and pN2c. Only 1 (3.3%) patient was staged pN3a. The histological features of the patients are summarized in Table 4.

Table 3. Summary of radiological nodal assessment.

Characteristics

n

%

Imaging Modality

CT Scan

22

73.3

MRI

8

26.7

Total

30

100

Patients with Suspicious Nodes

No

9

30.0

Yes

21

70.0

Total

30

100

Levels with suspicious nodes of the 21 patients

Level I

18

85.7

Level II

10

47.6

Level III

2

9.5

Patients with multiple levels of suspicious nodes

One level

13

61.9

Two levels

7

33.3

Three levels

1

4.8

Total

21

100

Radiological features of suspicious Nodes

Nodes > 9 mm in Diameter

28

73.6

Round Shape Node

2

5.3

Abnormal Hilum Architecture

6

15.8

Matted Nodes

2

5.3

Total

38

100

Radiological Nodal Category

N0

9

30.0

N1

7

23.3

N2a

1

3.3

N2b

8

26.7

N2c

3

10.0

N3a

1

3.3

N3b

1

3.3

Total

30

100

Figure 1. Number of histologically identified and involved lymph nodes by levels.

Table 4. Summary of histological assessment.

Nodal Characteristics

n

%

Level of Neck Dissection

Level I

30

100

Level II

25

83.3

Level III

20

66.7

Level IV

11

36.7

Nodes identified histologically per Level

Level I

146

42.6

Level II

106

30.9

Level III

62

18.1

Level IV

29

8.4

Total

343

100

Patients with metastatic nodes

Yes

16

53.3

No

14

46.7

Levels with metastatic nodes of the 16 patients

Level I

16

100.0

Level II

7

43.8

Level III

3

18.8

Level IV

1

6.3

Number of metastatic lymph nodes per level

Level I

44

74.6

Level II

11

18.6

Level III

3

5.1

Level IV

1

1.7

Total

59

100

Histological features of metastatic nodes

Abnormal Hilum Architecture

30

50.8

Nodes > 9 mm in Diameter

24

40.7

Matted Nodes

5

8.5

Total

59

100

Extra nodal extension among the 16 patients with nodal metastasis

Yes

6

37.5

No

10

62.5

Total

16

100

Pathological nodal categories

N0

14

46.7

N1

3

10.0

N2b

3

10.0

N2c

3

10.0

N3a

1

3.3

N3b

6

20.0

Total

30

100

3.2. Histopathological Assessments of Cervical Lymph Nodes in OSCC/OPSCC

Out of a total of 343 lymph nodes identified during neck dissection for histopathological examination, 59 were confirmed to be positive for tumor. A paired t-test was conducted to compare the number of lymph nodes dissected out and the number of metastatic lymph nodes confirmed on histology. There was a statistically significant difference in the number of lymph nodes dissected out (M = 11.43, SD = 6.83) and the number of metastatic lymph nodes (M = 1.97, SD = 2.81); t (29) = 7.349, p < 0.001 from the patients. The effect size was large, with a Cohen’s d of 1.81, indicating that more than 96% of the number of lymph nodes involved would be below the average number of lymph nodes dissected. The comparison of the number of lymph nodes identified and involved is summarized in Table 5.

Table 5. Comparison of the number of lymph nodes identified and involved.

95% Confidence Interval of the Difference

t

df

P

Number of lymph nodes

n

Mean

SD

Lower

Upper

Histologically identified

30

11.43

6.83

6.83

12.10

7.349*

29

<0.001

Histologically positive

30

1.97

2.81

Note: Paired t-test was applied. *: The mean difference is statistically significant at the level of 0.05.

Histopathological evaluation of the number of nodes dissected per level showed Level I {146 (42.6%)} had the most nodes, followed by Level II {106 (30.9%)}, then Level III {62 (18.1%)} and Level IV {29 (8.4%)}. Of the 30 patients, 16 (53.3%) were positive for tumor in the cervical lymph nodes, while 14 (46.7%) did not exhibit any lymph node involvement. Analysis of the 16 patients with metastatic nodes showed 14 (87.5%) had clinically suspicious nodes but 2 (12.5%) were clinically negative nodes prior to surgery. Of the 16 (53.3%) histologically positive cases, the most common Tumor (T) categorization was T4a with 11 (68.8%) cases followed by T3 with 2 (12.5%) cases while T1, T2, and T4b had 1 (6.3%) case each. The distribution of Tumor (T) categorization among the histologic positive cases is summarized in Figure 2.

Figure 2. Distribution of radiological features of suspicious nodes by levels.

The histological nodal categorization had 14 (46.7%) patients at pN0 followed by 6 (20.0%) patients staged pN3b. pN1, pN2b and pN2c had 3 (10.0%) patients each. Only 1 (3.3%) patient was staged pN3a. Sixteen patients (53.3%) were found to have histologically confirmed tumours within their cervical lymph nodes (pN+). These histopathological characteristics of the nodes were described as follows; 14 patients had nodes > 9 mm in diameter (radiographically), 9 had with abnormal hilum architecture with 6 showing extra-nodal extension. Within this group of pN+ patients, the predominant nodal classification was N3b, identified in six patients Table 4.

Out of 59 metastatic lymph nodes, 44 (74.6%) were located in Level I, followed by 11 (18.6%) in Level II, 3 (5.1%) Level III and 1 (1.7%) in Level IV 3 (5.1%). On characterization of the 59 involved lymph nodes, 30 (50.8) nodes had abnormal hilar architecture, 24 (40.7%) nodes were greater than 9mm in diameter, 5 (16.7%) nodes were matted. The distribution of the metastatic nodes per criteria and cervical level is summarized in Table 4.

3.3. Pattern of Agreement between Radiological and Histopathological Assessment of Cervical Lymph Nodes in OSCC/OPSCC

Due to the small sample size of 30, Cohen’s Kappa (κ) test was used to determine the patterns of agreement based on matched (paired) cases for the study. There was fair agreement between the two groups of patients, κ = 0.384, p < 0.05. The pattern of agreement between patients with suspicious nodes and patients with involved lymph nodes is summarized in Table 6. Cohen’s κ was run to determine the pattern of agreement between levels of suspicious nodes and levels of involved lymph nodes. There was a moderate agreement between the two groups of levels of nodes, κ = 0.512, p < 0.05. The pattern of agreement between clinically suspicious and histologically confirmed involved lymph nodes is summarized in Table 7. Cohen’s κ was run to determine the pattern of agreement between radiological and pathological nodal categories. There was a substantial agreement between the two groups of nodal categories, κ = 0.629, p < 0.05. The pattern of agreement between radiological and pathological nodal categories is summarized in Table 8.

Table 6. Pattern of agreement between patients with clinically suspicious nodes and patients with histological confirmation of involved lymph nodes.

Patients with suspicious node

Total

Kappa (κ)

p

No

Yes

Patients with involved lymph nodes

No

n

7

7

14

0.384*

0.025

%

23.3

23.3

46.7

Yes

n

2

14

16

%

6.7

46.7

53.3

Total

n

9

21

30

%

30.0

70.0

100.0

Note: Cohen’s Kappa (κ) test was applied. *: Cohen’s Kappa (κ) is significant at the level 0.05.

Table 7. Pattern of agreement between cervical levels with suspicious and involved lymph nodes.

Lymph Nodes

Involved

Total

Kappa (κ)

p

Level I

Level II

Level III

Suspicious

Level I

n

8

1

1

10

0.512*

<0.001

%

57.1

7.1

7.1

71.4

Level II

n

0

1

1

2

%

0.0

7.1

7.1

14.3

Level III

n

0

2

0

2

%

0.0

14.3

0.0

14.3

Total

n

8

4

2

14

%

57.1

28.6

14.3

100.0

Note: Cohen’s Kappa (κ) test was applied. *: Cohen’s Kappa (κ) is significant at the level 0.05.

Table 8. Pattern of agreement between radiological and pathological nodal categories.

Nodal categories

Histological

N0

N1

N2b

N2c

N3a

N3b

Total

Kappa (κ)

p

Radiological

N0

N

9

0

0

0

0

0

9

0.629*

0.009

%

30.0

0.0

0.0

0.0

0.0

0.0

30.0

N1

N

4

3

0

0

0

0

7

%

13.3

10.0

0.0

0.0

0.0

0.0

23.3

N2a

N

1

0

0

0

0

0

1

%

3.3

0.0

0.0

0.0

0.0

0.0

3.3

N2b

N

0

0

3

0

0

5

8

%

0.0

0.0

10.0

0.0

0.0

16.7

26.8

N2c

N

0

0

0

3

0

0

3

%

0.0

0.0

0.0

10.0

0.0

0.0

10.0

N3a

N

0

0

0

0

1

0

1

%

0.0

0.0

0.0

0.0

3.3

0.0

3.3

N3b

N

0

0

0

0

0

1

1

%

0.0

0.0

0.0

0.0

0.0

3.3

3.3

Total

N

14

3

3

3

1

6

30

%

46.7

10.0

10.0

10.0

3.3

20.0

100.0

Note: Cohen’s Kappa (κ) test was applied. *: Cohen’s Kappa (κ) is significant at the level 0.05.

3.4. Sensitivity, Specificity, False Positives and False Negatives of Radiological Investigations

The sensitivity, specificity, false positives and false negatives of the two diagnostic tests (MRI and CT scan) were compared with the histopathological results as the gold standard. Evaluation of the MRI results showed a sensitivity (true positive) rate of 100.0%, a specificity (true negative) rate of 60.0%, a false positive rate of 40.0% and a false negative rate of 0.0%. A McNemar’s exact test determined that the difference in the proportions of MRI positive results and histological results was not statistically significant, p = 0.500.

Evaluation of the CT Scan results showed a sensitivity (true positive) rate of 83.3%, a specificity (true negative) rate of 44.4%, a false positive rate of 55.6% and false negative rate of 16.7%. A McNemar’s exact test determined that the difference in the proportions of CT scan positive results and histological results was not statistically significant, p = 0.453. A comparison between the two imaging modalities showed that there was a difference of 16.7% sensitivity rate between MRI (100.0%) and CT scan (83.3%). A McNemar’s exact test determined that the difference in the proportion of positive radiological results and histological results was not statistically significant, p = 0.180. The sensitivity, specificity, false positives and false negatives of the radiological investigations are summarized in Table 9.

Table 9. Sensitivity, specificity, false positives and false negatives of the radiological investigations.

Diagnostic Tests

Radiological Results

Histological Results

Total

McNemar’s test

Negative

Positive

n

p

MRI

Negative

n

3

0

3

9

0.500

%

60.0%

0.0%

33.3%

Positive

n

2

4

6

%

40.0%

100.0%

66.7%

Total

n

5

4

9

%

100.0%

100.0%

100.0%

CT Scan

Negative

n

4

2

6

21

0.453

%

44.4%

16.7%

28.6%

Positive

n

5

10

15

%

55.6%

83.3%

71.4%

Total

n

9

12

21

%

100.0%

100.0%

100.0%

Note: A McNemar’s exact test was applied.

4. Discussion

4.1. Radiological Assessment of Cervical Lymph Nodes in OSCC/OPSCC

This study found that CT scan was the most common radiological modality requested for assessing cervical lymph node metastasis. This was similar to other studies by Horváth et al. and Thoenissen et al. [9] [18]. The preference for CT scans may partly stem from their greater availability, lower cost, and quicker procedure time when compared to MRI.

Approximately 30% of the patients did not have radiological evidence of cervical lymph node metastasis (cN0) but still underwent neck dissection to rule out occult metastasis. Previous studies have shown the prevalence of this prophylactic neck dissection to range from 31% to 60% [11] [18]-[21]. Elective neck dissection is supported by evidence of occult metastasis from previous studies [11] [22] [23].

Cervical Level I had the greatest number of suspicious lymph nodes. This was similar to a prospective study by Narayana et al., of 24 patients which found Level I (combined Ia and Ib) to be the most prevalent suspicious cervical level. It is well demonstrated that level I has the most sentinel lymph nodes for primary tumors located in the floor of the mouth [24] [25]. Thus, meticulous clinical assessment of Level I is very important [25].

In this study, the most common radiological feature of suspicious lymph nodes identified was an enlarged node of more than 9 mm in diameter. Most studies advocate for assessment criteria based on a combination of nodal size, architecture and signs of extra nodal spread like matted nodes [26]-[28]. Relying on size criteria for diagnosis of clinical cervical lymph node metastasis reduces the accuracy of CT scan to 45% compared to 95% - 100% accuracy when based on central necrosis [29]. This aspect is important in this study given that calculation of sensitivities and specificities was one of the objectives.

The most frequent clinical nodal categories in this study were cN2b and cN1. This differed from a German retrospective study of 242 patients by Voss et al. in 2022 which found cN1 to be the most prevalent clinical nodal category [20]. The higher nodal categorization in this current study could be due to the higher number of patients with higher T categorization. It could also be due to factors associated with delays in diagnosis of oral cancer, especially in developing countries [30].

4.2. Histopathological Assessment of Cervical Lymph Nodes in OSCC/OPSCC

In the current study, level I had the highest number of positive lymph nodes confirmed on histology. Several previous studies found similar results [11] [21] [31] [32]. Thoenissen et al., found a near equal prevalence between Levels I and II (9). On the other hand, Nithya et al., when looking specifically at carcinoma of the tongue, found level II to be most commonly involved [33]. Levels I and II are known sentinel lymph nodes of primaries from the oral cavity [24]. These levels have to be thoroughly dissected out during neck dissection.

Almost half the patients who underwent neck dissection in the current study did not have cervical lymph node metastasis. Previous studies support this finding [11] [23] [31]-[35]. In contrast, Qiao et al., and Mehta et al., in retrospective studies found a lower prevalence of 30% and 20% respectively [19] [31]. As demonstrated by Kligerman et al. in a randomized controlled trial of 67 patients with stage 1 and 2 OSCC of the floor of the mouth and tongue, survival rate is better when elective neck dissection is done [36].

In this study, the most common histopathological feature of positive lymph nodes was abnormal hilum architecture. Pandeshwar et al., found most metastatic cervical lymph nodes to have central necrosis. Presence of tumor distorts the architecture of the lymph node by causing necrosis, deposition of keratin pearls, among others. Most of these architectural changes can be seen on radiological examination and inform their assessment and subsequent clinical staging [21].

A third of all the positive nodes in this study had extra nodal extension. The prevalence of extra nodal extension in other studies ranges from 24% to 45% [20] [32] [37]. Extra nodal extension lowers the prognosis in OSCC [35]. It is recommended that adjuvant chemotherapy be administered after neck dissection in patients with extra capsular spread [38].

The most prevalent pathological nodal category in this study was pN3b. This was similar to studies by Rabie et al., and Voss et al., [20] [37]. This, however, contrasted to the study by Thoenissen et al., who found N1 and N2b to be most prevalent [9]. N3b was introduced as part of TNM staging in the AJCC 8th edition of 2018 and may not be captured in research done prior to 2018 [14]. N3b denotes extra nodal extension and has poor prognosis [35]. AJCC recommends adjuvant chemotherapy for N3b [14].

4.3. Pattern of Agreement between Radiological and Histological Assessment of Cervical Lymph Nodes in OSCC/OPSCC

In this study, there was a fair agreement between patients with clinically suspicious nodes and the patients with histologically confirmed nodal metastasis. This low pattern of agreement could be due to the overreliance on size criteria in identifying suspicious nodes on radiology. Assessing lymph node architecture on imaging, rather than size alone, may improve detection of malignant invasion. The level of agreement increased to moderate when the unit of comparison was the cervical nodal level. The agreement increased to substantial when the comparison was between clinical (cN) and pathological (pN) nodal categories. This suggests that ultimately, the clinical (radiological) nodal assessment in TNM staging, which considers a combination of size, numbers, laterality and extra nodal extension, is an effective tool in predicting lymph node metastasis.

4.4. Sensitivity and Specificity of Radiological Investigations in Diagnosis of Cervical Lymph Node Metastasis

In this study population, CT had a sensitivity (true positive) of 83.3%. This was within the range of 52% to 83% found in other similar studies. However, the 44.4% specificity of CT scan in this study was lower than the range of 68% - 98% from other studies [9] [26]-[28] [39]. A common factor in the studies by Suryavanshi et al., Sumi et al., and Saafan et al., was their use of three or more criteria in assessing cervical lymph node metastasis (Central necrosis with peripheral enhancement, conglomeration of three or more lymph nodes and short axial diameter size criteria) [26]-[28]. The lower ability to exclude metastasis (specificity) in this study could be due to the overreliance on the size criteria. As a result, overtreatment of the neck may occur, leading to a considerable number of patients undergoing unnecessary neck dissections and experiencing related complications and increased morbidity.

The sensitivity (true positive) of MRI in this study was higher at 100%. The range observed in other studies was between 66% - 81%. On the other hand, the specificity of MRI in this study was 60%. This was lower than other studies which ranged from 68% to 80% [9] [39]. The wide variation in sensitivity and specificity of MRI in this study could be due to the smaller number of patients who had MRI as their radiological investigation before surgery.

In this study, the false positive rates were 55.6% and 40% for CT and MRI, respectively (cumulatively 50% false positive for radiological assessment). This implies approximately half of the patients without metastatic nodal disease were found to have been falsely categorized as positive on radiological assessment. Other studies have shown false positive rates of 2% - 32% from radiological assessment. The relatively higher false positive rate in this study correlates to the lower specificity of CT and MRI found. On the other hand, the false negative rates in this study were 16.7% for CT and none for MRI. This is similar to previous studies which found a false negative rate of 17% - 48% [9] [26]-[28] [39]. This study’s small sample size means that the comparison between CT and MRI performance was not statistically significant and does not confirm an actual lack of difference between the two modalities.

Our study had a few limitations. First, the sample size was relatively small. However, this was similar to other cross-sectional studies where data was collected before and after surgery [25] [26]. Secondly, there was possibility of bias in the reporting of the radiological images. This was mitigated by having an independent radiologist re-assess the radiological images for inter observer variability. Thirdly, the wide variation in MRI sensitivity and specificity could be due to the small number who were had an MRI investigation. Fourthly, the surgeries were performed by different surgeons thus raising the possibility of different qualities of neck dissection. The principal investigator was present at all neck dissections to ensure they followed ASCO guidelines [38].

5. Conclusions

The most common radiological feature of suspicious lymph nodes identified was an enlarged node of more than 9 mm in diameter while the most common histopathological feature of positive lymph nodes was abnormal hilar architecture. There was a substantial agreement between radiological and histopathological assessment of cervical lymph nodes in patients with OSCC/OPSCC. MRI and CT scan had higher sensitivity (true positives) but lower specificity (true negatives).

Future studies with larger or multicentric samples should incorporate diagnostic criteria such as irregular node margins or central necrosis, using advanced techniques like diffusion-weighted imaging.

Conflicts of Interest

The authors declare no conflicts of interest regarding the publication of this paper.

References

[1] Ferlay, J., Soerjomataram, I., Ervik, M., Dikshit, R., Eser, S., Mathers, C., et al. (2014) GLOBOCAN2012v1.1, CancerIncidence and Mortality Worldwide. IARC Cancer Base No. 11, International Agency for Research on Cancer.
http://globocan.iarc.fr
[2] Ho, A.S., Kim, S., Tighiouart, M., Gudino, C., Mita, A., Scher, K.S., et al. (2017) Metastatic Lymph Node Burden and Survival in Oral Cavity Cancer. Journal of Clinical Oncology, 35, 3601-3609.[CrossRef] [PubMed]
[3] Massey, C., Dharmarajan, A., Bannuru, R.R. and Rebeiz, E. (2018) Management of N0 Neck in Early Oral Squamous Cell Carcinoma: A Systematic Review and Meta‐Analysis. The Laryngoscope, 129, E284-E298.[CrossRef] [PubMed]
[4] Kim, S., Pak, K. and Kim, K. (2019) Diagnostic Accuracy of F-18 FDG PET or PET/CT for Detection of Lymph Node Metastasis in Clinically Node Negative Head and Neck Cancer Patients; a Systematic Review and Meta-Analysis. American Journal of Otolaryngology, 40, 297-305.[CrossRef] [PubMed]
[5] Sun, R., Tang, X., Yang, Y. and Zhang, C. (2015) 18FDG-PET/CT for the Detection of Regional Nodal Metastasis in Patients with Head and Neck Cancer: A Meta-Analysis. Oral Oncology, 51, 314-320.[CrossRef] [PubMed]
[6] Liao, C., Wang, H., Huang, S., Chen, I., Kang, C., Lin, C., et al. (2011) PET and PET/CT of the Neck Lymph Nodes Improves Risk Prediction in Patients with Squamous Cell Carcinoma of the Oral Cavity. Journal of Nuclear Medicine, 52, 180-187.[CrossRef] [PubMed]
[7] Piao, Y., Bold, B., Tayier, A., Ishida, R., Omura, K., Okada, N., et al. (2009) Evaluation of 18F-FDG PET/CT for Diagnosing Cervical Nodal Metastases in Patients with Oral Cavity or Oropharynx Carcinoma. Oral Surgery, Oral Medicine, Oral Pathology, Oral Radiology, and Endodontology, 108, 933-938.[CrossRef] [PubMed]
[8] Bae, M.R., Roh, J., Kim, J.S., Lee, J.H., Cho, K., Choi, S., et al. (2019) 18F-FDG PET/CT versus CT/MR Imaging for Detection of Neck Lymph Node Metastasis in Palpably Node-Negative Oral Cavity Cancer. Journal of Cancer Research and Clinical Oncology, 146, 237-244.[CrossRef] [PubMed]
[9] Thoenissen, P., Heselich, A., Burck, I., Sader, R., Vogl, T. and Ghanaati, S. (2023) The Role of Magnetic Resonance Imaging and Computed Tomography in Oral Squamous Cell Carcinoma Patients’ Preoperative Staging. Frontiers in Oncology, 13, Article ID: 972042.[CrossRef] [PubMed]
[10] Anand, A., Vidhyadharan, S., Subramaniam, N., Balsubramanian, D., Battoo, A.J., Iyer, S., et al. (2021) Selective Neck Dissection in Oral Cavity Cancer Is Not without Morbidity. Indian Journal of Surgical Oncology, 12, 5-11.[CrossRef] [PubMed]
[11] Hoda, N., BC, R., Ghosh, S., KS, S., B, V. and Nathani, J. (2021) Cervical Lymph Node Metastasis in Squamous Cell Carcinoma of the Buccal Mucosa: A Retrospective Study on Pattern of Involvement and Clinical Analysis. Medicina Oral Patología Oral y Cirugia Bucal, 26, e84-e89.[CrossRef] [PubMed]
[12] Dejaco, D., Url, C., Schartinger, V.H., Haug, A.K., Fischer, N., Riedl, D., et al. (2015) Approximation of Head and Neck Cancer Volumes in Contrast Enhanced CT. Cancer Imaging, 15, Article No. 16.[CrossRef] [PubMed]
[13] Varshney, P., Shenoy, V.S., M Kamath, P., Zuturu, N., Dhawan, S., Kudlu, K., et al. (2024) Lymph Nodal Volume in Head and Neck Malignancy: Can Adding a Third Dimension Improve the Detection of Nodal Metastasis? The Egyptian Journal of Otolaryngology, 40, Article No. 137.[CrossRef]
[14] Amin, M.B., Greene, F.L., Edge, S.B., Compton, C.C., Gershenwald, J.E., Brookland, R.K., et al. (2017) The Eighth Edition AJCC Cancer Staging Manual: Continuing to Build a Bridge from a Population‐Based to a More “Personalized” Approach to Cancer Staging. CA: A Cancer Journal for Clinicians, 67, 93-99.[CrossRef] [PubMed]
[15] Yoon, D.Y., Hwang, H.S., Chang, S.K., Rho, Y., Ahn, H.Y., Kim, J.H., et al. (2009) CT, MR, US, 18F-FDG PET/CT, and Their Combined Use for the Assessment of Cervical Lymph Node Metastases in Squamous Cell Carcinoma of the Head and Neck. European Radiology, 19, 634-642.[CrossRef] [PubMed]
[16] Landis, J.R. and Koch, G.G. (1977) The Measurement of Observer Agreement for Categorical Data. Biometrics, 33, 159-174.[CrossRef] [PubMed]
[17] World Medical Association (2013) World Medical Association Declaration of Helsinki: Ethical Principles for Medical Research Involving Human Subjects. JAMA, 310, 2191-2194.
[18] Horváth, A., Prekopp, P., Polony, G., Székely, E., Tamás, L. and Dános, K. (2021) Accuracy of the Preoperative Diagnostic Workup in Patients with Head and Neck Cancers Undergoing Neck Dissection in Terms of Nodal Metastases. European Archives of Oto-Rhino-Laryngology, 278, 2041-2046.[CrossRef] [PubMed]
[19] Qiao, Y., Wang, Y., Kang, P., Li, R., Liu, Y. and He, W. (2019) The Assessment of the Accuracy of Clinical Preoperative Lymph Node. Medicine, 98, e13778.[CrossRef] [PubMed]
[20] Voss, J.O., Freund, L., Neumann, F., Mrosk, F., Rubarth, K., Kreutzer, K., et al. (2022) Prognostic Value of Lymph Node Involvement in Oral Squamous Cell Carcinoma. Clinical Oral Investigations, 26, 6711-6720.[CrossRef] [PubMed]
[21] Pandeshwar, P., Jayanthi, K. and Raghuram, P. (2013) Pre-Operative Contrast Enhanced Computer Tomographic Evaluation of Cervical Nodal Metastatic Disease in Oral Squamous Cell Carcinoma. Indian Journal of Cancer, 50, 310-315.[CrossRef] [PubMed]
[22] Norling, R., Buron, B.M.D., Therkildsen, M.H., Henriksen, B.M., von Buchwald, C. and Nielsen, M.B. (2014) Staging of Cervical Lymph Nodes in Oral Squamous Cell Carcinoma: Adding Ultrasound in Clinically Lymph Node Negative Patients May Improve Diagnostic Work-Up. PLOS ONE, 9, e90360.[CrossRef] [PubMed]
[23] Driessen, D.A.J.J., Dijkema, T., Weijs, W.L.J., Takes, R.P., Pegge, S.A.H., Zámecnik, P., et al. (2021) Novel Diagnostic Approaches for Assessment of the Clinically Negative Neck in Head and Neck Cancer Patients. Frontiers in Oncology, 10, Article ID: 637513.[CrossRef] [PubMed]
[24] Shoaib, T., Soutar, D.S., MacDonald, D.G., Camilleri, I.G., Dunaway, D.J., Gray, H.W., et al. (2001) The Accuracy of Head and Neck Carcinoma Sentinel Lymph Node Biopsy in the Clinically N0 Neck. Cancer, 91, 2077-2083.[CrossRef] [PubMed]
[25] Narayana, M.L., Kumarguru, B.N., Arafath A., H., Gaur, U., Lakshmi, P. and Sravani, A.L. (2020) Correlation of Clinical, Radiological and Histopathological Cervical Lymph Node Involvement in Oral Cancer. International Journal of Otorhinolaryngology and Head and Neck Surgery, 6, 311-315.[CrossRef]
[26] Suryavanshi, S., Kumar, J., Manchanda, A., Singh, I. and Khurana, N. (2021) Comparison of CECT and CT Perfusion in Differentiating Benign from Malignant Neck Nodes in Oral Cavity Cancers. European Journal of Radiology Open, 8, Article 100339.[CrossRef] [PubMed]
[27] Sumi, M., Ohki, M. and Nakamura, T. (2001) Comparison of Sonography and CT for Differentiating Benign from Malignant Cervical Lymph Nodes in Patients with Squamous Cell Carcinoma of the Head and Neck. American Journal of Roentgenology, 176, 1019-1024.[CrossRef] [PubMed]
[28] Saafan, M.E. (2013) Assessment of Cervical Lymph Nodes in Squamous Cell Carcinoma of the Head and Neck. Surgery: Current Research, 3, Article 1000145.[CrossRef]
[29] Imhof, H., Czerny, C. and Dirisamer, A. (2003) Head and Neck Imaging with MDCT. European Journal of Radiology, 45, S23-S31.[CrossRef] [PubMed]
[30] Lima, A., Meira, I., Soares, M., Bonan, P., Mélo, C. and Piagge, C. (2021) Delay in Diagnosis of Oral Cancer: A Systematic Review. Medicina Oral Patología Oral y Cirugia Bucal, 26, e815-e824.[CrossRef] [PubMed]
[31] Sharma, R., Mehta, N., Madhok, R., Agrawal, T. and Sharma, V. (2018) A Clinical, Radiological, and Histopathological Correlation of Neck Nodes in Patients Undergoing Neck Dissection. International Journal of Applied and Basic Medical Research, 8, 15-19.[CrossRef] [PubMed]
[32] Andersen, P.E., Warren, F., Spiro, J., Burningham, A., Wong, R., Wax, M.K., et al. (2002) Results of Selective Neck Dissection in Management of the Node-Positive Neck. Archives of OtolaryngologyHead & Neck Surgery, 128, 1180-1184.[CrossRef] [PubMed]
[33] Nithya, C., Pandey, M., Naik, B. and Ahamed, I.M. (2003) Patterns of Cervical Metastasis from Carcinoma of the Oral Tongue. World Journal of Surgical Oncology, 1, Article No. 10.[CrossRef] [PubMed]
[34] Koech, K.J., Bulimo, W., Karanja, S. and Wanzala, P. (2021) Sociodemographic, Clinical and Pathological Features of Oral Squamous Cell Carcinoma in a Kenyan Centre. East African Medical Journal, 98, 4316-4324.
[35] Noda, Y., Ishida, M., Ueno, Y., Fujisawa, T., Iwai, H. and Tsuta, K. (2022) Novel Pathological Predictive Factors for Extranodal Extension in Oral Squamous Cell Carcinoma: A Retrospective Cohort Study Based on Tumor Budding, Desmoplastic Reaction, Tumor-Infiltrating Lymphocytes, and Depth of Invasion. BMC Cancer, 22, Article No. 402.[CrossRef] [PubMed]
[36] Kligerman, J., Lima, R.A., Soares, J.R., Prado, L., Dias, F.L., Freitas, E.Q., et al. (1994) Supraomohyoid Neck Dissection in the Treatment of T1/T2 Squamous Cell Carcinoma of Oral Cavity. The American Journal of Surgery, 168, 391-394.[CrossRef] [PubMed]
[37] Evan Roche, R. and Ciska-Mari, S. (2021) The Correlation between Clinical and Pathological Lymph Node Status in Oral Squamous Cell Carcinoma. Journal of Oral Cancer and Research, 4, 49-56.[CrossRef]
[38] Li, L., Sun, J., Li, B., Li, C., Li, Y., Su, F., et al. (2015) Computed Tomography versus Magnetic Resonance Imaging for Diagnosing Cervical Lymph Node Metastasis of Head and Neck Cancer: A systematic Review and Meta-Analysis. OncoTargets and Therapy, 8, 1291-1313.[CrossRef] [PubMed]
[39] Koyfman, S.A., Ismaila, N., Crook, D., D’Cruz, A., Rodriguez, C.P., Sher, D.J., et al. (2019) Management of the Neck in Squamous Cell Carcinoma of the Oral Cavity and Oropharynx: ASCO Clinical Practice Guideline. Journal of Clinical Oncology, 37, 1753-1774.[CrossRef] [PubMed]

Copyright © 2026 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.