Objectives
To evaluate the diagnostic accuracy of magnetic resonance imaging (MRI) in detecting lymph node metastases in patients with head and neck squamous cell carcinoma (HNSCC).
Methods
MEDLINE, EMBASE, the CBM disc databases, and other databases were searched for relevant original articles published between January 1990 and January 2011. Meta-analysis methods were used to pool sensitivity and specificity and to construct summary receiver-operating characteristic, and to calculate positive and negative likelihood ratios (LR+ and LR-). We also compared the performance of MRI with other diagnostic methods (positron emission tomography, computed tomography, and ultrasound) by analyzing studies that had also used these diagnostic methods on the same patients.
Results
Across 16 studies, there was no evidence of publication bias ( P = .15). Sensitivity and specificity of MRI for cervical lymph node status in patients with HNSCC across all studies were 76% (95% CI: 70%–82%) and 86% (95% CI: 73%–93%), respectively. Overall, Positive likelihood ratios was 5.47 (95% CI: 2.69–11.11) and positive negative likelihood ratios was 0.28 (95% CI: 0.21–0.36), respectively. The comparison of MRI performance with that of other diagnostic tools (positron emission tomography, computed tomography, and ultrasound) suggested no major differences against any of these methods. The Subgroup by using diffusion-weighted imaging had higher pooled sensitivity (0.86, 95% CI 0.78–0.92) than the subgroup without diffusion-weighted imaging.
Conclusion
MRI has good diagnostic performance in the overall pretreatment evaluation of node staging with HNSCC. A limited number of small studies suggest DWI is superior to conventional imaging for nodal staging of HNSCC.
Lymphatic metastasis is an important prognostic factor in patients with head and neck squamous cell carcinoma (HNSCC) . Therefore, accurate assessment of the lymph node status is important for the choice of treatment. Lymph node staging by physical examination is not accurate in discriminating metastatic from benign lymph nodes. Even in superficial areas such as the cervical regions, a physical evaluation of lymph nodes cannot reliably detect metastases . Thus, imaging techniques are often used to enhance the preoperative assessment of cervical lymph node status .
Radiological imaging modalities, such as positron emission tomography (PET), ultrasonography (US), computed tomography (CT) and magnetic resonance imaging (MRI), can be used to support treatment decisions when an unexpected lymph node metastasis is detected on the opposite side in the neck or when it is detected on the ipsilateral side where it is not suspected. Compared to US, CT and MRI are more commonly used to detect cervical lymph node metastases. The main advantage of CT and MRI are the lower interobserver variation, and these techniques are, in general, less time consuming. Compared with PET, PET has potential disadvantages. First, nodal necrosis may cause false-negative findings on PET because of the low glycolytic activity of the necrotic material. Second, false-positive PET results may be caused by inflammatory processes in benign lymph nodes. However, the overall diagnostic accuracy of CT and MRI for detecting node metastases in the HNSCC is insufficient ; sensitivities range from 14% to 80% for CT and from 29% to 85% for MRI , and specificities range from 80% to 100% for both CT and MRI using pathology as the reference standard. Furthermore, a wide variation in patient population, imaging techniques, study design, and results exists. These factors make it difficult for workers in this field to know the exact diagnostic value of these imaging modalities. Thus, whether these imaging techniques perform well enough and whether one modality is superior to others, need answers.
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Materials and methods
Search Strategy
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Studies Selection
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Data Extraction and Quality Assessment
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Data Synthesis and Analysis
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Results
Literature Search and Selection of Studies
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Table 1
The Principal Characteristics Eligible Studies
Study ID Number, Authors Year Number of Patients Design Age (Average) Patient Enrollment Gender (M/F) Blind Field Strength Other Methods Used With DWI, SPIO, or Gd-DTPA Sensitivity Specificity Prevalence Neck Dissection after MR Imaging 1. Dirix P, et al 2010 22 Prospective 60 (41–83) ND 13/9 Blind 1.5-T CT DWI 89 97 23 ND 2. Vandecaveye V, et al 2009 33 Prospective ND (48–81) Consecutive ND Blind 1.5-T None DWI 84 93 25 ND 3. Yoon DY, et al 2009 67 Retrospective 60 (24–85) ND 58/9 Blind 1.5-T CT, US, PET None 77 99 18 3 weeks 4. Krabbe CA, et al 2008 10 Retrospective 59 (53–68) Consecutive ND Blind ND PET, US, CT None 33 50 60 ND 5. Hafidh MA, et al 2006 48 prospective 5 6 (32–80) Consecutive 42/6 ND 1.5-T CT, PET None 50 100 88 ND 6. Akoğlu E et al 2005 23 ND 58.3 (40–78) Consecutive 19/4 ND ND US, CT None 59 100 89 ND 7. Brouwer J, et al 2004 7 ND ND Consecutive ND Blind 1.5-T CT, US, PET None 100 100 29 ND 8. Sigal R, et al 2002 81 ND 54.7 (35–83) ND 73/8 Blind 1.0-T None SPIO 92 40 20 ND 9. Stuckensen T, et al 2000 106 Prospective 59.6 (41–87) ND 89/17 ND ND CT, US, PET Gd-DTPA 64 69 54 15 days 10. Curtin HD, et al 1998 213 ND 63 (18–84) ND 150/63 ND ND CT Gd-DTPA 81 48 40 3–4 weeks 11. Adams S, et al 1998 60 Prospective 58.3 (38–76) Consecutive 44/16 Blind ND CT, US, PET Gd-DTPA 80 79 9 ND 12. Laubenbacher C, et al 1995 22 Prospective ND (38–70) Consecutive 20/2 ND 1.5-T PET Gd-DTPA 78 71 16 2 weeks 13. Braams JW, et al 1995 12 ND 65.3 (55.3–75.3) ND 8/4 Blind 1.5-T PET None 64 69 46 2 weeks 14. Anzai Y, et al 1994 12 ND ND (39–78) ND 7/5 Blind 1.5-T None SPIO 67 94 46 ND 15. van den Brekel MW, et al 1993 132 ND ND Consecutive ND Blind 0.6-T CT, US None 82 81 60 ND 16. Feinmesser R, et al 1990 30 Retrospective ND Consecutive ND ND ND None None 76 78 70 1–4 weeks
CT, computed tomography; DWI, diffusion-weighted magnetic resonance imaging; Gd-DTPA, gadolinium diethylenetriaminepenta-acetic acid; ND, not documented; PET, 18 F-fluorodeoxyglucose positron emission tomography; SPIO, superparamagnetic iron oxide; US, ultrasonography.
The study identification (ID) numbers correspond to study numbers on the graphs in Figures 2 and 5 . Sensitivity, specificity, and prevalence are percentages.
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Study Description, Study Quality, Publication Bias
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Methodological Quality Assessment
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Pooled Sensitivity, Pooled Specificity, Summary ROC Curves, and AUC
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Heterogeneity Assessing and Meta-regression Analysis
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Subgroup Analysis
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Table 2
Diagnostic Accuracy of MRI in Detecting of Cervical Lymph Node Metastasis in Patients with HNSCC
Study Characteristics Reference Numbers Summary Sensitivity, % (95% CI) Summary Specificity, % (95% CI) AUC Diagnostic OR All 0.703 (0.682–0.723) 0.740 (0.726–0.753) 0.8509 15.883 (7.974–31.634) Prospective design 0.675 (0.651–0.698) 0.764 (0.749–0.780) 0.8430 21.392 (7.016–65.221) Retrospective design 0.743 (0.646–0.824) 0.982 (0.962–0.994) 0.5982 16.223 (0.326–808.50) Consecutive 0.775 (0.734–0.813) 0.789 (0.770–0.807) 0.8660 14.896 (7.346–30.209) Nonconsecutive or unclear 0.681 (0.657–0.705) 0.695 (0.674–0.715) 0.8646 19.628 (6.237–61.771) Blind 0.816 (0.782–0.847) 0.777 (0.760–0.793) 0.8810 27.274 (10.951–67.927) Nonblind or unclear 0.656 (0.631–0.681) 0.682 (0.659–0.705) 0.7613 5.241 (3.454–7.953) Conventional MRI 0.735 (0.677–0.787) 0.947 (0.922–0.966) 0.7540 14.052 (3.291–60.001) DWI 0.857 (0.781–0.915) 0.953 (0.926–0.972) 0.5000 136.44 (37.694–493.90)
AUC, area under the curve; DWI, diffusion-weighted MRI; HNSCC, head and neck squamous cell carcinoma; MRI, magnetic resonance imaging.
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Comparison Against Other Diagnostic Methods
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Table 3
Comparison of the Diagnostic Accuracy of MRI with Other Diagnostic Methods
Diagnostic Methods Compared Number of Studies (References) Sensitivity Specificity LR+ LR– AUC 18 F-FDG PET 7 0.662 (0.620–0.680) 0.814 (0.768–0.843) 4.082 (3.413–6.849) 0.286 (0.103–0.454) 0.8043 MRI 0.665 (0.641–0.689) 0.766 (0.750–0.781) 3.621 (2.373–5.525) 0.361 (0.244–0.535) 0.7975 CT 10 0.642 (0.611–0.684) 0.754 (0.632–0.796) 3.123 (2.324–4.215) 0.354 (0.236–0.507) 0.7480 MRI 0.674 (0.650–0.697) 0.787 (0.772–0.803) 5.536 (3.229–9.491) 0.339 (0.222–0.520) 0.7958 US 7 0.445 (0.153–0.764) 0.824 (0.765–0.874) 4.453 (3.568–6.887) 0.349 (0.246–0.546) 0.8126 MRI 0.670 (0.646–0.694) 0.776 (0.759–0.792) 4.104 (2.410–6.991) 0.358 (0.223–0.576) 0.7807
AUC, area under the curve; FDG, [18F]fluorodeoxyglucose; LR, likelihood ratio; MRI, magnetic resonance imaging; PET, positron emission tomography; US, ultrasound.
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Discussion
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Conclusion
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