AJR AJR-based Continuing Ed for Technologists
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
 QUICK SEARCH:   [advanced]


     


This Article
Right arrow Abstract Freely available
Right arrow Figures Only
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Sumi, M.
Right arrow Articles by Nakamura, T.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Sumi, M.
Right arrow Articles by Nakamura, T.
Social Bookmarking
 Add to CiteULike   Add to Complore   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?
Hotlight (NEW!)
Right arrow
What's Hotlight?
DOI:10.2214/AJR.04.1832
AJR 2006; 186:749-757
© American Roentgen Ray Society


Original Research

MR Microimaging of Benign and Malignant Nodes in the Neck

Misa Sumi1, Marc Van Cauteren2 and Takashi Nakamura1

1 Department of Radiology and Cancer Biology, Nagasaki University School of Dentistry, 1-7-1 Sakamoto, Nagasaki 852-8588, Japan. Address correspondence to T. Nakamura
2 Philips Medical Systems, Toyko, Japan.

Received November 30, 2004; accepted after revision February 1, 2005.

 
Address correspondence to T. Nakamura (taku{at}net.nagasaki-u.ac.jp).


Abstract
Top
Abstract
Introduction
Subjects and Methods
Results
Discussion
References
 
OBJECTIVE. We evaluated the diagnostic criteria of high-resolution MRI in differentiating benign and malignant cervical nodes that were palpable and superficial in the neck.

SUBJECTS AND METHODS. We performed MR microimaging on 24 histologically proven metastatic nodes, 14 histologically proven lymphomas, and 35 histologically or clinically proven benign nodes in the necks of 26 patients. The lymph nodes were imaged with T1-weighted spin-echo, fat-suppressed T2-weighted turbo spin-echo, and spin-echo diffusion-weighted echo-planar sequences using a 47-mm microscopy coil.

RESULTS. MR microimaging provided high-resolution images of the nodes. Hilar fat was lost in 92%, 79%, and 46% of the metastatic nodes, lymphomas, and benign nodes, respectively. Smooth nodal margins were lost in 58%, 23%, and 9% of metastatic nodes, lymphomas, and benign nodes, respectively. Heterogeneous nodal parenchyma on T1- or fat-suppressed T2-weighted images, or both, was observed in 88%, 29%, and 23% of metastatic nodes, lymphomas, and benign nodes, respectively. The apparent diffusion coefficients were significantly different among these three node groups (p < 0.001), with metastatic nodes being the highest, followed by benign nodes. Logistic regression analyses showed that heterogeneous nodal parenchyma and apparent diffusion coefficient levels were significant in discriminating metastatic nodes, and apparent diffusion coefficient levels in discriminating lymphomas. Combined use of these MR microscopic criteria on nodal architecture and apparent diffusion coefficients yielded 90% accuracy (86% sensitivity, 94% specificity) and 93% accuracy (85% sensitivity, 95% specificity) for discriminating metastatic nodes and lymphomas, respectively.

CONCLUSION. The nodal architecture and apparent diffusion coefficient levels on MR microimaging may provide useful information in diagnosing benign and malignant nodes in the neck.

Keywords: cancer • head and neck imaging • lymph nodes • MR microimaging


Introduction
Top
Abstract
Introduction
Subjects and Methods
Results
Discussion
References
 
The presence of lymph node metastasis in the neck of patients with cancer of the head and neck regions is an important prognostic determinant in staging cancers and in planning radiation therapy for cancer patients. For the detection of metastatic nodes in the neck, CT and sonography have been widely used to obtain successful results [1-5]. On the other hand, the performance of MRI in diagnosing metastatic nodes in the neck has not been highly ranked. For instance, MRI criteria regarding the presence or absence of central nodal necrosis yielded an accuracy of 86-87% with T1- or T2-weighted images, but CT yielded higher accuracies (91-96%) [6]. Curtin et al. [7] compared CT and MRI in diagnosing metastatic nodes in the neck to show that CT performed better than MRI when size and parenchymal architecture criteria of the nodes were used.

On CT and MRI, the internal architecture of the node was poorly imaged, and additional evaluation of the parenchymal signals from the node did not significantly improve the diagnostic ability of the size criteria for metastatic nodes [7]. The nodal size alone was also reported to have limited value in the diagnosis of metastatic nodes in the neck [2]. A separate trial using diffusion-weighted MRI was performed for the detection of metastatic nodes to show that the apparent diffusion coefficient (ADC) levels were useful determinants in discriminating metastatic nodes from benign nodes in patients with head and neck cancer [8]. The ADCs also effectively differentiate the nodal lymphomas from metastatic nodes.

Lymph node metastases, which are associated with proliferation and necrosis of cancer cells, angiogenesis, and obliteration of hilar fat, cause drastic changes in the components and structures of the nodes. Recently, an application of the small surface coil has been reported to show detailed architecture of the superficial organs [9]. In this study, we sought to determine whether the assessment of the architecture and ADCs of the nodes on high-resolution MR microimaging using a microscopy coil might be effective in differentiating metastatic nodes, lymphomas, and benign nodes in the neck.


Subjects and Methods
Top
Abstract
Introduction
Subjects and Methods
Results
Discussion
References
 
Patients
MRI was performed on 26 consecutive patients with palpable lymph nodes in the neck. We obtained institutional review board approval from our hospital and informed consent from the patients. The study cohort included 10 patients (average age, 71 years) with head and neck squamous cell carcinoma, six patients (average age, 58 years) with lymphoma, and 10 patients (average age, 35 years) with benign lymphadenopathy. Consequently, we performed MR microimaging of 24 metastatic nodes, 14 nodal lymphomas, and 35 benign nodes in the neck.

All metastatic nodes were surgically removed or biopsied and were histopathologically proven. Of the 10 patients with squamous cell carcinoma, the primary cancers arose in the oropharynx (n = 3), gingiva (n = 3), larynx (n = 3), and tongue (n = 1).

The lymphoma nodes were biopsied or excised and histologic types were determined. The histologic types of the lymphomas were four B-cell neoplasms, including one mantle cell lymphoma, two diffuse large B-cell lymphomas, and one follicular lymphoma; one T-cell neoplasm (peripheral unspecified lymphoma); and one Hodgkin's lymphoma (nodular lymphocyte predominant).

Some of the benign nodes were imaged and biopsied because they were clinically suggestive of malignancy, mainly as a result of their large size; and the remaining benign nodes were clinically evaluated for their responsiveness to treatment with antibiotics after long (6 months) periods of follow-up.

MR Microimaging
MR microimaging was performed using a 1.5-T MR imager (Gyroscan Intera 1.5 T Master, Philips Medical Systems) and a 47-mm microscopy coil. The coil was positioned so that the palpable nodes were under the coil and was secured using adhesive tape. Axial T1-weighted images of the cervical lymph nodes were obtained using a conventional spin-echo sequence (TR/TE, 550/10; number of signal acquisitions, 3). Axial, fat-suppressed SPIR (spectral presaturation with inversion recovery) T2-weighted images of the lymph nodes were obtained using a turbo spin-echo sequence (3,000/90; number of signal acquisitions, 6) and a turbo factor of 11. For all of these sequences, the section thickness was 2 mm. MRI was performed with a matrix of 160 x 128, a field of view of 7 cm, and an interslice gap of 0.2 mm. The acquisition time for each sequence was less than 4 min. To compensate for the image intensity inhomogeneity inherent to the use of small microscopy coils, we used the CLEAR (constant level appearance) postprocessing technique (Philips Medical Systems). CLEAR uses the premeasured sensitivity profile of the coil to calculate the compensation needed to apply to the pixel intensities to achieve even image intensity. The 26 patients also underwent conventional T1- and fat-suppressed T2-weighted imaging for primary cancer lesions and for deeper nodal lesions.

Diffusion-Weighted MR Microimaging
Axial diffusion-weighted images of the nodes were obtained using a single-shot, spin-echo type echo-planar imaging sequence (2,973/121; number of signal acquisitions, 6) using the same 47-mm microscopy coil. The sequence was repeated for two values of motion-probing gradients (b = 500 and 1,000 sec/mm2). The section thickness was 2 mm. Diffusion-weighted MRI was performed with a matrix of 80 x 56, a field of view of 70 mm, and an interslice gap of 0.2 mm. The acquisition time was less than 3 min.

The ADCs were determined using the two b factors, by the following formula:

Formula
where b1 (= 500) and b2 (= 1,000) are gradient factors of sequences S1 and S2, and SI1 and SI2 are signal intensities by sequence S1 and S2, respectively. The two b factors were used to exclude the effects of perfusion in the nodes. The ADC determination was performed in regions of interest (ROIs) placed in the nodes on ADC maps. Each ROI was placed manually in the lymph node on all slices that contained a single node. Each ROI was variable so that it included as much of the nodal parenchyma as possible. The ADC of a node was an average of all values from a single node.

Assessments for Diagnostic Ability
We calculated the sensitivity (number of nodes positive at both imaging and histology / number of nodes positive at histology) and specificity (number of nodes negative at both imaging and histology / number of nodes negative at histology) after varying combinations of MR microimaging criteria determined on T1- and fat-suppressed T2-weighted images plus varying thresholds of ADC value, for discrimination of metastatic nodes, nodal lymphomas, and benign nodes. The accuracy was calculated by the following formula: (number of nodes positive at both imaging and histology + number of nodes negative at both imaging and histology) / total number of nodes.

Positive and negative predictive values were also used to assess the performance of the MRI criteria in the detection of metastatic nodes. The positive and negative predictive values are the percentages of nodes interpreted using the MR microscopic criteria as positive or negative for the particular diagnoses that were positive histopathologically.

Statistical Analyses
Logistic analysis was performed to identify MRI characteristics that could be used as predictive indicators for differentiating metastatic nodes, lymphomas, and benign nodes in the neck. MR images that were found to be important at univariate analysis were entered into multivariate models to determine their independent predictive value. Analysis was performed with the statistical software package SPSS version 6.1 for Windows (SPSS).

Significance in the architectural data and ADC data between the different patient groups was determined using the Fisher's exact probability test, Mann-Whitney U test, or Student's t test, as indicated in the table footnotes, using commercially available statistical software (StatView 4.51, Abacus Concepts).


Results
Top
Abstract
Introduction
Subjects and Methods
Results
Discussion
References
 
Hilum Structure of the Nodes
The hilum structure was depicted as a concavity of the node that was filled with fat tissue (Figs. 1A and 1B). The vessels may be also evident in the hilum on T1-weighted and fat-suppressed T2-weighted MR microimages (Figs. 1A and 1B). The hilar fat, which was depicted as a high-intensity area on T1-weighted images and was a low-intensity area on fat-suppressed T2-weighted images, was lost at a high rate in metastatic nodes (92%) but was also lost in nodal lymphomas (79%) and in benign nodes (46%) (Table 1). The difference was significant only between metastatic and benign nodes.


Figure 1
View larger version (105K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 1A —27-year-old healthy male volunteer with enlarged node at level I. Axial T1-weighted (TR/TE, 550/10) MR microimage shows homogeneous parenchyma (arrow) associated with hilum structures containing fat tissue and blood vessels (arrowheads). M = mandible, SMG = submandibular gland. Scale bar indicates 1 cm.

 

Figure 2
View larger version (93K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 1B —27-year-old healthy male volunteer with enlarged node at level I. Axial fat-suppressed T2-weighted (3,000/90) MR microimage shows same node as in A, with homogeneously hyperintense nodal parenchyma (arrow) contrasting with hypointense fat tissue and hyperintense blood vessels (arrowheads). Scale bar indicates 1 cm.

 

View this table:
[in this window]
[in a new window]

 
TABLE 1: MR Microimaging Findings of Metastatic Nodes, Nodal Lymphomas, and Benign Nodes in the Neck

 

Margins of the Nodes
We found that T1-weighted imaging was good for the depiction of nodal margins. Nodal margins blending into the surrounding tissue were found in 58% of metastatic nodes (Figs. 2A, 2B, and 2C, Table 1). Irregular margins were also found in some lymphomas (23%) but were rarely observed in benign nodes (9%) (Table 1).


Figure 3
View larger version (126K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 2A —76-year-old man with squamous cell carcinoma of mesopharynx. Axial T1-weighted (TR/TE, 550/10) MR microimage shows irregular or blending nodal margin of metastatic parotid node (arrows). PG = parotid gland. Scale bar indicates 1 cm.

 

Figure 4
View larger version (101K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 2B —76-year-old man with squamous cell carcinoma of mesopharynx. Axial fat-suppressed T2-weighted (3,000/90) MR microimage shows hypointense parenchyma blending into surrounding tissue (arrows). Scale bar indicates 1 cm.

 

Figure 5
View larger version (190K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 2C —76-year-old man with squamous cell carcinoma of mesopharynx. Photomicrograph shows extensive proliferation of metastatic cancer cells with destruction of nodal capsule (arrow). Necrotic areas are rarely seen. (H and E, original magnification x1.6)

 

Parenchymal Architecture of the Nodes
Metastatic nodes frequently (88%) exhibited heterogeneous architecture of the parenchyma on T1- or fat-suppressed T2-weighted MR microimages, or both (Table 1). MR microimaging showed that metastatic nodes contained hypointense to intermediately intense areas indicative of cancer cell nests and interstitial fibrous tissue with (Figs. 3A, 3B, 3C, 4A, 4B, 4C, 4D, 4E, and 4F) or without (Figs. 4A, 4B, 4C, 4D, 4E, and 4F) central hyperintense areas indicative of liquefaction necrosis on fat-suppressed T2-weighted images. These changes in nodal architecture were depicted well on fat-suppressed T2-weighted images compared with T1-weighted images (Table 2).


Figure 6
View larger version (106K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 3A —70-year-old man with squamous cell carcinoma in larynx. Axial T1-weighted (TR/TE, 550/10) MR microimage shows heterogeneous parenchyma of metastatic node at level IV (arrow). Scale bar indicates 1 cm.

 

Figure 7
View larger version (88K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 3B —70-year-old man with squamous cell carcinoma in larynx. Axial fat-suppressed T2-weighted (3,000/90) MR microimage shows heterogeneous nodal parenchyma associated with large hyperintense area (arrow). Note thin intermediate to hypointense zone demarcating hyperintense area. Scale bar indicates 1 cm.

 

Figure 8
View larger version (196K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 3C —70-year-old man with squamous cell carcinoma in larynx. Photomicrograph shows large area of necrosis (N). In juxtanecrotic area are proliferating cancer cells (C). (H and E, original magnification x1.6)

 

Figure 9
View larger version (123K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 4A —62-year-old man with squamous cell carcinoma of mesopharynx. Axial T1-weighted (TR/TE, 550/10) MR microimage shows relatively homogeneous metastatic nodes at level II (arrows). SMG = submandibular gland. Scale bar indicates 1 cm.

 

Figure 10
View larger version (117K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 4B —62-year-old man with squamous cell carcinoma of mesopharynx. Axial fat-suppressed T2-weighted (3,000/90) MR microimage shows heterogeneous parenchyma (large arrows) with hypointense focus (small arrows) in two metastatic nodes. Note that proximal node (P) also exhibits small hyperintense areas (arrowhead). Scale bar indicates 1 cm.

 

Figure 11
View larger version (166K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 4C —62-year-old man with squamous cell carcinoma of mesopharynx. Photomicrograph shows metastatic node (node "P" in B) with cyst formation (N), which has cancer cell lining. C = cancer cell nests. (H and E, original magnification x1.6)

 

Figure 12
View larger version (112K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 4D —62-year-old man with squamous cell carcinoma of mesopharynx. Axial T1-weighted (550/10) MR microimage shows homogeneous nodal parenchyma of metastatic node at level II (arrow). SMG = submandibular gland. Scale bar indicates 1 cm.

 

Figure 13
View larger version (98K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 4E —62-year-old man with squamous cell carcinoma of mesopharynx. Axial fat-suppressed T2-weighted (3,000/90) MR microimage shows heterogeneous parenchyma (large arrow) with hypointense area (small arrow). Scale bar indicates 1 cm.

 

Figure 14
View larger version (131K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 4F —62-year-old man with squamous cell carcinoma of mesopharynx. Photomicrograph shows large area of cancer cell nests (C) and residual lymphoid tissues of node (L). Arrowhead indicates dense fibrous stroma among cancer nests. Note that no apparent liquefaction necrosis is evident. (H and E, original magnification x1.6)

 

View this table:
[in this window]
[in a new window]

 
TABLE 2: Heterogeneity of Nodal Parenchyma

 

Heterogeneous architecture of the nodal parenchyma was also evident in some lymphomas (29%) and benign nodes (23%), but the incidence was significantly low compared with metastatic nodes (Table 1). Basically, lymphomas exhibited homogeneous architecture. However, lymphomas may be associated with narrowed hilum and blood vessels, which were depicted as the so-called small-vessel sign [10] on fat-suppressed T2-weighted images (Figs. 5A, 5B, and 5C). In two cases of lymphomas (diffuse large B-cell type), unenhanced foci were noted, suggestive of necrosis. Unlike metastatic nodes, however, these foci were hypointense on T2-weighted images.


Figure 15
View larger version (131K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 5A —53-year-old man with non-Hodgkin's lymphoma (follicular lymphoma) at level I. Axial T1-weighted (TR/TE, 550/10) MR microimage shows homogeneous node (large arrow) lacking hilar fat structure. Hypointense streaks ("small-vessel" sign) (small arrow) radiating toward periphery of node are evident. Scale bar indicates 1 cm.

 

Figure 16
View larger version (102K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 5B —53-year-old man with non-Hodgkin's lymphoma (follicular lymphoma) at level I. Axial fat-suppressed T2-weighted (3,000/90) MR microimage shows homogeneously hyperintense parenchyma (large arrow) and small-vessel sign (small arrow). Scale bar indicates 1 cm.

 

Figure 17
View larger version (115K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 5C —53-year-old man with non-Hodgkin's lymphoma (follicular lymphoma) at level I. Photomicrograph shows proliferating lymphoma cells occupying entire node. (H and E, original magnification x1.6)

 
In benign (inflammatory) nodes, we noted hyperintense streaks or hypointense foci (Figs. 6A, 6B, and 6C) on fat-suppressed T2-weighted images; the characteristic MRI features were noted in 17% (6/35) of benign nodes. Doppler sonography showed that these foci and streaks in inflammatory nodes were blood vessels (Figs. 6A, 6B, and 6C).


Figure 18
View larger version (135K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 6A —52-year-old woman with lymphadenitis of nodes at level II. Axial T1-weighted (TR/TE, 550/10) MR microimage shows homogeneous parenchyma (arrow). PG = parotid gland. Scale bar indicates 1 cm.

 

Figure 19
View larger version (134K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 6B —52-year-old woman with lymphadenitis of nodes at level II. Axial fat-suppressed T2-weighted (3,000/90) MR microimage shows hypointense area (small arrow) in center of parenchyma (large arrow), from which hyperintense striations radiate to periphery. Scale bar indicates 1 cm.

 

Figure 20
View larger version (104K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 6C —52-year-old woman with lymphadenitis of nodes at level II. Power Doppler sonogram shows blood flow signals in hilar region.

 
ADC of the Nodes
Next we compared the ADCs of the nodes in three disease groups (Fig. 7). The ADC of metastatic nodes (1.167 ± 0.447 x 10-3 mm2/sec) was significantly higher than that of benign nodes (0.652 ± 0.101 x 10-3 mm2/sec) and that of lymphomas (0.601 ± 0.427 x 10-3 mm2/sec). The ADC of the lymphomas was significantly lower than that of the benign nodes, whereas atypical lymphomas, which were associated with necrosis in the lesions (not shown), exhibited higher ADC levels compared with the remaining typical lymphomas.


Figure 21
View larger version (13K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 7 —Graph of box plots shows apparent diffusion coefficient (ADC) levels of metastatic nodes, nodal lymphomas, and benign nodes. Horizontal line in each box is median (50th percentile) of measured values; top and bottom of boxes represent 25th and 75th percentiles, respectively; and whiskers indicate range from largest to smallest observed data points within 1.5 interquartile range presented by box. Values for p were determined using Mann-Whitney U test. Circles = outliers.

 
Diagnostic Ability of MR Microscopic Criteria in Discriminating Nodal Diseases
To evaluate the diagnostic significance of the MR microimaging findings, we first performed logistic regression analyses. On univariate analysis, the absence of hilar fat, the irregular margins, the heterogeneous parenchyma on T1- or fat-suppressed T2-weighted images, and the ADCs were statistically significant in differentiating metastatic nodes (Table 3). For nodal lymphomas, the nodal size and the ADCs significantly contributed to the diagnosis (Table 4).


View this table:
[in this window]
[in a new window]

 
TABLE 3: Logistic Regression Analysis of Diagnostic Criteria for Metastatic Nodes

 

View this table:
[in this window]
[in a new window]

 
TABLE 4: Logistic Regression Analysis of Diagnostic Criteria for Lymphomas

 

On multivariate analysis, however, the heterogeneous parenchyma and the ADCs were statistically significant in differentiating metastatic nodes from benign nodes or nodal lymphomas (Table 3). On the other hand, only the ADCs were statistically significant in differentiating lymphomas from the other two entities (Table 4).

Finally, we assessed the diagnostic ability of MRI findings using combined criteria of nodal architecture and ADCs. The best results we obtained were as follows: When a node was diagnosed as metastatic if it exhibited heterogeneous parenchyma on T1- or fat-suppressed T2-weighted images and an ADC equal to or greater than 0.73 x 10-3 mm2/sec, we obtained 83% sensitivity, 94% specificity, 87% positive and 92% negative predictive values, and 90% accuracy. When a node was diagnosed as lymphoma if it had an ADC equal to or less than 0.51 x 10-3 mm2/sec, we obtained 86% sensitivity, 95% specificity, 80% positive and 97% negative predictive values, and 93% accuracy.


Discussion
Top
Abstract
Introduction
Subjects and Methods
Results
Discussion
References
 
We have presented our early results on MR microimaging features characteristic of benign and malignant nodes in the neck. We found that the details of the nodal structures obtained with the microscopy coil were informative in differentiating metastatic nodes, nodal lymphomas, and benign nodes in the neck. We also found that good performance was obtained with criteria based on the presence or absence of hilar fat, heterogeneous parenchyma on T1- or fat-suppressed T2-weighted images, or both, and on the varying ADC cutoff points.

Proliferating metastatic cells frequently extend into the nodal hilum, thereby obstructing the hilum. The intact hilum contains fat tissue, blood vessels, and efferent lymphatic vessels, and thus the loss of fat tissue in the hilum has been an important imaging feature highly suggestive of metastatic nodes [1, 2]. However, conventional MRI inconsistently detects this feature. The high-resolution images on MR microscopy coils enable efficient assessment of the nodal structures on T1-weighted and fat-suppressed T2-weighted images. It is interesting to assume that when metastatic foci are small, and the intact hilar structures are not yet obliterated, the heterogeneous MR signals from proliferating cancer cells may be more critical than the loss of hilar structures in diagnosing metastatic nodes. Our results support this notion (Table 3).

Loss of the hilar fat was most frequently observed in, but not limited to, the metastatic nodes. Hilar fat was lost in 79% of nodal lymphomas and in 46% of benign nodes. Consequently, loss of hilar fat was a significant finding differentiating metastatic from benign nodes but not from lymphomas (Table 1). Previous studies using sonography showed that hilum structures with or without vascular flow signals were frequently lost or narrowed in lymphomas [11, 12]. Our MRI findings were consistent with these previous studies.

The heterogeneity of the internal architecture of the nodes on MR images may be due to the presence of necrosis, cancer nests, and interstitial fibrous tissue, which has been considered to be a pathognomonic feature for metastatic nodes from head and neck squamous cell carcinomas [13]. We found in this study that heterogeneous parenchyma was a significant finding for discriminating metastatic nodes from lymphomas and benign nodes (Table 1). Central nodal necrosis was reported to occur in 32% of metastatic nodes [14]. Enhanced CT may be more effective than unenhanced CT or enhanced MRI in detecting nodal necrosis [6]. However, a recent report showed that no significant difference occurred in sensitivity or specificity for detecting nodal necrosis between enhanced CT and enhanced MRI [15].

In our study, high-resolution imaging using a microscopy coil showed that the hyperintense areas were surrounded by rims or areas that were hypointense relative to the residual nodal parenchyma. Histologic evaluation confirmed that such hypointense areas corresponded to cancer cell nests, which were composed of proliferating cancer cells and coagulation necrosis, and to surrounding fibrous tissue. On the other hand, central hyperintense areas were caused by liquefaction necrosis. Hypointense foci with or without hyperintense areas on fat-suppressed T2-weighted images were noted in 67% of the metastatic nodes and in 14% and 9% of lymphomas and benign nodes, respectively (Table 2). Considering the reportedly low incidence of central nodal necrosis in metastatic nodes in the neck [14], a combined use of these MR microimaging features (hyperintense focus of central nodal necrosis plus hypointense area) on fat-suppressed T2-weighted images may be a better MR criterion than central nodal necrosis alone for the diagnosis of metastatic nodes.

We found in this study that heterogeneous parenchyma was not an MRI feature limited to metastatic nodes, but was also observed in nodal lymphomas and even in benign nodes. Our finding that heterogeneous architecture of the nodes occurred in approximately 30% of nodal lymphomas was unexpected. The observed heterogeneity in the nodal architecture may be due to the presence of necrotic areas. Necrosis is well described in Hodgkin's disease, but it has been considered to be uncommon in head and neck non-Hodgkin's disease. King et al. [16] reported that 27% of non-Hodgkin's disease in the neck was associated with necrosis. Thus, the notion that the homogeneous MRI architecture is characteristic of nodal lymphomas is open to dispute.

ADC measurement may shed light on other aspects of the diseased nodes and may provide additional information distinct from the morphologic features. Among the three nodal diseases, ADCs were highest in metastatic nodes and lowest in lymphomas (Fig. 7). A previous study showed that ADCs were significantly different among metastatic nodes, nodal lymphomas, and benign nodes [8, 17]. In our study, we confirmed that the ADC measurements significantly and independently contributed to the discrimination of metastatic nodes and nodal lymphomas in the neck (Tables 3 and 4). We conclude that a node that has an ADC value equal to or less than 0.51 x 10-3 mm2/sec is highly suggestive of lymphoma.

The MR microimaging technique has some limitations in the evaluation of head and neck lymph nodes: First, MR microimaging requires additional time for the examination and evaluation of the image data. Second, the small field of view makes it difficult to see the surrounding structures and the exact location of lymph nodes. Third, the technique does not apply to deep nodes. A rapid and sensitive MRI technique, such as a STIR turbo sequence coupled with parallel imaging (SENSE [sensitivity encoding]), would be useful to survey suspicious nodes in the neck before an extensive examination with a microscopy coil.

In the present study we examined relatively larger nodes that were 8 mm or more in the long-axis diameter on axial images. MR microscopy may be useful for the diagnosis of nodes that are relatively large, but size criteria alone are not effective in differentiating metastatic nodes in the neck. However, an answer to the question whether MR microscopy is also useful in the diagnosis of smaller (< 8 mm) nodes, and in the effective detection of micrometastasis, must be revealed by future studies.

In conclusion, high-resolution MRI using a microscopy coil can effectively characterize the morphologic details of benign and metastatic nodes in the neck without using gadolinium enhancement. This technique provided better results than previous studies using MRI and CT [7]. In particular, a palpable node in the neck that exhibits heterogeneous parenchyma on T1- or fat-suppressed T2-weighted images, or both, and also has an ADC value equal to or greater than 0.73 x 10-3 mm2/sec is suggestive of a metastatic node, whereas a node that has an ADC value equal to or less than 0.51 x 10-3 mm2/sec is suggestive of lymphoma. Therefore, the proposed MRI technique may be the primary technique for palpable nodes in the neck.


References
Top
Abstract
Introduction
Subjects and Methods
Results
Discussion
References
 

  1. Ariji Y, Kimura Y, Hayashi N, et al. Power Doppler sonography of cervical lymph nodes in patients with head and neck cancer. AJNR 1998; 19:303 -307[Abstract]
  2. Chikui T, Yonetsu K, Nakamura T. Multivariate feature analysis of sonographic findings of metastatic cervical lymph nodes: contribution of blood flow features revealed by power Doppler sonography for predicting metastasis. AJNR 2000; 21:561 -567[Abstract/Free Full Text]
  3. Yonetsu K, Sumi M, Izumi M, Ohki M, Eida S, Nakamura T. Contribution of Doppler sonography blood flow information to the diagnosis of metastatic cervical nodes in patients with head and neck cancer: assessment in relation to anatomic levels of the neck. AJNR2001; 22:163 -169[Abstract/Free Full Text]
  4. Sumi M, Ohki M, Nakamura T. Comparison of sonography and CT for differentiating benign from malignant cervical lymph nodes in patients with squamous cell carcinoma of the head and neck. AJR2001; 176:1019 -1024[Abstract/Free Full Text]
  5. Eida S, Sumi M, Yonetsu K, Kimura Y, Nakamura T. Combination of helical CT and Doppler sonography in the follow-up of patients with clinical N0 stage neck disease and oral cancer. AJNR2003; 24:312 -318[Abstract/Free Full Text]
  6. Yousem DM, Som PM, Hackney DB, Schwaibold F, Henddrix RA. Central nodal necrosis and extracapsular neoplastic spread in cervical lymph nodes: MR imaging versus CT. Radiology 1992;182 : 753-759[Abstract/Free Full Text]
  7. Curtin HD, Ischwaran H, Mancuso AA, Dalley RW, Caudry DJ, McNeil BJ. Comparison of CT and MR imaging in staging of neck metastases. Radiology 1998;207 : 123-130[Abstract/Free Full Text]
  8. Sumi M, Sakihama N, Sumi T, et al. Discrimination of metastatic cervical lymph nodes with diffusion-weighted MR imaging in patients with head and neck cancer. AJNR 2003;24 : 1627-1634[Abstract/Free Full Text]
  9. Kanemaki Y, Kurihara Y, Itoh D, et al. MR mammary ductography using a microscopy coil for assessment of intraductal lesions. AJR 2004; 182:1340 -1342[Free Full Text]
  10. Majer MC, Hess CF, Kölbel G, Schmiedl U. Small arteries in peripheral lymph nodes: a specific US sign of lymphomatous involvement. Radiology 1988;168 : 241-243[Abstract/Free Full Text]
  11. Na DG, Lim HK, Byun HS, Kim HD, Ko YH, Baek JH. Differential diagnosis of cervical lymphadenopathy: usefulness of color Doppler sonography. AJR 1997; 168:1311 -1316[Abstract/Free Full Text]
  12. Papakonstantinou O, Bakantaki A, Paspalaki P, Charoulakis N, Gourtsoyiannis N. High-resolution and color Doppler ultrasonography of cervical lymphadenopathy in children. Acta Radiol2001; 42:470 -476[CrossRef][Medline]
  13. Ishikawa M, Anzai Y. MR imaging of lymph nodes in the head and neck. Magn Reson Imaging Clin N Am 2002;10 : 527-542[CrossRef][Medline]
  14. van den Brekel MW, Stel HV, Castelijins JA, et al. Cervical lymph node metastasis: assessment of radiologic criteria. Radiology 1990;177 : 379-384[Abstract/Free Full Text]
  15. King AD, Tse GMK, Ahuja AT, et al. Necrosis in metastatic neck nodes: diagnostic accuracy of CT, MR imaging, and US. Radiology 2004;230 : 720-726[Abstract/Free Full Text]
  16. King AD, Lei KI, Ahuja AT. MRI of neck nodes in non-Hodgkin's lymphoma of the head and neck. Br J Radiol2004; 77:111 -115[Abstract/Free Full Text]
  17. Wang J, Takashima S, Takayama F, et al. Head and neck lesions: characterization with diffusion-weighted echo-planar MR imaging. Radiology 2001;220 : 621-630[Abstract/Free Full Text]

Add to CiteULike CiteULike   Add to Complore Complore   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati    What's this?


This article has been cited by other articles:


Home page
RadioGraphicsHome page
C. S. Whittaker, A. Coady, L. Culver, G. Rustin, M. Padwick, and A. R. Padhani
Diffusion-weighted MR Imaging of Female Pelvic Tumors: A Pictorial Review
RadioGraphics, May 1, 2009; 29(3): 759 - 774.
[Abstract] [Full Text] [PDF]


Home page
RadiologyHome page
V. Vandecaveye, F. De Keyzer, V. Vander Poorten, P. Dirix, E. Verbeken, S. Nuyts, and R. Hermans
Head and Neck Squamous Cell Carcinoma: Value of Diffusion-weighted MR Imaging for Nodal Staging
Radiology, April 1, 2009; 251(1): 134 - 146.
[Abstract] [Full Text] [PDF]


Home page
RadiologyHome page
K. Tanitame, K. Sasaki, T. Sone, S. Uyama, M. Sumida, T. Ichiki, and K. Ito
Anterior Chamber Configuration in Patients with Glaucoma: MR Gonioscopy Evaluation with Half-Fourier Single-Shot RARE Sequence and Microscopy Coil
Radiology, October 1, 2008; 249(1): 294 - 300.
[Abstract] [Full Text] [PDF]


Home page
Am. J. Neuroradiol.Home page
Y. Kimura, M. Sumi, N. Sakihama, F. Tanaka, H. Takahashi, and T. Nakamura
MR Imaging Criteria for the Prediction of Extranodal Spread of Metastatic Cancer in the Neck
AJNR Am. J. Neuroradiol., August 1, 2008; 29(7): 1355 - 1359.
[Abstract] [Full Text] [PDF]


Home page
Am. J. Neuroradiol.Home page
Y. Kawai, M. Sumi, and T. Nakamura
Turbo Short {tau} Inversion Recovery Imaging for Metastatic Node Screening in Patients with Head and Neck Cancer
AJNR Am. J. Neuroradiol., June 1, 2006; 27(6): 1283 - 1287.
[Abstract] [Full Text] [PDF]


This Article
Right arrow Abstract Freely available
Right arrow Figures Only
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Sumi, M.
Right arrow Articles by Nakamura, T.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Sumi, M.
Right arrow Articles by Nakamura, T.
Social Bookmarking
 Add to CiteULike   Add to Complore   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?
Hotlight (NEW!)
Right arrow
What's Hotlight?


HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS