Review
DOI: 10.11152/mu.2013.2066.152.smd1cbj2Abstract
The aim of the paper is to provide a comprehensive overview on the applications of real time sonoelastography (SE) in the diagnosis of superficial lymphadenopathy. Some technical aspects of performing SE are presented as a preamble. The typical appearance of benign and malignant nodes is illustrated. The paper discusses and depicts the various elastographic scores in use. It also provides a critical appraisal of the relative strain ratio (SR) or stiffness index. Shear wave elastography, as a novel technique, is mentioned. In conclusion, hardness on more than 50% of the node surface or SR > 1.5 is fair to good indicators of malignancy. Work is still needed both to fully understand the various appearance of disease and to standardize the application.
Keywords: sonoelastography, lymph nodes, neoplasm
Differentiating benign from malignant superficial lymph nodes with sonoelastography
Sorin M. Dudea, Carolina Botar-Jid, Dana Dumitriu, Dan Vasilescu, Simona Manole, Manuela Lavinia Lenghel
Radiology Department, “Iuliu Haţieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania
Received 10.03.2013 Accepted 30.03.2013 Med Ultrason
2013, Vol. 15, No 2, 132-139
Corresponding author: Sorin M. Dudea Dept. Radiology Str. Clinicilor 1-3
400006 Cluj-Napoca, Cluj, Romania Email: [email protected]
Accurate assessment of the superficial lymph node status is of paramount importance in the treatment plan- ning, follow-up and prognosis of malignancies originat- ing in the head and neck, breast, superficial tissues or in lymphoma. Ultrasonography (US) is extensively used as a first line diagnostic means, due to its cost-effectiveness, ease of use and high resolution of provided information.
However, grey-scale and Doppler information are lim- ited either in sensitivity or specificity and no single US criterion has sufficient diagnostic accuracy [1-5].
Sonoelastography (SE) depicts the relative stiffness of tissues. Beyond breast, prostate and thyroid applica- tions, over the last five years, the method was also used as a complimentary imaging technique to conventional US for the assessment of superficial lymph nodes [6- 9]. Assessment of nodal SE information is done either by grading the appearance on a score system (elasticity score – ES) or by calculating a relative stiffness or strain ration (SR) [10].
The aim of this paper is to review the current status of the knowledge on the applications of SE in the diagnosis of the character of superficial lymphadenopathy.
Technical aspects
Real-time sonoelastography is, essentially, an elabo- rate speckle tracking technique with autocorrelation for out-of-plane displacement of the target [11,12]. It provides information about the relative stiffness of the structures within the scan plane, inside a region of inter- est (ROI). It is, therefore, important to encompass in the scan area not only the target lesion but also surrounding
„normal” reference soft tissues. There are no standard recommendations on how to achieve this. In our experi- ence [13,14], the upper limit of the ROI should always be placed as close to the transducer as possible. When aim- ing to use ES, the ROI should exceed the target bounda- ries at least 5 mm on each side. When the purpose is to calculate SR, the ROI should be as wide as possible, to encompass both the target lesion and the surrounding, reference tissue, at the same depth with the lesion. Trans- ducer stabilizer, although desirable, is difficult to use of curved surfaces such as neck or axilla. During compres- sion the transducer should be perpendicular to the skin surface and the compression quality factor, whenever
available, should be comprised within the optimal range (our group only uses quality factor 3 or 4) [15]. The most representative image obtained with optimal compression factor is stored for further assessment.
Some groups [7,16] suggest encompassing the target area and peripheral reference tissue in the approximate same proportion within the ROI. Other authors [17,18]
suggest that the lymph node should occupy no more than 30% of the ROI and neighboring tissue at least 70%. It is, however, important to avoid the presence of bone or blood vessels in the scan area, as it may alter the overall image interpretation.
Debate is on its way on how to represent stiffness in real time sonoelastography. The first commercially avail- able machines depicted hard areas in blue and soft areas in red. However, nowadays more and more manufactur- ers choose the opposite.
Benign lymph nodes
Inflammatory or reactive lymph nodes, not contain- ing metastatic deposits, have the same SE appearance as the soft tissues of the neck and are scarcely visible as distinct entities on SE images [6]. They contain almost no hard, blue areas or, when present, sparse blue areas occupy less than 45% of the node surface [7]. Benign nodes are mostly displayed in colors of yellow, green and turquoise, color red being never encountered and blue of sparse and inconstant occurrence. On the color scale, nodal cortex appears harder than the medulla [17] (fig 1).
Unfortunately, not all non-malignant nodes comply with this appearance. Tuberculous nodes, with scarring, calcification or necrosis may display hard areas [18] or a mixture of colors. Little is still known about the SE ap- pearance of relapsing or chronic lymphadenitis and there are no reports on the SE aspect in rare benign disease such as Kikuchi or Kimura disease.
Malignant lymph nodes
On SE images, malignant nodes stand out from neigh- boring tissues, due to their increased stiffness [6]. Blue areas, depicting rigid, hard tissue, occupy more than 45%
of the lymph node area [7]. Red, yellow and green are not encountered in malignant deposit areas, where stiff tissue is depicted only in turquoise and blue [17]. The cortex is stiffer than the medulla or the node is uniformly hard (fig 2).
The assumption that malignant tissue is harder than surrounding normal tissue is only true for the majority of cases but not for every patient. Focal deposits within a lymph node may produce a small, hard area, occupying
Fig 1. Gray scale (right) and sonoelastogram (left) of a typical benign hypoechoic lymph node (ar- row), displaying almost exclusively hues of orange, yellow, green and turquoise.
Fig 2. Gray scale (right) and sonoelastogram (left) of a typical malignant hypoechoic inhomogeneous lymph node (arrow), displaying almost exclusively blue hues.
Fig 3. Focal metastatic deposits (arrow) that oc- cupy less than 50% of the node surface.
less than 45% of the node surface (fig 3). Some malig- nancies, especially lymphomas, produce „softer” appear- ing nodes, with less blue [15] (fig 4). Necrotic nodes with liquefaction will display an evocative blue-green-red pat- tern (fig 5).
All the above mentioned technical and interpretation- al issues lead to the need of using either a scoring system or a numerical value, in the attempt to better differentiate benign nodes from malignancy.
Elasticity scores and diagnostic value
The SE appearance of the nodes is classified into scores. Several types of scoring are currently in use.
In an early work, using offline processing and no color coding, Lyshchik et al [6] classified the nodes ac- cording to their visualization, brightness compared to neighboring muscle and regularity of the outline (table I).
According to these criteria, malignancy is suggested by partial or intense visibility of the nodes, which are substantially darker or very dark compared to the sur- rounding muscles. On the other hand, margin regular- ity or definition does not allow differentiation of benign from malignant nodes.
Alam et al [7] suggested a five pattern classification system, presented in table II.
All reactive nodes displayed pattern 1 or 2. Most of the metastatic nodes, but not all, displayed patterns 3, 4 or 5. The cutoff value of 45% was obtained by planimetry and statistical analysis.
Another classification, using ES from 1 (entirely soft) to 4 (completely stiff), proposed by Bhatia et al [8], with ES > 2 as a cutoff for malignancy, achieved suboptimal discrimination and fair to good interobserver variability.
Similarly, the classification proposed by Furukawa et al [16,19,20] uses four patterns (table III). Patterns 3 and Fig 4. Malignant lymphoma: node with sizeable
strain and little stiff, blue areas.
Fig 5. Malignant necrotic lymph node displaying the typical blue-green-red pattern (arrow).
Table I. Lymph node appearance on SE and diagnostic value, according to Lyshchik [6]
Score
Criterion 1 2 3 4
Node visualization none Barely Partially intense
Brightness compared to surrounding neck muscles Same or brighter Slightly darker Substantially darker Very dark
Margin irregularity regular slight moderate Very
Definition of node margin Distinct, > 50% Indistinct, < 50%
Table II. Classification of SE appearance of lymph nodes according to Alam [7].
Pattern
1 2 3 4 5
Absent or very small
hard area Hard area < 45%
of lymph node Hard area > 45%
of lymph node Peripheral hard and
central soft area Hard area over the entire node, with or without soft rim
Table III. Classification of SE appearance of lymph nodes proposed by Furukawa [19,20]
Pattern
1 2 3 4
> 80% of the cross sectional area is soft
(red or green) 50 – 80% of the node area is soft
(green or red) 50 – 80 % of the area
is blue > 80% of the node area is blue
4 are only observed in malignant nodes. Pattern 1 and 2 are encountered both in benign and malignant nodes.
More recently, Ishibashi et al [21] proposed another five level scoring system, presented in table IV. Scores 3 to 5 are independent indicators of malignancy.
Table IV. SE scoring system of lymph nodes proposed by Ishibashi [21]
Score (% of blue area on cross section)
1 2 3 4 5
0 <50% 50% >50% Central necrosis
Table V. SE scoring system [15].
Score Description
1 the whole nodule is soft (similar to the surrounding tissues)
2 <50% of the nodule surface is blue and no individualized hypoechoic nodules are seen in the lymph node structure 3 <50% of the nodule surface is blue and individualized soft hypoechoic nodules are seen in the lymph node structure 4 <50% of the nodule surface is blue and individualized hard hypoechoic nodules are seen in the lymph node structure 5 50% - 100% of the nodule surface is blue and no individualized hypoechoic nodules are seen in the lymph node structure 6 50% - 100% of the nodule surface is blue and individualized hard hypoechoic nodules are seen in the lymph node structure 7 the blue area covers the whole nodules and extends in the soft tissues
8 blue (hard) nodule containing fluid areas (necrosis)
Fig 6. Appearance of lymph node types on sonoelastography: a. benign, soft node, type 1 in all scores; b. node with less than 50% hard surface, type 2 in most scores, type 1 by Fu- rukawa [19]; c. Node with central stiff area, occupying more than 50% of the surface, type 3 according to Alam [7] and [19], type 4 according to Ishibashi [21] and type 5 by Lenghel [15]; d. node with central elastic core and hard peripheral rim, more than 50% blue, type 4 by [7] and [21], type 3 by [19], type 5 by [15]; e. the node surface is entirely blue, type 5 by [7], type 4 by [19] and [21], type 7 by [15]; f. Node with central necrosis displaying the blue-green- red pattern, type 5 by [21], type 8 by [15], unclassified by other authors.
Our group proposed a scoring system that takes into account both the SE and the grey scale appearance of the node [15] (table V). Scores 4 to 8 were highly indicative of malignancy. This scoring system takes into account the occurrence of focal metastatic deposits that occupy less than 50% of the node sectional area but may still be depicted as hard foci (score 4).
The various appearances of lymph nodes on sonoe- lastography, according to the suggested scores, are de- picted in figure 6.
Table VI. Diagnostic value of different scoring systems for the SE diagnosis of malignancy in superficial lymph nodes.
Author Reference
Year Criterion SE SP VVP NPV OA AUROC Reference
standard Obs.
Lyshchik [6] 2007
Node visualization ≥
score 3 67 93 87 79 82 – histology – experimental setting, com-
mercially unavailable – only thyroid and hy- popharyngeal metastases Node darker than sur-
rounding tissues (≥ score 3)
63 95 91 78 82 –
Regular or moderately irregular margins (Score
< 3)
35 95 84 66 70 –
>50% of border distinct
(score <3) 48 73 57 66 62 –
Alam [7] 2008
Hard area > 45% of
lymph node (Score ≥ 3) 83 100 100 78 89 0,873 Histology or imaging, follow–up
– commercially available equipment
– metastatic nodes, mixed origin
Zhang [16]
2009
More than 50% of nodal
surface blue (Score > 2) 74,4 97,1 – – 84,5 – FNAB, imaging, follow–up
– using the Furukawa score – mixture of metastatic sources, and lymphoma Bhatia
[8]2010
Score >2 62,2 83,8 73 0,68–0,74
Taylor [22]
2011
Score > 2 90 86 83 93 Axilla, breast cancer
Choi[23]
2011
Score >2 80,7 66,7 73,4 Axilla, breast cancer
Teng[18]
2012
More than 50% of nodal
surface blue (Score > 2) 88,4 35,1 – – 66,3 – Histology and fol- low–up
using the Furukawa score mixture of metastasis of vari- ous sources and lymphoma Ying[10]
2012
Meta–analysis 74 90 0,88
Lenghel [15]
2012
Score ≥ 4 66,67 96,67 – – – 0,846 Histology
and fol- low–up
Benign vs. malignant, lym- phoma included
71,43 96,67 – – – 0,855 Benign vs. metastatic, lym-
phoma excluded
The diagnostic value of the different scoring systems is summarized in table VI.
The possible reasons for the variance in the above re- sults are related to the equipment used, the pathology of the explored lesions, the scoring system applied and the reference standard for diagnosis.
In certain studies, the equipment was experimental.
Commercially available equipment came from at least three different manufacturers, each of them with a pro- prietary implementation of the technology.
muscles. The ROI sizes ranged from 5 – 10 mm. The depth difference of the two ROIs never exceeded 10 mm, in order to avoid the effect of stress decay with depth.
Zhang et al [16] measured the strain ration between the surrounding tissue and the lymph node. However, there was no specification on what surrounding tissue referred to. ROI area and position were also not quantified. Other groups [9,18] calculated the muscle-to-lymph node strain ratio without referring to ROI size or relative position.
Taylor et al [22] compared the lymph node and the (non- specified) background tissue while Choi et al [23] calculated the strain ratio of the lymph node and subcutaneous fat tissue.
The cutoff values and diagnostic benefit of the strain ration is summarized in table VII.
Fig 7. Calculating lymph node to muscle strain ratio.
The studied groups were also very different. In some studies only metastases with a specific origin were as- sessed, while other studies evaluated malignancies with different origin, both metastatic and primary. As shown in more studies, including ours [15], lymphomas show more strain and may alter the overall outcome.
The scoring systems are also very different in layout.
Some use planimetry, which may be tedious or may ne- cessitate specialized software and/or offline processing.
Most of the scores define more than 50% of the node sur- face blue (i.e. hard) as cutoff criterion for malignancy.
This approach does not take into account the fact that elastography may detect small (less than 50%) metastatic deposits into an otherwise normal node [24].
Finally, the reference method used for diagnosing malignancy varied from histology to cytology (FNAB), imaging methods or clinical outcome and follow-up.
Relative stiffness index or strain ratio: calculation and diagnostic value.
Most of real-time elastography scanners provide a means to compare the relative stiffness of two neighbor- ing areas (fig 7).
Lyshchik et al [6] calculated the muscle – to-lymph node strain ratio. The ROIs were placed on the same im- age, over the lymph node and over the surrounding neck
Table VII. Diagnostic value of strain ratio for the SE diagnosis of malignancy in superficial lymph nodes.
Author Reference Year
Strain
index SE SP VVP NPV OA AUROC Reference
standard Obs.
Lyshchik [6]2007
> 1,5 85 98 96 90 92 – histology – experimental setting, commer- cially unavailable
– only thyroid and hypopharyn- geal metastases
Zhang [16]2009
> 2,395 78,41 98,51 0,915 FNAB, imaging,
follow-up – mixture of metastatic sources, and lymphoma
Tan[9]
2010
>1,5 92,8 53,4 70,7 86,1 75 histology Mixture of nonmalignant condi- tions, including tuberculosis and primary and secondary malignan- cies.
Taylor [22]2011
< 0,65 100 48 58 100 Axilla, breast cancer
Choi[23]
2011
>2,3 82,8 56,3 Axilla, breast cancer
Ying[10]
2012
Meta–
analysis 88 81 0,91
The fluctuation in the data has many explanations.
Some of them are common to the already discussed sources of variation encountered in ES nodal assessment (technological implementation, sources of metastases, reference standard for diagnosis). Others are due to the still nonstandardized measurement technique of SR.
Most machines compute strain ratio as B/A where B is the strain of normal, reference tissue and A is the strain of the investigated lymph node. This implies that nodal strain should be measured first (A) and reference tissue strain, second (B). As malignant nodes display little or almost no strain as compared to surrounding reference tissues, as expected, the ratio is greater than one. How- ever, if for any reason, such as measuring reference tissue strain first, the ratio is computed as A/B, the value will be subunitary, as in the paper of Taylor et al [22]. In effect, if A/B is less than 0, 65 then B/A will be greater than 1.53, which is in accordance with some of the other papers.
Another explanation of the variation lies in the tissue used for reference. Intuitively, fat displays more strain than muscle, therefore it is to be expected that, with the same malignant node to be explored, strain ratio using fat for reference (as in the paper of Choi et al [23]) will have a greater value than strain ratio computed with muscle as the reference tissue, as in the papers of Lyshchik et al [6]
or Tan et al [9].
There are still nonquantified issues concerning strain ratio in most papers. Box size, shape and distance from the transducer may represent factors that induce varia- tion. Intra- and interobserver variability are poorly stud- ied and so is inter-image variability for the same case.
Variation associated with manufacturer implementation of the technique is not really known. There is no clear an- swer to how to measure strain ratio in a partially involved node. Different cellularity of the malignant nodes may also induce different elastic behavior [16].
Shear-wave elastography is a rather novel technique that allows for absolute measurement of stiffness in kilo- pascal units. Bhatia et al [25] found that, in the diagnosis benign versus malignant nodes, the value of 30.1 kPa has the accuracy 61.8%, with 41.9% sensitivity, and 100%
specificity. Another group [26] found that mean and max- imal stiffness measurement allows for differentiation of malignant lymph nodes in breast cancer patients assessed for sentinel nodes. With only few papers published on this topic yet, it is not clear what underlies malignant nodal heterogeneity as observed in this technique. Shear wave elastography seems to be rather suited for the diagnosis of a subset of nodes and not for screening purposes [25].
In conclusion, elastography with its various techni- cal implementations seems to be a promising tool that complements standard ultrasonography for the diagnosis
of malignant superficial lymph nodes. Hardness on more than 50% of the node surface or SR > 1.5 are fair to good indicators of malignancy. Much work is still needed both to fully understand the various appearance of disease and to standardize the application.
References
1. Ahuja AT, Ying M, Ho SY, et al. Ultrasound of malignant cervical lymph nodes. Cancer Imaging 2008; 8: 48-56.
2. Neal CH, Daly CP, Nees AV, Helvie MA. Can preoperative axillary US help exclude N2 and N3 metastatic breast can- cer? Radiology 2010; 257: 335-341.
3. Landry CS, Grubbs EG, Busaidy NL, et al. Cystic lymph nodes in the lateral neck as indicators of metastatic papil- lary thyroid cancer. Endocr Pract 2011; 17: 240-244.
4. Choi JS, Kim J, Kwak JY, Kim MJ, Chang HS, Kim EK.
Preoperative staging of papillary thyroid carcinoma: com- parison of ultrasound imaging and CT. AJR Am J Roent- genol 2009; 193:871-878.
5. Dudea SM, Lenghel M, Botar-Jid C, Vasilescu D, Duma M. Ultrasonography of superficial lymph nodes: benign vs.
malignant. Med Ultrason 2012; 14: 294-306.
6. Lyshchik A, Higashi T, Asato R, et al. Cervical lymph node metastases: diagnosis at sonoelastography - initial experi- ence. Radiology 2007; 243: 258-267.
7. Alam F, Naito K, Horiguchi J, Fukuda H, Tachikake T, Ito K. Accuracy of sonographic elastography in the differential diagnosis of enlarged cervical lymph nodes: comparison with conventional B-mode sonography. AJR Am J Roent- genol 2008; 191: 604-610.
8. Bhatia KS, Cho CC, Yuen YH, Rasalkar DD, King AD, Ahuja AT. Real-time qualitative ultrasound elastography of cervical lymph nodes in routine clinical practice: interob- server agreement and correlation with malignancy. Ultra- sound Med Biol 2010; 36: 1990-1997.
9. Tan R, Xiao Y, He Q. Ultrasound elastography: Its potential role in assessment of cervical lymphadenopathy. Acad Ra- diol 2010; 17: 849-855.
10. Ying L, Hou Y, Zheng HM, Lin X, Xie ZL, Hu YP. Re- al-time elastography for the differentiation of benign and malignant superficial lymph nodes: a meta-analysis. Eur J Radiol 2012;81:2576-2584.
11. Ophir J, Cespedes I, Ponnekanti H, Yazdi Y, Li X. Elastog- raphy: a quantitative method for imaging the elasticity of biological tissues. Ultrason Imaging 1991; 13: 111-134.
12. Shiina T, Nitta N, Ueno E, Bamber JC. Real time tissue elasticity imaging using the combined autocorrelation method. J Med Ultrason 2002; 29: 119-128.
13. Ciurea AI, Bolboacă SD, Ciortea CA, Botar-Jid C, Dudea SM. The influence of technical factors on sonoelastographic assessment of solid breast nodules. Ultraschall Med 2011;
32: S27-34.
14. Chiorean AR, Duma MM, Dudea SM, et al. Typical and unusual sonoelastographic patterns of breast cystic lesions:
impact on BI-RADS classification. Ultraschall Med 2012;
33: E138–E144.
15. Lenghel LM, Bolboacă SD, Botar-Jid C, Băciuţ G, Dudea SM. The value of a new score for sonoelastographic dif- ferentiation between benign and malignant cervical lymph nodes. Med Ultrason 2012; 14: 271-277.
16. Zhang Y, Lv Q , Yin Y, et al. The value of ultrasound elas- tography in differential diagnosis of superficial lymph nodes. Front Med China 2009; 3: 368–374.
17. Wojcinski S, Dupont J, Schmidt W, Cassel M, Hillemanns P. Real-time ultrasound elastography in 180 axillary lymph nodes: elasticity distribution in healthy lymph nodes and prediction of breast cancer metastases. BMC Med Imaging 2012; 12 :35.
18. Teng DK, Wang H, Lin YQ, Sui GQ, Guo F, Sun LN. Value of ultrasound elastography in assessment of enlarged cervi- cal lymph nodes. Asian Pac J Cancer Prev 2012; 13: 2081 - 2085.
19. Furukawa MK, Fujita Y, Kubota A, Furukawa M, Hanamu- ra H. Diagnosis of cervical lymph node metastasis of head and neck squamous cell carcinoma - usefulness of Power Doppler ultrasonography and elastography. Medix 2007;
Suppl: 20-23.
20. Furukawa MK, Kubota A, Hanamura H, Furukawa M.
Clinical application of real-time tissue elastography to head and neck cancer—evaluation of cervical lymph node me-
tastasis with realtime tissue elastography. [abstract] Nippon Jibiinkoka Gakkai Kaiho 2007; 110: 503-505.
21. Ishibashi N, Yamagata K, Sasaki H, et al. Real-time tissue elastography for the diagnosis of lymph node metastasis in oral squamous cell carcinoma. Ultrasound Med Biol 2012;
38: 389-395.
22. Taylor K, O’Keeffe S, Britton PD, et al. Ultrasound elastog- raphy as an adjuvant to conventional ultrasound in the pre- operative assessment of axillary lymph nodes in suspected breast cancer: a pilot study. Clin Radiol 2011; 66: 1064- 1071.
23. Choi JJ, Kang BJ, Kim SH, et al. Role of sonographic elas- tography in the differential diagnosis of axillary lymph nodes in breast cancer. J Ultrasound Med 2011; 30: 429- 24. Aoyagi S, Izumi K, Hata H, Kawasaki H, Shimizu H. 436.
Usefulness of real-time tissue elastography for detecting lymph-node metastases in squamous cell carcinoma. Clin Exp Dermatol 2009; 34: e744-747.
25. Bhatia KS, Cho CC, Tong CS, Yuen EH, Ahuja AT. Shear wave elasticity imaging of cervical lymph nodes. Ultra- sound Med Biol 2012; 38: 195-201.
26. Tourasse C, Dénier JF, Awada A, Gratadour AC, Nessah- Bousquet K, Gay J. Elastography in the assessment of sen- tinel lymph nodes prior to dissection. Eur J Radiol 2012;
81: 3154-3159.
