Practical Applications of Endoscopic Ultrasound-Guided Elastography: Core Principles, Techniques, and Pitfalls

Abstract

Recent advancements in endoscopic technology have established endoscopic ultrasonography (EUS) as a valuable tool for gastroenterologists. The integration of complementary imaging techniques, such as contrast enhancement and elastography, has significantly enhanced the capabilities of EUS. EUS-guided elastography (EUS-E) is an innovative imaging modality that improves the diagnostic accuracy of standard B-mode EUS by measuring the mechanical properties of tissues, particularly their elasticity or stiffness. These measurements are indicative of pathological changes and can aid in differentiating benign from malignant tissues. By combining elastography with EUS, it is now possible to assess tissue stiffness in organs such as the liver, pancreas, and lymph nodes. This approach not only aids in differential diagnosis but also enables the identification of the most accurate areas for EUS-guided tissue acquisition. EUS-E is performed using two main techniques: strain elastography and shear wave elastography, each with distinct advantages and limitations. This article provides an in-depth review of EUS-E, including its principles, techniques, clinical applications, and inherent limitations.

 

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Keywords

endoscopic ultrasonography - EUS-guided elastography - shear wave elastography - liver stiffness - EUS-guided fine needle aspiration/biopsy

Introduction

Endoscopic ultrasonography (EUS) has evolved into a highly valuable diagnostic and therapeutic tool in gastroenterology, offering high spatial resolution that overcomes the limitations of transabdominal ultrasound.[1] [2] While standard B-mode EUS is effective, it has limitations in characterizing solid lesions, as they often appear as hypoechoic, hyperechoic, isoechoic, or heteroechoic without providing detailed information about their nature. This can lead to inaccuracies, especially when inflammation or other features of the lesion, such as fibrosis, neoplasm, or necrosis, obscure the diagnosis. The assessment of vascularity and elasticity enhances the characterization of solid lesions. Ancillary imaging techniques, such as elastography and contrast enhancement, provide detailed insights into lesion characteristics, thus improving the diagnostic utility of EUS.

This article explores EUS-guided elastography (EUS-E) in detail, covering its underlying principles, various techniques, and limitations. A thorough understanding of these aspects can enable clinicians to better utilize this advanced technology for more accurate diagnoses and improved patient outcomes.

 

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Principles of Elastography

Basic Concepts

EUS-E measures the elasticity of tissue, enabling the endosonographer to differentiate areas with varying elastic properties within the target organ. The principle behind elastography is based on the observation that diseased tissues often exhibit different mechanical characteristics compared with healthy tissues. By assessing tissue elasticity, EUS-E can differentiate benign (soft/inflammatory) tissue from malignant (hard/fibrotic) tissue. EUS-E has increasingly been used for the differential diagnosis of solid gastrointestinal tract and pancreatic lesions, offering several advantages over computed tomography and magnetic resonance imaging. Notably, EUS-E can be performed in patients with renal failure and provides the benefit of repeated, dynamic imaging.

 

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Mechanical Properties of Tissues

Elastography evaluates several mechanical properties, including the following:

• Elastic Modulus: Quantifies a material's ability to deform elastically when subjected to stress, which directly correlates to tissue stiffness.

• Viscoelasticity: Reflects the time-dependent strain that a material experiences under stress, influencing tissue behavior, especially in chronic conditions.

• Shear Wave Velocity (SWV): In shear wave elastography (SWE), the speed at which shear waves travel through tissues is directly related to their stiffness. Stiffer tissues show higher SWVs.

 

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Types and Techniques of EUS-E

There are two primary methods of EUS-E ([Fig. 1])[3]: strain elastography and Shear wave elastography (SWE).

Fig. 1 Flowchart describing different types of endoscopic ultrasound (EUS)-guided elastography techniques.

Strain Elastography

Strain elastography measures the strain induced by compression of the target tissue by the EUS probe. The principle is based on the idea that compression of a tissue by an echoendoscope probe creates a strain (i.e., displacement of one tissue structure by another), which varies according to the tissue's hardness or softness ([Fig. 2]). Strain elastography can be performed in two ways:

Fig. 2 This figure describes the basic principles of EUS-guided strain elastography. Based on the hue color map, the hard tissues are represented as dark blue, intermediate tissues are green, followed by soft tissues, which are red.

• Qualitative assessment

• Semiquantitative assessment

Procedure Steps for EUS-Guided Strain Elastography

• Image Acquisition: The following steps should be taken:

  • ○ Use standard EUS imaging to identify the lesion of interest.

  • ○ Apply manual compression to the transducer while maintaining a steady ultrasound image.

  • ○ Capture images during and after compression to assess the tissue response.

• Data Analysis: The ultrasound system gives the color pattern and computes the strain ratio (SR) and strain histogram (SH) between the target lesion and surrounding normal tissue, providing insights into the lesion's characteristics. The following section details how to interpret strain elastography results.

 

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Qualitative Analysis

During EUS-E, color-coded images (red, green, and blue) are overlaid on the standard gray-scale B-mode EUS image. Softer tissues appear red, indicating higher strain, while harder tissues appear dark blue, indicating lower strain. A color map is used to interpret strain values:

• Hard: Dark blue

• Medium-hard: Cyan

• Intermediate: Green

• Medium-soft: Yellow

• Soft tissue: Red

Giovannini et al proposed a scoring system for qualitative strain elastography, where scores of 1 and 2 are grouped as benign and scores of 3 to 5 as malignant ([Fig. 3]).[4] Based on this, sensitivity, specificity, positive predictive value, and negative predictive value for differentiating benign from malignant pancreatic masses were 92.3, 80.0, 93.3, and 77.4%, respectively. [Fig. 4A–F] shows color patterns in different clinical scenarios.

Fig. 3 Figure describing scoring system of qualitative endoscopic ultrasound-guided strain elastography proposed by Giovannini et al.[4]

Fig. 4 (A–F)Qualitative strain elastography (color pattern) in different clinical scenarios. (A, B) Pancreatic head malignancy showing heterogeneous predominantly blue pattern. (C, D) Pancreatic head inflammatory mass with heterogeneous predominantly green pattern. (E, F) Reactive lymph node mass with heterogeneous predominantly green pattern.

Limitations of Qualitative Strain Elastography

• Intraobserver variation/selection bias

• Lack of reproducibility

• Irregular application of pressure

• Inadequate representation of the surrounding tissue

• Overlapping color patterns

• Subjectivity in distinguishing between benign and malignant lesions based on color distribution

 

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Semiquantitative Assessment

This method involves the following:

1. Strain Ratio (SR): SR compares the strain of an area of interest (A) to a reference area (B), calculated as B/A. The SR provides a relative ratio of stiffness between the lesion and the reference area. SR is preferred over qualitative assessment as it helps reduce subjectivity [5]. In a study by Gracia et al, a cutoff SR value of 6.04 demonstrated 100% sensitivity and 92.9% specificity for detecting pancreatic malignancies.[6] The strain ratio is significantly higher among patients with malignant pancreatic tumors than those with inflammatory masses. In their study, normal pancreatic tissue showed a mean SR of 1.68 (95% confidence interval [CI]: 1.59–1.78), Inflammatory masses presented a strain ratio (mean 3.28; 95% CI: 2.61–3.96), which was significantly higher than that of the normal pancreas (p <0.001), but lower than that of pancreatic adenocarcinoma (mean: 18.12; 95% CI: 16.03–20.21) (p <0.001).[6] [Fig. 5A–F] shows strain ratios in different clinical scenarios.

2. Strain Histogram (SH): SH displays the mean strain value within a selected area. The histogram plots strain values (on the X-axis) against the number of pixels (on the Y-axis) in the region of interest (ROI). The mean value of the histogram corresponds to the global hardness or elasticity of the lesion. An SH value <50 favors a malignant lesion in pancreatic masses.[6] [Fig. 6A–F] shows the SH in different clinical scenarios.

Fig. 5 (A–F)The strain ratio in different clinical scenarios. (A, B) Pancreatic head malignancy with a strain ratio of 10.83. (C, D) Pancreatic head inflammatory mass with a strain ratio of 3.63. (E, F) Reactive lymph node mass with a strain ratio of 3.79.

Fig. 6 (A–F)Strain histogram in different clinical scenarios. (A, B) Pancreatic head malignancy with a strain histogram value of 9.56. (C, D) Pancreatic head inflammatory mass with a strain histogram value of 42.32. (E, F) Reactive lymph node mass with a strain histogram value of 66.94. (Depth is the distance of the region of interest over the lesion from the probe; L ax is the long axis, and S ax is the short axis diameter of the region of interest.)

 

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Shear Wave Elastography

In this method, instead of measuring the velocity of the returning longitudinal wave, the velocity of the propagated shear wave is measured. A push pulse is sent by the transducer to the focal point in the ROI. This push pulse then generates a shear wave. The velocity of this propagated shear wave is calculated from the detection of the shear wave arrival by the search pulses. [Fig. 7] shows how to measure SWV by the SWE technique.

Fig. 7 Describing the technique of shear wave elastography. Region of interest (ROI) should be at 30 to 45 degrees with depth <3 cm and with width: 0.5 to 1.5 cm. Care should be taken to avoid duct, vessels, avoid reverberation/shadows/artifacts/calcification/duct, and avoid big wheel up. (Vs is the shear wave velocity; E is the elasticity measure in kilopascals [kPa]; ATT is the fat attenuation index; VsN is the percentage of the net amount of effective shear wave velocity measurement.)

Procedure Steps of SWE

Similar to strain elastography, ensure the patient is adequately prepared.

• Image Acquisition: Once the organ or the lesion is identified, the following steps should be taken:

  • ○ We need to keep the ROI at an angle of 30 to 45 degrees with respect to the transducer. The depth should be less than 3 cm, and the width should be between 0.5 and 1.5 cm. One needs to be careful to avoid ductal structure, vessels, reverberation, shadows, artifacts, and calcification in the ROI. We should avoid causing too much tissue compression and try to keep the big wheel in the neutral position as much as possible.

  • ○ Then activate the SWE mode on the ultrasound machine, which generates shear waves.

  • ○ The program assesses and reports the reliability of the measurement as VsN, which is the percentage of the net amount of effective SWV measurement. For effective SWV measurements, the VsN should be >50% for liver evaluation and > 60% for pancreas evaluation. Five to 10 consecutive measurements should be done.

• Data Analysis: The system translates SWV into stiffness measurements, expressed in kilopascals (kPa), which can be quantitatively compared against known values for various pathologies.

In the study by Wang and Ryou, the mean SWV values for normal pancreatic parenchyma ranged from 1.52 to 1.99 m/s.[7] In their study, the SWV cutoff value for diagnosing chronic pancreatitis (CP) was 2.19 m/s, and for autoimmune pancreatitis, it was 2.57 m/s.[7] When comparing shear wave with strain elastography, studies have shown shear wave to be superior for defining CP based on Rosemont criteria.[8] Further research is going on to evaluate the usefulness of EUS-SWE for the evaluation of the severity of CP and pancreatic exocrine and endocrine dysfunction. In a study by Schulman et al, patients with cirrhosis had significantly increased mean liver fibrosis index compared with the fatty liver (3.2 vs. 1.7, p <0.001) and normal (3.2 vs. 0.8, p <0.001) groups.[9] The fatty liver group showed significantly increased liver fibrosis index compared with the normal group (3.8 vs. 1.4, p <0.001). Here, the liver fibrosis index was calculated incorporating SWE values by computer software. There is an evolving literature on the use of SWE in measuring spleen stiffness as well.

Further Enhancements: In recent technologically advanced EUS equipments, the following additional features are added[10]:

• iElast—makes it easier to view the elastic image even when the displacement due to pulsation is modest.

• sFocus—reduces the change in resolution with distance from the ultrasound transducer surface and eliminates the need to manually adjust the focal zones during the procedure.

• Potential Advantages, Pitfalls, and Limitations:

Potential Advantages: This technique has the following advantages:

1. May help the endosonographer select a site for fine needle aspiration/biopsy. This is especially useful in CP, where the negative predictive value of standard B-mode EUS is low (around 65–70%).

2. EUS-E may reduce the number of false negative results in cases of suspicious malignant lymph nodes, as morphology alone may be insufficient to make an accurate diagnosis.

3. It is easy to learn and use.

4. Applying elastography does not increase the cost of the procedure.

5. It provides real-time results, and immediate information is available to the endosonographer.

6. It can be combined with other techniques such as contrast-enhanced EUS.

Pitfalls and Limitations: This technique also has certain limitations:

1. Operator Dependency

   One significant limitation of EUS-E is its operator dependency. Accurate results require considerable skill and experience, as the quality of elastographic measurements can vary significantly among operators. Training and standardization of techniques are crucial for ensuring consistent and reliable outcomes.

2. Artifacts and Limitations

   • Compression Artifacts: Excessive or uneven compression during the elastography process can lead to inaccurate results, including false positives. Proper technique and patient cooperation are essential to minimize these artifacts.

   • Overlapping Pathologies: Conditions such as inflammation or fibrosis can alter tissue elasticity, complicating the interpretation of elastography findings. This necessitates a comprehensive understanding of the clinical context when interpreting results.

   • Anatomical Limitations: The accessibility of certain lesions may restrict the application of EUS-E. Deep-seated lesions or those located in challenging anatomical locations may pose difficulties in obtaining reliable measurements.

3. Equipment Limitations

   Differences in ultrasound equipment and settings can result in variability in elastography measurements. Standardizing equipment and protocols across institutions will enhance the reproducibility of results.

4. Lack of Standardized Protocols

   Currently, there is a lack of universally accepted protocols for performing and interpreting EUS elastography. This variability can lead to discrepancies in clinical practice and outcomes, highlighting the need for consensus guidelines.

   • 4. Clinical Applications: EUS elastography has widespread application. We briefly describe the following current clinical applications and potential future uses of EUS-E:

Pancreatic diseases: EUS is considered as gold standard in evaluating both diffuse parenchymal pancreatic disease and focal pancreatic lesions. The chances of a false negative increase when a pancreatic mass is seen in the background of chronic pancreatitis (CP), with the sensitivity of B-mode EUS being around 75% in this scenario.[11] With the addition of elastography to standard EUS, its utility is further enhanced. EUS-elastography can help narrow down the differential diagnosis of focal pancreatic lesions and help increase the accuracy of EUS-guided tissue acquisition.[12]

Role in differentiating malignant and benign focal pancreatic mass: Initial study on utility of EUS-E in differential diagnosis of focal pancreatic masses was described by Giovannini et al, where they analyzed all the lesion using a subjective scoring system as described earlier.[12] Sensitivity and specificity in detecting malignancy using qualitative strain elastography was 100 and 67%, respectively. Extrapolating this scoring system in 121 cases, Giovannini et al found that sensitivity, specificity, positive predictive value, and negative predictive value of the differentiation between benign and malignant pancreatic masses were 92.3, 80.0, 93.3, and 77.4%, respectively.[13] Similarly, another study by Iglesias-Garcia et al using qualitative EUS-E showed that sensitivity, specificity, positive and negative predictive values, and overall accuracy of EUS elastography for detecting malignancy were 100, 85.5, 90.7, 100, and 94.0%, respectively.[6] In this study, they broadly classified color patterns into four broad types—homogeneous green pattern, present only in normal pancreas; a heterogeneous, predominantly green pattern with slight yellow and red lines present only in inflammatory pancreatic masses; a heterogeneous, predominantly blue pattern with small green areas and red lines; and a geographic appearance, present mainly in pancreatic malignant tumors; and a homogeneous blue pattern, present only in pancreatic neuroendocrine malignant lesions. These studies also showed good interobserver agreement in describing various color patterns. However, certain studies have found utility of qualitative EUS-E limited in certain clinical scenarios. The presence of lesion size >35 mm, lesion being far away from transducer, presence of intervening fluid filled structure, etc. were some of the limiting factors in assessing color patterns. So, we suggest that color pattern using qualitative strain elastography should be used as an initial screening modality, which should be further confirmed by quantitative elastography measurements. As described earlier, strain ratio is a useful parameter. Study by Iglesias-Garcia et al showed that strain ratio of pancreatic adenocarcinoma was significantly more than that of inflammatory mass (18.12 vs. 3.28). Strain ratio of CP with inflammatory mass was more than that of normal pancreas (3.28 vs. 1.68). There was good interobserver agreement as well. They suggested using strain ratio cutoff of 6.04 had 100% sensitivity and 92.9% specificity in differentiating malignant from nonmalignant lesion.[6] In another study, mean strain ratio for malignant lesions was 39.08 ± 20.54 as compared with 23.66 ± 12.65 for inflammatory lesions.[14] Studies describing the use of hue histogram has also been described. Using a cutoff of 175 value for hue histogram, a multicenter study showed that sensitivity, specificity, positive and negative predictive values, and accuracy were 93.4, 66.0, 92.5, 68.9, and 85.4%, respectively.[15] Comparative studies have shown no difference in accuracy between the use of strain ratio and SH. Sonthalia et al showed combined use of hypoenhance pattern on contrast-enhanced EUS and strain ratio above 6.24 had 100% sensitivity and specificity for detecting malignancy in pancreatic masses arising in the background of CP.[16] The use of EUS SWE for solid focal pancreatic lesions is still evolving. In a retrospective study of 64 patients with solid pancreatic lesions who underwent both SWM and strain elastography with images analyzed by SH, the Vs (m/s) values of solid pancreatic lesions were 2.19 for pancreatic cancer, 1.31 for pancreatic neuroendocrine neoplasm, 2.56 for mass-forming pancreatitis, and 1.58 for metastatic tumors. Vs showed no significant difference based on the disease. They concluded that EUS-SWM tends to be unstable for the measurement of elasticity of solid pancreatic lesions.[8] Thus, EUS-E has a complementary role in addition to standard B-mode and contrast-enhanced EUS to increase the diagnostic yield in cases of focal pancreatic lesions.

Role in evaluation of CP: Studies using SR by strain elastography have shown a significant difference between values among different Rosemont categories evaluated by B-mode. SR values for cases with “consistent with CP” based on Rosemont criteria had the highest strain ratio, followed by those with “indeterminate for CP” and normal pancreas (3.6 vs. 2.4 vs. 1.8).[17] [18] The use of SWE in diagnosing CP is evolving. In a study by Yamashita et al, the cutoff values of 1.96, 1.96, and 2.34 for diagnosing CP, exocrine dysfunction, and endocrine dysfunctions had 83, 90, and 75% sensitivity, respectively, and 100, 65, and 64% specificity, respectively.[19] The areas under the receiver operating characteristic (AUROC) curve for the diagnostic accuracy of EUS-SWM for CP, exocrine dysfunction, and endocrine dysfunction were 0.92, 0.78, and 0.63 in this study. In another study by the same group, EUS-SWE showed a significant positive correlation with the EUS Rosemont criteria and the number of EUS features.[20] The AUROC curve for the diagnostic accuracy of EUS-SWM for CP was 0.97. The cutoff value of 2.19 had 100% sensitivity and 94% specificity. For endocrine dysfunction in CP, the AUROC was 0.75. The cutoff value of 2.78 had 70% sensitivity and 56% specificity.[20] EUS-SWM can be a useful modality for evaluating CP in addition to standard B-mode evaluation.

Role in lymph nodes: In a study by Giovannini et al, the sensitivity and specificity of qualitative EUS elastography for detecting malignancy in lymph nodes were 100 and 50%, respectively.[12] In another large multicenter study evaluating 101 lymph nodes, the sensitivity, specificity, positive predictive value, and negative predictive value for the detection of malignancy were 91.8, 82.5, 88.8, and 86.8%, respectively, with overall diagnostic accuracy of 88.1%.[13] In another qualitative study, the presence of predominantly green pattern was suggestive of benign lymph nodes in 100% of cases, and the presence of predominantly blue pattern was suggestive of malignant lymph nodes in 92.3% of cases.[21] In a meta-analysis of 431 patients, elastography had a pooled sensitivity of 88% and specificity of 85% in differentiating benign from malignant lymph node.[22] Studies of the use of quantitative EUS elastography for differential diagnosis of lymph nodes are few. In one of the studies, using a cutoff of 166, the sensitivity, specificity, and accuracy in the detection of malignancy were 85.4, 91.9, and 88.5%, respectively.[23] Further studies are needed to determine the cutoff values of SR, SH, and SWE in different lymph nodal diseases.

Role in liver diseases: Quantitative EUS-guided shear wave measurement is a promising tool for assessing fibrosis in chronic liver parenchymal diseases. There have been studies comparing EUS-SWM with transcutaneous shear wave measurement. In a pilot study, 42 patients underwent EUS-SWE, vibration-controlled transient elastography (VCTE), and liver biopsy sampling.[24] Liver elasticity cutoffs for different stages of fibrosis were estimated. They found that AUROCs for advanced fibrosis were similar between VCTE and EUS-SWE (0.87 vs. 0.8). AUROCs for diagnosing cirrhosis were VCTE, 0.9 (95% CI, 0.83–0.97); EUS-SWE left lobe, 0.96 (95% CI, 0.9–1); and EUS-SWE right lobe, 0.9 (95% CI, 0.8–1).[24] Currently, a multicenter study in India is underway comparing EUS-SWE, VCTE, and liver biopsy to find out the utility of EUS-SWM. In the era of endohepatology, incorporating EUS-SWM for suspected parenchymal liver disease patients has the potential to provide a one-stop solution by incorporating diagnosis of cirrhosis by EUS-SWM, confirmation of cirrhosis by EUS-guided liver biopsy, prognostication by EUS-guided portal pressure gradient measurement, and treatment by EUS-guided variceal obliteration.

Other potential applications: There are other potential applications of EUS elastography such as (1) evaluation of solid lesions in the left suprarenal gland, thereby helping in differentiation of adenoma from metastasis, (2) evaluation of focal liver lesions, and (3) staging of esophageal and gastric cancer. Further studies are needed to evaluate the role in these conditions.

 

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Future Directions

Ongoing advancements in ultrasound technology, particularly the integration of artificial intelligence (AI) and machine learning, hold great promise for enhancing the precision and utility of EUS-E. AI algorithms can analyze elastography data, improving diagnostic accuracy and reducing operator dependency. Additionally, research into the development of standardized protocols and thresholds for elastography measurements will further solidify its role in clinical practice. Furthermore, ongoing studies should explore the potential of elastography in various clinical settings, including its role in treatment monitoring and prognostication.

 

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Conclusion

EUS-E represents a significant advancement in the field of gastrointestinal and pancreatic imaging. By providing critical insights into tissue stiffness, it enhances the diagnostic accuracy of traditional EUS and offers a noninvasive alternative for assessing various conditions. Understanding the principles, techniques, and limitations of EUS-E is crucial for its effective application in clinical practice, ultimately leading to improved patient outcomes.

 

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Conflict of Interest

None declared.

Declaration of GenAI use

The authors acknowledge the use of ChatGPT for language polishing of the manuscript.

Authors' Contributions

N.S., A.T., A.R., and U.C.G. performed literature review and data collection; N.S. and A.T. wrote the manuscript; A.R., M.K.G., and U.C.G. performed critical review of the manuscript; N.S., A.R., M.K.G., and U.C.G. contributed to editing and final approval of the manuscript.

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Publication History

Article published online:
08 September 2025