Pressed for an answer: has elastography finally come to EUS?

Efficacy of Endoscopic Ultrasound Elastography in Differential Diagnosis of Gastrointestinal Stromal Tumor Versus Gastrointestinal Leiomyoma

BACKGROUND The diagnostic efficacy of endoscopic ultrasound (EUS) elastography for alimentary tract diseases remains uncertain. The aim of this study was to evaluate the utility of EUS elastography in differential diagnosis between the 2 most common subepithelium tumors of the digestive tract - gastrointestinal stromal tumors (GISTs) and gastrointestinal leiomyomas (GILs) - which cannot be differentiated by conventional EUS imaging. MATERIAL AND METHODS Electronic records were retrospectively reviewed from Jan 2015 to Jul 2019. Patients accepting EUS elastography with histopathological diagnosis of GISTs or GILs were included. The images of EUS elastography were analyzed by hue histogram in Photoshop. Hue values of RGB, R, G, and B channels of each group were acquired. We used the t test, ROC curve analysis, and binary logistic regression analysis for data post-processing. RESULTS We included 47 patients with GISTs and 14 with GILs. The mean±standard deviations (SD) of hue values were 20.25±0.72, -0.79±0.78, 20.79±1.68, 39.72±1.30 for GISTs and 20.80±0.46, 1.80±1.05, 28.39±2.15, and 31.95±2.60 for GILs of RGB, R, G, and B channels, respectively. The t test showed statistically significant differences in mean hue values between GISTs and GILs in B and G channels, but not in RGB and R channels. The area under the ROC curve combining B and G values was 0.723. Binary logistic regression analysis suggested no statistically significant difference in ability to differentiate between GISTs and GILs with B and G values (P>0.05). CONCLUSIONS There was insufficient evidence to support the application of quantitative EUS elastography for differential diagnosis of GISTs and GILs in this study.

Enhanced EUS imaging (with videos)

BACKGROUND AND AIMS

EUS remains a primary diagnostic tool for the evaluation of pancreaticobiliary disease. Although EUS combined with FNA or biopsy sampling is highly sensitive for the diagnosis of neoplasia within the pancreaticobiliary tract, limitations exist in specific clinical settings such as chronic pancreatitis. Enhanced EUS imaging technologies aim to aid in the detection and diagnosis of lesions that are commonly evaluated with EUS.

METHODS

We reviewed technologies and methods for enhanced imaging during EUS and applications of these methods. Available data regarding efficacy, safety, and financial considerations are summarized.

RESULTS

Enhanced EUS imaging methods include elastography and contrast-enhanced EUS (CE-EUS). Both technologies have been best studied in the setting of pancreatic mass lesions. Robust data indicate that neither technology has adequate specificity to serve as a stand-alone test for pancreatic malignancy. However, there may be a role for improving the targeting of sampling and in the evaluation of peritumoral lymph nodes, inflammatory pancreatic masses, and masses with nondiagnostic FNA or fine-needle biopsy sampling. Further, novel applications of these technologies have been reported in the evaluation of liver fibrosis, pancreatic cysts, and angiogenesis within neoplastic lesions.

CONCLUSIONS

Elastography and CE-EUS may improve the real-time evaluation of intra- and extraluminal lesions as an adjunct to standard B-mode and Doppler imaging. They are not a replacement for EUS-guided tissue sampling but provide adjunctive diagnostic information in specific clinical situations. The optimal clinical use of these technologies continues to be a focus of ongoing research.

The role of EUS in diagnosis and treatment of liver disorders

Background and aim  Transabdominal ultrasound (US), computed tomographic scanning (CT) and magnetic resonance imaging (MRI) are established diagnostic tools for liver diseases. Percutaneous transhepatic cholangiography is used to perform hepatic interventional procedures including biopsy, biliary drainage procedures, and radiofrequency ablation. Despite their widespread use, these techniques have limitations. Endoscopic ultrasound (EUS), a tool that has proven useful for evaluating the mediastinum, esophagus, stomach, pancreas, and biliary tract, has an expanding role in the field of hepatology complementing the traditional investigational modalities. This review aimed to assess the current scientific evidence regarding diagnostic and therapeutic applications of EUS for hepatic diseases.

Endoscopic Ultrasound in the Diagnosis and Staging of Pancreatic Cancer

Pancreatic cancer is one of the digestive cancers with the poorest prognosis, so an early and correct diagnosis is of utmost importance. With the development of new therapeutic options an accurate staging is essential. Endoscopic ultrasonography (EUS) has a major role in all stages of the management of these patients. EUS has a high accuracy in the diagnosis of pancreatic adenocarcinoma and the possibility to perform fine-needle aspiration/biopsy (FNA/FNB) increases the diagnostic yield of EUS. There is still no consensus on the several technical aspects of FNA, namely on the rapid on-site evaluation (ROSE), the diameter and type of needle, the number of passes and the use of stylet and suction. Contrast-enhanced EUS (CE-EUS) and EUS elastography (EUS-E) have been used in recent years as an adjunct to EUS-FNA. Given the higher sensitivity of these techniques a negative cytology by EUS-FNA should not exclude malignancy when CE-EUS and/or EUS-E are suggestive of pancreatic neoplasia. EUS remains one of the main methods in the staging of pancreatic adenocarcinoma, namely to further evaluate patients with non-metastatic disease that appears resectable on initial imaging. EUS is crucial for an accurate preoperative evaluation of pancreatic cancer which is essential to choose the correct management strategy. The possibility to obtain samples from suspicious lesions or lymph nodes, by means of EUS-guided fine-needle aspiration as well as the use of contrast-enhanced and elastography, makes EUS an ideal modality for the diagnosis and staging of pancreatic cancer.

EUS elastography for diagnosis of solid pancreatic masses: a meta-analysis

BACKGROUND

The differential diagnosis of solid pancreatic masses has been a significant challenge up until now. EUS elastography is now used as a new technique to distinguish benign from malignant pancreatic masses. However, the sensitivity, specificity, and accuracy are still questionable.

OBJECTIVE

To evaluate the accuracy of EUS elastography for diagnosis of solid pancreatic masses.

DESIGN

Thirteen articles for EUS elastography diagnosing solid pancreatic masses were selected. The Mantel-Haenszel and DerSimonian Laird methods were used to analyze pooled results.

PATIENTS

This study involved 1044 patients.

INTERVENTION

EUS elastography.

MAIN OUTCOME MEASUREMENTS

The pooled sensitivity, specificity, likelihood ratios, diagnostic odds ratio, and summary receiver operating characteristic (sROC) curve.

RESULTS

The pooled sensitivity, specificity, and diagnostic odds ratio of EUS elastography distinguishing benign from malignant solid pancreatic masses were 0.95 (95% confidence interval [CI], 0.94-0.97), 0.67 (95% CI, 0.61-0.73), and 42.28 (95% CI, 26.90-66.46), respectively. The sROC area under the curve was 0.9046. The subgroup analysis based on excluding the outliers showed that the heterogeneity was eliminated, and the pooled sensitivity and specificity were 0.95 (95% CI, 0.93-0.97) and 0.7 (95% CI, 0.63-0.76), respectively. The sROC area under the curve was 0.8872.

LIMITATIONS

Varied diagnostic standards for EUS elastography were used in the enrolled studies.

CONCLUSION

EUS elastography is a reliable technique for the characterization of solid pancreatic masses and may be a useful complementary tool for EUS-guided FNA. However, a more accurate computer-aided diagnosis method for EUS elastography is in demand to reduce various biases and improve the accuracy of EUS elastography for diagnosis of solid pancreatic masses.

Endoscopic ultrasound elastography for the pancreas in Korea: a preliminary single center study

BACKGROUND/AIMS

Endoscopic ultrasound elastography (EUS-EG) has been widely used for the evaluation of pancreatic cancer in the Western world. To date, there is very little experience with EUS-EG in Korea. We described the results of comparison between normal pancreas and pancreatic cancer in Korea.

METHODS

The present study was performed at a tertiary hospital on 35 subjects comprising 20 with normal pancreas (control group) and 15 with pancreatic cancer (disease group). We compared the EUS-EG performance of the two groups.

RESULTS

The pancreas in the control group showed a mean elasticity value of 0.53% (95% confidence interval [CI], 0.45 to 0.61). The elasticity value was higher than that previously reported from Western country (0.47%; 95% CI, 0.38 to 0.57). In the disease group, the mean elasticity value of pancreatic lesions was 0.02% (95% CI, 0.01 to 0.02). The mean elasticity value of the disease group was significantly lower than that of the control group (p<0.0001).

CONCLUSIONS

EUS-EG could be a highly sensitive diagnostic modality for pancreatic cancer in Korea with little EUS-EG experience. We also provided the reference range of elasticity value of normal pancreas, which might be valuable in the interpretation of pancreatic elasticity data for Korean adults.

EUS elastography combined with the strain ratio of tissue elasticity for diagnosis of solid pancreatic masses

BACKGROUND

Recently, the usefulness of endoscopic ultrasound (EUS) elastography has been reported for the diagnosis of pancreatic lesions. In the present study, we retrospectively assessed EUS elastography as a diagnostic tool by evaluating tissue elasticity distribution and elasticity semiquantification, using the strain ratio (SR) of tissue elasticity, in patients with pancreatic masses.

METHODS

One hundred and nine patients who underwent EUS elastography between September 2006 and May 2009 were retrospectively evaluated. The final diagnosis was chronic pancreatitis (CP) in 20 patients [6 with non-mass-forming pancreatitis, 7 with mass-forming pancreatitis (MFP), and 7 with autoimmune pancreatitis (AIP)], pancreatic cancer (PC) in 72, pancreatic neuroendocrine tumor (PNET) in 9, and normal pancreas in 8. The tissue elasticity distribution calculation was performed in real time, and the results were represented in color in fundamental B-mode imaging. In addition, we performed quantification using the SR (non-mass area/mass area).

RESULTS

Elastography for all PC patients showed intense blue coloration, indicating malignant lesions. In contrast, MFP presented with a mixed coloration pattern of green, yellow, and low-intensity blue. Normal controls showed an even distribution of green to red. The mean SR was 23.66 ± 12.65 for MFP and 39.08 ± 20.54 for PC (P < 0.05).

CONCLUSIONS

Endoscopic ultrasound elastography is a promising diagnostic tool for defining the tissue characteristics of pancreatic masses. In addition, semiquantitative analysis of elasticity using the SR may allow the differentiation of MFP from PC.

Differential diagnosis of pancreatic cancer from normal tissue with digital imaging processing and pattern recognition based on a support vector machine of EUS images

BACKGROUND

EUS can detect morphologic abnormalities of pancreatic cancer with high sensitivity but with limited specificity.

OBJECTIVE

To develop a classification model for differential diagnosis of pancreatic cancer by using a digital imaging processing (DIP) technique to analyze EUS images of the pancreas.

DESIGN

A retrospective, controlled, single-center design was used.

SETTING

The study took place at the Second Military Medical University, Shanghai, China.

PATIENTS

There were 153 pancreatic cancer and 63 noncancer patients in this study.

INTERVENTION

All patients underwent EUS-guided FNA and pathologic analysis.

MAIN OUTCOME MEASUREMENTS

EUS images were obtained and correlated with cytologic findings after FNA. Texture features were extracted from the region of interest, and multifractal dimension vectors were introduced in the feature selection to the frame of the M-band wavelet transform. The sequential forward selection process was used for a better combination of features. By using the area under the receiver operating characteristic curve and other texture features based on separability criteria, a predictive model was built, trained, and validated according to the support vector machine theory.

RESULTS

From 67 frequently used texture features, 20 better features were selected, resulting in a classification accuracy of 99.07% after being added to 9 other features. A predictive model was then built and trained. After 50 random tests, the average accuracy, sensitivity, specificity, positive predictive value, and negative predictive value for the diagnosis of pancreatic cancer were 97.98 ± 1.23%, 94.32 ± 0.03%, 99.45 ± 0.01%, 98.65 ± 0.02%, and 97.77 ± 0.01%, respectively.

LIMITATIONS

The limitations of this study include the small sample size and that the support vector machine was not performed in real time.

CONCLUSION

The classification of EUS images for differentiating pancreatic cancer from normal tissue by DIP is quite useful. Further refinements of such a model could increase the accuracy of EUS diagnosis of tumors.

Real-time ultrasound elastography in the differential diagnosis of benign and malignant thyroid nodules

OBJECTIVE

The purpose of this study was to evaluate the diagnostic utility of real-time ultrasound elastography in differentiating benign from malignant thyroid nodules.

METHODS

A total of 90 consecutive patients with thyroid nodules who were referred for surgical treatment were examined in this prospective study. One hundred forty-five nodules in these patients were examined by B-mode ultrasound, color Doppler ultrasound, and ultrasound elastography. The final diagnosis was obtained from histologic findings. Tissue stiffness on ultrasound elastography was scored from 1 (low stiffness over the entire nodule) to 6 (high stiffness over the entire nodule and surrounding tissue).

RESULTS

On real-time ultrasound elastography, 86 of 96 benign nodules (90%) had a score of 1 to 3, whereas 43 of 49 malignant nodules (88%) had a score of 4 to 6 (P <.001), with sensitivity of 88%, specificity of 90%, a positive predictive value of 81%, and a negative predictive value of 93%. The predictivity of ultrasound elastographic measurement was independent of the nodule size. High sensitivity (88%) and specificity (93%) were also observed in 68 nodules that had a greatest diameter of 1 cm or less.

CONCLUSIONS

Real-time ultrasound elastography is a promising imaging technique that is useful in the differential diagnosis of thyroid cancer.

Neural network analysis of dynamic sequences of EUS elastography used for the differential diagnosis of chronic pancreatitis and pancreatic cancer

BACKGROUND

EUS elastography is a newly developed imaging procedure that characterizes the differences of hardness and strain between diseased and normal tissue.

OBJECTIVE

To assess the accuracy of real-time EUS elastography in pancreatic lesions.

DESIGN

Cross-sectional feasibility study.

PATIENTS

The study group included, in total, 68 patients with normal pancreas (N = 22), chronic pancreatitis (N = 11), pancreatic adenocarcinoma (N = 32), and pancreatic neuroendocrine tumors (N = 3). A subgroup analysis of 43 cases with focal pancreatic masses was also performed.

INTERVENTIONS

A postprocessing software analysis was used to examine the EUS elastography movies by calculating hue histograms of each individual image, data that were further subjected to an extended neural network analysis to differentiate benign from malignant patterns.

MAIN OUTCOME MEASUREMENTS

To differentiate normal pancreas, chronic pancreatitis, pancreatic cancer, and neuroendocrine tumors.

RESULTS

Based on a cutoff of 175 for the mean hue histogram values recorded on the region of interest, the sensitivity, specificity, and accuracy of differentiation of benign and malignant masses were 91.4%, 87.9%, and 89.7%, respectively. The positive and negative predictive values were 88.9% and 90.6%, respectively. Multilayer perceptron neural networks with both one and two hidden layers of neurons (3-layer perceptron and 4-layer perceptron) were trained to learn how to classify cases as benign or malignant, and yielded an excellent testing performance of 95% on average, together with a high training performance that equaled 97% on average.

LIMITATION

A lack of the surgical standard in all cases.

CONCLUSIONS

EUS elastography is a promising method that allows characterization and differentiation of normal pancreas, chronic pancreatitis, and pancreatic cancer. The currently developed methodology, based on artificial neural network processing of EUS elastography digitalized movies, enabled an optimal prediction of the types of pancreatic lesions. Future multicentric, randomized studies with adequate power will have to establish the clinical impact of this procedure for the differential diagnosis of focal pancreatic masses.