The evaluation method in strain elastography that yields the highest quality results is color pattern diagnosis. Generally, color pattern diagnosis is used to evaluate tumors; images display major color tones (whereby blue represents hard tissue and red represents soft tissue) and can be used to evaluate tumors with heterogeneous or homogeneous color tones. Giovannini et al. [6] first described the elastic score, which is a color pattern diagnosis, and five combinations of the elastic score, color pattern, and heterogenicity of distribution of elastography. Quantity evaluation methods include the use of the strain ratio and histogram analysis. The strain ratio is defined as the ratio of the target lesion strain to the peripheral tissue strain [7]. In histogram analysis, a histogram is created by the conversion of an elastographic image into a 256-tone grayscale, and feature values are created from this grayscale image (Fig. 1) [8].

For shear wave elastography, only the quantity evaluation methods are used, and the values are expressed in meters per second or kilopascals. The tissue elasticity is proportional to the square of the SWV [9,10]. An acoustic push pulse transmitted by the ultrasonographic transducer through the tissue induces an elastic shear wave that propagates through the tissue; this wave is followed by detection pulses, which are used to measure the velocity of the shear wave propagation. The method traditionally used in EUS elastography was mainly strain elastography, but shear wave elastography has recently become available (Fig. 2) [11–14].

We got started this discussion by describing a study with histopathological specimens. Presently, in the process of diagnosing CP, EUS elastography is performed to confirm pancreatic fibrosis or hardness, as well as other factors. Itoh et al. [8] reported EUS elastography in the quantitative analysis of pancreatic fibrosis with an emphasis on the comparison of surgical specimens. They performed a strain histogram analysis of the EUS elastographic image in Fig. 3. To convert the strain histogram from a color image to a 256-tone grayscale image (distortion value image), an arbitrary area on the EUS elastographic image was selected. The image was then converted into a binarized image under a certain threshold value. A plurality of features was automatically calculated from the strain value image and the binarized image. Preoperative EUS elastographic images in the upstream pancreas were statistically quantified, and the results were retrospectively compared with postoperative histological images of fibrosis in the same area. For the quantification of EUS elastographic images, four parameters (mean, standard deviation [SD], skewness, and kurtosis) were calculated with the use of novel software. Klöppel’s score was calculated according to an ascending risk scale of pancreatic fibrosis (0–12) [19]. Histological fibrosis was graded according to four categories (normal, mild fibrosis, marked fibrosis, and severe fibrosis) on the basis of a previously reported scoring system (Fig. 4) [20].

Itoh et al. [8] found significant correlations between all four quantification parameters and the grade of pancreatic fibrosis. The latter was negatively correlated with the mean (r = −0.752) and SD (r = −0.54) and positively correlated with skewness (r = 0.69) and kurtosis (r = 0.67). In an analysis of the ability of the four quantification parameters to diagnose pancreatic fibrosis, the receiver operating characteristic (ROC) curve indicated that the mean was the most useful parameter. The areas under the curves of the mean were all 0.90 for the diagnoses of mild and higher grade fibrosis, moderate and higher grade fibrosis, and severe fibrosis. Thus, the diagnostic ability of the mean was high, regardless of the grade of fibrosis. Moreover, the mean value showed the most sensitive negative correlation with pancreatic fibrosis. This showed that pancreatic fibrosis can be diagnosed by EUS elastography.

Itoh et al.’s [8] study had some limitations. First, the reproducibility of the EUS elastographic images was poor. Second, the relevance of these findings to nonobstructive CP was unknown; the cases of fibrosis that they studied were mostly caused by neoplasia and thus could have differed from fibrosis caused by nonobstructive CP. The other limitations were the relatively small number of patients and the retrospective nature of the study. Despite these limitations, Itoh et al. [8] were the first to quantify the grade of pancreatic fibrosis by using EUS elastography. Unlike several other evaluation techniques, EUS elastography allows the accurate grading of pancreatic fibrosis.

To compare pancreatic fibrosis or hardness with the stage of CP, we examined the correlation between the Rosemont classification [21] and the results of EUS elastography. Kuwahara et al. [22] reported that they calculated the “mean value” by performing EUS elastography and histogram analysis of the pancreatic parenchyma or tumors.

EUS elastography was repeated five times for each patient. The average value of the five measurements was defined as the “mean value.” The mean values in the histogram analysis for the Rosemont classification (normal, indeterminate for CP, suggestive of CP, and consistent with CP) were significantly correlated inversely with the number of features found on EUS elastography. These findings indicate that CP can be diagnosed using EUS elastography. Particularly, the mean value of NP cases was significantly higher than that of CP cases, and the mean value was significantly elevated as CP progressed. A more objective diagnosis of CP by EUS is possible with the use of EUS B-mode images. The recognition of early-stage CP according to mechanistic definition [23] is extremely important for maintaining the quality of life because therapeutic intervention can begin early. EUS elastography and histogram analysis may contribute to the diagnosis of early-stage CP, and future studies are important.

We concluded EUS elastography have a potential usefulness in the diagnosis of pancreatic diseases including CP staging and other diseases such as pancreatic ductal adenocarcinoma (PDAC). We think EUS plays an important role in the diagnosis of many other pancreatic disorders as well, but the diagnosis of CP with EUS depends on the skill of the endoscopic sonographer.

Kuwahara et al. [24] also studied 53 patients who underwent shear wave elastography with ultrasonography of the pancreatic parenchyma preoperatively and in whom the pancreatic parenchyma was evaluated histologically. Histological fibrosis was graded into the same four categories (normal, mild, moderate, and severe) as in Itoh et al.’s [8] study. Kuwahara et al. [24] found a significant positive correlation between the pancreatic elastic modulus and the histological grade of pancreatic fibrosis (r = 0.63, p < 0.001). Regarding the pancreatic parenchyma, the areas under the ROC curve for the accuracy of shear wave elastography were 0.85 for diagnosing mild fibrosis, 0.84 for diagnosing moderate fibrosis, and 0.87 for diagnosing severe fibrosis. Kuwahara et al. [24] concluded that shear wave elastography with ultrasonography was a useful noninvasive method of determining the stage of pancreatic fibrosis with high accuracy and reproducibility.

Uchida et al. [16] reported on the usefulness of elastography with ultrasonography in evaluating the pancreas. They reviewed 10 cases of the normal pancreas, five of PDACs, two of endocrine tumors, and five of CP in which elastography was performed, and they reported the typical color map observed in ultrasonographic elastography as follows: homogeneous color characterized normal pancreases, markedly hard areas with soft spots characterized PDAC, uniform and soft areas comparable with the parenchyma characterized neuroendocrine tumors, and a mixture of various colors characterized CP. Kawada et al. [26] performed ultrasonographic elastography for 36 consecutive solid pancreatic tumors. They reported that the strain ratio was higher in ductal adenocarcinomas than in benign tumors.

ARFI imaging of the entire pancreas can be performed wherever desired in shear wave elastography. Thus, shear wave elastography is considered a breakthrough in the history of elastography for the pancreas. Virtual Touch Quantification (Siemens Healthineers, Erlangen, Germany) is a representative application of shear wave elastography that shows the stiffness of target tissue digitally by measuring SWV.

Yashima et al. [27] first reported using ARFI elastography to measure the stiffness of normal pancreases and that of pancreases affected by definite CP. They studied 46 patients with CP and 52 with normal pancreases and determined that the optimal SWV for diagnosing CP was 1.40 m/sec according to ROC analysis, and the sensitivity, specificity, and positive and negative predictive values for diagnosing CP were 75%, 72%, 69%, and 78%, respectively. They concluded that ARFI elastography is useful for the diagnosis of CP. Llamoza-Torres et al. [28] also reported the usefulness of percutaneous ARFI elastography for the diagnosis of CP. They examined 33 patients and found a significant difference between the mean SWV without CP (1.27 m/sec) and the mean SWV with CP (1.57 m/sec; p = 0.037). The area under the ROC curve was 71.3%, and the accuracy of ARFI imaging for diagnosing CP was 69.7% when SWV was 1.4 m/sec. They concluded that SWV was significantly correlated with the number of EUS criteria for CP.

Besides ARFI imaging, shear wave elastography was used to measure SWV, which led to the development of the Virtual Touch Imaging and Quantification (VTIQ) application (Siemens Healthineers). VTIQ has been available in Japan since March 2012, and only linear probes have been used in VTIQ so far. Several researchers have evaluated the usefulness of VTIQ in assessing other organs [29–31]. In ElastPQ (Philips, Amsterdam, The Netherlands), SWV is measured in kilopascals. Several researchers have used ElastPQ to evaluate the correlation between SWV and the stage of chronicliver disease [32–34]. Pozzi et al. [35] first reported using ElastPQ with SWV to measure pancreatic stiffness in CP. They studied 52 consecutive patients with CP and 42 healthy controls and found that pancreatic stiffness with point shear wave elastography was significantly higher in patients with CP (4.3 ± 2.4 kPa) than in healthy controls (2.8 ± 1.1 kPa; p = 0.001). Among the patients with CP, values were significantly higher when the disease was of longer duration (for > 10 years, 5.8 ± 4 kPa; for ≤ 10 years, 3.9 ± 1.5 kPa; p = 0.01), when patients were taking long-term analgesic drugs (6.0 kPa vs. 3.5 kPa, p < 0.05), and in patients with lower body weight (r = −0.38; p < 0.05). They concluded that using ElastPQ to measure SWV is promising and reproducible in assessing pancreatic stiffness, which mainly reflects disease length and severity.

Kuwahara et al. [36] also used ElastPQ to measure SWV with an iU22 ultrasound system (Philips Healthcare, Bothell, WA, USA), using a convex probe (C5-1). They investigated 85 patients with known or suspected CP that was categorized into the four grades of the Rosemont classification and into three stages according to the 2009 clinical diagnostic criteria of the Japan Pancreas Society, which were based on EUS measurements for the diagnosis of CP. SWV was measured five times in the pancreatic parenchyma in each study participant, and the median value was defined as the pancreatic elastic modulus. Kuwahara et al.’s [36] results showed that the pancreatic elastic modulus was significantly correlated with Rosemont classification grade (r = 0.54), Japan Pancreas Society stage (r = 0.41), and the number of EUS features (r = 0.47). The area under the ROC curve for the accuracy of SWV measurement (consistent with CP and suggestive of CP vs. normal and indeterminate for CP) was 0.77 (with 77.1% sensitivity, and 64.9% specificity). Kuwahara et al. [36] concluded that shear wave elastography may be used to diagnose CP noninvasively and objectively.

In an unpublished study, we used an iU22 ultrasound system to measure SWV, but with a convex probe (C5-1) in ElastPQ mode for CP (Fig. 5). We investigated whether SWV could help diagnose early-stage CP. Shear wave elastography was performed at least five times in each patient for the pancreatic parenchyma, and the median of five repeated measurements was defined as the pancreatic elastic modulus, as in Kuwahara et al.’s study [36]. The participants in the study were outpatients, and early-stage CP was suspected before diagnosis in 42 patients who had two or more Japan Pancreas Society clinical criteria for early-stage CP (Fig. 6) [37].

First, we measured SWV in the 42 patients with suspected early-stage CP. The cutoff value for early-stage CP calculated by the ROC analysis was 4.44 kPa. A higher value was predictive of early CP, and a lower value indicated possible CP. Next, EUS and endoscopic retrograde cholangiopancreatography (ERCP) were performed for the final diagnosis; when findings met the diagnostic criteria, early-stage CP was diagnosed, and when the findings did not, possible CP was diagnosed (Fig. 7).

The diagnostic accuracy of EUS/ERCP with SWV had 76% sensitivity and 88% specificity, and the rate of correct diagnosis was 81% rate (Table 2). We concluded that SWV could be used to diagnose CP with high accuracy and could also contribute to the diagnosis of early-stage CP.