| Literature DB >> 29085561 |
Tanyaporn Chantarojanasiri1, Pradermchai Kongkam2.
Abstract
Elastography is one of technologies assisting diagnosis of solid pancreatic lesions (SPL). This technology has been previously used for measuring the stiffness of various organs based on a principle of "harder the lesions, higher chance for malignancy". Two elastography techniques; strain and shear wave elastography, are available. For endoscopic ultrasound (EUS), only the former is existing. To interpret results of EUS elastography for SPL, 3 methods are used: (1) pattern recognition; (2) strain ratio; and (3) strain histogram. Based on results of existing studies, these 3 techniques provide high sensitivity but low to moderate specificity and accuracy rate. This review will summarize all available information in order to update current situation of using elastography for an evaluation of SPLs to readers.Entities:
Keywords: Chronic pancreatitis; Elastography; Endoscopic ultrasound; Pancreatic cancer; Solid pancreatic lesions
Year: 2017 PMID: 29085561 PMCID: PMC5648993 DOI: 10.4253/wjge.v9.i10.506
Source DB: PubMed Journal: World J Gastrointest Endosc
Figure 1The principle of strain elastography is illustrated by coil spring appearance. A: After applying pressure, more deformation is demonstrated in tissue with higher elasticity; B: The strain on each tissue depends on the tissue stiffness; C: Higher strain is seen in softer tissue after compression (Adapted from Ophir[2]).
Figure 2The principle of endoscopic ultrasound elastography for solid pancreatic lesions. A: Pancreatic carcinoma has more stiffness than normal pancreas; B: The strain elastography measured the degree of displacement after applying manual pressure or vascular pulsation; C: The degree of displacement is represented as colors: Green is the average stiffness, blue is stiffer tissue, and red is softer tissue.
Figure 3Classification of elastography findings proposed by Giovannini[4].
Results of 4 large studies using pattern recognition of elastography for diagnosis of solid pancreatic lesions
| Score and interpretation | Distortion for entire low echo area | Normal pancreas | A (elastic score 1 and 2) | Benign | Homogeneous | A = blue | B = normal pancreas | Homogeneous green | Normal pancreas |
| No distortion on low echo area even for a part | Fibrosis, chronic pancreatitis | Heterogenous green | Inflammatory pancreas | ||||||
| Distortion at the edge of low echo area, even for a part | Small adeno-carcinoma | B (elastic score 3) | Indeter-minate | 2 or 3 colors | B = green/yellow | Homogeneous blue | Ductal pancreatic adenocarcinoma | ||
| No distortion for entire low echo area | Endocrine tumor | C (elastic score 4 and 5) | Malignant | Heterogeneous | C = red | A/B = chronic pancreatitis and neoplasia | Heterogeneous blue | Neuroendocrine tumor | |
| No distortion on low echo area and surrounding | Advanced adeno-carcinoma | ||||||||
| Sensitivity | 100 | 92.3 | 65.9 (chronic pancreatitis), | 100 | |||||
| 93.8 (neoplasia) | |||||||||
| Specificity | 67 | 80 | 56.9 (chronic pancreatitis), | 85.5 | |||||
| 65.4 (neoplasia) | |||||||||
| Accuracy | NA | 89.2 | 60.2 (chronic pancreatitis), 73.5 (neoplasia) | 94 | |||||
NA: Not available.
Results of studies using strain ratio of elastography for an evaluation of solid pancreatic lesions
| Iglesia-Garcia et al[ | PC (49) | Soft tissue | 6.04 | 100 | 96.3 |
| PC (49) | 26.63 | 100 | 87.8 | ||
| Itokawa et al[ | PC (72), PNET (9), CP (20), normal pancreas (8) | Normal pancreas | 23.66 in MFP | ||
| Dawwas et al[ | Malignant (87): (PC, PNET, metastatic cancer) And benign (17) (pancreatitis) | Soft tissue | 4.65 | 100 | 16.7 |
| Kongkam et al[ | PC (23), PNET (5), Meatastasis (1), CP (2), AIP (3), other (4) | Soft tissue | 3.17 | 86.2 | 66.7 |
| 6.04 | 75.9 | 77.8 |
PC: Pancreatic cancer; PNET: Pancreatic neuroendocrine tumor; CP: Chronic pancreatitis; AIP: Autoimmune pancreatitis.
Figure 4Histogram analysis using MATLABver 1.6.7. A and B: The color image of the elastography is converted into the gray scale (value) of 256 tones ranging from 0 to 255:0 represents the blue area (hard) and 255 represents the red area (soft); C: The distribution of the gray scale is presented as a histogram from which the parameters are calculated.
The histogram parameters[5,21,45]
| Gray scale images | Mean | Mean of the gray levels | Higher mean value indicates softer tissue |
| Standard deviation | Standard deviation of the gray levels | Higher value indicating heterogeneous hardness | |
| ASM | Measure of the homogeneity on the gray scale image | ||
| Contrast | Measure of local gray level variation on the gray scale image | ||
| Correlation | Measure of gray level linear | ||
| dependence on the gray scale image | |||
| Entropy | Measure of the randomness of gray level distribution | ||
| IDM | Measure of the homogeneity on the gray scale image | ||
| Skewness | Measure of the asymmetry of the gray level distribution | Higher value indicating higher or lower hardness | |
| Kurtosis | Measure of the “peakedness” of the gray level distribution | Higher value indicating concentration of a specific hardness | |
| Black and white image | % area | Percentage of the white area (= hard area) | |
| Mean of Complexity | Complex ratio of the shape of the white area (= hard area) and is calculated as periphery2/area of the white area |
Figure 5Endoscopic ultrasound elastography of pancreatic adenocarcinoma. The color pattern showed predominant blue color pattern without distortion of surrounding area.