In the present study, we demonstrate that ioUS strain elastography is a safe and easy-to-apply technique. Furthermore, through the semi-quantitative analysis of the elastograms, it is possible to characterize the different tumor types based on the calculated values of MTE.
Among the strengths of our study, we can mention that this is the largest published series about the application of ioUS strain elastography in brain tumor surgery. In addition, we confirm the findings of an initial study of our group in which we applied and validated the semi-quantitative analysis technique of the colorimetric scale of the elastograms to obtain a measure of the stiffness of the tissues. As far as we know, we are pioneers in applying this type of ultrasound image analysis in brain pathology.
Among the limitations of our work, we can mention the lack of external validation of the elastogram acquisition technique. Furthermore, in our series of cases, the images were acquired by a single surgeon (S.C.). Therefore, in future work, an evaluation of the reproducibility of the acquisition of images must be carried out. Despite this, we offer a detailed description of the ultrasound technique to be replicated in future studies.
The image quality of ultrasound images and elastograms is susceptible to multiple factors.[1, 34, 36] The ultrasound equipment used in our series requires gentle mechanical compressions to acquire strain images. However, other ultrasound scanners are capable of generating elastograms using spontaneous brain pulsations.[27, 28] To obtain high-quality images, the elastograms are acquired before the dural opening. The dura mater offers resistance, and thanks to its elastic capacity, it is possible to perform more homogeneous pulsations, which translates into more uniform elastograms and fewer signal voids. Figure 4. In those cases in which small dural tears occurred, the quality of the elastogram did not vary significantly, at least in a qualitative way. Figure 5A-B. These variations should be studied in the future.
Regarding the ROI size, strain elastography demonstrates the relative stiffness of tissue, so it is crucial to include enough normal tissue surrounding the tumor. The most suitable image quality was registered in phantom experiments when the lesion of interest covered 25–50 % of the ROI. Caution must be taken when using a convex probe since the region immediately in the middle of the transducer could apply more stress than the lateral portions of the probe, producing a “lateral stiffness artifact”.
Another factor that influences the quality of the image is the presence of cystic areas. Figure 5C. The interposition of liquid content can seriously influence the transmission of mechanical pulsations. In these cases, the penetration of mechanical waves does not occur homogeneously throughout the tissue to be explored. Measuring displacement between two frames solely detects random noise, which is displayed in different ways. A commonly described artifact is the BGR (blue-green-red) sign encountered in small cystic tumors. Large cystic lesions are more likely to be seen as "black holes". This circumstance occurs especially in metastases and less frequently in high-grade gliomas, possibly due to their content (cystic-mucinous or necrotic).
Elastograms can also vary depending on the tumor's location and, therefore, on how the mechanical impulse spreads. For example, in deep-seated tumors, the distance from the probe to the tumor can produce artifactual images and overestimate its stiffness. Figure 5D. In addition, in those cases of tumors of the skull base or posterior fossa, the mechanical impulse can make the tissue collide against bone structures, altering its compressibility and, consequently, the elastographic image. Also, it is recommendable to avoid assessment of tissue near stiff areas, as soft tissue will undergo more strain when it is above hard tissue.
In meningioma surgery, strain elastography permits addressing the resection of the tumor with reliable information about its stiffness. The presence of a cleavage plane and the relationships with surrounding neurovascular structures allow the surgeon to adapt the surgical technique and anticipate the extent of the resection. This utility has been demonstrated in previous works.[6, 21, 27] In addition, they are a tumor group in which the elastograms are usually relatively homogeneous because they generally behave as compact masses.
The elastographic pattern of gliomas is very characteristic from a qualitative and quantitative point of view. They are usually tumors softer than the surrounding brain parenchyma, with extensive involvement of the peritumoral white matter, which also shows less stiffness. Peritumoral infiltration may explain a change in elasticity in these regions, as has been postulated.[10, 31] On the other hand, the contrast of the color image is superior to the B-mode when establishing the tumor's edges, as reported by Selbekk et al. in his work.
Metastases also tend to be softer than the normal parenchyma. However, the stiffness of the white matter does not appear to be significantly different compared to that found in primary tumors. Possibly, the presence of pure vasogenic edema present in metastases and meningiomas could explain this difference in peritumoral elasticity. For this, it is essential in future studies to carry out a histopathological correlation of these areas.
Histological classification based on elastography and glioma grading
Our results show significant differences in tumor and peritumoral stiffness expressed through MTE between gliomas and the rest of the tumor groups (metastases and meningiomas). These results are validated by applying the classification algorithm based on a decision tree, which reaches a precision of 70%. However, even though metastases showed less tumor stiffness than meningiomas (113 vs. 120), these differences were not statistically significant. Furthermore, their peritumoral MTE values were very similar (122 vs. 126).
Regarding glioma grading by ioUS elastography, we found previous descriptions in the literature in which a lower elasticity was observed in high-grade gliomas than low-grade gliomas.[7, 13, 28, 43] However, in our study, although tumor and peritumoral MTE values are indeed lower in high-grade glioma than low-grade glioma (80 vs. 86, 91 vs. 96, respectively), these differences were not statistically significant. Neither, we found differences after analyzing the histological subtypes and degrees of aggressiveness in the glioma group.
Strain elastography versus shear wave elastography
There are two types of ultrasound elastography, strain and shear wave. Strain elastography is a qualitative technique and provides knowledge on the relative stiffness between one tissue and another. Shear wave elastography (SWE) is a quantitative method that offers an estimated value of the tissue stiffness that can be expressed in either the shear wave speed through the tissues in meters per second or converted to Young’s modulus and expressed in kilopascals. A critical advantage of SWE is to perform acquisitions to assess the extent of the resection. Using strain elastography, it is impossible to perform compressions on the deformed parenchyma and the interposition of fluid that fills the surgical cavity. In this sense, the SWE stands as the best option to assess residual tumor.
The main limitation of the SWE is the size of the Q-box, which is the region of interest in which the color maps and elasticity values are obtained. Unfortunately, this region is usually limited in size, and the vast majority of cases do not cover the entire tumor and peritumor area. In this regard, strain elastography has an advantage by offering a more extensive and visually richer image compared to SWE. In addition, strain elastography allows an overview of relative tissue stiffness in a large field of view. This aspect is advantageous if we want to assess, for example, the stiffness of a tumor area close to a noble structure and to know globally if its stiffness has a homogeneous or heterogeneous pattern.
Each technique has its advantages and disadvantages, and maybe they should be used in a complementary way in brain tumor surgery.
Brain elastography and future perspectives
The usefulness of intraoperative cerebral elastography goes beyond the characterization of the histopathological types and serves as a support for surgical resection. Knowledge of the elasticity and stiffness of tissues is biologically based and is related to the cytoarchitecture of tumors and their ability to infiltrate in gliomas.[37, 38]
Advanced image processing techniques, such as texture analysis, also known as radiomics, can increase the diagnostic potential of this imaging technique and even contribute to predict the survival and progression of primary brain neoplasms.
On the other hand, image processing automation and the combination of recognition techniques based on artificial intelligence are yet to be explored in depth.