Research code: 1400-1-103-21205
Ethics code: IR.IUMS.FMD.REC.1401.176
Clinical trials code: 1400-1-103-21205
Iran University of Medical Science , salar.ea93@gmail.com
Abstract: (264 Views)
Background:
Strain Elastography (SE) is an emerging ultrasound-based imaging technique that allows the real-time assessment of tissue elasticity. By evaluating how tissues deform in response to applied mechanical stress, SE provides surgeons with a dynamic, intraoperative view of tissue consistency, offering critical insights into tumor and healthy tissue differentiation. This capability is particularly vital in neurosurgery, where the challenge of accurately delineating tumor margins is paramount for reducing the risk of residual tumor tissue and preserving healthy brain matter. In brain tumor resections, achieving a complete resection without damaging surrounding healthy tissue is essential, especially in high-grade tumors like glioblastomas, where recurrence rates are high if residual tumor remains. This study investigates using SE in the intraoperative setting to assist neurosurgeons in achieving more precise tumor resections. Specifically, the study evaluates SE's effectiveness in distinguishing between tumor and healthy brain tissues during surgery and its impact on postoperative outcomes, such as the rate of residual tumor tissue and the need for further surgical interventions.
Methods:
This study was conducted at Rasoul Akram Hospital of Iran University of Medical Sciences, focusing on 15 patients who underwent brain tumor resections. These patients were selected based on the following inclusion criteria: diagnosed brain tumors requiring surgical resection based on pre-operative MRI and CT scans and consent to the use of SE during their surgical procedures. The types of tumors are low-grade gliomas, high-grade glioblastomas, and metastasis. All patients ranged in age from 13 to 73, with 40% female and 60% male.
Before surgery, each patient underwent standard imaging protocols, including MRI with contrast and CT scans. These imaging modalities provided a detailed map of the brain lesions, including tumor location and involvement of critical structures. A multidisciplinary team, including neurosurgeons, neuroradiologists, and neurooncologists, reviewed these pre-operative images to develop a surgical plan to maximize tumor resection while preserving neurological function.
During the surgery, the surgeon evaluated the remaining tumor by examining tissue texture; afterward, the tumor residue was assessed using conventional B-mode ultrasound, followed by SE.
The key aspect of SE is its ability to visualize tissue deformation under stress, allowing surgeons to map out tumor boundaries more accurately. The elasticity contrast between tumor and healthy tissues was measured by applying gentle pressure with the ultrasound probe, causing the tissue to compress. SE captured the resultant deformation and produced a color-coded map indicating areas of differing elasticity. Firmer tissues, indicative of tumor presence, were displayed in cooler colors (blue), while more elastic tissues, corresponding to healthy brain matter, were displayed in warmer colors (red and green). If all assessments indicate a resectable tumor residue, the steps mentioned above are repeated until all the tumor is resected or unresectable residue remains. Following surgery, all patients underwent post-operative MRI within 48 hours to assess the extent of tumor resection and to identify any residual tumor tissue.
The primary outcome measure was the correlation between SE findings and post-operative MRI results regarding residual tumor presence, as well as the correlation between the Surgeon’s assessment and B-Mode Ultrasonography with each other and post-operative MRI has been calculated. Statistical analyses were performed using SPSS software, with a significance threshold set at p < 0.05. The Pearson correlation coefficient was used to evaluate the relationship between SE findings and residual tumor detection on postoperative MRI.
Results:
The study's results highlight the effectiveness of Strain Elastography (SE) as a valuable intraoperative tool for brain tumor resections. Out of the 15 patients evaluated, 53.3% (8 patients) achieved complete tumor resections, confirmed through post-operative MRI. SE demonstrated high sensitivity in detecting residual tumor tissue, successfully identifying areas of concern in 6 patients. Post-operative MRI confirmed these findings, illustrating SE's capability to provide accurate intraoperative feedback. SE missed residual tumor tissue in only one case, which underscores its generally strong correlation with post-operative MRI (0.87, p = 0.0043). This high correlation suggests that SE can significantly improve the precision of brain tumor resections by enabling surgeons to identify tumor margins more accurately.
The study also revealed a considerable disparity between SE and the other evaluation methods—B-mode ultrasound and surgeon assessment—regarding residual tumor detection. The surgeon's evaluation correlated less with post-operative MRI (0.53), and B-mode ultrasound showed an even weaker correlation (0.47), both falling below statistical significance. These findings emphasize the superior accuracy of SE in providing real-time assessments of brain tissue elasticity, especially in cases of high-grade tumors like glioblastomas, where tissue consistency plays a critical role in distinguishing tumor from healthy tissue. Moreover, the lack of correlation between tumor location and residual detection suggests that SE’s accuracy is consistent across different tumor sites.
Analyzing patient demographics, SE’s effectiveness remained consistent across various age groups and tumor types, demonstrating that this technology is reliable for a wide range of patients. While glioblastomas and other high-grade tumors present significant surgical challenges, SE’s color-coded elasticity mapping proved crucial in differentiating firmer tumor tissues from softer healthy tissues, contributing to more thorough resections.
Conclusion:
The study concludes that SE substantially enhances the precision of brain tumor resections by offering real-time, intraoperative insights into tissue elasticity. SE’s high correlation with post-operative MRI findings underscores its potential as an essential tool for neurosurgeons, particularly in the resection of high-grade tumors such as glioblastomas. Its ability to differentiate between tumor and healthy brain tissue reduces the risk of residual tumor tissue, which could otherwise lead to tumor recurrence and the need for additional surgeries.
SE outperformed traditional methods such as surgeon assessment and B-mode ultrasound, demonstrating superior sensitivity in identifying residual tumors. These findings suggest that integrating SE into neurosurgical procedures could lead to improved patient outcomes by reducing the incidence of incomplete tumor resections and associated complications.
The study highlights the need for further research to standardize SE protocols and expand their applicability to a broader range of brain lesions. Future research should also focus on larger patient populations and long-term outcomes, including survival rates and recurrence. As SE becomes more accessible, it is expected to play a pivotal role in improving the precision of brain surgeries, ultimately contributing to better patient prognosis.
Strain Elastography (SE) is an emerging ultrasound-based imaging technique that allows the real-time assessment of tissue elasticity. By evaluating how tissues deform in response to applied mechanical stress, SE provides surgeons with a dynamic, intraoperative view of tissue consistency, offering critical insights into tumor and healthy tissue differentiation. This capability is particularly vital in neurosurgery, where the challenge of accurately delineating tumor margins is paramount for reducing the risk of residual tumor tissue and preserving healthy brain matter. In brain tumor resections, achieving a complete resection without damaging surrounding healthy tissue is essential, especially in high-grade tumors like glioblastomas, where recurrence rates are high if residual tumor remains. This study investigates using SE in the intraoperative setting to assist neurosurgeons in achieving more precise tumor resections. Specifically, the study evaluates SE's effectiveness in distinguishing between tumor and healthy brain tissues during surgery and its impact on postoperative outcomes, such as the rate of residual tumor tissue and the need for further surgical interventions.
Methods:
This study was conducted at Rasoul Akram Hospital of Iran University of Medical Sciences, focusing on 15 patients who underwent brain tumor resections. These patients were selected based on the following inclusion criteria: diagnosed brain tumors requiring surgical resection based on pre-operative MRI and CT scans and consent to the use of SE during their surgical procedures. The types of tumors are low-grade gliomas, high-grade glioblastomas, and metastasis. All patients ranged in age from 13 to 73, with 40% female and 60% male.
Before surgery, each patient underwent standard imaging protocols, including MRI with contrast and CT scans. These imaging modalities provided a detailed map of the brain lesions, including tumor location and involvement of critical structures. A multidisciplinary team, including neurosurgeons, neuroradiologists, and neurooncologists, reviewed these pre-operative images to develop a surgical plan to maximize tumor resection while preserving neurological function.
During the surgery, the surgeon evaluated the remaining tumor by examining tissue texture; afterward, the tumor residue was assessed using conventional B-mode ultrasound, followed by SE.
The key aspect of SE is its ability to visualize tissue deformation under stress, allowing surgeons to map out tumor boundaries more accurately. The elasticity contrast between tumor and healthy tissues was measured by applying gentle pressure with the ultrasound probe, causing the tissue to compress. SE captured the resultant deformation and produced a color-coded map indicating areas of differing elasticity. Firmer tissues, indicative of tumor presence, were displayed in cooler colors (blue), while more elastic tissues, corresponding to healthy brain matter, were displayed in warmer colors (red and green). If all assessments indicate a resectable tumor residue, the steps mentioned above are repeated until all the tumor is resected or unresectable residue remains. Following surgery, all patients underwent post-operative MRI within 48 hours to assess the extent of tumor resection and to identify any residual tumor tissue.
The primary outcome measure was the correlation between SE findings and post-operative MRI results regarding residual tumor presence, as well as the correlation between the Surgeon’s assessment and B-Mode Ultrasonography with each other and post-operative MRI has been calculated. Statistical analyses were performed using SPSS software, with a significance threshold set at p < 0.05. The Pearson correlation coefficient was used to evaluate the relationship between SE findings and residual tumor detection on postoperative MRI.
Results:
The study's results highlight the effectiveness of Strain Elastography (SE) as a valuable intraoperative tool for brain tumor resections. Out of the 15 patients evaluated, 53.3% (8 patients) achieved complete tumor resections, confirmed through post-operative MRI. SE demonstrated high sensitivity in detecting residual tumor tissue, successfully identifying areas of concern in 6 patients. Post-operative MRI confirmed these findings, illustrating SE's capability to provide accurate intraoperative feedback. SE missed residual tumor tissue in only one case, which underscores its generally strong correlation with post-operative MRI (0.87, p = 0.0043). This high correlation suggests that SE can significantly improve the precision of brain tumor resections by enabling surgeons to identify tumor margins more accurately.
The study also revealed a considerable disparity between SE and the other evaluation methods—B-mode ultrasound and surgeon assessment—regarding residual tumor detection. The surgeon's evaluation correlated less with post-operative MRI (0.53), and B-mode ultrasound showed an even weaker correlation (0.47), both falling below statistical significance. These findings emphasize the superior accuracy of SE in providing real-time assessments of brain tissue elasticity, especially in cases of high-grade tumors like glioblastomas, where tissue consistency plays a critical role in distinguishing tumor from healthy tissue. Moreover, the lack of correlation between tumor location and residual detection suggests that SE’s accuracy is consistent across different tumor sites.
Analyzing patient demographics, SE’s effectiveness remained consistent across various age groups and tumor types, demonstrating that this technology is reliable for a wide range of patients. While glioblastomas and other high-grade tumors present significant surgical challenges, SE’s color-coded elasticity mapping proved crucial in differentiating firmer tumor tissues from softer healthy tissues, contributing to more thorough resections.
Conclusion:
The study concludes that SE substantially enhances the precision of brain tumor resections by offering real-time, intraoperative insights into tissue elasticity. SE’s high correlation with post-operative MRI findings underscores its potential as an essential tool for neurosurgeons, particularly in the resection of high-grade tumors such as glioblastomas. Its ability to differentiate between tumor and healthy brain tissue reduces the risk of residual tumor tissue, which could otherwise lead to tumor recurrence and the need for additional surgeries.
SE outperformed traditional methods such as surgeon assessment and B-mode ultrasound, demonstrating superior sensitivity in identifying residual tumors. These findings suggest that integrating SE into neurosurgical procedures could lead to improved patient outcomes by reducing the incidence of incomplete tumor resections and associated complications.
The study highlights the need for further research to standardize SE protocols and expand their applicability to a broader range of brain lesions. Future research should also focus on larger patient populations and long-term outcomes, including survival rates and recurrence. As SE becomes more accessible, it is expected to play a pivotal role in improving the precision of brain surgeries, ultimately contributing to better patient prognosis.
Type of Study: Research |
Subject:
Neurosurgery
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