Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Histopathological diagnosis is the current standard for the classification of brain and spine tumors. Raman spectroscopy has been reported to allow fast and easy intraoperative tissue analysis. Here, we report data on the intraoperative implementation of a stimulated Raman histology (SRH) as an innovative strategy offering intraoperative near real-time histopathological analysis. A total of 429 SRH images from 108 patients were generated and analyzed by using a Raman imaging system (Invenio Imaging Inc.). We aimed at establishing a dedicated workflow for SRH serving as an intraoperative diagnostic, research, and quality control tool in the neurosurgical operating room (OR). First experiences with this novel imaging modality were reported and analyzed suggesting process optimization regarding tissue collection, preparation, and imaging. The Raman imaging system was rapidly integrated into the surgical workflow of a large neurosurgical center. Within a few minutes of connecting the device, the first high-quality images could be acquired in a "plug-and-play" manner. We did not encounter relevant obstacles and the learning curve was steep. However, certain prerequisites regarding quality and acquisition of tissue samples, data processing and interpretation, and high throughput adaptions must be considered. Intraoperative SRH can easily be integrated into the workflow of neurosurgical tumor resection. Considering few process optimizations that can be implemented rapidly, high-quality images can be obtained near real time. Hence, we propose SRH as a complementary tool for the diagnosis of tumor entity, analysis of tumor infiltration zones, online quality and safety control and as a research tool in the neurosurgical OR.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8976801 | PMC |
http://dx.doi.org/10.1007/s10143-021-01712-0 | DOI Listing |
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