| Title |
A surgical strategy for lower grade gliomas using intraoperative molecular diagnosis
|
|---|---|
| Published in |
Brain Tumor Pathology, July 2018
|
| DOI | 10.1007/s10014-018-0324-1 |
| Pubmed ID | |
| Authors |
Shunichi Koriyama, Masayuki Nitta, Tatsuya Kobayashi, Yoshihiro Muragaki, Akane Suzuki, Takashi Maruyama, Takashi Komori, Kenta Masui, Taiichi Saito, Takayuki Yasuda, Junji Hosono, Saori Okamoto, Takahiro Shioyama, Hiroaki Yamatani, Takakazu Kawamata |
| Abstract |
Lower grade gliomas are both treated and diagnosed via surgical resection. Maximum tumor resection is currently the standard of care; however, this risks the loss of brain function. Glioma can be genetically subdivided into three different types, based on isocitrate dehydrogenase (IDH) mutation status and the presence of 1p/19q codeletion, which have radically different prognoses and responses to adjuvant therapies. Therefore, the means to identify the subtype and evaluate the surrounding tissues during surgery would be advantageous. In this study, we have developed a new surgical strategy for lower grade glioma based on the fourth edition of the World Health Organization Brain Tumor Classification, involving intraoperative molecular diagnosis. High-resolution melting analysis was used to evaluate IDH mutational status, while rapid immunohistochemistry of p53 and alpha-thalassemia/mental retardation syndrome X-linked (ATRX) was used to evaluate the 1p/19q codeletion status, allowing genetic classification during surgery. In addition, intraoperative flow cytometry was used to evaluate the surgical cavity for additional tumor lesions, allowing maximal resection while mitigating the risk of functional losses. This strategy allows the rapid intraoperative diagnosis and mapping of lower grade gliomas, and its clinical use could dramatically improve its prognosis. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 19 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 5 | 26% |
| Other | 3 | 16% |
| Student > Master | 3 | 16% |
| Student > Ph. D. Student | 1 | 5% |
| Professor | 1 | 5% |
| Other | 2 | 11% |
| Unknown | 4 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 7 | 37% |
| Biochemistry, Genetics and Molecular Biology | 3 | 16% |
| Computer Science | 1 | 5% |
| Neuroscience | 1 | 5% |
| Engineering | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 6 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 July 2018.
All research outputs
#20,525,274
of 23,094,276 outputs
Outputs from Brain Tumor Pathology
#117
of 170 outputs
Outputs of similar age
#287,067
of 327,716 outputs
Outputs of similar age from Brain Tumor Pathology
#4
of 6 outputs
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