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Abdolmohammadi J, Shafiee M, Faeghi F, et al. Determination of intra-axial brain tumors cellularity through the analysis of T2 Relaxation time of brain tumors before surgery using MATLAB software. Electron Physician. 2016;8(8):2726-2732doi: 10.19082/2726.
Abdolmohammadi, J., Shafiee, M., Faeghi, F., Arefan, D., Zali, A., Motiei-Langroudi, R., Farshidfar, Z., Nazarlou, A. K., Tavakkoli, A., & Yarham, M. (2016). Determination of intra-axial brain tumors cellularity through the analysis of T2 Relaxation time of brain tumors before surgery using MATLAB software. Electronic physician, 8(8), 2726-2732. https://doi.org/10.19082/2726
Abdolmohammadi, Jamil, et al. "Determination of intra-axial brain tumors cellularity through the analysis of T2 Relaxation time of brain tumors before surgery using MATLAB software." Electronic physician vol. 8,8 (2016): 2726-2732. doi: https://doi.org/10.19082/2726
Abdolmohammadi J, Shafiee M, Faeghi F, Arefan D, Zali A, Motiei-Langroudi R, Farshidfar Z, Nazarlou AK, Tavakkoli A, Yarham M. Determination of intra-axial brain tumors cellularity through the analysis of T2 Relaxation time of brain tumors before surgery using MATLAB software. Electron Physician. 2016 Aug 25;8(8):2726-2732. doi: 10.19082/2726. eCollection 2016 Aug. PMID: 27757181; PMCID: PMC5053452.
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Electron Physician. 2016 Aug 25;8(8):2726-2732. doi: 10.19082/2726. eCollection 2016 Aug.

Determination of intra-axial brain tumors cellularity through the analysis of T2 Relaxation time of brain tumors before surgery using MATLAB software.

Electronic physician

Jamil Abdolmohammadi, Mohsen Shafiee, Fariborz Faeghi, Douman Arefan, Alireza Zali, Rouzbeh Motiei-Langroudi, Zahra Farshidfar, Ali Kiani Nazarlou, Ali Tavakkoli, Mohammad Yarham

Affiliations

  1. M.Sc. of Medical Imaging Technology (MRI), Department of Radiology, Faculty of Paramedical Sciences, Kurdistan University of Medical Sciences, Sanandaj, Iran.
  2. M.Sc. of Medical Physics, Cellular and Molecular Research Center, Yasuj University of Medical sciences, Yasuj, Iran.
  3. Ph.D. in Medical Physics, Radiology Technology Department, School of Allied Medical Sciences, Shahid Beheshti University of Medical Science, Tehran, Iran.
  4. Department of Radiation Medicine Engineering, Shahid Beheshti University, Evin, Tehran, Iran.
  5. Neurosurgeon, Head of Neurosurgery Department of Shohada-E Tajrish Hospital, Chairman of the Medical Council of Iran, Tehran, Iran.
  6. Department of Neurosurgery, Shohada Tajrish Hospital, Shahid Beheshti University of Medical Science, Tehran, Iran.
  7. M.Sc. of Medical Imaging Technology (MRI), Radiology Department of Paramedical School, Shiraz University of Medical Science, Shiraz, Iran.
  8. M.Sc. of Medical Imaging Technology, Department of Radiology, Imam Reza Medical Research and Training Hospital, Golgasht Ave., Tabriz, Iran.
  9. M.Sc. of Medical Imaging Technology (MRI), Bahonar Medical Research and Training Hospital, Alborz University of Medical Science, Karaj, Iran.

PMID: 27757181 PMCID: PMC5053452 DOI: 10.19082/2726

Abstract

INTRODUCTION: Timely diagnosis of brain tumors could considerably affect the process of patient treatment. To do so, para-clinical methods, particularly MRI, cannot be ignored. MRI has so far answered significant questions regarding tumor characteristics, as well as helping neurosurgeons. In order to detect the tumor cellularity, neuro-surgeons currently have to sample specimens by biopsy and then send them to the pathology unit. The aim of this study is to determine the tumor cellularity in the brain.

METHODS: In this cross-sectional study, 32 patients (18 males and 14 females from 18-77 y/o) were admitted to the neurosurgery department of Shohada-E Tajrish Hospital in Tehran, Iran from April 2012 to February 2014. In addition to routine pulse sequences, T2W Multi echo pulse sequences were taken and the images were analyzed using the MATLAB software to determine the brain tumor cellularity, compared with the biopsy.

RESULTS: These findings illustrate the need for more T2 relaxation time decreases, the higher classes of tumors will stand out in the designed table. In this study, the results show T2 relaxation time with a 85% diagnostic weight, compared with the biopsy, to determine the brain tumor cellularity (p<0.05).

CONCLUSION: Our results indicate that the T2 relaxation time feature is the best method to distinguish and present the degree of intra-axial brain tumors cellularity (85% accuracy compared to biopsy). The use of more data is recommended in order to increase the percent accuracy of this techniques.

Keywords: Intra-axial tumor; MATLAB software; MRI; T2 relaxation time

Conflict of interest statement

There is no conflict of interest to be declared.

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