| ORIGINAL ARTICLE |
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| Year : 2022 | Volume
: 29
| Issue : 1 | Page : 33-41 |
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Multiparametric differentiation of intracranial central nervous system lymphoma and high-grade glioma using diffusion-, perfusion-, susceptibility-weighted magnetic resonance imaging, and spectroscopy
Santosh Rai1, Fathima Raeesa1, Mayur Kamath2, Sharada Rai3, Muralidhar K Pai2, Sonali D Prabhu1
1 Department of Radiodiagnosis, Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, Karnataka, India
2 Department of Neurosurgery, Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, Karnataka, India
3 Department of Pathology, Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, Karnataka, India
Correspondence Address:
Dr. Santosh Rai
Department of Radiodiagnosis, Kasturba Medical College, Manipal Academy of Higher Education, Mangalore - 575 001, Karnataka
India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/wajr.wajr_16_21
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Aims and Objectives: To observe the characteristics of primary central nervous system lymphoma (PCNSL) and high-grade glioma (HGG) in diffusion-weighted imaging (DWI), perfusion-weighted imaging (PWI), susceptibility-weighted imaging (SWI) and spectroscopy, and differentiate them based on these parameters.
Materials and Methods: A total of 45 patients diagnosed with the central nervous system (CNS) neoplasm on magnetic resonance imaging (MRI) using 1.5 Tesla MRI Siemens Magnetom Avanto (Siemens, Germany) and with subsequent histopathological evidence as glioblastoma or CNS lymphoma were included. The study was completed over a period of 2 years.
Results: It was found that DWI is effective in the differentiation of HGGs and PCNSLs. A total of 20 (57.1%) HGGs showed diffusion restriction, whereas 9 (90%) of the PCNSLs showed diffusion restriction. The mean apparent diffusion coefficient (ADC) (×10–6 mm2/s) in PCNSLs was 646 whereas, in HGGs, it was found to be 824.3. Thirty-one (88.6%) of the HGGs showed increased perfusion. The mean value of rCBVmean in HGG was found to be 4.06 and the mean value of rCBVmax was 3.63. None of the PCNSLs showed increased perfusion. The mean value of rCBVmean in PCNSLs was 0.097 and rCBVmax was 0.133. 30 (85.7%) of HGGs showed significant areas of blooming on SWI (in the form of intratumoral susceptibility signals [ITSS]). None of the PCNSLs showed blooming. All HGGs and PCNSLs showed increased choline and decreased N acetyl aspartate (NAA) on spectroscopy. Mean Choline/Creatine (Cho/Cr) in HGGs was found to be 3.06, whereas in PCNSLs, it was 1.84.
Conclusion: It is important to make a distinction between HGG and PCNSL as the treatment modalities are different for both. Multiparametric evaluation of ADC, ITSS, and rCBVmean allows the differentiation of PCNSLs and solid glioblastoma which supports the integration of advanced MR imaging techniques including DSC-PWI, DWI, and SWI for the routine diagnostic workup of these tumors.
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