Diagnosis and analysis of primary central nervous system lymphoma based on MRI segmentation algorithm
Objective: This paper summarizes the MRI imaging findings of primary central nervous system lymphoma (PCNSL) in the posterior cranial fossa to improve the accuracy of PCNSL diagnosis in the posterior cranial fossa.
Methods: This study retrospectively analyzed the MRI imaging manifestations of 15 PCNSL posterior cranial fossa cases confirmed by puncture or surgical pathology from June 2017 to May 2018, including their occurrence sites, the number of lesions, MRI plain and enhanced manifestations, and diffusion-weighted imaging (DWI) and magnetic resonance spectroscopy. Imaging (MRS) performance.
Results: A total of 15 cases were enrolled, including 10 cases of single lesion and five cases of multiple lesions. The total number of lesions was 25, which were in the cerebellar hemisphere and cerebellar vermis, midbrain, fourth ventricle, and pontine cerebellum. The lesions were round, irregular, nodular, patchy, with low or medium signals on T1WI, equal or slightly higher signals on T2WI, and enhanced with 25 meningiomas-like gray matter signals. All of them were significantly strengthened. “Acupoint sign” and “umbilical depression sign” were seen in eight lesions. There were 17 massive and nodular enhancements, four striped enhancements, three patchy enhancements, and one circular enhancement. five cases of DWI showed homogeneous high signal, two cases showed uneven high signal, and 3 cases showed medium signal. The ADC value of tumor parenchyma in 10 patients was (0.62±0.095)×10-3mm2/s. MRS examination showed obvious Lip peak in two cases.
Conclusion: PCNSL in posterior cranial fossa has certain characteristics. DWI, ADC value and MRS are helpful to improve the correct diagnosis rate of PCNSL.
How to cite this:
Lu G, Li Y, Liang X, Zhao Z. Diagnosis and analysis of primary central nervous system lymphoma based on MRI segmentation algorithm. Pak J Med Sci. 2021;37(6):1585-1589. doi: https://doi.org/10.12669/pjms.37.6-WIT.4843
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.