TY - JOUR

T1 - Utilizing the amide proton transfer technique to characterize diffuse gliomas based on the WHO 2021 classification of CNS tumors

AU - Filimonova, Elena

AU - Pashkov, Anton

AU - Borisov, Norayr

AU - Kalinovsky, Anton

AU - Rzaev, Jamil

PY - 2024/8

Y1 - 2024/8

N2 - Diffuse gliomas present a significant challenge for healthcare systems globally. While brain MRI plays a vital role in diagnosis, prognosis, and treatment monitoring, accurately characterizing gliomas using conventional MRI techniques alone is challenging. In this study, we explored the potential of utilizing the amide proton transfer (APT) technique to predict tumor grade and type based on the WHO 2021 Classification of CNS Tumors. Methods: Forty-two adult patients with histopathologically confirmed brain gliomas were included in the study. They underwent 3T MRI imaging, which involved APT sequence. Multinomial and binary logistic regression models were employed to classify patients into clinically relevant groups based on MRI findings and demographic variables. Results: We found that the best model for tumor grade classification included patient age along with APT values. The highest sensitivity (88%) was observed for Grade 4 tumors, while Grade 3 tumors showed the highest specificity (79%). For tumor type classification, our model incorporated four predictors: APT values, patient’s age, necrosis, and the presence of hemorrhage. The glioblastoma group had the highest sensitivity and specificity (87%), whereas balanced accuracy was the lowest for astrocytomas (0.73). Conclusion: The APT technique shows great potential for noninvasive evaluation of diffuse gliomas. The changes in the classification of gliomas as per the WHO 2021 version of the CNS Tumor Classification did not affect its usefulness in predicting tumor grade or type.

AB - Diffuse gliomas present a significant challenge for healthcare systems globally. While brain MRI plays a vital role in diagnosis, prognosis, and treatment monitoring, accurately characterizing gliomas using conventional MRI techniques alone is challenging. In this study, we explored the potential of utilizing the amide proton transfer (APT) technique to predict tumor grade and type based on the WHO 2021 Classification of CNS Tumors. Methods: Forty-two adult patients with histopathologically confirmed brain gliomas were included in the study. They underwent 3T MRI imaging, which involved APT sequence. Multinomial and binary logistic regression models were employed to classify patients into clinically relevant groups based on MRI findings and demographic variables. Results: We found that the best model for tumor grade classification included patient age along with APT values. The highest sensitivity (88%) was observed for Grade 4 tumors, while Grade 3 tumors showed the highest specificity (79%). For tumor type classification, our model incorporated four predictors: APT values, patient’s age, necrosis, and the presence of hemorrhage. The glioblastoma group had the highest sensitivity and specificity (87%), whereas balanced accuracy was the lowest for astrocytomas (0.73). Conclusion: The APT technique shows great potential for noninvasive evaluation of diffuse gliomas. The changes in the classification of gliomas as per the WHO 2021 version of the CNS Tumor Classification did not affect its usefulness in predicting tumor grade or type.

KW - Brain glioma

KW - Ki-67

KW - amide proton transfer imaging

KW - qualitative magnetic resonance imaging

KW - Humans

KW - Glioma/diagnostic imaging

KW - Male

KW - Female

KW - Middle Aged

KW - Brain Neoplasms/diagnostic imaging

KW - Adult

KW - Magnetic Resonance Imaging/methods

KW - Neoplasm Grading

KW - Sensitivity and Specificity

KW - Aged

KW - Young Adult

KW - Protons

KW - Amides

KW - World Health Organization

UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85189043591&origin=inward&txGid=339b8a6458667f45ecf6d6b40d5b8814

UR - https://www.mendeley.com/catalogue/846cdfef-289c-300d-b7a2-771794817a37/

U2 - 10.1177/19714009241242658

DO - 10.1177/19714009241242658

M3 - Article

C2 - 38548655

VL - 37

SP - 490

EP - 499

JO - Neuroradiology Journal

JF - Neuroradiology Journal

SN - 1971-4009

IS - 4

ER -