Detecting Double Expression Status in Primary Central Nervous System Lymphoma Using Multiparametric <scp>MRI</scp> Based Machine Learning

Guo-li, Liu; Zhang, Xinyue; Zhang, Nan; Xiao, Hua-Feng; Chen, Xinjing; Ma, Lin

doi:10.1002/jmri.28782

Cited by 5 publications

(1 citation statement)

References 40 publications

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“…Both DHL and DEL are associated with a more aggressive clinical course and a worse prognosis for DLBCL patients [ 232 ]. Compared to DHL, DEL is more common in patients with PCNSL[ 130 , 233 , 234 ]. Therefore, we focused on the impact of DEL on the prognosis of PCNSL patients.…”

Section: Prognostic Markers For Pcnslmentioning

confidence: 99%

Extranodal lymphoma: pathogenesis, diagnosis and treatment

Yang,

Xun,

et al. 2023

Mol Biomed

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Approximately 30% of lymphomas occur outside the lymph nodes, spleen, or bone marrow, and the incidence of extranodal lymphoma has been rising in the past decade. While traditional chemotherapy and radiation therapy can improve survival outcomes for certain patients, the prognosis for extranodal lymphoma patients remains unsatisfactory. Extranodal lymphomas in different anatomical sites often have distinct cellular origins, pathogenic mechanisms, and clinical manifestations, significantly influencing their diagnosis and treatment. Therefore, it is necessary to provide a comprehensive summary of the pathogenesis, diagnosis, and treatment progress of extranodal lymphoma overall and specifically for different anatomical sites. This review summarizes the current progress in the common key signaling pathways in the development of extranodal lymphomas and intervention therapy. Furthermore, it provides insights into the pathogenesis, diagnosis, and treatment strategies of common extranodal lymphomas, including gastric mucosa-associated lymphoid tissue (MALT) lymphoma, mycosis fungoides (MF), natural killer/T-cell lymphoma (nasal type, NKTCL-NT), and primary central nervous system lymphoma (PCNSL). Additionally, as PCNSL is one of the extranodal lymphomas with the worst prognosis, this review specifically summarizes prognostic indicators and discusses the challenges and opportunities related to its clinical applications. The aim of this review is to assist clinical physicians and researchers in understanding the current status of extranodal lymphomas, enabling them to make informed clinical decisions that contribute to improving patient prognosis.

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Section: Prognostic Markers For Pcnslmentioning

confidence: 99%

Extranodal lymphoma: pathogenesis, diagnosis and treatment

Yang,

Xun,

et al. 2023

Mol Biomed

View full text Add to dashboard Cite

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Editorial for “Detecting Double Expression Status in Primary Central Nervous System Lymphoma Using Multiparametric MRI Based Machine Learning”

Hwang

2023

Magnetic Resonance Imaging

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Prognostic Assessment in Patients With Primary Diffuse Large B‐Cell Lymphoma of the Central Nervous System Using MRI‐Based Radiomics

Liu,

Tu,

et al. 2024

Magnetic Resonance Imaging

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BackgroundPrimary central nervous system lymphoma (PCNSL) carries a poor prognosis. Radiomics may hold potential value in prognostic assessment.PurposeTo develop and validate an MRI‐based radiomics model and combine it with clinical factors to assess progression‐free survival (PFS) and overall survival (OS) of patients with PCNSL.Study TypeRetrospective and prospective.PopulationThree hundred seventy‐nine patients (179 female, 53 ± 7 years) from 2014 to 2022.Field Strength/SequenceT2/fluid‐attenuated inversion recovery, contrast‐enhanced T1WI and diffusion‐weighted echo‐planar imaging sequences on 3.0 T.AssessmentRadiomics features were extracted from enhanced tumor regions on preoperative multi‐sequence MRI. Using a least absolute shrinkage and selection operator (LASSO) Cox regression model to select radiomic signatures in training cohort (N = 169). Cox proportional hazards models were constructed for clinical, radiomics, and combined models, with internal (N = 72) and external (N = 32) cohorts validating model performance.Statistical TestsChi‐squared, Mann–Whitney, Kaplan–Meier, log‐rank, LASSO, Cox, decision curve analysis, time‐dependent Receiver Operating Characteristic, area under the curve (AUC), and likelihood ratio test. P‐value <0.05 was considered significant.ResultsFollow‐up duration was 28.79 ± 22.59 months (median: 25). High‐risk patients, determined by the median radiomics score, showed significantly lower survival rates than low‐risk patients. Compared with NCCN‐IPI, conventional imaging and clinical models, the combined model achieved the highest C‐index for both PFS (0.660 internal, 0.802 external) and OS (0.733 internal, 0.781 external) in validation. Net benefit was greater with radiomics than with clinical alone. The combined model exhibited performance with AUCs of 0.680, 0.752, and 0.830 for predicting 1‐year, 3‐year, and 5‐year PFS, and 0.770, 0.789, and 0.863 for OS in internal validation, with PFS AUCs of 0.860 and 0.826 and OS AUCs of 0.859 and 0.748 for 1‐year and 3‐year survival in external validation.Data ConclusionIncorporating a multi‐sequence MR‐based radiomics model into clinical models enhances the assess accuracy for the prognosis of PCNSL.Evidence Level4Technical EfficacyStage 2

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Detecting Double Expression Status in Primary Central Nervous System Lymphoma Using Multiparametric MRI Based Machine Learning

Cited by 5 publications

References 40 publications

Extranodal lymphoma: pathogenesis, diagnosis and treatment

Extranodal lymphoma: pathogenesis, diagnosis and treatment

Editorial for “Detecting Double Expression Status in Primary Central Nervous System Lymphoma Using Multiparametric MRI Based Machine Learning”

Prognostic Assessment in Patients With Primary Diffuse Large B‐Cell Lymphoma of the Central Nervous System Using MRI‐Based Radiomics

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