Role of intra-tumoral vasculature imaging features on susceptibility weighted imaging in differentiating primary central nervous system lymphoma from glioblastoma: a multiparametric comparison with pathological validation.
Purpose: Primary objective of this study was to retrospectively evaluate the potential of a range of qualitative and quantitative multiparametric features assessed on T2, post-contrast T1, DWI, DCE-MRI, and susceptibility-weighted-imaging (SWI) in differentiating evenly sampled cohort of primary-cen...
| Publicado en: | Neuroradiology Vol. 64; no. 9; pp. 1801 - 1819 |
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| Autores principales: | , , , , , , , , , , |
| Formato: | diagnostic images pictorial research tables/charts Journal Article |
| Publicado: |
Springer Nature
Sep2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=158447265&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 158447265 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00283940 NYZ jtl: Neuroradiology issn: 00283940 maglogo: N pubinfo: dt: Sep2022 vid: 64 iid: 9 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 158447265 156376797 158447265 158447265 10.1007/s00234-022-02946-5 158447265 ppf: 1801 ppct: 18 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Role of intra-tumoral vasculature imaging features on susceptibility weighted imaging in differentiating primary central nervous system lymphoma from glioblastoma: a multiparametric comparison with pathological validation. aug: au: Bhattacharjee, Rupsa Gupta, Mamta Singh, Tanu Sharma, Shalini Khanna, Gaurav Parvaze, Suhail P. Patir, Rana Vaishya, Sandeep Ahlawat, Sunita Singh, Anup Gupta, Rakesh Kumar affil: Center for Biomedical Engineering, Indian Institute of Technology Delhi, Delhi, India sug: subj: Central Nervous System Neoplasms Diagnosis Lymphoma Diagnosis Glioma Diagnosis Magnetic Resonance Imaging Methods Brain Pathology Human Retrospective Design Female Male Adult Middle Age Aged Aged, 80 and Over Adult: 19-44 years Middle Aged: 45-64 years Aged: 65+ years Aged, 80 & over Female Male ab: Purpose: Primary objective of this study was to retrospectively evaluate the potential of a range of qualitative and quantitative multiparametric features assessed on T2, post-contrast T1, DWI, DCE-MRI, and susceptibility-weighted-imaging (SWI) in differentiating evenly sampled cohort of primary-central-nervous-system-lymphoma (PCNSL) vs glioblastoma (GB) with pathological validation. Methods: The study included MRI-data of histopathologically confirmed ninety-five GB and PCNSL patients scanned at 3.0 T MRI. A total of six qualitative features (three from T2 and post-contrast T1, three from SWI: thin-linear-uninterrupted-intra-tumoral-vasculature, broken-intra-tumoral-microvasculature, hemorrhage) were analyzed by three independent radiologists. Ten quantitative features from DWI and DCE-MRI were computed using in-house-developed algorithms. For qualitative features, Cohen's Kappa-interrater-variability-analysis was performed. Z-test and independent t-tests were performed to find significant qualitative and quantitative features respectively. Logistic-regression (LR) classifiers were implemented for evaluating performance of individual and various combinations of features in differentiating PCNSL vs GB. Performance evaluation was done via ROC-analysis. Pathological validation was performed to verify disintegration of vessel walls in GB and rim of viable neoplastic lymphoid cells with angiocentric-pattern in PCNSL. Results: Three qualitative SWI features and four quantitative DCE-MRI features (rCBVcorr, Kep, Ve, and necrosis-volume-percentage) were significantly different (p < 0.05) between PCNSL and GB. Best diagnostic performance was observed with LR classifier using SWI features (AUC-0.99). The inclusion of quantitative features with SWI feature did not improve the differentiation accuracy. Conclusions: The combination of three qualitative SWI features using LR provided the highest accuracy in differentiating PCNSL and GB. Thin-linear-uninterrupted-intra-tumoral-vasculature in PCNSL and broken-intra-tumoral-microvasculature with hemorrhage in GB are the major contributors to the differentiation. pubtype: Academic Journal doctype: diagnostic images pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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