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- F., Durmo, et al.
(författare)
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Multivoxel 1H MR spectroscopy biometrics for preoprerative differentiation between brain tumors
- 2018
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Ingår i: Neuroradiology. - : Springer Science and Business Media LLC. - 1432-1920 .- 0028-3940. ; 60:S2, s. 444-444
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Konferensbidrag (refereegranskat)abstract
- Purpose To investigate multivoxel proton Magnetic Resonance Spectroscopy (1HMRS) biometrics for preoperative differentiation and prognosis of patients with brain metastases (MET), low-(LGG) and high grade glioma (HGG). Methods Thirty-five patients (15 HGG, 9 LGG and 11 MET) were included. Proton Magnetic Resonance Spectroscopy Imaging(1H-MRSI) data was assessed and neurochemical profiles for metabolites (NAA+NAAG, Cr+PCr, Glu+Gln (Glx), Lac, Ins, GPC+PCho) and total Lipids (tLip) and macromolecule (tMM) signals were estimated. Concentrations were reported as either absolute or ratios to total choline (tCho=GPC+PCho) and creatine (tCr=Cr+PCr) levels. Voxels of interest (VOIs) in a MRSI matrix were labelled accordingly to contrast-enhancing/nonenhancing lesional, edema, ipsi- or contralateral healthy appearing tissue and the metabolite averages were reported for each tissue type. Multi-biometric analysis with logistic regression, ROC- and Kaplan-Meier survival analysis was performed in SPSS v.24 and postprocessing with LC Model. Results Across HGG/LGG/MET; the average Ins/tCho was shown to be prognostic for overall survival (OS): with low values (≤1.29) in affected hemisphere predicting worse OS than high values (>1.29), (Log Rank
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| 3. |
- F., Durmo, et al.
(författare)
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Mutlimodality MR imaging for differentiation between brain tumor lesions
- 2016
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Ingår i: Neuroradiology. - : Springer Science and Business Media LLC. - 0028-3940 .- 1432-1920. ; 58:Suppl 1, s. 53-54
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Konferensbidrag (refereegranskat)abstract
- Purpose: Applying diffusion and perfusion metrics for evaluation of low-(LGG), high grade glioma (HGG) and metastases (MET) for differential diagnosis. Materials and Method: 43 patients (18HGG, 10 LGG, and 15MET) were included. MR data for tumour volume, perilesional edema, rCBF-, rCBV-, FLAIR-, FA-, ADC-maps were quantified by regions of interest (ROI). Measures of different parameters, and ratios, using contralateral white matter as denominator, were performed. A binary logistic regression model was constructed for multi-parametric analysis and ROCanalysis. Results: Significant difference was found for nADCt, rCBF, rCBV between LGG and HGG, nADCe between HGG and MET, and Ev, Ev-Tv ratio, nADCt, nADCe, rCBF, rCBV between LGG and MET. ROCanalysis for HGG compared to LGG showed 80 % sensitivity and 81.2 % specificity for nADCt, 100 % sensitivity and 100 % specificity for rCBF and 80 % sensitivity and 90 % specificity for rCBV. ROC-curves betweenMETand LGG showed sensitivity and specificity for Ev 73.3 % and 90 %, Ev-Tv ratio 80 % and 100 %, nADCt 90 % and 86.7 %, nADCe 80 % and 90 %, rCBF 93.3 % and 100 %, and rCBV 60 % and 100 %. Combining Ev, Ev-Tv ratio, nADCt, nADCe and rCBV between METand LGG gave 93.3%sensitivity and 100%specificity. Combining nADCt and rCBV between HGG and LGG 86.7 % sensitivity and 100 % specificity. Conclusion: Multi-parametric imaging protocols is an advantage for preoperative distinction of LGG, HGG and MET.
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