Dataset Information

Evaluating survival in subjects with astrocytic brain tumors by dynamic susceptibility-weighted perfusion MR imaging.

ABSTRACT:

Purpose

Studies have evaluated the application of perfusion MR for predicting survival in patients with astrocytic brain tumors, but few of them statistically adjust their results to reflect the impact of the variability of treatment administered in the patients. Our aim was to analyze the association between the perfusion values and overall survival time, with adjustment for various clinical factors, including initial treatments and follow-up treatments.

Materials and methods

This study consisted of 51 patients with astrocytic brain tumors who underwent perfusion-weighted MRI with MultiHance® at a dose of 0.1 mmol/kg prior to initial surgery. We measured the mean rCBV, the 5% & 10% maximum rCBV, and the variation of rCBV in the tumors. Comparisons were made between patients with and without 2-year survival using two-sample t-test or Wilcoxon rank-sum test for the continuous data, or chi-square and Fisher exact tests for categorical data. The multivariate cox-proportional hazard regression was fit to evaluate the association between rCBV and overall survival time, with adjustment for clinical factors.

Results

Patients who survived less than 2 years after diagnosis had a higher mean and maximum rCBV and a larger variation of rCBV. After adjusting for clinical factors including therapeutic measures, we found no significant association of overall survival time within 2 years with any of these rCBV values.

Conclusions

Although patients who survived less than 2 years had a higher mean and maximum rCBV and a larger variation of rCBV, rCBV itself may not be used independently for predicting 2-year survival of patients with astrocytic brain tumors.

SUBMITTER: White ML

PROVIDER: S-EPMC7787526 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Publications

Evaluating survival in subjects with astrocytic brain tumors by dynamic susceptibility-weighted perfusion MR imaging.

White Matthew L ML Zhang Yan Y Kazmi Syed A Jaffar SAJ Aizenberg Michele M Shonka Nicole N Yu Fang F Appiah Adams Kusi AK

PloS one 20210106 1

<h4>Purpose</h4>Studies have evaluated the application of perfusion MR for predicting survival in patients with astrocytic brain tumors, but few of them statistically adjust their results to reflect the impact of the variability of treatment administered in the patients. Our aim was to analyze the association between the perfusion values and overall survival time, with adjustment for various clinical factors, including initial treatments and follow-up treatments.<h4>Materials and methods</h4>Thi ...[more]

PMID: 33406116

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Project description:To investigate whether estimates of relative cerebral blood volume (rCBV) in brain tumors, obtained by using dynamic susceptibility-weighted contrast material-enhanced magnetic resonance (MR) imaging vary with choice of data acquisition and postprocessing methods.Four acquisition methods were used to collect data in 22 high-grade glioma patients, with informed written consent under HIPAA-compliant guidelines approved by the institutional review board. During bolus administration of a standard single dose of gadolinium-based contrast agent (0.1 mmol per kilogram of body weight), one of three acquisition methods was used: gradient-echo (GRE) echo-planar imaging (echo time [TE], 30 msec; flip angle, 90 degrees ; n = 10), small-flip-angle GRE echo-planar imaging (TE, 54 msec; flip angle, 35 degrees ; n = 7), or dual-echo GRE spiral-out imaging (TE, 3.3 and 30 msec; flip angle, 72 degrees ; n = 5). Next, GRE echo-planar imaging (TE, 30 msec; flip angle, 90 degrees ; n = 22) was used to collect data during administration of a second dose of contrast agent (0.2 mmol/kg). Subsequently, six methods of analysis were used to calculate rCBV. Mean rCBV values from whole tumor, tumor hot spots, and contralateral brain were normalized to mean rCBV in normal-appearing white matter.Friedman two-way analysis of variance and Kruskal-Wallis one-way analysis of variance results indicated that qualitative rCBV values were dependent on acquisition and postprocessing methods for both tumor and contralateral brain. By using the nonparametric Mann-Whitney test, a consistently positive (greater than zero) tumor-contralateral brain rCBV ratio resulted when either the preload-postprocessing correction approach or dual-echo acquisition approach (P < .008 for both methods) was used.The dependence of tumor rCBV on the choice of acquisition and postprocessing methods is caused by their varying sensitivities to T1 and T2 and/or T2* leakage effects. The preload-correction approach and dual-echo acquisition approach are the most robust choices for the evaluation of brain tumors when the possibility of contrast agent extravasation exists.

Project description:PURPOSE:To identify clinically relevant magnetic resonance imaging (MRI) features of different types of metastatic brain lesions, including standard anatomical, diffusion weighted imaging (DWI) and dynamic susceptibility contrast (DSC) perfusion MRI. METHODS:MRI imaging was retrospectively assessed on one hundred and fourteen (N = 114) brain metastases including breast (n = 27), non-small cell lung cancer (NSCLC, n = 43) and 'other' primary tumors (n = 44). Based on 114 patient's MRI scans, a total of 346 individual contrast enhancing tumors were manually segmented. In addition to tumor volume, apparent diffusion coefficients (ADC) and relative cerebral blood volume (rCBV) measurements, an independent component analysis (ICA) was performed with raw DSC data in order to assess arterio-venous components and the volume of overlap (AVOL) relative to tumor volume, as well as time to peak (TTP) of T2* signal from each component. RESULTS:Results suggests non-breast or non-NSCLC ('other') tumors had higher volume compare to breast and NSCLC patients (p = 0.0056 and p = 0.0003, respectively). No differences in median ADC or rCBV were observed across tumor types; however, breast and NSCLC tumors had a significantly higher "arterial" proportion of the tumor volume as indicated by ICA (p = 0.0062 and p = 0.0018, respectively), while a higher "venous" proportion were prominent in breast tumors compared with NSCLC (p = 0.0027) and 'other' lesions (p = 0.0011). The AVOL component was positively related to rCBV in all groups, but no correlation was found for arterial and venous components with respect to rCBV values. Median time to peak of arterial and venous components were 8.4 s and 12.6 s, respectively (p < 0.0001). No difference was found in arterial or venous TTP across groups. CONCLUSIONS:Advanced ICA-derived component analysis demonstrates perfusion differences between metastatic brain tumor types that were not observable with classical ADC and rCBV measurements. These results highlight the complex relationship between brain tumor vasculature characteristics and the site of primary tumor diagnosis.

Dataset Information

Evaluating survival in subjects with astrocytic brain tumors by dynamic susceptibility-weighted perfusion MR imaging.

Purpose

Materials and methods

Results

Conclusions

Publications

Evaluating survival in subjects with astrocytic brain tumors by dynamic susceptibility-weighted perfusion MR imaging.

Similar Datasets

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