Applying chemical shift images (in-phase/opposed phased) for differentiating low-grade from high-grade glioma and comparison with magnetic resonance spectroscopy.
{"title":"Applying chemical shift images (in-phase/opposed phased) for differentiating low-grade from high-grade glioma and comparison with magnetic resonance spectroscopy.","authors":"Bita Abbasi, Afshar Ghamari Khameneh, Hadi Zareh Soltaniye, Gisoo Darban Hosseini Amirkhiz, Ehsan Karimi, Reza Akhavan","doi":"10.1007/s00117-024-01339-4","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Grading gliomas is essential for treatment decisions and patient prognosis. In this study we evaluated the in-phase and out-of-phase sequences for distinguishing high-grade (HGG) from low-grade glioma (LGG) and the correlation with magnetic resonance spectroscopy (MRS) results.</p><p><strong>Methods: </strong>This observational study comprised patients with brain tumors referred to our center for brain MRS. The gold standard for diagnosis was based on the World Health Organization (WHO) glioma classification. A standard tumor protocol was accomplished using a 1.5‑T MRS scanner. Before contrast medium administration, extra in- and out-phase sequences were acquired. Three 20-30-mm<sup>2</sup> oval regions of interest (ROIs) were placed in the solid component and the signal loss ratio (SLR) was calculated with the following formula: SLR <sub>tumor</sub> = (SI <sub>In phase</sub> - SI <sub>Opposed phase</sub>) / SI <sub>In phase</sub> Correlations and comparisons between groups were made using the Pearson, chi-square and, independent samples t tests. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic performance. Statistical significance was set at p < 0.05.</p><p><strong>Results: </strong>In total, 20 patients were included in the LGG and 13 were included in the HGG group. The mean SLR in the HGG and LGG groups was 3.66 ± 2.12 and 1.63 ± 1.86, respectively (p = 0.01). There was a statistically significant correlation between lipid lactate (0.48, p = 0.004) and free lipid (0.44, p = 0.009) concentrations on MRS with SLR.</p><p><strong>Conclusions: </strong>The SLR is a simple, rapid, and noninvasive marker for differentiating between LGG and HGG. There is a significant correlation with both the concentration and presence of free lipid and lipid-lactate peaks in MRS.</p>","PeriodicalId":74635,"journal":{"name":"Radiologie (Heidelberg, Germany)","volume":" ","pages":"116-122"},"PeriodicalIF":0.0000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Radiologie (Heidelberg, Germany)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s00117-024-01339-4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/7/8 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Grading gliomas is essential for treatment decisions and patient prognosis. In this study we evaluated the in-phase and out-of-phase sequences for distinguishing high-grade (HGG) from low-grade glioma (LGG) and the correlation with magnetic resonance spectroscopy (MRS) results.
Methods: This observational study comprised patients with brain tumors referred to our center for brain MRS. The gold standard for diagnosis was based on the World Health Organization (WHO) glioma classification. A standard tumor protocol was accomplished using a 1.5‑T MRS scanner. Before contrast medium administration, extra in- and out-phase sequences were acquired. Three 20-30-mm2 oval regions of interest (ROIs) were placed in the solid component and the signal loss ratio (SLR) was calculated with the following formula: SLR tumor = (SI In phase - SI Opposed phase) / SI In phase Correlations and comparisons between groups were made using the Pearson, chi-square and, independent samples t tests. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic performance. Statistical significance was set at p < 0.05.
Results: In total, 20 patients were included in the LGG and 13 were included in the HGG group. The mean SLR in the HGG and LGG groups was 3.66 ± 2.12 and 1.63 ± 1.86, respectively (p = 0.01). There was a statistically significant correlation between lipid lactate (0.48, p = 0.004) and free lipid (0.44, p = 0.009) concentrations on MRS with SLR.
Conclusions: The SLR is a simple, rapid, and noninvasive marker for differentiating between LGG and HGG. There is a significant correlation with both the concentration and presence of free lipid and lipid-lactate peaks in MRS.