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Advanced Hyperpolarized 13 C Metabolic Imaging Protocol for Patients with Gliomas: A Comprehensive Multimodal MRI Approach.
- Source :
-
Cancers [Cancers (Basel)] 2024 Jan 13; Vol. 16 (2). Date of Electronic Publication: 2024 Jan 13. - Publication Year :
- 2024
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Abstract
- This study aimed to implement a multimodal <superscript>1</superscript> H/HP- <superscript>13</superscript> C imaging protocol to augment the serial monitoring of patients with glioma, while simultaneously pursuing methods for improving the robustness of HP- <superscript>13</superscript> C metabolic data. A total of 100 <superscript>1</superscript> H/HP [1- <superscript>13</superscript> C]-pyruvate MR examinations (104 HP- <superscript>13</superscript> C datasets) were acquired from 42 patients according to the comprehensive multimodal glioma imaging protocol. Serial data coverage, accuracy of frequency reference, and acquisition delay were evaluated using a mixed-effects model to account for multiple exams per patient. Serial atlas-based HP- <superscript>13</superscript> C MRI demonstrated consistency in volumetric coverage measured by inter-exam dice coefficients (0.977 ± 0.008, mean ± SD; four patients/11 exams). The atlas-derived prescription provided significantly improved data quality compared to manually prescribed acquisitions ( n = 26/78; p = 0.04). The water-based method for referencing [1- <superscript>13</superscript> C]-pyruvate center frequency significantly reduced off-resonance excitation relative to the coil-embedded [ <superscript>13</superscript> C]-urea phantom (4.1 ± 3.7 Hz vs. 9.9 ± 10.7 Hz; p = 0.0007). Significantly improved capture of tracer inflow was achieved with the 2-s versus 5-s HP- <superscript>13</superscript> C MRI acquisition delay ( p = 0.007). This study demonstrated the implementation of a comprehensive multimodal <superscript>1</superscript> H/HP- <superscript>13</superscript> C MR protocol emphasizing the monitoring of steady-state/dynamic metabolism in patients with glioma.
Details
- Language :
- English
- ISSN :
- 2072-6694
- Volume :
- 16
- Issue :
- 2
- Database :
- MEDLINE
- Journal :
- Cancers
- Publication Type :
- Academic Journal
- Accession number :
- 38254844
- Full Text :
- https://doi.org/10.3390/cancers16020354