CEST MR fingerprinting (CEST-MRF) for brain tumor quantification using EPI readout and deep learning reconstruction Journal Article
| Authors: | Cohen, O.; Yu, V. Y.; Tringale, K. R.; Young, R. J.; Perlman, O.; Farrar, C. T.; Otazo, R. |
| Article Title: | CEST MR fingerprinting (CEST-MRF) for brain tumor quantification using EPI readout and deep learning reconstruction |
| Abstract: | Purpose: To develop a clinical CEST MR fingerprinting (CEST-MRF) method for brain tumor quantification using EPI acquisition and deep learning reconstruction. Methods: A CEST-MRF pulse sequence originally designed for animal imaging was modified to conform to hardware limits on clinical scanners while keeping scan time under 2 min. Quantitative MRF reconstruction was performed using a deep reconstruction network (DRONE) to yield the water relaxation and chemical exchange parameters. The feasibility of the six parameter DRONE reconstruction was tested in simulations using a digital brain phantom. A healthy subject was scanned with the CEST-MRF sequence, conventional MRF and CEST sequences for comparison. Reproducibility was assessed via test–retest experiments and the concordance correlation coefficient calculated for white matter and gray matter. The clinical utility of CEST-MRF was demonstrated on four patients with brain metastases in comparison to standard clinical imaging sequences. Tumors were segmented into edema, solid core, and necrotic core regions and the CEST-MRF values compared to the contra-lateral side. Results: DRONE reconstruction of the digital phantom yielded a normalized RMS error of ≤7% for all parameters. The CEST-MRF parameters were in good agreement with those from conventional MRF and CEST sequences and previous studies. The mean concordance correlation coefficient for all six parameters was 0.98 ± 0.01 in white matter and 0.98 ± 0.02 in gray matter. The CEST-MRF values in nearly all tumor regions were significantly different (P = 0.05) from each other and the contra-lateral side. Conclusion: Combination of EPI readout and deep learning reconstruction enabled fast, accurate and reproducible CEST-MRF in brain tumors. © 2022 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine. |
| Keywords: | adult; clinical article; controlled study; aged; middle aged; cancer patient; neuroimaging; nuclear magnetic resonance imaging; brain tumor; brain neoplasms; magnetic resonance imaging; reproducibility; reproducibility of results; animal; animals; ph; diagnostic imaging; feasibility study; correlation coefficient; brain; medical imaging; tumors; brain metastasis; magnetic resonance; test retest reliability; phantoms, imaging; image processing, computer-assisted; image processing; brain necrosis; white matter; image reconstruction; brain edema; magnetism; phantoms; echo planar imaging; gray matter; procedures; chemical exchange; imaging phantom; human; male; female; article; exchange rates; deep learning; chemical exchange rate; chemical exchange saturation transfer (cest); magnetic resonance fingerprinting (mrf); magnetorheological fluids; chemical exchange saturation transfer; drone; drones; structural frames; brain tumor quantifications; deep reconstruction network; magnetic resonance fingerprinting; reconstruction networks |
| Journal Title: | Magnetic Resonance in Medicine |
| Volume: | 89 |
| Issue: | 1 |
| ISSN: | 0740-3194 |
| Publisher: | John Wiley & Sons |
| Date Published: | 2023-01-01 |
| Start Page: | 233 |
| End Page: | 249 |
| Language: | English |
| DOI: | 10.1002/mrm.29448 |
| PUBMED: | 36128888 |
| PROVIDER: | scopus |
| PMCID: | PMC9617776 |
| DOI/URL: | |
| Notes: | Article -- The NIH/NCI Cancer Center Support Grant P30 CA008748 is acknowledged in PubMed and in the PDF -- Corresponding author is MSK author Ouri Cohen -- Source: Scopus |
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