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Research ArticleBrain Tumor Imaging

“Synthetic” DSC Perfusion MRI with Adjustable Acquisition Parameters in Brain Tumors Using Dynamic Spin-and-Gradient-Echo Echoplanar Imaging

Francesco Sanvito, Jingwen Yao, Nicholas S. Cho, Catalina Raymond, Donatello Telesca, Whitney B. Pope, Richard G. Everson, Noriko Salamon, Jerrold L. Boxerman, Timothy F. Cloughesy and Benjamin M. Ellingson
American Journal of Neuroradiology February 2025, 46 (2) 311-320; DOI: https://doi.org/10.3174/ajnr.A8475
Francesco Sanvito
aFrom the UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers (F.S., J.Y., N.S.C., C.R., B.M.E.), University of California Los Angeles, Los Angeles, California
bDepartment of Radiological Sciences (F.S., J.Y., N.S.C., C.R., W.B.P., N.S., B.M.E.), David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
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Jingwen Yao
aFrom the UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers (F.S., J.Y., N.S.C., C.R., B.M.E.), University of California Los Angeles, Los Angeles, California
bDepartment of Radiological Sciences (F.S., J.Y., N.S.C., C.R., W.B.P., N.S., B.M.E.), David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
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Nicholas S. Cho
aFrom the UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers (F.S., J.Y., N.S.C., C.R., B.M.E.), University of California Los Angeles, Los Angeles, California
bDepartment of Radiological Sciences (F.S., J.Y., N.S.C., C.R., W.B.P., N.S., B.M.E.), David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
cMedical Scientist Training Program (N.S.C.), David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
dDepartment of Bioengineering (N.S.C., B.M.E.), Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, California
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Catalina Raymond
aFrom the UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers (F.S., J.Y., N.S.C., C.R., B.M.E.), University of California Los Angeles, Los Angeles, California
bDepartment of Radiological Sciences (F.S., J.Y., N.S.C., C.R., W.B.P., N.S., B.M.E.), David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
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Donatello Telesca
eDepartment of Biostatistics (D.T.), University of California, Los Angeles, Los Angeles, California
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Whitney B. Pope
bDepartment of Radiological Sciences (F.S., J.Y., N.S.C., C.R., W.B.P., N.S., B.M.E.), David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
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Richard G. Everson
fDepartment of Neurosurgery (R.G.E., B.M.E.), David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
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Noriko Salamon
bDepartment of Radiological Sciences (F.S., J.Y., N.S.C., C.R., W.B.P., N.S., B.M.E.), David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
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Jerrold L. Boxerman
gDepartment of Diagnostic Imaging (J.L.B.), Warren Alpert Medical School, Brown University, Providence, Rhode Island
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Timothy F. Cloughesy
hDepartment of Neurology (T.F.C.), David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
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Benjamin M. Ellingson
aFrom the UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers (F.S., J.Y., N.S.C., C.R., B.M.E.), University of California Los Angeles, Los Angeles, California
bDepartment of Radiological Sciences (F.S., J.Y., N.S.C., C.R., W.B.P., N.S., B.M.E.), David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
dDepartment of Bioengineering (N.S.C., B.M.E.), Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, California
fDepartment of Neurosurgery (R.G.E., B.M.E.), David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
iDepartment of Psychiatry and Biobehavioral Sciences (B.M.E.), David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
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Abstract

BACKGROUND AND PURPOSE: Normalized relative cerebral blood volume (nrCBV) and percentage of signal recovery (PSR) computed from dynamic susceptibility contrast (DSC) perfusion imaging are useful biomarkers for differential diagnosis and treatment response assessment in brain tumors. However, their measurements are dependent on DSC acquisition factors, and CBV-optimized protocols technically differ from PSR-optimized protocols. This study aimed to generate “synthetic” DSC data with adjustable synthetic acquisition parameters using dual-echo gradient-echo (GE) DSC datasets extracted from dynamic spin-and-gradient-echo echoplanar imaging (dynamic SAGE-EPI). Synthetic DSC was aimed at: 1) simultaneously create nrCBV and PSR maps using optimal sequence parameters, 2) compare DSC datasets with heterogeneous external cohorts, and 3) assess the impact of acquisition factors on DSC metrics.

MATERIALS AND METHODS: Thirty-eight patients with contrast-enhancing brain tumors were prospectively imaged with dynamic SAGE-EPI during a non-preloaded single-dose contrast injection and included in this cross-sectional study. Multiple synthetic DSC curves with desired pulse sequence parameters were generated using the Bloch equations applied to the dual-echo GE data extracted from dynamic SAGE-EPI datasets, with or without optional preload simulation.

RESULTS: Dynamic SAGE-EPI allowed for simultaneous generation of CBV-optimized and PSR-optimized DSC datasets with a single contrast injection, while PSR computation from guideline-compliant CBV-optimized protocols resulted in rank variations within the cohort (Spearman’s ρ = 0.83-0.89, i.e. 31%-21% rank variation). Treatment-naïve glioblastoma exhibited lower parameter-matched PSR compared to the external cohorts of treatment-naïve primary CNS lymphomas (PCNSL) (p<0.0001), supporting a role of synthetic DSC for multicenter comparisons. Acquisition factors highly impacted PSR, and nrCBV without leakage correction also showed parameter-dependence, although less pronounced. However, this dependence was remarkably mitigated by post-hoc leakage correction.

CONCLUSIONS: Dynamic SAGE-EPI allows for simultaneous generation of CBV-optimized and PSR-optimized DSC data with one acquisition and a single contrast injection, facilitating the use of a single perfusion protocol for all DSC applications. This approach may also be useful for comparisons of perfusion metrics across heterogeneous multicenter datasets, as it facilitates post-hoc harmonization.

ABBREVIATIONS:

CBV
cerebral blood volume
DSC
dynamic susceptibility contrast
FA
flip angle
GBCA
gadolinium-based contrast agent
GBM
glioblastoma
GE
gradient echo
IDH
isocitrate dehydrogenase
IDHm
IDH-mutant
IDHwt
IDH-wild-type
1p19qcod
1p19q codeleted
1p19qint
1p19q intact
MRI
magnetic resonance imaging
nrCBV
normalized relative CBV
PCNSL
primary CNS lymphoma
PSR
percentage of signal recovery
Rec
recurrent
ROI
region of interest
SAGE-EPI
spin-and-gradient-echo echoplanar imaging
TE
echo time
TN
treatment-naïve
TR
repetition time
  • © 2025 by American Journal of Neuroradiology
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American Journal of Neuroradiology: 46 (2)
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Cite this article
Francesco Sanvito, Jingwen Yao, Nicholas S. Cho, Catalina Raymond, Donatello Telesca, Whitney B. Pope, Richard G. Everson, Noriko Salamon, Jerrold L. Boxerman, Timothy F. Cloughesy, Benjamin M. Ellingson
“Synthetic” DSC Perfusion MRI with Adjustable Acquisition Parameters in Brain Tumors Using Dynamic Spin-and-Gradient-Echo Echoplanar Imaging
American Journal of Neuroradiology Feb 2025, 46 (2) 311-320; DOI: 10.3174/ajnr.A8475

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Synthetic DSC MRI for Brain Tumors: New Insights
Francesco Sanvito, Jingwen Yao, Nicholas S. Cho, Catalina Raymond, Donatello Telesca, Whitney B. Pope, Richard G. Everson, Noriko Salamon, Jerrold L. Boxerman, Timothy F. Cloughesy, Benjamin M. Ellingson
American Journal of Neuroradiology Feb 2025, 46 (2) 311-320; DOI: 10.3174/ajnr.A8475
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  • Normalization of the percentage of signal recovery derived from dynamic susceptibility contrast perfusion MRI in brain tumors
    Francesco Sanvito, Jingwen Yao, Nicholas S. Cho, Donatello Telesca, Noriko Salamon, Timothy F. Cloughesy, Benjamin M. Ellingson
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