Cerebral Ultrasound Perfusion Imaging

Cerebral Ultrasound Perfusion Imaging

Ultrasound Perfusion Imaging is feasible to enable detection of cerebral hypoperfusion after aneurysmal subarachnoid hemorrhage, and the left-right difference of time to peak (TTP) values is the most indicative result of this finding 1).


Over the past 20 years, ultrasonic cerebral perfusion imaging (UPI) has been introduced and validated by applying different data acquisition and processing approaches. Clinical data were collected mainly in acute stroke patients. Some efforts were undertaken in order to compare different technical settings and validate results to gold standard perfusion imaging. A review illustrates the evolution of the method, explicating different technical aspects and milestones achieved over time. Up to date, advancements of ultrasound technology, as well as data processing approaches, enable semi-quantitative, gold standard proven identification of critically hypo-perfused tissue in acute stroke patients. The rapid distribution of CT perfusion over the past 10 years has limited the clinical need for UPI. However, the unexcelled advantage of mobile applications raises reasonable expectations for future applications. Since the identification of intracerebral hematoma and large vessel occlusion can also be revealed by ultrasound exams, UPI is a supplementary multi-modal imaging technique with the potential of the pre-hospital application. Some further applications are outlined to highlight the future potential of this underrated bedside method of microcirculatory perfusion assessment 2).


Ultrasound perfusion imaging provides a simple and non-invasive way to detect the VN time window, which increases the feasibility of vascular normalization (VN) in clinical cancer applications 3).


Reitmeir et al. compared contrast-enhanced ultrasound perfusion imaging with magnetic resonance perfusion-weighted imaging or perfusion computed tomography for detecting normo-, hypo-, and nonperfused brain areas in acute middle cerebral artery stroke. We performed high mechanical index contrast-enhanced ultrasound perfusion imaging in 30 patients. The time-to-peak intensity of 10 ischemic regions of interest was compared to four standardized nonischemic regions of interests of the same patient. A time-to-peak >3 s (ultrasound perfusion imaging) or >4 s (perfusion computed tomography and magnetic resonance perfusion) defined hypoperfusion. In 16 patients, 98 of 160 ultrasound perfusion imaging regions of interest of the ischemic hemisphere were classified as normal, and 52 as hypoperfused or nonperfused. Ten regions of interest were excluded due to artifacts. There was a significant correlation between the ultrasound perfusion imaging and magnetic resonance perfusion or perfusion computed tomography (Pearson’s chi-squared test 79.119, p < 0.001) (OR 0.1065, 95% CI 0.06-0.18). No perfusion in ultrasound perfusion imaging (18 regions of interest) correlated highly with diffusion restriction on magnetic resonance imaging (Pearson’s chi-squared test 42.307, p < 0.001). Analysis of receiver operating characteristics proved a high sensitivity of ultrasound perfusion imaging in the diagnosis of the hypoperfused area under the curve, (AUC = 0.917; p < 0.001) and nonperfused (AUC = 0.830; p < 0.001) tissue in comparison with perfusion computed tomography and magnetic resonance perfusion. They presented a proof of concept in determining normo-, hypo-, and nonperfused tissue in acute stroke by advanced contrast-enhanced ultrasound perfusion imaging 4).


A review detail the methodology of ultrasound perfusion imaging, discuss aspects of its safety and present the clinical applications of brain perfusion assessment with ultrasound in acute stroke patients 5).


1)

Fung C, Heiland DH, Reitmeir R, Niesen WD, Raabe A, Eyding J, Schnell O, Rölz R, Z Graggen WJ, Beck J. Ultrasound Perfusion Imaging for the Detection of Cerebral Hypoperfusion After Aneurysmal Subarachnoid Hemorrhage. Neurocrit Care. 2022 Feb 24. doi: 10.1007/s12028-022-01460-z. Epub ahead of print. PMID: 35211837.
2)

Eyding J, Fung C, Niesen WD, Krogias C. Twenty Years of Cerebral Ultrasound Perfusion Imaging-Is the Best yet to Come? J Clin Med. 2020 Mar 17;9(3):816. doi: 10.3390/jcm9030816. PMID: 32192077; PMCID: PMC7141340.
3)

Ho YJ, Chu SW, Liao EC, Fan CH, Chan HL, Wei KC, Yeh CK. Normalization of Tumor Vasculature by Oxygen Microbubbles with Ultrasound. Theranostics. 2019 Sep 25;9(24):7370-7383. doi: 10.7150/thno.37750. PMID: 31695774; PMCID: PMC6831304.
4)

Reitmeir R, Eyding J, Oertel MF, Wiest R, Gralla J, Fischer U, Giquel PY, Weber S, Raabe A, Mattle HP, Z’Graggen WJ, Beck J. Is ultrasound perfusion imaging capable of detecting mismatch? A proof-of-concept study in acute stroke patients. J Cereb Blood Flow Metab. 2017 Apr;37(4):1517-1526. doi: 10.1177/0271678×16657574. Epub 2016 Jan 1. PMID: 27389180; PMCID: PMC5453469.
5)

Meairs S, Kern R. Intracranial perfusion imaging with ultrasound. Front Neurol Neurosci. 2015;36:57-70. doi: 10.1159/000366237. Epub 2014 Dec 22. PMID: 25531663.

Magnetic resonance perfusion imaging in glioblastoma

Indications

Magnetic resonance perfusion imaging, may:

Provide a noninvasive diagnostic tool for properly grading lesions.

Identifying the most malignant region of a tumor for guiding biopsy

Monitoring response to therapy that may precede conventionally assessed changes in tumor morphology and enhancement characteristics.

May help quantitatively predict recurrent glioblastoma/progression for glioblastomas. The active tumor histological fraction correlated with quantitative radiologic measurements including rCBV and rCBF.

The dominant predictors of OS are normalized perfusion parameters Normalized Relative Tumor Blood Volume (n_rTBV) and Normalized Relative Tumor Blood Flow (n_rTBF). Pre-operative perfusion imaging may be used as a surrogate to predict glioblastoma aggressiveness and survival independent of treatment 1).


For metastases, Perfusion MRI may not be as useful in predicting mean active tumor fraction (AT). Clinicians must be judicious with their use of MRP in predicting tumor recurrence and radiation necrosis 2).

While perfusion MRI is not the ideal diagnostic method for differentiating glioma recurrence from pseudoprogression, it could improve diagnostic accuracy. Therefore, further research on combining perfusion MRI with other imaging modalities is warranted 3).

Perfusion-weighted magnetic resonance imaging (PW-MRI) techniques, such as dynamic contrast-enhanced MRI (DCE-MRI) and dynamic susceptibility contrast-MRI (DSC-MRI), have demonstrated much potential as powerful imaging biomarkers for glioma management as they can provide information of vascular hemodynamics 4) 5) 6).

PW-MRI is now rapidly expanding its application spectrum by noninvasively exploring the relationship between imaging parameters and the molecular characteristics of gliomas 7).


Dynamic contrast enhanced magnetic resonance imaging and Dynamic susceptibility weighted contrast enhanced perfusion imaging represent a widely accepted method to assess glioblastoma (GBM) microvasculature.

The aim of Navone et al. from the Laboratory of Experimental Neurosurgery and Cell Therapy, Neurosurgery Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Postgraduate School in Radiodiagnostics Department of Neuroradiology, Milan, was to investigate the correlation between plasma von Willebrand Factor (VWF):Ag, permeability and perfusion MRI parameters, and examine their potential in predicting GBM patient prognosis.

They retrospectively analysed pre-operative DCE-, DSC-MRI, and VWF:Ag level of 26 GBM patients. They assessed the maximum values of relative cerebral blood flow (rCBF) and volume (rCBV), volume transfer constant Ktrans, plasma volume (Vp) and reflux rate constant between fractional volume of the extravascular space and blood plasma (Kep). Non-parametric Mann-Withney test and Kaplan-Meier survival analyses were conducted and a p-value<0.05 was considered statistically significant.

The median VWF:Ag value was 248 IU/dL and the median follow-up duration was about 13 months. They divided patients according to low- and high-VWF:Ag and found significant differences in the median follow-up duration (19 months vs 10 months, p=0.04) and in Ktrans (0.31 min-1 vs 0.53 min-1, p=0.02), and Kep (1.79 min-1 vs 3.89 min-1, p=0.005) values. The cumulative 1-year survival was significantly shorter in patients with high-VWF:Ag and high-Kep compared to patients with low-VWF:Ag and low-Kep (37.5% vs. 68%, p = 0.05).

These findings, in a small group of patients, suggest a role for VWF:Ag, similar to Ktrans, and Kep as a prognostic indicator of postoperative GBM patient survival 8).

References

1)

Hou BL, Wen S, Katsevman GA, Liu H, Urhie O, Turner RC, Carpenter J, Bhatia S. MRI Parameters and Their Impact on the Survival of Patients with Glioblastoma: Tumor Perfusion Predicts Survival. World Neurosurg. 2018 Dec 26. pii: S1878-8750(18)32908-5. doi: 10.1016/j.wneu.2018.12.085. [Epub ahead of print] PubMed PMID: 30593971.
2)

Shah AH, Kuchakulla M, Ibrahim GM, Dadheech E, Komotar RJ, Gultekin SH, Ivan ME. The utility of Magnetic Resonance Perfusion imaging in quantifying active tumor fraction and radiation necrosis in recurrent intracranial tumors. World Neurosurg. 2018 Oct 9. pii: S1878-8750(18)32288-5. doi: 10.1016/j.wneu.2018.09.233. [Epub ahead of print] PubMed PMID: 30312826.
3)

Wan B, Wang S, Tu M, Wu B, Han P, Xu H. The diagnostic performance of perfusion MRI for differentiating glioma recurrence from pseudoprogression: A meta-analysis. Medicine (Baltimore). 2017 Mar;96(11):e6333. doi: 10.1097/MD.0000000000006333. PubMed PMID: 28296759; PubMed Central PMCID: PMC5369914.
4)

Jain R. Measurements of tumor vascular leakiness using DCE in brain tumors: clinical applications. NMR in Biomedicine. 2013;26(8):1042–1049. doi: 10.1002/nbm.2994.
5)

O’Connor J. P. B., Jackson A., Parker G. J. M., Roberts C., Jayson G. C. Dynamic contrast-enhanced MRI in clinical trials of antivascular therapies. Nature Reviews Clinical Oncology. 2012;9(3):167–177. doi: 10.1038/nrclinonc.2012.2.
6)

Barajas R. F. R., Cha S. Benefits of dynamic susceptibility-weighted contrast-enhanced perfusion MRI for glioma diagnosis and therapy. CNS oncology. 2014;3(6):407–419. doi: 10.2217/cns.14.44.
7)

Chung C., Metser U., Ménard C. Advances in magnetic resonance imaging and positron emission tomography imaging for grading and molecular characterization of glioma. Seminars in Radiation Oncology. 2015;25(3):164–171. doi: 10.1016/j.semradonc.2015.02.002.
8)

Navone SE, Doniselli FM, Summers P, Guarnaccia L, Rampini P, Locatelli M, Campanella R, Marfia G, Costa A. Correlation of preoperative Von Willebrand Factor with MRI perfusion and permeability parameters as predictors of prognosis in glioblastoma. World Neurosurg. 2018 Oct 9. pii: S1878-8750(18)32271-X. doi: 10.1016/j.wneu.2018.09.216. [Epub ahead of print] PubMed PMID: 30312827.
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