Methods for molecular imaging of brain tumours in a hybrid MR-PET context: Water content, T2∗, diffusion indices and FET-PET

Oros-Peusquens, Ana-Maria; Loução, Ricardo; Zimmermann, Markus; Langen, Karl‐Josef; Shah, N. Jon

doi:10.1016/j.ymeth.2017.07.025

Cited by 11 publications

(12 citation statements)

References 80 publications

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“…For the tumor patient, an active tumor volume of 16.65 mL was defined based on PET information as described in Oros-Peusquens et al (78), and an additional volume of 18.80 mL affected by oedema was identified based on FLAIR.…”

Section: In Vivo Results: Measurements On Patientsmentioning

confidence: 99%

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A Single-Scan, Rapid Whole-Brain Protocol for Quantitative Water Content Mapping With Neurobiological Implications

Loução

Abbas

et al. 2019

Front. Neurol.

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Water concentration is tightly regulated in the healthy human brain and changes only slightly with age and gender in healthy subjects. Consequently, changes in water content are important for the characterization of disease. MRI can be used to measure changes in brain water content, but as these changes are usually in the low percentage range, highly accurate and precise methods are required for detection. The method proposed here is based on a long-TR (10 s) multiple-echo gradient-echo measurement with an acquisition time of 7:21 min. Using such a long TR ensures that there is no T 1 weighting, meaning that the image intensity at zero echo time is only proportional to the water content, the transmit field, and to the receive field. The receive and transmit corrections, which are increasingly large at higher field strengths and for highly segmented coil arrays, are multiplicative and can be approached heuristically using a bias field correction. The method was tested on 21 healthy volunteers at 3T field strength. Calibration using cerebral-spinal fluid values (∼100% water content) resulted in mean values and standard deviations of the water content distribution in white matter and gray matter of 69.1% (1.7%) and 83.7% (1.2%), respectively. Measured distributions were coil-independent, as seen by using either a 12-channel receiver coil or a 32-channel receiver coil. In a test-retest investigation using 12 scans on one volunteer, the variation in the mean value of water content for different tissue types was ∼0.3% and the mean voxel variability was ∼1%. Robustness against reduced SNR was assessed by comparing results for 5 additional volunteers at 1.5T and 3T. Furthermore, water content distribution in gray matter is investigated and regional contrast reported for the first time. Clinical applicability is illustrated with data from one stroke patient and one brain tumor patient. It is anticipated that this fast, stable, easyto-use, high-quality mapping method will facilitate routine quantitative MR imaging of water content.

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Section: In Vivo Results: Measurements On Patientsmentioning

confidence: 99%

“…This would approximately preserve the total measurement time, whereas the measurement time per scan would be halved. Alternatively, shorter TR values in conjunction with lower flip angles could be used (78). The acquisition time for a single scan, in this case, drops to around 4 min, reducing the likelihood of head movement.…”

Section: Measurement Time Reductionmentioning

confidence: 99%

A Single-Scan, Rapid Whole-Brain Protocol for Quantitative Water Content Mapping With Neurobiological Implications

Loução

Abbas

et al. 2019

Front. Neurol.

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“…Other relevant parameters were the following: TE1, 3.34 ms; deltaTE, 2.85 ms; 12 echoes; resolution, 1 ϫ 1 ϫ 1.5 mm (50% slice gap); bandwidth, 510 Hz/px; partial Fourier factor, 6/8; number of slices, 84. 3…”

Section: Methodsmentioning

confidence: 99%

“…Quantitative MR imaging allows the quantification of water content of brain lesions within a clinically acceptable acquisition time of a few minutes. 3,4 For instance, it has been shown that quantitative water mapping allows one to detect an increase in cerebral water content in hepatic encephalopathy and to evaluate the surrounding edema in brain tumors. 5,6 We hypothesized that quantitative MR imaging allows differentiation between PVCs and microvascular white matter lesions (WML).…”

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confidence: 99%

Increased Water Content in Periventricular Caps in Patients without Acute Hydrocephalus

Sichtermann

Furtmann

Dekeyzer³

et al. 2019

AJNR Am J Neuroradiol

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BACKGROUND AND PURPOSE: Periventricular caps are a common finding on MR imaging and are believed to reflect focally increased interstitial water content due to dysfunctional transependymal transportation rather than ischemic-gliotic changes. We compared the quantitative water content of periventricular caps and microvascular white matter lesions, hypothesizing that periventricular caps associated with increased interstitial fluid content display higher water content than white matter lesions and are therefore differentiable from microvascular white matter lesions by measurement of the water content. MATERIALS AND METHODS:In a prospective study, we compared the water content of periventricular caps and white matter lesions in 50 patients using a quantitative multiple-echo, gradient-echo MR imaging water-mapping sequence. RESULTS:The water content of periventricular caps was significantly higher than that of white matter lesions (P ϭ .002). Compared with normal white matter, the mean water content of periventricular caps was 17% Ϯ 5% higher and the mean water content of white matter lesions was 11% Ϯ 4% higher. Receiver operating characteristic analysis revealed that areas in which water content was 15% higher compared with normal white matter correspond to periventricular caps rather than white matter lesions, with a specificity of 93% and a sensitivity of 60% (P Ͻ .001). There was no significant correlation between the water content of periventricular caps and whole-brain volume (P ϭ .275), white matter volume (P ϭ .243), gray matter volume (P ϭ .548), lateral ventricle volume (P ϭ .800), white matter lesion volume (P ϭ .081), periventricular cap volume (P ϭ .081), and age (P ϭ .224). CONCLUSIONS:Quantitative MR imaging allows differentiation between periventricular caps and white matter lesions. Water content quantification of T2-hyperintense lesions may be a useful additional tool for the characterization and differentiation of T2-hyperintense diseases.ABBREVIATIONS: iNPH ϭ idiopathic normal pressure hydrocephalus; PVC ϭ periventricular cap; WML ϭ white matter lesions

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“…It means the water content among various tissues is “scaled” to EPs in a non‐uniform manner, which cause a different contrast information between water content and EPs. For example, in glioma and white matter tissue, the water content is 84% and 69%, while the conductivity is 0.68 S/m and 0.342 S/m. 3 22% difference in water content leads to ~2‐fold conductivity contrast change.…”

Section: Discussionmentioning

confidence: 99%

Statistical analysis of the accuracy of water content‐based electrical properties tomography

et al. 2020

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Water content-based electrical properties tomography (wEPT) can retrieve electrical properties (EPs) from water content maps, thereby eliminating the need for B 1 field measurement in the traditional magnetic resonance electrical properties tomography method. The wEPT is performed by conventional MR scanning, such as T 1 -weighted spin-echo imaging, and thus can be directly applied to clinical settings. However, the random noise propagation involved in wEPT causes inaccuracy in EP mapping. To guarantee the EP estimates desired for clinical practice, this study statically investigates the noise-specific uncertainty of wEPT through probability density function models. We calculated the probability distribution of EP maps with different noise levels and examined the effects of scan parameters on reconstruction accuracy with various flip angles (FAs) and repetition time (TR) settings. The theoretical derivation was validated by Monte Carlo simulations and human imaging experiment at 3 T.Results showed that a serious deviation could occur in tissues with large conductivity value at a low signal-to-noise ratio and quantitatively demonstrate that such deviation could be mitigated by increased FAs or TRs. This study provided useful information for the setup of scan parameters, evaluation of accuracy of the wEPT under specific SNR levels, and promote its clinical applications. K E Y W O R D Selectrical conductivity, electrical properties tomography, magnetic resonance imaging, probability density function, relative permittivity, water content

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Methods for molecular imaging of brain tumours in a hybrid MR-PET context: Water content, T2∗, diffusion indices and FET-PET

Cited by 11 publications

References 80 publications

A Single-Scan, Rapid Whole-Brain Protocol for Quantitative Water Content Mapping With Neurobiological Implications

A Single-Scan, Rapid Whole-Brain Protocol for Quantitative Water Content Mapping With Neurobiological Implications

Increased Water Content in Periventricular Caps in Patients without Acute Hydrocephalus

Statistical analysis of the accuracy of water content‐based electrical properties tomography

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