Parallel MR imaging Deshmane, Anagha; Gulani, Vikas; Griswold, Mark A. ...
Journal of magnetic resonance imaging,
July 2012, Volume:
36, Issue:
1
Journal Article
Magnetic resonance (MR) fingerprinting is a technique for acquiring and processing MR data that simultaneously provides quantitative maps of different tissue parameters through a pattern recognition ...algorithm. A predefined dictionary models the possible signal evolutions simulated using the Bloch equations with different combinations of various MR parameters and pattern recognition is completed by computing the inner product between the observed signal and each of the predicted signals within the dictionary. Though this matching algorithm has been shown to accurately predict the MR parameters of interest, one desires a more efficient method to obtain the quantitative images. We propose to compress the dictionary using the singular value decomposition, which will provide a low-rank approximation. By compressing the size of the dictionary in the time domain, we are able to speed up the pattern recognition algorithm, by a factor of between 3.4-4.8, without sacrificing the high signal-to-noise ratio of the original scheme presented previously.
To develop a magnetic resonance (MR) "fingerprinting" technique for quantitative abdominal imaging.
This HIPAA-compliant study had institutional review board approval, and informed consent was ...obtained from all subjects. To achieve accurate quantification in the presence of marked B0 and B1 field inhomogeneities, the MR fingerprinting framework was extended by using a two-dimensional fast imaging with steady-state free precession, or FISP, acquisition and a Bloch-Siegert B1 mapping method. The accuracy of the proposed technique was validated by using agarose phantoms. Quantitative measurements were performed in eight asymptomatic subjects and in six patients with 20 focal liver lesions. A two-tailed Student t test was used to compare the T1 and T2 results in metastatic adenocarcinoma with those in surrounding liver parenchyma and healthy subjects.
Phantom experiments showed good agreement with standard methods in T1 and T2 after B1 correction. In vivo studies demonstrated that quantitative T1, T2, and B1 maps can be acquired within a breath hold of approximately 19 seconds. T1 and T2 measurements were compatible with those in the literature. Representative values included the following: liver, 745 msec ± 65 (standard deviation) and 31 msec ± 6; renal medulla, 1702 msec ± 205 and 60 msec ± 21; renal cortex, 1314 msec ± 77 and 47 msec ± 10; spleen, 1232 msec ± 92 and 60 msec ± 19; skeletal muscle, 1100 msec ± 59 and 44 msec ± 9; and fat, 253 msec ± 42 and 77 msec ± 16, respectively. T1 and T2 in metastatic adenocarcinoma were 1673 msec ± 331 and 43 msec ± 13, respectively, significantly different from surrounding liver parenchyma relaxation times of 840 msec ± 113 and 28 msec ± 3 (P < .0001 and P < .01) and those in hepatic parenchyma in healthy volunteers (745 msec ± 65 and 31 msec ± 6, P < .0001 and P = .021, respectively).
A rapid technique for quantitative abdominal imaging was developed that allows simultaneous quantification of multiple tissue properties within one 19-second breath hold, with measurements comparable to those in published literature.
Purpose To develop and evaluate an examination consisting of magnetic resonance (MR) fingerprinting-based T1, T2, and standard apparent diffusion coefficient (ADC) mapping for multiparametric ...characterization of prostate disease. Materials and Methods This institutional review board-approved, HIPAA-compliant retrospective study of prospectively collected data included 140 patients suspected of having prostate cancer. T1 and T2 mapping was performed with fast imaging with steady-state precession-based MR fingerprinting with ADC mapping. Regions of interest were drawn by two independent readers in peripheral zone lesions and normal-appearing peripheral zone (NPZ) tissue identified on clinical images. T1, T2, and ADC were recorded for each region. Histopathologic correlation was based on systematic transrectal biopsy or cognitively targeted biopsy results, if available. Generalized estimating equations logistic regression was used to assess T1, T2, and ADC in the differentiation of (a) cancer versus NPZ, (b) cancer versus prostatitis, (c) prostatitis versus NPZ, and (d) high- or intermediate-grade tumors versus low-grade tumors. Analysis was performed for all lesions and repeated in a targeted biopsy subset. Discriminating ability was evaluated by using the area under the receiver operating characteristic curve (AUC). Results In this study, 109 lesions were analyzed, including 39 with cognitively targeted sampling. T1, T2, and ADC from cancer (mean, 1628 msec ± 344, 73 msec ± 27, and 0.773 × 10
mm
/sec ± 0.331, respectively) were significantly lower than those from NPZ (mean, 2247 msec ± 450, 169 msec ± 61, and 1.711 × 10
mm
/sec ± 0.269) (P < .0001 for each) and together produced the best separation between these groups (AUC = 0.99). ADC and T2 together produced the highest AUC of 0.83 for separating high- or intermediate-grade tumors from low-grade cancers. T1, T2, and ADC in prostatitis (mean, 1707 msec ± 377, 79 msec ± 37, and 0.911 × 10
mm
/sec ± 0.239) were significantly lower than those in NPZ (P < .0005 for each). Interreader agreement was excellent, with an intraclass correlation coefficient greater than 0.75 for both T1 and T2 measurements. Conclusion This study describes the development of a rapid MR fingerprinting- and diffusion-based examination for quantitative characterization of prostatic tissue.
RSNA, 2017 Online supplemental material is available for this article.
Background
Conventional MRI can be limited in detecting subtle epileptic lesions or identifying active/epileptic lesions among widespread, multifocal lesions.
Purpose
We developed a high‐resolution ...3D MR fingerprinting (MRF) protocol to simultaneously provide quantitative T1, T2, proton density, and tissue fraction maps for detection and characterization of epileptic lesions.
Study type
Prospective.
Population
National Institute of Standards and Technology (NIST) / International Society for Magnetic Resonance in Medicine (ISMRM) phantom, five healthy volunteers and 15 patients with medically intractable epilepsy undergoing presurgical evaluation with noninvasive or invasive electroclinical data.
Field Strength/Sequence
3D MRF scans and routine clinical epilepsy MR protocols were acquired at 3 T.
Assessment
The accuracy of the T1 and T2 values were first evaluated using the NIST/ISMRM phantom. The repeatability was then estimated with both phantom and volunteers based on the coefficient of variance (CV). For epilepsy patients, all the maps were qualitatively reviewed for lesion detection by three independent reviewers (S.E.J., M.L., I.N.) blinded to clinical data. Region of interest (ROI) analysis was performed on T1 and T2 maps to quantify the multiparametric signal differences between lesion and normal tissues. Findings from qualitative review and quantitative ROI analysis were compared with patients' electroclinical data to assess concordance.
Statistical Tests
Phantom results were compared using R‐squared, and patient results were compared using linear regression models.
Results
The phantom study showed high accuracy with the standard values, with an R2 of 0.99. The volunteer study showed high repeatability, with an average CV of 4.3% for T1 and T2 in various tissue regions. For the 15 patients, MRF showed additional findings in four patients, with the remaining 11 patients showing findings consistent with conventional MRI. The additional MRF findings were highly concordant with patients' electroclinical presentation.
Data Conclusion
The 3D MRF protocol showed potential to identify otherwise inconspicuous epileptogenic lesions from the patients with negative conventional MRI diagnosis, as well as to correlate with different levels of epileptogenicity when widespread lesions were present.
Level of Evidence: 3.
Technical Efficacy Stage: 3.
J. Magn. Reson. Imaging 2019;49:1333–1346.
Magnetic particle imaging (MPI) is an emerging imaging modality with promising applications in diagnostic imaging and guided therapy. The image quality in MPI is strongly dependent on the nature of ...its iron oxide nanoparticle–based tracers. The selection of potential MPI tracers is currently limited, and the underlying physics of tracer response is not yet fully understood. An in-depth understanding of the magnetic relaxation processes that govern MPI tracers, gained through concerted theoretical and experimental work, is crucial to the development of optimized MPI tracers. Although tailored tracers will lead to improvements in image quality, tailored relaxation may also be exploited for biomedical applications or more flexible image contrast, as in the recent demonstration of color MPI.
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