Dataset Information

Iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) magnetic resonance imaging as a biomarker for symptomatic multiple myeloma.

ABSTRACT: To evaluate the effectiveness of iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) magnetic resonance imaging (MRI) to discriminate between symptomatic and asymptomatic myeloma in lumbar bone marrow without visible focal lesions.The lumbar spine was examined with 3-T MRI in 11 patients with asymptomatic myeloma and 24 patients with symptomatic myeloma. The fat-signal fraction was calculated from the ratio of the signal intensity in the fat image divided by the signal intensity of the corresponding ROI in the in-phase IDEAL image. The t test was used to compare the asymptomatic and symptomatic groups. ROC curves were constructed to determine the ability of variables to discriminate between symptomatic and asymptomatic myeloma.Univariate analysis showed that ?2-microglobulin and bone marrow plasma cell percent (BMPC%) were significantly higher and fat-signal fraction was significantly lower with symptomatic myeloma than with asymptomatic myeloma. Areas under the curve were 0.847 for ?2;-microglobulin, 0.834 for fat-signal fraction, and 0.759 for BMPC%.The fat-signal fraction as a biomarker for multiple myeloma enables discrimination of symptomatic myeloma from asymptomatic myeloma. The fat-signal fraction offers superior sensitivity and specificity to BMPC% of biopsy specimens.

SUBMITTER: Takasu M

PROVIDER: S-EPMC4338220 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) magnetic resonance imaging as a biomarker for symptomatic multiple myeloma.

Takasu Miyuki M Kaichi Yoko Y Tani Chihiro C Date Shuji S Akiyama Yuji Y Kuroda Yoshiaki Y Sakai Akira A Awai Kazuo K

PloS one 20150223 2

<h4>Introduction</h4>To evaluate the effectiveness of iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) magnetic resonance imaging (MRI) to discriminate between symptomatic and asymptomatic myeloma in lumbar bone marrow without visible focal lesions.<h4>Materials and methods</h4>The lumbar spine was examined with 3-T MRI in 11 patients with asymptomatic myeloma and 24 patients with symptomatic myeloma. The fat-signal fraction was calculated from th ...[more]

PMID: 25706753

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Project description:Energy resolving detectors provide more than one spectral measurement in one image acquisition. The purpose of this study is to investigate, with simulation, the ability to decompose four materials using energy discriminating detectors and least squares minimization techniques.Three least squares parameter estimation decomposition techniques were investigated for four-material breast imaging tasks in the image domain. The first technique treats the voxel as if it consisted of fractions of all the materials. The second method assumes that a voxel primarily contains one material and divides the decomposition process into segmentation and quantification tasks. The third is similar to the second method but a calibration was used. The simulated computed tomography (CT) system consisted of an 80 kVp spectrum and a CdZnTe (CZT) detector that could resolve the x-ray spectrum into five energy bins. A postmortem breast specimen was imaged with flat panel CT to provide a model for the digital phantoms. Hydroxyapatite (HA) (50, 150, 250, 350, 450, and 550 mg/ml) and iodine (4, 12, 20, 28, 36, and 44 mg/ml) contrast elements were embedded into the glandular region of the phantoms. Calibration phantoms consisted of a 30/70 glandular-to-adipose tissue ratio with embedded HA (100, 200, 300, 400, and 500 mg/ml) and iodine (5, 15, 25, 35, and 45 mg/ml). The x-ray transport process was simulated where the Beer-Lambert law, Poisson process, and CZT absorption efficiency were applied. Qualitative and quantitative evaluations of the decomposition techniques were performed and compared. The effect of breast size was also investigated.The first technique decomposed iodine adequately but failed for other materials. The second method separated the materials but was unable to quantify the materials. With the addition of a calibration, the third technique provided good separation and quantification of hydroxyapatite, iodine, glandular, and adipose tissues. Quantification with this technique was accurate with errors of 9.83% and 6.61% for HA and iodine, respectively. Calibration at one point (one breast size) showed increased errors as the mismatch in breast diameters between calibration and measurement increased. A four-point calibration successfully decomposed breast diameter spanning the entire range from 8 to 20 cm. For a 14 cm breast, errors were reduced from 5.44% to 1.75% and from 6.17% to 3.27% with the multipoint calibration for HA and iodine, respectively.The results of the simulation study showed that a CT system based on CZT detectors in conjunction with least squares minimization technique can be used to decompose four materials. The calibrated least squares parameter estimation decomposition technique performed the best, separating and accurately quantifying the concentrations of hydroxyapatite and iodine.

Dataset Information

Iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) magnetic resonance imaging as a biomarker for symptomatic multiple myeloma.

Publications

Iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) magnetic resonance imaging as a biomarker for symptomatic multiple myeloma.

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