Low-dose imaging technique (LITE) MRI: initial experience in breast imaging

Objectives: To compare a low-dose dynamic contrast-enhanced breast MRI protocol (LITE MRI) to standard-dosage using a dual-dose injection technique. Methods: 8 females with a total of 10 lesions with imaging features compatible with fibroadenoma were imaged using a dual-dose dynamic contrast-enhanced-MRI (DCE-MRI) technique. After pre-contrast scans, 15% of a standard dose of contrast was administered; approximately 10 min later, the remaining 85% of the standard dose was administered. Enhancement kinetic parameters, conspicuity and signal-to-noise ratio were measured quantitatively. Results: One lesion showed no enhancement in either DCE series. All nine of the enhancing lesions were visualized in both the low-dose and standard-dose images. While the (low-to-standard) ratio of contrast doses was roughly 0.18, this did not match the ratios of kinetic parameters. Lesion conspicuity and enhancement rate were both higher in the low-dose images, with (low-to-standard) ratios 1.5 ± 0.1 and 1.2 ± 0.4, respectively. The upper limit of enhancement (ratio 0.3 ± 0.1) and signal-to-noise ratio (ratio 0.5 ± 0.1) were higher in the standard-dose images, but less than expected based on the ratio of the doses. Conclusions: This preliminary study demonstrates that LITE MRI has the potential to match standard DCE-MRI in the detection of enhancing lesions. Additionally, LITE MRI may enhance sensitivity to contrast media dynamics. Advances in knowledge: Lower doses of MRI contrast media may be equally effective in the detection of breast lesions, and increase sensitivity to contrast media dynamics. LITE MRI may help increase screening compliance and long-term patient safety.

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Quality assurance in MRI breast screening: comparing signal-to-noise ratio in dynamic contrast-enhanced imaging protocols

Physics in Medicine and Biology ◽

10.1088/0031-9155/61/1/37 ◽

2015 ◽

Vol 61 (1) ◽

pp. 37-49 ◽

Cited By ~ 4

Author(s):

Evanthia Kousi ◽

Marco Borri ◽

Jamie Dean ◽

Rafal Panek ◽

Erica Scurr ◽

...

Keyword(s):

Quality Assurance ◽

Breast Screening ◽

Signal To Noise Ratio ◽

Signal To Noise ◽

Dynamic Contrast Enhanced Imaging ◽

Dynamic Contrast Enhanced ◽

Imaging Protocols ◽

Contrast Enhanced ◽

Noise Ratio ◽

Enhanced Imaging

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Signal-to-noise ratio, contrast-to-noise ratio and pharmacokinetic modeling considerations in dynamic contrast-enhanced magnetic resonance imaging

Magnetic Resonance Imaging ◽

10.1016/j.mri.2012.05.005 ◽

2012 ◽

Vol 30 (9) ◽

pp. 1313-1322 ◽

Cited By ~ 31

Author(s):

Xin Li ◽

Wei Huang ◽

William D. Rooney

Keyword(s):

Magnetic Resonance Imaging ◽

Magnetic Resonance ◽

Signal To Noise Ratio ◽

Pharmacokinetic Modeling ◽

Resonance Imaging ◽

Signal To Noise ◽

Dynamic Contrast Enhanced ◽

Contrast Enhanced ◽

Noise Ratio

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Low-dose, phase-contrast mammography with high signal-to-noise ratio

Biomedical Optics Express ◽

10.1364/boe.7.000381 ◽

2016 ◽

Vol 7 (2) ◽

pp. 381 ◽

Cited By ~ 13

Author(s):

Lukas B. Gromann ◽

Dirk Bequé ◽

Kai Scherer ◽

Konstantin Willer ◽

Lorenz Birnbacher ◽

...

Keyword(s):

Phase Contrast ◽

Low Dose ◽

Signal To Noise Ratio ◽

High Signal ◽

Signal To Noise ◽

Noise Ratio

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Patch based reconstruction of undersampled data (PROUD) for high signal-to-noise ratio and high frame rate contrast enhanced liver imaging

Magnetic Resonance in Medicine ◽

10.1002/mrm.25551 ◽

2014 ◽

Vol 74 (6) ◽

pp. 1587-1597 ◽

Cited By ~ 4

Author(s):

Mitchell A. Cooper ◽

Thanh D. Nguyen ◽

Bo Xu ◽

Martin R. Prince ◽

Michael Elad ◽

...

Keyword(s):

Signal To Noise Ratio ◽

Frame Rate ◽

High Signal ◽

Liver Imaging ◽

Signal To Noise ◽

High Frame Rate ◽

Contrast Enhanced ◽

Noise Ratio ◽

Undersampled Data

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Deep learning–based denoising of low-dose SPECT myocardial perfusion images: quantitative assessment and clinical performance

European Journal of Nuclear Medicine and Molecular Imaging ◽

10.1007/s00259-021-05614-7 ◽

2021 ◽

Author(s):

Narges Aghakhan Olia ◽

Alireza Kamali-Asl ◽

Sanaz Hariri Tabrizi ◽

Parham Geramifar ◽

Peyman Sheikhzadeh ◽

...

Keyword(s):

Dose Reduction ◽

Low Dose ◽

Signal To Noise Ratio ◽

Standard Dose ◽

Pearson Correlation ◽

List Mode ◽

Signal To Noise ◽

Spect Myocardial Perfusion ◽

Dose Levels ◽

Nuclear Medicine Specialist

Abstract Purpose This work was set out to investigate the feasibility of dose reduction in SPECT myocardial perfusion imaging (MPI) without sacrificing diagnostic accuracy. A deep learning approach was proposed to synthesize full-dose images from the corresponding low-dose images at different dose reduction levels in the projection space. Methods Clinical SPECT-MPI images of 345 patients acquired on a dedicated cardiac SPECT camera in list-mode format were retrospectively employed to predict standard-dose from low-dose images at half-, quarter-, and one-eighth-dose levels. To simulate realistic low-dose projections, 50%, 25%, and 12.5% of the events were randomly selected from the list-mode data through applying binomial subsampling. A generative adversarial network was implemented to predict non-gated standard-dose SPECT images in the projection space at the different dose reduction levels. Well-established metrics, including peak signal-to-noise ratio (PSNR), root mean square error (RMSE), and structural similarity index metrics (SSIM) in addition to Pearson correlation coefficient analysis and clinical parameters derived from Cedars-Sinai software were used to quantitatively assess the predicted standard-dose images. For clinical evaluation, the quality of the predicted standard-dose images was evaluated by a nuclear medicine specialist using a seven-point (− 3 to + 3) grading scheme. Results The highest PSNR (42.49 ± 2.37) and SSIM (0.99 ± 0.01) and the lowest RMSE (1.99 ± 0.63) were achieved at a half-dose level. Pearson correlation coefficients were 0.997 ± 0.001, 0.994 ± 0.003, and 0.987 ± 0.004 for the predicted standard-dose images at half-, quarter-, and one-eighth-dose levels, respectively. Using the standard-dose images as reference, the Bland–Altman plots sketched for the Cedars-Sinai selected parameters exhibited remarkably less bias and variance in the predicted standard-dose images compared with the low-dose images at all reduced dose levels. Overall, considering the clinical assessment performed by a nuclear medicine specialist, 100%, 80%, and 11% of the predicted standard-dose images were clinically acceptable at half-, quarter-, and one-eighth-dose levels, respectively. Conclusion The noise was effectively suppressed by the proposed network, and the predicted standard-dose images were comparable to reference standard-dose images at half- and quarter-dose levels. However, recovery of the underlying signals/information in low-dose images beyond a quarter of the standard dose would not be feasible (due to very poor signal-to-noise ratio) which will adversely affect the clinical interpretation of the resulting images.

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Influence of Iodinated Contrast Media and Isotope 99mTc on Changes of Signal to Noise Ratio of Magnetic Resonance Imaging

Applied Magnetic Resonance ◽

10.1007/s00723-015-0695-y ◽

2015 ◽

Vol 46 (8) ◽

pp. 931-940

Author(s):

Jin-Hyeok Lee ◽

Hae-Kag Lee ◽

Jae-Hwan Cho

Keyword(s):

Magnetic Resonance Imaging ◽

Magnetic Resonance ◽

Contrast Media ◽

Signal To Noise Ratio ◽

Iodinated Contrast Media ◽

Resonance Imaging ◽

Signal To Noise ◽

Iodinated Contrast ◽

Noise Ratio

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Can imaging kinetic parameters of dynamic contrast-enhanced magnetic resonance imaging be valuable in predicting clinicopathological prognostic factors of invasive breast cancer?

Acta Radiologica ◽

10.1177/0284185117740746 ◽

2017 ◽

Vol 59 (7) ◽

pp. 813-821 ◽

Cited By ~ 3

Author(s):

Cuiyan Wang ◽

Wei Wei ◽

Lumarie Santiago ◽

Gary Whitman ◽

Basak Dogan

Keyword(s):

Breast Cancer ◽

Prognostic Factors ◽

Kinetic Parameters ◽

Invasive Breast Cancer ◽

Imaging Biomarkers ◽

High Grade ◽

Maximum Slope ◽

Dce Mri ◽

Dynamic Contrast Enhanced ◽

Contrast Enhanced

Background Intrinsic molecular profiling of breast cancer provides clinically relevant information that helps tailor therapy directed to the specific tumor subtype. We hypothesized that dynamic contrast-enhanced MRI (DCE-MRI) derived quantitative kinetic parameters (CD-QKPs) may help predict molecular tumor profiles non-invasively. Purpose To determine the association between DCE-MRI (CD-QKPs) and breast cancer clinicopathological prognostic factors. Material and Methods Clinicopathological factors in consecutive women with biopsy-confirmed invasive breast cancer who underwent breast DCE-MRI were retrospectively reviewed. Analysis of variance was used to examine associations between prognostic factors and CD-QKPs. Fisher’s exact test was used to investigate the relationship between kinetic curve type and prognostic factors. Results A total of 198 women with invasive breast cancer were included. High-grade and HER2+ tumors were more likely to have a washout type curve while luminal A tumors were less likely. High-grade was significantly associated with increased peak enhancement (PE; P = 0.01), enhancement maximum slope (MS; P = 0.03), and mean enhancement ( ME, P = 0.03), while high clinical lymph node stage (cN3) was significantly associated with increased MS and time to peak (tP; P = 0.01). HER2+ tumors were associated with a higher PE ( P = 0.03) and ME ( P = 0.06) than HER2- counterparts, and ER-/HER2+ tumors showed higher PE and ME values than ER+/HER2- tumors ( P = 0.06). Conclusion DCE-MRI time-intensity CD-QKPs are associated with high tumor grade, advanced nodal stage, and HER2+ status, indicating their utility as imaging biomarkers.

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Maximum Entropy Approach in Dynamic Contrast-Enhanced Magnetic Resonance Imaging

Methods of Information in Medicine ◽

10.3414/me17-01-0027 ◽

2017 ◽

Vol 56 (06) ◽

pp. 461-468 ◽

Cited By ~ 1

Author(s):

Zahra Farsani ◽

Volker Schmid

Keyword(s):

Magnetic Resonance Imaging ◽

Kinetic Parameters ◽

Maximum Entropy ◽

Maximum Entropy Method ◽

Input Function ◽

Entropy Method ◽

Resonance Imaging ◽

Dce Mri ◽

Dynamic Contrast Enhanced ◽

Contrast Enhanced

SummaryBackground: In the estimation of physiological kinetic parameters from Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) data, the determination of the arterial input function (AIF) plays a key role.Objectives: This paper proposes a Bayesian method to estimate the physiological parameters of DCE-MRI along with the AIF in situations, where no measurement of the AIF is available.Methods: In the proposed algorithm, the maximum entropy method (MEM) is combined with the maximum a posterior approach (MAP). To this end, MEM is used to specify a prior probability distribution of the unknown AIF. The ability of this method to estimate the AIF is validated using the Kullback-Leibler divergence. Subsequently, the kinetic parameters can be estimated with MAP. The proposed algorithm is evaluated with a data set from a breast cancer MRI study.Results: The application shows that the AIF can reliably be determined from the DCE-MRI data using MEM. Kinetic parameters can be estimated subsequently.Conclusions: The maximum entropy method is a powerful tool to reconstructing images from many types of data. This method is useful for generating the probability distribution based on given information. The proposed method gives an alternative way to assess the input function from the existing data. The proposed method allows a good fit of the data and therefore a better estimation of the kinetic parameters. In the end, this allows for a more reliable use of DCE-MRI.

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