Subject-specific models of susceptibility-induced B0 field variations in breast MRI

Multishot Diffusion-Weighted MRI of the Breasts in the Supine vs. Prone Position

BACKGROUND

Diffusion-weighted imaging (DWI) may allow for breast cancer screening MRI without a contrast injection. Multishot methods improve prone DWI of the breasts but face different challenges in the supine position.

PURPOSE

To establish a multishot DWI (msDWI) protocol for supine breast MRI and to evaluate the performance of supine vs. prone msDWI.

STUDY TYPE

Prospective.

POPULATION

Protocol optimization: 10 healthy women (ages 22-56), supine vs. prone: 24 healthy women (ages 22-62) and five women (ages 29-61) with breast tumors.

FIELD STRENGTH/SEQUENCE

3-T, protocol optimization msDWI: free-breathing (FB) 2-shots, FB 4-shots, respiratory-triggered (RT) 2-shots, RT 4-shots, supine vs. prone: RT 4-shot msDWI, T2-weighted fast-spin echo.

ASSESSMENT

Protocol optimization and supine vs. prone: three observers performed an image quality assessment of sharpness, aliasing, distortion (vs. T2), perceived SNR, and overall image quality (scale of 1-5). Apparent diffusion coefficients (ADCs) in fibroglandular tissue (FGT) and breast tumors were measured.

STATISTICAL TESTS

Effect of study variables on dichotomized ratings (4/5 vs. 1/2/3) and FGT ADCs were assessed with mixed-effects logistic regression. Interobserver agreement utilized Gwet's agreement coefficient (AC). Lesion ADCs were assessed by Bland-Altman analysis and concordance correlation (ρc ). P value <0.05 was considered statistically significant.

RESULTS

Protocol optimization: 4-shots significantly improved sharpness and distortion; RT significantly improved sharpness, aliasing, perceived SNR, and overall image quality. FGT ADCs were not significantly different between shots (P = 0.812), FB vs. RT (P = 0.591), or side (P = 0.574). Supine vs. prone: supine images were rated significantly higher for sharpness, aliasing, and overall image quality. FGT ADCs were significantly higher supine; lesion ADCs were highly correlated (ρc  = 0.92).

DATA CONCLUSION

Based on image quality, supine msDWI outperformed prone msDWI. Lesion ADCs were highly correlated between the two positions, while FGT ADCs were higher in the supine position.

EVIDENCE LEVEL

2.

TECHNICAL EFFICACY

Stage 1.

A T1-based correction method for proton resonance frequency shift thermometry in breast tissue

PURPOSE

Develop and evaluate the effectiveness of a T1-based correction method for errors in proton resonant frequency shift thermometry due to non-local field effects caused by heating in fatty breast tissues.

METHODS

Computational models of human breast tissue were created by segmenting MRI data from a healthy human volunteer. MR-guided focused ultrasound (MRgFUS) heating and MR thermometry measurements were simulated in several locations in the heterogeneous segmented breast models. A T1-based correction method for PRF thermometry errors was applied and the maximum positive and negative errors and the root mean squared error (RMSE) in a region around each heating location was evaluated with and without correction. The method uses T1 measurements to estimate the temperature change in fatty tissues and correct for their influence. Experimental data from a heating study in cadaver breast tissue were analyzed, and the expected PRFS error computed.

RESULTS

The simulated MR thermometry had maximum single voxel errors ranging between 10% and 18% when no correction was applied. Applying the correction led to a considerable improvement, lowering the maximum error range to 2%-5%. The 5th to 95th percentile interval of the temperature error distribution was also lowered with correction, from approximately 3.5 to 1°C. This correction worked even when T1 times were uniformly raised or lowered by 5%-10%. The experimental data showed predicted errors of 15%.

CONCLUSIONS

This simulation study demonstrates that the T1-based correction method reduces MR thermometry errors due to non-local effects from heating in fatty tissues, potentially improving the accuracy of thermometry measurements during MRgFUS treatments. The presented correction method is reliant on having a patient-specific 3D model of the breast, and may be limited by the accuracy of the fat temperatures which in turn may be limited by noise or bias present in the T1 measurements.

B0 field homogeneity recommendations, specifications, and measurement units for MRI in radiation therapy

PURPOSE

The purpose is: (a) Relate magnetic resonance imaging (MRI) quality recommendations for radiation therapy (RT) to B₀ field homogeneity; (b) Evaluate manufacturer specifications of B₀ homogeneity for 34 commercial whole-body MRI systems based on the MRI quality recommendations and RT application; (c) Measure field homogeneity in five commercial MRI systems and one commercial MRI-Linac used in RT and compare the results with their B₀ homogeneity specifications.

METHODS

Magnetic resonance imaging quality recommendations for spatial integrity, image blurring, fat saturation, and null banding in RT were developed based on the literature. Guaranteed (maximum) and typical B₀ field homogeneity specifications for various diameter spherical volumes (DSVs) were provided by GE, Philips, Siemens, and Canon. For each system, the DSV that conforms to each MRI quality recommendation and anatomical RT application was estimated based on the manufacturer specifications. B₀ field homogeneity was measured on six MRI systems including Philips (1.5 T), Siemens (1.5 and 3 T), and ViewRay MRI (0.35 T) systems using 24 and 35 cm DSV spherical phantoms. Two measurement techniques were used: (a) MRI using phase contrast field mapping to measure peak-to-peak (pk-pk), volume root mean square (VRMS), and standard deviation (SD); and (b) Magnetic resonance (MR) spectroscopy by acquiring a volumetric free induction decay (FID) to measure full width at half maximum (FWHM). The measurements were used to assess: (a) conformance with the manufacturer specifications; and (b) the relationship between the various field homogeneity measurement units. Measurements were made with and without gradient shimming (gradshim) or second-order active shimming. Multiple comparisons, analysis of variance (ANOVA), and Pearson correlations were performed to assess the dependence of pk-pk, VRMS, SD, and FWHM measurements of field homogeneity on shim volume, level of shim, and MRI system.

RESULTS

For a 40 cm DSV, the B₀ homogeneity specifications ranged from 0.35 to 5 ppm (median = 0.75 ppm) VRMS for 1.5 T systems and 0.2 to 1.4 ppm (median = 0.5 ppm) VRMS for 3 T systems. The usable DSVs ranged from 16 to 49 cm (median = 35 cm) based on the image quality recommendations and the manufacturer specifications. There was general compliance between the six measured field homogeneities and manufacturer specifications although signal dephasing was observed in two systems at < 35 cm DSV. The relationships between pk-pk, VRMS, SD, and FWHM varied based on MRI system, shim volume, and quality of shim. However, VRMS and SD measurements were highly correlated.

CONCLUSIONS

The delineation of the diseased lesion from organs at risk is the main priority for RT. Therefore, field homogeneity performance for RT must minimize image blurring and image artifacts (null bands and signal dephasing) while optimizing spatial integrity and fat saturation. Based on the specifications and recommendations for field homogeneity, some MRI systems are not well suited to meet the strict demands of RT particularly for the large imaging volumes used in body MRI. VRMS and SD measurements of B₀ field homogeneity tend to be more stable and sensitive to field inhomogeneities in RT applications than pk-pk and FWHM.

Model-based reconstruction framework for correction of signal pile-up and geometric distortions in prostate diffusion MRI

PURPOSE

Prostate diffusion-weighted MRI scans can suffer from geometric distortions, signal pileup, and signal dropout attributed to differences in tissue susceptibility values at the interface between the prostate and rectal air. The aim of this work is to present and validate a novel model based reconstruction method that can correct for these distortions.

METHODS

In regions of severe signal pileup, standard techniques for distortion correction have difficulty recovering the underlying true signal. Furthermore, because of drifts and inaccuracies in the determination of center frequency, echo planar imaging (EPI) scans can be shifted in the phase-encoding direction. In this work, using a B0 field map and a set of EPI data acquired with blip-up and blip-down phase encoding gradients, we model the distortion correction problem linking the distortion-free image to the acquired raw corrupted k-space data and solve it in a manner analogous to the sensitivity encoding method. Both a quantitative and qualitative assessment of the proposed method is performed in vivo in 10 patients.

RESULTS

Without distortion correction, mean Dice similarity scores between a reference T2W and the uncorrected EPI images were 0.64 and 0.60 for b-values of 0 and 500 s/mm2 , respectively. Compared to the Topup (distortion correction method commonly used for neuro imaging), the proposed method achieved Dice scores (0.87 and 0.85 versus 0.82 and 0.80) and better qualitative results in patients where signal pileup was present because of high rectal gas residue.

CONCLUSION

Model-based reconstruction can be used for distortion correction in prostate diffusion MRI.

Rapid, theoretically artifact-free calculation of static magnetic field induced by voxelated susceptibility distribution in an arbitrary volume of interest

PURPOSE

To demonstrate a computationally efficient and theoretically artifact-free method to calculate static field (B₀ ) inhomogeneity in a volume of interest induced by an arbitrary voxelated susceptibility distribution.

METHODS

Our method computes B₀ by circular convolution between a zero-filled susceptibility matrix and a shifted, voxel-integrated dipolar field kernel on a grid of size N_S +N_T - 1 in each dimension, where N_S and N_T are the sizes of the susceptibility source and B₀ target grids, respectively. The computational resource requirement is independent of source-target separation. The method, called generalized susceptibility voxel convolution, is demonstrated on three susceptibility models: an ellipsoid, MR-compatible screws, and a dynamic human heartbeat model.

RESULTS

B₀ in an ellipsoid calculated by generalized susceptibility voxel convolution matched an analytical solution nearly exactly. The method also calculated screw-induced B₀ in agreement with experimental data. Dynamic simulation demonstrated its computational efficiency for repeated B₀ calculations on time-varying susceptibility. On the contrary, conventional and alias-subtracted k-space-discretized Fourier convolution methods showed nonnegligible aliasing and Gibbs ringing artifacts in the tested models.

CONCLUSION

Generalized susceptibility voxel convolution can be a fast and reliable way to compute susceptibility-induced B₀ when the susceptibility source is not colocated with the B₀ target volume of interest, as in modeling B₀ variations from motion and foreign objects.

Quantitative Magnetization Transfer Imaging of the Breast at 3.0 T: Reproducibility in Healthy Volunteers

Quantitative magnetization transfer magnetic resonance imaging provides a means for indirectly detecting changes in the macromolecular content of tissue noninvasively. A potential application is the diagnosis and assessment of treatment response in breast cancer; however, before quantitative magnetization transfer imaging can be reliably used in such settings, the technique's reproducibility in healthy breast tissue must be established. Thus, this study aims to establish the reproducibility of the measurement of the macromolecular-to-free water proton pool size ratio (PSR) in healthy fibroglandular (FG) breast tissue. Thirteen women with no history of breast disease were scanned twice within a single scanning session, with repositioning between scans. Eleven women had appreciable FG tissue for test–retest measurements. Mean PSR values for the FG tissue ranged from 9.5% to 16.7%. The absolute value of the difference between 2 mean PSR measurements for each volunteer ranged from 0.1% to 2.1%. The 95% confidence interval for the mean difference was ±0.75%, and the repeatability value was 2.39%. These results indicate that the expected measurement variability would be ±0.75% for a cohort of a similar size and would be ±2.39% for an individual, suggesting that future studies of change in PSR in patients with breast cancer are feasible.

Breast density assessment using a 3T MRI system: comparison among different sequences

Purpose

To compare MRI sequences for breast density measurements on a 3T MRI system using IDEAL (Iterative Decomposition of water and fat with Echo Asymmetry and Least squares estimation) as possible physiology-like reference.

Materials and Methods

MRI examination was performed in 48 consecutive patients (mean age 41, years; range, 35–67 years) on a 3.0T scanner and 46 were included. All (fertile) women, were examined between days 5 and 15 of their menstrual cycle. MRI protocol included: T1-turbo spin-echo (T1-tSE), T2-turbo spin-echo (T2-tSE), VIBRANT (Volume Imaging for Breast Assessment) before and after injection of contrast media and IDEAL. Breast density was calculated with semi-automated software. Statistical analysis was performed with non-parametric tests.

Results

Mean percentage of breast density calculated in each sequence was: T1-tSE  = 56%; T2-tSE  = 52%; IDEAL FatOnly  = 55%; IDEAL WaterOnly  = 53%, VIBRANT  = 55%. Significant differences were observed between T2-tSE and both T1-tSE (p<0.001), VIBRANT sequences (p = 0.009), T1-tSE and both IDEAL WaterOnly (p = 0.007) and IDEAL FatOnly (p = 0.047). Breast density percentage showed a positive linear correlation among different sequences: r≥0.93.

Conclusions

Differences exist between MRI sequences used to assess breast density percentage. T1-weighted sequences values were similar to IDEAL sequences.