Distortions In Diffusion-weighted Images Research Articles

Optimization of non-endorectal prostate MR image quality using PI-QUAL: A multidisciplinary team approach

PurposeTo evaluate the utility of the PI-QUAL score in assessing protocol changes aimed to improve image quality from a non-endorectal coil prostate MR imaging protocol during a 9-month quality improvement (QI) project and to quantify the inter-reader agreement of PI-QUAL scores between radiologists, technologists, and physicists. MethodsThis retrospective study audited 1,012 multiparametric prostate MRI examinations as part of a national QI project according to the PI-QUAL standard. PI-QUAL scores were used to inform MR protocol changes. Following the project, 4 radiologists, 2 technologists, and 1 medical physicist collectively audited an additional set of 150 examinations to identify statistical improvements in image quality using the two-tailed Wilcoxon rank sum test. The improvements due to individual protocol changes were assessed among subsets of the 1,012 examinations which compared examinations occurring before and after the isolated protocol change. Inter-reader variability was assessed using the percent majority agreement and the average standard deviation of PI-QUAL scores between evaluators. ResultsDuring this QI project, PI-QUAL scores improved from 3.67 ± 0.75 to 4.16 ± 0.59 (p < 0.01) after implementing a series of protocol changes. Among a subset of 451 cases, we found that adopting R/L rather than A/P phase encoding reduced distortion in diffusion-weighted imaging (DW) from 21.6% (41/190 A/P phase encoded cases) to 11.5% (30/261 R/L phase encoded cases) (p < 0.01). Similarly, in the same 451 cases, adopting R/L phase encoding in T2WI reduced breathing motion artifacts from 34.6% (94/272 A/P phase encoding cases) to 12.8% (23/179 R/L phase encoding cases) (p < 0.01). DWI wraparound artifact was mitigated by employing a full-pelvis shim and enabling the abdomen shim option. The occurrence of low signal-to-noise ratio was reduced from 19.4% (19/98 cases without a weight-based threshold) to 6.3% (10/160) by instituting a weight-based threshold for using an endorectal coil (p < 0.01). The percent majority agreement was similar between radiologists, technologists and physicists, and all evaluators combined (72%, 77%, and 67%, respectively). ConclusionsPI-QUAL can evaluate image quality changes resulting from protocol optimizations at both the exam- and series-levels. With training, radiologists, technologists, and physicists can perform PI-QUAL scoring with similar performance. Broadening the scope of the quality improvement team can result in meaningful and lasting change.

Evaluating Reproducibility of the ADC and Distortion in Diffusion-weighted Imaging (DWI) with Reverse Encoding Distortion Correction (RDC).

To compare image distortion and reproducibility of quantitative values between reverse encoding distortion correction (RDC) diffusion-weighted imaging (DWI) and conventional DWI techniques in a phantom study and in healthy volunteers. This prospective study was conducted with the approval of our institutional review board. Written informed consent was obtained from each participant. RDC-DWIs were created from images obtained at 3T in three orthogonal directions in a phantom and in 10 participants (mean age, 70.9 years; age range, 63-83 years). Images without distortion correction (noDC-DWI) and those corrected with B0 (B0c-DWI) were also created. To evaluate distortion, coefficients of variation were calculated for each voxel and ROIs were placed at four levels of the brain. To evaluate the reproducibility of apparent diffusion coefficient (ADC) measurements, intra- and inter-scan variability (%CVADC) were calculated from repeated scans of the phantom. Analysis was performed using Wilcoxon signed-rank test with Bonferroni correction, and P < 0.05 was considered statistically significant. In the phantom, distortion was less in RDC-DWI than in B0c-DWI (P < 0.006), and was less in B0c-DWI than in noDC-DWI (P < 0.006). Intra-scan %CVADC was within 1.30%, and inter-scan %CVADC was within 2.99%. In the volunteers, distortion was less in RDC-DWI than in B0c-DWI in three of four locations (P < 0.006), and was less in B0c-DWI than in noDC-DWI (P < 0.006). At the middle cerebellar peduncle, distortion was less in RDC-DWI than in noDC-DWI (P < 0.006), and was less in noDC-DWI than in B0c-DWI (P < 0.0177). In both the phantom and in volunteers, distortion was the least in RDC-DWI than in B0c-DWI and noDC-DWI.

A Preliminary Study of the Geometric Distortion in Diffusion-Weighted Imaging of Magnetic Resonance Imaging Simulation

A Preliminary Study of the Geometric Distortion in Diffusion-Weighted Imaging of Magnetic Resonance Imaging Simulation

Diffusion-weighted imaging in the assessment of prostate cancer: Comparison of zoomed imaging and conventional technique

PurposeTo compare reduced field-of-view (zoomed) diffusion-weighted imaging (DWI) and conventional DWI in the evaluation of prostate cancer with respect to lesion detection, image quality and alignment accuracy. Material and methodsThe study was carried out in accordance with the Declaration of Helsinki and was approved by the institutional review board. Image data of 29 histology-proven prostate cancer lesions in 15 patients were evaluated. All patients underwent both conventional DWI and zoomed DWI at 3T. Zoomed DWI and conventional DWI sequences were analysed qualitatively and quantitatively. Subjective image quality, visual distortion and presence of artefacts were rated on a 5-point Likert scale (1=excellent) by two readers in consensus. Lesion conspicuity, sensitivity and specificity in lesion detection were evaluated and compared for both DWI sequences using ROC curves and area under the curve (AUC). To analyze the geographic distortion in DWI the alignment accuracy of prostate and lesions was measured in three spatial dimensions referring to the T2-weighted anatomical images as reference. In a region of interest (ROI) evaluation, ADC values were measured in prostate tissue and malignant lesions. Comparison of qualitative and quantitative parameters was performed using Wilcoxon test with subsequent Bonferroni correction. ResultsSubjective image quality was rated significantly higher in zoomed DWI compared to conventional DWI (2.1±0.9 vs. 2.7±0.9; p=0.0375). Visual distortion and artefacts were reduced in zoomed DWI without reaching statistical significance (1.8±0.7 vs. 2.4±1.0 and 2.1±1.0 vs. 2.5±1.0). Sensitivity and specificity of zoomed and conventional DWI were not significantly different. Zoomed DWI had a slightly higher AUC compared to conventional DWI without significant difference (0.82 versus 0.78; p=0.0576). Lesion conspicuity did not significantly differ between zoomed DWI and conventional DWI (1.8±0.8 vs. 1.9±1.0; p=0.8523). The alignment accuracy of zoomed DWI was significantly higher regarding both the prostate gland and lesions (deviation of outer contours of lesions in sagittal plane: 3±4mm vs. 5±3mm; p=0.0008). ADC tended to be higher in zoomed DWI without statistical significance (ADCmean in peripheral zone: 1.7±0.2×10−3mm2/s vs. 1.5±0.4×10−3mm2/s; ADCmean in lesion: 1.0±0.71×10−3mm2/s vs. 0.8±0.2×10−3mm2/s). ConclusionsZoomed technique offers improved image quality for diffusion-weighted imaging of the prostate with reduced image distortion both for the whole gland as well as for cancer lesions and at least comparable diagnostic performance. The zoomed technique could be useful for multiparametric tissue characterization but also for biopsy and radiation therapy planning.

Distortion correction of echo-planar diffusion-weighted images of uterine cervix.

PurposeTo investigate the clinical utility of the reverse gradient algorithm in correcting distortions in diffusion‐weighted images of the cervix and for increasing diagnostic performance.Materials and MethodsForty‐one patients ages 25–72 years (mean 40 ± 11 years) with suspected or early stage cervical cancer were imaged at 3T using an endovaginal coil. T 2‐weighted (W) and diffusion‐weighted images with right and left phase‐encode gradient directions were obtained coronal to the cervix (b = 0, 100, 300, 500, 800 s mm−2). Differences in angle of the endocervical canal to the x‐axis between T 2W and right‐gradient, left‐gradient, and corrected images were measured. Uncorrected and corrected images were assessed for diagnostic performance when viewed together with T 2W images by two independent observers against subsequent histology.ResultsThe angles of the endocervical canal relative to the x‐axis were significantly different between the T 2W images and the right‐gradient images (P = 0.007), approached significance for left‐gradient images (P = 0.055), and were not significantly different after correction (P = 0.95). Corrected images enabled a definitive diagnosis in 34% (n = 14) of patients classified as equivocal on uncorrected images. Tumor volume in this subset was 0.18 ± 0.44 cm3 (mean ± SD; sensitivity of detection 100% [8/8], specificity 50% [3/6] for an experienced observer). Correction did not improve diagnostic performance for the less‐experienced observer.ConclusionDistortion‐corrected diffusion‐weighted images improved correspondence with T 2W images and diagnostic performance in a third of cases. J. Magn. Reson. Imaging 2016;43:1218–1223.

Distortion correction of high b-valued and high angular resolution diffusion images using iterative simulated images

High b-valued diffusion-weighted images (DWI), which were designed to solve fiber-crossing problems, are susceptible to many artifacts and distortions. Since DWIs with different diffusion gradients produce dissimilar intensity contrasts, and since the distortion is nonlinear when multiple artifactual sources are intermixed, the mutual information-based affine registration may not be adequate for precise correction of distortions in DWIs, especially for images acquired with high b-values. To overcome these problems, we proposed an iterative image registration technique through which simulated DWIs are generated, driven from a diffusion tensor estimate, as targets for measured DWIs in the registration. Since simulated DWIs have similar intensity profiles to those of measured DWIs and the same geometric profiles as b(0)-images, an iterative procedure enables intensity-based nonlinear registration. As a pre-processing step, we also proposed a motion detection and sub-volume utilization for interleaved volumes. Performance evaluation with high b-valued DWIs for high angular resolution diffusion imaging and diffusion kurtosis imaging showed that the proposed method had a superior advantage over the conventional registration technique.

Distortion correction for diffusion‐weighted MRI tractography and fMRI in the temporal lobes

Single shot echo-planar imaging (EPI) sequences are currently the most commonly used sequences for diffusion-weighted imaging (DWI) and functional magnetic resonance imaging (fMRI) as they allow relatively high signal to noise with rapid acquisition time. A major drawback of EPI is the substantial geometric distortion and signal loss that can occur due to magnetic field inhomogeneities close to air-tissue boundaries. If DWI-based tractography and fMRI are to be applied to these regions, then the distortions must be accurately corrected to achieve meaningful results. We describe robust acquisition and processing methods for correcting such distortions in spin echo (SE) EPI using a variant of the reversed direction k space traversal method with a number of novel additions. We demonstrate that dual direction k space traversal with maintained diffusion-encoding gradient strength and direction results in correction of the great majority of eddy current-associated distortions in DWI, in addition to those created by variations in magnetic susceptibility. We also provide examples to demonstrate that the presence of severe distortions cannot be ignored if meaningful tractography results are desired. The distortion correction routine was applied to SE-EPI fMRI acquisitions and allowed detection of activation in the temporal lobe that had been previously found using PET but not conventional fMRI.