Prostate Diffusion-weighted Imaging Research Articles

Partial Fourier in the presence of respiratory motion in prostate diffusion-weighted echo planar imaging.

To investigate the effect of respiratory motion in terms of signal loss in prostate diffusion-weighted imaging (DWI), and to evaluate the usage of partial Fourier in a free-breathing protocol in a clinically relevant b-value range using both single-shot and multi-shot acquisitions. A controlled breathing DWI acquisition was first employed at 3T to measure signal loss from deep breathing patterns. Single-shot and multi-shot (2-shot) acquisitions without partial Fourier (no pF) and with partial Fourier (pF) factors of 0.75 and 0.65 were employed in a free-breathing protocol. The apparent SNR and ADC values were evaluated in 10 healthy subjects to measure if low pF factors caused low apparent SNR or overestimated ADC. Controlled breathing experiments showed a difference in signal coefficient of variation between shallow and deep breathing. In free-breathing single-shot acquisitions, the pF 0.65 scan showed a significantly (p < 0.05) higher apparent SNR than pF 0.75 and no pF in the peripheral zone (PZ) of the prostate. In the multi-shot acquisitions in the PZ, pF 0.75 had a significantly higher apparent SNR than 0.65 pF and no pF. The single-shot pF 0.65 scan had a significantly lower ADC than single-shot no pF. Deep breathing patterns can cause intravoxel dephasing in prostate DWI. For single-shot acquisitions at a b-value of 800s/mm2, any potential risks of motion-related artefacts at low pF factors (pF 0.65) were outweighed by the increase in signal from a lower TE, as shown by the increase in apparent SNR. In multi-shot acquisitions however, the minimum pF factor should be larger, as shown by the lower apparent SNR at low pF factors.

Feasibility of Accelerated Prostate Diffusion-Weighted Imaging on 0.55 T MRI Enabled With Random Matrix Theory Denoising.

Prostate cancer diffusion weighted imaging (DWI) MRI is typically performed at high-field strength (3.0 T) in order to overcome low signal-to-noise ratio (SNR). In this study, we demonstrate the feasibility of prostate DWI at low field enabled by random matrix theory (RMT)-based denoising, relying on the MP-PCA algorithm applied during image reconstruction from multiple coils. Twenty-one volunteers and 2 prostate cancer patients were imaged with a 6-channel pelvic surface array coil and an 18-channel spine array on a prototype 0.55 T system created by ramping down a commercial magnetic resonance imaging system (1.5 T MAGNETOM Aera Siemens Healthcare) with 45 mT/m gradients and 200 T/m/s slew rate. Diffusion-weighted images were acquired with 4 non-collinear directions, for which b = 50 s/mm 2 was used with 8 averages and b = 1000 s/mm 2 with 40 averages; 2 extra b = 50 s/mm 2 were used as part of the dynamic field correction. Standard and RMT-based reconstructions were applied on DWI over different ranges of averages. Accuracy/precision was evaluated using the apparent diffusion coefficient (ADC), and image quality was evaluated over 5 separate reconstructions by 3 radiologists with a 5-point Likert scale. For the 2 patients, we compare image quality and lesion visibility of the RMT reconstruction versus the standard one on 0.55 T and on clinical 3.0 T. The RMT-based reconstruction in this study reduces the noise floor by a factor of 5.8, thereby alleviating the bias on prostate ADC. Moreover, the precision of the ADC in prostate tissue after RMT increases over a range of 30%-130%, with the increase in both signal-to-noise ratio and precision being more prominent for a low number of averages. Raters found that the images were consistently of moderate to good overall quality (3-4 on the Likert scale). Moreover, they determined that b = 1000 s/mm 2 images from a 1:55-minute scan with the RMT-based reconstruction were on par with the corresponding images from a 14:20-minute scan with standard reconstruction. Prostate cancer was visible on ADC and calculated b = 1500 images even with the abbreviated 1:55-minute scan reconstructed with RMT. Prostate imaging using DWI is feasible at low field and can be performed more rapidly with noninferior image quality compared with standard reconstruction.

A dual attention-guided 3D convolution network for automatic segmentation of prostate and tumor

BackgroundIn middle-aged and older men, prostate cancer (PCa) is a common tumor disease with a mortality rate second only to lung cancer. The automatic and accurate segmentation of the prostate and tumor in magnetic resonance imaging (MRI) images can help doctors diagnose malignancies more efficiently. T2 weighted imaging (T2W) is now used in the majority of studies on prostate MRI image segmentation; however, diffusion-weighted imaging (DWI) is more valuable in the diagnosis of PCa. The morphological differences between the prostate and tumor regions are minimal, the tumor size is uncertain, the border between the tumor and surrounding tissue is hazy, and the categories separating normal regions from tumors are uneven. Consequently, it is challenging to segment prostate and tumor on DWI images. MethodsFor the segmentation of prostate and tumor regions on DWI images, this study offers a dual attention-guided 3D convolutional neural network (3D DAG-Net). A visual attention method is built into the encoder step to obtain the features of various receptive fields and deliver more detailed contextual information. A multiscale attention technique is proposed at the decoder stage to fuse multiscale features to acquire finer global and local details. To resolve the class discrepancies between the prostate, tumor, and background regions in segmentation tasks, we propose a hybrid loss function for handling class imbalance. ResultsWe tested the algorithm on DWI images of PCa obtained from a nearby hospital, demonstrating the uniqueness and effectiveness of the method. Dice similarity coefficient (DSC) values for prostate and tumor DWI segmentation were 92.28% and 88.73%, respectively. ConclusionWe present a unique dual-attention mechanism 3D segmentation network architecture for quantitative assessment of prostate and tumor volumes on DWI. The automatic segmentation results produced by our technology were highly correlated and consistent with expert manual segmentation findings.

Reproducibility of apparent diffusion coefficient measurement in normal prostate peripheral zone at 1.5T MRI

PurposeThe purpose of this study was to quantify the influence of factors of variability on apparent diffusion coefficient (ADC) estimation in the normal prostate peripheral zone (PZ). Materials and methodsFifty healthy volunteers underwent in 2017 (n = 17) or 2020 (n = 33) two-point (0, 800 s/mm²) prostate diffusion-weighted imaging in the morning on 1.5 T scanners A and B from different manufacturers. Additional five-point (50, 150, 300, 500, 800 s/mm²) acquisitions were performed on scanner B in the morning and evening. ADC was measured in PZ at midgland using ADC maps reconstructed with various b-value combinations. ADC distributions from 2017 and 2020 were compared using Wilcoxon rank sum test. ADC obtained in the same volunteers were compared using Bland Altman methodology. The 95% confidence interval upper limit of the repeatability/reproducibility coefficient defined the lowest detectable ADC difference. ResultsForty-nine participants with a mean age of 24.6 ± 3.8 [SD] years (range: 21–37 years) were finally included. ADC distributions from 2017 and 2020 were not significantly different and were combined. Despite high individual variability, there was no significant bias (10 × 10−6 mm²/s, P = 0.58) between ADC measurements made on both scanners. On scanner B, differences in lowest b-values chosen within the 0–500 s/mm² range for two-point ADC computation induced significant biases (56-109 × 10−6 mm²/s, P < 0.0001). ADC was significantly lower in the morning (bias: 33 × 10−6 mm²/s, P = 0.006). The number of b-values had little influence on ADC values. The lowest detectable ADC difference varied from 85 × 10−6 to 311 × 10−6 mm²/s across scanners, b-value combinations and periods of the day. ConclusionsThe MRI scanner, the lowest b-value used and the period of the day induce substantial variability in ADC computation.

Read-out Segmented Echo Planar Imaging with Two-Dimensional Navigator Correction (RESOLVE): An Alternative Sequence to Improve Image Quality on Diffusion-Weighted Imaging of Prostate.

We aimed to investigate if the use of read-out segmented echoplanar imaging with additional two-dimensional navigator correction (Readout Segmentation of Long Variable Echo, RESOLVE) for acquiring prostate diffusion-weighted imaging (DWI) improves image quality, compared to single-shot echoplanar imaging (ss-EPI). This single-center prospective study cohort included 162 males with suspected prostate cancer, who underwent 3 Tesla multiparametric MRI (3T-mpMRI). Two abdominal radiologists, blinded to the clinical information, separately reviewed each 3T-mpMRI study to rank geometrical distortion, degree of rectal distention, lesion conspicuity, and anatomic details delineation first on ss-EPI-DWI and later on RESOLVE-DWI using 5-point scales (1 = excellent, 5 = poor). The average of the ranking scores given by two readers was generated and used as the final score. There was good-to-excellent interreader agreement for scoring image quality parameters on both ss-EPI and RESOLVE. Geometrical distortion scores > 3 was seen in 12.3% (20/162) of ss-EPI images, with all having geometrical distortion score <3 on RESOLVE (p < .001). The mean image distortion score was significantly less on RESOLVE than ss-EPI (1.16 vs 1.61, p < .01 regardless of rectal gas, p< .05 when stratified by the degree of rectal distention ). RESOLVE was superior to ss-EPI for lesion conspicuity (mean 1.35 vs 1.53, p< .002) and anatomic delineation (2.60 vs 2.68, p< .001) of prostate on DWI. Compared to conventional ss-EPI, the use of RESOLVE for acquisition of prostate DWI resulted in significantly enhanced image quality and reduced geometrical distortion. RESOLVE could be an alternative or replacement of ss-EPI for acquiring prostate DWI with significantly less geometrical distortion and significantly improved lesion conspicuity and anatomic delineation.

Feasibility of diffusion weighting with a local inside-out nonlinear gradient coil for prostate MRI.

Prostate cancer remains the second leading cancer killer of men, yet it is also a disease with a high rate of overtreatment. Diffusion-weighted imaging (DWI) has shown promise as a reliable, grade-sensitive imaging method, but it is limited by low image quality. Currently, DWI quality image is directly related to low gradient amplitudes, since weak gradients must be compensated with long echo times. We propose a new type of MRI accessory, an "inside-out" and nonlinear gradient, whose sole purpose is to deliver diffusion encoding to a region of interest. Performance was simulated in OPERA and the resulting fields were used to simulate DWI with two-compartment and kurtosis models. Experiments with a nonlinear head gradient prove the accuracy of DWI and apparent diffusion coefficient (ADC) maps encoded with nonlinear gradients. Simulations validated thermal and mechanical safety while showing a 5- to 10-fold increase in gradient strength over prostate. With these strengths, lesion contrast to noise ratio in ADC maps approximately doubled for a range of anatomical positions. Proof-of-principle experiments show that spatially varying b-values can be corrected for accurate DWI and ADC. Dedicated nonlinear diffusion encoding hardware could improve prostate DWI.

Diffusion and quantification of diffusion of prostate cancer.

For assessing a cancer treatment, and for detecting and characterizing cancer, Diffusion-weighted imaging (DWI) is commonly used. The key in DWI's use extracranially has been due to the emergence of of high-gradient amplitude and multichannel coils, parallelimaging, and echo-planar imaging. The benefit has been fewer motion artefacts and high-quality prostate images.Recently, new techniques have been developed to improve the signal-to-noise ratio of DWI with fewer artefacts, allowing an increase in spatial resolution. For apparent diffusion coefficient quantification, non-Gaussian diffusion models have been proposed as additional tools for prostate cancer detection and evaluation of its aggressiveness. More recently, radiomics and machine learning for prostate magnetic resonance imaging have emerged as novel techniques for the non-invasive characterisation of prostate cancer. This review presents recent developments in prostate DWI and discusses its potential use in clinical practice.

Accelerating Prostate Diffusion-weighted MRI Using a Guided Denoising Convolutional Neural Network: Retrospective Feasibility Study

To investigate the feasibility of accelerating prostate diffusion-weighted imaging (DWI) by reducing the number of acquired averages and denoising the resulting image using a proposed guided denoising convolutional neural network (DnCNN). Raw data from the prostate DWI scans were retrospectively gathered between July 2018 and July 2019 from six single-vendor MRI scanners. There were 103 datasets used for training (median age, 64 years; interquartile range [IQR], 11), 15 for validation (median age, 68 years; IQR, 12), and 37 for testing (median age, 64 years; IQR, 12). High b-value diffusion-weighted (hb DW) data were reconstructed into noisy images using two averages and reference images using all 16 averages. A conventional DnCNN was modified into a guided DnCNN, which uses the low b-value DW image as a guidance input. Quantitative and qualitative reader evaluations were performed on the denoised hb DW images. A cumulative link mixed regression model was used to compare the readers' scores. The agreement between the apparent diffusion coefficient (ADC) maps (denoised vs reference) was analyzed using Bland-Altman analysis. Compared with the original DnCNN, the guided DnCNN produced denoised hb DW images with higher peak signal-to-noise ratio (32.79 ± 3.64 [standard deviation] vs 33.74 ± 3.64), higher structural similarity index (0.92 ± 0.05 vs 0.93 ± 0.04), and lower normalized mean square error (3.9% ± 10 vs 1.6% ± 1.5) (P < .001 for all). Compared with the reference images, the denoised images received higher image quality scores from the readers (P < .0001). The ADC values based on the denoised hb DW images were in good agreement with the reference ADC values (mean ADC difference ranged from -0.04 to 0.02 × 10-3 mm2/sec). Accelerating prostate DWI by reducing the number of acquired averages and denoising the resulting image using the proposed guided DnCNN is technically feasible. Supplemental material is available for this article. © RSNA, 2020.

Prostate diffusion MRI with minimal echo time using eddy current nulled convex optimized diffusion encoding.

Prostate diffusion-weighted imaging (DWI) using monopolar encoding is sensitive to eddy-current-induced distortion artifacts. Twice-refocused bipolar encoding suppresses eddy current artifacts, but increases echo time (TE), leading to lower signal-to-noise ratio (SNR). Optimization of the diffusion encoding might improve prostate DWI. To evaluate eddy current nulled convex optimized diffusion encoding (ENCODE) for prostate DWI with minimal TE. Prospective cohort study. A diffusion phantom, an ex vivo prostate specimen, 10 healthy male subjects (27 ± 3 years old), and five prostate cancer patients (62 ± 7 years old). 3T; single-shot spin-echo echoplanar DWI. Eddy-current artifacts, TE, SNR, apparent diffusion coefficient (ADC), and image quality scores from three independent readers were compared between monopolar, bipolar, and ENCODE prostate DWI for standard-resolution (1.6 × 1.6 mm2 , partial Fourier factor [pF] = 6/8) and higher-resolution protocols (1.6 × 1.6 mm2 , pF = off; 1.0 × 1.0 mm2 , pF = 6/8). SNR and ADC differences between techniques were tested with Kruskal-Wallis and Wilcoxon signed-rank tests (P < 0.05 considered significant). Eddy current suppression with ENCODE was comparable to bipolar encoding (mean coefficient of variation across three diffusion directions of 9.4% and 9%). For a standard-resolution protocol, ENCODE achieved similar TE as monopolar and reduced TE by 14 msec compared to bipolar, resulting in 27% and 29% higher mean SNR in prostate transition zone (TZ) and peripheral zone (PZ) (P < 0.05) compared to bipolar, respectively. For higher-resolution protocols, ENCODE achieved the shortest TE (67 msec), with 17-21% and 58-70% higher mean SNR compared to monopolar (TE = 77 msec) and bipolar (TE = 102 msec) in PZ and TZ (P < 0.05). No significant differences were found in mean TZ (P = 0.91) and PZ ADC (P = 0.94) between the three techniques. ENCODE achieved similar or higher image quality scores than bipolar DWI in patients, with mean intraclass correlation coefficient of 0.77 for overall quality between three independent readers. ENCODE minimizes TE (improves SNR) and reduces eddy-current distortion for prostate DWI compared to monopolar and bipolar encoding. 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2020;51:1526-1539.

Improved accuracy of apparent diffusion coefficient quantification using a fully automatic noise bias compensation method: Preliminary evaluation in prostate diffusion weighted imaging.

Noise in diffusion magnetic resonance imaging can introduce bias in apparent diffusion coefficient (ADC) quantification. Previous studies proposed methods that are site-specific techniques as research tools with limited availability and typically require manual intervention, not completely ready to use in the clinical environment. The purpose of this study was to develop a fully automatic computational method to correct noise bias in ADC quantification and perform a preliminary evaluation in the clinical prostate diffusion weighted imaging (DWI). Using a pseudo replica approach for the noise map calculation as well as a direct mapping and a stepwise Chebychev polynomial modelling approach for the ADC fitting, a fully automatic noise-bias-compensated ADC calculation method was proposed and implemented both on the scanner and offline. The proposed method was validated in a computer simulation and a standardized diffusion phantom with ground-truth values. Two in vivo studies were performed to evaluate the proposed method in the clinical environment. The first in vivo study performed acquisitions using a clinically routine prostate DWI protocol on 29 subjects to evaluate the consistency between simulated and empirical results. In the second in vivo study, prostate ADC values of 14 subjects were compared between data acquired with external coils only and reconstructed with the proposed method vs. acquired with external combined with endorectal coils and reconstructed with the conventional method. In statistical analyses, p < 0.05 was regarded as significantly different. In the computer simulation, the proposed method showed smaller error percentage than the other methods and was significantly different (p < 2.2 × 10-16). With low signal-to-noise ratio (SNR), the conventional method underestimated ADC values compared to the ground truth values of the diffusion phantom, while the results of the proposed method were more consistent with the ground truth values. Statistical analyses showed no significant differences between measured and simulated results in the first in vivo study (p = 0.5618). Data from the second in vivo study showed that agreement between ADC measured with external coils only and combined coils was improved for the proposed method (mean bias: 0.04 × 10-3 mm2/s, 95% confidence interval (CI) = [-0.01, 0.09] × 10-3 mm2/s, p = 0.187), compared to the conventional method (mean bias: -0.12 × 10-3 mm2/s, 95% CI = [-0.17, -0.06] × 10-3 mm2/s, p < 0.0001). The proposed method compensates noise bias in low-SNR diffusion-weighted acquisitions and results show improved ADC quantification accuracy in the prostate. This method may be suitable for both clinical imaging and research utilizing ADC quantification.

Quantitative diffusion MRI using reduced field-of-view and multi-shot acquisition techniques: Validation in phantoms and prostate imaging

PurposeTo evaluate the reproducibility of quantitative diffusion measurements obtained with reduced Field of View (rFOV) and Multi-shot EPI (msEPI) acquisitions, using single-shot EPI (ssEPI) as a reference. MethodsDiffusion phantom experiments, and prostate diffusion-weighted imaging in healthy volunteers and patients with known or suspected prostate cancer were performed across the three different sequences. Quantitative diffusion measurements of apparent diffusion coefficient, and diffusion kurtosis parameters (healthy volunteers), were obtained and compared across diffusion sequences (rFOV, msEPI, and ssEPI). Other possible confounding factors like b-value combinations and acquisition parameters were also investigated. ResultsBoth msEPI and rFOV have shown reproducible quantitative diffusion measurements relative to ssEPI; no significant difference in ADC was observed across pulse sequences in the standard diffusion phantom (p = 0.156), healthy volunteers (p ≥ 0.12) or patients (p ≥ 0.26). The ADC values within the non-cancerous central gland and peripheral zone of patients were 1.29 ± 0.17 × 10−3 mm2/s and 1.74 ± 0.23 × 10−3 mm2/s respectively. However, differences in quantitative diffusion parameters were observed across different number of averages for rFOV, and across b-value groups and diffusion models for all the three sequences. ConclusionBoth rFOV and msEPI have the potential to provide high image quality with reproducible quantitative diffusion measurements in prostate diffusion MRI.

Measurement and modeling of diffusion time dependence of apparent diffusion coefficient and fractional anisotropy in prostate tissue ex vivo.

The purpose of this study was to measure and model the diffusion time dependence of apparent diffusion coefficient (ADC) and fractional anisotropy (FA) derived from conventional prostate diffusion-weighted imaging methods as used in recommended multiparametric MRI protocols. Diffusion tensor imaging (DTI) was performed at 9.4T with three radical prostatectomy specimens, with diffusion times in the range 10-120ms and b-values 0-3000s/mm2 . ADC and FA were calculated from DTI measurements at b-values of 800 and 1600s/mm2 . Independently, a two-component model (restricted isotropic plus Gaussian anisotropic) was used to synthesize DTI data, from which ADC and FA were predicted and compared with the measured values. Measured ADC and FA exhibited a diffusion time dependence, which was closely predicted by the two-component model. ADC decreased by about 0.10-0.15μm2 /ms as diffusion time increased from 10 to 120ms. FA increased with diffusion time at b-values of 800 and 1600s/mm2 but was predicted to be independent of diffusion time at b=3000s/mm2 . Both ADC and FA exhibited diffusion time dependence that could be modeled as two unmixed water pools - one having isotropic restricted dynamics, and the other unrestricted anisotropic dynamics. These results highlight the importance of considering and reporting diffusion times in conventional ADC and FA calculations and protocol recommendations, and inform the development of improved diffusion methods for prostate cancer imaging.

Small Field-of-view single-shot EPI-DWI of the prostate: Evaluation of spatially-tailored two-dimensional radiofrequency excitation pulses

PurposeSpatially-tailored (RF) excitation pulses in echo-planar imaging (EPI), combined with a decreased FOV in the phase-encoding direction, enable a reduction of k-space acquisition lines, which shortens the echo train length (ETL) and reduces susceptibility artifacts. The purpose of this study was to evaluate the image quality of a zoomed EPI (z-EPI) sequence in diffusion-weighted imaging (DWI) of the prostate in comparison to a conventional single-shot EPI using single-channel (c-EPI1) and multi-channel (c-EPI2) RF excitation, with and without use of an endorectal coil. Materials and Methods33 consecutive patients (mean age: 61 +/- 9 years; mean PSA: 8.67±6.23 ng/ml) with examinations between 10/2012 and 02/2014 were analyzed in this retrospective study. In 26 of 33 patients the initial multiparametric (mp)-MRI was performed on a whole-body 3T scanner (Magnetom Trio, Siemens, Erlangen, Germany) using an endorectal coil (c (conventional)-EPI1). Zoomed-EPI (Z-EPI) examinations of these patients and a complete mp-MRI protocol including c-EPI2 of 7 additional patients were carried out on another 3T wb MR scanner with two-channel dynamic parallel transmit capability (Magnetom Skyra with TimTX TrueShape, Siemens). For z-EPI, the one-dimensional spatially selective RF excitation pulse was replaced by a two-dimensional RF pulse. Degree of image blur and susceptibility artifacts (0=not present to 3= non-diagnostic), maximum image distortion (mm), apparent diffusion coefficient (ADC) values, as well as overall scan preference were evaluated. SNR maps were generated to compare c-EPI2 and z-EPI. ResultsOverall image quality of z-EPI was preferred by both readers in all examinations with a single exception. Susceptibility artifacts were rated significantly lower on z-EPI compared to both other methods (z-EPI vs c-EPI1: p<0.01; z-EPI vs c-EPI2: p<0.01) as well as image blur (z-EPI vs c-EPI1: p<0.01; z-EPI vs c-EPI2: p<0.01). Image distortion was not statistically significantly reduced with z-EPI (z-EPI vs c-EPI1: p=0.12; z-EPI vs c-EPI2: p=0.42). Interobserver agreement for ratings of susceptibility artifacts, image blur and overall scan preference was good. SNR was higher for z-EPI than for c-EPI1 (n=1). ConclusionZ-EPI leads to significant improvements in image quality and artifacts as well as image blur reduction improving prostate DWI and enabling accurate fusion with conventional sequences. The improved fusion could lead to advantages in the field of MRI-guided biopsy suspicous lesions and performance of locally ablative procedures for prostate cancer.

Improved Ant Colony Algorithm and Application in Sequence Images of Prostate DWI Registration

Because of the drift which exists in sequence image of prostate DWI (Diffusion Weighted Imaging), the global ant colony algorithm is introduced into the paper for registration optimization. The paper introduces an ant colony algorithm for continuous function optimization, based on max-min ant system (MMAS). This paper controls the transition probabilities and enhances the abilities of ants seeking globally optimal solutions by adding an adjustable factor in the basic ant colony algorithm and updating the local pheromone and global pheromone. Experimental results verify the effectiveness of the algorithm.

Evaluation of different mathematical models for diffusion-weighted imaging of normal prostate and prostate cancer using high b-values: a repeatability study.

To evaluate monoexponential, stretched exponential, kurtosis, and biexponential models for diffusion-weighted imaging (DWI) of normal prostate and prostate cancer (PCa), using b-values up to 2000 s/mm(2) , in terms of fitting quality and repeatability. Eight healthy volunteers and 16 PCa patients underwent a total of four repeated 3T DWI examinations using 16 and 12 b-values, respectively. The highest b-value was 2000 s/mm(2) . The normalized mean signal intensities of regions of interest, placed in normal tissue and PCa using anatomical images and prostatectomy sections, were fitted using the four models. The fitting quality was evaluated using Akaike information criteria and F-ratio. Repeatability of the fitted parameters was evaluated using intraclass correlation coefficient ICC(3,1). The biexponential model provided the best fit to normal prostate and PCa DWI data. The parameters of the monoexponential, kurtosis, and stretched exponential (with the exception of the α parameter) models had higher ICC(3,1) values compared with the biexponential model. The kurtosis model provided a better fit to DWI data of normal prostate and PCa than the monoexponential model, whereas these models had comparable reliability and repeatability based on ICC(3,1) values. Considering the model fit and repeatability, the kurtosis model seems to be the preferred model for characterization of normal prostate and PCa DWI using b-values up to 2000 s/mm(2) .

High-resolution diffusion-weighted imaging of the prostate.

The purpose of this study was to evaluate the effect of increasing the spatial resolution of the prostate DWI protocol on image quality and lesion conspicuity. Twenty-nine patients with biopsy-proven prostate cancer undergoing MRI examinations were imaged with two diffusion-weighted imaging (DWI) protocols: current standard clinical protocol (6.7 mm(3) voxels) and a new high-resolution protocol (3.1 mm(3) voxels). Diffusion-weighted images were independently and subjectively scored on lesion conspicuity, internal architecture definition, and overall image quality by two radiologists. Average apparent diffusion coefficient (ADC) values were measured in normal tissue and cancerous lesions on both sequences. Reader scores and ADC and contrast values were compared between the two protocols. Cancer ADC values were correlated with Gleason scores. The signal-to-noise ratio of the new high-resolution DWI protocol was 40% lower than that of the standard protocol. The reader scores were higher by 0.73 (range, 0.29-1.16) grades, or 19% (range, 7-32%), on average, for the new protocol, indicating better image quality. The average ADC values were 8% higher with the new protocol, with ADC contrast values between cancer and normal prostate unchanged. There was marginally significant correlation of cancer ADC values with Gleason scores (p = 0.05, r ≈ -0.36). We showed that for DWI of the prostate at 3-7 mm(3) voxel sizes the benefits of higher spatial resolution outweigh the effects of reduced signal-to-noise and contrast-to-noise ratios, potentially improving the sensitivity to small or sparse prostate cancers. Radiologists can consider using higher-spatial-resolution DWI sequences in their practices.

Zoomed echo-planar imaging using parallel transmission: impact on image quality of diffusion-weighted imaging of the prostate at 3T.

To assess impact of two-channel parallel transmission (pTx) with focused excitation [zoomed echo-planar imaging (EPI)] on image quality of prostate diffusion-weighted imaging (DWI) at 3T. 27 male volunteers (27±8years) underwent 3T prostate MRI using 2-channel radiofrequency-transmit system and 18-channel torso receive coil. Scans included EPI-DWI sequence (b values 50, 500, 1000s/mm(2)) acquired both with standard sinc pulse and 2-channel pTX with focused excitation, each acquired at large-field-of-view (FOV) (20×20cm) and small-FOV (14×14cm). An abdominal radiologist scored b-1000 images and ADC maps for image quality measures. Sequences were compared using paired Wilcoxon tests. pTx with focused excitation showed significant improvements compared with standard DWI on b-1000 images at large-FOV for the absence of wrap and overall image quality (p≤0.049); on b-1000 images at small-FOV for reduced distortion of prostate, absence of ghosting, absence of wrap, clarity of prostate capsule, clarity of peripheral/transition zone boundary, clarity of peri-urethral region, and overall image quality (p≤0.004); and on ADC maps at small-FOV for reduced distortion of prostate, sharpness of prostate, clarity of prostatic capsule, clarity of peri-urethral region, and overall image quality (p=0.002-0.036). When compared with standard large-FOV images, small-FOV images obtained using pTx with focused excitation showed no significant difference on the b-1000 images for any feature (p≥0.175), while showing significant improvements on the ADC maps in terms of reduced distortion, absence of ghosting, and absence of wrap (p=0.010-0.030). Zoomed DWI using 2-channel pTx reduced artifacts and improved image quality for 3T prostate DWI; benefit was most apparent for small-FOV images.

Optimization of b-value distribution for biexponential diffusion-weighted MR imaging of normal prostate

To determine the optimal b-value distribution for biexponential diffusion-weighted imaging (DWI) of normal prostate using both a computer modeling approach and in vivo measurements. Optimal b-value distributions for the fit of three parameters (fast diffusion Df, slow diffusion Ds, and fraction of fast diffusion f) were determined using Monte-Carlo simulations. The optimal b-value distribution was calculated using four individual optimization methods. Eight healthy volunteers underwent four repeated 3 Tesla prostate DWI scans using both 16 equally distributed b-values and an optimized b-value distribution obtained from the simulations. The b-value distributions were compared in terms of measurement reliability and repeatability using Shrout-Fleiss analysis. Using low noise levels, the optimal b-value distribution formed three separate clusters at low (0-400 s/mm2), mid-range (650-1200 s/mm2), and high b-values (1700-2000 s/mm2). Higher noise levels resulted into less pronounced clustering of b-values. The clustered optimized b-value distribution demonstrated better measurement reliability and repeatability in Shrout-Fleiss analysis compared with 16 equally distributed b-values. The optimal b-value distribution was found to be a clustered distribution with b-values concentrated in the low, mid, and high ranges and was shown to improve the estimation quality of biexponential DWI parameters of in vivo experiments.

High-b-Value Diffusion-Weighted Imaging at 3 T to Detect Prostate Cancer: Comparisons Between b Values of 1,000 and 2,000 s/mm2

The objective of our study was to investigate the diagnostic performance of 3-T MRI of the prostate using diffusion-weighted imaging (DWI) with high b values (1,000 and 2,000 s/mm2) and a phased-array coil in predicting localized prostate cancer. Forty-eight patients underwent single-shot echo-planar DWI at 3 T, followed by radical prostatectomy. DWI was performed at high b values of 1,000 and 2,000 s/mm2. Apparent diffusion coefficient (ADC) maps were analyzed by visual and quantitative assessment for tumor and benign tissue in the peripheral and transition zones. The visual and quantitative results of ADC maps obtained at b values of 1,000 and 2,000 s/mm2 were compared with the histopathologic findings. To predict localized prostate cancer, the sensitivity of ADC maps obtained at a b value of 1,000 versus 2,000 s/mm2 was 88% and 71%, respectively, and the accuracy was 89% and 86% (p<0.01). The mean ADC values of tumors in both the peripheral and transition zones were significantly lower than those of benign tissues at both b values of 1,000 and 2,000 s/mm2 (p<0.001). Prostate DWI performed at 3 T using high b values was able to improve differentiation of tumors from benign tissue. DWI performed using a b value of 1,000 s/mm2 was more sensitive and more accurate in predicting localized prostate cancer than DWI performed using a b value of 2,000 s/mm2.

Diffusion-Weighted Imaging of the Prostate at 3 T for Differentiation of Malignant and Benign Tissue in Transition and Peripheral Zones

To evaluate prospectively the use of apparent diffusion coefficients (ADCs) for the differentiation of malignant and benign tissue in the transition (TZ) and peripheral (PZ) zones of the prostate diffusion-weighted imaging (DWI) at 3 T magnetic resonance imaging (MRI) using a phased-array coil. The DWI at 3-T MRI was performed on a total of 35 patients before radical prostatectomy. A single-shot echo-planar imaging DWI technique with b = 0 and b = 1000 s/mm2 was used. The ADC values were measured in both benign and malignant tissues in the PZ and TZ using regions of interest. Differences between PZ and TZ ADC values were estimated using a paired Student t test. Presumed ADC cutoff values in the PZ and TZ for the diagnosis of cancer were assessed by receiver operating characteristic analysis. The ADC values of malignant tissues were significantly lower than those of benign tissues in the PZ and TZ (P < 0.001; 1.32 +/- 0.24 x 10(-3) mm2/s vs 1.97 +/- 0.25 x 10(-3) mm2/s, and 1.37 +/- 0.29 x 10(-3) mm2/s vs 1.79 +/- 0.19 x 10(-3) mm2/s, respectively). For tumor diagnosis, cutoff values of 1.67 x 10(-3) mm2/s (PZ) and 1.61 x 10(-3) mm2/s (TZ) resulted in sensitivities and specificities of 94% and 91% and 90% and 84%, respectively. The DWI of the prostate at 3T MRI using a phased-array coil was useful for the differentiation of malignant and benign tissues in the TZ and PZ.