Diffusion tensor imaging of normal prostate at 3 T: effect of number of diffusion-encoding directions on quantitation and image quality

Acquisition Parameters Influence Diffusion Metrics Effectiveness in Probing Prostate Tumor and Age-Related Microstructure

This study aimed to investigate the Diffusion-Tensor-Imaging (DTI) potential in the detection of microstructural changes in prostate cancer (PCa) in relation to the diffusion weight (b-value) and the associated diffusion length l_D. Thirty-two patients (age range = 50-87 years) with biopsy-proven PCa underwent Diffusion-Weighted-Imaging (DWI) at 3T, using single non-zero b-value or groups of b-values up to b = 2500 s/mm². The DTI maps (mean-diffusivity, MD; fractional-anisotropy, FA; axial and radial diffusivity, D// and D┴), visual quality, and the association between DTI-metrics and Gleason Score (GS) and DTI-metrics and age were discussed in relation to diffusion compartments probed by water molecules at different b-values. DTI-metrics differentiated benign from PCa tissue (p ≤ 0.0005), with the best discriminative power versus GS at b-values ≥ 1500 s/mm², and for b-values range 0-2000 s/mm², when the l_D is comparable to the size of the epithelial compartment. The strongest linear correlations between MD, D//, D┴, and GS were found at b = 2000 s/mm² and for the range 0-2000 s/mm². A positive correlation between DTI parameters and age was found in benign tissue. In conclusion, the use of the b-value range 0-2000 s/mm² and b-value = 2000 s/mm² improves the contrast and discriminative power of DTI with respect to PCa. The sensitivity of DTI parameters to age-related microstructural changes is worth consideration.

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.

Clinical application and progress of quantitative functional magnetic resonance imaging in prostate cancer

Magnetic resonance imaging (MRI) is a very important imaging method for diagnosis and treatment of prostate cancer (PCa) in clinical practice. As functional MRI is growing and maturing, its quantitative parameters are expected to enhance the clinical value of MRI furtherly. Intravoxel incoherent motion diffusion imaging, diffusion tensor imaging, and diffusion kurtosis imaging, which were derived from diffusion weighted imaging, have provided richer and more accurate parameters. The newly-developed magnetic resonance elastography can complement the mechanical characteristics of PCa.

Diffusion Is Directional: Innovative Diffusion Tensor Imaging to Improve Prostate Cancer Detection

In the prostate, water diffusion is faster when moving parallel to duct and gland walls than when moving perpendicular to them, but these data are not currently utilized in multiparametric magnetic resonance imaging (mpMRI) for prostate cancer (PCa) detection. Diffusion tensor imaging (DTI) can quantify the directional diffusion of water in tissue and is applied in brain and breast imaging. Our aim was to determine whether DTI may improve PCa detection. We scanned patients undergoing mpMRI for suspected PCa with a DTI sequence. We calculated diffusion metrics from DTI and diffusion weighted imaging (DWI) for suspected lesions and normal-appearing prostate tissue, using specialized software for DTI analysis, and compared predictive values for PCa in targeted biopsies, performed when clinically indicated. DTI scans were performed on 78 patients, 42 underwent biopsy and 16 were diagnosed with PCa. The median age was 62 (IQR 54.4–68.4), and PSA 4.8 (IQR 1.3–10.7) ng/mL. DTI metrics distinguished PCa lesions from normal tissue. The prime diffusion coefficient (λ₁) was lower in both peripheral-zone (p < 0.0001) and central-gland (p < 0.0001) cancers, compared to normal tissue. DTI had higher negative and positive predictive values than mpMRI to predict PCa (positive predictive value (PPV) 77.8% (58.6–97.0%), negative predictive value (NPV) 91.7% (80.6–100%) vs. PPV 46.7% (28.8–64.5%), NPV 83.3% (62.3–100%)). We conclude from this pilot study that DTI combined with T2-weighted imaging may have the potential to improve PCa detection without requiring contrast injection.

Advanced Diffusion-weighted Imaging Modeling for Prostate Cancer Characterization: Correlation with Quantitative Histopathologic Tumor Tissue Composition-A Hypothesis-generating Study

Purpose To correlate quantitative diffusion-weighted imaging (DWI) parameters derived from conventional monoexponential DWI, stretched exponential DWI, diffusion kurtosis imaging (DKI), and diffusion-tensor imaging (DTI) with quantitative histopathologic tumor tissue composition in prostate cancer in a preliminary hypothesis-generating study. Materials and Methods This retrospective institutional review board-approved study included 24 patients with prostate cancer (mean age, 63 years) who underwent magnetic resonance (MR) imaging, including high-b-value DWI and DTI at 3.0 T, before prostatectomy. The following parameters were calculated in index tumors and nontumoral peripheral zone (PZ): apparent diffusion coefficient (ADC) obtained with monoexponential fit (ADC_ME), ADC obtained with stretched exponential modeling (ADC_SE), anomalous exponent (α) obtained at stretched exponential DWI, ADC obtained with DKI modeling (ADC_DKI), kurtosis with DKI, ADC obtained with DTI (ADC_DTI), and fractional anisotropy (FA) at DTI. Parameters in prostate cancer and PZ were compared by using paired Student t tests. Pearson correlations between tumor DWI and quantitative histologic parameters (nuclear, cytoplasmic, cellular, stromal, luminal fractions) were determined. Results All DWI parameters were significantly different between prostate cancer and PZ (P < .012). ADC_ME, ADC_SE, and ADC_DKI all showed significant negative correlation with cytoplasmic and cellular fractions (r = -0.546 to -0.435; P < .034) and positive correlation with stromal fractions (r = 0.619-0.669; P < .001). ADC_DTI and FA showed correlation only with stromal fraction (r = 0.512 and -0.413, respectively; P < .045). α did not correlate with histologic parameters, whereas kurtosis showed significant correlations with histopathologic parameters (r = 0.487, 0.485, -0.422 for cytoplasmic, cellular, and stromal fractions, respectively; P < .040). Conclusion Advanced DWI methods showed significant correlations with histopathologic tissue composition in prostate cancer. These findings should be validated in a larger study. ^© RSNA, 2017 Online supplemental material is available for this article. An earlier incorrect version of this article appeared online. This article was corrected on November 10, 2017.

Evaluation of Peripheral Zone Prostate Cancer Aggressiveness Using the Ratio of Diffusion Tensor Imaging Measures

Purpose

To evaluate the aggressiveness of peripheral zone prostate cancer by correlating the Gleason score (GS) with the ratio of the diffusion tensor imaging (DTI) measures.

Materials and Methods

Forty-two peripheral zone prostate tumors were imaged using DTI. Regions of interest focusing on the center of tumor foci and noncancerous tissue were used to extract statistical measures of mean diffusivity (MD) and fractional anisotroy (FA). Measure ratio was calculated by dividing tumor measure by noncancerous tissue measure.

Results

Strong correlations are observable between GS and MD measures while weak correlations are present between GS and FA measures. Minimum tumor MD (MD_min) and the ratio of minimum MD (rMD_min) show the same highest correlation with GS (both ρ = −0.73). Between GS ≤ 7 (3 + 4) and GS ≥ 7 (4 + 3), differences are significant for all MD measures but for some FA measures. MD measures perform better than FA measures in discriminating GS ≥ 7 (4 + 3).

Conclusion

Ratios of MD measures can be used in evaluation of peripheral zone prostate cancer aggressiveness; however tumor MD measures alone perform similarly.

Diffusion tensor imaging beyond brains: Applications in abdominal and pelvic organs

Functional magnetic resonance imaging (MRI) provided critical functional information in addition to the anatomic profiles offered by conventional MRI, and has been enormously used in the initial diagnosis and followed evaluation of various diseases. Diffusion tensor imaging (DTI) is a newly developed and advanced technique that measures the diffusion properties including both diffusion motion and its direction in situ, and has been extensively applied in central nerve system with acknowledged success. Technical advances have enabled DTI in abdominal and pelvic organs. Its application is increasing, yet remains less understood. A systematic overview of clinical application of DTI in abdominal and pelvic organs such as liver, pancreas, kidneys, prostate, uterus, etc., is therefore presented. Exploration of techniques with less artifacts and more normative post-processing enabled generally satisfactory image quality and repeatability of measurement. DTI appears to be more valuable in the evaluation of diffused diseases of organs with highly directionally arranged structures, such as the assessment of function impairment of native and transplanted kidneys. However, the utility of DTI to diagnose focal lesions, such as liver mass, pancreatic and prostate tumor, remains limited. Besides, diffusion of different layers of the uterus and the fiber structure disruption can be depicted by DTI. Finally, a discussion of future directions of research is given. The underlying heterogeneous pathologic conditions of certain diseases need to be further differentiated, and it is suggested that DTI parameters might potentially depict certain pathologic characterization such as cell density. Nevertheless, DTI should be better integrated into the current multi-modality evaluation in clinical practice.

Diffusion tensor imaging in abdominal organs

Initially, diffusion tensor imaging (DTI) was mainly applied in studies of the human brain to analyse white matter tracts. As DTI is outstanding for the analysis of tissue´s microstructure, the interest in DTI for the assessment of abdominal tissues has increased continuously in recent years. Tissue characteristics of abdominal organs differ substantially from those of the human brain. Further peculiarities such as respiratory motion and heterogenic tissue composition lead to difficult conditions that have to be overcome in DTI measurements. Thus MR measurement parameters have to be adapted for DTI in abdominal organs. This review article provides information on the technical background of DTI with a focus on abdominal imaging, as well as an overview of clinical studies and application of DTI in different abdominal regions. Copyright © 2015 John Wiley & Sons, Ltd.

Zoomed echo-planar diffusion tensor imaging for MR tractography of the prostate gland neurovascular bundle without an endorectal coil: a feasibility study

PURPOSE

The purpose of this study was to assess the feasibility of zoomed echo-planar imaging (EPI) diffusion tensor imaging (DTI) with 2-channel parallel transmission (pTx) for MR tractography of the periprostatic neurovascular bundle (NVB) without an endorectal coil, and to compare its performance to that of conventionally acquired DTI.

METHODS

8 healthy males (28.9 ± 4.6 years) underwent pelvic phased-array coil prostate MRI on a 3T system using both zoomed-EPI DTI (z-DTI) with 2-channel pTx and conventional single-shot spin-echo EPI DTI (c-DTI) acquisitions with 6 encoding directions and b-values of 0 and 1000 s/mm(2). Fractional anisotropy (FA) maps and tractography analysis incorporating 3D visualization of the NVB were performed from each acquisition. Fiber tract counts, estimated signal-to-noise ratio (eSNR), and image quality measures of the FA maps and NVB tractography were compared. Quantitative and image quality measures were compared using Wilcoxon signed rank tests.

RESULTS

3 of 8 subjects had no tracts detected with c-DTI acquisition, while all 8 had tracts detected with z-DTI. z-DTI acquisition yielded significantly more fiber tracts (c-DTI: 77 ± 116 tracts; z-DTI: 430 ± 228 tracts; p = 0.019) and higher eSNR (c-DTI: 2.9 ± 1.2; z-DTI: 13.17 ± 9.9; p = 0.014). Relative to c-DTI acquisitions, z-DTI FA maps showed significantly reduced artifact (p = 0.008) and reduced anatomic distortion of the prostate (p = 0.010), while z-DTI tractography showed significantly better overall visual quality (p = 0.011), tract symmetry (p = 0.010), tract coherence (p = 0.011), and subjective similarity to the actual NVB (p = 0.011).

CONCLUSION

Zoomed-EPI DTI acquisition for tractography of the prostate gland NVB improves quantitative and qualitative measures of image and tract fiber quality, allowing tractography of the NVB at 3T without using an endorectal coil.

Quantitative study of prostate cancer using three dimensional fiber tractography

AIM: To investigate feasibility of a quantitative study of prostate cancer using three dimensional (3D) fiber tractography.

METHODS: In this institutional review board approved retrospective study, 24 men with biopsy proven prostate cancer underwent prostate magnetic resonance imaging (MRI) with an endorectal coil on a 1.5 T MRI scanner. Single shot echo-planar diffusion weighted images were acquired with b = 0.600 s/mm², six gradient directions. Open-source available software TrackVis and its Diffusion Toolkit were used to generate diffusion tensor imaging (DTI) map and 3D fiber tracts. Multiple 3D spherical regions of interest were drawn over the areas of tumor and healthy prostatic parenchyma to measure tract density, apparent diffusion coefficient (ADC) and fractional anisotropy (FA), which were statistically analyzed.

RESULTS: DTI tractography showed rich fiber tract anatomy with tract heterogeneity. Mean tumor region and normal parenchymal tract densities were 2.53 and 3.37 respectively (P < 0.001). In the tumor, mean ADC was 0.0011 × 10^-3 mm²/s vs 0.0014 × 10^-3 mm²/s in the normal parenchyma (P < 0.001). The FA values for tumor and normal parenchyma were 0.2047 and 0.2259 respectively (P = 0.3819).

CONCLUSION: DTI tractography of the prostate is feasible and depicts congregate fibers within the gland. Tract density may offer new biomarker to distinguish tumor from normal tissue.

Quantitative Imaging in Radiation Oncology: An Emerging Science and Clinical Service

Radiation oncology has long required quantitative imaging approaches for the safe and effective delivery of radiation therapy. The past 10 years has seen a remarkable expansion in the variety of novel imaging signals and analyses that are starting to contribute to the prescription and design of the radiation treatment plan. These include a rapid increase in the use of magnetic resonance imaging, development of contrast-enhanced imaging techniques, integration of fluorinated deoxyglucose-positron emission tomography, evaluation of hypoxia imaging techniques, and numerous others. These are reviewed with an effort to highlight challenges related to quantification and reproducibility. In addition, several of the emerging applications of these imaging approaches are also highlighted. Finally, the growing community of support for establishing quantitative imaging approaches as we move toward clinical evaluation is summarized and the need for a clinical service in support of the clinical science and delivery of care is proposed.

3-T diffusion tensor imaging (DTI) of normal uterus in young and middle-aged females during the menstrual cycle: evaluation of the cyclic changes of fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values

OBJECTIVE

To evaluate cyclic changes of fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values of normal uterus in different age groups during the menstrual cycle, and the correlation with serum female hormone levels.

METHODS

29 normal volunteers accepted diffusion tensor imaging of the uterus on menstrual phase (MP), follicular phase (FP), ovulatory phase (OP) and luteal phase. FA and ADC values of different uterine layers on midsagittal images were measured. Differences between two age groups during the menstrual cycle were evaluated using liner mixed models and one-way analysis of variance. Pearson correlation analysis compared variation of FA and ADC values with serum female hormone levels measured in MP.

RESULTS

During menstrual cycle, endometrial FA values declined, whereas ADC values increased with significant differences (p < 0.05). Serum oestradiol (E) levels correlated moderately with variations of FA values between MP-FP (p = 0.045; r = 0.389) and MP-OP (p = 0.008; r = 0.511). FA and ADC values of junctional zones showed no significant difference (p > 0.05) as well as FA values of myometrium (p = 0.0961), while ADC values of myometrium showed significant increase from menstrual phase to luteal phase (p < 0.05). FA and ADC values of uterine three zonal structures showed significant differences (p < 0.05) at each phase during the menstrual cycle. No significant difference of FA and ADC values was found between age groups (p > 0.05).

CONCLUSION

Dynamic changes of uterine FA and ADC values were observed during menstrual cycle. Variation of FA values between MP-FP, MP-OP correlated moderately with serum E levels.

ADVANCES IN KNOWLEDGE

No publications on the relationship between FA and ADC values and the female hormone levels were found; our study prospectively investigated the cyclic changes of FA and ADC values of the normal uterus and the correlation with the basic serum female hormone levels in MP.

Diffusion-tensor MRI at 3 T: differentiation of central gland prostate cancer from benign prostatic hyperplasia

OBJECTIVE

The purpose of this article is to retrospectively evaluate the utility of diffusion-tensor imaging (DTI) at 3 T in differentiating central gland prostate cancer from benign prostatic hyperplasia (BPH).

MATERIALS AND METHODS

Eighty consecutive patients (57 with central gland cancer and 23 without central gland cancer) were included in this study. All patients underwent T2-weighted imaging and DTI at 3 T, followed by surgery. For predicting central gland cancer, experienced and less-experienced radiologists independently analyzed T2-weighted imaging and combined T2-weighted imaging and DTI, respectively. Apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values were measured for central gland cancers and BPH foci of stromal and glandular hyperplasia. Statistical analyses were performed using McNemar test, linear mixed model, receiver operating characteristic (ROC), and kappa statistics.

RESULTS

For predicting central gland cancers, the area under the curve (Az) of combined T2-weighted imaging and DTI for the experienced (0.915) and less-experienced reader (0.753) was superior to that of T2-weighted imaging (0.723 vs 0.664; p<0.001). The mean ADC and FA values were 0.77×10(-3) mm2/s and 0.35, respectively, for central gland cancers, 1.22×10(-3) mm2/s and 0.26, respectively, for stromal hyperplasia foci, and 1.59×10(-3) mm2/s and 0.21, respectively, for glandular hyperplasia foci, and the values differed significantly. For differentiating central gland cancer from stromal hyperplasia foci and glandular hyperplasia foci, Az values of ADC versus FA were 0.989 and 1.0 versus 0.818 and 0.916, respectively, and the difference was statistically different.

CONCLUSION

DTI at 3 T is useful for distinguishing central gland cancers from BPH foci, with significantly different ADC and FA values. Furthermore, ADC showed greater diagnostic accuracy than FA in differentiating central gland cancers from stromal and glandular hyperplasia foci.

Optimization of the parameters for diffusion tensor magnetic resonance imaging data acquisition for breast fiber tractography at 1.5 T

INTRODUCTION

Diffusion tensor MRI has emerged as a promising tool for the analysis of the microscopic properties of tissues. Optimizing image acquisition parameters is essential for producing high-quality DTI. This study aimed to optimize the parameters for DTI data acquisition for breast fiber tractography at 1.5 T.

PATIENTS AND METHODS

A total of 21 healthy volunteers received breast DTI scanning using an ASSET-based EPI technique operated under different parameters including b value, the number of diffusion gradient directions, and spatial resolution. The images were analyzed for signal-to-noise, signal intensity ratio, mean number and length of reconstructive fiber tracts, and fractional anisotropy value.

RESULTS

The optimal acquisition parameters at 1.5 T for breast DT-MRI fiber tractography were determined as follows: axial 31 direction, b = 600 seconds per mm(2), matrix 128 × 128 with slice thickness of 3 mm.

CONCLUSION

The optimization of data acquisition parameters could improve the quality of breast DT-MRI images and assist fiber tractography at 1.5 T.