Diffusion-weighted magnetic resonance imaging of the prostate: improved robustness with stretched exponential modeling

Influence of Gadolinium-based Contrast Media and Inter-reader Variation on the Estimation of Intravoxel Incoherent Motion (IVIM) Parameters in Breast MR Imaging

PURPOSE

Gadolinium-based contrast media (GBCM) may affect apparent diffusion coefficient measurements on diffusion-weighted imaging. We aimed at investigating the effect of GBCM and inter-reader variation on intravoxel incoherent motion (IVIM) parameters in breast lesions.

METHODS

A total of 89 patients referred to 3T breast MRI with at least one histologically verified lesion were included. IVIM data were acquired using a single-shot echo planar imaging sequence before and after GBCM administration. D (true diffusion coefficient), D* (pseudo-diffusion coefficient) and f (perfusion fraction) were calculated and measured by two readers (R1, R2). Inter-reader and intra-reader agreements were assessed by intraclass correlation coefficients (ICCs) and Bland-Altman plots.

RESULTS

D was comparable before and after GBCM administration and between readers. D* and f decreased after GBCM administration and showed a lower agreement between readers. Intra-reader agreement before and after GBCM administration was almost perfect for D for both R1 and R2 (ICC 0.955 and 0.887). The intra-reader agreement was substantial to moderate for D* (ICC R1 0.708, R2 0.583) and moderate for f (ICC R1 0.529 and R2 0.425). Inter-reader agreement before GBCM administration was almost perfect for D (ICC 0.905), substantial for D* (ICC 0.733), and moderate for f (ICC 0.404); after contrast media administration, it was almost perfect for D (ICC 0.876) and substantial for D* (ICC 0.654) and f (ICC 0.606). Bland-Altman plots revealed no significant bias.

CONCLUSION

Administration of GBCM seems to have a stronger effect on D* and f values than on D values. This should be considered when applying IVIM in clinical practice.

Intravoxel incoherent motion magnetic resonance imaging to assess early tumor response to radiation therapy: Review and future directions

Early prediction of radiation response by imaging is a dynamic field of research and it can be obtained using a variety of noninvasive magnetic resonance imaging methods. Recently, intravoxel incoherent motion (IVIM) has gained interest in cancer imaging. IVIM carries both diffusion and perfusion information, making it a promising tool to assess tumor response. Here, we briefly introduced the basics of IVIM, reviewed existing studies of IVIM in various type of tumors during radiotherapy in order to show whether IVIM is a useful technique for an early assessment of radiation response. 31/40 studies reported an increase of IVIM parameters during radiotherapy compared to baseline. In 27 studies, this increase was higher in patients with good response to radiotherapy. Future directions including implementation of IVIM on MR-Linac and its limitation are discussed. Obtaining new radiologic biomarkers of radiotherapy response could open the way for a more personalized, biology-guided radiation therapy.

Identification of the Benignity and Malignancy of BI-RADS 4 Breast Lesions Based on a Combined Quantitative Model of Dynamic Contrast-Enhanced MRI and Intravoxel Incoherent Motion

The aim of this study was to explore whether intravoxel incoherent motion (IVIM) combined with a dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) quantitative model can improve the ability to distinguish between benign and malignant BI-RADS 4 breast lesions. We enrolled 100 patients who underwent breast MRI at our institution and extracted the quantitative parameters of lesions with a post-processing workstation. Statistical differences in these parameters between benign and malignant BI-RADS 4 lesions were assessed using a two independent samples t-test or a Mann-Whitney U test. Binary logistic regression analysis was performed to establish five diagnostic models (model_{_ADC}, model_{_IVIM}, model_{_DCE}, model_{_DCE+ADC}, and model_{_DCE+IVIM}). Receiver operating characteristic (ROC) curves, leave-one-out cross-validation, and the Delong test were used to assess and compare the diagnostic performance of these models. The model_{_DCE+IVIM} showed the highest area under the curve (AUC) of 0.903 (95% confidence interval (CI): 0.828-0.953, sensitivity: 87.50%, specificity: 85.00%), which was significantly higher than that of model_{_ADC} (p = 0.014) and model_{_IVIM} (p = 0.033). The model_{_ADC} had the lowest diagnostic performance (AUC = 0.768, 95%CI: 0.672-0.846) but was not significantly different from model_{_IVIM} (p = 0.168). The united quantitative model with DCE-MRI and IVIM could improve the ability to evaluate the malignancy in BI-RADS 4 lesions, and unnecessary breast biopsies may be obviated.

Evaluation of Monoexponential, Stretched-Exponential and Intravoxel Incoherent Motion MRI Diffusion Models in Early Response Monitoring to Neoadjuvant Chemotherapy in Patients With Breast Cancer-A Preliminary Study

BACKGROUND

There has been a growing interest in exploring the applications of stretched-exponential (SEM) and intravoxel incoherent motion (IVIM) models of diffusion-weighted imaging (DWI) in breast imaging, with the focus on differentiation of breast lesions. However, the use of SEM and IVIM models to predict early response to neoadjuvant chemotherapy (NACT) has received less attention.

PURPOSE

To investigate the value of monoexponential, SEM, and IVIM models to predict early response to NACT in patients with primary breast cancer.

STUDY TYPE

Prospective.

POPULATION

Thirty-seven patients with primary breast cancer (aged 46 ± 11 years) due to undergo NACT.

FIELD STRENGTH/SEQUENCES

A 1.5-T MR scanner, T1 -weighted three-dimensional spoiled gradient-echo, two-dimensional single-shot spin-echo echo-planar imaging sequence (DWI) at six b-values (0-800 s mm-2 ).

ASSESSMENT

Tumor volume, apparent diffusion coefficient, tissue diffusion (Dt ), pseudo-diffusion coefficient (Dp ), perfusion fraction (f), distributed diffusion coefficient, and alpha (α) were extracted, following volumetric sampling of the tumors, at three time-points: pretreatment, post one and three cycles of NACT.

STATISTICAL TESTS

Mann-Whitney test, receiver operating characteristic (ROC) curve. Statistical significance level was P < 0.05.

RESULTS

Following NACT, 17 patients were determined to be pathological responders and 20 nonresponders. Tumor volume was significantly larger in nonresponders at each MRI time-point and demonstrated reasonable performance in predicting response (area under the ROC curve [AUC] = 0.83-0.87). No significant differences between groups were found in the diffusion coefficients at each time-point (P = 0.09-1). The parameters α (SEM), f, and f × Dp (IVIM) were able to differentiate between response groups after one cycle of NACT (AUC = 0.73, 0.72, and 0.74, respectively).

CONCLUSION

Diffusion coefficients derived from the monoexponential, SEM, and IVIM models did not predict pathological response. However, the IVIM-derived parameters f and f × Dp and the SEM-derived parameter α were able to predict response to NACT in breast cancer patients following one cycle of NACT.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY STAGE: 2.

A comparative study of four diffusion-weighted imaging models in the diagnosis of cervical cancer

BACKGROUND

Most commonly used diffusion-weighted imaging (DWI) models include intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), stretched exponential model (SEM), and mono-exponential model (MEM). Previous studies of the four models were inconsistent on which model was more effective in distinguishing cervical cancer from normal cervical tissue.

PURPOSE

To assess the performance of four DWI models in characterizing cervical cancer and normal cervical tissue.

MATERIAL AND METHODS

Forty-seven women with suspected cervical carcinoma underwent DWI using eight b-values before treatment. Imaging parameters, calculated using IVIM, SEM, DKI, and MEM, were compared between cervical cancer and normal cervical tissue. The diagnostic performance of the models was evaluated using independent t-test, Mann-Whitney U test, receiver operating characteristic (ROC) curve analysis, and multivariate logistic regression analysis.

RESULTS

All parameters except pseudo-diffusion coefficient (D*) differed significantly between cervical cancer and normal cervical tissue (P < 0.001). Through logistic regression analysis, all combined models showed a significant improvement in area under the ROC curve (AUC) compared to individual DWI parameters. The model with combined IVIM parameters had a larger AUC value compared to those of other combined models (P < 0.05).

CONCLUSION

All four DWI models are useful for differentiating cervical cancer from normal cervical tissue and IVIM may be the optimal model.

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.

Intravoxel Incoherent Motion Magnetic Resonance Imaging in Skeletal Muscle: Review and Future Directions

Throughout the body, muscle structure and function can be interrogated using a variety of noninvasive magnetic resonance imaging (MRI) methods. Recently, intravoxel incoherent motion (IVIM) MRI has gained momentum as a method to evaluate components of blood flow and tissue diffusion simultaneously. Much of the prior research has focused on highly vascularized organs, including the brain, kidney, and liver. Unique aspects of skeletal muscle, including the relatively low perfusion at rest and large dynamic range of perfusion between resting and maximal hyperemic states, may influence the acquisition, postprocessing, and interpretation of IVIM data. Here, we introduce several of those unique features of skeletal muscle; review existing studies of IVIM in skeletal muscle at rest, in response to exercise, and in disease states; and consider possible confounds that should be addressed for muscle-specific evaluations. Most studies used segmented nonlinear least squares fitting with a b-value threshold of 200 sec/mm² to obtain IVIM parameters of perfusion fraction (f), pseudo-diffusion coefficient (D*), and diffusion coefficient (D). In healthy individuals, across all muscles, the average ± standard deviation of D was 1.46 ± 0.30 × 10^-3  mm² /sec, D* was 29.7 ± 38.1 × 10^-3  mm² /sec, and f was 11.1 ± 6.7%. Comparisons of reported IVIM parameters in muscles of the back, thigh, and leg of healthy individuals showed no significant difference between anatomic locations. Throughout the body, exercise elicited a positive change of all IVIM parameters. Future directions including advanced postprocessing models and potential sequence modifications are discussed. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

Distinguishing between benign and malignant breast lesions using diffusion weighted imaging and intravoxel incoherent motion: A systematic review and meta-analysis

PURPOSE

We sought to evaluate the diagnostic performance of diffusion weighted imaging (DWI) and intravoxel incoherent motion (IVIM) for distinguishing between benign and malignant breast tumors by performing a meta-analysis.

METHODS

We comprehensively searched the electronic databases PubMed and Embase from January 2000 to April 2020 for studies in English. Studies were included if they reported the sensitivity and specificity for identifying benign and malignant breast lesions using DWI or IVIM. Studies were reviewed according to QUADAS-2. The data inhomogeneity and publication bias were also assessed. In order to explore the influence of different field strengths and different b values on diagnostic efficiency, we conducted subgroup analysis.

RESULTS

We analyzed 79 studies, which included a total of 6294 patients with 4091 malignant lesions and 2793 benign lesions. Overall, the pooled sensitivity and specificity of ADC for detecting malignant breast tumors were 0.87 (0.86-0.88) and 0.80 (0.78-0.81), respectively. The PLR was 5.09 (4.16-6.24); the NLR was 0.15 (0.13-0.18); and the DOR was 38.95 (28.87-52.54). The AUC value was 0.9297. The highest performing parameter for IVIM was tissue diffusivity (D), and the pooled sensitivity and specificity was 0.85 (0.82-0.88) and 0.87(0.83-0.90), respectively; the PLR was 5.65 (3.91-8.18); the NLR was 0.17 (0.12-0.26); and the DOR was 38.44 (23.57-62.69). The AUC value was 0.9265. Most of parameters demonstrated considerable statistically significant heterogeneity (P < 0.05, I²>50 %) except the pooled DOR, PLR of D and the pooled DOR and NLR of D*.

CONCLUSIONS

Our meta-analysis indicated that DWI and IVIM had high sensitivity and specificity in the differential diagnosis of breast lesions; and compared with DWI, IVIM could not further increase the diagnostic performance. There was no significant difference in diagnostic accuracy.

Parsimonious modeling of skeletal muscle perfusion: Connecting the stretched exponential and fractional Fickian diffusion

PURPOSE

To develop an anomalous (non-Gaussian) diffusion model for characterizing skeletal muscle perfusion using multi-b-value DWI.

THEORY AND METHODS

Fick's first law was extended for describing tissue perfusion as anomalous superdiffusion, which is non-Gaussian diffusion exhibiting greater particle spread than that of the Gaussian case. This was accomplished using a space-fractional derivative that gives rise to a power-law relationship between mean squared displacement and time, and produces a stretched exponential signal decay as a function of b-value. Numerical simulations were used to estimate parameter errors under in vivo conditions, and examine the effect of limited SNR and residual fat signal. Stretched exponential DWI parameters, α and D , were measured in thigh muscles of 4 healthy volunteers at rest and following in-magnet exercise. These parameters were related to a stable distribution of jump-length probabilities and used to estimate microvascular volume fractions.

RESULTS

Numerical simulations showed low dispersion in parameter estimates within 1.5% and 1%, and bias errors within 3% and 10%, for α and D , respectively. Superdiffusion was observed in resting muscle, and to a greater degree following exercise. Resting microvascular volume fraction was between 0.0067 and 0.0139 and increased between 2.2-fold and 4.7-fold following exercise.

CONCLUSIONS

This model captures superdiffusive molecular motions consistent with perfusion, using a parsimonious representation of the DWI signal, providing approximations of microvascular volume fraction comparable with histological estimates. This signal model demonstrates low parameter-estimation errors, and therefore holds potential for a wide range of applications in skeletal muscle and elsewhere in the body.

Quantitative study of preoperative staging of gastric cancer using intravoxel incoherent motion diffusion-weighted imaging as a potential clinical index

PURPOSE

To determine the utility of intravoxel incoherent motion (IVIM) diffusion-weighted imaging in quantitative analysis of preoperative tumor (T) and node (N) stages of gastric cancer, and to quantify the diagnostic threshold of IVIM parameters for serosal invasion and lymphatic metastasis.

MATERIALS AND METHODS

From October 2016 to February 2020, 98 patients with gastric cancer who were receiving treatment in Zhongshan Hospital, China, were subject to an IVIM sequence imaging analysis. The IVIM sequence data were imported into software for post-processing of tumor regions of interest, and the IVIM parameters (the microvascular volume fraction (f), the molecular diffusion coefficient (D) and perfusion-related incoherent microcirculation (D*) were calculated. The variation of these IVIM parameters with different tumor-node metastasis (TNM) stages were analyzed by one-way analysis of variance. The IVIM parameters of serosal invasion and lymphatic metastasis were examined by receiver operating characteristic curve analysis and t-tests.

RESULTS

A total of 98 gastric cancer patients (65 males and 33 females) with an average age of 61.9 years were enrolled in this study. There were 14 patients in stage T1, 14 in stage T2, 10 in stage T3 and 60 in stage T4_a+b. There were 37 patients in stage N0, 19 in stage N1, 18 in stage N2 and 24 in stage N3. Statistically significant associations were found between the D values and T stages of gastric cancer. The D values of stage T4 cancers were significantly different from those of stage T2, T3 and T4 cancers. The D value decreased with increasing T stage. The mean D values of stages were 1.432 × 10^-3 mm²/s (T1), 1.225 × 10^-3 mm²/s (T2), 1.154 × 10^-3 mm²/s (T3) and 0.9468 × 10^-3 mm²/s (T4). The extent of the invasion of serosa was found to be significantly correlated with D value, with the diagnostic threshold for D being 1.107 × 10^-3 mm²/s. In addition, different pathological N stages of gastric cancer lesions showed statistically significantly variations in f values, but no correlation was found with different N stages. Finally, the extent of lymphatic metastasis was found to be correlated with D values, with the diagnostic threshold being 1.1739 × 10^-3 mm²/s. There was no statistically significant correlation between the IVIM MRI parameters and tumor size. The grade of tumor was found to be significantly correlated with D* value, with the diagnostic threshold for D* being 1.516 × 10^-2 mm²/s. There was no statistically significant correlation between the ADC value and tumor size. There was a significant difference in the ADC values among different T and N stage cancers. ADC value had statistically significant to distinguish gastric cancer with or without serosal invasion, its detection efficiency was not as high as that of D value, with an AUC of 0.628 and 0.830, respectively. The ADC value was not statistically significant in distinguishing gastric cancer with or without lymphatic metastasis (P ≥ 0.05). The ADC value had not statistically significant in distinguishing gastric cancer between low and medium-high grade (P ≥ 0.05).

CONCLUSION

We found that significant differences existed between whole-volume IVIM parameters of different T or N stages in gastric cancers, and were able to quantify different T or N stages of gastric cancer by the values of these parameters. The results of this quantitative study provide new tools for evaluating the prognosis of gastric cancer and will be valuable for the development of an new imaging method for determining the morphological stages of gastric cancer.

Differentiation of high-grade from low-grade diffuse gliomas using diffusion-weighted imaging: a comparative study of mono-, bi-, and stretched-exponential diffusion models

Purpose

Diffusion-weighted imaging (DWI) plays an important role in the preoperative assessment of gliomas; however, the diagnostic performance of histogram-derived parameters from mono-, bi-, and stretched-exponential DWI models in the grading of gliomas has not been fully investigated. Therefore, we compared these models’ ability to differentiate between high-grade and low-grade gliomas.

Methods

This retrospective study included 22 patients with diffuse gliomas (age, 23–74 years; 12 males; 11 high-grade and 11 low-grade gliomas) who underwent preoperative 3 T-magnetic resonance imaging from October 2014 to August 2019. The apparent diffusion coefficient was calculated from the mono-exponential model. Using 13 b-values, the true-diffusion coefficient, pseudo-diffusion coefficient, and perfusion fraction were obtained from the bi-exponential model, and the distributed-diffusion coefficient and heterogeneity index were obtained from the stretched-exponential model. Region-of-interests were drawn on each imaging parameter map for subsequent histogram analyses.

Results

The skewness of the apparent diffusion, true-diffusion, and distributed-diffusion coefficients was significantly higher in high-grade than in low-grade gliomas (0.67 ± 0.67 vs. − 0.18 ± 0.63, 0.68 ± 0.74 vs. − 0.08 ± 0.66, 0.63 ± 0.72 vs. − 0.15 ± 0.73; P = 0.0066, 0.0192, and 0.0128, respectively). The 10th percentile of the heterogeneity index was significantly lower (0.77 ± 0.08 vs. 0.88 ± 0.04; P = 0.0004), and the 90th percentile of the perfusion fraction was significantly higher (12.64 ± 3.44 vs. 7.14 ± 1.70%: P < 0.0001), in high-grade than in low-grade gliomas. The combination of the 10th percentile of the true-diffusion coefficient and 90th percentile of the perfusion fraction showed the best area under the receiver operating characteristic curve (0.96).

Conclusion

The bi-exponential model exhibited the best diagnostic performance for differentiating high-grade from low-grade gliomas.

Electronic supplementary material

The online version of this article (10.1007/s00234-020-02456-2) contains supplementary material, which is available to authorized users.

Synthetic Apparent Diffusion Coefficient for High b-Value Diffusion-Weighted MRI in Prostate

Purpose

It has been reported that diffusion-weighted imaging (DWI) with ultrahigh b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher Materials and Methods. Fifteen patients (7 malignant and 8 benign) were included in this study retrospectively with the institutional ethical committee approval. All images were acquired at a 3T MR scanner. The ADC values were calculated using a monoexponential model. Synthetic ADC (sADC) for higher b-value increases the diagnostic power of prostate cancer. DWI with higher

Results

No significant difference was observed between actual ADC and sADC for b-value increases the diagnostic power of prostate cancer. DWI with higher p=0.002, paired t-test) in sDWI as compared to DWI. Malignant lesions showed significantly lower sADC as compared to benign lesions (p=0.002, paired t-test) in sDWI as compared to DWI. Malignant lesions showed significantly lower sADC as compared to benign lesions (Discussion/

Conclusion

Our initial investigation suggests that the ADC values corresponding to higher b-value can be computed using log-linear relationship derived from lower b-values (b ≤ 1000). Our method might help clinicians to decide the optimal b-value for prostate lesion identification.b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher

Breast Tumor Detection and Classification Using Intravoxel Incoherent Motion Hyperspectral Imaging Techniques

Breast cancer is a main cause of disease and death for women globally. Because of the limitations of traditional mammography and ultrasonography, magnetic resonance imaging (MRI) has gradually become an important radiological method for breast cancer assessment over the past decades. MRI is free of the problems related to radiation exposure and provides excellent image resolution and contrast. However, a disadvantage is the injection of contrast agent, which is toxic for some patients (such as patients with chronic renal disease or pregnant and lactating women). Recent findings of gadolinium deposits in the brain are also a concern. To address these issues, this paper develops an intravoxel incoherent motion- (IVIM-) MRI-based histogram analysis approach, which takes advantage of several hyperspectral techniques, such as the band expansion process (BEP), to expand a multispectral image to hyperspectral images and create an automatic target generation process (ATGP). After automatically finding suspected targets, further detection was attained by using kernel constrained energy minimization (KCEM). A decision tree and histogram analysis were applied to classify breast tissue via quantitative analysis for detected lesions, which were used to distinguish between three categories of breast tissue: malignant tumors (i.e., central and peripheral zone), cysts, and normal breast tissues. The experimental results demonstrated that the proposed IVIM-MRI-based histogram analysis approach can effectively differentiate between these three breast tissue types.

VERDICT MRI for Prostate Cancer: Intracellular Volume Fraction versus Apparent Diffusion Coefficient

Background Biologic specificity of diffusion MRI in relation to prostate cancer aggressiveness may improve by examining separate components of the diffusion MRI signal. The Vascular, Extracellular, and Restricted Diffusion for Cytometry in Tumors (VERDICT) model estimates three distinct signal components and associates them to (a) intracellular water, (b) water in the extracellular extravascular space, and (c) water in the microvasculature. Purpose To evaluate the repeatability, image quality, and diagnostic utility of intracellular volume fraction (FIC) maps obtained with VERDICT prostate MRI and to compare those maps with apparent diffusion coefficient (ADC) maps for Gleason grade differentiation. Materials and Methods Seventy men (median age, 62.2 years; range, 49.5-82.0 years) suspected of having prostate cancer or undergoing active surveillance were recruited to a prospective study between April 2016 and October 2017. All men underwent multiparametric prostate and VERDICT MRI. Forty-two of the 70 men (median age, 67.7 years; range, 50.0-82.0 years) underwent two VERDICT MRI acquisitions to assess repeatability of FIC measurements obtained with VERDICT MRI. Repeatability was measured with use of intraclass correlation coefficients (ICCs). The image quality of FIC and ADC maps was independently evaluated by two board-certified radiologists. Forty-two men (median age, 64.8 years; range, 49.5-79.6 years) underwent targeted biopsy, which enabled comparison of FIC and ADC metrics in the differentiation between Gleason grades. Results VERDICT MRI FIC demonstrated ICCs of 0.87-0.95. There was no significant difference between image quality of ADC and FIC maps (score, 3.1 vs 3.3, respectively; P = .90). FIC was higher in lesions with a Gleason grade of at least 3+4 compared with benign and/or Gleason grade 3+3 lesions (mean, 0.49 ± 0.17 vs 0.31 ± 0.12, respectively; P = .002). The difference in ADC between these groups did not reach statistical significance (mean, 1.42 vs 1.16 × 10-3 mm2/sec; P = .26). Conclusion Fractional intracellular volume demonstrates high repeatability and image quality and enables better differentiation of a Gleason 4 component cancer from benign and/or Gleason 3+3 histology than apparent diffusion coefficient. Published under a CC BY 4.0 license. Online supplemental material is available for this article. See also the editorial by Sigmund and Rosenkrantz in this issue.

Monoexponential, Biexponential, and stretched-exponential models using diffusion-weighted imaging: A quantitative differentiation of breast lesions at 3.0T

BACKGROUND

Diffusion-weighted imaging (DWI) plays an important role in the differentiation of malignant and benign breast lesions.

PURPOSE

To investigate the utility of various diffusion parameters obtained from monoexponential, biexponential, and stretched-exponential DWI models in the differential diagnosis of breast lesions.

STUDY TYPE

Prospective.

POPULATION

Sixty-one patients (age range: 25-68 years old; mean age: 46 years old) with 31 malignant lesions, 42 benign lesions, and 28 normal breast tissues diagnosed initially by clinical palpation, ultrasonography, or conventional mammography were enrolled in the study from January to September 2016.

FIELD STRENGTH

3.0T MR scanner, T₁ WI, T₂ WI, DWI (conventional and multi-b values), dynamic contrast-enhanced.

ASSESSMENT

The apparent diffusion coefficient (ADC) was calculated by monoexponential analysis. The diffusion coefficient (ADC_slow ), pseudodiffusion coefficient (ADC_fast ), and perfusion fraction (f) were calculated using the biexponential model. The distributed diffusion coefficient (DDC) and water molecular diffusion heterogeneity index (α) were obtained using a stretched-exponential model. All parameters were compared for malignant tumors, benign tumors, and normal breast tissues. A receiver operating characteristic curve was used to compare the ability of these parameters, in order to differentiate benign and malignant breast lesions.

STATISTICAL TESTS

All statistical analyses were performed using statistical software (SPSS).

RESULTS

ADC, ADC_slow , f, DDC, and α values were significantly lower in malignant tumors when compared with normal breast tissues and benign tumors (P < 0.05). However, ADC and f had higher area under the receiver operating characteristic curve (AUC) values (0.889 and 0.919, respectively).

DATA CONCLUSION

The parameters derived from the biexponential and stretched-exponential DWI could provide additional information for differentiating between benign and malignant breast tumors when compared with conventional diffusion parameters.

LEVEL OF EVIDENCE

4 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2019;50:1461-1467.

Comparison of the Diagnostic Value of Monoexponential, Biexponential, and Stretched Exponential Diffusion-weighted MRI in Differentiating Tumor Stage and Histological Grade of Bladder Cancer

RATIONALE AND OBJECTIVES

We aimed to determine the utility of various diffusion parameters obtained from monoexponential, biexponential, and stretched exponential diffusion-weighted imaging (DWI) models in differentiating tumor stage and grade of bladder cancer.

MATERIALS AND METHODS

Forty-five patients with pathologically confirmed bladder cancer underwent multi-b-value DWI. An apparent diffusion coefficient (ADC) was calculated from DWI by using a monoexponential model. A true diffusion coefficient (D), perfusion-related pseudo-diffusion coefficient (D*), and perfusion fraction (f) were calculated from DWI by using a biexponential model. A water molecular diffusion heterogeneity index (α) and distributed diffusion coefficient (DDC) were calculated from DWI by using a stretched exponential model. All parameters were compared between different stages and grades by using the Mann-Whitney U test. Receiver operating characteristic and intrareader correlation coefficient analysis were used for statistical evaluations.

RESULTS

ADC, D, f, and DDC values were significantly higher in the non-muscle-invasive vs muscle-invasive bladder cancers (P = .000, .000, .002, and .000, respectively) and in low-grade vs high-grade ones (P = .000, .000, .018, and .000, respectively). D* value was significantly lower in the low-grade bladder cancers compared to high-grade ones (P = .012). The areas under the receiver operating characteristic curve of ADC, D, and DDC values were 0.945, 0.912, and 0.946 in staging bladder cancers; 0.866, 0.862, and 0.856 in grading bladder cancers, respectively.

CONCLUSION

Biexponential and stretched exponential DWI models may provide more parameters in staging and grading bladder cancers and show a slight difference between DDC and ADC values in staging bladder cancers. These two DWI models, as well as the monoexponential models, were very helpful in staging and grading bladder cancers.

Feasibility of Intravoxel Incoherent Motion for Differentiating Benign and Malignant Thyroid Nodules

RATIONALE AND OBJECTIVES

This study aimed to preliminarily investigate the feasibility of intravoxel incoherent motion (IVIM) theory in the differential diagnosis of benign and malignant thyroid nodules.

MATERIALS AND METHODS

Forty-five patients with 56 confirmed thyroid nodules underwent preoperative routine magnetic resonance imaging and IVIM diffusion-weighted imaging. The histopathologic diagnosis was confirmed by surgery. Apparent diffusion coefficient (ADC), perfusion fraction f, diffusivity D, and pseudo-diffusivity D* were quantified. Independent samples t test of IVIM-derived metrics were conducted between benign and malignant nodules. Receiver-operating characteristic analyses were performed to determine the optimal thresholds as well as the sensitivity and specificity for differentiating.

RESULTS

Significant intergroup difference was observed in ADC, D, D*, and f (p < 0.001). Malignant tumors featured significantly lower ADC, D and D* values and a higher f value than that of benign nodules. The ADC, D, and D* could distinguish the benign from malignant thyroid nodules, and parameter f differentiate the malignant tumors from benign nodules. The values of the area under the curve for parameter ADC, D, and D* were 0.784 (p = 0.001), 0.795 (p = 0.001), and 0.850 (p < 0.001), separately, of which the area under the curve of f value was the maximum for identifying the malignant from benign nodules, which was 0.841 (p < 0.001).

CONCLUSION

This study suggested that ADC and IVIM-derived metrics, including D, D*, and f, could potentially serve as noninvasive predictors for the preoperative differentiating of thyroid nodules, and f value performed best in identifying the malignant from benign nodules among these parameters.

Abdominal organ perfusion and inflammation in experimental sepsis: a magnetic resonance imaging study

Diffusion-weighted magnetic resonance imaging (DW-MRI) uses water as contrast and enables the study of perfusion in many organs simultaneously in situ. We used DW-MRI in a hypodynamic sepsis model, comparing abdominal organ perfusion with global hemodynamic measurements and inflammation. Sixteen anesthetized piglets were randomized into 3 groups: 2 intervention (sepsis) groups: HighMAP (mean arterial pressure, MAP > 65 mmHg) and LowMAP (MAP between 50 and 60 mmHg), and a Healthy Control group (HC). Sepsis was obtained with endotoxin and the desired MAP maintained with norepinephrine. After 6 h, DW-MRI was performed. Acute inflammation was assessed with IL-6 and TNFα in abdominal organs, ascites, and blood and by histology of intestine (duodenum). Perfusion of abdominal organs was reduced in the LowMAP group compared with the HighMAP group and HC. Liver perfusion was still reduced by 25% in the HighMAP group compared with HC. Intestinal perfusion did not differ significantly between the intervention groups. Cytokine concentrations were generally higher in the LowMAP group but did not correlate with global hemodynamics. However, cytokines correlated with regional perfusion and, for liver and intestine, also with intra-abdominal pressure. Histopathology of intestine worsened with decreasing perfusion. In conclusion, although a low MAP (≤60 mmHg) indicated impeded abdominal perfusion in experimental sepsis, it did not predict inflammation, nor did other global measures of circulation. Decreased abdominal perfusion partially predicted inflammation but intestine, occupying most of the abdomen, and liver were also affected by intra-abdominal pressure. NEW & NOTEWORTHY The study increases the knowledge of abdominal perfusion during sepsis. We used diffusion weighted imaging to assess perfusion simultaneously and noninvasively in different abdominal organs. The technique has not been used in a sepsis model before. Cytokine concentrations were measured in different abdominal organs and vascular beds and related to regional perfusion. Decreased abdominal perfusion, but not global measures of circulation, predicted inflammation. Intestine, occupying most of the abdomen, and liver were also affected by intra-abdominal pressure.

Diffusion MRI of cancer: From low to high b-values

Following its success in early detection of cerebral ischemia, diffusion-weighted imaging (DWI) has been increasingly used in cancer diagnosis and treatment evaluation. These applications are propelled by the rapid development of novel diffusion models to extract biologically valuable information from diffusion-weighted MR signals, and significant advances in MR hardware that has enabled image acquisition with high b-values. This article reviews recent technical developments and clinical applications in cancer imaging using DWI, with a special emphasis on high b-value diffusion models. The article is organized in four sections. First, we provide an overview of diffusion models that are relevant to cancer imaging. The model parameters are discussed in relation to three tissue properties-cellularity, vascularity, and microstructures. An emphasis is placed on characterization of microstructural heterogeneity, given its novelty and close relevance to cancer. Second, we illustrate diffusion MR clinical applications in each of the following three categories: 1) cancer detection and diagnosis; 2) cancer grading, staging, and classification; and 3) cancer treatment response prediction and evaluation. Third, we discuss several practical issues, including selection of image acquisition parameters, reproducibility and reliability, motion management, image distortion, etc., that are commonly encountered when applying DWI to cancer in clinical settings. Lastly, we highlight a few ongoing challenges and provide some possible future directions, particularly in the area of establishing standards via well-organized multicenter clinical trials to accelerate clinical translation of advanced DWI techniques to improving cancer care on a large scale. Level of Evidence: 5 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:23-40.

Characterization of prostate microstructure using water diffusion and NMR relaxation

For many pathologies, early structural tissue changes occur at the cellular level, on the scale of micrometers or tens of micrometers. Magnetic resonance imaging (MRI) is a powerful non-invasive imaging tool used for medical diagnosis, but its clinical hardware is incapable of reaching the cellular length scale directly. In spite of this limitation, microscopic tissue changes in pathology can potentially be captured indirectly, from macroscopic imaging characteristics, by studying water diffusion. Here we focus on water diffusion and NMR relaxation in the human prostate, a highly heterogeneous organ at the cellular level. We present a physical picture of water diffusion and NMR relaxation in the prostate tissue, that is comprised of a densely-packed cellular compartment (composed of stroma and epithelium), and a luminal compartment with almost unrestricted water diffusion. Transverse NMR relaxation is used to identify fast and slow T ₂ components, corresponding to these tissue compartments, and to disentangle the luminal and cellular compartment contributions to the temporal evolution of the overall water diffusion coefficient. Diffusion in the luminal compartment falls into the short-time surface-to-volume (S/V) limit, indicating that only a small fraction of water molecules has time to encounter the luminal walls of healthy tissue; from the S/V ratio, the average lumen diameter averaged over three young healthy subjects is measured to be 217.7±188.7 μm. Conversely, the diffusion in the cellular compartment is highly restricted and anisotropic, consistent with the fibrous character of the stromal tissue. Diffusion transverse to these fibers is well described by the random permeable barrier model (RPBM), as confirmed by the dynamical exponent ϑ = 1/2 for approaching the long-time limit of diffusion, and the corresponding structural exponent p = -1 in histology. The RPBM-derived fiber diameter and membrane permeability were 19.8±8.1 μm and 0.044±0.045 μm/ms, respectively, in agreement with known values from tissue histology and membrane biophysics. Lastly, we revisited 38 prostate cancer cases from a recently published study, and found the same dynamical exponent ϑ = 1/2 of diffusion in tumors and benign regions. Our results suggest that a multi-parametric MRI acquisition combined with biophysical modeling may be a powerful non-invasive complement to prostate cancer grading, potentially foregoing biopsies.

Quantitative evaluation of intravoxel incoherent motion diffusion-weighted imaging (IVIM) for differential diagnosis and grading prediction of benign and malignant breast lesions

BACKGROUND

That breast carcinoma is the most common malignant lesion in women. This study aimed to differentiate benign from malignant breast lesions and to predict grading of the latter by comparing the diagnostic value of different parameters in intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI).

MATERIALS AND METHODS

Retrospective analysis was performed utilizing imaging and pathological data from 112 patients with 124 breast lesions that underwent IVIM-DWI examination with 3.0 T MRI. Out of 124, 47 benign and 77 malignant lesions were confirmed by pathological diagnosis. The diagnostic performance of f, D, and D* value to distinguish benign from malignant breast lesions, was evaluated using pathological results as the gold standard. Correlation between D value and Ki-67 index was evaluated to predict grading of malignant breast lesions.

RESULTS

The D value (0.99 ± 0.21) of patients with malignant lesions was significantly lower than that (1.34 ± 0.18) of patients harboring benign lesions (P = .00). The D* value (7.60 ± 2.10) in malignant lesion group was higher than that (6.83 ± 2.13) of the benign lesion group (P = .113). The f value (8.50 ± 2.13) in malignant lesion group was remarkably higher than that (7.68 ± 1.98) of benign lesion group (P = .035). For differential diagnosis of benign from malignant breast lesions, optimal diagnostic threshold of D value and f value were 1.21 and 7.86, respectively. The areas of D and f values under the ROC curve were 0.883 and 0.601, respectively. The sensitivity, specificity, and accuracy of D value were 83.0%, 86.7%, and 85.5%, respectively. Accordingly, those indexes of f value were 64.9%, 57.4%, and 62.1%, respectively. Furthermore, the Ki-67 staining index of malignant lesions was robustly negatively correlated with D value (r = -0.395, P < .01).

CONCLUSION

Concrete parameters of IVIM-DWI can help to improve the specificity and accuracy in differential diagnosis of breast benign and malignant lesions. D value is most relevant and valuable in predicting the grading of malignant breast lesions.

Dual-Phase ADC Modelling of Breast Masses in Diffusion-Weighted Imaging: Comparison with Histopathologic Findings

Objective

To investigate the diagnostic value of dual-phase apparent diffusion coefficient (ADC) compared to traditional ADC values in quantitative diffusion-weighted imaging (DWI) for differentiating between benign and malignant breast masses.

Materials and Methods

Diffusion-weighted images of pathologically confirmed 88 benign and 85 malignant lesions acquired using a 3.0T MR scanner were analyzed. Small region-of-interests focusing on the highest signal intensity of lesions were used. Lesion ADC estimates were obtained separately from all b-value images (ADC; b=50, 400 and 800s/mm²), lower b-value images (ADC_low; b=50 and 400s/mm²) and higher b-value images (ADC_high; b=400 and 800s/mm²). A set of dual-phase ADC (dpADC) models were constructed using ADC_low, ADC_high and a perfusion influence factor ranging from 0 to 1.

Results

Strong positive correlation is observable between ADC and all dpADCs (ρ=0.80-1.00). Differences in ADC and dpADCs between the benign and the malignant lesions are all significant (p<0.05). In detecting malignancy, traditional lesion ADC provides a good performance (AUC=89.9%) however dpADC_0.5 (dpADC with a factor of 0.5) accomplishes a better performance (AUC=90.8%). At optimal thresholds, ADC achieves 94.1% sensitivity, 72.7% specificity and 83.2% accuracy while dpADC_0.5 leads to 92.9% sensitivity, 79.5% specificity and 86.1% accuracy.

Conclusion

Dual-phase ADC modelling may improve the accuracy in breast cancer diagnosis using DWI. Further prospective studies are needed to justify its benefit in clinical setting.

Role of intravoxel incoherent motion MR imaging in preoperative assessing HER2 status of gastric cancers

Purpose

To explore the role of intravoxel incoherent motion (IVIM) magnetic resonance (MR) imaging in evaluating human epidermal growth factor receptor 2 (HER2) status of gastric cancers preoperatively.

Results

The apparent diffusion coefficient (ADC) and pure diffusion coefficient (D) values correlated positively with HER2 scores of gastric cancers significantly (r = 0.276, P = 0.048; r = 0.481, P < 0.001, respectively). The ADC and D values of HER2 positive gastric cancers were significantly higher than those of HER2 negative tumors (P = 0.033, 0.007, respectively). With a cut-off value of 1.321 and 1.123 × 10⁻³ mm²/sec, the ADC and D values could distinguish HER2 positive gastric cancers from HER2 negative ones with an area under the curve of 0.733 and 0.762, respectively (P = 0.023, 0.011, respectively).

Materials and methods

Fifty-three patients with gastric cancers underwent IVIM MR imaging preoperatively. The values of ADC, D, pseudo diffusion coefficient (D*) and perfusion related fraction (f) of the lesions were obtained. Partial correlation test including tumor volume was performed to analyze correlations between IVIM values and HER2 scores excluding the impact of tumor size. IVIM parameters of gastric cancers with different HER2 status were compared using independent samples t test. Diagnostic performance of IVIM parameters in distinguishing HER2 positive gastric cancers from negative ones was tested with receiver operating characteristic analysis.

Conclusions

We confirmed the feasibility of IVIM MR imaging in preoperative assessment of HER2 status of gastric cancers, which might make up the shortfall of biopsy and facilitate personalized treatment for patients with gastric cancers.

Implementing diffusion-weighted MRI for body imaging in prospective multicentre trials: current considerations and future perspectives

For body imaging, diffusion-weighted MRI may be used for tumour detection, staging, prognostic information, assessing response and follow-up. Disease detection and staging involve qualitative, subjective assessment of images, whereas for prognosis, progression or response, quantitative evaluation of the apparent diffusion coefficient (ADC) is required. Validation and qualification of ADC in multicentre trials involves examination of i) technical performance to determine biomarker bias and reproducibility and ii) biological performance to interrogate a specific aspect of biology or to forecast outcome. Unfortunately, the variety of acquisition and analysis methodologies employed at different centres make ADC values non-comparable between them. This invalidates implementation in multicentre trials and limits utility of ADC as a biomarker. This article reviews the factors contributing to ADC variability in terms of data acquisition and analysis. Hardware and software considerations are discussed when implementing standardised protocols across multi-vendor platforms together with methods for quality assurance and quality control. Processes of data collection, archiving, curation, analysis, central reading and handling incidental findings are considered in the conduct of multicentre trials. Data protection and good clinical practice are essential prerequisites. Developing international consensus of procedures is critical to successful validation if ADC is to become a useful biomarker in oncology.

KEY POINTS

• Standardised acquisition/analysis allows quantification of imaging biomarkers in multicentre trials. • Establishing "precision" of the measurement in the multicentre context is essential. • A repository with traceable data of known provenance promotes further research.

Histogram analysis of stretched-exponential and monoexponential diffusion-weighted imaging models for distinguishing low and intermediate/high gleason scores in prostate carcinoma

BACKGROUND

Noninvasive measures to evaluate the aggressiveness of prostate carcinoma (PCa) may benefit patients.

PURPOSE

To assess the value of stretched-exponential and monoexponential diffusion-weighted imaging (DWI) for predicting the aggressiveness of PCa.

STUDY TYPE

Retrospective study.

SUBJECTS

Seventy-five patients with PCa.

FIELD STRENGTH

3T DWI examinations were performed using b-values of 0, 500, 1000, and 2000 s/mm² .

ASSESSMENT

The research were based on entire-tumor histogram analysis and the reference standard was radical prostectomy.

STATISTICAL TESTS

The correlation analysis was programmed with Spearman's rank-order analysis between the histogram variables and Gleason grade group (GG). Receiver operating characteristic (ROC) regression was used to analyze the ability of these histogram variables to differentiate low-grade (LG) from intermediate/high-grade (HG) PCa.

RESULTS

The percentiles and mean of apparent diffusion coefficient (ADC) and distributed diffusion coefficient (DDC) were correlated with GG (ρ: 0.414-0.593), while there was no significant relation among α value, skewnesses, and kurtosises with GG (ρ:0.034-0.323). HG tumors (ADC:484 ± 136, 592 ± 139, 670 ± 144, 788 ± 146, 895 ± 141 mm² /s; DDC: 410 ± 142, 532 ± 172, 666 ± 193, 786 ± 196, 914 ± 181 mm² /s) had lower values in the 10^th , 25^th , 50^th , 75^th percentiles and means than LG tumors (ADC: 644 ± 779, 737 ± 84, 836 ± 83, 919 ± 82, 997 ± 107 mm² /s; DDC: 552 ± 82, 680 ± 94, 829 ± 112, 931 ± 106, 1045 ± 100 mm² /s). However, there was no difference between LG and HG tumors in α value (0.671 ± 0.041 vs. 0.633 ± 0.114), kurtosises (ADC 0.09 vs. 0.086; DDC -0.033 vs. -0.317), or skewnesses (ADC -0.036 vs. 0.073; DDC -0.063 vs. 0.136). The above statistics were P < 0.01. ADC10 with AUC = 0.840 and DDC10 with AUC = 0.799 were similar in discriminating between LG and HG PCa at P < 0.05.

DATA CONCLUSION

Histogram variables of DDC and ADC may predict the aggressiveness of PCa, while α value does not. The abilities of ADC10 and DDC10 to discriminate LG from HG tumors were similar, and both better than their respective means.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2018;48:491-498.

Accuracy of high b-value diffusion-weighted MRI for prostate cancer detection: a meta-analysis

Background The diagnostic accuracy of diffusion-weighted imaging (DWI) to detect prostate cancer is well-established. DWI provides visual as well as quantitative means of detecting tumor, the apparent diffusion coefficient (ADC). Recently higher b-values have been used to improve DWI's diagnostic performance. Purpose To determine the diagnostic performance of high b-value DWI at detecting prostate cancer and whether quantifying ADC improves accuracy. Material and Methods A comprehensive literature search of published and unpublished databases was performed. Eligible studies had histopathologically proven prostate cancer, DWI sequences using b-values ≥ 1000 s/mm², less than ten patients, and data for creating a 2 × 2 table. Study quality was assessed with QUADAS-2 (Quality Assessment of diagnostic Accuracy Studies). Sensitivity and specificity were calculated and tests for statistical heterogeneity and threshold effect performed. Results were plotted on a summary receiver operating characteristic curve (sROC) and the area under the curve (AUC) determined the diagnostic performance of high b-value DWI. Results Ten studies met eligibility criteria with 13 subsets of data available for analysis, including 522 patients. Pooled sensitivity and specificity were 0.59 (95% confidence interval [CI], 0.57-0.61) and 0.92 (95% CI, 0.91-0.92), respectively, and the sROC AUC was 0.92. Subgroup analysis showed a statistically significant ( P = 0.03) improvement in accuracy when using tumor visual assessment rather than ADC. Conclusion High b-value DWI gives good diagnostic performance for prostate cancer detection and visual assessment of tumor diffusion is significantly more accurate than ROI measurements of ADC.

Quantitative intravoxel incoherent motion parameters derived from whole-tumor volume for assessing pathological complete response to neoadjuvant chemotherapy in locally advanced rectal cancer

BACKGROUND

Many locally advanced rectal cancer (LARC) patients can benefit from neoadjuvant chemotherapy (NACT), with some achieving a pathological complete response (pCR). However, there is limited research reporting on the value of intravoxel incoherent motion (IVIM) in monitoring pCR in patients with LARC.

PURPOSE

To identify whether IVIM parameters derived from whole-tumor volume (WTV) before and after NACT could accurately assess pCR in patients with LARC.

STUDY TYPE

Prospective patient control study.

POPULATION

Fifty-one patients with LARC before and after NACT, prior to surgery.

FIELD STRENGTH/SEQUENCE

IVIM-diffusion imaging at 3T.

ASSESSMENT

Apparent diffusion coefficient (ADC), slow diffusion coefficient (D), fast diffusion coefficient (D*), and perfusion-related diffusion fraction (f) values were obtained on diffusion-weighted magnetic resonance images (DW-MRI) using WTV methods and calculated using a biexponential model before and after NACT.

STATISTICAL TESTS

DWI-derived ADC and IVIM-derived parameters and their percentage changes (ΔADC%, ΔD%, ΔD*%, and Δf%) were compared using independent-samples t-test and Mann-Whitney U-test between the pCR and non-pCR groups. The diagnostic performance of IVIM parameters and their percentage changes were evaluated using receiver operating characteristic curves.

RESULTS

Compared with the non-pCR group, the pCR group exhibited significantly lower pre-ADC_mean (P = 0.003) and pre-D values (P = 0.024), and significantly higher post-f (P = 0.002), ΔADC_mean % (P = 0.002), ΔD% (P = 0.001), and Δf% values (P = 0.017). Receiver operating characteristic curves showed that the pre-D value had the best specificity (95.12%) and accuracy (86.27%) in predicting the pCR status, and ΔD% had the highest area under the curve (0.832) in assessing the pCR response to NACT.

DATA CONCLUSIONS

The IVIM-derived D value is a promising tool in predicting the pCR status before therapy. The percentage changes in D values after therapy may help assess the pCR status prior to surgery.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017.

Optimization of prostate MRI acquisition and post-processing protocol: a pictorial review with access to acquisition protocols

The aim of this review article is to provide insight into the optimization of 1.5-Testla (T) and 3-T prostate magnetic resonance imaging (MRI). An approach for optimization of data quantification, especially diffusion-weighted imaging (DWI), is provided. Benefits and limitations of various pulse sequences are discussed. Importable MRI protocols and access to imaging datasets is provided. Careful optimization of prostate MR acquisition protocol allows the acquisition of high-quality prostate MRI using clinical 1.5-T/3-T MR scanners with an overall acquisition time < 15 min.

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.

Design and validation of diffusion MRI models of white matter

Diffusion MRI is arguably the method of choice for characterizing white matter microstructure in vivo. Over the typical duration of diffusion encoding, the displacement of water molecules is conveniently on a length scale similar to that of the underlying cellular structures. Moreover, water molecules in white matter are largely compartmentalized which enables biologically-inspired compartmental diffusion models to characterize and quantify the true biological microstructure. A plethora of white matter models have been proposed. However, overparameterization and mathematical fitting complications encourage the introduction of simplifying assumptions that vary between different approaches. These choices impact the quantitative estimation of model parameters with potential detriments to their biological accuracy and promised specificity. First, we review biophysical white matter models in use and recapitulate their underlying assumptions and realms of applicability. Second, we present up-to-date efforts to validate parameters estimated from biophysical models. Simulations and dedicated phantoms are useful in assessing the performance of models when the ground truth is known. However, the biggest challenge remains the validation of the "biological accuracy" of estimated parameters. Complementary techniques such as microscopy of fixed tissue specimens have facilitated direct comparisons of estimates of white matter fiber orientation and densities. However, validation of compartmental diffusivities remains challenging, and complementary MRI-based techniques such as alternative diffusion encodings, compartment-specific contrast agents and metabolites have been used to validate diffusion models. Finally, white matter injury and disease pose additional challenges to modeling, which are also discussed. This review aims to provide an overview of the current state of models and their validation and to stimulate further research in the field to solve the remaining open questions and converge towards consensus.

Non-Mono-Exponential Analysis of Diffusion-Weighted Imaging for Treatment Monitoring in Prostate Cancer Bone Metastases

Diffusion-weighted imaging quantified using the mono-exponential model has shown great promise for monitoring treatment response in prostate cancer bone metastases. The aim of this prospective study is to evaluate whether non-mono-exponential diffusion models better describe the water diffusion properties and may improve treatment response assessment. Diffusion-weighted imaging data of 12 treatment-naïve patients with 34 metastases acquired before and at one, two, and three months after initiation of antiandrogen treatment are analysed using the mono-exponential, the intravoxel incoherent motion, the stretched exponential, and the statistical model. Repeatability of the fitted parameters and changes under therapy are quantified. Model preference is assessed and correlation coefficients across times are calculated to delineate the relationship between the prostate-specific antigen levels and the diffusion parameters as well as between the diffusion parameters within each model. There is a clear preference for non-mono-exponential diffusion models at all time points. Particularly the stretched exponential is favoured in approximately 60% of the lesions. Its parameters increase significantly in response to treatment and are highly repeatable. Thus, the stretched exponential may be utilized as a potential optimal model for monitoring treatment response. Compared with the mono-exponential model, it may provide complementary information on tissue properties and improve response assessment.

Assessment of early treatment response to neoadjuvant chemotherapy in breast cancer using non-mono-exponential diffusion models: a feasibility study comparing the baseline and mid-treatment MRI examinations

OBJECTIVES

To assess the feasibility of the mono-exponential, bi-exponential and stretched-exponential models in evaluating response of breast tumours to neoadjuvant chemotherapy (NACT) at 3 T.

METHODS

Thirty-six female patients (median age 53, range 32-75 years) with invasive breast cancer undergoing NACT were enrolled for diffusion-weighted MRI (DW-MRI) prior to the start of treatment. For assessment of early response, changes in parameters were evaluated on mid-treatment MRI in 22 patients. DW-MRI was performed using eight b values (0, 30, 60, 90, 120, 300, 600, 900 s/mm2). Apparent diffusion coefficient (ADC), tissue diffusion coefficient (D t), vascular fraction (ƒ), distributed diffusion coefficient (DDC) and alpha (α) parameters were derived. Then t tests compared the baseline and changes in parameters between response groups. Repeatability was assessed at inter- and intraobserver levels.

RESULTS

All patients underwent baseline MRI whereas 22 lesions were available at mid-treatment. At pretreatment, mean diffusion coefficients demonstrated significant differences between groups (p < 0.05). At mid-treatment, percentage increase in ADC and DDC showed significant differences between responders (49 % and 43 %) and non-responders (21 % and 32 %) (p = 0.03, p = 0.04). Overall, stretched-exponential parameters showed excellent repeatability.

CONCLUSION

DW-MRI is sensitive to baseline and early treatment changes in breast cancer using non-mono-exponential models, and the stretched-exponential model can potentially monitor such changes.

KEY POINTS

• Baseline diffusion coefficients demonstrated significant differences between complete pathological responders and non-responders. • Increase in ADC and DDC at mid-treatment can discriminate responders and non-responders. • The ƒ fraction at mid-treatment decreased in responders whereas increased in non-responders. • The mono- and stretched-exponential models showed excellent inter- and intrarater repeatability. • Treatment effects can potentially be assessed by non-mono-exponential diffusion models.

Separation of type and grade in cervical tumours using non-mono-exponential models of diffusion-weighted MRI

OBJECTIVES

Assessment of empirical diffusion-weighted MRI (DW-MRI) models in cervical tumours to investigate whether fitted parameters distinguish between types and grades of tumours.

METHODS

Forty-two patients (24 squamous cell carcinomas, 14 well/moderately differentiated, 10 poorly differentiated; 15 adenocarcinomas, 13 well/moderately differentiated, two poorly differentiated; three rare types) were imaged at 3 T using nine b-values (0 to 800 s mm-2). Mono-exponential, stretched exponential, kurtosis, statistical, and bi-exponential models were fitted. Model preference was assessed using Bayesian Information Criterion analysis. Differences in fitted parameters between tumour types/grades and correlation between fitted parameters were assessed using two-way analysis of variance and Pearson's linear correlation coefficient, respectively.

RESULTS

Non-mono-exponential models were preferred by 83 % of tumours with bi-exponential and stretched exponential models preferred by the largest numbers of tumours. Apparent diffusion coefficient (ADC) and diffusion coefficients from non-mono-exponential models were significantly lower in poorly differentiated tumours than well/moderately differentiated tumours. α (stretched exponential), K (kurtosis), f and D* (bi-exponential) were significantly different between tumour types. Strong correlation was observed between ADC and diffusion coefficients from other models.

CONCLUSIONS

Non-mono-exponential models were preferred to the mono-exponential model in DW-MRI data from cervical tumours. Parameters of non-mono-exponential models showed significant differences between types and grades of tumours.

KEY POINTS

• Non-mono-exponential DW-MRI models are preferred in the majority of cervical tumours. • Poorly differentiated cervical tumours exhibit lower diffusion coefficients than well/moderately differentiated tumours. • Non-mono-exponential model parameters α, K, f, and D* differ between tumour types. • Micro-structural features are likely to affect parameters in non-mono-exponential models differently.

Assessment of pathological complete response to preoperative chemoradiotherapy by means of multiple mathematical models of diffusion-weighted MRI in locally advanced rectal cancer: A prospective single-center study

PURPOSE

To assess stretched-exponential, mono-exponential and intravoxel incoherent motion (IVIM) models of diffusion-weighted MRI(DWI) in predicting pathological complete response (pCR) to neoadjuvant chemoradiotherapy (CRT) in rectal cancer patients.

MATERIALS AND METHODS

This prospective study recruited 98 consecutive patients with locally advanced rectal cancer who underwent 3 Tesla MR examination before, during and after CRT. The apparent diffusion coefficient (ADC), IVIM-derived parameters (D, f, and D*), and stretched-exponential model-derived parameters (DDC and α) were measured. The parameters and their corresponding changes during and after CRT were compared between pCR and non-pCR. Receiver-operating characteristic curve analysis was performed to evaluate the diagnostic performance. Coefficient of variations and intraclass correlation coefficient were calculated to assess reliability and agreement.

RESULTS

Nineteen patients achieved pCR while 79 did not. The pCR group had higher ADC and α (ADC₂ and α₂ ), and their changes (ΔADC₂ , and Δα₂ ) at the endpoint than non-pCR group. α₂ and ADC₂ yielded similar AUCs (P = 0.339), Δα₂ and ΔADC₂ yielded similar AUCs (P = 0.263) ADC and α presented substantial agreement, and α presented the minimum CV (5.0-7.0%).

CONCLUSION

ADC and α were useful for assessing pCR after CRT. α might be more useful because it demonstrated better diagnostic performance than IVIM-derived parameters and better reliability than ADC.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:175-183.

Comparison of non-Gaussian and Gaussian diffusion models of diffusion weighted imaging of rectal cancer at 3.0 T MRI

Water molecular diffusion in vivo tissue is much more complicated. We aimed to compare non-Gaussian diffusion models of diffusion-weighted imaging (DWI) including intra-voxel incoherent motion (IVIM), stretched-exponential model (SEM) and Gaussian diffusion model at 3.0 T MRI in patients with rectal cancer, and to determine the optimal model for investigating the water diffusion properties and characterization of rectal carcinoma. Fifty-nine consecutive patients with pathologically confirmed rectal adenocarcinoma underwent DWI with 16 b-values at a 3.0 T MRI system. DWI signals were fitted to the mono-exponential and non-Gaussian diffusion models (IVIM-mono, IVIM-bi and SEM) on primary tumor and adjacent normal rectal tissue. Parameters of standard apparent diffusion coefficient (ADC), slow- and fast-ADC, fraction of fast ADC (f), α value and distributed diffusion coefficient (DDC) were generated and compared between the tumor and normal tissues. The SEM exhibited the best fitting results of actual DWI signal in rectal cancer and the normal rectal wall (R² = 0.998, 0.999 respectively). The DDC achieved relatively high area under the curve (AUC = 0.980) in differentiating tumor from normal rectal wall. Non-Gaussian diffusion models could assess tissue properties more accurately than the ADC derived Gaussian diffusion model. SEM may be used as a potential optimal model for characterization of rectal cancer.

Evaluation of the impact of computed high b-value diffusion-weighted imaging on prostate cancer detection

PURPOSE

The purpose of this study was to compare high b-value (b = 2000 s/mm(2)) acquired diffusion-weighted imaging (aDWI) with computed DWI (cDWI) obtained using four diffusion models-mono-exponential (ME), intra-voxel incoherent motion (IVIM), stretched exponential (SE), and diffusional kurtosis (DK)-with respect to lesion visibility, conspicuity, contrast, and ability to predict significant prostate cancer (PCa).

METHODS

Ninety four patients underwent 3 T MRI including acquisition of b = 2000 s/mm(2) aDWI and low b-value DWI. High b = 2000 s/mm(2) cDWI was obtained using ME, IVIM, SE, and DK models. All images were scored on quality independently by three radiologists. Lesions were identified on all images and graded for lesion conspicuity. For a subset of lesions for which pathological truth was established, lesion-to-background contrast ratios (LBCRs) were computed and binomial generalized linear mixed model analysis was conducted to compare clinically significant PCa predictive capabilities of all DWI.

RESULTS

For all readers and all models, cDWI demonstrated higher ratings for image quality and lesion conspicuity than aDWI except DK (p < 0.001). The LBCRs of ME, IVIM, and SE were significantly higher than LBCR of aDWI (p < 0.001). Receiver Operating Characteristic curves obtained from binomial generalized linear mixed model analysis demonstrated higher Area Under the Curves for ME, SE, IVIM, and aDWI compared to DK or PSAD alone in predicting significant PCa.

CONCLUSION

High b-value cDWI using ME, IVIM, and SE diffusion models provide better image quality, lesion conspicuity, and increased LBCR than high b-value aDWI. Using cDWI can potentially provide comparable sensitivity and specificity for detecting significant PCa as high b-value aDWI without increased scan times and image degradation artifacts.

Diffusion-weighted MR imaging of metastatic abdominal and pelvic tumours is sensitive to early changes induced by a VEGF inhibitor using alternative diffusion attenuation models

OBJECTIVES

To assess the utility of diffusion weighted imaging for monitoring early treatment effects associated with a VEGF inhibitor.

MATERIALS AND METHODS

Twenty-nine patients with metastatic abdominal and pelvic tumours were recruited and imaged with DW-MRI: twice at baseline, and after 7 and 28 days of treatment with cediranib. Tumour measures were derived using mono-exponential, bi-exponential and stretched-exponential models, and parameter repeatability and treatment effects seen after 7 and 28 days were assessed. Correlations with volume changes and DCE-MRI metrics were also assessed.

RESULTS

Diffusion coefficient repeatabilities from all models were < 6%; f and D* (bi-exponential) were 22% and 44%; α (stretched-exponential) was 4.2%. Significant increases in the diffusion coefficients from all models were observed at day 28 but not day 7. Significant decreases in D* and f.D* were observed at day 7 and in f at day 28; significant increases in α were observed at both time-points. Weak correlations between DW-MRI changes and volume changes and DCE-MRI changes were observed.

CONCLUSION

DW-MRI is sensitive to early and late treatment changes caused by a VEGF inhibitor using non-mono-exponential models. Evidence of over-fitting using the bi-exponential model suggests that the stretched-exponential model is best suited to monitor such changes.

KEY POINTS

• Non-mono-exponential diffusion models widen sensitivity to a broader class of tissue properties. • A stretched-exponential model robustly detects changes after 7 days of VEGF-inhibitor treatment. • There are very weak correlations between DWI-IVIM perfusion and similar DCE-MRI measures. • Diffusion-weighted MRI is a highly informative technique for assessing novel tumour therapies.

Fitting methods for intravoxel incoherent motion imaging of prostate cancer on region of interest level: Repeatability and gleason score prediction

PURPOSE

To evaluate different fitting methods for intravoxel incoherent motion (IVIM) imaging of prostate cancer in the terms of repeatability and Gleason score prediction.

METHODS

Eighty-one patients with histologically confirmed prostate cancer underwent two repeated 3 Tesla diffusion-weighted imaging (DWI) examinations performed using 14 b-values in the range of 0-500 s/mm² and diffusion time of 19.004 ms. Mean signal intensities of regions-of-interest were fitted using five different fitting methods for IVIM as well as monoexponential, kurtosis, and stretched exponential models. The fitting methods and models were evaluated in the terms of fitting quality [Akaike information criteria (AIC)], repeatability, and Gleason score prediction. Tumors were classified into three groups (3 + 3, 3 + 4, > 3 + 4). Machine learning algorithms were used to evaluate the performance of the combined use of the parameters. Simulation studies were performed to evaluate robustness of the fitting methods against noise.

RESULTS

Monoexponential model was preferred over IVIM based on AIC. The "pseudodiffusion" parameters demonstrated low repeatability and clinical value. Median "pseudodiffusion" fraction values were below 8.00%. Combined use of the parameters did not outperform the monoexponential model.

CONCLUSION

Monoexponential model demonstrated the highest repeatability and clinical values in the regions-of-interest based analysis of prostate cancer DWI, b-values in the range of 0-500 s/mm² . Magn Reson Med 77:1249-1264, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Evaluating early response of cervical cancer under concurrent chemo-radiotherapy by intravoxel incoherent motion MR imaging

BACKGROUND

Intravoxel incoherent motion (IVIM) MR imaging has been applied in researches of various diseases, however its potential in cervical cancer patients has not been fully explored. The purpose of this study was to investigate the feasibility of IVIM MR imaging to monitor early treatment response in patients receiving concurrent chemo-radiotherapy (CCRT) for advanced cervical cancers.

METHODS

Twenty-one patients receiving CCRT for advanced cervical cancer were prospectively enrolled. MR examinations including IVIM imaging (with 14 b values, 0 ~ 1000 s/mm(2)) were performed at 4 time points: 1-week prior to, 2-week and 4-week during, as well as immediately post CCRT (within 1 week). The apparent diffusion coefficient (ADC) maps were derived from the mono-exponential model, while the diffusion coefficient (D), perfusion fraction (f) and pseudo-diffusion coefficient (D*) maps were calculated from the bi-exponential model. Dynamic changes of ADC, D, f and D* in cervical cancers were investigated as early surrogate markers for treatment response.

RESULTS

ADC and D values increased throughout the CCRT course. Both f and D* increased in the first 2 to 3 weeks of CCRT and started to decrease around 4 weeks of CCRT. Significant increase of f value was observed from prior to CCRT (f 1 = 0.12 ± 0.52) to two-week during CCRT (f2 = 0.20 ± 0.90, p = 0.002).

CONCLUSIONS

IVIM MR imaging has the potential in monitoring early tumor response induced by CCRT in patients with cervical cancers.

Evaluation of diffusion models in breast cancer

PURPOSE

The purpose of this study is to investigate whether the microvascular pseudodiffusion effects resulting with non-monoexponential behavior are present in breast cancer, taking into account tumor spatial heterogeneity. Additionally, methodological factors affecting the signal in low and high diffusion-sensitizing gradient ranges were explored in phantom studies.

METHODS

The effect of eddy currents and accuracy of b-value determination using a multiple b-value diffusion-weighted MR imaging sequence were investigated in test objects. Diffusion model selection and noise were then investigated in volunteers (n = 5) and breast tumor patients (n = 21) using the Bayesian information criterion.

RESULTS

54.3% of lesion voxels were best fitted by a monoexponential, 26.2% by a stretched-exponential, and 19.5% by a biexponential intravoxel incoherent motion (IVIM) model. High correlation (0.92) was observed between diffusion coefficients calculated using mono- and stretched-exponential models and moderate (0.59) between monoexponential and IVIM (medians: 0.96/0.84/0.72 × 10(-3) mm(2)/s, respectively). Distortion due to eddy currents depended on the direction of the diffusion gradient and displacement varied between 1 and 6 mm for high b-value images. Shift in the apparent diffusion coefficient due to intrinsic field gradients was compensated for by averaging diffusion data obtained from opposite directions.

CONCLUSIONS

Pseudodiffusion and intravoxel heterogeneity effects were not observed in approximately half of breast cancer and normal tissue voxels. This result indicates that stretched and IVIM models should be utilized in regional analysis rather than global tumor assessment. Cross terms between diffusion-sensitization gradients and other imaging or susceptibility-related gradients are relevant in clinical protocols, supporting the use of geometric averaging of diffusion-weighted images acquired with diffusion-sensitization gradients in opposite directions.

Modelling DW-MRI data from primary and metastatic ovarian tumours

OBJECTIVES

To assess goodness-of-fit and repeatability of mono-exponential, stretched exponential and bi-exponential models of diffusion-weighted MRI (DW-MRI) data in primary and metastatic ovarian cancer.

METHODS

Thirty-nine primary and metastatic lesions from thirty-one patients with stage III or IV ovarian cancer were examined before and after chemotherapy using DW-MRI with ten diffusion-weightings. The data were fitted with (a) a mono-exponential model to give the apparent diffusion coefficient (ADC), (b) a stretched exponential model to give the distributed diffusion coefficient (DDC) and stretching parameter (α), and (c) a bi-exponential model to give the diffusion coefficient (D), perfusion fraction (f) and pseudodiffusion coefficient (D*).

RESULTS

Coefficients of variation, established from repeated baseline measurements, were: ADC 3.1%, DDC 4.3%, α 7.0%, D 13.2%, f 44.0%, D* 165.1%. The bi-exponential model was unsuitable in these data owing to poor repeatability. After excluding the bi-exponential model, analysis using Akaike Information Criteria showed that the stretched exponential model provided the better fit to the majority of pixels in 64% of lesions.

CONCLUSIONS

The stretched exponential model provides the optimal fit to DW-MRI data from ovarian, omental and peritoneal lesions and lymph nodes in pre-treatment and post-treatment measurements with good repeatability.

KEY POINTS

• DW-MRI data in ovarian cancer show deviation from mono-exponential behaviour • Parameters derived from the stretched exponential model showed good repeatability (CV 7%) • The bi-exponential model was unsuitable because of poor parameter repeatability • The stretched exponential model showed comparable repeatability to the mono-exponential model • The extra parameter (α) provides scope for investigation of heterogeneity or response.

Impact of the calculation algorithm on biexponential fitting of diffusion-weighted MRI in upper abdominal organs

PURPOSE

To compare the variability, precision, and accuracy of six different algorithms (Levenberg-Marquardt, Trust-Region, Fixed-Dp , Segmented-Unconstrained, Segmented-Constrained, and Bayesian-Probability) for computing intravoxel-incoherent-motion-related parameters in upper abdominal organs.

METHODS

Following the acquisition of abdominal diffusion-weighted magnetic resonance images of 10 healthy men, six distinct algorithms were employed to compute intravoxel-incoherent-motion-related parameters in the left and right liver lobe, pancreas, spleen, renal cortex, and renal medulla. Algorithms were evaluated regarding inter-reader and intersubject variability. Comparability of results was assessed by analyses of variance. The algorithms' precision and accuracy were investigated on simulated data.

RESULTS

A Bayesian-Probability based approach was associated with very low inter-reader variability (average Intraclass Correlation Coefficients: 96.5-99.6%), the lowest inter-subject variability (Coefficients of Variation [CV] for the pure diffusion coefficient Dt : 3.8% in the renal medulla, 6.6% in the renal cortex, 10.4-12.1% in the left and right liver lobe, 15.3% in the spleen, 15.8% in the pancreas; for the perfusion fraction Fp : 15.5% on average; for the pseudodiffusion coefficient Dp : 25.8% on average), and the highest precision and accuracy. Results differed significantly (P < 0.05) across algorithms in all anatomical regions.

CONCLUSION

The Bayesian-Probability algorithm should be preferred when computing intravoxel-incoherent-motion-related parameters in upper abdominal organs.

Comparison of stretched-Exponential and monoexponential model diffusion-Weighted imaging in prostate cancer and normal tissues

BACKGROUND

To compare stretched-exponential and monoexponential model diffusion-weighted imaging (DWI) in prostate cancer and normal tissues.

METHODS

Twenty-seven patients with prostate cancer underwent DWI exam using b-values of 0, 500, 1000, and 2000 s/mm(2) . The distributed diffusion coefficients (DDC) and α values of prostate cancer and normal tissues were obtained with stretched-exponential model and apparent diffusion coefficient (ADC) values using monoexponential model. The ADC, DDC (both in 10(-3) mm(2)/s), and α values (range, 0-1) were compared among different prostate tissues. The ADC and DDC were also compared and correlated in each tissue, and the standardized differences between DDC and ADC were compared among different tissues.

RESULTS

Data were obtained for 31 cancers, 36 normal peripheral zone (PZ) and 26 normal central gland (CG) tissues. The ADC (0.71 ± 0.12), DDC (0.60 ± 0.18), and α value (0.64 ± 0.05) of tumor were all significantly lower than those of the normal PZ (1.41 ± 0.22, 1.47 ± 0.20, and 0.85 ± 0.09) and CG (1.25 ± 0.14, 1.32 ± 0.13, and 0.82 ± 0.06) (all P < 0.05). ADC was significantly higher than DDC in cancer, but lower than DDC in the PZ and CG (all P < 0.05). The ADC and DDC were strongly correlated (R(2)  = 0.99, 0.98, 0.99, respectively, all P < 0.05) in all the tissue, and standardized difference between ADC and DDC of cancer was slight but significantly higher than that in normal tissue.

CONCLUSION

The stretched-exponential model DWI provides more parameters for distinguishing prostate cancer and normal tissue and reveals slight differences between DDC and ADC values.