High and ultra-high b-value diffusion-weighted imaging in prostate cancer: a quantitative analysis

Improved effects of the b-value for 2000 sec/mm2 DWI on an accurate qualitative and quantitative assessment of rectal cancer

BACKGROUND AND STUDY OBJECTIVES

A higher b-value Diffusion-weighted imaging (DWI) would improve the contrast between cancerous and noncancerous tissue. Apparent diffusion coefficient (ADC)-histogram analysis is a method that can provide statistical data and quantitative information on tumor heterogeneity. This study aimed to compare two high b-values (1000 and 2000 sec/mm2) DWI in tumor detection and diagnostic performance in identifying early-stage tumor rectal cancer.

PATIENTS AND METHODS

This blinded and blinded retrospective study involved 56 patients with rectal cancer and 45 patients. Two radiologists evaluated the qualitative detection parameters and quantitative parameters of the ADC evaluated histogram and compared them between two DWI sequences (b-value for 1000 sec/mm2 and 2000 sec/mm2). The characteristic curves were used to assess diagnostic administration for the ADC histogram in discriminating early-stage tumors.

RESULTS

The b-value for 2000 sec/mm2 DWI significantly improved AUCs, sensitivity, specificity, and precision and decreased false-positive rate for detection compared to the b-value for 1000 sec/mm2 (p < 0.05). The mean and fifth percentile ADC value for stage I using the b-value for 1000 sec/mm2 DWI was significantly higher than stage ≥ II (p = 0.036II and 0.016 respectively), as the well as fifth, 10th, mean ADC of the fifth, 10th, and 25th ADC percentile at b-value for 2000 sec/mm2 (p = 0.031, 0.014, 0.035 and 0.025 respectively). The AUCs of the fifth percentile ADC at b-value for 2000 sec/mm2 DWI in both readers in differentiating the stage Ⅰ tumor were the highest (0.732 and 0.751).

CONCLUSION

The b-value for 2000 sec/mm2 DWI could improve the accurate detection of rectal cancer. The fifth percentile ADC at b-value for 2000 sec/mm2 sec/mm2 DWI was more useful for discriminating early stage than the b-value for 1000 sec/mm2 DWI.

Noninferiority of Monoparametric MRI Versus Multiparametric MRI for the Detection of Prostate Cancer: Diagnostic Accuracy of ADC Ratios Based on Advanced "Zoomed" Diffusion-Weighted Imaging

OBJECTIVES

The aim of this study was to compare the diagnostic accuracy of apparent diffusion coefficient (ADC) ratios as a monoparametric magnetic resonance imaging (MRI) protocol for the detection of prostate cancer (PCa) with the established multiparametric (mp) MRI at 3.0 T.

MATERIALS AND METHODS

According to power analysis, 52 male patients were included in this monocenter study with prospective data collection and retrospective, blinded multireader image analysis. The study was approved by the local ethics committee. Patients were recruited from January to December 2020. Based on mpMRI findings, patients underwent in-bore MR biopsy or prostatectomy for histopathologic correlation of suspicious lesions. Three readers, blinded to the histopathologic results and images of mpMRI, independently evaluated ADC maps for the detection of PCa. The ADC ratio was defined as the lowest signal intensity (SI) of lesions divided by the SI of normal tissue in the zone of origin. Predictive accuracy of multiparametric and monoparametric MRI were compared using logistic regression analysis. Moreover, both protocols were compared applying goodness-of-fit analysis with the Hosmer-Lemeshow test for continuous ADC ratios and Pearson χ2 test for binary decision calls, correlation analysis with Spearman ρ and intraclass correlation coefficients, as well as noninferiority assessment with a TOST ("two one-sided test").

RESULTS

Eighty-one histopathologically proven, unique PCa lesions (Gleason score [GS] ≥ 3 + 3) in 52 patients could be unequivocally correlated, with 57 clinically significant (cs) PCa lesions (GS ≥ 3 + 4). Multiparametric MRI detected 95%, and monoparametric ADC detected ratios 91% to 93% of csPCa. Noninferiority of monoparametric MRI was confirmed by TOST (P < 0.05 for all comparisons). Logistic regression analysis revealed comparable predictive diagnostic accuracy of ADC ratios (73.7%-87.8%) versus mpMRI (72.2%-84.7%). Spearman rank correlation coefficient for PCa aggressiveness revealed satisfactory correlation of ADC ratios (P < 0.013 for all correlations). The Hosmer-Lemeshow test for the logistic regression analysis for continuous ADC ratios indicated adequate predictive accuracy (P = 0.55-0.87), and the Pearson χ2 test showed satisfactory goodness of fit (P = 0.35-0.69, χ2 = 0.16-0.87).

CONCLUSIONS

Normalized ADC ratios based on advanced DWI are noninferior to mpMRI at 3.0 T for the detection of csPCa in a preselected patient cohort and proved a fast and accurate assessment tool, thus showing a potential prospect of easing the development of future screening methods for PCa.

Prostate Cancer Diffusion-Weighted Magnetic Resonance Imaging: Does the Choice of Diffusion-Weighting Level Matter?

BACKGROUND

Diffusion-weighted magnetic resonance imaging plays an important role in multiparametric assessment of prostate lesions. The derived apparent diffusion coefficient (ADC) could be a useful quantitative biomarker for malignant growth, but lacks acceptance because of low reproducibility.

PURPOSE

To investigate the impact of the choice of diffusion-weighting levels (b-values) on contrast-to-noise ratio and quantitative measures in prostate diffusion-weighted MRI.

STUDY TYPE

Retrospective and simulation based on published data.

SUBJECTS

Patient cohort (21 men with Prostate Imaging-Reporting and Data System (PI-RADS) version 2 score ≥3) from a single-center study.

FIELD STRENGTH/SEQUENCE

3 T/diffusion-weighted imaging with single-shot echo-planar imaging.

ASSESSMENT

Both clinical data and simulations based on previously acquired data were used to quantify the influence of b-value choice in normal peripheral zone (PZ) and PZ tumor lesions. For clinical data, ADC was determined for different combinations of b-values. Contrast-to-noise ratio and quantitative diffusion measures were simulated for a wide range of b-values.

STATISTICAL TESTS

Tissue ADC and the lesion-to-normal tissue ADC ratios of different b-value combinations were compared with paired two-tailed Student's t-tests. A P-value <0.05 was considered statistically significant.

RESULTS

Findings about b-value dependence derived from clinical data and from simulations agreed with each other. Provided measurement was limited to two b-values, simulation-derived optimal b-value choices coincided with PI-RADSv2 recommendations. For two-point measurements, ADC decreased by 15% when the maximum b-value increased from 1000 to 1500 seconds/mm² , but corresponding lesion-to-normal tissue ADC ratio showed no significant change (P = 0.86 for acquired data). Simulations with three or more measurement points produced ADCs that declined by only 8% over this range of maximum b-value. Corresponding ADC ratios declined between 2.6% (three points) and 3.8% (21 points). Simulations also revealed an ADC reduction of about 19% with the shorter echo and diffusion time evaluated.

DATA CONCLUSION

The comprehensive assessment of b-value dependence permits better formulation of protocol and analysis recommendations for obtaining reproducible results in prostate cancer diffusion-weighted MRI.

LEVEL OF EVIDENCE

4 TECHNICAL EFFICACY: Stage 2.

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

PURPOSE

Prostate cancer remains the 2nd leading cancer killer of men, yet it is also a disease with a high rate of overtreatment. Diffusion weighted imaging (DWI) has shown promise as a reliable, grade-sensitive imaging method, but it is limited by low image quality. Currently, DWI quality image is directly related to low gradient amplitudes, since weak gradients must be compensated with long echo times.

METHODS

We propose a new type of MRI accessory, an "inside-out" and nonlinear gradient, whose sole purpose is to deliver diffusion encoding to a region of interest. Performance was simulated in OPERA and the resulting fields were used to simulate DWI with two compartment and kurtosis models. Experiments with a nonlinear head gradient prove the accuracy of DWI and ADC maps diffusion encoded with nonlinear gradients.

RESULTS

Simulations validated thermal and mechanical safety while showing a 5 to 10-fold increase in gradient strength over prostate. With these strengths, lesion CNR in ADC maps approximately doubled for a range of anatomical positions. Proof-of-principle experiments show that spatially varying b-values can be corrected for accurate DWI and ADC.

CONCLUSIONS

Dedicated nonlinear diffusion encoding hardware could improve prostate DWI.

Measured Multipoint Ultra-High b-Value Diffusion MRI in the Assessment of MRI-Detected Prostate Lesions

OBJECTIVES

The aim of this study was to assess quantitative ultra-high b-value (UHB) diffusion magnetic resonance imaging (MRI)-derived parameters in comparison to standard clinical apparent diffusion coefficient (SD-ADC-2b-1000, SD-ADC-2b-1500) for the prediction of clinically significant prostate cancer, defined as Gleason Grade Group greater than or equal to 2.

MATERIALS AND METHODS

Seventy-three patients who underwent 3-T prostate MRI with diffusion-weighted imaging acquired at b = 50/500/1000/1500s/mm2 and b = 100/500/1000/1500/2250/3000/4000 s/mm2 were included. Magnetic resonance lesions were segmented manually on individual sequences, then matched to targeted transrectal ultrasonography/MRI fusion biopsies. Monoexponential 2-point and multipoint fits of standard diffusion and of UHB diffusion were calculated with incremental b-values. Furthermore, a kurtosis fit with parameters Dapp and Kapp with incremental b-values was obtained. Each parameter was examined for prediction of clinically significant prostate cancer using bootstrapped receiver operating characteristics and decision curve analysis. Parameter models were compared using Vuong test.

RESULTS

Fifty of 73 men (age, 66 years [interquartile range, 61-72]; prostate-specific antigen, 6.6 ng/mL [interquartile range, 5-9.7]) had 64 MRI-detected lesions. The performance of SD-ADC-2b-1000 (area under the curve, 0.82) and SD-ADC-2b-1500 (area under the curve, 0.82) was not statistically different (P = 0.99), with SD-ADC-2b-1500 selected as reference. Compared with the reference model, none of the 19 tested logistic regression parameter models including multipoint and 2-point UHB-ADC, Dapp, and Kapp with incremental b-values of up to 4000 s/mm2 outperformed SD-ADC-2b-1500 (all P's > 0.05). Decision curve analysis confirmed these results indicating no higher net benefit for UHB parameters in comparison to SD-ADC-2b-1500 in the clinically important range from 3% to 20% of cancer threshold probability. Net reduction analysis showed no reduction of MR lesions requiring biopsy.

CONCLUSIONS

Despite evaluation of a large b-value range and inclusion of 2-point, multipoint, and kurtosis models, none of the parameters provided better predictive performance than standard 2-point ADC measurements using b-values 50/1000 or 50/1500. Our results suggest that most of the diagnostic benefits available in diffusion MRI are already represented in an ADC composed of one low and one 1000 to 1500 s/mm2 b-value.

Can the low and high b-value distribution influence the pseudodiffusion parameter derived from IVIM DWI in normal brain?

Background

Our study aims to reveal whether the low b-values distribution, high b-values upper limit, and the number of excitation (NEX) influence the accuracy of the intravoxel incoherent motion (IVIM) parameter derived from multi-b-value diffusion-weighted imaging (DWI) in the brain.

Methods

This prospective study was approved by the local Ethics Committee and informed consent was obtained from each participant. The five consecutive multi-b DWI with different b-value protocols (0–3500 s/mm²) were performed in 22 male healthy volunteers on a 3.0-T MRI system. The IVIM parameters from normal white matter (WM) and gray matter (GM) including slow diffusion coefficient (D), fast perfusion coefficient (D*) and perfusion fraction (f) were compared for differences among defined groups with different IVIM protocols by one-way ANOVA.

Results

The D* and f value of WM or GM in groups with less low b-values distribution (less than or equal to 5 b-values) were significantly lower than ones in any other group with more low b-values distribution (all P <  0.05), but no significant differences among groups with more low b-values distribution (P > 0.05). In addition, no significant differences in the D, D* and f value of WM or GM were found between group with one and more NEX of low b-values distribution (all P > 0.05). IVIM parameters in normal WM and GM strongly depended on the choice of the high b-value upper limit.

Conclusions

Metrics of IVIM parameters can be affected by low and high b value distribution. Eight low b-values distribution with high b-value upper limit of 800–1000 s/mm² may be the relatively proper set when performing brain IVIM studies.

Diffusion-weighted imaging of cervical cancer: Feasibility of ultra-high b-value at 3T

PURPOSE

We sought to evaluate the image quality and compare the signal intensity (SI) and apparent diffusion coefficient (ADC) maps of ultra-high b-value (2000 s/mm²; B2) images against those of 800 s/mm² b-value (B1) images of diffusion-weighted imaging (DWI) for cervical cancer.

METHOD

This study was approved by the institutional review board. Sixty patients diagnosed with cervical cancer by pathology were prospectively included. Female pelvic magnetic resonance imaging was performed using a 3 T magnetic resonance scanner; B1 and B2 images were obtained for evaluation. Two radiologists blinded to the scan parameters evaluated the images for signal loss in the background, spatial distortion, image ghosting, confidence in the lesion delineation, and overall image quality using a 5-point scoring system. The scores were compared using a paired Wilcoxon test. SI was measured in the B1 and B2 images for the tumour and normal reference tissues. Additionally, the SI contrast ratios were calculated and compared using the Mann-Whitney U test, the ADC values of tumours and normal tissues were measured, and the maximum tumour diameters were measured from the B1 and B2 images and compared with those from the T2-weighted images, which was the reference standard.

RESULTS

The signal loss in the background, confidence of the lesion delineation and overall image quality scores were higher for the B2 images than for the B1 images (all p < 0.001). The contrast ratios of the tumour-to-normal SI were also higher for the B2 images than for the B1 images (p < 0.01). The mean ADC values derived from the B2 images showed better correlations with the tumour differentiation grades than those from the B1 images. The tumour diameters measured from the B2 images experienced less bias than those from the B1 images.

CONCLUSIONS

B2 images of DWI are technically feasible to acquire and provide more promising additional information for the delineation of cervical cancer tumours than B1 images of the female pelvis.

Signal Intensity of High B-value Diffusion-weighted Imaging for the Detection of Prostate Cancer

Background:

Diffusion-weighted imaging (DWI) is a main component of multiparametric MRI for prostate cancer detection. Recently, high b value DWI has gained more attention because of its capability for tumor characterization.

Objective:

To assess based on histopathological findings of transrectal ultrasound (TRUS)-guided prostate biopsy as a reference, an increase in signal intensity of prostatic lesions in comparison with normal background tissue on high b-value diffusion-weighted images could be a sign of malignancy.

Material and Methods:

Fifty-three consecutive patients retrospectively included in the study. All patients underwent routine TRUS-guided prostate biopsies involving 12 cores after the magnetic resonance imaging (MRI) examinations. In seventeen patients (n =35 lesions), the prostate cancer was histologically confirmed by TRUS-guided prostate biopsy. The biopsy results of other patients were negative. Signal intensities on the high b-value (1600 s/mm²) images of the peripheral zone, the central gland, and the defined lesions were evaluated using region of interest-based measurements. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for prostate cancer detection using signal intensity of high b value diffusion-weighted images were calculated.

Results:

In the patients with confirmed prostate cancer, fourteen had visually increased SI on the high b-value images. The SI of lesions for these patients was higher than the SI of peripheral zone (22±18%) or central gland (31±20%). In patients with a negative biopsy, eight had visually increased SI on the high b-value images. The SI of lesions for these patients was 23±21% and 35±18% higher than the SI in the peripheral zone and the central gland, respectively. The sensitivity, specificity, PPV, and NPV for prostate cancer using SI of high b value DWI were 71, 87, 62, and 87 %, respectively.

Conclusion:

Visually increased SI on the high b-value images can be an indication of malignancy, although some benign lesions also show this increase in signal intensity.

Differentiating Transition Zone Cancers From Benign Prostatic Hyperplasia by Histogram Analysis of Apparent Diffusion Coefficient Maps With Standard and Ultrahigh b-value Diffusion-weighted MR Imaging

OBJECTIVE

To compare the diagnostic performance of standard and ultrahigh b-value Diffusion-weighted Imaging (DWI) using volumetric histogram analysis in differentiating transition zone (TZ) cancer from benign prostatic hyperplasia (BPH).

METHODS

57 TZ cancer and 61 BPH patients received standard (1000 s/mm) and ultrahigh b-value (2000 s/mm) DWI. The diagnostic ability of ADC histogram parameters derived from two DWI for differentiating TZ cancer from BPH was determined by receiver operating characteristic curve.

RESULTS

Median, minimum, the 10th, 25th percentile ADC in both ADC1000 and ADC2000 and skewness in ADC2000 had significant differences between TZ cancer and BPH (for all, P < 0.05).The 10th percentile ADC showed highest area under the ROC curve (AUC) in both ADC1000 and ADC2000.The 10th percentile ADC of ADC2000 showed significantly higher AUC than did ADC1000 (P = 0.0385).

CONCLUSIONS

The 10th percentile ADC obtained from ultrahigh b-value DWI performed better for differentiating TZ cancer from BPH.

Diagnostic value of high b-value (2000 s/mm2) DWI for thyroid micronodules

The aim of the study was to assess the diagnostic value of high b-value (2000 s/mm) diffusion-weighted imaging (DWI) in differentiating malignant from benign thyroid micronodules.Consecutive patients with thyroid micronodules scheduled for Ultrasound (US)-guided fine-needle aspiration biopsy (FNAB) or surgery were underwent high b-value DWI with 3 b-values: 0, 800, and 2000 s/mm. Signal intensity ratios (SIRs) of thyroid micronodules to adjacent normal thyroid tissue on DWI were measured as SIRb0, SIRb800 and SIRb2000. Apparent diffusion coefficients (ADCs) according to the three different b-values were acquired as: ADCb0-800, ADCb0-2000 and ADCb0-800-2000. The 6 diagnostic indicators were evaluated by receiver operating characteristic (ROC) and diagnostic ability was compared between the high b-value DWI and US.Sixty-two malignant thyroid micronodules (48 patients, 13 men and 35 women, aged 44.8 ± 11.7 years) and 57 benign thyroid micronodules (40 patients, 6 men and 34 women, aged 49.6 ± 12.5 years) were enrolled into the final statistical analysis. Among the alone diagnostic indicators, SIRb2000 had the highest diagnostic ability in differentiating malignant from benign thyroid micronodules with area under curve (AUC) of 0.975, sensitivity of 90.32% and specificity of 96.49%. Compared to US, SIRb2000 had a significantly better diagnostic ability US for thyroid micronodules (P < .001) with dramatically raised positive predict value (96.6% vs 78.9%) and reduced false-positive rate (3.51% vs 26.32%).High b-value (2000 s/mm) DWI can contribute to differentiating malignant from benign thyroid micronodules.

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.

Utility of high b-value (2000 sec/mm2) DWI with RESOLVE in differentiating papillary thyroid carcinomas and papillary thyroid microcarcinomas from benign thyroid nodules

Purpose

The aim of the study was to evaluate the role of high b-value (2000 sec/mm²) diffusion-weighted imaging (DWI) by using Readout Segmentation of Long Variable Echo-trains (RESOLVE) in differentiating papillary thyroid carcinomas (PTCs) and papillary thyroid microcarcinomas (PTMCs) from benign thyroid nodules.

Materials and methods

Consecutive patients with thyroid nodules scheduled for surgery underwent high b-value DWI with 3 b-values: 0, 800 and 2000 sec/mm². Signal intensity ratios (SIRs) of thyroid nodules to adjacent normal thyroid tissue on DWI were measured as: SIR_b0, SIR_b800 and SIR_b2000. Apparent diffusion coefficient (ADC) values based on the 3 different b-values were acquired as: ADC_b0-800, ADC_b0-2000, and ADC_b0-800-2000. The 6 diagnostic indicators were evaluated by receiver operating characteristic (ROC) and diagnostic ability was compared between high b-value DWI and Ultrasound (US).

Results

A total of 52 PTCs including 33 PTMCs (38 patients, 8 men and 30 women, aged 45.68 ± 11.93 years) and 62 benign thyroid nodules (46 patients, 7 men and 39 women, aged 48.73 ± 11.98 years) were enrolled into the final statistical analysis. ADC_b0-800-2000 had the highest diagnostic ability in differentiating PTCs from benign thyroid nodules with area under curve (AUC) of 0.944, sensitivity of 96.15% and specificity of 85.48%, and PTMCs from benign thyroid nodules with AUC of 0.940, sensitivity of 93.94% and specificity of 85.48%. On the strength of lower false-positive rates than US (14.52% vs. 32.26% for PTCs and 14.52% vs. 32.26% for PTMCs), ADC_b0-800-2000 had significantly better diagnostic ability in PTCs (P = 0.002) and PTMCs (P = 0.005).

Conclusion

High b-value (2000 sec/mm²) DWI can contribute to differentiating PTCs and PTMCs from benign thyroid nodules and can be potentially used as an active surveillance imaging method for PTMCs.

Differentiation of prostate cancer and stromal hyperplasia in the transition zone with histogram analysis of the apparent diffusion coefficient

Background Prostate cancer and stromal hyperplasia (SH) in the transition zone (TZ) are difficult to discriminate by conventional magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI). Purpose To investigate the apparent diffusion coefficient (ADC) of prostate cancer and SH in the TZ with histogram analysis and the ability of ADC metrics to differentiate between these two tissues. Material and Methods Thirty-three cancer and 29 SH lesions in the TZ of 54 patients undergoing preoperative DWI (b-value 0, 1000 s/mm²) were analyzed. All the lesions on the MR images were localized based on histopathologic correlations. The 10th, 25th, and 50th percentiles, and the mean ADC values were calculated for the two tissues and compared. The efficiencies of the 10th, 25th, and 50th ADC percentiles in differentiating the two tissues were compared with that of the mean ADC with receiver operating characteristic (ROC) analysis. Results The 10th, 25th, and 50th percentiles and mean ADC values (×10^-3 mm²/s) were 0.86 ± 0.15, 0.89 ± 0.16, 0.94 ± 0.16, and 1.03 ± 0.17 in SH and 0.64 ± 0.12, 0.69 ± 0.12, 0.72 ± 0.16, and 0.83 ± 0.15 in TZ cancer, respectively. The parameters were all significantly lower in cancer than SH. The 10th ADC percentile yielded an area under the ROC curve (AUC) of 0.87 for the differentiation of carcinomas from SH, which was higher than the mean ADC (0.80) ( P < 0.05), and the AUCs of the 25th (0.82) and 50th (0.83) percentiles exhibited no differences from those of the mean ADC ( P > 0.05). Conclusion Histogram analysis of ADC values may potentially improve the differentiation of prostate cancer from SH in the TZ.

PI-RADS version 2: evaluation of diffusion-weighted imaging interpretation between b = 1000 and b = 1500 s mm-2

OBJECTIVE

To investigate the variability of diffusion-weighted imaging (DWI) interpretation of Prostate Imaging Reporting and Data System (PI-RADS) version 2 (v2) in evaluating prostate cancer (PCa).

METHODS

154 patients with PCa underwent multiparametric 3T MRI, followed by radical prostatectomy. DWI with different b values (b = 0, 100, 1000 and 1500 s mm^-2) was obtained. Using the PI-RADS v2, two radiologists independently scored suspicious lesions in each patient and compared DWI of b = 1000 (DWI₁₀₀₀) with 1500 (DWI₁₅₀₀) s mm^-2.

RESULTS

On DWI₁₀₀₀ and DWI₁₅₀₀, the intermethod and interobserver agreements of DWI scores were excellent in all patients (κ ≥ 0.873). In each peripheral zone and transition zone DWI scores, both observers showed excellent intermethod agreement between DWI₁₀₀₀ and DWI₁₅₀₀ (κ ≥ 0.897), and interobserver agreement for DWI₁₀₀₀ and DWI₁₅₀₀ was good to excellent (κ ≥ 0.796). For estimating clinically significant cancer, the area under receiver operating characteristics curves of DWI₁₀₀₀ and DWI₁₅₀₀ were 0.710 and 0.724 for observer 1 (p = 0.11), and 0.649 and 0.656 for observer 2 (p = 0.12), respectively.

CONCLUSION

The PI-RADS v2 scoring at 3T shows excellent agreement between DWI₁₀₀₀ and DWI₁₅₀₀ in evaluating PCa, with excellent inter-observer agreement. Advance in knowledge: DWI using b = 1000 s mm^-2 instead of b = 1500 s mm^-2 reduces examination time or image distortion, with improved the signal-to-noise ratio.

Head-To-Head Comparison Between High- and Standard-b-Value DWI for Detecting Prostate Cancer: A Systematic Review and Meta-Analysis

OBJECTIVE

The purpose of this study was to perform a head-to-head comparison between high-b-value (> 1000 s/mm²) and standard-b-value (800-1000 s/mm²) DWI regarding diagnostic performance in the detection of prostate cancer.

MATERIALS AND METHODS

The MEDLINE and EMBASE databases were searched up to April 1, 2017. The analysis included diagnostic accuracy studies in which high- and standard-b-value DWI were used for prostate cancer detection with histopathologic examination as the reference standard. Methodologic quality was assessed with the revised Quality Assessment of Diagnostic Accuracy Studies tool. Sensitivity and specificity of all studies were calculated and were pooled and plotted in a hierarchic summary ROC plot. Meta-regression and multiple-subgroup analyses were performed to compare the diagnostic performances of high- and standard-b-value DWI.

RESULTS

Eleven studies (789 patients) were included. High-b-value DWI had greater pooled sensitivity (0.80 [95% CI, 0.70-0.87]) (p = 0.03) and specificity (0.92 [95% CI, 0.87-0.95]) (p = 0.01) than standard-b-value DWI (sensitivity, 0.78 [95% CI, 0.66-0.86]); specificity, 0.87 [95% CI, 0.77-0.93] (p < 0.01). Multiple-subgroup analyses showed that specificity was consistently higher for high- than for standard-b-value DWI (p ≤ 0.05). Sensitivity was significantly higher for high- than for standard-b-value DWI only in the following subgroups: peripheral zone only, transition zone only, multiparametric protocol (DWI and T2-weighted imaging), visual assessment of DW images, and per-lesion analysis (p ≤ 0.04).

CONCLUSION

In a head-to-head comparison, high-b-value DWI had significantly better sensitivity and specificity for detection of prostate cancer than did standard-b-value DWI. Multiple-subgroup analyses showed that specificity was consistently superior for high-b-value DWI.

Clinically insignificant prostate cancer suitable for active surveillance according to Prostate Cancer Research International: Active surveillance criteria: Utility of PI-RADS v2

BACKGROUND

Active surveillance (AS) is an important treatment strategy for prostate cancer (PCa). Prostate Imaging-Reporting and Data System (PI-RADS) v2 has been addressed, but few studies have reported the value of PI-RADS v2 for assessing risk stratification in patients with PCa, especially on selecting potential candidates for AS.

PURPOSE

To investigate the utility of PI-RADS v2 and apparent diffusion coefficient (ADC) in evaluating patients with insignificant PCa, who are suitable for AS.

STUDY TYPE

Retrospective.

SUBJECTS

In all, 238 patients with PCa who met the Prostate Cancer Research International: Active Surveillance criteria underwent radical prostatectomy.

FIELD STRENGTH/SEQUENCE

3.0T, including T₂ -weighted, diffusion-weighted, and dynamic contrast-enhanced imaging.

ASSESSMENT

Insignificant cancer was defined histopathologically as an organ-confined disease with a tumor volume <0.5 cm³ without Gleason score 4-5. Patients were divided into two groups based on the PI-RADS v2 and tumor ADC: A, PI-RADS score ≤3 and ADC ≥1.095 × 10^-3 mm² /s; and B, PI-RADS score 4-5 or ADC <1.095 × 10^-3 mm² /s. Preoperative clinical and imaging variables were evaluated regarding the associations with insignificant cancer.

RESULTS

Of the 238 patients, 101 (42.8%) were diagnosed with insignificant cancer on pathological findings. The number of positive cores, prostate-specific antigen density (PSAD), PI-RADS v2 and tumor ADC were significantly associated with insignificant cancer on univariate analysis (P < 0.05). However, multivariate analysis indicated tumor ADC (odds ratio [OR] = 4.57, P < 0.001) and PI-RADS v2 (OR = 3.60, P < 0.001) were independent predictors of insignificant cancer. Area under the receiver operating characteristics curve (AUC) reached 0.803 when PI-RADS v2 (AUC = 0.747) was combined with tumor ADC (AUC = 0.786).

DATA CONCLUSION

The PI-RADS v2 together with tumor ADC may be a useful marker for predicting patients with insignificant PCa when considering AS.

LEVEL OF EVIDENCE

4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1072-1079.

Prostate cancer detection among readers with different degree of experience using ultra-high b-value diffusion-weighted Imaging: Is a non-contrast protocol sufficient to detect significant cancer?

AIM

To evaluate the accuracy of a T2-weighted (T2w) - and a parallel transmit zoomed b = 2000 s/mm2 (b2000) - diffusion-weighted imaging sequence among three readers with different degrees of experience for prostate cancer (Pca) detection.

METHODS

Ninety-three patients with suspected Pca were enrolled. For b2000 a two-dimensional spatially-selective RF pulse using an echo-planar transmit trajectory was applied, and the field of view (FOV) was reduced to one-third. All three readers (Reader A: 7, B 4 and C <1 years of experience in prostate MRI) independently evaluated b2000 with regard to the presence of suspicious lesions that displayed increased signal. The results were compared to histopathology obtained by real-time MR/ultrasound fusion and systematic biopsy.

RESULTS

In 62 patients Pca was confirmed. One significant Pca (Gleason score (GS) 7b) was missed by Reader C. Overall, sensitivity/specificity/positive predictive value/negative predictive value were 90/71/86/79% for Reader A, 87/84/92/76% for Reader B and 85/74/87/72% for Reader C, respectively. Detection rates for significant Pca (GS >7a) were 100/100/94% for Readers A/B/C, respectively. Inter-reader agreement was generally good (Kappa A/B: 0.8; A/C: 0.82; B/C: 0.74).

CONCLUSION

B2000 in combination with a T2w could be useful to detect clinically significant Pca.

KEY POINTS

• Significant prostate cancer using zoomed ultra-high b-value DWI was detected. • Diagnostic performance among readers with different degrees of experience was good. • mp- MRI of the prostate using a comprehensive non-contrast protocol is clinically feasible.

Computer-aided Detection of Prostate Cancer with MRI: Technology and Applications

One in six men will develop prostate cancer in his lifetime. Early detection and accurate diagnosis of the disease can improve cancer survival and reduce treatment costs. Recently, imaging of prostate cancer has greatly advanced since the introduction of multiparametric magnetic resonance imaging (mp-MRI). Mp-MRI consists of T2-weighted sequences combined with functional sequences including dynamic contrast-enhanced MRI, diffusion-weighted MRI, and magnetic resonance spectroscopy imaging. Because of the big data and variations in imaging sequences, detection can be affected by multiple factors such as observer variability and visibility and complexity of the lesions. To improve quantitative assessment of the disease, various computer-aided detection systems have been designed to help radiologists in their clinical practice. This review paper presents an overview of literatures on computer-aided detection of prostate cancer with mp-MRI, which include the technology and its applications. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application.