Feasibility study of computed vs measured high b-value (1400 s/mm²) diffusion-weighted MR images of the prostate

Comparison of synthesized and acquired high b-value diffusion-weighted MRI for detection of prostate cancer

BACKGROUND

High b-value diffusion-weighted images (DWI) are used for detection of clinically significant prostate cancer (csPCa). This study qualitatively and quantitatively compares synthesized DWI (sDWI) to acquired (aDWI) for detection of csPCa.

METHODS

One hundred fifty-one consecutive patients who underwent prostate MRI and biopsy were included in the study. Axial DWI with b = 0, 500, 1000, and 2000 s/mm2 using a 3T clinical scanner using a 32-channel phased-array body coil were acquired. We retrospectively synthesized DWI for b = 2000 s/mm2 via extrapolation based on mono-exponential decay, using b = 0 and b = 500 s/mm2 (sDWI500) and b = 0, b = 500 s/mm2, and b = 1000 s/mm2 (sDWI1000). Differences in signal intensity between sDWI and aDWI were evaluated within different regions of interest (prostate alone, prostate plus 5 mm, 30 mm and 70 mm margin and full field of view). The maximum DWI value within each ROI was evaluated for prediction of csPCa. Classification accuracy was compared to Restriction Spectrum Imaging restriction score (RSIrs), a previously validated biomarker based on multi-exponential DWI. Discrimination of csPCa was evaluated via area under the receiver operating characteristic curve (AUC).

RESULTS

Within the prostate, mean ± standard deviation of percent mean differences between sDWI and aDWI signal were -46 ± 35% for sDWI1000 and -67 ± 24% for sDWI500. AUC for aDWI, sDWI500, sDWI1000, and RSIrs within the prostate 0.62[95% confidence interval: 0.53, 0.71], 0.63[0.54, 0.72], 0.65[0.56, 0.73] and 0.78[0.71, 0.86], respectively.

CONCLUSION

sDWI is qualitatively comparable to aDWI within the prostate. However, hyperintense artifacts are introduced with sDWI in the surrounding pelvic tissue that interfere with quantitative cancer detection and might mask metastases. In the prostate, RSIrs yields superior quantitative csPCa detection than sDWI or aDWI.

Strategies for improving image quality in prostate MRI

Prostate magnetic resonance imaging (MRI) stands as the cornerstone in diagnosing prostate cancer (PCa), offering superior detection capabilities while minimizing unnecessary biopsies. Despite its critical role, global disparities in MRI diagnostic performance persist, stemming from variations in image quality and radiologist expertise. This manuscript reviews the challenges and strategies for enhancing image quality in prostate MRI, spanning patient preparation, MRI unit optimization, and radiology team engagement. Quality assurance (QA) and quality control (QC) processes are pivotal, emphasizing standardized protocols, meticulous patient evaluation, MRI unit workflow, and radiology team performance. Additionally, artificial intelligence (AI) advancements offer promising avenues for improving image quality and reducing acquisition times. The Prostate-Imaging Quality (PI-QUAL) scoring system emerges as a valuable tool for assessing MRI image quality. A comprehensive approach addressing technical, procedural, and interpretative aspects is essential to ensure consistent and reliable prostate MRI outcomes.

Update on Optimization of Prostate MR Imaging Technique and Image Quality

Prostate MR imaging quality has improved dramatically over recent times, driven by advances in hardware, software, and improved functional imaging techniques. MRI now plays a key role in prostate cancer diagnostic work-up, but outcomes of the MRI-directed pathway are heavily dependent on image quality and optimization. MR sequences can be affected by patient-related degradations relating to motion and susceptibility artifacts which may enable only partial mitigation. In this Review, we explore issues relating to prostate MRI acquisition and interpretation, mitigation strategies at a patient and scanner level, PI-QUAL reporting, and future directions in image quality, including artificial intelligence solutions.

Enhanced Image Processing Using Complex Averaging in Diffusion-Weighted Imaging of the Prostate: The Impact on Image Quality and Lesion Detectability

Diffusion-weighted images of the prostate can suffer from a "hazy" background in low signal-intensity areas. We hypothesize that enhanced image processing (EIP) using complex averaging reduces artifacts, noise, and distortion in conventionally acquired diffusion-weighted images and synthesized high b-value images, thus leading to higher image quality and better detection of potentially malignant lesions. Conventional DWI trace images with a b-value of 1000 s/mm² (b1000), calculated images with a b-value of 2000 s/mm² (cb2000), and ADC maps of 3T multiparametric prostate MRIs in 53 patients (age 68.8 ± 10 years) were retrospectively evaluated. Standard images were compared to images using EIP. In the standard images, 36 lesions were detected in the peripheral zone and 20 in the transition zone. In 13 patients, EIP led to the detection of 8 additional lesions and the upgrading of 6 lesions; 6 of these patients were diagnosed with prostate carcinoma Gleason 7 or 8. EIP improved qualitative ratings for overall image quality and lesion detectability. Artifacts were significantly reduced in the cb2000 images. Quantitative measurements for lesion detectability expressed as an SI ratio were significantly improved. EIP using complex averaging led to image quality improvements in acquired and synthesized DWI, potentially resulting in elevated diagnostic accuracy and management changes.

Staging of Prostate Cancer: Role of Multiparametric Magnetic Resonance Imaging in Different Risk Classes

Using multiparametric magnetic resonance imaging, it is now possible to diagnose prostate cancer and categorize its risk. As it can accurately determine the extracapsu- lar extension of the tumor, invasion of seminal vesicles, involvement of lymph nodes, and the potential presence of bone metastases, multiparametric magnetic resonance imaging plays a crucial role not only in the diagnosis but also in the local staging of prostate cancer. The patients with a history of negative biopsy/increasing prostate- specific antigen and the existence of further data supporting its use in biopsy-naive patients and active surveillance are the most blatant indications for multiparametric magnetic resonance imaging in guidelines. The traditional clinical examination, pros- tate-specific antigen tests, and systematic biopsy are all enhanced by multiparametric magnetic resonance imaging, which will miss certain cancers due to insufficient size or changes in tissue density. The use of multiparametric magnetic resonance imaging is expected to rise, and further advances in the method will be crucial for the secure adoption of targeted therapeutic ideas. Here, we give a succinct overview of multipa- rametric magnetic resonance imaging's application to the identification and risk clas- sification of prostate cancer.

Evaluating Biliary Malignancy with Measured and Calculated Ultra-high b-value Diffusion-weighted MR Imaging at 3T

PURPOSE

Although diffusion-weighted imaging (DWI) with ultra-high b-values is reported to be advantageous in the detection of some tumors, its applicability is not yet known in biliary malignancy. Therefore, this study aimed to evaluate the impact of measured b = 1400 s/mm² (M1400) and calculated b = 1400 s/mm² (C1400) DWI on image quality and quality of lesion discernibility using a modern 3T MR system compared to conventional b = 800 s/mm² DWI (M800).

METHODS

We evaluated 56 patients who had pathologically proven biliary malignancy. All the patients underwent preoperative or baseline 3T MRI using DWI (b = 50, 400, 800, and 1400 s/mm²). The calculated DWI was obtained using a conventional DWI set (b = 50, 400, and 800). The tumor-to-bile contrast ratio (CR) and tumor SNR were compared between the different DWI images. Likert scores were given on a 5-point scale to assess the overall image quality, overall artifacts, ghost artifacts, misregistration artifacts, margin sharpness, and lesion discernibility. Repeated-measures analysis of variance with post hoc analyses was used for statistical evaluations.

RESULTS

The CR of the tumor-to-bile was significantly higher in both M1400 and C1400 than in M800 (P^a < 0.01). SNRs were significantly higher in M800, followed by C1400 and M1400 (P^a < 0.01). Lesion discernibility was significantly improved for M1400, followed by C1400 and M800 for both readers (P^a < 0.01).

CONCLUSION

Using a 3T MRI, both measured and calculated DWI with an ultra-high b-value offer superior lesion discernibility for biliary malignancy compared to the conventional DWI.

Comparison of synthesized and acquired high b -value diffusion-weighted MRI for detection of prostate cancer

Background

High b -value diffusion-weighted images (DWI) are used for detection of clinically significant prostate cancer (csPCa). To decrease scan time and improve signal-to-noise ratio, high b -value (>1000 s/mm 2 ) images are often synthesized instead of acquired.

Purpose

Qualitatively and quantitatively compare synthesized DWI (sDWI) to acquired (aDWI) for detection of csPCa.

Study Type

Retrospective.

Subjects

151 consecutive patients who underwent prostate MRI and biopsy.

Sequence

Axial DWI with b =0, 500, 1000, and 2000 s/mm 2 using a 3T clinical scanner using a 32-channel phased-array body coil.

Assessment

We synthesized DWI for b =2000 s/mm 2 via extrapolation based on monoexponential decay, using b =0 and b =500 s/mm 2 (sDWI 500 ) and b =0, b =500, and b =1000 s/mm 2 (sDWI 1000 ). Differences between sDWI and aDWI were evaluated within regions of interest (ROIs). The maximum DWI value within each ROI was evaluated for prediction of csPCa. Classification accuracy was also compared to Restriction Spectrum Imaging restriction score (RSIrs), a previously validated biomarker based on multi-exponential DWI.

Statistical Tests

Discrimination of csPCa was evaluated via area under the receiver operating characteristic curve (AUC). Statistical significance was assessed using bootstrap difference (two-sided α=0.05).

Results

Within the prostate, mean ± standard deviation of percent mean differences between sDWI and aDWI signal were -46±35% for sDWI 1000 and -67±24% for sDWI 500 . AUC for aDWI, sDWI 500, sDWI 1000 , and RSIrs within the prostate 0.62[95% confidence interval: 0.53, 0.71], 0.63[0.54, 0.72], 0.65[0.56, 0.73] and 0.78[0.71, 0.86], respectively. When considering the whole field of view, classification accuracy and qualitative image quality decreased notably for sDWI compared to aDWI and RSIrs.

Data Conclusion

sDWI is qualitatively comparable to aDWI within the prostate. However, hyperintense artifacts are introduced with sDWI in the surrounding pelvic tissue that interfere with quantitative cancer detection and might mask metastases. In the prostate, RSIrs yields superior quantitative csPCa detection than sDWI or aDWI.

Advanced Diffusion-Weighted Imaging Sequences for Breast MRI: Comprehensive Comparison of Improved Sequences and Ultra-High B-Values to Identify the Optimal Combination

This study investigated the image quality and choice of ultra-high b-value of two DWI breast-MRI research applications. The study cohort comprised 40 patients (20 malignant lesions). In addition to s-DWI with two m-b-values (b50 and b800) and three e-b-values (e-b1500, e-b2000, and e-b2500), z-DWI and IR m-b1500 DWI were applied. z-DWI was acquired with the same measured b-values and e-b-values as the standard sequence. For IR m-b1500 DWI, b50 and b1500 were measured, and e-b2000 and e-b2500 were mathematically extrapolated. Three readers used Likert scales to independently analyze all ultra-high b-values (b1500-b2500) for each DWI with regards to scan preference and image quality. ADC values were measured in all 20 lesions. z-DWI was the most preferred (54%), followed by IR m-b1500 DWI (46%). b1500 was significantly preferred over b2000 for z-DWI and IR m-b1500 DWI (p = 0.001 and p = 0.002, respectively). Lesion detection was not significantly different among sequences or b-values (p = 0.174). There were no significant differences in measured ADC values within lesions between s-DWI (ADC: 0.97 [±0.09] × 10^-3 mm²/s) and z-DWI (ADC: 0.99 [±0.11] × 10^-3 mm²/s; p = 1.000). However, there was a trend toward lower values in IR m-b1500 DWI (ADC: 0.80 [±0.06] × 10^-3 mm²/s) than in s-DWI (p = 0.090) and z-DWI (p = 0.110). Overall, image quality was superior and there were fewer image artifacts when using the advanced sequences (z-DWI + IR m-b1500 DWI) compared with s-DWI. Considering scan preferences, we found that the optimal combination was z-DWI with a calculated b1500, especially regarding examination time.

Impact of enema prep on the false-negative rate of a PI-RADS 1 MRI of the prostate for clinically significant prostate cancer

PURPOSE

To investigate whether use of an enema prep reduces the false-negative (FN) rate of PI-RADS 1 MRI of the prostate for clinically significant prostate cancer (csPCa).

MATERIALS AND METHODS

1108 consecutive patients with a PI-RADS 1 MRI performed 01/2016-09/2021 were retrospectively collected. Patient charts were examined for subsequent systematic prostate biopsy performed within 1 year if positive or anytime thereafter if negative. Patients without biopsy were excluded. Use of an enema prep 1-2 h before MRI, which was implemented in 03/2019, was recorded. FN rate of MRI for detection of csPCa, defined as Gleason score ≥ 7, using systematic biopsy was assessed per patient and compared between those with and without an enema prep. Χ² test and logistic regression were performed.

RESULTS

255 patients (median age 64, IQR 58-69) with median PSA 5.6 (IQR 4.2-8.1), PI-RADS 1 MRI, and subsequent biopsy were included in the analysis. 66 patients (26%) had an enema prep and 189 patients (74%) did not. 7 (11%) patients with and 21 (11%) patients without enema prep had a FN biopsy. There was no significant association between enema prep and FN biopsy (OR 0.95, 95% CI 0.38-2.35, p = 0.91).

CONCLUSIONS

Use of an enema prep prior to prostate MRI did not decrease the FN rate of PI-RADS 1 MRI of the prostate for clinically significant prostate cancer.

Multi-Parametric Magnetic Resonance Imaging-Based Radiomics Analysis of Cervical Cancer for Preoperative Prediction of Lymphovascular Space Invasion

Background

Detection of lymphovascular space invasion (LVSI) in early cervical cancer (CC) is challenging. To date, no standard clinical markers or screening tests have been used to detect LVSI preoperatively. Therefore, non-invasive risk stratification tools are highly desirable.

Objective

To train and validate a multi-parametric magnetic resonance imaging (mpMRI)-based radiomics model to detect LVSI in patients with CC and investigate its potential as a complementary tool to enhance the efficiency of risk assessment strategies.

Materials and Methods

The model was developed from the tumor volume of interest (VOI) of 125 patients with CC. A total of 1037 radiomics features obtained from conventional magnetic resonance imaging (MRI), including a small field-of-view (sFOV) high-resolution (HR)-T2-weighted MRI (T2WI), apparent diffusion coefficient (ADC), T2WI, fat-suppressed (FS)-T2WI, as well as axial and sagittal contrast-enhanced T1-weighted MRI (T1c). We conducted a radiomics-based characterization of each tumor region using pretreatment image data. Feature selection was performed using the least absolute shrinkage and selection operator method on the training set. The predictive performance was compared with single variates (clinical data and single-layer radiomics signatures) analyzed using a receiver operating characteristic (ROC) curve. Three-fold cross-validation performed 20 times was used to evaluate the accuracy of the trained classifiers and the stability of the selected features. The models were validated by using a validation set.

Results

Feature selection extracted the six most important features (3 from sFOV HR-T2WI, 1 T2WI, 1 FS-T2WI, and 1 T1c) for model construction. The mpMRI-combined radiomics model (area under the curve [AUC]: 0.940) reached a significantly higher performance (better than the clinical parameters [AUC: 0.730]), including any single-layer model using sFOV HR-T2WI (AUC: 0.840), T2WI (AUC: 0.770), FS-T2WI (AUC: 0.710), ADC maps (AUC: 0.650), sagittal, and axial T1c values (AUC: 0.710, 0.680) in the validation set.

Conclusion

Biomarkers using multi-parametric radiomics features derived from preoperative MR images could predict LVSI in patients with CC.

High-Resolution, High b-Value Computed Diffusion-Weighted Imaging Improves Detection of Pancreatic Ductal Adenocarcinoma

Background: Our purpose was to investigate the potential of high-resolution, high b-value computed DWI (cDWI) in pancreatic ductal adenocarcinoma (PDAC) detection. Materials and Methods: We retrospectively enrolled 44 patients with confirmed PDAC. Respiratory-triggered, diffusion-weighted, single-shot echo-planar imaging (ss-EPI) with both conventional (i.e., full field-of-view, 3 × 3 × 4 mm voxel size, b = 0, 50, 300, 600 s/mm2) and high-resolution (i.e., reduced field-of-view, 2.5 × 2.5 × 3 mm voxel size, b = 0, 50, 300, 600, 1000 s/mm2) imaging was performed for suspected PDAC. cDWI datasets at b = 1000 s/mm2 were generated for the conventional and high-resolution datasets. Three radiologists were asked to subjectively rate (on a Likert scale of 1–4) the following metrics: image quality, lesion detection and delineation, and lesion-to-pancreas intensity relation. Furthermore, the following quantitative image parameters were assessed: apparent signal-to-noise ratio (aSNR), contrast-to-noise ratio (aCNR), and lesion-to-pancreas contrast ratio (CR). Results: High-resolution, high b-value computed DWI (r-cDWI1000) enabled significant improvement in lesion detection and a higher incidence of a high lesion-to-pancreas intensity relation (type 1, clear hyperintense) compared to conventional high b-value computed and high-resolution high b-value acquired DWI (f-cDWI1000 and r-aDWI1000, respectively). Image quality was rated inferior in the r-cDWI1000 datasets compared to r-aDWI1000. Furthermore, the aCNR and CR were higher in the r-cDWI1000 datasets than in f-cDWI1000 and r-aDWI1000. Conclusion: High-resolution, high b-value computed DWI provides significantly better visualization of PDAC compared to the conventional high b-value computed and high-resolution high b-value images acquired by DWI.

Synthesizing High-b-Value Diffusion-weighted Imaging of the Prostate Using Generative Adversarial Networks

Purpose

To develop and evaluate a diffusion-weighted imaging (DWI) deep learning framework based on the generative adversarial network (GAN) to generate synthetic high-b-value (b =1500 sec/mm²) DWI (SYN_b1500) sets from acquired standard-b-value (b = 800 sec/mm²) DWI (ACQ_b800) and acquired standard-b-value (b = 1000 sec/mm²) DWI (ACQ_b1000) sets.

Materials and Methods

This retrospective multicenter study included 395 patients who underwent prostate multiparametric MRI. This cohort was split into internal training (96 patients) and external testing (299 patients) datasets. To create SYN_b1500 sets from ACQ_b800 and ACQ_b1000 sets, a deep learning model based on GAN (M₀) was developed by using the internal dataset. M₀ was trained and compared with a conventional model based on the cycle GAN (M_cyc). M₀ was further optimized by using denoising and edge-enhancement techniques (optimized version of the M₀ [Opt-M₀]). The SYN_b1500 sets were synthesized by using the M₀ and the Opt-M₀ were synthesized by using ACQ_b800 and ACQ_b1000 sets from the external testing dataset. For comparison, traditional calculated (b =1500 sec/mm²) DWI (CAL_b1500) sets were also obtained. Reader ratings for image quality and prostate cancer detection were performed on the acquired high-b-value (b = 1500 sec/mm²) DWI (ACQ_b1500), CAL_b1500, and SYN_b1500 sets and the SYN_b1500 set generated by the Opt-M₀ (Opt-SYN_b1500). Wilcoxon signed rank tests were used to compare the readers' scores. A multiple-reader multiple-case receiver operating characteristic curve was used to compare the diagnostic utility of each DWI set.

Results

When compared with the M_cyc, the M₀ yielded a lower mean squared difference and higher mean scores for the peak signal-to-noise ratio, structural similarity, and feature similarity (P < .001 for all). Opt-SYN_b1500 resulted in significantly better image quality (P ≤ .001 for all) and a higher mean area under the curve than ACQ_b1500 and CAL_b1500 (P ≤ .042 for all).

Conclusion

A deep learning framework based on GAN is a promising method to synthesize realistic high-b-value DWI sets with good image quality and accuracy in prostate cancer detection.Keywords: Prostate Cancer, Abdomen/GI, Diffusion-weighted Imaging, Deep Learning Framework, High b Value, Generative Adversarial Networks© RSNA, 2021 Supplemental material is available for this article.

Integrated slice-specific dynamic shimming diffusion weighted imaging (DWI) for rectal Cancer detection and characterization

PURPOSE

To compare integrated slice-specific dynamic shimming (iShim) diffusion weighted imaging (DWI) and single-shot echo-planar imaging (SS-EPI) DWI in image quality and pathological characterization of rectal cancer.

MATERIALS AND METHODS

A total of 193 consecutive rectal tumor patients were enrolled for retrospective analysis. Among them, 101 patients underwent iShim-DWI (b = 0, 800, and 1600 s/mm²) and 92 patients underwent SS-EPI-DWI (b = 0, and 1000 s/mm²). Qualitative analyses of both DWI techniques was performed by two independent readers; including adequate fat suppression, the presence of artifacts and image quality. Quantitative analysis was performed by calculating standard deviation (SD) of the gluteus maximus, signal intensity (SI) of lesion and residual normal rectal wall, apparent diffusion coefficient (ADC) values (generated by b values of 0, 800 and 1600 s/mm² for iShim-DWI, and by b values of 0 and 1000 s/mm² for SS-EPI-DWI) and image quality parameters, such as signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of primary rectal tumor. For the primary rectal cancer, two pathological groups were divided according to pathological results: Group 1 (well-differentiated) and Group 2 (poorly differentiated). Statistical analyses were performed with p < 0.05 as significant difference.

RESULTS

Compared with SS-EPI-DWI, significantly higher scores of image quality were obtained in iShim-DWI cases (P < 0.001). The SD_background was significantly reduced on b = 1600 s/mm² images and ADC maps of iShim-DWI. Both SNR and CNR of b = 800 s/mm² and b = 1600 s/mm² images in iShim-DWI were higher than those of b = 1000 s/mm² images in SS-EPI-DWI. In primary rectal cancer of iShim-DWI cohort, SI_lesion was significantly higher than SI_rectum in both b = 800 and 1600 s/mm² images. ADC values were significantly lower in Group 2 (0.732 ± 0.08) × 10^- 3 mm²/s) than those in Group 1 ((0.912 ± 0.21) × 10^- 3 mm²/s). ROC analyses showed significance of ADC values and SI_lesion between the two groups.

CONCLUSION

iShim-DWI with b values of 0, 800 and 1600 s/mm² is a promising technique of high image quality in rectal tumor imaging, and has potential ability to differentiate rectal cancer from normal wall and predicting pathological characterization.

Multiparametric MRI in the Diagnosis of Prostate Cancer: Physical Foundations, Limitations, and Prospective Advances of Diffusion-Weighted MRI

BACKGROUND

 Diffusion-weighted imaging (DWI) is an essential component of the multiparametric MRI exam for the diagnosis and assessment of prostate cancer (PCa). Over the last two decades, various models have been developed to quantitatively correlate the DWI signal with microstructural characteristics of prostate tissue. The simplest approach (ADC: apparent diffusion coefficient) - currently established as the clinical standard - describes monoexponential decay of the DWI signal. While numerous studies have shown an inverse correlation of ADC values with the Gleason score, the ADC model lacks specificity and is based on water diffusion dynamics that are not true in human tissue. This article aims to explain the biophysical limitations of the standard DWI model and to discuss the potential of more complex, advanced DWI models.

METHODS

 This article is a review based on a selective literature review.

RESULTS

 Four phenomenological DWI models are introduced: diffusion tensor imaging, intravoxel incoherent motion, biexponential model, and diffusion kurtosis imaging. Their parameters may potentially improve PCa diagnostics but show varying degrees of statistical significance with respect to the detection and characterization of PCa in current studies. Phenomenological model parameters lack specificity, which has motivated the development of more descriptive tissue models that directly relate microstructural features to the DWI signal. Finally, we present two of such structural models, i. e. the VERDICT (Vascular, Extracellular, and Restricted Diffusion for Cytometry in Tumors) and RSI (Restriction Spectrum Imaging) model. Both have shown promising results in initial studies regarding the characterization and prognosis of PCa.

CONCLUSION

 Recent developments in DWI techniques promise increasing accuracy and more specific statements about microstructural changes of PCa. However, further studies are necessary to establish a standardized DWI protocol for the diagnosis of PCa.

KEY POINTS

  · DWI is paramount to the mpMRI exam for the diagnosis of PCa.. · Though of clinical value, the ADC model lacks specificity and oversimplifies tissue complexities.. · Advanced phenomenological and structural models have been developed to describe the DWI signal.. · Phenomenological models may improve diagnostics but show inconsistent results regarding PCa assessment.. · Structural models have demonstrated promising results in initial studies regarding PCa characterization..

CITATION FORMAT

· Wichtmann BD, Zöllner FG, Attenberger UI et al. Multiparametric MRI in the Diagnosis of Prostate Cancer: Physical Foundations, Limitations, and Prospective Advances of Diffusion-Weighted MRI. Fortschr Röntgenstr 2021; 193: 399 - 409.

Feasibility Study of Synthetic Diffusion-Weighted MRI in Patients with Breast Cancer in Comparison with Conventional Diffusion-Weighted MRI

OBJECTIVE

To investigate the clinical feasibility of synthetic diffusion-weighted imaging (sDWI) at different b-values in patients with breast cancer by assessing the diagnostic image quality and the quantitative measurements compared with conventional diffusion-weighted imaging (cDWI).

MATERIALS AND METHODS

Fifty patients with breast cancer were assessed using cDWI at b-values of 800 and 1500 s/mm² (cDWI₈₀₀ and cDWI₁₅₀₀) and sDWI at b-values of 1000 and 1500 s/mm² (sDWI₁₀₀₀ and sDWI₁₅₀₀). Qualitative analysis (normal glandular tissue suppression, overall image quality, and lesion conspicuity) was performed using a 4-point Likert-scale for all DWI sets and the cancer detection rate (CDR) was calculated. We also evaluated cancer-to-parenchyma contrast ratios for each DWI set in 45 patients with the lesion identified on any of the DWI sets. Statistical comparisons were performed using Friedman test, one-way analysis of variance, and Cochran's Q test.

RESULTS

All parameters of qualitative analysis, cancer-to-parenchyma contrast ratios, and CDR increased with increasing b-values, regardless of the type of imaging (synthetic or conventional) (p < 0.001). Additionally, sDWI₁₅₀₀ provided better lesion conspicuity than cDWI₁₅₀₀ (3.52 ± 0.92 vs. 3.39 ± 0.90, p < 0.05). Although cDWI₁₅₀₀ showed better normal glandular tissue suppression and overall image quality than sDWI₁₅₀₀ (3.66 ± 0.78 and 3.73 ± 0.62 vs. 3.32 ± 0.90 and 3.35 ± 0.81, respectively; p < 0.05), there was no significant difference in their CDR (90.0%). Cancer-to-parenchyma contrast ratios were greater in sDWI₁₅₀₀ than in cDWI₁₅₀₀ (0.63 ± 0.17 vs. 0.55 ± 0.18, p < 0.001).

CONCLUSION

sDWI₁₅₀₀ can be feasible for evaluating breast cancers in clinical practice. It provides higher tumor conspicuity, better cancer-to-parenchyma contrast ratio, and comparable CDR when compared with cDWI₁₅₀₀.

Advanced zoomed diffusion-weighted imaging vs. full-field-of-view diffusion-weighted imaging in prostate cancer detection: a radiomic features study

OBJECTIVES

We aimed to compare the efficiency of prostate cancer (PCa) detection using a radiomics signature based on advanced zoomed diffusion-weighted imaging and conventional full-field-of-view DWI.

METHODS

A total of 136 patients, including 73 patients with PCa and 63 without PCa, underwent multi-parametric magnetic resonance imaging (mp-MRI). Radiomic features were extracted from prostate lesion areas segmented on full-field-of-view DWI with b-value = 1500 s/mm² (f-DWI_b1500), advanced zoomed DWI images with b-value = 1500 s/mm² (z-DWI_b1500), calculated zoomed DWI with b-value = 2000 s/mm² (z-calDWI_b2000), and apparent diffusion coefficient (ADC) maps derived from both sequences (f-ADC and z-ADC). Single-imaging modality radiomics signature, mp-MRI radiomics signature, and a mixed model based on mp-MRI and clinically independent risk factors were built to predict PCa probability. The diagnostic efficacy and the potential net benefits of each model were evaluated.

RESULTS

Both z-DWI_b1500 and z-calDWI_b2000 had significantly better predictive performance than f-DWIb1500 (z-DWIb1500 vs. f-DWIb1500: p = 0.048; z-calDWIb2000 vs. f-DWIb1500: p = 0.014). z-ADC had a slightly higher area under the curve (AUC) value compared with f-ADC value but was not significantly different (p = 0.127). For predicting the presence of PCa, the AUCs of clinical independent risk factors model, mp-MRI model, and mixed model were 0.81, 0.93, and 0.94 in training sets, and 0.74, 0.92, and 0.93 in validation sets, respectively.

CONCLUSION

Radiomics signatures based on the z-DWI technology had better diagnostic accuracy for PCa than that based on the f-DWI technology. The mixed model was better at diagnosing PCa and guiding clinical interventions for patients with suspected PCa compared with mp-MRI signatures and clinically independent risk factors.

KEY POINTS

• Advanced zoomed DWI technology can improve the diagnostic accuracy of radiomics signatures for PCa. • Radiomics signatures based on z-calDWI_b2000 have the best diagnostic performance among individual imaging modalities. • Compared with the independent clinical risk factors and the mp-MRI model, the mixed model has the best diagnostic efficiency.

Prostate magnetic resonance imaging technique

Multiparametric magnetic resonance (MR) imaging of the prostate is an excellent tool to detect clinically significant prostate cancer, and it has widely been incorporated into clinical practice due to its excellent tissue contrast and image resolution. The aims of this article are to describe the prostate MR imaging technique for detection of clinically significant prostate cancer according to PI-RADS v2.1, as well as alternative sequences and basic aspects of patient preparation and MR imaging artifact avoidance.

Editorial for "Qualitative and Quantitative Reporting of a Unique Biparametric MRI: Towards Biparametric MRI-Based Nomograms for Prediction of Prostate Biopsy Outcome in Men With a Clinical Suspicion of Prostate Cancer (IMPROD and MULTI-IMPROD Trials)"

LEVEL OF EVIDENCE

5 Technical Efficacy Stage: 5 J. Magn. Reson. Imaging 2020;51:1568-1569.

Usefulness of Bi-Parametric Magnetic Resonance Imaging with b=1,800 s/mm² Diffusion-Weighted Imaging for Diagnosing Clinically Significant Prostate Cancer

Purpose

This study was conducted to compare the accuracy of bi-parametric magnetic resonance imaging (bpMRI) with high b-value (b=1,000 s/mm², b1000) diffusion-weighted imaging (DWI) to that of bpMRI with ultra-high b-value (b=1,800 s/mm², b1800) DWI to detect clinically significant prostate cancer (csPCa).

Materials and Methods

A total of 408 patients with suspected PCa were evaluated by bpMRI prior to biopsy. One reader retrospectively reviewed all images for confirmation of Prostate Imaging–Reporting and Data System (PI-RADS) score. Cognitive magnetic resonance/ultrasound fusion target biopsy was done for all visible lesions (PI-RADS 3–5). Systematic biopsy was done for all cases. The csPCa detection rates were compared according to the bpMRI protocol (with/without b1800 DWI) or PI-RADS score. The accuracy of PI-RADS score was estimated using receiver operating characteristics curve. The signal intensity (SI) ratio (visible lesion/surrounding background) was evaluated.

Results

Among 164 men confirmed having PCa, 102 had csPCa (Gleason score≥7). Proportions of PI-RADS score 1–2/3/4/5 without b1800 DWI (n=133) and with b1800 DWI (n=275) were 19.5%/57.9%/15.8%/6.8% and 21.1%/48.7%/22.2%/8.0%, respectively. csPCa detection rates with/without b1800 DWI were 27.6%/19.5% (p=0.048), respectively. Areas under the curve of PI-RADS grading with/without b1800 DWI for csPCa detection were 0.885 and 0.705, respectively. The SI ratio in b1800 DWI was higher than that in b1000 DWI (p<0.001).

Conclusions

Adding b1800 DWI to bpMRI protocol improved the diagnostic accuracy and detection rate of csPCa. The higher SI ratio (lesion/background) in b1800 DWI enabled clearer identification of lesions.

Image quality and diagnostic accuracy of complex-averaged high b value images in diffusion-weighted MRI of prostate cancer

PURPOSE

To evaluate the impact of complex-averaging on image quality (IQ) and diagnostic accuracy of acquired and calculated high b value (aHBV, cHBV) images in diffusion-weighted prostate MRI.

MATERIALS AND METHODS

This retrospective study included 84 patients who underwent multiparametric prostate MRI at 3 Tesla without endorectal coil. DWIs were acquired at three different b values which included two lower b values (b = 50,900 s/mm²) and one higher b value (aHBV at 2000 s/mm²). The acquired data were postprocessed to generate two different types of trace-weighted images-using conventional magnitude-averaging and complex-averaging. Using lower b values (b = 50,900 s/mm²) from both conventional and complex-averaged image sets, cHBV images (b = 2000 s/mm²) and ADC maps were derived. All image sets were reviewed by two radiologists in different reading sessions to assess image quality and PIRADS. The diagnostic accuracy of different image sets for the detection of prostate lesions was performed by correlating PIRADS and Gleason scores.

RESULTS

Complex-averaging did not impact ADC values of the prostate lesions compared to magnitude-averaging (P = 0.08). Complex-averaging improved image quality of acquired high b value and calculated high b value images (P < 0.0001). Complex-averaging also improved the level of confidence (LOC) of the acquired high b value for both readers (P < 0.0001, P < 0.05), but only for reader A in calculated high b value (P < 0.0001). The image quality of calculated high b value images was not significantly different than acquired high b value images. The dataset combining complex-averaging and calculated high b value provided the highest diagnostic accuracy (but not statistically significant) for detection of the significant prostate lesion compared to the magnitude-averaged acquired high b value (79.55% vs. 72.73%; P = 0.317). The mean acquisition time for b = 2000 s/mm² sequence (aHBV) was 6 min 30 s (± 1 min 16 s) out of a total of 28 min 31 s (± 4 min 26 s) for the entire mp-MRI protocol (approximately 25% of total scan time).

CONCLUSION

Complex-averaging provides better image quality and level of confidence without significant impact on ADC values and diagnostic accuracy for detection of the significant prostate lesions . The calculated high b value images are also comparable to (and can substitute) the acquired high b value images which can help in reducing the imaging time.

Diffusion-Weighted MRI of Breast Cancer: Improved Lesion Visibility and Image Quality Using Synthetic b-Values

BACKGROUND

Diffusion-weighted imaging (DWI) is an MRI technique with the potential to serve as an unenhanced breast cancer detection tool. Synthetic b-values produce images with high diffusion weighting to suppress residual background signal, while avoiding additional measurement times and reducing artifacts.

PURPOSE

To compare acquired DWI images (at b = 850 s/mm² ) and different synthetic b-values (at b = 1000-2000 s/mm² ) in terms of lesion visibility, image quality, and tumor-to-tissue contrast in patients with malignant breast tumors.

STUDY TYPE

Retrospective.

POPULATION

Fifty-three females with malignant breast lesions.

FIELD STRENGTH/SEQUENCE

T₂ w, DWI EPI with STIR fat-suppression, and dynamic contrast-enhanced T₁ w at 3T.

ASSESSMENT

From acquired images using b-values of 50 and 850 s/mm² , synthetic images were calculated at b = 1000, 1200, 1400, 1600, 1800, and 2000 s/mm² . Four readers independently rated image quality, lesion visibility, preferred b-value, as well as the lowest and highest b-value, over the range of b-values tested, to provide a diagnostic image.

STATISTICAL TESTS

Medians and mean ranks were calculated and compared using the Friedman test and Wilcoxon signed-rank test. Reproducibility was analyzed by intraclass correlation (ICC), Fleiss, and Cohen's κ.

RESULTS

Relative signal-to-noise and contrast-to-noise ratios decreased with increasing b-values, while the signal-intensity ratio between tumor and tissue increased significantly (P < 0.001). Intermediate b-values (1200-1800 s/mm² ) were rated best concerning image quality and lesion visibility; the preferred b-value mostly lay at 1200-1600 s/mm² . Lowest and highest acceptable b-values were 850 s/mm² and 2000 s/mm² . Interreader agreement was moderate to high concerning image quality (ICC: 0.50-0.67) and lesion visibility (0.70-0.93), but poor concerning preferred and acceptable b-values (κ = 0.032-0.446).

DATA CONCLUSION

Synthetically increased b-values may be a way to improve tumor-to-tissue contrast, lesion visibility, and image quality of breast DWI, while avoiding the disadvantages of performing DWI at very high b-values.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:1754-1761.

MRI for prostate cancer: can computed high b-value DWI replace native acquisitions?

OBJECTIVE

To compare computed high b-value diffusion-weighted images (c-DWI) derived from low b-value DWI images and acquired high b-value DWI (a-DWI), in overall image quality and prostate cancer detection rate.

MATERIALS AND METHODS

A total of 124 consecutive men with suspected prostate cancer (PCa) underwent diagnosis prostate MRI on a 3.0 T MR system using a 32-channel phased-array torso coil. Among them, 63 underwent prostate biopsy. MRI protocol included 3DT2w images, high resolution Fov Optimized and Constrained Undistorted Single-Shot (FOCUS™) DWI images with b-values of 100, 400, 800, and 2000 s/mm² and dynamic contrast enhanced images. C-DWI images (2000 and 2500 s/mm²) were derived from the three lower acquired b-value DWI images using a mono-exponential diffusion decay. C-DWI and acquired high b-value DWI (a-DWI) (2000 s/mm²) were compared for image quality (background signal suppression, anatomic clarity, ghosting, distortion) and tumor conspicuity by four radiologists.

RESULTS

C-DWIs demonstrated higher rating than a-DWIs for overall image quality despite worsened ghosting. In patients with a biopsy, similar detection rate was observed while conspicuity was better with c-DWI (p < 0.001). Non-acquisition of high b-value a-DWI reduced total acquisition time by 220 s per patient.

CONCLUSION

C-DWI provides a substantial reduction in acquisition time while maintaining comparable prostate cancer detection rate and improving global image quality.

KEY POINTS

• Computed DWI improves global quality of prostate MRI. • Computed DWI improves analysis of DWI images with decrease acquisition time. • Computed DWI provides greater background suppression of parenchyma and improves conspicuity of suspicious lesion.

[Imaging for initial diagnosis of localized prostate cancer]

The initial diagnosis of prostate cancer has been traditionally performed using systematic core biopsies with the use of magnetic resonance imaging (MRI) reserved to problem-solving scenarios. There is currently an ongoing paradigm shift towards the use of MRI prior to targeted biopsy as the standard approach. Prostate cancer therefore does not remain the last solid tumor entity diagnosed by non-targeted techniques but joins other solid tumor entities for which targeted diagnostic approaches have existed for a while. However, the complexity of the background tissue signal in the prostate makes lesion detection challenging. This article will provide an overview of the components of multiparametric prostate MRI and their interpretation using structured interpretation according to the current PI-RADSv2 (Prostate Imaging Reporting and Data System version 2) guidelines and of novel ultrasound techniques for primary diagnosis.

Computed Diffusion-Weighted Imaging in Prostate Cancer: Basics, Advantages, Cautions, and Future Prospects

Computed diffusion-weighted MRI is a recently proposed post-processing technique that produces b-value images from diffusion-weighted imaging (DWI), acquired using at least two different b-values. This article presents an argument for computed DWI for prostate cancer by viewing four aspects of DWI: fundamentals, image quality and diagnostic performance, computing procedures, and future uses.

National implementation of multi-parametric magnetic resonance imaging for prostate cancer detection - recommendations from a UK consensus meeting

OBJECTIVES

To identify areas of agreement and disagreement in the implementation of multi-parametric magnetic resonance imaging (mpMRI) of the prostate in the diagnostic pathway.

MATERIALS AND METHODS

Fifteen UK experts in prostate mpMRI and/or prostate cancer management across the UK (involving nine NHS centres to provide for geographical spread) participated in a consensus meeting following the Research and Development Corporation and University of California-Los Angeles (UCLA-RAND) Appropriateness Method, and were moderated by an independent chair. The experts considered 354 items pertaining to who can request an mpMRI, prostate mpMRI protocol, reporting guidelines, training, quality assurance (QA) and patient management based on mpMRI levels of suspicion for cancer. Each item was rated for agreement on a 9-point scale. A panel median score of ≥7 constituted 'agreement' for an item; for an item to reach 'consensus', a panel majority scoring was required.

RESULTS

Consensus was reached on 59% of items (208/354); these were used to provide recommendations for the implementation of prostate mpMRI in the UK. Key findings include prostate mpMRI requests should be made in consultation with the urological team; mpMRI scanners should undergo QA checks to guarantee consistently high diagnostic quality scans; scans should only be reported by trained and experienced radiologists to ensure that men with unsuspicious prostate mpMRI might consider avoiding an immediate biopsy.

CONCLUSIONS

Our consensus statements demonstrate a set of criteria that are required for the practical dissemination of consistently high-quality prostate mpMRI as a diagnostic test before biopsy in men at risk.

The impact of computed high b-value images on the diagnostic accuracy of DWI for prostate cancer: A receiver operating characteristics analysis

To evaluate the performance of computed high b value diffusion-weighted images (DWI) in prostate cancer detection. 97 consecutive patients who had undergone multiparametric MRI of the prostate followed by biopsy were reviewed. Five radiologists independently scored 138 lesions on native high b-value images (b = 1200 s/mm²), apparent diffusion coefficient (ADC) maps, and computed high b-value images (contrast equivalent to b = 2000 s/mm²) to compare their diagnostic accuracy. Receiver operating characteristic (ROC) analysis and McNemar’s test were performed to assess the relative performance of computed high b value DWI, native high b-value DWI and ADC maps. No significant difference existed in the area under the curve (AUC) for ROCs comparing B1200 (b = 1200 s/mm²) to computed B2000 (c-B2000) in 5 readers. In 4 of 5 readers c-B2000 had significantly increased sensitivity and/or decreased specificity compared to B1200 (McNemar’s p < 0.05), at selected thresholds of interpretation. ADC maps were less accurate than B1200 or c-B2000 for 2 of 5 readers (P < 0.05). This study detected no consistent improvement in overall diagnostic accuracy using c-B2000, compared with B1200 images. Readers detected more cancer with c-B2000 images (increased sensitivity) but also more false positive findings (decreased specificity).

Computed diffusion weighted imaging (cDWI) and voxelwise-computed diffusion weighted imaging (vcDWI) for oncologic liver imaging: A pilot study

Objective

Aim of the study was to evaluate the influence of the selection of measured b-values on the precision of cDWI in the upper abdomen as well as on the lesion contrast of PET-positive liver metastases in cDWI and vcDWI.

Methods

We performed a retrospective analysis of 10 patients (4 m, 63.5 ± 12.9 y/o) with PET-positive liver metastases examined in 3 T-PET/MRI with b = 100,600,800,1000 and 1500s/mm². cDWI (cb1000/cb1500) and vcDWI were computed based on following combinations: i) b = 100/600 s/mm², ii) b = 100/800 s/mm², iii) b = 100/1000s/mm², iv) b = 100/600/1000s/mm² v) all measured b-values. Mean signal intensity (SI) and standard deviation (SD) in the liver, spleen, kidney, bone marrow and in liver lesions were acquired. The coefficient of variation (CV = SD/SI), the differences of SI between measured and calculated high b-value images and the lesion contrast (SI lesion/liver) were computed.

Results

With increasing upper measured b-values, the CV in cDWI and vcDWI decreased (CV in the liver in cb1500: 0.42 with b100/600 s/mm² and 0.28 with b100/b1000s/mm²) while the differences of measured and calculated b-value images decreased (in the liver in cb1500: 30.7% with b = 100/600 s/mm², 19.7% with b100/b1000s/mm²). In diffusion-restricted lesions, lesion contrast was at least 1.6 in cb1000 and 1.4 in cb1500, respectively, with an upper measured b-value of b = 800 s/mm² and 2.1 for vcDWI with an upper measured b-value of b = 1000s/mm². Overall, the lesion contrast was superior in cb1500 and vcDWI compared to cb1000 (15% and 11%, respectively).

Conclusion

Measuring higher upper b-values seems to lead to more precise computed high b-value images and a decrease of CV. vcDWI provides a comparable lesion contrast to b = 1500s/mm² and offers additionally the reduction of T2 shine-through effects. For vcDWI, measuring b = 1000s/mm² as upper b-value seems to be necessary to guarantee good lesion visibility in the liver based on our preliminary results.

Technique of Multiparametric MR Imaging of the Prostate

Multiparametric MR imaging provides detailed anatomic assessment of the prostate as well as information that allows the detection and characterization of prostate cancer. To obtain high-quality MR imaging of the prostate, radiologists must understand sequence optimization to overcome commonly encountered technical challenges. This review discusses the techniques that are used in state-of-the-art MR imaging of the prostate, including imaging protocols, hardware considerations, and important aspects of patient preparation, with an emphasis on the recommendations provided in the prostate imaging-reporting and data system version 2 guidelines.

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.

[Selected clinically established and scientific techniques of diffusion-weighted MRI. In the context of imaging in oncology]

BACKGROUND

Diffusion-weighted imaging (DWI) is a magnetic resonance imaging (MRI) technique that was established in the clinical routine primarily for the detection of brain ischemia. In the past 15 years its clinical use has been extended to oncological radiology, as tumor and metastases can be depicted in DWI due to their hypercellular nature.

PRINCIPLES

The basis of DWI is the Stejskal-Tanner experiment. The diffusion properties of tissue can be visualized after acquisition of at least two diffusion-weighted series using echo planar imaging and a specific sequence of gradient pulses.

CLINICAL APPLICATIONS

The use of DWI in prostate MRI was reported to be one of the first established applications that found its way into internationally recognized clinical guidelines of the European Society of Urological Radiology (ESUR) and the prostate imaging reporting and data system (PI-RADS) scale. Due to recently reported high specificity and negative predictive values of 94% and 92%, respectively, its regular use for breast MRI is expected in the near future. Furthermore, DWI can also reliably be used for whole-body imaging in patients with multiple myeloma or for measuring the extent of bone metastases.

OUTLOOK

New techniques in DWI, such as intravoxel incoherent motion imaging, diffusion kurtosis imaging and histogram-based analyses represent promising approaches to achieve a more quantitative evaluation for tumor detection and therapy response.

Prostate Cancer Detection Using Computed Very High b-value Diffusion-weighted Imaging: How High Should We Go?

RATIONALE AND OBJECTIVES

The aim of this study was to assess prostate cancer detection using a broad range of computed b-values up to 5000 s/mm(2).

MATERIALS AND METHODS

This retrospective Health Insurance Portability and Accountability Act-compliant study was approved by an institutional review board with consent waiver. Forty-nine patients (63 ± 8 years) underwent 3T prostate magnetic resonance imaging before prostatectomy. Examinations included diffusion-weighted imaging (DWI) with b-values of 50 and 1000 s/mm(2). Seven computed DWI image sets (b-values: 1000, 1500, 2000, 2500, 3000, 4000, and 5000 s/mm(2)) were generated by mono-exponential fit. Two blinded radiologists (R1 [attending], R2 [fellow]) independently evaluated diffusion weighted image sets for image quality and dominant lesion location. A separate unblinded radiologist placed regions of interest to measure tumor-to-peripheral zone (PZ) contrast. Pathologic findings from prostatectomy served as reference standard. Measures were compared between b-values using the Jonckheere-Terpstra trend test, Spearman correlation coefficient, and generalized estimating equations based on logistic regression for correlated data.

RESULTS

As b-value increased, tumor-to-PZ contrast and benign prostate suppression for both readers increased (r = +0.65 to +0.71, P ≤ 0.001), whereas anatomic clarity, visualization of the capsule, and visualization of peripheral-transition zone edge decreased (r = -0.69 to -0.75, P ≤ 0.003). Sensitivity for tumor was highest for R1 at b1500-3000 (84%-88%) and for R2 at b1500-2500 (70%-76%). Sensitivities for both pathologic outcomes were lower for both readers at both b1000 and the highest computed b-values. Sensitivity for Gleason >6 tumor was highest for R1 at b1500-3000 (90%-93%) and for R2 at 1500-2500 (78%-80%). The positive predictive value for tumor for R1 was similar from b1000 to 4000 (93%-98%) and for R2 was similar from b1500 to 4000 (88%-94%).

CONCLUSIONS

Computed b-values in the range of 1500-2500 s/mm(2) (but not higher) were optimal for prostate cancer detection; b-values of 1000 or 3000-5000 exhibited overall lower performance.

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.

Body Diffusion-weighted MR Imaging in Oncology: Imaging at 3 T

Advances in hardware and software enable high-quality body diffusion-weighted images to be acquired for oncologic assessment. 3.0 T affords improved signal/noise for higher spatial resolution and smaller field-of-view diffusion-weighted imaging (DWI). DWI at 3.0 T can be applied as at 1.5 T to improve tumor detection, disease characterization, and the assessment of treatment response. DWI at 3.0 T can be acquired on a hybrid PET-MR imaging system, to allow functional MR information to be combined with molecular imaging.

PI-RADS Prostate Imaging - Reporting and Data System: 2015, Version 2

The Prostate Imaging - Reporting and Data System Version 2 (PI-RADS™ v2) is the product of an international collaboration of the American College of Radiology (ACR), European Society of Uroradiology (ESUR), and AdMetech Foundation. It is designed to promote global standardization and diminish variation in the acquisition, interpretation, and reporting of prostate multiparametric magnetic resonance imaging (mpMRI) examination, and it is based on the best available evidence and expert consensus opinion. It establishes minimum acceptable technical parameters for prostate mpMRI, simplifies and standardizes terminology and content of reports, and provides assessment categories that summarize levels of suspicion or risk of clinically significant prostate cancer that can be used to assist selection of patients for biopsies and management. It is intended to be used in routine clinical practice and also to facilitate data collection and outcome monitoring for research.