Comparison of calculated and acquired high b value diffusion-weighted imaging in prostate cancer

Multiparametric Magnetic Resonance Imaging of Penile Cancer: A Pictorial Review

The role of multiparametric magnetic resonance imaging (mpMRI) in assessing penile cancer is not well defined. However, this modality may be successfully applied for preoperative staging and patient selection; postoperative local and regional surveillance; and assessments of treatment response after oncological therapies. Previous studies have been mostly limited to a few small series evaluating the accuracy of MRI for the preoperative staging of penile cancer. This review discusses the principles of non-erectile mpMRI, including functional techniques and their applications in evaluating the male genital region, along with clinical protocols and technical considerations. The latest clinical classifications and guidelines are reviewed, focusing on imaging recommendations and discussing potential gaps and disadvantages. The development of functional MRI techniques and the extraction of quantitative parameters from these sequences enables the noninvasive assessment of phenotypic and genotypic tumor characteristics. The applications of advanced techniques in penile MRI are yet to be defined. There is a need for prospective trials and feasible multicenter trials due to the rarity of the disease, highlighting the importance of minimum technical requirements for MRI protocols, particularly image resolution, and finally determining the role of mpMRI in the assessment of penile cancer.

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.

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.

Truly reproducible uniform estimation of the ADC with multi-b diffusion data- Application in prostate diffusion imaging

PURPOSE

The ADC is a well-established parameter for clinical diagnostic applications, but lacks reproducibility because it is also influenced by the choice diffusion weighting level. A framework is evaluated that is based on multi-b measurement over a wider range of diffusion-weighting levels and higher order tissue diffusion modeling with retrospective, fully reproducible ADC calculation.

METHODS

Averaging effect from curve fitting for various model functions at 20 linearly spaced b-values was determined by means of simulations and theoretical calculations. Simulation and patient multi-b image data were used to compare the new approach for diffusion-weighted image and ADC map reconstruction with and without Rician bias correction to an active clinical trial protocol probing three non-zero b-values.

RESULTS

Averaging effect at a certain b-value varies for model function and maximum b-value used. Images and ADC maps from the novel procedure are on-par with the clinical protocol. Higher order modeling and Rician bias correction is feasible, but comes at the cost of longer computation times.

CONCLUSIONS

Application of the new framework makes higher order modeling more feasible in a clinical setting while still providing patient images and reproducible ADC maps of adequate quality.

Diffusion Weighted Imaging of the Abdomen and Pelvis: Recent Technical Advances and Clinical Applications

Diffusion weighted imaging (DWI) serves as one of the most important functional magnetic resonance imaging techniques in abdominal and pelvic imaging. It is designed to reflect the diffusion of water molecules and is particularly sensitive to the malignancies. Yet, the limitations of image distortion and artifacts in single-shot DWI may hamper its widespread use in clinical practice. With recent technical advances in DWI, such as simultaneous multi-slice excitation, computed or reduced field-of-view techniques, as well as advanced shimming methods, it is possible to achieve shorter acquisition time, better image quality, and higher robustness in abdominopelvic DWI. This review discussed the recent advances of each DWI approach, and highlighted its future perspectives in abdominal and pelvic imaging, hoping to familiarize physicians and radiologists with the technical improvements in this field and provide future research directions.

Canadian Association of Radiologists Prostate MRI White Paper

Prostate cancer is the most common malignancy and the third most common cause of death in Canadian men. In light of evolving diagnostic pathways for prostate cancer and the increased use of MRI, which now includes its use in men prior to biopsy, the Canadian Association of Radiologists established a Prostate MRI Working Group to produce a white paper to provide recommendations on establishing and maintaining a Prostate MRI Programme in the context of the Canadian healthcare system. The recommendations, which are based on available scientific evidence and/or expert consensus, are intended to maintain quality in image acquisition, interpretation, reporting and targeted biopsy to ensure optimal patient care. The paper covers technique, reporting, quality assurance and targeted biopsy considerations and includes appendices detailing suggested reporting templates, quality assessment tools and sample image acquisition protocols relevant to the Canadian healthcare context.

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.

Whole-Body MRI with an Ultrahigh b-Value of 2000 s/mm2 Improves the Specificity of Diffusion-Weighted Imaging in Patients with Plasma Cell Dyscrasias

RATIONALE AND OBJECTIVES

Our study compared sensitivity, specificity, and accuracy of whole-body diffusion-weighted imaging (WB-DWI) using a b-value of 2000 s/mm² with that of the commonly used b-value of 800 s/mm² for depiction of active tumor sites in patients with plasma cell diseases. We introduced an ultrahigh b-value to reduce interfering signals from benign and post-therapeutic inactive lesions by suppressing T2-shine-through effects.

MATERIALS AND METHODS

The prospective single-center study included patients when they went through a whole-body MRI (WB-MRI) staging or response evaluation procedure. The apparent diffusion coefficient (ADC) and morphologic appearance served as reference for classifying focal lesions on WB-DWI as vital or post-therapeutic. Additionally, we compared our classification with patients' serological markers of disease activity.

RESULTS

One hundred participants (65 ± 10 years, 58 men) underwent WB-DWI between June and October 2019. The detection rate of vital focal lesions was similar for both b-values with a sensitivity of 0.99 using b = 800 s/mm² and 0.98 using b = 2000 s/mm². By contrast, specificity and accuracy were 0.09 and 0.71 when using a b-value of 800 s/mm², and 0.96 and 0.98 when using a b-value of 2000 s/mm², respectively. The difference in specificity and accuracy was statistically significant (p < 0.001).

CONCLUSION

Using a b-value of 2000 s/mm² significantly improved the specificity of lesion detection with WB-DWI as compared to the commonly used b-value of 800 s/mm². The high b-value significantly reduced signal intensities of post-therapeutic or benign lesions and provided a significantly more accurate representation of active tumor load.

Using IVIM Parameters to Differentiate Prostate Cancer and Contralateral Normal Tissue through Fusion of MRI Images with Whole-Mount Pathology Specimen Images by Control Point Registration Method

The intravoxel incoherent motion (IVIM) model may enhance the clinical value of multiparametric magnetic resonance imaging (mpMRI) in the detection of prostate cancer (PCa). However, while past IVIM modeling studies have shown promise, they have also reported inconsistent results and limitations, underscoring the need to further enhance the accuracy of IVIM modeling for PCa detection. Therefore, this study utilized the control point registration toolbox function in MATLAB to fuse T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) MRI images with whole-mount pathology specimen images in order to eliminate potential bias in IVIM calculations. Sixteen PCa patients underwent prostate MRI scans before undergoing radical prostatectomies. The image fusion method was then applied in calculating the patients’ IVIM parameters. Furthermore, MRI scans were also performed on 22 healthy young volunteers in order to evaluate the changes in IVIM parameters with aging. Among the full study cohort, the f parameter was significantly increased with age, while the D* parameter was significantly decreased. Among the PCa patients, the D and ADC parameters could differentiate PCa tissue from contralateral normal tissue, while the f and D* parameters could not. The presented image fusion method also provided improved precision when comparing regions of interest side by side. However, further studies with more standardized methods are needed to further clarify the benefits of the presented approach and the different IVIM parameters in PCa characterization.

Precise Identification of Prostate Cancer from DWI Using Transfer Learning

Background and Objective: The use of computer-aided detection (CAD) systems can help radiologists make objective decisions and reduce the dependence on invasive techniques. In this study, a CAD system that detects and identifies prostate cancer from diffusion-weighted imaging (DWI) is developed. Methods: The proposed system first uses non-negative matrix factorization (NMF) to integrate three different types of features for the accurate segmentation of prostate regions. Then, discriminatory features in the form of apparent diffusion coefficient (ADC) volumes are estimated from the segmented regions. The ADC maps that constitute these volumes are labeled by a radiologist to identify the ADC maps with malignant or benign tumors. Finally, transfer learning is used to fine-tune two different previously-trained convolutional neural network (CNN) models (AlexNet and VGGNet) for detecting and identifying prostate cancer. Results: Multiple experiments were conducted to evaluate the accuracy of different CNN models using DWI datasets acquired at nine distinct b-values that included both high and low b-values. The average accuracy of AlexNet at the nine b-values was 89.2±1.5% with average sensitivity and specificity of 87.5±2.3% and 90.9±1.9%. These results improved with the use of the deeper CNN model (VGGNet). The average accuracy of VGGNet was 91.2±1.3% with sensitivity and specificity of 91.7±1.7% and 90.1±2.8%. Conclusions: The results of the conducted experiments emphasize the feasibility and accuracy of the developed system and the improvement of this accuracy using the deeper CNN.

The diagnostic value of intravoxel incoherent motion imaging in differentiating high-grade from low-grade gliomas: a systematic review and meta-analysis

OBJECTIVE

This meta-analysis was carried out for assessing the accuracy of intravoxel incoherent motion (IVIM) parameters true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) in differentiating low-grade gliomas (LGGs) from high-grade gliomas (HGGs).

METHODS

Literatures concerning IVIM in the grading of brain gliomas published prior to October 20, 2020, searched in the Embase, PubMed, and Cochrane library. Use the quality assessment of diagnostic accuracy studies 2 (QUADAS 2) to evaluate the quality of studies. We estimated the pooled sensitivity, specificity, and the area under the summary ROC (SROC) curve to identification the accuracy of IVIM parameters D, D*, and f evaluation in grading gliomas.

RESULTS

Totally, 6 articles including 252 brain gliomas conform to the inclusion criteria. The pooled sensitivity of parameters D, D*, and f derived from IVIM were 0.85 (95%Cl, 0.76-0.91), 0.78 (95%Cl, 0.71-0.85), and 0.89 (95%Cl, 0.76-0.96), respectively. The pooled specificity were 0.78 (95%Cl, 0.60-0.90), 0.68 (95%Cl, 0.56-0.79), and 0.88 (95%Cl, 0.76-0.94), respectively. Meanwhile, the AUC of SROC curve were 0.89 (95%Cl, 0.86-0.92) , 0.81 (95%Cl, 0.77-0.84), and 0.94 (95%Cl, 0.92-0.96), respectively.

CONCLUSION

This meta-analysis suggested that IVIM parameters D, D*, and f have moderate or high diagnosis value accuracy in differentiating HGGs from LGGs, and the parameter f has greater sensitivity and specificity. Standardized methodology is warranted to guide the use of this method for clinical decision-making. However, more clinical studies are needed to prove our view.

ADVANCES IN KNOWLEDGE

IVIM parameter f showed greater sensitivity and specificity, as well as excellent performance than parameter D* and D.

The Primacy of High B-Value 3T-DWI Radiomics in the Prediction of Clinically Significant Prostate Cancer

Predicting clinically significant prostate cancer (csPCa) is crucial in PCa management. 3T-magnetic resonance (MR) systems may have a novel role in quantitative imaging and early csPCa prediction, accordingly. In this study, we develop a radiomic model for predicting csPCa based solely on native b2000 diffusion weighted imaging (DWI_b2000) and debate the effectiveness of apparent diffusion coefficient (ADC) in the same task. In total, 105 patients were retrospectively enrolled between January–November 2020, with confirmed csPCa or ncsPCa based on biopsy. DWI_b2000 and ADC images acquired with a 3T-MRI were analyzed by computing 84 local first-order radiomic features (RFs). Two predictive models were built based on DWI_b2000 and ADC, separately. Relevant RFs were selected through LASSO, a support vector machine (SVM) classifier was trained using repeated 3-fold cross validation (CV) and validated on a holdout set. The SVM models rely on a single couple of uncorrelated RFs (ρ < 0.15) selected through Wilcoxon rank-sum test (p ≤ 0.05) with Holm–Bonferroni correction. On the holdout set, while the ADC model yielded AUC = 0.76 (95% CI, 0.63–0.96), the DWI_b2000 model reached AUC = 0.84 (95% CI, 0.63–0.90), with specificity = 75%, sensitivity = 90%, and informedness = 0.65. This study establishes the primary role of 3T-DWI_b2000 in PCa quantitative analyses, whilst ADC can remain the leading sequence for detection.

Voxel-level Classification of Prostate Cancer on Magnetic Resonance Imaging: Improving Accuracy Using Four-Compartment Restriction Spectrum Imaging

BACKGROUND

Diffusion magnetic resonance imaging (MRI) is integral to detection of prostate cancer (PCa), but conventional apparent diffusion coefficient (ADC) cannot capture the complexity of prostate tissues and tends to yield noisy images that do not distinctly highlight cancer. A four-compartment restriction spectrum imaging (RSI₄ ) model was recently found to optimally characterize pelvic diffusion signals, and the model coefficient for the slowest diffusion compartment, RSI₄ -C₁ , yielded greatest tumor conspicuity.

PURPOSE

To evaluate the slowest diffusion compartment of a four-compartment spectrum imaging model (RSI₄ -C₁ ) as a quantitative voxel-level classifier of PCa.

STUDY TYPE

Retrospective.

SUBJECTS

Forty-six men who underwent an extended MRI acquisition protocol for suspected PCa. Twenty-three men had benign prostates, and the other 23 men had PCa.

FIELD STRENGTH/SEQUENCE

A 3 T, multishell diffusion-weighted and axial T2-weighted sequences.

ASSESSMENT

High-confidence cancer voxels were delineated by expert consensus, using imaging data and biopsy results. The entire prostate was considered benign in patients with no detectable cancer. Diffusion images were used to calculate RSI₄ -C₁ and conventional ADC. Classifier images were also generated.

STATISTICAL TESTS

Voxel-level discrimination of PCa from benign prostate tissue was assessed via receiver operating characteristic (ROC) curves generated by bootstrapping with patient-level case resampling. RSI₄ -C₁ was compared to conventional ADC for two metrics: area under the ROC curve (AUC) and false-positive rate for a sensitivity of 90% (FPR₉₀ ). Statistical significance was assessed using bootstrap difference with two-sided α = 0.05.

RESULTS

RSI₄ -C₁ outperformed conventional ADC, with greater AUC (mean 0.977 [95% CI: 0.951-0.991] vs. 0.922 [0.878-0.948]) and lower FPR₉₀ (0.032 [0.009-0.082] vs. 0.201 [0.132-0.290]). These improvements were statistically significant (P < 0.05).

DATA CONCLUSION

RSI₄ -C₁ yielded a quantitative, voxel-level classifier of PCa that was superior to conventional ADC. RSI classifier images with a low false-positive rate might improve PCa detection and facilitate clinical applications like targeted biopsy and treatment planning.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 2.

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.

Advances in Prostate Magnetic Resonance Imaging

Prostate magnetic resonance (MR) imaging is a widely used imaging technique to detect intraprostatic lesions and guide prostate biopsies, with continuous technical advances for better accuracy in prostate cancer diagnosis. Current evaluation of prostate multiparametric MR imaging mainly depends on qualitative evaluation, which is prone to inter-reader variation. Recent advances in prostate MR imaging, such as quantitative T2 mapping and abbreviated MR imaging protocols (eg, biparametric MR imaging), are designed to simplify prostate MR imaging acquisition and interpretation.

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.

Role of MRI in Staging of Penile Cancer

Penile cancer is one of the male-specific cancers. Accurate pretreatment staging is crucial due to a plethora of treatment options currently available. The 8^th edition American Joint Committee on Cancer-Tumor Node and Metastasis (AJCC-TNM) revised the staging for penile cancers, with invasion of corpora cavernosa upstaged from T2 to T3 and invasion of urethra downstaged from T3 to being not separately relevant. With this revision, MRI is more relevant in local staging because MRI is accurate in identifying invasion of corpora cavernosa, while the accuracy is lower for detection of urethral involvement. The recent European Urology Association (EAU) guidelines recommend MRI to exclude invasion of the corpora cavernosa, especially if penis preservation is planned. Identification of satellite lesions and measurement of residual-penile-length help in surgical planning. When nonsurgical treatment modalities of the primary tumor are being considered, accurate local staging helps in decision-making regarding upfront inguinal lymph node dissection as against surveillance. MRI helps in detection and extent of inguinal and pelvic lymphadenopathy and is superior to clinical palpation, which continues to be the current approach recommended by National Comprehensive Cancer Network (NCCN) treatment guidelines. MRI helps the detection of "bulky" lymph nodes that warrant neoadjuvant chemotherapy and potentially identify extranodal extension. However, tumor involvement in small lymph nodes and differentiation of reactive vs. malignant lymphadenopathy in large lymph nodes continue to be challenging and the utilization of alternative contrast agents (superparamagnetic iron oxide), positron emission tomography (PET)-MRI along with texture analysis is promising. In locally recurrent tumors, MRI is invaluable in identification of deep invasion, which forms the basis of treatment. Multiparametric MRI, especially diffusion-weighted-imaging, may allow for quantitative noninvasive assessment of tumor grade and histologic subtyping to avoid biopsy undersampling. Further research is required for incorporation of MRI with deep learning and artificial intelligence algorithms for effective staging in penile cancer. Level of Evidence: 5 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2020;51:1612-1629.

Update on MR urography (MRU): technique and clinical applications

Magnetic resonance imaging of the upper tract (pyelocalyces and ureters) or MR Urography (MRU) is technically possible and when performed correctly offers similar visualization of the upper tracts and for detection of non-calculous diseases of the collecting system similar specificity but with lower sensitivity compared to CTU. MRU provides the ability to simultaneously image the kidneys and urinary bladder with improved soft tissue resolution, better tissue characterization and when combined with assessment of the upper tract, a comprehensive examination of the urinary system. MRU requires meticulous attention to technical details and is a longer more demanding examination compared to CTU. Advances in MR imaging techniques including: parallel imaging, free-breathing motion compensation techniques and compressed sensing can dramatically shorten examination times and improve image quality and patient tolerance for the exam. This review article discusses updates in the MRU technique, summarizes clinical indications and opportunities for MRU in clinical practice and reviews advantages and disadvantages of MRU compared to CTU.

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.

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.

Can computer-aided diagnosis assist in the identification of prostate cancer on prostate MRI? a multi-center, multi-reader investigation

For prostate cancer detection on prostate multiparametric MRI (mpMRI), the Prostate Imaging-Reporting and Data System version 2 (PI-RADSv2) and computer-aided diagnosis (CAD) systems aim to widely improve standardization across radiologists and centers. Our goal was to evaluate CAD assistance in prostate cancer detection compared with conventional mpMRI interpretation in a diverse dataset acquired from five institutions tested by nine readers of varying experience levels, in total representing 14 globally spread institutions. Index lesion sensitivities of mpMRI-alone were 79% (whole prostate (WP)), 84% (peripheral zone (PZ)), 71% (transition zone (TZ)), similar to CAD at 76% (WP, p=0.39), 77% (PZ, p=0.07), 79% (TZ, p=0.15). Greatest CAD benefit was in TZ for moderately-experienced readers at PI-RADSv2 <3 (84% vs mpMRI-alone 67%, p=0.055). Detection agreement was unchanged but CAD-assisted read times improved (4.6 vs 3.4 minutes, p<0.001). At PI-RADSv2 ≥ 3, CAD improved patient-level specificity (72%) compared to mpMRI-alone (45%, p<0.001). PI-RADSv2 and CAD-assisted mpMRI interpretations have similar sensitivities across multiple sites and readers while CAD has potential to improve specificity and moderately-experienced radiologists' detection of more difficult tumors in the center of the gland. The multi-institutional evidence provided is essential to future prostate MRI and CAD development.

Low-to-high b value DWI ratio approaches in multiparametric MRI of the prostate: feasibility, optimal combination of b values, and comparison with ADC maps for the visual presentation of prostate cancer

Background

Diffusion-weighted imaging (DWI) is considered by experts as one of the key elements in multi-parametric magnetic resonance imaging (mpMRI) employed in oncological studies outside the brain. A low-to-high b value ratio DWI has been proposed as an approach to decrease acquisition time and simplify the analysis of DWI data without the need to use a mathematical model.

Methods

Forty-three men with biopsy-proven prostate cancer (PCa) who underwent mpMRI of the prostate were included. Apparent diffusion coefficient (ADC) maps were created in the MRI scanner using a mono-exponential algorithm [b value (× number of averages) =0 (×1), 10 (×1), 25 (×1), 50 (×1), 100 (×1), 250 (×1), 450 (×1), 1,000 (×2), 1,500 (×3), and 2,000 (×5) s/mm²]. DWI ratio images were calculated with three previously estimated optimal b value combinations: (I) b=100 and b=1,000 s/mm² (R1); (II) b=100 and b=1,500 s/mm² (R2); and (III) b=100 and b=2,000 s/mm² (R3). For quantitative analysis, contrast-to-noise ratio (CNR) between normal and cancerous tissue was compared between the ADC maps and the DWI ratio images in terms of noninferiority. For qualitative analysis, two radiologists read all images in a randomized order without knowing whether the presented image was an ADC map or a DWI ratio image. All images were scored in terms of artifacts, cancer conspicuity and overall image quality with a 5-point scale. Agreement between the readers was assessed by weighted kappa statistics. Agreement was considered as poor when kappa <0.4, fair to good when kappa >0.4 and <0.75 and excellent when kappa >0.75. Mean scores were compared between ADC and each of the DWI ratio images. Agreement between ADC maps and DWI ratio based synthetic ADC were assessed by intraclass correlation (ICC). Values less than 0.5, between 0.5 and 0.75, between 0.75 and 0.9, and greater than 0.90 were indicative of poor, moderate, good, and excellent reliability, respectively. Median difference between low and intermediate/high risk were tested.

Results

Quantitative analysis shows DWI ratio images were not inferior to ADC maps quantitatively [P=0.0298 (ADC vs. R1), <0.0001 (ADC vs. R2) and <0.0001 (ADC vs. R3)]. Qualitatively, DWI ratio images were no more than 0.5 point on Likert scale lower than ADC in overall quality [P=0.0043 (ADC vs. R1), <0.0001 (ADC vs. R2), <0.0001 (ADC vs. R3)]. Reader agreement for the qualitative analysis was good to excellent (weighted kappa =0.4-0.7). Agreement between ADC maps and the synthetic ADC's were excellent. Significant difference between low and intermediate/high risk were found in all measurements on average (all P values <0.05).

Conclusions

We presented an analytical method for searching for the optimal combination of high and low b values for DWI ratio images in terms of minimizing CNR between cancer and surrounding benign tissues. Optimized DWI ratio images are comparable both quantitatively and qualitatively to ADC maps for the interpretation of DWI data in the context of prostate mpMRI.

Computed Diffusion Weighted Imaging of the Liver Using Extrapolation Technique in Patients Who Underwent Liver Transplantation With Hepatocellular Carcinomas: Initial Experience and Feasibility Study

OBJECTIVE

This study aimed to evaluate the feasibility and image quality of computed diffusion weighted imaging (DWI) of the liver in patients with hepatocellular carcinoma (HCC).

METHODS

Twenty-four patients who underwent liver transplantation with HCC were enrolled. Computed DWI was synthesized for b-values of 800 (cDWI800) and 1200 s/mm (cDWI1200) using directly acquired DWI with b-values of 0, 50, and 500 s/mm. Signal intensity of HCC, background liver, and contrast-to-noise ratio were evaluated for directly acquired DWI of 800 s/mm (dDWI800), cDWI800, and cDWI1200. Two radiologists evaluated the image quality for contrast between HCC and liver, suppression of background signal and T2 shine-through, and overall image quality.

RESULTS

cDWI1200 showed the lowest contrast-to-noise ratio. Qualitative scores for background suppression and decreased T2 shine-through were highest for cDWI1200. However, contrast between HCC and background liver was worst in cDWI1200.

CONCLUSIONS

In computed DWI of high b-values, contrast between HCC and background liver was very low.

Intravoxel incoherent motion: application in differentiation of hepatocellular carcinoma and focal nodular hyperplasia

PURPOSE

We aimed to explore whether intravoxel incoherent motion (IVIM)-related parameters of hepatocellular carcinoma (HCC) and focal nodular hyperplasia (FNH) demonstrate differences that could be used to differentiate and improve diagnostic efficiency.

METHODS

A total of 27 patients, including 22 with HCC and 5 with FNH, underwent liver 3.0 T magnetic resonance imaging for routine sequences. They were concurrently examined by IVIM diffusion-weighted imaging (DWI) scanning with 11 different b values (0-800 s/mm2). IVIM-derived parameters, such as pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), and apparent diffusion coefficient (ADCtotal), were quantified automatically by post-processing software and compared between HCC and FNH groups. A receiver operating characteristic (ROC) curve was then created to predict their diagnostic value.

RESULTS

D* was weak in terms of reproducibility among the other parameters. ADCtotal, D, and D* were significantly lower in the HCC group than in the FNH group, while f did not show a significant difference. ADCtotal and D had the largest area under the curve values (AUC; 0.915 and 0.897, respectively) and similarly high efficacy to differentiate the two conditions.

CONCLUSION

IVIM provides a new modality to differentiate the HCC and FNH. ADCtotal and D demonstrated outstanding and comparable diagnosing utility.

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).

Multiparametric magnetic resonance imaging for transition zone prostate cancer: essential findings, limitations, and future directions

OBJECTIVE

Review the multiparametric MRI (mpMRI) findings of transition zone (TZ) prostate cancer (PCa) using T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) MRI and to integrate mpMRI findings with clinical history, laboratory values, and histopathology.

CONCLUSION

TZ prostate tumors are challenging to detect clinically and at MRI. mpMRI using the combination of sequences has the potential to improve accuracy of TZ cancer detection and staging.

Advances in medical imaging for the diagnosis and management of common genitourinary cancers

Medical imaging of the 3 most common genitourinary (GU) cancers-prostate adenocarcinoma, renal cell carcinoma, and urothelial carcinoma of the bladder-has evolved significantly during the last decades. The most commonly used imaging modalities for the diagnosis, staging, and follow-up of GU cancers are computed tomography, magnetic resonance imaging (MRI), and positron emission tomography (PET). Multiplanar multidetector computed tomography and multiparametric MRI with diffusion-weighted imaging are the main imaging modalities for renal cell carcinoma and urothelial carcinoma, and although multiparametric MRI is rapidly becoming the main imaging tool in the evaluation of prostate adenocarcinoma, biopsy is still required for diagnosis. Functional and molecular imaging using 18-fluorodeoxyglucose-PET and sodium fluoride-PET are essential for the diagnosis, and especially follow-up, of metastatic GU tumors. This review provides an overview of the latest advances in the imaging of these 3 major GU cancers.

Detection of prostate cancer in multiparametric MRI using random forest with instance weighting

A prostate computer-aided diagnosis (CAD) based on random forest to detect prostate cancer using a combination of spatial, intensity, and texture features extracted from three sequences, T2W, ADC, and B2000 images, is proposed. The random forest training considers instance-level weighting for equal treatment of small and large cancerous lesions as well as small and large prostate backgrounds. Two other approaches, based on an AutoContext pipeline intended to make better use of sequence-specific patterns, were considered. One pipeline uses random forest on individual sequences while the other uses an image filter described to produce probability map-like images. These were compared to a previously published CAD approach based on support vector machine (SVM) evaluated on the same data. The random forest, features, sampling strategy, and instance-level weighting improve prostate cancer detection performance [area under the curve (AUC) 0.93] in comparison to SVM (AUC 0.86) on the same test data. Using a simple image filtering technique as a first-stage detector to highlight likely regions of prostate cancer helps with learning stability over using a learning-based approach owing to visibility and ambiguity of annotations in each sequence.

Feasibility of Computed Diffusion Weighted Imaging and Optimization of b-value in Cervical Cancer

Purpose:

To evaluate the feasibility of computed diffusion weighted imaging (DWI) in cervical cancer and investigate the optimal b-value using computed DWI.

Methods:

The present retrospective study involved 85 patients with cervical cancer in the International Federation of Gynecology and Obstetrics (FIGO) stage IB, IIA or IIB. DWI was obtained with b-values of 0, 100, 500 and 1000 s/mm². Computed DWI with b-values of 800, 1000, 1300, 1600 and 2000 s/mm² (cDWI₈₀₀, cDWI₁₀₀₀, cDWI₁₃₀₀, cDWI₁₆₀₀, cDWI₂₀₀₀) were generated from all measured DWI (mDWI) data. Qualitatively, computed DWI was evaluated in terms of tumor conspicuity, signal suppression of the fat in the imaged area and total image quality by two radiologists independently with reference to mDWI with b-value of 1000 s/mm². The b-value at which the signal of the endocervical canal was suppressed was recorded. Quantitatively, the signal intensities of tumor, myometrium, endocervical canal, endometrium, and gluteal subcutaneous fat were measured and represented as contrast ratios (CR).

Results:

Regarding tumor conspicuity and total image quality, significantly higher scores were obtained at cDWI₁₃₀₀ and cDWI₁₆₀₀ compared to the others (post-hoc comparison, P < 0.001), except for the total image quality between cDWI₁₀₀₀ and cDWI₁₆₀₀ in one reader. Signal suppression of the fat was the worst at cDWI₂₀₀₀. The signal intensity of the endocervical canal was suppressed in 24/27 cases on cDWI₁₆₀₀ and in 26/27 cases on cDWI₂₀₀₀. The CRs of tumor to myometrium, cervix, and endometrium increased with higher b-values, while the CRs of tumor to fat decreased and were statistically significant (post-hoc comparison, P < 0.001).

Conclusion:

Computed DWI with the b-values of 1300 and 1600 would be suitable for the evaluation of cervical cancer due to good tumor conspicuity.

Optimal high b-value for diffusion weighted MRI in diagnosing high risk prostate cancers in the peripheral zone

PURPOSE

To retrospectively determine the optimal b-value(s) of diffusion-weighted imaging (DWI) associated with intermediate-high risk cancer in the peripheral zone (PZ) of the prostate.

MATERIALS AND METHODS

Forty-two consecutive patients underwent multi b-value (16 evenly spaced b-values between 0 and 2000 s/mm² ) DWI along with multi-parametric MRI (MP-MRI) of the prostate at 3 Tesla followed by trans-rectal ultrasound/MRI fusion guided targeted biopsy of suspicious lesions detected at MP-MRI. Computed DWI images up to a simulated b-value of 4000 s/mm² were also obtained using a pair of b-values (b = 133 and 400 or 667 or 933 s/mm² ) from the multi b-value DWI. The contrast ratio of average intensity of the targeted lesions and the background PZ was determined. Receiver operator characteristic curves and the area under the curve (AUCs) were obtained for separating patients eligible for active surveillance with low risk prostate cancers from intermediate-high risk prostate cancers as per the cancer of the prostate risk assessment (CAPRA) scoring system.

RESULTS

The AUC first increased then decreased with the increase in b-values reaching maximum at b = 1600 s/mm² (0.74) with no statistically significant different AUC of DWI with b-values 1067-2000 s/mm² . The AUC of computed DWI increased then decreased with the increase in b-values reaching a maximum of 0.75 around b = 2000 s/mm² . There was no statistically significant difference between the AUC of optimal acquired DWI and either of optimal computed DWI.

CONCLUSION

The optimal b-value for acquired DWI in differentiating intermediate-high from low risk prostate cancers in the PZ is b = 1600 s/mm² . The computed DWI has similar performance as that of acquired DWI with the optimal performance around b = 2000 s/mm² .

LEVEL OF EVIDENCE

4 J. Magn. Reson. Imaging 2017;45:125-131.

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.

Limitations and Prospects for Diffusion-Weighted MRI of the Prostate

Diffusion-weighted imaging (DWI) is the most effective component of the modern multi-parametric magnetic resonance imaging (mpMRI) scan for prostate pathology. DWI provides the strongest prediction of cancer volume, and the apparent diffusion coefficient (ADC) correlates moderately with Gleason grade. Notwithstanding the demonstrated cancer assessment value of DWI, the standard measurement and signal analysis methods are based on a model of water diffusion dynamics that is well known to be invalid in human tissue. This review describes the biophysical limitations of the DWI component of the current standard mpMRI protocol and the potential for significantly improved cancer assessment performance based on more sophisticated measurement and signal modeling techniques.

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.

Evaluating the Role of mpMRI in Prostate Cancer Assessment

Prostate cancer is the most common malignancy among American men. The role of multi-parametric MRI has recently gained more importance in detection of prostate cancer, its targeted biopsy, and focal therapy guidance. In this review, uses of multi-parametric MRI in prostate cancer assessment and treatment are discussed.

Novel Imaging of Prostate Cancer with MRI, MRI/US, and PET

Imaging of prostate cancer presents many challenges to the imaging community. There has been much progress in this space in large part due to MRI and PET radiopharmaceuticals. Though MRI has been focused on the evaluation of local disease and PET on the detection of metastatic disease, these two areas do converge and will be complementary especially with the growth of new PET/MRI technologies. In this review article, we review novel MRI, MRI/US, and PET radiopharmaceuticals which will offer insight into the future direction of imaging in prostate cancer.

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.