Comparison of multiparametric and biparametric MRI of the prostate: are gadolinium-based contrast agents needed for routine examinations?

Relative Enhanced Diffusivity in Prostate Cancer: Protocol Optimization and Diagnostic Potential

BACKGROUND

Relative enhanced diffusivity (RED) is a potential biomarker for indirectly measuring perfusion in tissue using diffusion-weighted magnetic resonance imaging (MRI) with 3 b values.

PURPOSE

To optimize the RED MRI protocol for the prostate, and to investigate its potential for prostate cancer (PCa) diagnosis.

STUDY TYPE

Prospective.

POPULATION

Ten asymptomatic healthy volunteers and 35 patients with clinical suspicion of PCa.

SEQUENCE

3T T₂ - and diffusion-weighted MRI with b values: b = 0, 50, [100], 150, [200], 250, [300], 400, 800 s/mm² (values in brackets were only used for patients).

ASSESSMENT

Monte Carlo simulations were performed to assess noise sensitivity of RED as a function of intermediate b value. Volunteers were scanned 3 times to assess repeatability of RED. Patient data were used to investigate RED's potential for discriminating between biopsy-confirmed cancer and healthy tissue, and between true and false positive radiological findings.

STATISTICAL TESTS

Within-subject coefficient of variation (WCV) to assess repeatability and receiver-operating characteristic curve analysis and logistic regression to assess diagnostic performance of RED.

RESULTS

The repeatability was acceptable (WCV = 0.2-0.3) for all intermediate b values tested, apart from b = 50 s/mm² (WCV = 0.3-0.4). The simulated RED values agreed well with the experimental data, showing that an intermediate b value between 150-250 s/mm² minimizes noise sensitivity in both peripheral zone (PZ) and transition zone (TZ). RED calculated with the b values 0, 150 and 800 s/mm² was significantly higher in tumors than in healthy tissue in both PZ (P < 0.001, area under the curve [AUC] = 0.85) and PZ + TZ (P < 0.001, AUC = 0.84). RED was shown to aid apparent diffusion coefficient (ADC) in differentiating between false-positive findings and true-positive PCa in the PZ (AUC; RED = 0.71, ADC = 0.74, RED+ADC = 0.77).

DATA CONCLUSION

RED is a repeatable biomarker that may have value for prostate cancer diagnosis. An intermediate b value in the range of 150-250 s/mm² minimizes the influence of noise and maximizes repeatability.

LEVEL OF EVIDENCE

2 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2020;51:1900-1910.

Multiparametric MRI and auto-fixed volume of interest-based radiomics signature for clinically significant peripheral zone prostate cancer

Objectives

To create a radiomics approach based on multiparametric magnetic resonance imaging (mpMRI) features extracted from an auto-fixed volume of interest (VOI) that quantifies the phenotype of clinically significant (CS) peripheral zone (PZ) prostate cancer (PCa).

Methods

This study included 206 patients with 262 prospectively called mpMRI prostate imaging reporting and data system 3–5 PZ lesions. Gleason scores > 6 were defined as CS PCa. Features were extracted with an auto-fixed 12-mm spherical VOI placed around a pin point in each lesion. The value of dynamic contrast-enhanced imaging(DCE), multivariate feature selection and extreme gradient boosting (XGB) vs. univariate feature selection and random forest (RF), expert-based feature pre-selection, and the addition of image filters was investigated using the training (171 lesions) and test (91 lesions) datasets.

Results

The best model with features from T2-weighted (T2-w) + diffusion-weighted imaging (DWI) + DCE had an area under the curve (AUC) of 0.870 (95% CI 0.980–0.754). Removal of DCE features decreased AUC to 0.816 (95% CI 0.920–0.710), although not significantly (p = 0.119). Multivariate and XGB outperformed univariate and RF (p = 0.028). Expert-based feature pre-selection and image filters had no significant contribution.

Conclusions

The phenotype of CS PZ PCa lesions can be quantified using a radiomics approach based on features extracted from T2-w + DWI using an auto-fixed VOI. Although DCE features improve diagnostic performance, this is not statistically significant. Multivariate feature selection and XGB should be preferred over univariate feature selection and RF. The developed model may be a valuable addition to traditional visual assessment in diagnosing CS PZ PCa.

Key Points

• T2-weighted and diffusion-weighted imaging features are essential components of a radiomics model for clinically significant prostate cancer; addition of dynamic contrast-enhanced imaging does not significantly improve diagnostic performance.

• Multivariate feature selection and extreme gradient outperform univariate feature selection and random forest.

• The developed radiomics model that extracts multiparametric MRI features with an auto-fixed volume of interest may be a valuable addition to visual assessment in diagnosing clinically significant prostate cancer.

Electronic supplementary material

The online version of this article (10.1007/s00330-019-06488-y) contains supplementary material, which is available to authorized users.

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.

Prostate Imaging Reporting and Data System 3 Category Cases at Multiparametric Magnetic Resonance for Prostate Cancer: A Systematic Review and Meta-analysis

CONTEXT

The Prostate Imaging Reporting and Data System (PI-RADS) 3 score represents a "grey zone" that need to be further investigated to solve the issue of whether to biopsy these equivocal cases or not.

OBJECTIVE

To critically analyze the current evidence on PI-RADS 3 cases. We evaluated the prevalence of PI-RADS 3 cases in the literature and detection rate of prostate cancer (PC) and clinically significant PC (csPC) at biopsy with regard to factors determining these rates.

EVIDENCE ACQUISITION

We searched in the Medline and Cochrane Library database from the literature from January 2009 to January 2019, following the Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA) guidelines.

EVIDENCE SYNTHESIS

A total of 28 studies were included in our analysis (total number of PI-RADS 3 cases: 1759, range 20-187). The prevalence of PI-RADS 3 cases reported in available studies was 17.3% (range 6.4-45.7%). The PC detection rate was 36% (95% confidence interval [CI] 33.8-37.4; range 10.3-55.8%), whereas that of csPC was 18.5% (95% CI 16.6-20.3; range 3.4-46.5%). Detection rates of PC and csPC were found to be similar in men who underwent a target biopsy versus those with a systematic biopsy (23.5% vs 23.9% and 11.4% vs 12.3%, respectively) and lower than the rates achieved with the combined strategy (36.9% and 19.6%, respectively). A prostate-specific antigen density (PSAD) of ≥0.15ng/ml/ml may represent an index to decide whether to submit a PI-RADS 3 case to biopsy.

CONCLUSIONS

In most investigations, PI-RADS 3 cases were not evaluated separately. A PI-RADS 3 lesion remains an equivocal lesion. Evaluation of clinical predictive factors in terms of csPC risk is a main aspect of helping clinicians in the biopsy decision process.

PATIENT SUMMARY

Management of Prostate Imaging Reporting and Data System 3 cases remains an unmet need, and the detection rate of clinically significant prostate cancer (csPC) among this population varies widely. Performing a combined target plus a systematic biopsy yields the highest detection of csPC. A prostate-specific antigen density of lower than 0.15ng/ml/ml may select patients for a follow-up strategy.

Evolution of prostate MRI: from multiparametric standard to less-is-better and different-is better strategies

Multiparametric magnetic resonance imaging (mpMRI) has become the standard of care to achieve accurate and reproducible diagnosis of prostate cancer. However, mpMRI is quite demanding in terms of technical rigour, patient's tolerability and safety, expertise in interpretation, and costs. This paper reviews the main technical strategies proposed as less-is-better solutions for clinical practice (non-contrast biparametric MRI, reduction of acquisition time, abbreviated protocols, computer-aided diagnosis systems), discussing them in the light of the available evidence and of the concurrent evolution of Prostate Imaging Reporting and Data System (PI-RADS). We also summarised research results on those advanced techniques representing an alternative different-is-better line of the still ongoing evolution of prostate MRI (quantitative diffusion-weighted imaging, quantitative dynamic contrast enhancement, intravoxel incoherent motion, diffusion tensor imaging, diffusional kurtosis imaging, restriction spectrum imaging, radiomics analysis, hybrid positron emission tomography/MRI).

Short review of biparametric prostate MRI

Magnetic resonance imaging (MRI) of the prostate has become the gold standard for visualization of prostate cancer. Prostate MRI is usually performed as multiparametric MRI (mpMRI). Since mpMRI has several drawbacks, a biparametric MRI (bpMRI) of the prostate has been proposed. Many studies have been published on mpMRI and bpMRI in recent years. This short review offers an overview of the latest developments in this rapidly evolving field of research.