Prostate cancer screening: the clinical value of diffusion-weighted imaging and dynamic MR imaging in combination with T2-weighted imaging

Automatic segmentation of prostate MRI based on 3D pyramid pooling Unet

PURPOSE

Automatic segmentation of prostate magnetic resonance (MR) images is crucial for the diagnosis, evaluation, and prognosis of prostate diseases (including prostate cancer). In recent years, the mainstream segmentation method for the prostate has been converted to convolutional neural networks. However, owing to the complexity of the tissue structure in MR images and the limitations of existing methods in spatial context modeling, the segmentation performance should be improved further.

METHODS

In this study, we proposed a novel 3D pyramid pool Unet that benefits from the pyramid pooling structure embedded in the skip connection (SC) and the deep supervision (DS) in the up-sampling of the 3D Unet. The parallel SC of the conventional 3D Unet network causes low-resolution information to be sent to the feature map repeatedly, resulting in blurred image features. To overcome the shortcomings of the conventional 3D Unet, we merge each decoder layer with the feature map of the same scale as the encoder and the smaller scale feature map of the pyramid pooling encoder. This SC combines the low-level details and high-level semantics at two different levels of feature maps. In addition, pyramid pooling performs multifaceted feature extraction on each image behind the convolutional layer, and DS learns hierarchical representations from comprehensive aggregated feature maps, which can improve the accuracy of the task.

RESULTS

Experiments on 3D prostate MR images of 78 patients demonstrated that our results were highly correlated with expert manual segmentation. The average relative volume difference and Dice similarity coefficient of the prostate volume area were 2.32% and 91.03%, respectively.

CONCLUSION

Quantitative experiments demonstrate that, compared with other methods, the results of our method are highly consistent with the expert manual segmentation.

Role of MRI in diagnosis of prostate cancer and correlation of results with transrectal ultrasound guided biopsy “TRUS”

Background

Prostate cancer is the most common cancer in elderly men, and the second leading cause of cancer-related death in developed countries. For a long time, TRUS is used in screening, diagnosis of prostate lesions. Recently the implementation of multi parametric MRI into a screening program currently seems to be the most promising technique to improve the early detection of prostate cancer.

Results

Thirty Patients were referred from urological outpatient clinics complaining of urological symptoms (dysuria, frequency and urine retention). The study was carried, and the patients were submitted to Ultrasonography, conventional magnetic resonance, diffusion weighted images and MR spectroscopy techniques, these results were correlated with histopathological data. In this study Conventional MRI has moderate sensitivity 81.8% and low specificity 37.3% in diagnosing prostate malignancy. Using of mpMRI combination of diffusion-weighted, Dynamic contrast enhanced and MR spectroscopic imaging is a promising approach for discriminating between benign and malignant lesions in the PZ and increase sensitivity 100% and specificity 96.6% in diagnosing prostate malignancy.

Conclusions

The standard for the definitive diagnosis of prostate cancer is trans-rectal ultrasound biopsy. However, TRUS guided biopsy has a significant sampling error and can miss up to 30% of cancers and may show underestimation of Gleason grade, especially in anteriorly located tumors. It may lead to an increase in complications. MRI has an essential role to play in making safer in diagnosis. It can aid in staging also and surgery or radiation treatment planning. Although T2W MRI has been used widely for diagnosis on the basis of its excellent soft tissue resolution, but its accuracy for the detection and localization of cancer prostate is unsatisfactory. The implementation of multi parametric MRI: MR spectroscopy, Dynamic contrast enhanced and diffusion weighted imaging into a diagnosis program improve the diagnostic performance. These advances are beginning to translate into better treatment selection and more accurate image-guided therapies. In addition, early detection of local recurrence.

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.

Automatic prostate and peri-prostatic fat segmentation based on pyramid mechanism fusion network for T2-weighted MRI

BACKGROUND AND OBJECTIVE

Automatic and accurate segmentation of prostate and peri-prostatic fat in male pelvic MRI images is a critical step in the diagnosis and prognosis of prostate cancer. The boundary of prostate tissue is not clear, which makes the task of automatic segmentation very challenging. The main issues, especially for the peri-prostatic fat, which is being offered for the first time, are hazy boundaries and a large form variation.

METHODS

We propose a pyramid mechanism fusion network (PMF-Net) to learn global features and more comprehensive context information. In the proposed PMF-Net, we devised two pyramid techniques in particular. A pyramid mechanism module made of dilated convolutions of varying rates is inserted before each down sample of the fundamental network architecture encoder. The module is intended to address the issue of information loss during the feature coding process, particularly in the case of segmentation object boundary information. In the transition stage from encoder to decoder, pyramid fusion module is designed to extract global features. The features of the decoder not only integrate the features of the previous stage after up sampling and the output features of pyramid mechanism, but also include the features of skipping connection transmission under the same scale of the encoder.

RESULTS

The segmentation results of prostate and peri-prostatic fat on numerous diverse male pelvic MRI datasets show that our proposed PMF-Net has higher performance than existing methods. The average surface distance (ASD) and Dice similarity coefficient (DSC) of prostate segmentation results reached 10.06 and 90.21%, respectively. The ASD and DSC of the peri-prostatic fat segmentation results reached 50.96 and 82.41%.

CONCLUSIONS

The results of our segmentation are substantially connected and consistent with those of expert manual segmentation. Furthermore, peri-prostatic fat segmentation is a new issue, and good automatic segmentation has substantial therapeutic implications.

Prostate cancer in PI-RADS scores 1 and 2 version 2.1: a comparison to previous PI-RADS versions

PURPOSE

To evaluate the validity of PI-RADS categories 1 and 2 version 2.1 (V2.1) as predictors of the absence of carcinoma and to reevaluate lesions that were analysed as suspicious prior to PI-RADS or according to PI-RADS versions 1 and 2 and classified as PI-RADS 1 or 2 in V2.1.

METHODS

Retrospective evaluation of 1170 multiparametric MRIs performed at one academic teaching hospital (2012-2019). Study cohort comprised 188 men that achieved PI-RADS scores 1 or 2 (V2.1) and underwent systematic and targeted biopsy, split into one group with suspect findings in the original reports that were created prior to PI-RADS or with version 1 and 2, and another group with unremarkable reports. Differences in presence of prostate cancer and PSA density were assessed by Chi-square and Fisher's exact test, and the negative predictive value (NPV) for both groups was conducted.

RESULTS

The NPV for clinically significant carcinoma (csCa) was 89.1% for 55 men with suspect findings in the original report and 93.2% for 133 men with negative MRI. There was no difference between the groups regarding the detection of csCa (p = 0.103). PSA density was significantly higher in the group with suspect original reports (p = 0.015).

CONCLUSION

A PI-RADS score 1 or 2 appears less likely to miss existing prostate cancer, although a small amount of csCa can be overlooked. In case of clinical suspicion or elevated PSA density and PI-RADS score 1 or 2, an individual decision has to be taken if biopsy is necessary or if monitoring is sufficient.

Progress in prostate cancer prevention

After lung, prostate cancer is the second most frequently diagnosed cancer and fourth in cancer-related mortality. The etiology is largely unknown and no clear risk factors have been identified. Primary prevention is therefore challenging. Also, secondary prevention, screening, in large populations is difficult. Germline mutations are implicated in hereditary prostate cancer, accounting for about 10% of screened men. Currently, only prostate-specific antigen test is adopted for early detection but is considered insufficient to further improve prevention and care. In this opinion article, we discuss novel diagnostic biomarkers and imaging tools, along with more promising targeted prostate biopsies.

Prostate zones and cancer: lost in transition?

Localized prostate cancer shows great clinical, genetic and environmental heterogeneity; however, prostate cancer treatment is currently guided solely by clinical staging, serum PSA levels and histology. Increasingly, the roles of differential genomics, multifocality and spatial distribution in tumorigenesis are being considered to further personalize treatment. The human prostate is divided into three zones based on its histological features: the peripheral zone (PZ), the transition zone (TZ) and the central zone (CZ). Each zone has variable prostate cancer incidence, prognosis and outcomes, with TZ prostate tumours having better clinical outcomes than PZ and CZ tumours. Molecular and cell biological studies can improve understanding of the unique molecular, genomic and zonal cell type features that underlie the differences in tumour progression and aggression between the zones. The unique biology of each zonal tumour type could help to guide individualized treatment and patient risk stratification.

Diagnostic accuracy of bi-parametric magnetic resonance imaging in suspected prostate cancer: Correlation of scan results with biopsy findings in a series of 266 patients

Objectives:

This study aimed to determine the diagnostic accuracy of bi-parametric magnetic resonance imaging (bpMRI) for clinically significant (CS) prostate cancer (PCa), and to assess the suitability of a new diagnostic pathway using bpMRI and prostate-specific antigen density (PSAd) to determine the need for biopsy.

Methods:

A total of 386 patients referred to one UK cancer centre with suspected PCa across 12 months from 2017 to 2018 underwent bpMRI, with a Prostate Imaging Reporting and Data System (PIRADS) score assigned. Of these, 266 (69%) were biopsied, with 150 CS-PCa (a Gleason score of 7 or a Gleason score of 3 with core length ⩾5 mm) detected: a 57% diagnostic yield. Imaging, PSAd and biopsy results were collated, and a confusion matrix was calculated.

Results:

Twenty-three men with PIRADS 1 were biopsied, with two CS-PCa detected: PSAd M=0.19 ( SD=0.07). Twenty-one men with PIRADS 2 lesions were biopsied, with one CS-PCa detected: PSAd was 0.28. Seventy-five men with PIRADS 3 were biopsied, with 25 CS-PCa detected: PSAd M=0.26 ( SD=0.16). Fifty-seven men with PIRADS 4 were biopsied, with 46 CS-PCa detected: PSAd M=0.26 ( SD=0.16). Ninety men with PIRADS 5 were biopsied, with 83 CS-PCa detected: PSAd M=0.55 ( SD=0.63). Among the 266 biopsied patients, a pathway offering biopsy if PIRADS is ⩾3 or PSAd ⩾0.1 spares 11 (4.2%) biopsies compared to baseline practice, with a sensitivity of 100% and a specificity of 10.1%, for biopsy-detected CS-PCa. The diagnostic yield is 61.8%.

Conclusion:

BpMRI is comparable to multi-parametric MRI for assessing need for biopsy in suspected PCa, albeit with lower specificity. A diagnostic pathway using bpMRI and PSAd can be safely used to avoid biopsy in men at low risk, increasing diagnostic yield of biopsy while reducing overdiagnosis and avoiding the risks and costs associated with gadolinium contrast.

Level of evidence:

Level 4.

Making a science out of preanalytics: An analytical method to determine optimal tissue fixation in real-time

Modern histopathology is built on the cornerstone principle of tissue fixation, however there are currently no analytical methods of detecting fixation and as a result, in clinical practice fixation is highly variable and a persistent source of error. We have previously shown that immersion in cold formalin followed by heated formalin is beneficial for preservation of histomorphology and have combined two-temperature fixation with ultra-sensitive acoustic monitoring technology that can actively detect formalin diffusing into a tissue. Here we expand on our previous work by developing a predictive statistical model to determine when a tissue is properly diffused based on the real-time acoustic signal. We trained the model based on the morphology and characteristic diffusion curves of 30 tonsil cores. To test our model, a set of 87 different tonsil samples were fixed with four different protocols: dynamic fixation according to our predictive algorithm (C/H:Dynamic, N = 18), gold-standard 24 hour room temperature (RT:24hr, N = 24), 6 hours in cold formalin followed by 1 hour in heated formalin (C/H:6+1, N = 21), and 2 hours in cold formalin followed by 1 hour in heated formalin (C/H:2+1, N = 24). Digital pathology analysis revealed that the C/H:Dynamic samples had FOXP3 staining that was spatially uniform and statistically equivalent to RT:24hr and C/H:6+1 fixation protocols. For comparison, the intentionally underfixed C/H:2+1 samples had significantly suppressed FOXP3 staining (p<0.002). Furthermore, our dynamic fixation protocol produced bcl-2 staining concordant with standard fixation techniques. The dynamically fixed samples were on average only submerged in cold formalin for 4.2 hours, representing a significant workflow improvement. We have successfully demonstrated a first-of-its-kind analytical method to assess the quality of fixation in real-time and have confirmed its performance with quantitative analysis of downstream staining. This innovative technology could be used to ensure high-quality and standardized staining as part of an expedited and fully documented preanalytical workflow.

A systematic review and meta-analysis of the diagnostic accuracy of biparametric prostate MRI for prostate cancer in men at risk

INTRODUCTION

Multiparametric magnetic resonance imaging (mpMRI), the use of three multiple imaging sequences, typically T2-weighted, diffusion weighted (DWI) and dynamic contrast enhanced (DCE) images, has a high sensitivity and specificity for detecting significant cancer. Current guidance now recommends its use prior to biopsy. However, the impact of DCE is currently under debate regarding test accuracy. Biparametric MRI (bpMRI), using only T2 and DWI has been proposed as a viable alternative. We conducted a contemporary systematic review and meta-analysis to further examine the diagnostic performance of bpMRI in the diagnosis of any and clinically significant prostate cancer.

METHODS

A systematic review of the literature from 01/01/2017 to 06/07/2019 was performed by two independent reviewers using predefined search criteria. The index test was biparametric MRI and the reference standard whole-mount prostatectomy or prostate biopsy. Quality of included studies was assessed by the QUADAS-2 tool. Statistical analysis included pooled diagnostic performance (sensitivity; specificity; AUC), meta-regression of possible covariates and head-to-head comparisons of bpMRI and mpMRI where both were performed in the same study.

RESULTS

Forty-four articles were included in the analysis. The pooled sensitivity for any cancer detection was 0.84 (95% CI, 0.80-0.88), specificity 0.75 (95% CI, 0.68-0.81) for bpMRI. The summary ROC curve yielded a high AUC value (AUC = 0.86). The pooled sensitivity for clinically significant prostate cancer was 0.87 (95% CI, 0.78-0.93), specificity 0.72 (95% CI, 0.56-0.84) and the AUC value was 0.87. Meta-regression analysis revealed no difference in the pooled diagnostic estimates between bpMRI and mpMRI.

CONCLUSIONS

This meta-analysis on contemporary studies shows that bpMRI offers comparable test accuracies to mpMRI in detecting prostate cancer. These data are broadly supportive of the bpMRI approach but heterogeneity does not allow definitive recommendations to be made. There is a need for prospective multicentre studies of bpMRI in biopsy naïve men.

Revisiting DCE-MRI: Classification of Prostate Tissue Using Descriptive Signal Enhancement Features Derived From DCE-MRI Acquisition With High Spatiotemporal Resolution

METHODS

A retrospective study (from January 2016 to July 2019) including 75 subjects (mean, 65 years; 46-80 years) with 2.5-second temporal resolution DCE-MRI and PIRADS 4 or 5 lesions was performed. Fifty-four subjects had biopsy-proven prostate cancer (Gleason 6, 15; Gleason 7, 20; Gleason 8, 13; Gleason 9, 6), whereas 21 subjects had negative MRI/ultrasound fusion-guided biopsies. Voxel-wise analysis of contrast signal enhancement was performed for all time points using custom-developed software, including automatic arterial input function detection. Seven descriptive parameter maps were calculated: normalized maximum signal intensity, time to start, time to maximum, time-to-maximum slope, and maximum slope with normalization on maximum signal and the arterial input function (SMN1, SMN2). The parameters were compared with ADC using multiparametric machine-learning models to determine classification accuracy. A Wilcoxon test was used for the hypothesis test and the Spearman coefficient for correlation.

RESULTS

There were significant differences (P < 0.05) for all 7 DCE-derived parameters between the normal peripheral zone versus PIRADS 4 or 5 lesions and the biopsy-positive versus biopsy-negative lesions. Multiparametric analysis showed better performance when combining ADC + DCE as input (accuracy/sensitivity/specificity, 97%/93%/100%) relative to ADC alone (accuracy/sensitivity/specificity, 94%/95%/95%) and to DCE alone (accuracy/sensitivity/specificity, 78%/79%/77%) in differentiating the normal peripheral zone from PIRADS lesions, biopsy-positive versus biopsy-negative lesions (accuracy/sensitivity/specificity, 68%/33%/81%), and Gleason 6 versus ≥7 prostate cancer (accuracy/sensitivity/specificity, 69%/60%/72%).

CONCLUSIONS

Descriptive perfusion characteristics derived from high-resolution DCE-MRI using model-free computations show significant differences between normal and cancerous tissue but do not reach the accuracy achieved with solely ADC-based classification. Combining ADC with DCE-based input features improved classification accuracy for PIRADS lesions, discrimination of biopsy-positive versus biopsy-negative lesions, and differentiation between Gleason 6 versus Gleason ≥7 lesions.

Simplified PI-RADS (S-PI-RADS) for biparametric MRI to detect and manage prostate cancer: What urologists need to know

Biparametric magnetic resonance imaging (bpMRI) of the prostate has emerged as an alternative to multiparametric MRI (mpMRI) for the detection of clinically significant prostate cancer (csPCa). However, while the Prostate Imaging Reporting and Data System (PI-RADS) is widely known for mpMRI, a proper PI-RADS for bpMRI has not yet been adopted. In this review, we report the current status and the future directions of bpMRI, and propose a simplified PI-RADS (S-PI-RADS) that could help radiologists and urologists in the detection and management of PCa.

Radiomics and Prostate MRI: Current Role and Future Applications

Multiparametric prostate magnetic resonance imaging (mpMRI) is widely used as a triage test for men at a risk of prostate cancer. However, the traditional role of mpMRI was confined to prostate cancer staging. Radiomics is the quantitative extraction and analysis of minable data from medical images; it is emerging as a promising tool to detect and categorize prostate lesions. In this paper we review the role of radiomics applied to prostate mpMRI in detection and localization of prostate cancer, prediction of Gleason score and PI-RADS classification, prediction of extracapsular extension and of biochemical recurrence. We also provide a future perspective of artificial intelligence (machine learning and deep learning) applied to the field of prostate cancer.

Practice Patterns and Challenges of Performing and Interpreting Prostate MRI: A Survey by the Society of Abdominal Radiology Prostate Disease-Focused Panel

OBJECTIVE. The purpose of this study was to report on the practice patterns and challenges of performing and interpreting prostate MRI. SUBJECTS AND METHODS. An electronic survey regarding prostate MRI practice patterns and challenges was sent to members of the Society of Abdominal Radiology. RESULTS. The response rate was 15% (212/1446). Most (65%) of the respondents were academic abdominal radiologists with 1-5 (52%), 6-10 (20%), 11-20 (15%), and more than 20 (5%) years of experience in reporting prostate MRI. The numbers of prostate MRI examinations reported per week were 0-5 (43%), 6-10 (38%), 11-20 (12%), 21-30 (5%), and more than 30 (2%). Imaging was performed at 3 T (58%), 1.5 T (20%), or either (21%), and most examinations (83%) were performed without an endorectal coil. Highest b values ranged from 800 to 5000 s/mm²; 1400 s/mm² (26%) and 1500 s/mm² (30%) were the most common. Most respondents (79%) acquired dynamic contrast-enhanced images with temporal resolution of less than 10 seconds. Most (71%) of the prostate MRI studies were used for fusion biopsy. PI-RADS version 2 was used by 92% of the respondents and template reporting by 80%. Challenges to performing and interpreting prostate MRI were scored on a 1-5 Likert scale (1, easy; 2, somewhat easy; 3, neutral; 4, somewhat difficult; 5, very difficult). The median scores were 2 or 3 for patient preparatory factors. Image acquisition and reporting factors were scored 1-2, except for performing spectroscopy or using an endorectal coil, both of which scored 4. Acquiring patient history scored 2 and quality factors scored 3. CONCLUSION. Most radiologists perform prostate MRI at 3 T without an endorectal coil and interpret the images using PI-RADS version 2. Challenges include obtaining quality images, acquiring feedback, and variability in the interpretation of PI-RADS scores.

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.

Is dynamic contrast enhancement still necessary in multiparametric magnetic resonance for diagnosis of prostate cancer: a systematic review and meta-analysis

Background

The purpose of this study is to systematically review the literatures assessing the value of dynamic contrast enhancement (DCE) in the multiparametric magnetic resonance imaging (mpMRI) for the diagnosis of prostate cancer (PCa).

Methods

We searched Embase, PubMed and Web of science until January 2019 to extract articles exploring the possibilities whether the pre-biopsy biparametric magnetic resonance imaging (bpMRI) can replace the position of mpMRI in the diagnosis of PCa. The sensitivity and specificity of bpMRI were all included. The study quality was assessed by QUADAS-2. Bivariate random effects meta-analyses and a hierarchical summary receiver operating characteristic plot were performed for further study through Revman 5 and Stata12.

Results

After searching, we acquired 752 articles among which 45 studies with 5,217 participants were eligible for inclusion. The positive likelihood ratio for the detection of PCa was 2.40 (95% CI: 1.50–3.80) and the negative likelihood ratio was 0.31 (95% CI: 0.18–0.53). The sensitivity and specificity were 0.77 (95% CI: 0.73–0.81) and 0.81 (95% CI: 0.76–0.85) respectively. Based on our result, pooled specificity demonstrated little difference between bpMRI and mpMRI [bpMRI, 0.81 (95% CI, 0.76–0.85); mpMRI, 0.82 (95% CI, 0.72–0.88); P=0.169]. The sensitivity, however, indicated a significant difference between these two groups [bpMRI, 0.77 (95% CI, 0.73–0.81); mpMRI, 0.84 (95% CI, 0.78–0.89); P=0.001].

Conclusions

bpMRI with high b-value is a sensitive tool for diagnosing PCa. Consistent results were found in multiple subgroup analysis.

Noninvasive Prediction of High-Grade Prostate Cancer via Biparametric MRI Radiomics

BACKGROUND

Gleason score (GS) is a histologic prognostic factor and the basis of treatment decision-making for prostate cancer (PCa). Treatment regimens between lower-grade (GS ≤7) and high-grade (GS >7) PCa differ largely and have great effects on cancer progression.

PURPOSE

To investigate the use of different sequences in biparametric MRI (bpMRI) of the prostate gland for noninvasively distinguishing high-grade PCa.

STUDY TYPE

Retrospective.

POPULATION

In all, 489 patients (training cohort: N = 326; test cohort: N = 163) with PCa between June 2008 and January 2018.

FIELD STRENGTH/SEQUENCE

3.0T, pelvic phased-array coils, bpMRI including T₂ -weighted imaging (T₂ WI) and diffusion-weighted imaging (DWI); apparent diffusion coefficient map extracted from DWI.

ASSESSMENT

The whole prostate gland was delineated. Radiomic features were extracted and selected using the Kruskal-Wallis test, the minimum redundancy-maximum relevance, and the sequential backward elimination algorithm. Two single-sequence radiomic (T₂ WI, DWI) and two combined (T₂ WI-DWI, T₂ WI-DWI-Clinic) models were respectively constructed and validated via logistic regression.

STATISTICAL TESTS

The Kruskal-Wallis test and chi-squared test were utilized to evaluate the differences among variable groups. P < 0.05 determined statistical significance. The area under the receiver operating characteristic curve (AUC), specificity, sensitivity, and accuracy were used to evaluate model performance. The Delong test was conducted to compare the differences between the AUCs of all models.

RESULT

All radiomic models showed significant (P < 0.001) predictive performances. Between the single-sequence radiomic models, the DWI model achieved the most encouraging results, with AUCs of 0.801 and 0.787 in the training and test cohorts, respectively. For the combined models, the T₂ WI-DWI models acquired an AUC of 0.788, which was almost the same with DWI in the test cohort, and no significant difference was found between them (training cohort: P = 0.199; test cohort: P = 0.924).

DATA CONCLUSION

Radiomics based on bpMRI can noninvasively identify high-grade PCa before the operation, which is helpful for individualized diagnosis of PCa.

LEVEL OF EVIDENCE

4 TECHNICAL EFFICACY STAGE: 2 J. Magn. Reson. Imaging 2020;52:1102-1109.

Similarities and differences between Likert and PIRADS v2.1 scores of prostate multiparametric MRI: a pictorial review of histology-validated cases

The UK National Institute for Health and Care Excellence (NICE) 2019 "Prostate cancer: diagnosis and management" guidelines have recommended that all patients suspected of prostate cancer undergo multiparametric magnetic resonance imaging (mpMRI) prior to biopsy. The Likert scoring system is advocated for mpMRI reporting based on multicentre studies that have demonstrated its effectiveness within the National Health Service (NHS). In recent years, there has been considerable drive towards standardised prostate reporting, which led to the development of "Prostate Imaging-Reporting And Data System" (PI-RADS). The PI-RADS system has been adopted by the majority of European countries and within the US. This paper reviews these systems indicating the similarities and specific differences that exist between PI-RADS and Likert assessment through a series of histologically proven clinical cases.

Landmarks in prostate cancer

The field of prostate cancer has been the subject of extensive research that has resulted in important discoveries and shaped our appreciation of this disease and its management. Advances in our understanding of the epidemiology, natural history, anatomy, detection, diagnosis, grading, staging, imaging, and management of prostate cancer have changed clinical practice and influenced guideline recommendations. The development of the Gleason score and subsequent modifications enabled accurate prediction of prognosis. Increased anatomical understanding and improved surgical techniques resulted in the development of nerve-sparing surgery for radical prostatectomy. The advent of active surveillance has changed the management of low-risk disease, and chemotherapy and hormonal therapy have improved the outcomes of patients with distant disease. Ongoing research and clinical trials are expected to yield more practice-changing results in the near future.

Quantitative evaluation of computed and voxelwise computed diffusion-weighted imaging in breast cancer

OBJECTIVES

To assess the value of computed diffusion-weighted imaging (cDWI) and voxelwise computed diffusion-weighted imaging (vcDWI) in breast cancer.

METHODS

This retrospective study involved 130 patients (age range, 25-70 years; mean age ± standard deviation, 48.6 ± 10.5 years) with 130 malignant lesions, who underwent MRI examinations, including a DWI sequence, prior to needle biopsy or surgery. cDWIs with higher b-values of 1500, 2000, 2500, 3000, 3500, and 4000 s/mm², and vcDWI were generated from measured (m) DWI with two lower b-values of 0/600, 0/800, or 0/1000 s/mm². The signal-to-noise ratio (SNR) and contrast ratio (CR) of all image sets were computed and compared among different DWIs by two experienced radiologists independently. To better compare the CR with the SNR, the CR value was multiplied by 100 (CR100).

RESULTS

The CR of vcDWI, and cDWIs, except for cDWI₁₀₀₀, differed significantly from that of measured diffusion-weighted imaging (mDWI) (cDWI₁₀₀₀: CR = 0.4904, p = 0.394; cDWI₁₅₀₀: CR = 0.5503, p = 0.006; cDWI₂₀₀₀: CR = 0.5889, p < 0.001; cDWI₂₅₀₀: CR = 0.6109, p < 0.001; cDWI₃₀₀₀: mean = 0.6214, p < 0.001; cDWI₃₅₀₀: CR = 0.6245, p < 0.001; cDWI₄₀₀₀: CR = 0.6228, p < 0.001). The vcDWI provided the highest CR, while the CRs of all cDWI image sets improved with increased b-values. The SNR of neither cDWI₁₀₀₀ nor vcDWI differed significantly from that of mDWI, but the mean SNRs of the remaining cDWIs were significantly lower than that of mDWI. The SNRs of cDWIs declined with increasing b-values, and the initial decrease at low b-values was steeper than the gradual attenuation at higher b-values; the CR₁₀₀ rose gradually, and the two converged on the b-value interval of 1500-2000 s/mm² .

CONCLUSIONS

The highest CR was achieved with vcDWI; this could be a promising approach easier detection of breast cancer.

ADVANCES IN KNOWLEDGE

This study comprehensively compared and evaluated the value of the emerging post-processing DWI techniques (including a set of cDWIs and vcDWI) in breast cancer.

Comparison of diagnostic value of multi-slice spiral CT and MRI for different pathological stages of prostate cancer

Diagnostic value of magnetic resonance imaging (MRI) and multi-slice spiral CT (MSCT) for different pathological stages of prostate cancer was compared. A total of 112 patients with prostate cancer who underwent surgical pathology in The Affiliated Yantai Yuhuangding Hospital of Qingdao University from February 2014 to January 2016 were enrolled as prostate cancer group, and another 100 patients who received physical health examinations during the same period as the normal group. MSCT and MRI scanning were performed on patients in both groups to analyze their diagnostic value for stages A/B and C/D of prostate cancer. Based on the apparent diffusion coefficient (ADC) value generated by the diffusion-weighted imaging (DWI) in MRI, there was a significant difference in the ADC value between different stages of prostate cancer (P<0.05); the pathological stage was negatively correlated with the ADC value (r=−0.7629, P<0.05), and the higher the stage was, the lower the ADC value was. The sensitivity was significantly higher in the MRI group than that in the MSCT group (92.0 vs. 79.5%, P<0.05), and the specificity was significantly higher in the MRI group than that in the MSCT group (90.0 vs. 70.0%, P<0.05). In the diagnosis of stage A and B of prostate cancer, the diagnostic coincidence rate was 86.7% in the MRI group, and 57.8% in the MSCT group (P<0.05); the misdiagnosis rate and missed diagnosis rate were significantly lower in the MRI group than those in the MSCT group (P<0.05). The accuracy of MRI is higher than that of MSCT in the diagnosis of early prostate cancer. Both MRI and MSCT can accurately detect stages C and D of prostate cancer, but the ADC value in MRI has great clinical significance for judging the risk of the tumor. Therefore, MRI is more valuable than MSCT in the diagnosis of patients with different pathological stages of prostate cancer.

Multiparametric MRI to improve detection of prostate cancer compared with transrectal ultrasound-guided prostate biopsy alone: the PROMIS study

BACKGROUND

Men with suspected prostate cancer usually undergo transrectal ultrasound (TRUS)-guided prostate biopsy. TRUS-guided biopsy can cause side effects and has relatively poor diagnostic accuracy. Multiparametric magnetic resonance imaging (mpMRI) used as a triage test might allow men to avoid unnecessary TRUS-guided biopsy and improve diagnostic accuracy.

OBJECTIVES

To (1) assess the ability of mpMRI to identify men who can safely avoid unnecessary biopsy, (2) assess the ability of the mpMRI-based pathway to improve the rate of detection of clinically significant (CS) cancer compared with TRUS-guided biopsy and (3) estimate the cost-effectiveness of a mpMRI-based diagnostic pathway.

DESIGN

A validating paired-cohort study and an economic evaluation using a decision-analytic model.

SETTING

Eleven NHS hospitals in England.

PARTICIPANTS

Men at risk of prostate cancer undergoing a first prostate biopsy.

INTERVENTIONS

Participants underwent three tests: (1) mpMRI (the index test), (2) TRUS-guided biopsy (the current standard) and (3) template prostate mapping (TPM) biopsy (the reference test).

MAIN OUTCOME MEASURES

Diagnostic accuracy of mpMRI, TRUS-guided biopsy and TPM-biopsy measured by sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) using primary and secondary definitions of CS cancer. The percentage of negative magnetic resonance imaging (MRI) scans was used to identify men who might be able to avoid biopsy.

RESULTS

Diagnostic study - a total of 740 men were registered and 576 underwent all three tests. According to TPM-biopsy, the prevalence of any cancer was 71% [95% confidence interval (CI) 67% to 75%]. The prevalence of CS cancer according to the primary definition (a Gleason score of ≥ 4 + 3 and/or cancer core length of ≥ 6 mm) was 40% (95% CI 36% to 44%). For CS cancer, TRUS-guided biopsy showed a sensitivity of 48% (95% CI 42% to 55%), specificity of 96% (95% CI 94% to 98%), PPV of 90% (95% CI 83% to 94%) and NPV of 74% (95% CI 69% to 78%). The sensitivity of mpMRI was 93% (95% CI 88% to 96%), specificity was 41% (95% CI 36% to 46%), PPV was 51% (95% CI 46% to 56%) and NPV was 89% (95% CI 83% to 94%). A negative mpMRI scan was recorded for 158 men (27%). Of these, 17 were found to have CS cancer on TPM-biopsy. Economic evaluation - the most cost-effective strategy involved testing all men with mpMRI, followed by MRI-guided TRUS-guided biopsy in those patients with suspected CS cancer, followed by rebiopsy if CS cancer was not detected. This strategy is cost-effective at the TRUS-guided biopsy definition 2 (any Gleason pattern of ≥ 4 and/or cancer core length of ≥ 4 mm), mpMRI definition 2 (lesion volume of ≥ 0.2 ml and/or Gleason score of ≥ 3 + 4) and cut-off point 2 (likely to be benign) and detects 95% (95% CI 92% to 98%) of CS cancers. The main drivers of cost-effectiveness were the unit costs of tests, the improvement in sensitivity of MRI-guided TRUS-guided biopsy compared with blind TRUS-guided biopsy and the longer-term costs and outcomes of men with cancer.

LIMITATIONS

The PROstate Magnetic resonance Imaging Study (PROMIS) was carried out in a selected group and excluded men with a prostate volume of > 100 ml, who are less likely to have cancer. The limitations in the economic modelling arise from the limited evidence on the long-term outcomes of men with prostate cancer and on the sensitivity of MRI-targeted repeat biopsy.

CONCLUSIONS

Incorporating mpMRI into the diagnostic pathway as an initial test prior to prostate biopsy may (1) reduce the proportion of men having unnecessary biopsies, (2) improve the detection of CS prostate cancer and (3) increase the cost-effectiveness of the prostate cancer diagnostic and therapeutic pathway. The PROMIS data set will be used for future research; this is likely to include modelling prognostic factors for CS cancer, optimising MRI scan sequencing and biomarker or translational research analyses using the blood and urine samples collected. Better-quality evidence on long-term outcomes in prostate cancer under the various management strategies is required to better assess cost-effectiveness. The value-of-information analysis should be developed further to assess new research to commission.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN16082556 and NCT01292291.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 22, No. 39. See the NIHR Journals Library website for further project information. This project was also supported and partially funded by the NIHR Biomedical Research Centre at University College London (UCL) Hospitals NHS Foundation Trust and UCL and by The Royal Marsden NHS Foundation Trust and The Institute of Cancer Research Biomedical Research Centre and was co-ordinated by the Medical Research Council's Clinical Trials Unit at UCL (grant code MC_UU_12023/28). It was sponsored by UCL. Funding for the additional collection of blood and urine samples for translational research was provided by Prostate Cancer UK.

Who Can Avoid Systematic Biopsy Without Missing Clinically Significant Prostate Cancer in Men Who Undergo Magnetic Resonance Imaging-Targeted Biopsy?

BACKGROUND

The objective of the study was to identify a subset of men who can avoid systematic multisite biopsy (SyB) among those undergoing magnetic resonance imaging (MRI)-targeted transperineal 4-core biopsy (TgB) without missing clinically significant cancer (SC).

PATIENTS AND METHODS

From April 2013 to December 2017, 304 men with elevated prostate-specific antigen levels (< 20 ng/mL) or abnormal digital rectal examination and positive MRI findings underwent transrecta ultrasound and MRI-targeted transperineal 4-core with 14-core systematic biopsy. MRI findings were prospectively collected and evaluated using Prostate Imaging-Reporting and Data System version 2 (PI-RADS), and scores ≥3 were considered positive. SC was defined as Gleason score ≥3 + 4 or maximum cancer length ≥5 mm. We evaluated the diagnostic performance of TgB and SyB to detect SC and characterized men who could avoid SyB without missing SC.

RESULTS

Detection rates of any cancer and SC for TgB/SyB/their combination were 59%/63%/68% and 51%/52%/61%, respectively. TgB alone missed 14% (29/207) of any cancer and 16% (29/184) of SC detected using TgB with SyB. In uni- and multivariable analyses, PI-RADS scores of 3 to 4 were independent predictors for missing SC using TgB alone. When restricted to 81 men with PI-RADS scores of 5 (27%), SC was missed using TgB alone only in 3 (4.6% vs. 22% for the remaining 223 men; P = .007).

CONCLUSION

SC was missed using TgB alone in a non-negligible proportion of men who underwent TgB and SyB. SyB might be safely avoided in men with PI-RADS score 5 lesions with reduced risks of missing SC.

Analysis of Diffusion-weighted MR Images Based on a Gamma Distribution Model to Differentiate Prostate Cancers with Different Gleason Score

Purpose:

Prostate cancer management includes identification of clinically significant cancers that may require curative treatment. Statistical models based on gamma distribution can describe diffusion signal decay curves of prostate cancer. The purpose of this study was to evaluate the ability of parameters obtained with the gamma model in differentiating prostate cancers with different Gleason score values.

Methods:

This study included 155 patients with prostate cancer who underwent multiparametric magnetic resonance imaging prior to prostate biopsy (127 patients) or radical prostatectomy (28 patients) between January 2015 and June 2017; 159 foci of prostate cancer were included in our study. We compared cases scored as Gleason score (GS) 3 + 3 and GS ≥ 3 + 4, and analyzed cases scored as GS ≤ 3+ 4 and GS ≥ 4 + 3 based on the gamma model (Frac < 1.0, Frac < 0.8, Frac < 0.5, Frac < 0.3, and Frac > 3.0), and apparent diffusion coefficient (ADC).

Results:

Among 159 cancerous lesions in 155 patients, 13 (8.2%) were GS 3 + 3 prostate cancers, 51 (32.0%) were GS 3 + 4 prostate cancers, 30 (18.2%) were GS 4 + 3 cancers, and 65 (40.9%) were GS ≥ 4 + 4 cancers. Frac < 0.3, Frac < 0.5, Frac < 0.8, and Frac < 1.0 were significantly higher and ADC values were significantly lower in GS ≥ 4 + 3 cancers than in GS ≤ 3 + 4 cancers (P < 0.01, P < 0.01, P < 0.01, P = 0.01, and P < 0.01, respectively). With receiver operating characteristic (ROC) analysis, Frac < 0.3 and Frac < 0.5 had significantly greater area under the ROC curve for discriminating GS ≥ 4 + 3 cancers from GS ≤ 3 + 4 cancers than ADC (P = 0.03, P < 0.01, respectively).

Conclusion:

Frac < 0.3 and Frac < 0.5 showed higher diagnostic performance than ADC for differentiating GS ≥ 4 + 3 from GS ≤ 3 + 4 cancers. The gamma model may add additional value in discrimination of tumor grades.

Multimodal PET/MRI Imaging Results Enable Monitoring the Side Effects of Radiation Therapy

Radiotherapy is one of the most frequently applied treatments in oncology. Tissue-absorbed ionizing radiation damages not only targeted cells but the surrounding cells too. The consequent long-term induced oxidative stress, irreversible tissue damage, or second malignancies draw attention to the urgent need of a follow-up medical method by which personalized treatment could be attained and the actually dose-limiting organ could be monitored in the clinical practice. We worked out a special hemisphere irradiation technique for mice which mimics the radiation exposure during radiotherapy. We followed up the changes of possible brain imaging biomarkers of side effects, such as cerebral blood flow, vascular endothelial function, and cellular metabolic processes for 60 days. BALB/c mice were divided into two groups (n=6 per group) based on the irradiation doses (5 and 20 Gy). After the irradiation procedure arterial spin labeling (ASL), diffusion-weighted imaging (DWI) in magnetic resonance modality and [¹⁸F]fluoro-deoxy-D-glucose positron emission tomography (FDG-PET) scans of the brain were obtained at several time points (3, 7, 30, and 60 days after the irradiation). Significant physiological changes were registered in the brain of animals following the irradiation by both applied doses. Elevated standard uptake values were detected all over the brain by FDG-PET studies 2 months after the irradiation. The apparent diffusion coefficients from DWI scans significantly decreased one month after the irradiation procedure, while ASL studies did not show any significant perfusion changes in the brain. Altogether, our sensitive multimodal imaging protocol seems to be an appropriate method for follow-up of the health status after radiation therapy. The presented approach makes possible parallel screening of healthy tissues and the effectiveness of tumor therapy without any additional radiation exposure.

Prospective comparison of a fast 1.5-T biparametric with the 3.0-T multiparametric ESUR magnetic resonance imaging protocol as a triage test for men at risk of prostate cancer

OBJECTIVE

To compare prospectively the diagnostic performance of a biparametric (T2-weighted imaging [T2WI] and diffusion-weighted imaging [DWI]) 1.5-T fast magnetic resonance imaging (fMRI) protocol with the standard 3.0-T multiparametric MRI (mpMRI) protocol of the European Society of Urological Imaging (ESUR) in men referred for a prostate biopsy.

PATIENTS AND METHODS

Ninety patients with a prostate cancer (PCa) risk of ≥10% according to the SWOP calculator 4 underwent first fMRI and then the reference mpMRI. Patients with Prostate Imaging Reporting and Data System (PI-RADS) v.2 lesions ≥3/5 on the mpMRI were scheduled for MRI/ultrasonography (US) fusion-guided prostate biopsy. Performance of fMRI was assessed using receiver-operating characteristic curve analysis and mpMRI as reference. Calculation of inter-technique agreement on PI-RADS v.2 score by Cohen's κ.

RESULTS

The diagnostic accuracy of fMRI shown by the lesion-based analysis was excellent: area under the curve (AUC) 0.961 (P < 0.001), sensitivity 95%, specificity 97%, positive predictive value (PPV) 99%, negative predictive value (NPV) 89%. The patient-based analysis showed an AUC for fMRI of 0.975 (P < 0.001), a sensitivity of 98%, a specificity of 97%, a PPV of 98% and an NPV of 97%. Agreement on the PI-RADS score between both protocols was found to be good (κ = 0.78 [0.57; 0.99]); fMRI missing PI-RADS 4 lesions in three patients. Biopsy results showed no cancer in two patients (two cores per nodule) and Gleason 6 cancer in one patient. There was only one false-positive fMRI, with a PI-RADS score of 4, whose biopsy was negative.

CONCLUSION

In the triage of men with a high risk of PCa for prostate biopsy, an f MRI protocol (1.5-T magnet, T2WI + DWI, <15 min) may safely replace the traditional ESUR 3.0-T mpMRI protocol, saving time and contrast injection.

Development of a robust diffusion-MR elastography (dMRE) technique to mitigate intravoxel phase dispersion

Diffusion-magnetic resonance elastography (dMRE) is an emerging practical technique that can acquire diffusion magnetic resonance imaging and MRE simultaneously. However, a signal loss attributable to intravoxel phase dispersion (IVPD) interferes with the calculation of the apparent diffusion coefficient (ADC). This study presents an approach to dMRE that reduces the influence of IVPD by introducing a new pulse sequence. The existing and proposed techniques were performed using a phantom comprising five rods with different elasticities at 60 Hz vibration to investigate the accuracy of previous and proposed dMRE techniques. The measures of ADC and stiffness, obtained by using both dMRE techniques, were compared with conventional spin-echo (SE) diffusion and SE-MRE. Then, we evaluated those differences by using the mean of absolute differences (MAD) in each rod within the phantom. The results of the MAD of the stiffness from both dMRE techniques showed almost no difference. In contrast, the value of the ADC MAD (MAD ≒ 0.16 × 10^-3 mm²/s), obtained in the soft region within the phantom with the previous dMRE technique, was large. This value was about 2.7 times that of the value produced by the proposed dMRE technique. This difference must reflect the degree of influence of IVPD in both techniques. These results demonstrate that our dMRE technique is a robust method for addressing the signal loss attributable to IVPD.

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

PURPOSE

To investigate, if and how omitting gadolinium-based contrast agents (GBCA) and dynamic contrast-enhanced imaging (DCE) influences diagnostic accuracy and tumor detection rates of prostate MRI.

METHODS

In this retrospective study, 236 patients were included. The results of biparametric (bpMRI) and multiparametric magnetic resonance imaging (mpMRI) were compared using the PI-RADS version 2 scoring system. The distribution of lesions to PIRADS score levels, tumor detection rates, diagnostic accuracy and RoC analysis were calculated and compared to the results of histopathological analysis or 5-year follow-up for benign findings.

RESULTS

Omitting DCE changed PI-RADS scores in 9.75% of patients, increasing the number of PI-RADS 3 scores by 8.89% when compared to mpMRI. No change of more than one score level was observed. BpMRI did not show significant differences in diagnostic accuracy or tumor detection rates. (AuC of 0.914 vs 0.917 in ROC analysis). Of 135 prostate carcinomas (PCa), 94.07% were scored identically, and 5.93% were downgraded only from PI-RADS 4 to PI-RADS 3 by bpMRI. All of them were low-grade PCa with Gleason Score 6 or 7a. No changes were observed for PCa ≥ 7b.

CONCLUSION

Omitting DCE did not lead to significant differences in diagnostic accuracy or tumor detection rates when using the PI-RADS 2 scoring system. According to these data, it seems reasonable to use a biparametric approach for initial routine prostate MRI. This could decrease examination time and reduce costs without significantly lowering the diagnostic accuracy.

Diagnostic Performance of Biparametric MRI for Detection of Prostate Cancer: A Systematic Review and Meta-Analysis

OBJECTIVE

The purpose of this study was to perform a systematic review and meta-analysis to estimate the diagnostic performance of biparametric MRI (bpMRI) for detection of prostate cancer (PCa).

MATERIALS AND METHODS

Two independent reviewers performed a systematic review of the literature published from January 2000 to July 2017 by using predefined search terms. The standard of pathologic reference was established at prostatectomy or prostate biopsy. The numbers of true- and false-positive and true- and false-negative results were extracted. The Quality Assessment of Diagnostic Accuracy Studies tool was used to assess the quality of the selected studies. Statistical analysis included pooling of diagnostic accuracy, meta-regression, subgroup analysis, head-to-head comparison, and identification of publication bias.

RESULTS

Thirty-three studies were used for general data pooling. The overall sensitivity was 0.81 (95% CI, 0.76-0.85), and overall specificity was 0.77 (95% CI, 0.69-0.84). As for clinically relevant PCa, bpMRI maintained high diagnostic value (AUC, 0.85; 95% CI, 0.82-0.88). There was no evidence of publication bias (p = 0.67). From head-to-head comparison for detection of PCa, multiparametric MRI (mpMRI) had significantly higher pooled sensitivity (0.85; 95% CI, 0.78-0.93) than did bpMRI (0.80; 95% CI, 0.71-0.90) (p = 0.01). However, the pooled specificity values were not significantly different (mpMRI, 0.77 [95% CI, 0.58-0.95]; bpMRI, 0.80 [95% CI, 0.64-0.96]; p = 0.82).

CONCLUSION

The results of this meta-analysis suggest that bpMRI has high diagnostic accuracy in the detection of PCa and maintains a high detection rate for clinically relevant PCa. However, owing to high heterogeneity among the included studies, caution is needed in applying the results of the meta-analysis.

Role and Application of Diffusion-weighted Imaging in Evaluation of Prostate Cancer

Introduction: Diffusion-weighted imaging (DWI) is an important part of magnetic resonance imaging (MRI) in the evaluation of specific organs, including the breast, kidney, liver, and prostate. Prostate cancer lesions are composed of tightly packed cells with reduced extracellular space, which can be visualized on DWIs as areas of restricted diffusion (i.e., high-signal intensity), with corresponding low-signal intensity on apparent diffusion coefficient (ADC) maps and low mean ADC value. Objective: The objective of this study is to identify the appropriate cutoff and mean ADC value to diagnose neoplastic prostatic lesions in central India. Materials and Methods: Sixty-six patients with suspected prostatic pathology were included in this study. All patients underwent MRI on a 1.5-T scanner with a phased-array body coil. MRIs were evaluated compared with the histopathological staging. Results:: The diagnostic accuracy of DWI in predicting malignancy was 39/41, i.e., 95.12%, which is the positive predicted value. The mean ADC for benign category was 1.14 with standard deviation (SD) of 0.14 while mean for prostatitis was 0.91 with SD of 0.26 and for carcinoma was 0.75 with SD of 0.19. The difference in the means was statistically highly significant. Conclusion: DWI demonstrates the restriction of diffusion and the reduction of ADC values in neoplastic tissue and improves the diagnostic accuracy in lesion characterization. This technique allows short acquisition time and provides high-contrast resolution between neoplastic and normal tissue. This technique can be a useful adjunct to the established dynamic contrast-enhanced-MRI.

The diagnostic accuracy of high b-value diffusion- and T2-weighted imaging for the detection of prostate cancer: a meta-analysis

Purpose

This study aims to investigate the role of diffusion-weighted imaging (DWI) and T₂-weighted imaging (T₂WI) in combination for the detection of prostate cancer, specifically assessing the role of high b-values (> 1000 s/mm²), with a systematic review and meta-analysis of the existing published data.

Methods

The electronic databases MEDLINE, EMBASE, and OpenSIGLE were searched between inception and September 1, 2017. Eligible studies were those that reported the sensitivity and specificity of DWI and T₂WI for the diagnosis of prostate cancer by visual assessment using a histopathologic reference standard. The QUADAS-2 critical appraisal tool was used to assess the quality of included studies. A meta-analysis with pooling of sensitivity, specificity, likelihood, and diagnostic odds ratios was undertaken, and a summary receiver-operating characteristics (sROC) curve was constructed. Predetermined subgroup analysis was also performed.

Results

Thirty-three studies were included in the final analysis, evaluating 2949 patients. The pooled sensitivity and specificity were 0.69 (95% CI 0.68–0.69) and 0.84 (95% CI 0.83–0.85), respectively, and the sROC AUC was 0.84 (95% CI 0.81–0.87). Subgroup analysis showed significantly better sensitivity with high b-values (> 1000 s/mm²). There was high statistical heterogeneity between studies.

Conclusion

The diagnostic accuracy of combined DWI and T₂WI is good with high b-values (> 1000 s/mm²) seeming to improve overall sensitivity while maintaining specificity. However, further large-scale studies specifically looking at b-value choice are required before a categorical recommendation can be made.

Electronic supplementary material

The online version of this article (10.1007/s00261-017-1400-4) contains supplementary material, which is available to authorized users.

Radio-pathomic Maps of Epithelium and Lumen Density Predict the Location of High-Grade Prostate Cancer

PURPOSE

This study aims to combine multiparametric magnetic resonance imaging (MRI) and digitized pathology with machine learning to generate predictive maps of histologic features for prostate cancer localization.

METHODS AND MATERIALS

Thirty-nine patients underwent MRI prior to prostatectomy. After surgery, tissue was sliced according to MRI orientation using patient-specific 3-dimensionally printed slicing jigs. Whole-mount sections were annotated by our pathologist and digitally contoured to differentiate the lumen and epithelium. Slides were co-registered to the T2-weighted MRI scan. A learning curve was generated to determine the number of patients required for a stable machine-learning model. Patients were randomly stratified into 2 training sets and 1 test set. Two partial least-squares regression models were trained, each capable of predicting lumen and epithelium density. Predicted density values were calculated for each patient in the test dataset, mapped into the MRI space, and compared between regions confirmed as high-grade prostate cancer.

RESULTS

The learning-curve analysis showed that a stable fit was achieved with data from 10 patients. Maps indicated that regions of increased epithelium and decreased lumen density, generated from each independent model, corresponded with pathologist-annotated regions of high-grade cancer.

CONCLUSIONS

We present a radio-pathomic approach to mapping prostate cancer. We find that the maps are useful for highlighting high-grade tumors. This technique may be relevant for dose-painting strategies in prostate radiation therapy.

Multiparametric (mp) MRI of prostate cancer

Prostate cancer (PCa) is one of the most prevalent cancers in men. A large number of men are detected with PCa; however, the clinical behavior ranges from low-grade indolent tumors that never develop into a clinically significant disease to aggressive, invasive tumors that may rapidly progress to metastatic disease. The challenges in clinical management of PCa are at levels of screening, diagnosis, treatment, and follow-up after treatment. Magnetic resonance imaging (MRI) methods have shown a potential role in detection, localization, staging, assessment of aggressiveness, targeting biopsies, etc. in PCa patients. Multiparametric MRI (mpMRI) is emerging as a better option compared to the individual imaging methods used in the evaluation of PCa. There are attempts to improve the reproducibility and reliability of mpMRI by using an objective scoring system proposed in the prostate imaging reporting and data system (PIRADS) for standardized reporting. Prebiopsy mpMRI may be used to detect PCa in men with elevated prostate-specific antigen or abnormal digital rectal examination and to enable targeted biopsies. mpMRI can also be used to decide on clinical management of patients, for example active surveillance, and may help in detecting only the pathology that requires detection. It can potentially not only guide patient selection for initial and repeat biopsy but also reduce false-negative biopsies. This review presents a description of the MR methods most commonly applied for investigations of prostate. The anatomical, functional and metabolic parameters obtained from these MR methods are discussed with regard to their physical basis and their contribution to mpMRI investigations of PCa.

Prostate cancer as a paradigm of multidisciplinary approach? Highlights from the Italian young radiation oncologist meeting

Aims and background

The diagnostic and therapeutic approach to prostate cancer has evolved rapidly in last decades. Young professionals need an update about these recent developments in order to improve the care of patients treated in their daily clinical practice.

Methods

On May 18, 2013, AIRO Giovani (the young section of the Italian Association of Radiation Oncology) organized a multidisciplinary meeting involving, as speakers, several young physicians from many parts of Italy actively involved in the diagnostic and therapeutic approach to prostate cancer. The meeting was specifically addressed to young physicians (radio-oncologists, urologists, medical oncologists) and presented the state-of-the-art of the diagnostic/therapeutic approach based on the latest evidence on the issue. Highlights of the congress are summarized and presented in this report.

Results

The large participation in the meeting (more than 120 participants were present) confirmed the interest of young radiation oncologists in improving their skills in prostate cancer management. The contributions of the speakers confirmed the need for regular updates, considering the promising results of recently published studies and the many new ongoing trials, on the diagnostic and therapeutic approaches to prostate cancer.

Conclusions

Multidisciplinary meetings are helpful to improve the skills of young professionals.

MRI and 11C Acetate PET/CT for Prediction of Regional Lymph Node Metastasis in Newly Diagnosed Prostate Cancer

Background

The aim of the study was to examine the value of quantitative and qualitative MRI and ¹¹C acetate PET/CT parameters in predicting regional lymph node (LN) metastasis of newly diagnosed prostate cancer (PCa).

Patients and methods

Patients with intermediate (n = 6) and high risk (n = 47) PCa underwent 3T MRI (40 patients) and ¹¹C acetate PET/CT (53 patients) before extended pelvic LN dissection. For each patient the visually most suspicious LN was assessed for mean apparent diffusion coefficient (ADCmean), maximal standardized uptake value (SUVmax), size and shape and the primary tumour for T stage on MRI and ADCmean and SUVmax in the index lesion. The variables were analysed in simple and multiple logistic regression analysis.

Results

All variables, except ADCmean and SUVmax of the primary tumor, were independent predictors of LN metastasis. In multiple logistic regression analysis the best model was ADCmean in combintion with MRI T-stage where both were independent predictors of LN metastasis, this combination had an AUC of 0.81 which was higher than the AUC of 0.65 for LN ADCmean alone and the AUC of 0.69 for MRI T-stage alone.

Conclusions

Several quantitative and qualitative imaging parameters are predictive of regional LN metastasis in PCa. The combination of ADCmean in lymph nodes and T-stage on MRI was the best model in multiple logistic regression with increased predictive value compared to lymph node ADCmean and T-stage on MRI alone.

Evaluation of diffusion weighted imaging in the context of multi-parametric MRI of the prostate in the assessment of suspected low volume prostatic carcinoma

Data from a multi-parametric MRI study of patients with possible early-stage prostate cancer was assessed with a view to creating a more efficient clinical protocol. Based on a correlation analysis suggesting that diffusion-weighted imaging (DWI) scores are more strongly correlated with overall PIRADS scores than other modalities such as dynamic contrast enhanced imaging or spectroscopy, we investigate the combination of T2-weighted imaging (T2w) and DWI as a potential diagnostic tool for prostate cancer detection, staging and guided biopsies. Quantification of the noise floor in the DWI images and careful fitting of the data suggests that the mono-exponential model provides a very good fit to the data and there is no evidence of non-Gaussian diffusion for b-values up to 1000s/mm². This precludes the use of kurtosis or other non-Gaussian measures as a biomarker for prostate cancer in our case. However, the ADC scores for healthy and probably malignant regions are significantly lower for the latter in all 20 but one patient. The results suggest that a simplified mp-MRI protocol combining T2w and DWI may be a good compromise for a cost and time efficient, early-stage prostate cancer diagnostic programme, combining robust MR biomarkers for prostate cancer that can be reliably quantified and appear well-suited for general clinical practice.

A systematic review on multiparametric MR imaging in prostate cancer detection

BACKGROUND

Literature data suggest that multi-parametric Magnetic Resonance Imaging (MRI), including morphologic T2-weigthed images (T2-MRI) and functional approaches such as Dynamic Contrast Enhanced-MRI (DCE-MRI), Diffusion Weighted Imaging (DWI) and Magnetic Resonance Spectroscopic Imaging (MRSI), give an added value in the prostate cancer localization and local staging.

METHODS

We performed a systematic review of literature about the role and the potentiality of morphological and functional MRI in prostate cancer, also in a multimodal / multiparametric approach, and we reported the diagnostic accuracy results for different imaging modalities and for different MR coil settings: endorectal coil (ERC) and phased array coil (PAC). Forest plots and receiver operating characteristic curves were performed. Risk of bias and the applicability at study level were calculated.

RESULTS

Thirty three papers were identified for the systematic review. Sensitivity and specificity values were, respectively, for T2-MRI of 75% and of 60%, for DCE-MRI of 80% and of 72%, for MRSI of 89% and of 69%, for combined T2-MRI and DCE-MRI of 87% and of 46%, for combined T2-MRI and MRSI of 79% and of 57%, for combined T2-MRI, DWI and DCE-MRI of 81% and of 84%, and for combined MRSI and DCE-MRI of 83% and of 83%. For MRI studies performed with ERC we obtained a pooled sensitivity and specificity of 81% and of 66% while the pooled values for MRI studies performed with PAC were of 78% and of 64%, respectively (p>0.05 at McNemar test). No studies were excluded from the analysis based on the quality assessment.

CONCLUSIONS

ERC use yielded no additional benefit in terms of prostate cancer detection accuracy compared to multi-channel PAC use (71% versus 68%) while the use of additional functional imaging techniques (DCE-MRI, DWI and MRSI) in a multiparametric MRI protocol improves the accuracy of prostate cancer detection allowing both the early cure and the guidance of biopsy.

Automated diagnosis of prostate cancer in multi-parametric MRI based on multimodal convolutional neural networks

Automated methods for prostate cancer (PCa) diagnosis in multi-parametric magnetic resonance imaging (MP-MRIs) are critical for alleviating requirements for interpretation of radiographs while helping to improve diagnostic accuracy (Artan et al 2010 IEEE Trans. Image Process. 19 2444-55, Litjens et al 2014 IEEE Trans. Med. Imaging 33 1083-92, Liu et al 2013 SPIE Medical Imaging (International Society for Optics and Photonics) p 86701G, Moradi et al 2012 J. Magn. Reson. Imaging 35 1403-13, Niaf et al 2014 IEEE Trans. Image Process. 23 979-91, Niaf et al 2012 Phys. Med. Biol. 57 3833, Peng et al 2013a SPIE Medical Imaging (International Society for Optics and Photonics) p 86701H, Peng et al 2013b Radiology 267 787-96, Wang et al 2014 BioMed. Res. Int. 2014). This paper presents an automated method based on multimodal convolutional neural networks (CNNs) for two PCa diagnostic tasks: (1) distinguishing between cancerous and noncancerous tissues and (2) distinguishing between clinically significant (CS) and indolent PCa. Specifically, our multimodal CNNs effectively fuse apparent diffusion coefficients (ADCs) and T2-weighted MP-MRI images (T2WIs). To effectively fuse ADCs and T2WIs we design a new similarity loss function to enforce consistent features being extracted from both ADCs and T2WIs. The similarity loss is combined with the conventional classification loss functions and integrated into the back-propagation procedure of CNN training. The similarity loss enables better fusion results than existing methods as the feature learning processes of both modalities are mutually guided, jointly facilitating CNN to 'see' the true visual patterns of PCa. The classification results of multimodal CNNs are further combined with the results based on handcrafted features using a support vector machine classifier. To achieve a satisfactory accuracy for clinical use, we comprehensively investigate three critical factors which could greatly affect the performance of our multimodal CNNs but have not been carefully studied previously. (1) Given limited training data, how can these be augmented in sufficient numbers and variety for fine-tuning deep CNN networks for PCa diagnosis? (2) How can multimodal MP-MRI information be effectively combined in CNNs? (3) What is the impact of different CNN architectures on the accuracy of PCa diagnosis? Experimental results on extensive clinical data from 364 patients with a total of 463 PCa lesions and 450 identified noncancerous image patches demonstrate that our system can achieve a sensitivity of 89.85% and a specificity of 95.83% for distinguishing cancer from noncancerous tissues and a sensitivity of 100% and a specificity of 76.92% for distinguishing indolent PCa from CS PCa. This result is significantly superior to the state-of-the-art method relying on handcrafted features.

Safety and Feasibility of Direct Magnetic Resonance Imaging-guided Transperineal Prostate Biopsy Using a Novel Magnetic Resonance Imaging-safe Robotic Device

OBJECTIVE

To evaluate safety and feasibility in a first-in-human trial of a direct magnetic resonance imaging (MRI)-guided prostate biopsy using a novel robotic device.

METHODS

MrBot is an MRI-safe robotic device constructed entirely with nonconductive, nonmetallic, and nonmagnetic materials and developed by our group. A safety and feasibility clinical trial was designed to assess the safety and feasibility of a direct MRI-guided biopsy with MrBot and to determine its targeting accuracy. Men with elevated prostate-specific antigen levels, prior negative prostate biopsies, and cancer-suspicious regions (CSRs) on MRI were enrolled in the study. Biopsies targeting CSRs, in addition to sextant locations, were performed.

RESULTS

Five men underwent biopsy with MrBot. Two men required Foley catheter insertion after the procedure, with no other complications or adverse events. Even though this was not a study designed to detect prostate cancer, biopsies confirmed the presence of a clinically significant cancer in 2 patients. On a total of 30 biopsy sites, the robot achieved an MRI-based targeting accuracy of 2.55 mm and a precision of 1.59 mm normal to the needle, with no trajectory corrections and no unsuccessful attempts to target a site.

CONCLUSION

Robot-assisted MRI-guided prostate biopsy appears safe and feasible. This study confirms that a clinically significant prostate cancer (≥5-mm radius, 0.5 cm³) depicted in MRI may be accurately targeted. Direct confirmation of needle placement in the CSR may present an advantage over fusion-based technology and gives more confidence in a negative biopsy result. Additional study is warranted to evaluate the efficacy of this approach.

MRI-based prostate cancer detection with high-level representation and hierarchical classification

PURPOSE

Extracting the high-level feature representation by using deep neural networks for detection of prostate cancer, and then based on high-level feature representation constructing hierarchical classification to refine the detection results.

METHODS

High-level feature representation is first learned by a deep learning network, where multiparametric MR images are used as the input data. Then, based on the learned high-level features, a hierarchical classification method is developed, where multiple random forest classifiers are iteratively constructed to refine the detection results of prostate cancer.

RESULTS

The experiments were carried on 21 real patient subjects, and the proposed method achieves an averaged section-based evaluation (SBE) of 89.90%, an averaged sensitivity of 91.51%, and an averaged specificity of 88.47%.

CONCLUSIONS

The high-level features learned from our proposed method can achieve better performance than the conventional handcrafted features (e.g., LBP and Haar-like features) in detecting prostate cancer regions, also the context features obtained from the proposed hierarchical classification approach are effective in refining cancer detection result.

Detection of Clinically Significant Prostate Cancer: Short Dual-Pulse Sequence versus Standard Multiparametric MR Imaging-A Multireader Study

Purpose To compare the diagnostic performance of a short dual-pulse sequence magnetic resonance (MR) imaging protocol versus a standard six-pulse sequence multiparametric MR imaging protocol for detection of clinically significant prostate cancer. Materials and Methods This HIPAA-compliant study was approved by the regional ethics committee. Between July 2013 and March 2015, 63 patients from a prospectively accrued study population who underwent MR imaging of the prostate including transverse T1-weighted; transverse, coronal, and sagittal T2-weighted; diffusion-weighted; and dynamic contrast material-enhanced MR imaging with a 3-T imager at a single institution were included in this retrospective study. The short MR imaging protocol image set consisted of transverse T2-weighted and diffusion-weighted images only. The standard MR imaging protocol image set contained images from all six pulse sequences. Three expert readers from different institutions assessed the likelihood of prostate cancer on a five-point scale. Diagnostic performance on a quadrant basis was assessed by using areas under the receiver operating characteristic curves, and differences were evaluated by using 83.8% confidence intervals. Intra- and interreader agreement was assessed by using the intraclass correlation coefficient. Transperineal template saturation biopsy served as the standard of reference. Results At histopathologic evaluation, 84 of 252 (33%) quadrants were positive for cancer in 38 of 63 (60%) men. There was no significant difference in detection of tumors larger than or equal to 0.5 mL for any of the readers of the short MR imaging protocol, with areas under the curve in the range of 0.74-0.81 (83.8% confidence interval [CI]: 0.64, 0.89), and for readers of the standard MR imaging protocol, areas under the curve were 0.71-0.77 (83.8% CI: 0.62, 0.86). Ranges for sensitivity were 0.76-0.95 (95% CI: 0.53, 0.99) and 0.76-0.86 (95% CI: 0.53, 0.97) and those for specificity were 0.84-0.90 (95% CI: 0.79, 0.94) and 0.82-0.90 (95% CI: 0.77, 0.94) for the short and standard MR protocols, respectively. Ranges for interreader agreement were 0.48-0.60 (83.8% CI: 0.41, 0.66) and 0.49-0.63 (83.8% CI: 0.42, 0.68) for the short and standard MR imaging protocols. Conclusion For the detection of clinically significant prostate cancer, no difference was found in the diagnostic performance of the short MR imaging protocol consisting of only transverse T2-weighted and diffusion-weighted imaging pulse sequences compared with that of a standard multiparametric MR imaging protocol. ^© RSNA, 2017 Online supplemental material is available for this article.