Detection of Prostate Cancer With Magnetic Resonance Imaging: Optimization of T1-Weighted, T2-Weighted, Dynamic-Enhanced T1-Weighted, Diffusion-Weighted Imaging Apparent Diffusion Coefficient Mapping Sequences and MR Spectroscopy, Correlated With Biopsy and Histopathological Findings

Multi-view radiomics and deep learning modeling for prostate cancer detection based on multi-parametric MRI

Introduction

This study aims to develop an imaging model based on multi-parametric MR images for distinguishing between prostate cancer (PCa) and prostate hyperplasia.

Methods

A total of 236 subjects were enrolled and divided into training and test sets for model construction. Firstly, a multi-view radiomics modeling strategy was designed in which different combinations of radiomics feature categories (original, LoG, and wavelet) were compared to obtain the optimal input feature sets. Minimum-redundancy maximum-relevance (mRMR) selection and least absolute shrinkage selection operator (LASSO) were used for feature reduction, and the next logistic regression method was used for model construction. Then, a Swin Transformer architecture was designed and trained using transfer learning techniques to construct the deep learning models (DL). Finally, the constructed multi-view radiomics and DL models were combined and compared for model selection and nomogram construction. The prediction accuracy, consistency, and clinical benefit were comprehensively evaluated in the model comparison.

Results

The optimal input feature set was found when LoG and wavelet features were combined, while 22 and 17 radiomic features in this set were selected to construct the ADC and T2 multi-view radiomic models, respectively. ADC and T2 DL models were built by transferring learning from a large number of natural images to a relatively small sample of prostate images. All individual and combined models showed good predictive accuracy, consistency, and clinical benefit. Compared with using only an ADC-based model, adding a T2-based model to the combined model would reduce the model's predictive performance. The ADCCombinedScore model showed the best predictive performance among all and was transformed into a nomogram for better use in clinics.

Discussion

The constructed models in our study can be used as a predictor in differentiating PCa and BPH, thus helping clinicians make better clinical treatment decisions and reducing unnecessary prostate biopsies.

Prediction of prostate cancer recurrence after radiation therapy using multiparametric magnetic resonance imaging and spectroscopy: assessment of prognostic factors on pretreatment imaging

BACKGROUND

To assess whether data from pre-therapeutic multiparametric magnetic resonance imaging (mpMRI) combined with three-dimensional magnetic resonance spectroscopy (3D MRS) provide prognostic factors of biochemical relapse in patients with localized prostate cancer treated by external radiotherapy or brachytherapy.

METHODS

In our single institution observational retrospective study we included a cohort of 230 patients treated by external radiotherapy or brachytherapy who had an initial mpMRI with 3D MRS from January 2008 to December 2015 for newly diagnosed localized prostatic cancer, proven histologically. Three trained radiologists recorded tumor characteristics, MRI T-stage and metabolic abnormalities from 3D MRS data. Univariate and multivariate Cox analyzes explored the relationship between clinical and imaging variables to highlight prognostic factors for recurrence, using biochemical relapse as the primary endpoint.

RESULTS

mpMRI data analysis allowed to reclassify 21.7% of the patients in a MRI National Comprehensive Cancer Network (NCCN) group higher than their initial clinical T-stage, but also to detect a lesion in 78% of the patients considered as clinically T1c. After a median of follow-up of 8.7 years (IQR, 6.6-10.1) following cancer diagnosis, 36 (16%) patients developed a biochemical relapse. The multivariate Cox analysis demonstrated the existence of 3 independent factors for prediction of biochemical recurrence: extracapsular extension (ECE) (HR =3.33; 95% CI: 1.93-5.73; P<0.01), choline/citrate ratio in healthy tissue in the transition zone (TZ) (HR =2.96; 95% CI: 1.06-8.28; P=0.04) and the NCCN Magnetic Resonance Imaging classification (intermediate versus low-risk, HR =3.06; 95% CI: 1.13-8.30; P<0.01).

CONCLUSIONS

Combination of mpMRI and 3DMRS could aid in the prognostic stratification of localized prostate cancer treated by radiotherapy or brachytherapy, by combining accurate evaluation of tumor extension, and quantification of prostate metabolism.

Comparison of Prostate Imaging Reporting and Data System versions 1 and 2 for the Detection of Peripheral Zone Gleason Score 3 + 4 = 7 Cancers

OBJECTIVE

The objective of our study was to compare Prostate Imaging Reporting and Data System version 1 (PI-RADSv1) and Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) for the detection of peripheral zone (PZ) Gleason score 3 + 4 = 7 cancers.

MATERIALS AND METHODS

Forty-seven consecutive patients with 52 PZ Gleason score 3 + 4 = 7 cancers that were 0.5 cm³ or larger underwent radical prostatectomy (RP) and 3-T MRI between 2012 and 2015. Two blinded radiologists (readers 1 and 2) retrospectively assigned PI-RADSv1 sequence (T2-weighted imaging, DWI, dynamic contrast-enhanced MRI [DCE-MRI]) and sum scores and PI-RADSv2 assessment categories. A third blinded radiologist (reader 3) measured apparent diffusion coefficient (ADC) ratio (ADC of tumor / ADC of normal PZ) using RP-MRI maps. Sensitivity, false-positive rate, and overall accuracy were compared using McNemar test. Pearson correlation was performed.

RESULTS

Using PI-RADSv1, reader 1 detected 86.5% (45/52) of the cancers and reader 2, 76.9% (40/52) of the cancers. Using PI-RADSv2, reader 1 detected 78.9% (41/52) and reader 2, 67.3% (35/52). Reader 1 detected 7.7% (4/52) and reader 2 detected 9.6% (5/52) more tumors using PI-RADSv1 due to T2-weighted imaging score ≥ 4 or DCE-MRI score ≥ 3. Sensitivity was higher for PI-RADSv1 (p = 0.01 and 0.03, readers 1 and 2). False-positive rates were higher with PI-RADSv1 than with PI-RADSv2 (1.8% vs 0.9% for reader 1; 3.6% vs 1.8% for reader 2) without significant differences in false-positive rate (p = 0.41 and 0.25) or overall accuracy (p = 0.06 and 0.23). PI-RADSv1 sum scores correlated strongly with PI-RADSv2 categories (B = 0.78-0.93, p < 0.0001). The mean ADC ratio was 0.61 ± 0.14 mm²/s with no difference between visible and nonvisible tumors (p = 0.06-0.5). Interobserver agreement was moderate for PI-RADSv2 (κ = 0.41) and ranged from slight to substantial for PI-RADSv1 (T2-weighted imaging, κ = 0.32; DWI, κ = 0.52; DCE-MRI, κ = 0.13).

CONCLUSION

There was no difference in overall detection of cancers comparing PI-RADSv1 and PI-RADSv2; however, PI-RADSv1 sequence scores on T2-weighted imaging and DCE-MRI detected approximately 10% more tumors that were otherwise underestimated on DWI and using PI-RADSv2 decision-tree rules.

Accuracy of dynamic contrast-enhanced magnetic resonance imaging in the diagnosis of prostate cancer: systematic review and meta-analysis

The goals of this meta-analysis were to assess the effectiveness of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in patients with prostate carcinoma (PCa) and to explore the risk profiles with the highest benefit. Systematic electronic searched were conducted in database. We used patient-based and biopsy-based pooled weighted estimates of the sensitivity, specificity, and a summary receiver operating characteristic (SROC) curve for assessing the diagnostic performance of DCE. We performed direct and indirect comparisons of DCE and other methods of imaging. A total of 26 articles met the inclusion criteria for the analysis. DCE-MRI pooled sensitivity was 0.53 (95% CI 0.39 to 0.67), with a specificity of 0.88 (95% CI 0.83 to 0.92) on whole gland. The peripheral zone pooled sensitivity was 0.70 (95% CI 0.46 to 0.86), with a specificity of 0.88 (95% CI 0.76 to 0.94). Compared with T2-weighted imaging (T2WI), DCE was statistically superior to T2. In conclusion, DCE had relatively high specificity in detecting PCa but relatively low sensitivity as a complementary functional method. DCE-MRI might help clinicians exclude cases of normal tissue and serve as an adjunct to conventional imaging when seeking to identify tumor foci in patients with PCa.

Apparent diffusion coefficient values are superior to transrectal ultrasound-guided prostate biopsy for the assessment of prostate cancer aggressiveness

Background Few studies have focused on comparing the utility of diffusion-weighted imaging (DWI) and transrectal ultrasound (TRUS)-guided biopsy in predicting prostate cancer aggressiveness. Whether apparent diffusion coefficient (ADC) values can provide more information than TRUS-guided biopsy should be confirmed. Purpose To retrospectively assess the utility of ADC values in predicting prostate cancer aggressiveness, compared to the TRUS-guided prostate biopsy Gleason score (GS). Material and Methods The DW images of 54 patients with biopsy-proven prostate cancer were obtained using 1.5-T magnetic resonance (MR). The mean ADC values of cancerous areas and biopsy GS were correlated with prostatectomy GS and D'Amico clinical risk scores, respectively. Meanwhile, the utility of ADC values in identifying high-grade prostate cancer (with Gleason 4 and/or 5 components in prostatectomy) in patients with a biopsy GS ≤ 3 + 3 = 6 was also evaluated. Results A significant negative correlation was found between mean ADC values of cancerous areas and the prostatectomy GS ( P < 0.001) and D'Amico clinical risk scores ( P < 0.001). No significant correlation was found between biopsy GS and prostatectomy GS ( P = 0.140) and D'Amico clinical risk scores ( P = 0.342). Patients harboring Gleason 4 and/or 5 components in prostatectomy had significantly lower ADC values than those harboring no Gleason 4 and/or 5 components ( P = 0.004). Conclusion The ADC values of cancerous areas in the prostate are a better indicator than the biopsy GS in predicting prostate cancer aggressiveness. Moreover, the use of ADC values can help identify the presence of high-grade tumor in patients with a Gleason score ≤ 3 + 3 = 6 during biopsy.

Image-guided high-dose-rate brachytherapy boost to the dominant intraprostatic lesion using multiparametric magnetic resonance imaging including spectroscopy: Results of a prospective study

PURPOSE

To evaluate the long-term outcomes of image-guided high-dose-rate (HDR) brachytherapy boost to the dominant intraprostatic lesion (DIL) using multiparametric magnetic resonance imaging (MRI), including spectroscopy (MRI/magnetic resonance spectroscopy [MRS]).

METHODS AND MATERIALS

Between December 2009 and March 2011, 20 patients with intermediate-risk prostate cancer underwent multiparametric MRI/MRS protocol before treatment. All patients were treated with an external beam radiotherapy dose of 40 Gy, combined with an HDR brachytherapy boost of 15 Gy. Concurrently, the DIL received a boost of 18 Gy. Missing data during followup were handled with multiple imputations.

RESULTS

The median followup was 62 months (range, 23-71 months). Six patients (31%) were classified as favorable intermediate risk and 13 patients (69%) as unfavorable intermediate risk. One patient experienced a prostate-specific antigen biochemical failure, and the 5-year biochemical failure-free survival rate was of 94.7%. The mean International Prostate Symptom Score rose from 7, with respect to baseline, to 10.42 1 month after treatment, and rapidly decreased to 6.97 after 3 months. Grade 1, 2, and 3 acute genitourinary toxicities were reported in 13 (68%), 3 (16%), and 1 (5%) patients, respectively. Grade 1 and 2 late genitourinary toxicities were reported in 9 (53%) and 3 (18%) patients, respectively. Only grade 1 acute and late gastrointestinal toxicities were reported in 4 (21%) and 3 (18%) patients, respectively.

CONCLUSIONS

Delivering an HDR brachytherapy boost to the DIL using image-guided multiparametric MRI/MRS is feasible with good outcomes for biochemical control, acute and late toxicities, and dosimetric constraints for critical organs.

Image-Guided High-Dose-Rate (HDR) Boost Localization Using MRI/MR Spectroscopy: A Correlation Study with Biopsy

PURPOSE

The purpose of this study is to compare the blind interpretations of magnetic resonance imaging (MRI) sequences, diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC), mapping, and magnetic resonance spectroscopy (MRS) of the prostate, in comparison to prostate biopsy to identify a valid dominant intraprostatic lesion (DIL) for dose escalation using high-dose rate brachytherapy.

METHODS

MRI/MRS were performed on 20 patients with intermediate risk adenocarcinoma of the prostate. T1W, T2W, DWI-ADC, and MRS sequences were performed at 1.5 T with pelvic and endorectal coils. An experienced radiologist rated the presence of cancer in each sextant by using a dichotomic approach, first on MR standard acquisitions (T1W and T2W), then on DWI-ADC mapping, and later on MRS images. Areas under the receiver's operating characteristic curve were calculated using a sextant as the unit of analysis. The transrectal ultrasonography-guided biopsy results were used as the reference standard. A table summarizing the MRI/MRS findings was made and compared to the corresponding area in the prostate biopsy report. A perfect match was defined to be the presence of cancer in the same sextant of the MRI/MRS exam and the prostate biopsy.

RESULTS

The interpretation of the MRI/MRS exams per sextant was compared to the diagnostic biopsy report. MRI readings were compared with the biopsy as a surrogate for the complete pathology specimen of the prostate. A sensitivity (Sn) of 98.6% (95% confidence interval, 92.2% - 99.9%) and specificity (Sp) of 60.8% (46.1% - 74.2%) were found. The positive and negative predictive values (PPV, NPV) were 77.3% (67.1% - 85.5%) and 96.9% (83.8% - 99.9%), respectively. When MRS readings were compared with biopsy, we found a Sn of 96.4% (87.7% - 99.6%) and Sp of 54.8% (38.7% - 70.2%). The PPV and NPV were 74% (62.4% - 83.6%) and 92% (74% - 99%), respectively. DWI-ADC mapping results were also compared with biopsy. We found a Sn and Sp of 93.7% (84.5% - 98.2%) and 82.1% (66.5% - 92.5%), respectively, and a PPV and NPV of 89.4% (79.4% - 95.6%) and 88.9% (73.9% - 96.9%), respectively. Finally, after combining MRI, MRS, and DWI-ADC mapping, compared with biopsy, we obtained a Sn, Sp, PPV, and NPV of 100% (94.8% - 100%), 49% (34.8% - 63.4%), 72.6% (62.5% - 81.3%), and 100% (86.3% - 100%), respectively.

CONCLUSIONS

The combination of MRI/MRS is a sensitive tool for both the structural and metabolic evaluation of prostate cancer location. MRI/MRS exams are useful to delineate a DIL for high-dose-rate (HDR) intraprostatic boost.

Clinical Imaging of Tumor Metabolism with ¹H Magnetic Resonance Spectroscopy

Magnetic resonance spectroscopy (MRS) is a noninvasive functional technique to evaluate the biochemical behavior of human tissues. This property has been widely used in assessment and therapy monitoring of brain tumors. MRS studies can be implemented outside the brain, with successful and promising results in the evaluation of prostate and breast cancer, although still with limited reproducibility. As a result of technical improvements, malignancies of the musculoskeletal system and abdominopelvic organs can benefit from the molecular information that MRS provides. The technical challenges and main applications in oncology of (1)H MRS in a clinical setting are the focus of this review.

Impact of an endorectal coil for 1H-magnetic resonance spectroscopy of the prostate at 3.0T in comparison to 1.5T: Do we need an endorectal coil?

OBJECTIVES

To evaluate the influence of endorectal coil (ERC) regarding spectral quality and diagnostic suitability and diagnostic performance in 3.0T 1H-magnetic resonance spectroscopy imaging (MRSI) compared to 1.5T MRSI.

MATERIALS AND METHODS

The study was approved by the Institutional Review Board. MRSI of the prostate was performed on 19 patients at 1.5T with ERC (protocol 1), at 3.0T with a disabled ERC (protocol 2) and at 3.0T with ERC (protocol 3). Age, weight, body size, body-mass-index, prostate volume, time between measurements, diagnostic suitability of spectra, histopathological results after biopsy of cancer suspect lesions (CSL), sensitivity and specificity were evaluated. Signal-to-noise ratio (SNR) was calculated and compared using semiparametrical multiple Conover-comparisons. Correlations between SNR and prostate volume and BMI were indicated using Pearson correlation coefficient. Distribution of SNR was evaluated for prostate quadrants.

RESULTS

Diagnostic suitable spectra were achieved in 76 % (protocol 1, 100% in CSL), 32 % (protocol 2, 59% in CSL) and 50 % (protocol 3, 80% in CSL) of the voxels. SNR was significantly higher in protocol 3 compared to protocol 2 and 1 (93,729 vs. 27,836 vs. 32,897, p<0.0001) with significant difference between protocol 2 and 1 (p<0.023). Highest SNR was achieved in the dorsal prostate (protocols 1 and 3; p<0.0001). Sensitivity at 3.0T was higher with use of ERC. Specificity was highest at 1.5T with ERC.

CONCLUSION

The ERC improves the diagnostic suitability and the SNR in MRSI at 3.0T. Less voxels at 3.0T with disabled ERC are suitable for diagnosis compared to 1.5T with ERC. MRSI at 3.0T with ERC shows the highest SNR. SNR in dorsal quadrants of the prostate was higher using ERC.

Prostate Cancer Magnetic Resonance Spectroscopy Imaging at 1.5 and 3.0 T

Objective:

We sought to assess the value of 1.5-T and 3-T magnetic resonance spectroscopy imaging in the diagnosis of prostate cancer by meta-analysis.

Methods:

Prospective studies were selected from MEDLINE, PubMed, Science Direct, OVID, and Springer between January 2004 and June 2014. Studies were reviewed based on Quality Assessment of Diagnostic Accuracy Studies criteria. Any publication bias was assessed using Deek funnel plot asymmetry test. Pooled sensitivities, specificities, positive likelihood ratios, negative likelihood ratios, and 95% confidence intervals were calculated. Summary receiver–operating characteristic curves were used to assess the results.

Results:

A total of 17 articles were included in this study. The area under the curve values of 1.5-T magnetic resonance spectroscopy imaging with the use of an endorectal coil, 1.5-T magnetic resonance spectroscopy imaging without the use of an endorectal coil, and 3.0-T magnetic resonance spectroscopy imaging without the use of an endorectal coil were 0.90 ± 0.03, 0.75 ± 0.03, and 0.93 ± 0.02, respectively.

Conclusion:

Three-tesla magnetic resonance spectroscopy imaging without the use of an endorectal coil and 1.5-T magnetic resonance spectroscopy imaging with the use of an endorectal coil both had similar applied values compared to the lower applied value of 1.5-T magnetic resonance spectroscopy imaging without the use of an endorectal coil.

Interpretation and reporting multiparametric prostate MRI: a primer for residents and novices

Multiparametric MRI has developed as a tool for prostate cancer lesion detection, characterization, staging, surveillance, and imaging of local recurrence. Given the disease frequency and the growing importance of imaging, as reliance on PSA declines, radiologists involved in prostate MRI imaging must become proficient with the fundamentals of multiparametric prostate MRI (T2WI, DWI, DCE-MRI, and MR spectroscopy). Interpretation and reporting must yield accuracy, consistency, and add value to clinical care. This review provides a primer to novices and trainees learning about multiparametric prostate MRI. MRI technique is presented along with the use of particular MRI sequences. Relevant prostate anatomy is outlined and imaging features of prostate cancer with staging are discussed. Finally structured reporting is introduced, and some limitations of prostate MRI are discussed.

Dynamic contrast-enhanced MRI for the detection of prostate cancer: meta-analysis

OBJECTIVE

The purpose of this study was to systematically review and meta-analyze dynamic contrast-enhanced MRI (DCE-MRI) for the detection of prostate cancer in comparison with standard evaluation with T2-weighted imaging.

MATERIALS AND METHODS

A PubMed electronic database search for the terms "dynamic contrast-enhanced," "prostate," and "MRI" was completed for articles up to September 17, 2013. All included studies had histopathologic correlation. Two by two contingency data were constructed for each study. A binormal bayesian ROC model was used to estimate and compare sensitivity, specificity, and AUC among eligible modalities.

RESULTS

Both DCE-MRI (0.82-0.86) and diffusion-weighted MRI (DWI) (0.84-0.88) yielded significantly better AUC than T2-weighted imaging (0.68-0.77). Moreover, partial AUC for the combination of DCE-MRI, DWI, and T2-weighted imaging was improved significantly (0.111; 0.103-0.119) when compared with DCE-MRI alone (0.079; 0.072-0.085) and T2-weighted imaging alone (0.079; 0.074-0.084) but not DWI alone (0.099; 0.091-0.108). Sensitivity and specificity were similar among the four modalities.

CONCLUSION

DCE-MRI improves AUC of tumor detection overall compared with T2-weighted imaging alone. Methods for DCE-MRI analysis require standardization, but visual analysis performs similar to semiquantitative methods. A two-parameter approach using DCE-MRI and T2-weighted imaging or DWI and T2-weighted imaging may be sufficient, and the latter may be more favorable for most routine prostate cancer imaging.

Feasibility of multiparametric prostate magnetic resonance imaging in the detection of cancer distribution: histopathological correlation with prostatectomy specimens

Purpose

To prevent overtreatment, it is very important to diagnose the precise distribution and characteristics of all cancer lesions, including small daughter tumors. The purpose of this study was to evaluate the efficacy of T2-weighted magnetic resonance imaging (T2W), diffusion-weighted magnetic resonance imaging (DWI), magnetic resonance spectroscopy (¹H-MRS), and prostate biopsy (PBx) in the detection of intraprostatic cancer distribution.

Methods

All patients underwent T2W, DWI, ¹H-MRS, and PBx followed by radical prostatectomy (RP). Individual prostates were divided into 12 segmental regions, each of which was examined for the presence or absence of malignancy on the basis of T2W, DWI, ¹H-MRS, and PBx, respectively. These results were compared with the histopathological findings for RP specimens.

Results

We included 54 consecutive patients with biopsy-proven prostate cancer (mean age, 62.7 years; median prostate-specific antigen level, 5.7 ng/mL) in this study. We could detect cancer in 247 of 540 evaluable lesions. The area under the receiver operator characteristic curve analysis yielded a higher value for DWI (0.68) than for T2W (0.65), ¹H-MRS (0.54), or PBx (0.56). In 180 cancerous regions of RP specimens with false-negative PBx results, T2W+DWI had the highest positive rate (53.3%) compared with that of each sequence alone, including T2W (45.6%), DWI (41.1%), and ¹H-MRS (30.0%).

Conclusions

Multiparametric magnetic resonance imaging (T2W, ¹H-MRS, DWI) enables the detection of prostate cancer distribution with reasonable sensitivity and specificity. T2W+DWI was particularly effective in detecting cancer distribution with false-negative PBx results.

Contrast enhancement by combining T1- and T2-weighted structural brain MR Images

PURPOSE

In order to more precisely differentiate cerebral structures in neuroimaging studies, a novel technique for enhancing the tissue contrast based on a combination of T1-weighted (T1w) and T2-weighted (T2w) MRI images was developed.

METHODS

The combined image (CI) was calculated as CI = (T1w - sT2w)/(T1w + sT2w), where sT2w is the scaled T2-weighted image. The scaling factor was calculated to adjust the gray- matter (GM) voxel intensities in the T2w image so that their median value equaled that of the GM voxel intensities in the T1w image. The image intensity homogeneity within a tissue and the discriminability between tissues in the CI versus the separate T1w and T2w images were evaluated using the segmentation by the FMRIB Software Library (FSL) and FreeSurfer (Athinoula A. Martinos Center for Biomedical Imaging at Massachusetts General Hospital, Boston, MA) software.

RESULTS

The combined image significantly improved homogeneity in the white matter (WM) and GM compared to the T1w images alone. The discriminability between WM and GM also improved significantly by applying the CI approach. Significant enhancements to the homogeneity and discriminability also were achieved in most subcortical nuclei tested, with the exception of the amygdala and the thalamus.

CONCLUSION

The tissue discriminability enhancement offered by the CI potentially enables more accurate neuromorphometric analyses of brain structures.

The value of diffusion-weighted imaging in the detection of prostate cancer: a meta-analysis

Objectives

To evaluate the diagnostic performance of diffusion-weighted imaging (DWI) as a single non-invasive method in detecting prostate cancer (PCa) and to deduce its clinical utility.

Methods

A systematic literature search was performed to identify relevant original studies. Quality of included studies was assessed by QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies). Data were extracted to calculate sensitivity and specificity as well as running the test of heterogeneity and threshold effect. The summary receiver operating characteristic (SROC) curve was drawn and area under SROC curve (AUC) served as a determination of the diagnostic performance of DWI for the detection of PCa.

Results

A total of 21 studies were included, with 27 subsets of data available for analysis. The pooled sensitivity and specificity with corresponding 95 % confidence interval (CI) were 0.62 (95 % CI 0.61–0.64) and 0.90 (95 % CI 0.89–0.90), respectively. Pooled positive likelihood ratio and negative likelihood ratio were 5.83 (95 % CI 4.61–7.37) and 0.30 (95 % CI 0.23–0.39), respectively. The AUC was 0.8991. Significant heterogeneity was observed. There was no notable publication bias.

Conclusions

DWI is an informative MRI modality in detecting PCa and shows moderately high diagnostic accuracy. General clinical application was limited because of the absence of standardized DW-MRI techniques.

Key points

• DWI provides incremental information for the detection and evaluation of PCa

• DWI has moderately high diagnostic accuracy in detecting PCa

• Patient condition, imaging protocols and study design positively influence diagnostic performance

• General clinical application requires optimization of image acquisition and interpretation

Prostate cancer detection and diagnosis: the role of MR and its comparison with other diagnostic modalities--a radiologist's perspective

It is now universally recognized that many prostate cancers are over-diagnosed and over-treated. The European Randomized Study of Screening for Prostate Cancer from 2009 evidenced that, to save one man from death from prostate cancer, over 1400 men need to be screened, and 48 need to undergo treatment. The detection of prostate cancer is traditionally based on digital rectal examination (DRE) and the measurement of serum prostate-specific antigen (PSA), followed by ultrasound-guided biopsy. The primary role of imaging for the detection and diagnosis of prostate cancer has been transrectal ultrasound (TRUS) guidance during biopsy. Traditionally, MRI has been used primarily for the staging of disease in men with biopsy-proven cancer. It has a well-established role in the detection of T3 disease, planning of radiation therapy, especially three-dimensional conformal or intensity-modulated external beam radiation therapy, and planning and guiding of interstitial seed implant or brachytherapy. New advances have now established that prostate MRI can accurately characterize focal lesions within the gland, an ability that has led to new opportunities for improved cancer detection and guidance for biopsy. Two new approaches to prostate biopsy are under investigation. Both use pre-biopsy MRI to define potential targets for sampling, and the biopsy is performed either with direct real-time MR guidance (in-bore) or MR fusion/registration with TRUS images (out-of-bore). In-bore and out-of-bore MRI-guided prostate biopsies have the advantage of using the MR target definition for the accurate localization and sampling of targets or suspicious lesions. The out-of-bore method uses combined MRI/TRUS with fusion software that provides target localization and increases the sampling accuracy of TRUS-guided biopsies by integrating prostate MRI information with TRUS. Newer parameters for each imaging modality, such as sonoelastography or shear wave elastography, contrast-enhanced ultrasound and MRI elastography, show promise to further enrich datasets.

The feasibility of multiparametric magnetic resonance imaging for targeted biopsy using novel navigation systems to detect early stage prostate cancer: the preliminary experience

BACKGROUND AND PURPOSE

The feasibility and diagnostic performance of multiparametric magnetic resonance imaging (mp-MRI) has to be proven further. In this study, we evaluate the role of mp-MRI for targeted biopsy of early stage prostate cancer (PCa).

PATIENTS AND METHODS

A total 32 consecutive patients with transrectal ultrasonography (TRUS)-guided biopsy-proven PCa meeting low-risk criteria and pursuing active surveillance were selected to undergo mp-MRI 3 Tesla (3T) with endorectal coil. Patients were divided then into three groups based on the method used to target the mp-MRI designated region of interest (ROI): Group 1 underwent TRUS-guided prostate biopsy using an MRI-based coordinate plan (cognitive targeting). Group 2 underwent MRI-targeted TRUS-guided prostate biopsy using MyLabTMTwice, which superimposed the archived MRI images onto the real-time ultrasonography image allowing targeted biopsy of the ROI (fusion targeting). Group 3 included selected patients who had an elevation in prostate-specific antigen levels, or patients followed after radiation therapy (two patients) for suspicious unifocal MRI lesion recurrence. These patients underwent MRI-guided biopsy of the suspicious ROI using the navigation system DynaTRIM.

RESULTS

The cancer detection rate in group 1 was 33.3% (3 of 10 patients), while in group 2, it was significantly higher at 46.2%. The sensitivity and specificity for group 1 was 45.5% and 33.3%, vs 61.9% and 20.8% in group 2, respectively. The positive predictive value in group 1 was 50.0% vs 53.8% in group 2 (P=0.04). In group 3, the cancer detection rate was much higher (80%) than in group 2, (P=0.005) although the majority of these patients (7 of 10) had a previously diagnosed prostate cancer on TRUS-guided 12-core biopsy.

CONCLUSION

Our preliminary experience of mp-MRI suggests the detection of early stage prostate cancer with low-risk features yields potential candidates for active surveillance or focal targeted therapy. The MRI-TRUS fusion system increases diagnostic yield compared with cognitive MRI-directed TRUS-guided biopsy.

Meta-analysis of diffusion-weighted magnetic resonance imaging in detecting prostate cancer

PURPOSE

The objective of this study was to determine the diagnostic performance of quantitative diffusion-weighted magnetic resonance imaging in detection of prostate cancer.

METHODS

A comprehensive search was performed for English articles published before May 2012 that fulfilled the following criteria: patients had histopathologically proved prostate cancer; diffusion-weighted imaging (DWI) was performed for the detection of prostate cancer, and data for calculating sensitivity and specificity were included. Methodological quality was assessed by using the quality assessment of diagnostic studies instrument. Publication bias analysis, homogeneity, inconsistency index, and threshold effect were performed by STATA version 12.

RESULTS

Of 119 eligible studies, 12 with 1637 malignant and 4803 benign lesions were included. There was notable heterogeneity beyond threshold effect and publication bias. The sensitivity and specificity with 95% confidence interval (CI) estimates of DWI on a per-lesion basis were 77% (CI, 0.76-0.84) and 84% (CI, 0.78-0.89), respectively, and the area under the curve of summary receiver operating characteristic curve was 0.88 (CI, 0.85-0.90). The overall positive and negative likelihood ratios with 95% CI were 4.93 (3.39-7.17) and 0.278 (0.19-0.39), respectively.

CONCLUSIONS

Quantitative DWI has a relative sensitivity and specificity to distinguish malignant from benign in prostate lesions. However, large-scale randomized control trials are necessary to assess its clinical value because of nonuniformed diffusion gradient b factor, diagnosis threshold, and small number of studies.