Original Research
Genitourinary Imaging
December 4, 2018

Abbreviated Biparametric Versus Standard Multiparametric MRI for Diagnosis of Prostate Cancer: A Systematic Review and Meta-Analysis


OBJECTIVE. The objective of our study was to evaluate the diagnostic accuracy of abbreviated biparametric MRI (bpMRI) versus standard multiparametric MRI (mpMRI) for prostate cancer (PCa) using guided biopsy or prostatectomy histopathology results as the reference standard.
MATERIALS AND METHODS. A comprehensive literature search of PubMed, Web of Science, and Cochrane Library databases was performed by two researchers independently and the relevant references were assessed. Original research studies comparing bpMRI with mpMRI in diagnosing PCa were included. The methodologic quality of eligible studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Data necessary to complete 2 × 2 contingency tables were obtained to calculate the diagnostic performance of bpMRI and mpMRI using Stata (version 14).
RESULTS. Ten studies were included, and a total of 1705 patients and 3419 lesions were analyzed. Sensitivity, specificity, positive likelihood ratio (LR), negative LR, and diagnostic odds ratio (DOR) of mpMRI in diagnosing PCa were 0.79 (95% CI, 0.69–0.87), 0.89 (95% CI, 0.70–0.96), 6.9 (95% CI, 2.5–18.8), 0.24 (95% CI, 0.16–0.35), and 29 (95% CI, 10–83). Sensitivity, specificity, positive LR, negative LR, and DOR of bpMRI in diagnosing PCa were 0.79 (95% CI, 0.69–0.87), 0.88 (95% CI, 0.73–0.95), 6.4 (95% CI, 2.9–14.5), 0.24 (95% CI, 0.16–0.35), and 27 (95% CI, 11–67). Meta-analysis showed no statistically significant difference between bpMRI and mpMRI for the diagnosis of PCa, and the areas under the summary ROC (SROC) curves were 0.89 and 0.88, respectively (p = 0.9944). Results of the sensitivity analysis were consistent, and the area under the SROC curve for bpMRI and mpMRI was 0.89 for both (p = 0.9349).
CONCLUSION. The available evidence indicates that bpMRI and mpMRI have similar diagnostic efficacy in diagnosing PCa.
Throughout the world, about one patient dies of prostate cancer (PCa) every 4 minutes [1]. The prevalence of PCa in older men will continue to rise in the future because the world's mean life expectancy is constantly on the rise [1]. According to the International Agency for Research on Cancer, PCa is expected to become a major contributor to the “doubling by 2030 of annual cancer cases” [2].
Multiparametric MRI (mpMRI) of the prostate is currently the most accurate imaging method for detection, localization, and staging of PCa [3], which was confirmed by a meta-analysis [4]. An mpMRI examination includes anatomic imaging sequences (T2-weighted imaging and T1-weighted imaging) and functional imaging sequences (DWI and dynamic contrast-enhanced MRI [DCE-MRI]) and has become a recognized standard method for evaluating clinically significant PCa [5]. With combined morphologic and functional MRI, mpMRI could help to improve diagnostic sensitivity and specificity correlated to biopsy Gleason grades [6]. According to the Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) scoring system, adopting mpMRI is recommended as a noninvasive and standard diagnostic tool compared with ultrasound-guided biopsy [7].
A recent study showed that the additional value of DCE-MRI to T2-weighted imaging and DWI was minimal: PCa detection was aided by the addition of DCE-MRI in only four of 125 peripheral zone (PZ) tumors ≥ 0.5 mL and 0 of 27 PZ tumors < 0.5 mL [8]. However, in another study, the authors found that the addition of DCE-MRI to DWI scores in the PZ yielded substantial improvements in the probability of PCa detection [9]. In yet another study, investigators reported that comparable accuracy could be achieved simply by a combination of bipara-metric MRI (bpMRI) and lesion volume [10]. In addition, clinical utilization of bpMRI helps to reduce costs and scanning time [10]. Three previous meta-analyses showed that the addition of DCE-MRI did not improve PCa detection compared with T2-weighted imaging and DWI alone [1113]. In the current study, we conducted a meta-analysis to compare abbreviated bpMRI versus standard mpMRI in diagnosing PCa.

Materials and Methods

Evidence Acquisition

This systematic review and meta-analysis were carried out according to the recommendations of Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. A comprehensive literature search of the PubMed (U.S. National Library of Medicine), Web of Science (Clarivate Analytics), and Cochrane Library databases was performed by two researchers independently to identify studies that evaluated the diagnostic value of bpMRI versus mpMRI for PCa with and using transrectal ultrasound (TRUS)-guided biopsy, MRI-TRUS fusion targeted biopsy, or pros-tatectomy and clinical follow-up data as the reference standard. We limited our search to studies published on or before April 14, 2018. The search strategy was as follows: diagnosis AND (multiparametric MRI OR multiparametric magnetic resonance imaging OR multiparametric MRI prostate OR multiparametric MRI prostate cancer) AND (bpMRI OR ((DWI OR diffusion-weighted imaging OR diffusion weighted MRI) AND (T2-weighted MRI OR T2WI)) OR bpMRI OR biparametric MRI OR biparametric prostate OR biparametric prostate MRI) AND prostate cancer. Medical subject heading terms and variations of each term were used. Language was not confined.
The reference lists of the relevant articles were manually screened to identify other potentially eligible articles. Titles and abstracts were initially screened independently; eligible abstracts were selected by reading the full text and finally were included or excluded. Any disagreement was discussed and resolved by consensus.
Types of studies—Retrospective and prospective studies comparing bpMRI with mpMRI in diagnosing PCa were considered. Studies in which only bpMRI outcomes were investigated were excluded, because these studies disregard essential information about comparison. Studies with insufficient data to create 2 × 2 tables to assess diagnostic accuracy were excluded.
Patients—The following patients were considered as participants: patients with clinical suspicion of PCa based on elevated prostate-specific antigen (PSA) value or an abnormal digital rectal examination (DRE) finding and patients with a previous negative prostate biopsy with continually increasing PSA values or an abnormal finding at DRE performed an interval before MRI examination. For this review, we focused on primary PCa diagnosis. Patients who already had a diagnosis of low-grade PCa and had been on active surveillance were not eligible, and patients with recurrent PCa were also excluded, as this generated multiple biases. The main indicator of observation in this study was detection of PCa regardless of Gleason score and location of the lesion.

Quality Assessment and Data Extraction

Each included study was assessed by two observers (with 8 and 5 years' experience of systematic reviews) using the revised instrument for the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). The observers used tailored QUADAS-2 quality checklists [14, 15]. Each item was scored as Yes or No or as Unclear when there was insufficient information to make a precise judgment. Discrepancies were resolved by consensus. We used RevMan software (version 5.3, The Cochrane Collaboration) [16] to display the QUADAS-2 results graphically.
The following data were extracted from each study: the first author's name, year of publication, country where study was performed, sample size, description of study population (age), study design (prospective, retrospective, or unknown), PSA value, location of lesions, characteristics of lesions analyzed, magnetic field strength, b values for DWI techniques, descriptions of interpretations of the diagnostic tests, and description of the reference standard. True-positive, false-positive, false-negative, true-negative, sensitivity, and specificity results for the detection of lesions were extracted, and 2 × 2 contingency tables were constructed.

Statistical Analysis

Heterogeneity was assessed using the Cochran Q test and the Higgins I2 heterogeneity index [17], where p ≤ 0.5 indicated significant heterogeneity. When I2 < 50%, a fixed-effect model was used for meta-analysis. When I2 > 50%, the random-effects model of DerSimonian and Laird was applied [18]. Source of heterogeneity was explored through meta-regression analysis, which was performed using Meta-DiSc software (version 1.4, Ramón y Cajal Hospital). If there was obvious heterogeneity, sensitivity analysis was performed. Our primary analysis included all the studies, but the sensitivity analysis was performed after removal of the studies indicating heterogeneity.
The statistical computations of sensitivity, specificity, diagnostic odds ratio (DOR), positive likelihood ratio (LR), and negative LR with 95% CIs were performed using Stata software (version 14, StataCorp). Summary ROC (SROC) curves and area under the SROC curve (AUC) were constructed to assess the diagnostic accuracy capabilities.


Literature Search Results

The literature search was performed of studies published on or before April 14, 2018. Six articles were retrieved from Cochrane Library databases; 206 articles from PubMed; and 185 articles from Web of Science. A total of 397 articles were identified from initial screening. A total of 50 articles were also identified from the relevant references. Of the 447 published studies, 185 studies were repetitive and thus were excluded. After a review of the titles and abstracts, 59 studies were found to be potentially relevant and their full texts were read. Figure 1 shows the flow diagram of the search for eligible studies. Finally, 10 published studies were included in the meta-analysis, consisting of a total of 1705 patients and 3419 lesions.
Fig. 1 —Flowchart shows process for selecting studies for meta-analysis.

Study Characteristics

The patient and study characteristics of the studies included in the meta-analysis are summarized in Table 1. The 10 studies came from seven countries: Seven studies were from Europe, and three studies were from Japan and the United States. The age of the included patients ranged from 41 to 86 years, with a median or mean age ranging from 62 to 69 years. The median or mean PSA value ranged from 6.8 to 20.51 ng/mL. Eight of 10 studies were conducted retrospectively. The lesions in three studies were located in PZ or transition zone (TZ), the lesions in one study were located in the TZ, and the lesions in one study were located at the TZ and anterior fibrous stroma; in the remaining five studies specific localization of the lesions was not reported.
TABLE 1: Study and Patient Characteristics of Studies Included in Meta-Analysis
First Author [Reference No.] (Year of Publication)CountryStudy DesignNo. of PatientsLocation of LesionsNo. of LesionsAge (y)aPSA (ng/mL)aProstate Volume (mL)aPCa (No. of Lesions)
De Visschere [21] (2017)BelgiumR245PZ or TZ24566 (44–85)9 (1.4–935.5)49.3 (19.8–201)144101
Iwazawa [24] (2011)JapanR178NR71268.8 (41–86)20.51 (4.04–568.50)NR159553
Kitajima [25] (2010)JapanR53NR42469 (56–84)11.1 (4.2–112.1)NR99325
Kuhl [22] (2017)GermanyR542NR54265 (42–80)7 (3.2–67.5)52 (13–196)180362
Radtke [23] (2015)GermanyP191TZ and AFS19166 (61–72)7.9 (6.1–12.3)44 (32–66)13952
Rosenkrantz [19] (2015)United StatesR106TZ63662 (46–81)6.9 (NR)NR62574
Scialpi [20] (2017)ItalyR41PZ or TZ13164.5 (53–78)6.8 (1.5–39.3)NR1310
Stanzione [28] (2016)ItalyP82PZ or TZ8265 (43–84)8.8 (NR)62.9 (NR)3448
Thestrup [27] (2016)DenmarkR204NR20465 (45–75)14 (2.2–120)60 (23–263)68136
Barth [26] (2017)SwitzerlandR63NR25265.2 (51.2–78.2)9.2 (0.3–32.4)NR84168

Note—PSA = prostate-specific antigen, PCa = prostate cancer, R = retrospective, P = prospective, PZ = peripheral zone, TZ = transition zone, NR = not reported, AFS = anterior fibrous stroma.

Data are expressed as means or medians with ranges in parentheses.
The technical characteristics of studies included in the meta-analysis are summarized in Table 2. Nine of 10 studies used 3-T MRI. One study used endorectal coil. All studies performed high-b-value acquisition (b value ≥ 800 s/mm2). Two studies [19, 20] used histopathology results from pure pros-tatectomy as the reference standard. Eight studies used TRUS-guided biopsy, MRI-targeted biopsy, or prostatectomy histopathology results and clinical data as the reference standard. The cutoff values for PCa diagnosis were reported in six studies; the cutoff values were PI-RADSv2 ≥ 4 in one study [21], PI-RADSv2 ≥ 3 in one study [22], PI-RADS ≥ 3 in one study [23], score ≥ 3 in two studies [24, 25], and score of ≥ 4 on 5-point scale in one study [26].
TABLE 2: Technical Characteristics of Studies Included in Meta-Analysis
First Author [Reference No.] (Year of Publication)Magnetic Field Strength (T)Coilb Values (s/mm2)Readers, Years of ExperienceReference StandardPathologistsCutoffValue
De Visschere [21] (2017)3NR50, 250, 500, 750, 1000NRSystematic biopsy or RP histopathology and clinical follow-up dataNRPI-RADSv2 ≥ 4
Iwazawa [24] (2011)1.5Phased-array coil0, 10002 Experienced abdominal radiologists, years NRSystematic or targeted biopsy histopathologyNRScore ≥ 3
Kitajima [25] (2010)3Multichannel phased-array body coil0, 10002 Experienced radiologists, 8 and 20 y reading prostate MRISystematic biopsy histopathologyNRScore ≥ 3
Kuhl [22] (2017)316-Element surface coil0, 800, 1000, 14004 Radiologists with between 2 and 9 y reading prostate MRISystematic or targeted biopsy or prostatectomy histopathologyCertified uropathologistPI-RADSv2 ≥ 3
Radtke [23] (2015)3NR0, 50, 100, 150, 200, 250, 8001 Experturoradiologist, years NRTargeted biopsy or RP histopathologyDedicated uropathologistPI-RADS ≥ 3
Rosenkrantz [19] (2015)3Phased-array coil50, 1000, 20003 Radiologists, 8, 2, and 1 y reading prostate MRIRP histopathologyDedicated uropathologistNR
Scialpi [20] (2017)316-Channel torso phased-array surface coil0, 750, 1500, 20002 Experienced radiologists, years NRRP histopathologyGenitourinary pathologistNR
Stanzione [28] (2016)3Phased-array surface coil0, 400, 20002 Radiologists, Hand 10 ySystematic biopsy histopathologyNRNR
Thestrup [27] (2016)3NR0, 100, 800, 20002 Experienced radiologists, years NRBiopsy or prostatectomy histopathologyNRNo grading
Barth [26] (2017)318-Channel phased-array receiver coil and endorectal coil0, 50, 100, 600, 1000, 14003 Experturoradiologists, 11, 6, and 12 yTransperineal template saturation biopsy histopathologyDedicated genitourinary pathologistsScore ≥ 4 on 5-point scale

Note—NR = not reported, PI-RADS = Prostate Imaging Reporting and Data System, PI-RADSv2 = PI-RADS version 2, RP = radical prostatectomy.

Quality Assessment

Results of QUADAS-2 assessment are presented in Figures 2 and 3. The quality of the studies varied from moderate to high. The main causes of potential bias were attributed to patient selection, index test, and flow and timing. The Deeks funnel plot asymmetry test indicated no publication bias, as shown in Figure 4.
Fig. 2 —Chart shows summary of results of methodologic quality analysis of 10 studies in meta-analysis according to Quality Assessment of Diagnostic Accuracy Studies 2.
Fig. 3 —Chart shows results of methodologic quality analysis for each study in meta-analysis according to Quality Assessment of Diagnostic Accuracy Studies 2.
Fig. 4 —Plot shows results of Deeks funnel plot asymmetry test of publication bias (p = 0.80). Numbers in circles are numbers assigned to studies. ESS = effective sample size.

Pooled Analysis of Individual Studies

Data were derived from the included studies, as shown in Table 3. The data of the Scialpi et al. [20] study could not be extracted. In that study [20], the reported sensitivity of detecting PCa lesions was the same and equal for bpMRI and mpMRI: 100% in the PZ, 97.6% in the entire prostate, and 94.7% in the TZ.
TABLE 3: Sensitivity, Specificity, True-Positive (TP), False-Positive (FP), False-Negative (FN), and True-Negative (TN) Results for Multiparametric MRI (mpMRI) and Biparametric MRI (bpMRI) Derived From the Studies Included in the Meta-Analysis
First Author [Reference No.] (Year of Publication)mpMRIbpMRI
Sensitivity (%)Specificity (%)TPFPFNTNSensitivity (%)Specificity (%)TPFPFNTN
De Visschere [21] (2017)72.982.210518398367.485.197154786
Iwazawa [24] (2011)72.980.11161104344374.879.811911240441
Kitajima [25] (2010)80.895.780141931175.894.2751924306
Kuhl [22] (2017)86.788.1156432431985.690.91543326329
Radtke [23] (2015)781001080315291.893.6896888
Rosenkrantz [19] (2015)63.494.939292354564.595.3402722547
Scialpi [20] (2017)97.6 for entire prostate, 94.7 for TZ, 100 for PZNRNRNRNRNR97.6 for entire prostate, 94.7 for TZ, 100 for PZNRNRNRNRNR
Stanzione [28] (2016)91.196.231234685.398.1291547
Thestrup [27] (2016)95.610.36512231494.114.764116420
Barth [26] (2017)49.39026212617949.390262226178

Note—TZ = transition zone, PZ = peripheral zone, NR = not reported.

The overall performance of mpMRI in diagnosing PCa was as follows: sensitivity, 0.79 (95% CI, 0.69–0.87); specificity, 0.89 (95% CI, 0.70–0.96); positive LR, 6.9 (95% CI, 2.5–18.8); negative LR, 0.24 (95% CI, 0.16–0.35); and DOR, 29 (95% CI, 10–83) (Fig. 5 and Table 4). The overall performance of bpMRI in diagnosing PCa was as follows: sensitivity, 0.79 (95% CI, 0.69–0.87); specificity, 0.88 (95% CI, 0.73–0.95); positive LR, 6.4 (95% CI, 2.9–14.5); negative LR, 0.24 (95% CI, 0.16–0.35); and DOR, 27 (95% CI, 11–67) (Fig. 6 and Table 4). Figure 7 shows the SROC plot with 95% CI area. The AUCs for mpMRI and bpMRI were 0.88 and 0.89, respectively, and the relative diagnostic odds ratio (RDOR) was 1 (95% CI, 0.31–3.24) (p = 0.9944).
Fig. 5 —Forest plots show sensitivity and specificity of multiparametric MRI for diagnosis of prostate cancer in each study included in meta-analysis. Horizontal bars indicate 95% CIs of individual studies. Diamond represents combined diagnostic effect, and diamond's breadth shows 95% CIs of pooled results. Vertical line indicates point estimates of pooled results.
TABLE 4: Summary of Performance of Multiparametric MRI (mpMRI) and Biparametric MRI (bpMRI) for the Diagnosis of Prostate Cancer
Statistical IndicatorsPrimary AnalysisSensitivity Analysis
Sensitivity0.79 (0.69–0.87)0.79 (0.69–0.87)0.73 (0.63–0.81)0.71 (0.62–0.79)
Specificity0.89 (0.70–0.96)0.88 (0.73–0.95)0.90 (0.84–0.94)0.90 (0.85–0.94)
Positive LR6.9 (2.5–18.8)6.4 (2.9–14.5)7.2 (4.5–11.6)7.3 (4.7–11.3)
Negative LR0.24 (0.16–0.35)0.24 (0.16–0.35)0.30 (0.21–0.42)0.32 (0.23–0.43)
DOR29 (10–83)27 (11–67)24 (12–48)23 (12–43)
Area under summary ROC curve0.88 (0.85–0.91)0.89 (0.86–0.91)0.89 (0.86–0.92)0.89 (0.86–0.92)

Note—Data in parentheses are 95% CIs. LR = likelihood ratio, DOR = diagnostic odds ratio.

Fig. 6 —Forest plots show sensitivity and specificity of biparametric MRI for diagnosis of prostate cancer in each study included in meta-analysis. Horizontal bars indicate 95% CIs of individual studies; Diamond represents combined diagnostic effect, and diamond's breadth shows 95% CIs of pooled results. Vertical line indicates point estimates of pooled results.
Fig. 7 —Summary ROC plot comparing multiparametric MRI (mpMRI) and biparametric MRI (bpMRI) for diagnosis of prostate cancer.
The posttest results are shown in Figure 8: The positive posttest probability increased from 20% to 64%, whereas the negative posttest probability decreased from 20% to 62%, indicating an increased diagnosis accuracy of bpMRI. Sensitivity increases and specificity decreases, indicating a threshold effect, were reported by Thestrup et al. [27]. Meanwhile, a meta-regression analysis showed that study design was a factor of heterogeneity (RDOR = 10.18 [95% CI, 2.55–40.67], p = 0.0028). After removal of the Thestrup et al. study and the two prospective studies [23, 28], sensitivity analysis showed no significant changes, and the AUCs for mpMRI and bpMRI were both 0.89 (Table 3) (RDOR = 1.05 [95% CI, 0.30–3.62], p = 0.9349).
Fig. 8 —Graphic shows posttest probability of biparametric MRI diagnosing prostate cancer.


The findings of this meta-analysis showed that bpMRI had a similar diagnosis performance compared with mpMRI with almost the same diagnosis sensitivity, specificity, and DOR. These results indicate that the role of DCE-MRI in mpMRI was minimal in diagnosing PCa and that an abbreviated bpMRI protocol consisting of T2-weighted imaging and DWI has the potential to replace standard mpMRI.
The sensitivity and specificity for mpMRI varied in the individual studies, with sensitivities ranging from 0.50 to 0.91 and specificity ranging from 0.80 to 1.00 except in the study by Thestrup et al. [27]. In the latter study, sensitivity was more than 90% while the specificity was 10.3%, which indicates an obvious threshold effect. The sensitivity of bpMRI ranged from 0.50 to 0.92, and specificity varied from 0.80 to 0.98, showing a similar diagnosis performance with mpMRI. In addition, SROC curve analysis showed that AUCs for mpMRI and bpMRI were very close, 0.88 and 0.89, respectively, and the result of sensitivity analysis was consistent, with an AUC of 0.89 for both. Moreover, posttest analysis showed that the positive LR did not change significantly and the negative LR decreased, indicating a good diagnostic performance.
In clinical practice, the majority of studies included in our meta-analysis used two or more radiologists to interpret the MR images, which was inevitable to avoid interpretation bias, but interobserver agreement was generally excellent or good in these studies; thus, the mean sensitivity and specificity were adopted in statistical analysis. PI-RADS or PI-RADSv2 or confidence scale or 5-point scale was adopted to assign the possibilities of PCa in these studies. Although the threshold for PCa diagnosis was not the same, the majority of the included studies used a threshold of PI-RADS ≥ 3. However, three studies [19, 20, 28] did not report the grading system used for PCa diagnosis, and one study reported that no grading was used [27]. In the latter study [27], images were categorized only according to harboring significant PCa or not, which may lead to interpretation bias.
We found a marked heterogeneous effect among different studies, with I2 far greater than 50%, even up to more than 90%. The fact that patient selection was not clearly reported as consecutive or random and that there may have been inappropriate exclusions may have introduced selection bias. A threshold not reported or prespecified may have led to interpretation bias. The study by Thestrup et al. [27] showed an obvious threshold effect, which may also have introduced interpretation bias. The fact that the same reference standard was not used for all studies may have led to flow and timing bias. Furthermore, we used meta-regression analysis to explore the sources of heterogeneity, and our results showed that research design was a source of heterogeneity. In this case, we performed sensitivity analysis, according to the study design in retrospective or prospective manner, and the results showed that sensitivity and specificity were not affected, which indicates that the results are robust.
Most of the included studies used 3-T MRI scans, but a study conducted in 2011 using 1.5-T MRI showed no difference in performance [24]. At present, the use of 3-T MRI of the prostate is widespread because of its higher image quality; however, low-field-strength MRI, which conforms to European Society of Urogenital Radiology (ESUR) guidelines, is also acceptable.
According to ESUR guidelines [29], a PI-RADS score of 3 means that findings are suspicious for clinically significant cancers and a PI-RADS score of 4 means that clinically significant cancer is likely to exist. Two included studies used a cutoff value for PCa diagnosis of PI-RADS 3, whereas two studies [24, 25] used the cutoff value of a confidential score of 3 [22, 23]; however, meta-regression analysis did not recognize that the cutoff value systems for the studies in the meta-analysis were a source of heterogeneity. Although PI-RADSv2 has been shown to detect PCa with a higher sensitivity than PI-RADS version 1 (PI-RADSv1) with no significant difference in specificity [30], we did not find any difference between PI-RADSv2 and the other scoring systems, such as the confidence scale that also uses five categories of scoring to indicate the likelihood of PCa. This may be due to the intrinsic similarity of the prostate scoring system [8] and the good consistency between the observers. A previous study has shown a need to further determine whether a lesion with PI-RADS 3 needs to be biopsied [31]; however, according to the results of this study—that is, the high sensitivity and high specificity of the meta-analysis, biopsy of PI-RADS 3 lesions should be recommended to avoid missing a PCa diagnosis. These results are consistent with the results reported by Schoots [32].
Approximately 70–75% of PCa lesions occur in the PZ [33]. Of the 10 studies included in this meta-analysis, five studies did not report specific localization of the lesions, three studies reported the lesions were located at the PZ or TZ, one study reported lesions in the TZ, and one study reported lesions in the TZ and anterior fibrous stroma. Therefore, PZ PCa and TZ PCa were not separated because of the limited studies in this primary meta-analysis. Future studies could further investigate the differences between PZ PCa and TZ PCa. The difference between PI-RADSv2 and PI-RADSv1 is that the imaging sequences are weighted according to the lesion location in the PZ or TZ to improve the performance of diagnosis. In PI-RADSv2, the role of DCE-MRI is secondary to T2-weighted imaging and DWI and DCE-MRI is expressed as positive or negative only [34]. DWI is defined as being dominant for evaluation of PZ lesions, and T2-weighted imaging is dominant for evaluation of TZ lesions. Further sequences will contribute to only the overall PI-RADS score if an intermediate finding—more precisely, a lesion of PI-RADS score 3—in the dominant sequence is found. In this case, a second sequence (DCE-MRI of PI-RADS 4 or 5 lesion in the PZ and DWI of PI-RADS 5 lesion in the TZ) can upgrade the lesion score to an overall PI-RADS 4. Therefore, DCE-MRI does not contribute to the TZ PI-RADS score, and T2-weighted imaging does not have relevance in scoring PZ lesions [35]. A recent study has confirmed the superiority of DWI and T2-weighted imaging compared with DCE-MRI and T2-weighted imaging [12]. In view of the time and cost of DCE-MRI, more studies have suggested that DCE-MRI should be omitted [36]. Moreover, performance of DWI has been found to be similar to that of DCE-MRI for PCa diagnosis [11]; bpMRI becomes an attractive proposition as a quick screening examination in biopsy-naive patients [36]. Our results showed that bpMRI and mpMRI were not statistically different both in sensitivity and specificity and in DOR values; thus, these results suggest that bpMRI has the potential to replace the tedious and time-consuming mpMRI as a simple solution.
The strengths of this systematic review include adequate studies in the literature available for meta-analysis, meta-regression analysis to find possible causes of heterogeneity, and credible and robust sensitivity analysis. However, it also has limitations. The sources of heterogeneity between studies were hard to identify even after excluding heterogeneity of study design. Four studies did not report a PCa diagnosis cutoff value, which may have caused bias. PZ PCa and TZ PCa were not divided into subgroups because of the limited number of studies in this initial metaanalysis. Future studies may investigate the differences between PZ PCa and TZ PCa.
In conclusion, abbreviated bpMRI was verified to be similar in diagnostic efficacy to mpMRI; therefore, abbreviated bpMRI may be of potential value in clinical practice.


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Information & Authors


Published In

American Journal of Roentgenology
Pages: 357 - 365
PubMed: 30512996


Submitted: May 4, 2018
Accepted: July 31, 2018
Version of record online: December 4, 2018


  1. biparametric MRI
  2. diagnosis
  3. meta-analysis
  4. multiparametric MRI
  5. prostate cancer



Zhen Kang
Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science & Technology, 1095 Jiefang Rd, Wuhan 430030, China.
Xiangde Min
Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science & Technology, 1095 Jiefang Rd, Wuhan 430030, China.
Jeffrey Weinreb
Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT.
Qiubai Li
Department of Radiology, UT Southwestern Medical Center, Dallas, TX.
Zhaoyan Feng
Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science & Technology, 1095 Jiefang Rd, Wuhan 430030, China.
Liang Wang
Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science & Technology, 1095 Jiefang Rd, Wuhan 430030, China.


Address correspondence to L. Wang ([email protected]).

Funding Information

Supported in part by grants 81171307 and 81671656 from the National Natural Science Foundation of China.

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