Abstract
OBJECTIVE
To validate the use of biparametric (T2- and diffusion-weighted) magnetic resonance imaging (B-MRI) and prostate-specific antigen (PSA) or PSA density (PSAD) in a biopsy-naive cohort at risk for prostate cancer (PCa).
METHODS
All patients (n = 59) underwent PSA screening and digital rectal exam prior to a B-MRI followed by MRI or transrectal ultrasound fusion-guided targeted biopsy. Previously reported composite formulas incorporating screen positive lesions (SPL) on B-MRI and PSA or PSAD were developed to maximize PCa detection. For PSA, a patient was considered screen positive if PSA level + 6 × (the number of SPL) >14. For PSAD, screening was positive if PSAD × 14 + (the number of SPL) >4.25. These schemes were employed in this new test set to validate the initial formulas. Performance assessment of these formulas was determined for all cancer detection and for tumors with Gleason ≥3 + 4.
RESULTS
Screen positive lesions on B-MRI had the highest sensitivity (95.5%) and negative predictive value of 71.4% compared with PSA and PSAD. B-MRI significantly improved sensitivity (43.2–72.7%, P = .0002) when combined with PSAD. The negative predictive value of PSA increased with B-MRI, achieving 91.7% for B-MRI and PSA for Gleason ≥3 + 4. Overall accuracies of the composite equations were 81.4% (B-MRI and PSA) and 78.0% (B-MRI and PSAD).
CONCLUSION
Validation with a biopsy-naive cohort demonstrates the parameter SPL performed better than PSA or PSAD alone in accurately detecting PCa. The combined use of B-MRI, PSA, and PSAD resulted in improved accuracy for detecting clinically significant PCa. UROLOGY 88: 125–134, 2016. Published by Elsevier Inc.
Following the recommendation of U.S. Preventive Services Task Force against widespread prostate-specific antigen (PSA) screening, the rate of PSA screening has decreased.1 There is concern in the urologic community that this will result in increases in prostate cancer (PCa)-specific mortality as PCa is already the second leading cause of cancer death after lung cancer in American men, with projections of nearly 30,000 deaths in 2015.2 Although PSA screening alone may not be adequate, it is important to develop new methods of detecting PCa while it is still amenable to curative therapy. Multiparametric magnetic resonance imaging (MP-MRI) has been utilized for PCa detection in hopes of better identifying high-grade disease that may be missed by conventional sextant biopsy.3 While reducing the burden imposed by the detection of low-grade disease, MP-MRI thereby reduces overtreatment for which PSA screening and blind transrectal ultrasound (TRUS) biopsy have been strongly criticized.4
MP-MRI of the prostate demonstrates that anatomic information combined with functional imaging offers precise detection, improved disease localization, and accurate staging of PCa.3,5–11 However, MP-MRI is expensive and efforts have been made to reduce its cost while still maintaining its value. Over the past decade, attempts to streamline the MP-MRI exam have included scanning without the endorectal coil, eliminating MR spectroscopy, which is time consuming, and reducing the emphasis on dynamic contrast enhancement (DCE). Similarly, incorporating MRI-TRUS fusion-guided biopsy as opposed to in gantry biopsies would make each diagnosis more cost-effective. It has been suggested that a biparametric MRI (B-MRI) including only the T2-weighted (T2W) and diffusion weighted imaging (DWI) parameters [with high b-value DWI and apparent diffusion coefficient (ADC) maps] could reliably detect PCa without incurring the time and cost of traditional three-parameter MP-MRI.12 This work led to the empiric development of two formulas that incorporate both B-MRI findings and PSA or PSAD values to predict clinically significant PCa. For PSA, a patient was considered screen positive when PSA level + 6 × (the number of SPL) >14. For PSAD, screening was positive if PSAD × 14 + (the number of SPL) >4.25. Using these uniquely optimized MRI and PSA-based formulas, B-MRI demonstrated a high accuracy (79%) in detecting clinically significant PCa. When compared with PSA level and PSA density (PSAD), B-MRI outperformed modality alone in a biopsy-naive population.12 Those data, however, must be considered simply a training set for the formulas, as they have not yet been tested on a separate cohort.
Our objective is to validate the use of previously proposed composite formulas in a new cohort of biopsy-naive men undergoing evaluation for PCa using PSA, PSAD, and B-MRI to detect disease.
METHODS
Patients and Methods
Retrospective review of a new cohort 307 patients enrolled in a protocol who underwent MP-MRI and MRI-TRUS fusion-guided targeted biopsy from December 2012 to December 2014 yielded 86 patients who were biopsy naive. Patients were referred for entry into this Institutional Review Board–approved protocol based on a clinical suspicion of PCa derived from either elevated PSA levels (>4 ng/mL) or abnormal findings on digital rectal exam (DRE). Subsequently, patients underwent MP-MRI prostate imaging as described previously.13 From the cohort of 86 biopsy-naive patients, 7 were excluded because of the referral to our institution secondary to abnormal PSA kinetics without a single PSA level >4 ng/mL. Two additional patients were excluded from the study because of artifacts on the MRI related to hip prostheses. Seventy-seven patients with lesions suspicious for PCa on MP-MRI subsequently underwent targeted biopsies in the axial and sagittal planes in addition to systematic 12-core extended sextant biopsies using an office-based MRI-TRUS fusion platform (UroNav, InVivo Corp). Systematic and targeted biopsies were performed in the same session (Supplemental Table S1).14 All 77 patients included in the study underwent a single MRI evaluation prior to biopsy, with no adverse events during imaging acquisition or biopsy. Positive biopsies revealed prostatic adenocarcinoma on pathology.
Data Collection and Analyses
MP-MRI identified suspicious lesions based on previously established imaging characteristics and parameters.15 Patients with lesions visible and suspicious on both T2W and DWI MRI (B-MRI) sequences were considered “screen-positive” lesions (SPL) in keeping with previously published work.12 Patient demographics, imaging, and biopsy pathology correlating to 12-core biopsy and SPL target biopsied were analyzed.
Statistical comparisons of categorical and continuous variables were performed using Fisher’s exact test and paired, two-tailed Student’s t-tests, respectively. Sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) were calculated for the detection of PCa based on the same formulas and the same thresholds previously published, including PSA >4 ng/mL, PSAD >0.15 ng/mL/mL, and SPL number on B-MRI >1.12 Receiver operating characteristic (ROC) curves were calculated to determine prebiopsy variable discriminative. Eighteen patients with findings concerning for cT4 disease on MRI and those with a single SPL ≥1.5 cm in greatest dimension were excluded based on ROC curve analyses (Supplemental Fig. S1). The area under the curve (AUC) was calculated for each ROC curve ability and compared according to DeLong’s test using MedCalc for Windows, version 12.5 (MedCalc Software, Ostend, Belgium). A total of 59 men were included in the final statistical analyses.
Composite equations for predicting PCa were previously created using logistic regression derived from a prior cohort of biopsy-naive males referred to our institution, resulting in two prediction equations: (1) PSA level + 6 × (the number of SPL) >14 and (2) 14 × (PSAD) + (the number of SPL) >4.25. The sensitivity, specificity, NPV, and PPV of these composite equations in detecting PCa in this new patient cohort were calculated. McNemar’s test was used to compare sensitivity and specificity across the PSA and PSAD predictors and the composite equations. Univariate statistical analyses were performed using JMP Pro 11.0 (SAS Institute Inc., 2013, Cary, NC).
RESULTS
The 59 patients included in this validation study had no prostate biopsies prior to MP-MRI and MRI-TRUS fusion-guided targeted biopsy. The mean age and prebiopsy PSA were 64.3 ± 8.9 years (range 45.0–84.9) and 6.6 ± 5.7 ng/mL (range 0.9–43.3). Complete demographic data are presented in Table 1. Patients with PCa tended to be older, have a higher PSA level, have higher PSAD, have smaller prostate volume, and have increased suspicion of bilateral lesions consistent with previous observations. None of these differences between patients with and without cancer were statistically significant except for DRE findings (Table 1).
Table 1.
Demographics and MRI findings
| Characteristics | Total | No Cancer | Cancer | P |
|---|---|---|---|---|
| Number of men | 59 | 15 | 44 | |
| Mean (SD) | ||||
| Age, years | 64.3 (8.9) | 60.9 (7.7) | 65.4 (9.1) | .09 |
| PSA level, ng/mL | 6.56 (5.7) | 4.35 (2.4) | 7.31 (6.3) | .08 |
| PSAD, ng/mL/mL | 0.16 (0.22) | 0.08 (0.04) | 0.19 (0.24) | .08 |
| Prostate volume, mL | 49.1 (24.4) | 58.4 (27.8) | 45.9 (22.5) | .09 |
| N (%) | ||||
| DRE staging | .04 | |||
| cT1c | 50 (84.7) | 10 (66.7) | 40 (90.9) | |
| cT2 | 9 (15.3) | 5 (33.3) | 4 (9.1) | |
| Race | .50 | |||
| White | 49 (83.1) | 12 (80.0) | 37 (84.1) | |
| Black | 6 (10.2) | 1 (6.7) | 5 (11.4) | |
| Other | 4 (6.8) | 2 (13.3) | 2 (4.5) | |
| Biopsy Gleason score | ||||
| No cancer | 15 (25.4) | |||
| Gleason 6 | 10 (16.9) | |||
| Gleason 7 | 22 (37.3) | |||
| Gleason ≥8 | 12 (20.3) |
DRE, digital rectal exam; MRI, magnetic resonance imaging; PSA, prostate-specific antigen; PSAD, PSA density; SD, standard deviation.
The following parameters were obtained in each of the patients: PSA, PSAD, and SPL on B-MRI. These measures were used to create ROC curves from which AUCs ranging from 0.70 for PSA level alone to 0.86 for PSAD alone were calculated. For SPL on B-MRI, the AUC was 0.8 (Fig. 1). Pairwise comparisons of the ROC curves and resultant AUCs showed a statistical difference between PSA and PSAD, P = .04, with no statistical differences between SPL and either PSA or PSAD (Fig. 1). The addition of B-MRI to PSA and PSAD were also used to calculate ROC curves and generate AUCs (Fig. 2). DeLong’s test indicated that the addition of B-MRI to PSA significantly increased the AUC from 0.70 to 0.85 (P = .04). Addition of B-MRI to PSAD increased the AUC from 0.86 to 0.9, but was not statistically significant (P = .23).
Figure 1.
Predictive power of individual and composite detection measures. Pairwise comparisons of all individual measures, including screen positive lesion (SPL) (B), prostate-specific antigen (PSA) (C), PSA density (PSAD) (D) are seen all in one figure (A), where a statistical difference between PSA and PSAD existed (P = .04). Meanwhile, receiver operating characteristic curves were not statistically different when comparing PSA and SPL (P = .25) or PSAD and SPL (P = .44). The addition of biparametric magnetic resonance imaging (B-MRI) to PSA (E) increased the AUC and was a statistically significant increase (G). The addition of B-MRI to PSAD (F) increased the area under the curve (AUC), but was not statistically significant (H). (Color version available online.)
Figure 2.
Distribution of biopsy Gleason scores on test positive (A) and negative (B) men.
Individual detection measures were compared with composite formulas analyzing the combination of PSA level and B-MRI (composite 1) and the combination of PSAD level and B-MRI (composite 2). The sensitivity, specificity, PPV, NPV, and overall accuracy of cancer detection were assessed (Table 2A). Of the individual measures of PCa detection, SPL had the highest sensitivity (95.5%) and NPV (71.4%), and PSAD had the highest specificity (93.3%). Compared with PSA alone, the addition of B-MRI to PSA led to a higher sensitivity (90.9%) and moderate improvement in specificity (53.3%), although neither were statistically significant (Supplemental Table S2). When combined with PSAD, B-MRI significantly improved sensitivity from 43.2 to 72.7% (P = .0002) with no difference in specificity (93.3%, p = 1.0). The NPV of both composite detection measures increased, improving to 66.7% for PSA with B-MRI and 53.9% for PSAD with B-MRI. Similarly, the PPV of both composite measures improved to 85.1% for PSA with B-MRI and 97.0% for PSAD with B-MRI.
Table 2.
Performance of PSA level, PSAD, the number of SPL, and composite detection models incorporating the number of SPL with PSA level and PSAD in detecting PCa (A) and in detecting clinically significant PCa (≥Gleason 3 + 4) (B). Positive thresholds were defined as PSA level >4 ng/mL, PSAD >0.15 ng/mL/mL, SPL >1, composite 1: PSA + 6 × the number of SPL >14, composite 2: PSAD × 14 + number of SPL >4.25
| (A) Detecting Prostate Cancer | PSA Level n/N (%) | PSADn/N (%) | Number of SPL n/N (%) | Composite 1: PSA and B-MRI n/N (%) | Composite 2: PSAD and B-MRI n/N (%) |
|---|---|---|---|---|---|
| Sensitivity | 39/44 (88.6) | 19/44 (43.2) | 42/44 (95.5) | 40/44 (90.9) | 32/44 (72.7) |
| Specificity | 6/15 (40.0) | 14/15 (93.3) | 5/15 (33.3) | 8/15 (53.3) | 14/15 (93.3) |
| PPV | 39/48 (81.3) | 19/20 (95.0) | 42/52 (80.8) | 40/47 (85.1) | 32/33 (97.0) |
| NPV | 6/11 (54.5) | 14/39 (35.9) | 5/7 (71.4) | 8/12 (66.7) | 14/26 (53.9) |
| Overall accuracy | 45/59 (76.3) | 33/59 (55.9) | 47/59 (79.7) | 48/59 (81.4) | 46/59 (78.0) |
|
| |||||
| (B) Clinically Signficant Prostate Cancer | PSA Level n/N (%) | PSADn/N (%) | Number of SPL n/N (%) | Composite 1: PSA and B-MRI n/N (%) | Composite 2: PSAD and B-MRI n/N (%) |
| Sensitivity | 32/34 (94.1) | 18/34 (52.9) | 33/34 (97.1) | 33/34 (97.1) | 27/34 (79.4) |
| Specificity | 9/25 (36.0) | 23/25 (92.0) | 6/25 (24.0) | 11/25 (44.0) | 19/25 (76.0) |
| PPV | 32/48 (66.7) | 18/20 (90.0) | 33/52 (63.5) | 33/47 (72.0) | 27/33 (81.8) |
| NPV | 9/11 (81.8) | 23/39 (59.0) | 6/7 (85.7) | 11/12 (91.7) | 19/26 (73.1) |
| Overall accuracy | 41/59 (69.5) | 41/59 (69.5) | 39/59 (66.1) | 44/59 (74.6) | 46/59 (78.0) |
B-MRI, biparametric magnetic resonance imaging; NPV, negative predictive value; PCa, prostate cancer; PPV, positive predictive value; PSA, prostate-specific antigen; PSAD, PSA density; SPL, screen positive lesions.
Sensitivity, specificity, PPV, NPV, and overall accuracy were recalculated considering only clinically significant cancers (Gleason ≥3 + 4) (Table 2B). SPL had the highest sensitivity (97.1%) and NPV (85.7%), and PSAD had the highest specificity (92.0%). The composite equations showed that the addition of B-MRI to PSA resulted in a high sensitivity (97.1%) and an increase in specificity from 36.0% to 44.0%. For PSAD, the addition of B-MRI significantly increased sensitivity to 79.4% (P = .0039), while decreasing specificity to 76.0% (P = .125) (Supplemental Table S3). For clinically significant PCa, the NPV for individual metrics ranged from 59.0% for PSAD to 85.7% for SPL. The addition of B-MRI to PSA had the highest NPV at 91.7%, whereas B-MRI combined with PSAD had a NPV of 73.1%. PPV increased from 66.7% for PSA alone to 72.0% when PSA and B-MRI were combined. PPV decreased from 90.0% to 81.8% comparing PSAD with PSAD plus B-MRI, respectively.
For each individual parameter or composite parameter, a patient could be considered “test positive” or “test negative” (Fig. 2). Figure 2A shows the distribution of Gleason scores from biopsies in the “test-positive” population. Addition of B-MRI to the models improved the detection of Gleason ≥7 disease. Addition of B-MRI minimized those patients considered false positive, that is those with high clinical suspicion of harboring disease based on PSA level or PSAD, but who ultimately showed no cancer on biopsy. In the “test-positive” group, PSAD had a high specificity (93.3%) and therefore resulted in the fewest number of false positives. However, PSAD alone did not detect all Gleason ≥7 lesions, as compared with the composite modalities which incorporated B-MRI. Figure 2B depicts the “test-negative” cohort. The addition of B-MRI to other parameters resulted in the greater number of men with no PCa correctly categorized as test negative. Overall, the composite formulas improved the true-positive yield, identifying Gleason score ≥7 lesions with high sensitivity while minimizing the number of false positives.
DISCUSSION
Biparametric MRI, which utilizes only T2W and DWI MRI sequences, can be acquired in less than 20 minutes and does not require intravenous access, subsequently eliminating contrast media exposure. B-MRI could be a relatively cost-effective means of testing for PCa. We have previously shown that B-MRI combined with PSA or PSAD is even more effective than any of the parameters alone.12 Here, we validate this previous work in a new, separate cohort of biopsy-naive patients. We found that the number of lesions on B-MRI was highly predictive of the presence of cancer, and this parameter outperformed PSA and PSAD alone. Similarly, the combination of B-MRI with PSA and PSAD using previously derived composite formulas increased the diagnostic accuracy, sensitivity, and specificity of detecting PCa. Accuracy values of 81.4% and 78.0% were observed when using the composite equations, consistent with previously published results.12 Our patient population is likely enriched for higher-risk patients because of our referral pattern. As such, the performance of PSA and PSAD in our cohort is superior to historical reports. PSAD alone had the highest AUC and specificity compared with other individual parameters, but missed several men with PCa, thereby generating several critical false-negative predictions. Compared with PSAD alone, PSAD and B-MRI showed increased efficiency by reducing the number of false negatives and better distinguishing disease states. Between the two composite formulas, however, composite 1 (PSA level and B-MRI) better detected high-grade disease, missing no men with ≥Gleason 8.
MRI-TRUS fusion-guided targeted prostate biopsy was used to validate the results of this study. This method has been used in other biopsy-naive patient cohorts. Validating with prostatectomy specimens alone, while potentially more accurate for low-grade tumors, biases the population toward more advanced disease. Abd-Alazeez and colleagues used MP-MRI and a 5-point ordinal scale to stratify risk prior to the first targeted biopsy session using a 5-mm template prostate biopsy map in 129 consecutive men, addressing the ability of MP-MRI to detect cancer.16 MP-MRI demonstrated a sensitivity of 94% and an NPV of 89% for PCa detection. The group secondarily analyzed the subset of Gleason ≥4 + 3 disease (n = 13) and found that MP-MRI was 100% sensitive. This suggests that template or targeted biopsies may be adequate for confirming the presence of PCa.
A study by Peltier et al examined 110 biopsy-naive patients who were referred with a clinical suspicion of PCa due to abnormal PSA or DRE results. These patients underwent subsequent screening using MP-MRI consisting of T1- and T2-weighted imaging, DCE, DWI, and chemical MR spectroscopic imaging.17 The median age and PSA were 65.8 years (interquartile range of 59.5–70.7) and 6.9 ng/mL (interquartile range of 4.6–9.6), respectively, for the 100 of 110 men who underwent standard TRUS and targeted biopsy of lesions detected on MP-MRI. A 62.7% cancer detection rate was reported and 51 clinically significant lesions (Gleason ≥3 + 4 or maximum cancer core length ≥6 mm) were found. This performance is somewhat lower than what we observed.
Similarly, Quentin et al used MP-MRI to assess 128 biopsy-naive males with an elevated PSA (>4 ng/mL). The MP-MRI included T2W, DWI, and DCE imaging parameters requiring a total scan time of approximately 33 minutes per patient.18 MRI-guided in-bore and systematic TRUS-guided biopsy had a cancer detection rate of 60.9% (78/128), of which 82.1% were clinically significant (Gleason ≥3 + 4). MRI-guided in-bore biopsy alone detected 68 out of 78 cases with 85.3% (58 out of 68) clinically significant cases. Major differences between this study and the current study were that the actual MRI-targeted biopsy was performed in-bore and the MRI protocol included DCE MRI, whereas in our study, MRI-TRUS fusion-guided targeted biopsy was performed and we did not include DCE MRI in our detection methods. We achieved very similar results with a shorter scan time and without the need for costly in-bore biopsies.19 Additionally, both Peltier et al and Quentin et al utilized a more extensive multiparametric MRI sequences compared with a biparametric MRI study (T2W and DWI MRI), as was assessed in our study.
Contrast adverse reactions occur in 0.1–0.2% of gaolinium exposed patients, with symptoms ranging from mild nausea, vomiting, hives, and pruritus to more moderate-severe symptoms, including throat tightness and shock.20,21 Additionally, MR studies of the abdomen and pelvis tend to have the highest rates of reactions.21 B-MRI eliminates the need for intravenous access and contrast administration, avoiding these adverse consequences. Also, B-MRI further improves the price point for the study, as physicians are no longer required to be present during the examination to treat potential contrast reactions, allowing these studies to be potentially performed during off-hours. A formal cost-analysis model may aid in determining clinical efficiency thresholds, where the use of B-MRI may prove to be cost-effective in terms of cost per diagnosis.
These data support the initial composite prediction formulas incorporating B-MRI, PSA, and PSAD that were based on a prior biopsy-naive patient cohort. This new cohort of patients had identical entry criteria—clinical suspicion with PSA >4 ng/mL or positive DRE with B-MRI as a screening filter prior to biopsy. These formulas need to be validated in a larger multicenter study assessing any individual, regardless of prior biopsy history. This would assess patient care benefit—that is avoiding overdetection of low-risk cancer and selecting for high-risk PCa. A future investigation performed prospectively in patients being screened for PCa, where B-MRI could be performed after PSA and DRE, could potentially alter the composite formulas since the formulas are currently modeled based on biases inherent in the patient population characterized by elevated PSA or palpable nodules on DRE. As the purpose of the study was to validate the formulas, the application benefit will require analyses of cost, which were outside the scope of this study due to the nature of our institution.
Another limitation of this study is that MRI negative patients were not included in this analysis because they did not undergo biopsy, representing approximately 10–15% of referred patients.3 Patients with very high-risk MRI suggestive of advanced disease (i.e. large lesions with evidence of both extra-prostatic extension and seminal vesicle invasion) were excluded as well, because these individuals represented patients warranting immediate evaluation.
It is reasonable to consider that B-MRI could improve over time. B-MRI allows for quantitative characterization of prostate findings, such as the ADC derived from DWI. Previous studies have shown that the ADC negatively correlates with Gleason score found on biopsy of peripheral zone lesions.22,23 Recent work by De Cobelli et al similarly found decreasing ADC values (at low and high b values) represented a strong risk factor, independent from biopsy features, for harboring poorly differentiated PCa.23 Therefore, incorporating ADC values into the composite equations may further improve the value of B-MRI.
CONCLUSION
Our findings confirm the value of B-MRI in PCa detection in biopsy-naive men. B-MRI represents a more limited, though potentially more time and cost efficient imaging study that may improve PCa detection in men who present with clinical suspicion of cancer. Future work with B-MRI must be directed toward maintaining the high diagnostic yield of MP-MRI without compromising cancer detection and oncologic outcomes. The use of MRI prior to biopsy may limit the risk of over-biopsy, reduce rates of overdetection and excess treatment, and subsequently cut costs to society by decreasing associated treatment morbidities. This work supports an optimized, efficient, limited noncontrast MRI as a potential adjunct tool for PCa detection. As imaging techniques and technology continue to improve and the use of MRI becomes more ubiquitous, B-MRI application may become more useful moving forward in screening for PCa.
Supplementary Material
Acknowledgments.
This research was supported by the Intramural Research Program of the NIH, National Cancer Institute, Center for Cancer Research, and the NIH Center for Interventional Oncology. This research was also made possible by the National Institutes of Health (NIH) Medical Research Scholars Program, a public-private partnership supported jointly by the NIH and generous contributions to the Foundation for the NIH from Pfizer Inc., The Doris Duke Charitable Foundation, The Newport Foundation, The American Association for Dental Research, The Howard Hughes Medical Institute, and the Colgate-Palmolive Company, as well as other private donors. For a complete list, please visit the Foundation website at: http://fnih.org/.
Financial Disclosure:
Dr. Pinto reports a patent (US 8447384B2) issued for which he receives no royalties. Dr. Wood reports NIH and Philips have a Cooperative Research Development Agreement (CRADA) resulting in intellectual property in the field; no royalties are received as a result of the CRADA. The remaining authors declare that they have no relevant financial interests.
References
- 1.Cohn JA, Wang CE, Lakeman JC, et al. Primary care physician PSA screening practices before and after the final U.S. Preventive Services Task Force recommendation. Urol Oncol. 2014;32:41. e23–41.e30. [DOI] [PubMed] [Google Scholar]
- 2.Siegel RL, Miller KD, Jemal A. Cancer statistics, 2015. CA Cancer J Clin. 2015;65:5–29. [DOI] [PubMed] [Google Scholar]
- 3.Siddiqui MM, Rais-Bahrami S, Turkbey B, et al. Comparison of MR/ultrasound fusion–guided biopsy with ultrasound-guided biopsy for the diagnosis of prostate cancer. JAMA. 2015;313:390–397. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.George AK, Pinto PA, Rais-Bahrami S. Multiparametric MRI in the PSA Screening Era. Biomed Res Int. 2014;doi: 10.1155/2014/465816. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Rais-Bahrami S, Siddiqui MM, Turkbey B, et al. Utility of multiparametric magnetic resonance imaging suspicion levels for detecting prostate cancer. J Urol. 2013;190:1721–1727. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Turkbey B, Mani H, Shah V, et al. Multiparametric 3T prostate magnetic resonance imaging to detect cancer: histopathological correlation using prostatectomy specimens processed in customized magnetic resonance imaging based molds. J Urol. 2011;186:1818–1824. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Le JD, Stephenson S, Brugger M, et al. Magnetic resonance imaging-ultrasound fusion biopsy for prediction of final prostate pathology. J Urol. 2014;192:1367–1373. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Rastinehad AR, Turkbey B, Salami SS, et al. Improving detection of clinically significant prostate cancer: magnetic resonance imaging/transrectal ultrasound fusion guided prostate biopsy. J Urol. 2014;191:1749–1754. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Walton Diaz A, Shakir NA, George AK, et al. Use of serial multiparametric magnetic resonance imaging in the management of patients with prostate cancer on active surveillance. Urol Oncol. 2015;33:202. e1–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Raskolnikov D, George AK, Rais-Bahrami S, et al. Multiparametric magnetic resonance imaging and image-guided biopsy to detect seminal vesicle invasion by prostate cancer. J Endourol. 2014;28:1283–1289. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Raskolnikov D, George AK, Rais-Bahrami S, et al. The role of magnetic resonance image-guided prostate biopsy in stratifying men for risk of extracapsular extension at radical prostatectomy. J Urol. 2015;194:105–111. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Rais-Bahrami S, Siddiqui MM, Vourganti S, et al. Diagnostic value of biparametric magnetic resonance imaging (MRI) as an adjunct to prostate-specific antigen (PSA)-based detection of prostate cancer in men without prior biopsies. BJU Int. 2015;115:381–388. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Pinto PA, Chung PH, Rastinehad AR, et al. Magnetic resonance imaging/ultrasound fusion guided prostate biopsy improves cancer detection following transrectal ultrasound biopsy and correlates with multiparametric magnetic resonance imaging. J Urol. 2011;186:1281–1285. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Hong CW, Rais-Bahrami S, Walton-Diaz A, et al. Comparison of magnetic resonance imaging and ultrasound (MRI-US) fusion-guided prostate biopsies obtained from axial and sagittal approaches. BJU Int. 2015;115:772–779. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Turkbey B, Mani H, Aras O, et al. Prostate cancer: can multiparametric MR imaging help identify patients who are candidates for active surveillance? Radiology. 2013;268:144–152. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Abd-Alazeez M, Kirkham A, Ahmed HU, et al. Performance of multiparametric MRI in men at risk of prostate cancer before the first biopsy: a paired validating cohort study using template prostate mapping biopsies as the reference standard. Prostate Cancer Prostatic Dis. 2014;17:40–46. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Peltier A, Aoun F, Lemort M, Kwizera F, Paesmans M, Van Velthoven R. MRI-targeted biopsies versus systematic transrectal ultrasound guided biopsies for the diagnosis of localized prostate cancer in biopsy naïve men. Biomed Res Int. 2015;doi: 10.1155/2015/571708. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Quentin M, Blondin D, Arsov C, et al. Prospective evaluation of magnetic resonance imaging guided in-bore prostate biopsy versus systematic transrectal ultrasound guided prostate biopsy in biopsy naïve men with elevated prostate specific antigen. J Urol. 2014;192:1374–1379. [DOI] [PubMed] [Google Scholar]
- 19.Logan JK, Rais-Bahrami S, Turkbey B, et al. Current status of magnetic resonance imaging (MRI) and ultrasonography fusion software platforms for guidance of prostate biopsies. BJU Int. 2014;114:641–652. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Fakhran S, Alhilali L, Kale H, Kanal E. Assessment of rates of acute adverse reactions to gadobenate dimeglumine: review of more than 130,000 administrations in 7.5 years. AJR Am J Roentgenol. 2015;204:703–706. [DOI] [PubMed] [Google Scholar]
- 21.Aran S, Shaqdan KW, Abujudeh HH. Adverse allergic reactions to linear ionic gadolinium-based contrast agents: experience with 194,400 injections. Clin Radiol. 2015;70:466–476. [DOI] [PubMed] [Google Scholar]
- 22.Turkbey B, Shah VP, Pang Y, et al. Is apparent diffusion coefficient associated with clinical risk scores for prostate cancers that are visible on 3-T MR images? Radiology. 2011;258:488–495. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.De Cobelli F, Ravelli S, Esposito A, et al. Apparent diffusion coefficient value and ratio as noninvasive potential biomarkers to predict prostate cancer grading: comparison with prostate biopsy and radical prostatectomy specimen. AJR Am J Roentgenol. 2015;204:550–557. [DOI] [PubMed] [Google Scholar]
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