Multi-parametric MRI imaging of the prostate—implications for focal therapy
Review Article

Multi-parametric MRI imaging of the prostate—implications for focal therapy

James S. Wysock, Herbert Lepor

Department of Urology, NYU Langone Medical Center, New York University School of Medicine, New York, NY, USA

Contributions: (I) Conception and design: All authors; (II) Administrative support: None; (III) Provision of study materials or patients: None; (IV) Collection and assembly of data: None; (V) Data analysis and interpretation: None; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

Correspondence to: James S. Wysock, MD, MS. Assistant Professor of Urology, Department of Urology, NYU Langone Medical Center, New York University School of Medicine, New York, NY 10016, USA. Email: james.wysock@nyumc.org.

Abstract: The primary goal of a focal therapy treatment paradigm is to achieve cancer control through targeted tissue destruction while simultaneously limiting deleterious effects on peri-prostatic structures. Focal therapy approaches are employed in several oncologic treatment protocols, and have been shown to provide equivalent cancer control for malignancies such as breast cancer and renal cell carcinoma. Efforts to develop a focal therapy approach for prostate cancer have been challenged by several concepts including the multifocal nature of the disease and limited capability of prostate ultrasound and systematic biopsy to reliably localize the site(s) and aggressiveness of disease. Multi-parametric MRI (mpMRI) of the prostate has significantly improved disease localization, spatial demarcation and risk stratification of cancer detected within the prostate. The accuracy of this imaging modality has further enabled the urologist to improve biopsy approaches using targeted biopsy via MRI-ultrasound fusion. From this foundation, an improved delineation of the location of disease has become possible, providing a critical foundation to the development of a focal therapy strategy. This chapter reviews the accuracy of mpMRI for detection of “aggressive“ disease, the accuracy of mpMRI in determining the tumor volume, and the ability of mpMRI to accurately identify the index lesion. While mpMRI provides a critical, first step in developing a strategy for focal therapy, considerable questions remain regarding the relationship between MR identified tumor volume and pathologic tumor volume, the accuracy and utility of mpMRI for treatment surveillance and the optimal role and timing of follow-up mpMRI.

Keywords: Focal therapy; prostate cancer; multi-parametric MRI (mpMRI); index lesion


Submitted Mar 15, 2017. Accepted for publication Apr 16, 2017.

doi: 10.21037/tau.2017.04.29


Introduction

Focal therapy for prostate cancer aims to address many of the critical limitations surrounding prostate cancer management. Many of these issues stem from the overtreatment of low-volume, low-grade disease by whole gland treatment and its subsequent impact on urinary continence and erectile function. One response to the overtreatment of low risk disease has been an increasing role for active surveillance (AS). While, AS aims to carefully select men who can consider deferring or avoiding active treatment, currently no formal selection criteria and follow up protocols exist. Furthermore, the results of the ProtecT trial indicate that almost 60% of men randomized to AS ultimately pursue active treatment. In addition, significantly more men randomized to AS experienced disease progression compared to those on active treatment (1). This is not surprising since over 50% of men with low risk disease based on SB harbor aggressive disease in radical prostatectomy surgical specimens (2). Accurate risk stratification is critical to selection for AS and employing mpMRI along with MR-US fusion biopsy has been shown to improve risk stratification (3,4). With increased utilization of mpMRI, men identified with MR visible disease that may qualify for focal therapy will likely increase.

Interest and utilization of focal treatment of clinically localized prostate cancer has increased. Multiple ablative technologies have been employed for focal therapy, including cryotherapy, high-intensity focused ultrasound (HIFU), electroporation, radiofrequency ablation, laser ablation and photodynamic therapy (5-15). Accurate disease risk stratification, precise tumor spatial localization and a reliable non-invasive, imaging-based treatment assessment are fundamental requirements to successful prostate cancer focal therapy.

Transrectal ultrasound (TRUS) imaging revolutionized prostate cancer (PCa) evaluation, diagnosis and monitoring by allowing the boundaries of the gland to be accurately demarcated and provided the foundation for systematic biopsies (16-21). However, TRUS imaging remains hindered by inadequate sensitivity and specificity for identifying precise tumor location, resulting in subpar negative predictive value and pathologic undergrading (22-25). These drawbacks have limited focal therapy approaches based solely on this imaging modality.

Multi-parametric MRI (mpMRI) vastly improves upon ultrasound prostate imaging by combining several MR sequences to improve tissue evaluation and differentiation, leading to improved cancer detection and tumor localization within the prostate (26-28). Utilizing software assistance, MRI image visible lesions can then be accurately sampled using targeted MR-US fusion techniques (29-32).

The inclusion of mpMRI in prostate cancer evaluation offers an imaging foundation that begins to address the critical challenges facing focal therapy strategies (33). This chapter reviews existing data supporting the role of mpMRI in providing information on the location and extent of disease within the prostate gland and the subsequent implications for identifying appropriate candidates for focal therapy and guiding the delivery of ablative energy to the treatment.


Multi-parametric MRI for prostate cancer disease detection and tumor volume

Imaging of the prostate using MRI has evolved from initial studies assessing the pelvis for staging purposes to dynamic, multi-parametric sequences aimed at characterizing disease within the gland itself (34). As mpMRI gains an increasing role as a triage test for disease detection it has been shown to be a useful tool for identifying men that may need a biopsy of the prostate (30,32,35). However, the ability of mpMRI to accurately identify and characterize disease depends upon size, location and aggressiveness of the cancer.

Disease detection on mpMRI

In a systematic review of data available in 2006, Kirkham et al. reported disease detection rates using early MRI referenced to disease detected whole mount pathology (36). This review reported on studies using unenhanced T2 weighted imaging (T2WI) with endorectal or pelvic phased array coils on 1.5T magnets and reported a sensitivity ranging from 37% to 96% and a specificity ranging from 21% to 67%. The authors concede that disease detection using T2WI alone can be confounded by hyperplasia, prostatitis, hemorrhage (post-biopsy) and the considerable signal heterogeneity of the transition zone (TZ). The accuracy of disease detection improved through addition of dynamic contrast enhancement (DCE). For example, in 1997, Jager et al. reported an increase in sensitivity from 57% to 73% and a specificity of 80% with the inclusion of DCE (37). In 2004, Schlemmer et al. reported an improvement in sensitivity for peripheral zone (PZ) tumor detection from 79% to 89% by combining T2 and DCE imaging (38). Emerging data suggested that 3T MRI as well as diffusion weighted imaging (DWI) would further impact imaging capabilities (39-42).

Diffusion weighted imaging (DWI) was initially used in neurologic imaging and evaluates the Brownian motion of protons (43). Restriction in this random motion correlates with increased cellular density associated with neoplasm (44-46). Jie et al. presented results of a meta-analysis of DWI on prostate cancer detection (47). They analyzed 21 studies and reported a sensitivity and specificity of 0.62 (95% CI: 0.61–0.64) and 0.90 (95% CI: 0.89–0.90) respectively.

In addition, Tan et al. performed a meta-analysis of the detection of prostate cancer with DCE (48). They demonstrated that the combination of DCE, DWI and T2WI provided the most accurate imaging on area under the curve (AUC) analysis. They also noted that DWI alone provided superior performance than DCE.

Recently, Hamoen et al. reported the results of a meta-analysis of T2WI combined with DCE and DWI on detection of prostate cancer using prostatectomy or biopsy as the reference standard (49). Of the 7 studies involving 526 men, 4 used 1.5T magnets with pelvic phased array coil of which 2 utilized an endorectal coil, 2 utilized 1.5T and torso phased array coil and 1 utilized 3T. The authors report sensitivity and specificity of 74% and 88% respectively.

More recently, Fütterer et al. systematically reviewed the accuracy of mpMRI for identifying clinically significant disease including T2WI plus at least two functional sequences (DWI, DCE or MRSI) using prostate biopsy or radical prostatectomy specimens as reference standards (28). This review primarily analyzed studies using mpMRI employing 3T with pelvic phased array coils and reported a detection rate of clinically significant disease ranging from 44% to 87% and a negative predictive value of 63% to 98%. In addition, Thompson et al. reported disease detection in a prospective cohort of 150 men undergoing mpMRI followed by transperineal 30 core prostate biopsy with additional MR-US fusion biopsies or cognitive targeted biopsies obtained from MRI findings when deemed to be outside of the 30 core template (50). This study reported a positive predictive value ranging from 43% to 57% and negative predictive value of 92% to 96% depending on the definition of “clinically significant” disease.

Defining the absence of disease—the negative predictive value of mpMRI

MRI lesions identified on mpMRI are associated with varying probabilities of harboring disease based on imaging characteristics derived from the T2WI, contrast enhancement and diffusion weighted imaging sequences. While lesions noted on mpMRI with high suspicion often represent clinically significant cancer, the lack of high suspicion lesions carries importance for focal therapy strategies as a marker for absence of disease. A high negative predictive value (NPV) for significant cancer has the potential to rule-out significant disease and provides further confidence in treatment of only the disease identified on mpMRI.

The NPV for prostate mpMRI has been reported in a number of studies. Puech et al. reported a NPV of 85% for foci greater than 0.2 cm3 and a NPV of 95% for foci greater than 0.5 cm3 on radical prostatectomy specimens in 24 men with suspicious areas detected by pre-biopsy MRI (51).

Squillaci et al. reported cancer detection rates amongst 65 men undergoing mpMRI with spectroscopy (52). This study reported a NPV for overall cancer detection of T2W-MRI alone, MRSI alone, and combined mpMRI with MRSI as 77%, 78%, and 74%, respectively. Manenti et al. also reported NPV for T2W-MRI, MRSI, and mpMRI with MRSI on 39 men of 77%, 74%, and 74%, respectively (53).

Girometti et al. reported a NPV of 100% for a series of 8 men with prior negative biopsy using DWI in addition to T2WI and MRSI prior to biopsy (54). Pokorny et al. reported an NPV in 69% of men with a negative mpMRI prior to biopsy (31). Of those with cancer on biopsy, 90% had either low volume Gleason 3+3 or very low Gleason 3+4. In this study, the NPV for high risk disease was 94%.

Itatani et al. reported 5-year outcomes of men with initial negative mpMRI. This study demonstrated an NPV on initial TRUS-guided biopsy of 87%, with only 15% and 10% of men found to have any cancer and clinically significant cancer, respectively, on biopsy or radical prostatectomy within the 5-year period following MRI (55).

Finally, Wysock et al. reported an NPV of 91.7% and 97.9% for all cancers and Gleason ≥7 on men undergoing systematic 12-corebiopsy without a prior diagnosis of prostate cancer (56).

While these studies demonstrate a reliable NPV for prostate cancer, they remain small single series and lack consistency in the reference test utilized to confirm absence of disease. In fact, most of the studies rely upon biopsy data to serve as the reference standard which inflates the NPV. Additional follow-up data or prostatectomy data is needed to further strengthen reliability of the negative MRI results.

PROMIS

The PROMIS trial provides the highest level (Level 1b) of evidence at this time to address the accuracy of mpMRI for diagnosing prostate cancer (35). Ahmed et al. prospectively evaluated 576 men at risk for prostate cancer at 11 centers using a 1.5T mpMRI who underwent 5 mm transperineal template mapping biopsy and transrectal ultrasound guided standard 10–12 core biopsy. The study demonstrated a sensitivity for clinically significant cancer (Gleason dominant pattern 4 or greater) of 93% (95% CI: 88–96%) and a specificity of 41% (95% CI: 36–46%). One criticism of the study is that many Gleason 3+4 disease would merit at least consideration for focal or whole gland treatment. A strength of the study is that many of the 11 sites were not centers with high-level of experience with prostate MRI performance or interpretation, strengthening the external validity of these results.

Prostate imaging reporting and data system (PI-RADS)

Due to the growing utilization of mpMRI, efforts to improve reporting standards led to the development of the PI-RADS (57). The PI-RADS system initially included T2WI, DWI, DCE and MR spectroscopy.

Hamoen et al. performed a meta-analysis of studies employing PI-RADS version 1 for prostate cancer diagnosis (49). This meta-analysis reviewed 14 studies, including 1,785 patients and using a variety of reference tests. Of the studies reviewed, 13 used biopsies as the reference standard and one used prostatectomy specimens. The authors reported sensitivity, specificity, negative predictive value, and value for cancer detection of 0.78 (95% CI: 0.70–0.84), 0.79 (95% CI: 0.68–0.86), 0.58–0.95 respectively. Of note, when these studies were analyzed for detection of only clinically significant cancer, the sensitivity increased to 0.84 (95% CI: 0.76–0.89) and specificity decreased to 0.75 (95% CI: 0.66–0.83). This meta-analysis reports an improvement in sensitivity from the meta-analysis on studies prior to publication of PI-RADS (49). However, only one study (58) utilized whole mount pathology as the reference standard, limiting the accuracy due to the potential of false-negative results based upon missed biopsies.

The PI-RADS system has recently been revised in order to further improve standardization of mpMRI interpretation and reporting by defining lesion scoring based upon sequence and prostate zonal anatomy (59). The revised PI-RADS version 2 redefines the analysis of DCE imaging, standardizes the 5 point scoring scale and removes spectroscopy. Future studies reporting on the results of PI-RADS version 2 will further define the accuracy for disease detection. It is also important to note that the PI-RADS system only applies to treatment naïve patients and thus does not apply for interpretation following therapy.

Disease detection summary

Overall, disease detection using mpMRI has significantly improved over the last 10 years. While these studies support an improvement in disease detection using mpMRI, they remain limited by lack of strict adherence to a common gold standard reference test. Using a gold standard reference of SB underestimates sensitivity and negative predictive value. Using a radical prostatectomy standard based on mpMRI coupled with MRFTB + SB detection is limited due to selection bias since the negative predictive value and sensitivity of the overall detection pathway is assumed to be 100%. Transperineal mapping biopsy is highly correlated with radical prostatectomy specimens and represents a preferred gold standard reference since it minimizes selection bias and maximizes disease detection. The results of the PROMIS trial address this criticism by providing a transperineal template mapping biopsy as the reference standard. Overall, these results serve as a strong argument for inclusion of mpMRI in the diagnostic paradigm for prostate cancer.

Currently, the reported specificity for clinically significant disease remains in the range of 50% (35). Given this level of specificity, precise disease localization requires biopsy confirmation. Further studies are necessary to define the optimal biopsy strategy to evaluate the findings on mpMRI. The ideal biopsy approach should serve to address not only confirmation of disease presence, but also accurately assess the boundaries of disease. An important converse to this concept, however, lies in the negative predictive value of mpMRI. Given that multiple studies demonstrate negative predictive values of 90% or greater, the role of biopsy to these negative regions requires further evaluation. From the perspective of focal therapy planning, confidence in the absence of disease within imaging negative regions is tantamount.

In summary, from the perspective of focal therapy, mpMRI is essential as an imaging study to identify men as candidates for focal therapy. Further confirmation with targeted biopsy is necessary for disease confirmation and also provides limited information on disease mapping. Current mpMRI technology can provide this necessary foundation for focal therapy and is recommended for selecting patients for this treatment option (59-61).


Tumor volume

The second critical requirement of focal therapy is to provide ablation energy to a volume of tissue that encompasses the tumor. Focal therapy strategies will rely upon these disease volume estimates in order to provide treatment margins. The ability of mpMRI to provide an accurate delineation of tumor volume is thus critical. However, the accuracy of mpMRI to estimate tumor volume remains to be clearly defined. Table 1 summarizes studies reporting on tumor volume.

Table 1
Table 1 Summary of studies evaluating MR tumor volume compared to histologic tumor volume
Full table

In their 2006 review, Kirkham et al. summarized existing whole mount analysis of MR tumor volume (MRTV) and histologic tumor volume (HTV) (36). Tumor volume estimation improved with tumor size, however, they noted volume discrepancies of ~50% for tumor volume of 5 mL (62). Early estimations of tumor volume based on unenhanced T2 imaging was noted to be approximately 40% of HTV; these estimations appeared to improve slightly with DCE (63-66,75-77).

Lemaitre et al. compared morphologic features on mpMRI with whole-mount radical prostatectomy specimens for anterior prostate tumors in 27 specimens (67). These authors noted ill-defined tumor margins on T2W imaging in 89% and a median volume of 1.01 cc on MRI vs. 2.84 cc on histopathology. They also reported an underestimation of MRTV up to 40%.

Turkbey et al. further compared MRTV measurements to HTV in 135 index tumors on whole-mount pathology (68). These authors reported a MRTV of 2.02 cm3 while mean HTV was 2.18 cm3, correcting for shrinkage.

More recent studies have corroborated these findings. Baco et al. compared MRTV and HTV on 135 prostatectomy specimens (69). They demonstrated that mpMRI underestimated the HTV by approximately 5% (95% CI, −6–8%). Radtke et al. reported MRTV underestimated HTV by 0.4 mL (36%), which decreased to 20% (0.3 mL) when reevaluated applying shrinkage factor (70). Rud et al. reported MRTV was significantly smaller than HTV in 199 radical prostatectomy specimens (71). These authors noted that MRTV underestimated HTV (mean MRTV Index Tumor 2.8 mL vs. HTV Index Tumor 4.0 mL). For tumors <0.5 mL, mean MRTV was found to be 0.1 mL while mean HTV was 2.8 mL larger than MRTV for tumor >0.5 mL.

Le Nobin et al. compared MRTV to HTV on 46 histologically confirmed cancers on 33 radical prostatectomy specimens and reported an MRTV underestimated by 18.5%, with underestimation increasing as lesion suspicion score increased and Gleason score increased above 6. A 9 mm treatment margin was recommended in order to achieve complete HTV destruction in 100% of lesions (72).

Cornud et al. compared MRTV and HTV in 84 prostatectomy specimens and noted that tumor volume measured on T2W imaging and DWI correlated significantly with HTV (73). These authors noted that MRTV on DWI appeared to provide the best approximation of HTV, however volume underestimation was noted in 49% of cases. Furthermore, these authors attempted to provide a deliberate overestimation of tumor volume by using the largest tumor area on any sequence along with the number of slices demonstrating tumor. Using this technique, they reported an underestimation rate of 17%.

Utilizing customized tumor molds made from preoperative mpMRI T2 imaging, Priester et al. noted a mean volume of 0.8 cc for tumors on mpMRI and a subsequent tumor volume of 2.5 cc on whole mount pathology (74). Volume was best estimated in the axial view. These authors conclude that mpMRI may underestimate tumor volume by one third and that the mean diameter is approximately 11 mm greater on pathology than on T2 weighted imaging.

Ultimately, current data supports a systematic underestimation of HTV on mpMRI. In order to ensure adequate treatment margins, focal therapy treatment volumes must take this into consideration. At this time, focal therapy treatment zones utilizing a margin of approximately 9 to 10 mm, as proposed by Le Nobin et al., appears reasonable as an initial estimate. Additional tumor mapping studies should serve to improve these estimations.


Utilization of mpMRI in treatment follow-up

Optimal strategies for focal therapy follow up remain to be defined. Utilizing mpMRI may offer a non-invasive method for estimating treatment success and post-treatment surveillance. However, the data to support this use is limited. The ideal timing of follow-up imaging also remains to be determined.

Follow up imaging approximately 2–3 weeks after focal treatment offers an opportunity to assess accuracy of ablation targeting. However, these results may only allow for identification of gross targeting as early post-treatment imaging results have failed to predict biopsy outcomes at 6 months post-ablation (78). The ability of early follow-up MRI to assess gross targeting may be useful during the initial adoption of an ablative treatment. Surveillance mpMRI using contrast enhancement assesses enhancement or viable tissue within or around the treatment site. Targeted biopsies using MRI-US fusion to regions of enhancement following ablation have been shown to improve detection of residual disease over non-targeted biopsies (79).

At this time, a clear post-ablation treatment protocol has yet to be defined in order to define oncological control. However, mpMRI is recommended for both treatment planning as well as follow up evaluation. One consensus panel has recommended post-treatment imaging with mpMRI at 6 months following treatment (59). The indications for biopsy of the ablation zone also remain highly controversial.


Defining the index lesion

Imaging basis of “index lesion”

The hypothesis of the “index lesion” represents the critical oncologic challenge to the focal therapy paradigm. Assuming the veracity of the biologic basis for the “index lesion”, the ability to accurately locate and characterize this tumor focus remains a crucial component of a successful focal therapy strategy. Localized treatment thus requires precise mapping of the contours (80) and extent of this index tumor focus.

Transrectal ultrasound (TRUS) imaging revolutionized prostate cancer evaluation, diagnosis and monitoring by allowing the boundaries of the gland to be accurately demarcated and provided the footprint for systematic mapping biopsies (16-21). Since prostate cancer is multi-focal in 75% of radical prostatectomy specimens, successful focal therapy strategies mandate that a single tumor drives the biology of the disease. The concept of an “index” tumor that represented the primary malignant source was typically identified as the largest tumor visible by ultrasound (16,81,82). However, current TRUS imaging remains hindered by well-described limitations in the ability to identify and map disease (22-25). Consequently, defining an accurate index lesion using TRUS has remained elusive.

Recent evidence supports the ability of mpMRI to accurately localize the index tumor.

Rosenkrantz et al. retrospectively evaluated mpMRI of 51 men who underwent prostatectomy and identified an index lesion in 49 (96%). They reported a sensitivity of 74.8% for identification of the index lesion for Gleason >6 and 80.3% for lesions greater than 1 cm (83). A second analysis by Rosenkrantz et al. demonstrated improved sensitivity for index lesion detection using DWI, correlation between tumor diameter on ADC map with radical prostatectomy specimen, and greater sensitivity for higher Gleason scores on both DWI and ADC maps ranging from 80–100% (84). An evaluation by Reisaeter et al. reported similar findings, and further demonstrated decreased sensitivity and specificity for index tumor localization within the transition zone (85).

Delongchamps et al. evaluated prostatectomy surgical specimens from 125 consecutive men with preoperative mpMRI imaging available and identified 151 suspicious zones and 230 individual tumor foci. MRI-US fusion targeted biopsy demonstrated cancer in 126 (83%) of the mpMRI identified lesions. A total of 95 tumor foci were invisible on mpMRI, and 14 (15%) of these were significant disease. However, 13 of these 14 (93%) were secondary foci within gland where an index tumor was visible on mpMRI and detected on targeted biopsy. Furthermore, all Gleason >6 tumors not identified on mpMRI were Gleason 3+4 with less than 20% pattern 4 and 8, (57%) were less than 0.5 cm3 in volume. Multivariate analysis of mpMRI target characteristics demonstrated that only PI-RADS score was associated with significant tumor foci. Interestingly, the size of mpMRI correlated with tumor volume and not Gleason score (86).

Le et al. evaluated 122 consecutive men undergoing radical prostatectomy with presurgical mpMRI imaging available. On whole mount evaluation, mpMRI identified 98 (80%) of index tumors and performed well for identifying higher grade and larger tumors (72% sensitivity, 75% positive predictive value) for Gleason >6 and diameter >1 cm. On multivariate analysis, index tumor status and lesion size were the strongest predictors of tumor detection. Multifocal disease was noted in 78 (64%) men and this did not significantly impact detection of the index tumor (86% in solitary tumors and 77% in multifocal tumors). Index tumor on mpMRI corresponded to highest grade tumor in 86% of cases, 20% of men had Gleason >6 non-index tumors, of which 15% were missed on mpMRI (87).

Baco et al. demonstrated a 95% concordance between the sites of mpMRI index lesion and histopathological index tumor on 135 prostatectomy specimens (69). Furthermore, they demonstrated that for all MR visible disease, MR-US targeted cancer location correlated with location of the index tumor on prostatectomy. Of seven MR invisible index tumors, 4 (3%) demonstrated any Gleason pattern 4 and only 1 (1%) demonstrated primary Gleason pattern 4.

Radtke et al. evaluated a cohort of 120 men undergoing transperineal fusion biopsy and 24 core systematic transperineal biopsy followed by radical prostatectomy. MRI detected 110 (92%) of index lesions, of which 89% harbored significant disease, and missed 86% of insignificant non-index lesions. Missed lesions demonstrated a median tumor volume of 0.6 cm3 and 56% were Gleason 3+4 (75% of which harbored <11% Gleason pattern 4) (88).

Rud et al. evaluated 199 men undergoing radical prostatectomy with mpMRI imaging prior to surgery. Imaging detected the histologic index tumor in 92%.

While the index lesion hypothesis remains under investigation, the ability of mpMRI to accurately identify the index tumor ranges widely and appears to improve with the size and Gleason score of the tumor. From the perspective of focal therapy planning, these findings suggest that mpMRI reliably identifies the highest oncologic risk disease and thus allows for confirmation using targeted biopsy. Based upon the results of targeted biopsy, the presence and location of an index lesion can be determined, allowing for index lesion based treatment strategies. The high negative predictive value of mpMRI for significant disease is also important in order to ensure clinically significant cancers are not left untreated.


Conclusions

The ability of mpMRI to reliably identify clinically significant disease has enabled selection of candidates for focal therapy. Focal therapy success relies upon accurate tumor localization, tumor boundary definition, effective ablation targeting with adequate margin control and accurate follow-up protocols to assess oncological control. The current data reviewed above illustrate the capability of mpMRI to provide information valuable for each of these requirements. The use of mpMRI thus sets the necessary foundation to begin exploring focal therapy strategies. Future studies will serve to strengthen these data and provide further definition on the exact role of this imaging in disease management.


Acknowledgements

None.


Footnote

Conflicts of Interest: The authors have no conflicts of interest to declare.


References

  1. Hamdy FC, Donovan JL, Lane JA, et al. 10-Year outcomes after monitoring, surgery, or radiotherapy for localized prostate cancer. N Engl J Med 2016;375:1415-24. [Crossref] [PubMed]
  2. Mufarrij P, Sankin A, Godoy G, et al. Pathologic outcomes of candidates for active surveillance undergoing radical prostatectomy. Urology 2010;76:689-92. [Crossref] [PubMed]
  3. Van Den Bergh RC, Ahmed HU, Bangma CH, et al. Novel tools to improve patient selection and monitoring on active surveillance for low-risk prostate cancer: a systematic review. Eur Urol 2014;65:1023-31. [Crossref] [PubMed]
  4. Bjurlin MA, Meng X, Le Nobin J, et al. Optimization of prostate biopsy: the role of magnetic resonance imaging targeted biopsy in detection, localization and risk assessment. J Urol 2014;192:648-58. [Crossref] [PubMed]
  5. Tsivian M, Polascik TJ. Focal cryotherapy for prostate cancer. Curr Urol Rep 2010;11:147-51. [Crossref] [PubMed]
  6. Cordeiro ER, Cathelineau X, Thüroff S, et al. High-intensity focused ultrasound (HIFU) for definitive treatment of prostate cancer. BJU Int 2012;110:1228-42. [Crossref] [PubMed]
  7. Oto A, Sethi I, Karczmar G, et al. Mr imaging-guided focal laser ablation for prostate cancer: phase I trial. Radiology 2013;267:932-40. [Crossref] [PubMed]
  8. Eggener SE, Yousuf A, Watson S, et al. Phase II evaluation of magnetic resonance imaging guided focal laser ablation of prostate cancer. J Urol 2016;196:1670-5. [Crossref] [PubMed]
  9. Jones TA, Natarajan S, Priester AM, et al. Focal Laser Ablation of Prostate Cancer. Urology 2017;99:e21-e22. [Crossref] [PubMed]
  10. Lepor H, Llukani E, Sperling D, et al. Complications, recovery, and early functional outcomes and oncologic control following in-bore focal laser ablation of prostate cancer. Eur Urol 2015;68:924-6. [Crossref] [PubMed]
  11. Jarow JP, Ahmed HU, Choyke PL, et al. Partial Gland Ablation for Prostate Cancer: Report of a Food and Drug Administration, American Urological Association, and Society of Urologic Oncology Public Workshop. Urology 2016;88:8-13. [Crossref] [PubMed]
  12. Valerio M, Stricker PD, Ahmed HU, et al. Initial assessment of safety and clinical feasibility of irreversible electroporation in the focal treatment of prostate cancer. Prostate Cancer Prostatic Dis 2014;17:343-7. [Crossref] [PubMed]
  13. Onik G, Mikus P, Rubinsky B. Irreversible electroporation: implications for prostate ablation. Technol Cancer Res Treat 2007;6:295-300. [Crossref] [PubMed]
  14. Taneja SS, Bennett J, Coleman J, et al. Final results of a phase I/II multicenter trial of WST11 vascular targeted photodynamic therapy for Hemi-Ablation of the prostate in men with unilateral low risk prostate cancer performed in the United States. J Urol 2016;196:1096-104. [Crossref] [PubMed]
  15. Moore CM, Emberton M, Bown SG. Photodynamic therapy for prostate cancer--an emerging approach for organ-confined disease. Lasers Surg Med 2011;43:768-75. [Crossref] [PubMed]
  16. Lee F, Torp-Pedersen ST, Siders DB, et al. Transrectal ultrasound in the diagnosis and staging of prostatic carcinoma. Radiology 1989;170:609-15. [Crossref] [PubMed]
  17. Scardino PT, Weaver R, Hudson MA. Early detection of prostate cancer. Hum Pathol 1992;23:211-22. [Crossref] [PubMed]
  18. Lee F, Littrup PJ, Torp-Pedersen ST, et al. Prostate cancer: comparison of transrectal US and digital rectal examination for screening. Radiology 1988;168:389-94. [Crossref] [PubMed]
  19. Ohori M, Wheeler TM, Greene DR, et al. Comparison of the pathologic features and DNA ploidy value of prostate cancers detectable by sonography and by palpation. Prostate 1993;23:271-81. [Crossref] [PubMed]
  20. Guinan P, Ray P, Rubenstein M. Prostatic ultrasound in follow-up of prostatic disease. Urology 1988;31:275-8. [Crossref] [PubMed]
  21. Lee F, Gray JM, Mcleary RD, et al. Transrectal ultrasound in the diagnosis of prostate cancer: location, echogenicity, histopathology, and staging. Prostate 1985;7:117-29. [Crossref] [PubMed]
  22. Chun FK, Epstein JI, Ficarra V, et al. Optimizing performance and interpretation of prostate biopsy: a critical analysis of the literature. Eur Urol 2010;58:851-64. [Crossref] [PubMed]
  23. Shariat SF, Roehrborn CG. Using biopsy to detect prostate cancer. Rev Urol 2008;10:262-80. [PubMed]
  24. Onik G, Miessau M, Bostwick DG. Three-dimensional prostate mapping biopsy has a potentially significant impact on prostate cancer management. J Clin Oncol 2009;27:4321-6. [Crossref] [PubMed]
  25. Scattoni V, Zlotta A, Montironi R, et al. Extended and saturation prostatic biopsy in the diagnosis and characterisation of prostate cancer: a critical analysis of the literature. Eur Urol 2007;52:1309-22. [Crossref] [PubMed]
  26. Ahmed HU, Kirkham A, Arya M, et al. Is it time to consider a role for MRI before prostate biopsy? Nat Rev Clin Oncol 2009;6:197-206. [Crossref] [PubMed]
  27. Dickinson L, Ahmed HU, Allen C, et al. Magnetic resonance imaging for the detection, localisation, and characterisation of prostate cancer: recommendations from a European consensus meeting. Eur Urol 2011;59:477-94. [Crossref] [PubMed]
  28. Fütterer JJ, Briganti A, De Visschere P, et al. Can Clinically Significant Prostate Cancer Be Detected with Multiparametric Magnetic Resonance Imaging? A Systematic Review of the Literature. Eur Urol 2015;68:1045-53. [Crossref] [PubMed]
  29. Hambrock T, Hoeks C, Hulsbergen-Van De Kaa C, et al. Prospective assessment of prostate cancer aggressiveness using 3-T diffusion-weighted magnetic resonance imaging-guided biopsies versus a systematic 10-core transrectal ultrasound prostate biopsy cohort. Eur Urol 2012;61:177-84. [Crossref] [PubMed]
  30. 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;313:390-7. [Crossref] [PubMed]
  31. Pokorny MR, De Rooij M, Duncan E, et al. Prospective study of diagnostic accuracy comparing prostate cancer detection by transrectal ultrasound-guided biopsy versus magnetic resonance (Mr) imaging with subsequent MR-guided biopsy in men without previous prostate biopsies. Eur Urol 2014;66:22-9. [Crossref] [PubMed]
  32. Meng X, Rosenkrantz AB, Mendhiratta N, et al. Relationship between prebiopsy multiparametric magnetic resonance imaging (MRI), biopsy indication, and MRI-ultrasound fusion-targeted prostate biopsy outcomes. Eur Urol 2016;69:512-7. [Crossref] [PubMed]
  33. Bass EJ, Ahmed HU. Focal therapy in prostate cancer: A review of seven common controversies. Cancer Treat Rev 2016;51:27-34. [Crossref] [PubMed]
  34. Rifkin MD, Zerhouni EA, Gatsonis CA, et al. Comparison of magnetic resonance imaging and ultrasonography in staging early prostate cancer. Results of a multi-institutional cooperative trial. N Engl J Med 1990;323:621-6. [Crossref] [PubMed]
  35. Ahmed HU, El-Shater Bosaily A, Brown LC, et al. Diagnostic accuracy of multi-parametric MRI and TRUS biopsy in prostate cancer (PROMIS): a paired validating confirmatory study. Lancet 2017;389:815-22. [Crossref] [PubMed]
  36. Kirkham AP, Emberton M, Allen C. How good is MRI at detecting and characterising cancer within the prostate? Eur Urol 2006;50:1163-74; discussion 1175. [Crossref] [PubMed]
  37. Jager GJ, Ruijter ET, Van De Kaa CA, et al. Dynamic TurboFLASH subtraction technique for contrast-enhanced Mr imaging of the prostate: correlation with histopathologic results. Radiology 1997;203:645-52. [Crossref] [PubMed]
  38. Schlemmer HP, Merkle J, Grobholz R, et al. Can pre-operative contrast-enhanced dynamic Mr imaging for prostate cancer predict microvessel density in prostatectomy specimens? Eur Radiol 2004;14:309-17. [Crossref] [PubMed]
  39. Rouvière O, Hartman RP, Lyonnet D. Prostate MR imaging at high-field strength: evolution or revolution? Eur Radiol 2006;16:276-84. [Crossref] [PubMed]
  40. Gibbs P, Tozer DJ, Liney GP, et al. Comparison of quantitative T2 mapping and diffusion-weighted imaging in the normal and pathologic prostate. Magn Reson Med 2001;46:1054-8. [Crossref] [PubMed]
  41. Hosseinzadeh K, Schwarz SD. Endorectal diffusion-weighted imaging in prostate cancer to differentiate malignant and benign peripheral zone tissue. J Magn Reson Imaging 2004;20:654-61. [Crossref] [PubMed]
  42. Sato C, Naganawa S, Nakamura T, et al. Differentiation of noncancerous tissue and cancer lesions by apparent diffusion coefficient values in transition and peripheral zones of the prostate. J Magn Reson Imaging 2005;21:258-62. [Crossref] [PubMed]
  43. Le Bihan D, Breton E, Lallemand D, et al. Mr imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders. Radiology 1986;161:401-7. [Crossref] [PubMed]
  44. Padhani AR, Liu G, Koh DM, et al. Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia 2009;11:102-25. [Crossref] [PubMed]
  45. Zelhof B, Pickles M, Liney G, et al. Correlation of diffusion-weighted magnetic resonance data with cellularity in prostate cancer. BJU Int 2009;103:883-8. [Crossref] [PubMed]
  46. Gibbs P, Liney GP, Pickles MD, et al. Correlation of ADC and T2 measurements with cell density in prostate cancer at 3.0 Tesla. Invest Radiol 2009;44:572-6. [Crossref] [PubMed]
  47. Jie C, Rongbo L, Ping T. The value of diffusion-weighted imaging in the detection of prostate cancer: a meta-analysis. Eur Radiol 2014;24:1929-41. [Crossref] [PubMed]
  48. Tan CH, Hobbs BP, Wei W, et al. Dynamic contrast-enhanced MRI for the detection of prostate cancer: meta-analysis. AJR Am J Roentgenol 2015;204:W439-48. [Crossref] [PubMed]
  49. Hamoen EH, de Rooij M, Witjes JA, et al. Use of the Prostate Imaging Reporting and Data System (PI-RADS) for prostate cancer detection with multiparametric magnetic resonance imaging: a diagnostic meta-analysis. Eur Urol 2015;67:1112-21. [Crossref] [PubMed]
  50. Thompson JE, Moses D, Shnier R, et al. Multiparametric magnetic resonance imaging guided diagnostic biopsy detects significant prostate cancer and could reduce unnecessary biopsies and over detection: a prospective study. J Urol 2014;192:67-74. [Crossref] [PubMed]
  51. Puech P, Potiron E, Lemaitre L, et al. Dynamic contrast-enhanced-magnetic resonance imaging evaluation of intraprostatic prostate cancer: correlation with radical prostatectomy specimens. Urology 2009;74:1094-9. [Crossref] [PubMed]
  52. Squillaci E, Manenti G, Mancino S, et al. MR spectroscopy of prostate cancer. Initial clinical experience. J Exp Clin Cancer Res 2005;24:523-30. [PubMed]
  53. Manenti G, Squillaci E, Carlani M, et al. Magnetic resonance imaging of the prostate with spectroscopic imaging using a surface coil. Initial clinical experience. Radiol Med 2006;111:22-32. [Crossref] [PubMed]
  54. Girometti R, Bazzocchi M, Como G, et al. Negative predictive value for cancer in patients with "gray-zone" PSA level and prior negative biopsy: preliminary results with multiparametric 3.0 Tesla MR. J Magn Reson Imaging 2012;36:943-50. [Crossref] [PubMed]
  55. Itatani R, Namimoto T, Atsuji S, et al. Negative predictive value of multiparametric MRI for prostate cancer detection: outcome of 5-year follow-up in men with negative findings on initial MRI studies. Eur J Radiol 2014;83:1740-5. [Crossref] [PubMed]
  56. Wysock JS, Mendhiratta N, Zattoni F, et al. Predictive value of negative 3T multiparametric magnetic resonance imaging of the prostate on 12-core biopsy results. BJU Int 2016;118:515-20. [Crossref] [PubMed]
  57. Barentsz JO, Richenberg J, Clements R, et al. ESUR prostate Mr guidelines 2012. Eur Radiol 2012;22:746-57. [Crossref] [PubMed]
  58. Rosenkrantz AB, Kim S, Lim RP, et al. Prostate cancer localization using multiparametric Mr imaging: comparison of Prostate Imaging Reporting and Data System (PI-RADS) and Likert scales. Radiology 2013;269:482-92. [Crossref] [PubMed]
  59. Muller BG, Fütterer JJ, Gupta RT, et al. The role of magnetic resonance imaging (MRI) in focal therapy for prostate cancer: recommendations from a consensus panel. BJU Int 2014;113:218-27. [Crossref] [PubMed]
  60. Muller BG, Van Den Bos W, Brausi M, et al. Role of multiparametric magnetic resonance imaging (MRI) in focal therapy for prostate cancer: a Delphi consensus project. BJU Int 2014;114:698-707. [Crossref] [PubMed]
  61. Van Den Bos W, Muller BG, Ahmed H, et al. Focal therapy in prostate cancer: international multidisciplinary consensus on trial design. Eur Urol 2014;65:1078-83. [Crossref] [PubMed]
  62. Kahn T, Bürrig K, Schmitz-Dräger B, et al. Prostatic carcinoma and benign prostatic hyperplasia: Mr imaging with histopathologic correlation. Radiology 1989;173:847-51. [Crossref] [PubMed]
  63. Quint LE, Van Erp JS, Bland PH, et al. Carcinoma of the prostate: Mr images obtained with body coils do not accurately reflect tumor volume. AJR Am J Roentgenol 1991;156:511-6. [Crossref] [PubMed]
  64. Sommer FG, Nghiem HV, Herfkens R, et al. Determining the volume of prostatic carcinoma: value of Mr imaging with an external-array coil. AJR Am J Roentgenol 1993;161:81-6. [Crossref] [PubMed]
  65. Jager GJ, Ruijter ET, Van De Kaa CA, et al. Local staging of prostate cancer with endorectal Mr imaging: correlation with histopathology. AJR Am J Roentgenol 1996;166:845-52. [Crossref] [PubMed]
  66. Nakashima J, Tanimoto A, Imai Y, et al. Endorectal MRI for prediction of tumor site, tumor size, and local extension of prostate cancer. Urology 2004;64:101-5. [Crossref] [PubMed]
  67. Lemaitre L, Puech P, Poncelet E, et al. Dynamic contrast-enhanced MRI of anterior prostate cancer: morphometric assessment and correlation with radical prostatectomy findings. Eur Radiol 2009;19:470-80. [Crossref] [PubMed]
  68. Turkbey B, Mani H, Aras O, et al. Correlation of magnetic resonance imaging tumor volume with histopathology. J Urol 2012;188:1157-63. [Crossref] [PubMed]
  69. Baco E, Ukimura O, Rud E, et al. Magnetic resonance imaging-transectal ultrasound image-fusion biopsies accurately characterize the index tumor: correlation with step-sectioned radical prostatectomy specimens in 135 patients. Eur Urol 2015;67:787-94. [Crossref] [PubMed]
  70. Radtke JP, Schwab C, Wolf MB, et al. Multiparametric magnetic resonance imaging (MRI) and MRI-Transrectal ultrasound fusion biopsy for index tumor detection: correlation with radical prostatectomy specimen. Eur Urol 2016;70:846-53. [Crossref] [PubMed]
  71. Rud E, Klotz D, Rennesund K, et al. Detection of the index tumour and tumour volume in prostate cancer using T2-weighted and diffusion-weighted magnetic resonance imaging (MRI) alone. BJU Int 2014;114:E32-42. [Crossref] [PubMed]
  72. Le Nobin J, Rosenkrantz AB, Villers A, et al. Image Guided Focal Therapy for Magnetic Resonance Imaging Visible Prostate Cancer: Defining a 3-Dimensional Treatment Margin Based on Magnetic Resonance Imaging Histology Co-Registration Analysis. J Urol 2015;194:364-70. [Crossref] [PubMed]
  73. Cornud F, Khoury G, Bouazza N, et al. Tumor target volume for focal therapy of prostate cancer-does multiparametric magnetic resonance imaging allow for a reliable estimation? J Urol 2014;191:1272-9. [Crossref] [PubMed]
  74. Priester A, Natarajan S, Khoshnoodi P, et al. Magnetic resonance imaging underestimation of prostate cancer geometry: use of patient specific molds to correlate images with whole mount pathology. J Urol 2017;197:320-6. [Crossref] [PubMed]
  75. Eichelberger LE, Koch MO, Daggy JK, et al. Predicting tumor volume in radical prostatectomy specimens from patients with prostate cancer. Am J Clin Pathol 2003;120:386-91. [Crossref] [PubMed]
  76. Ponchietti R, Di Loro F, Fanfani A, et al. Estimation of prostate cancer volume by endorectal coil magnetic resonance imaging vs. pathologic volume. Eur Urol 1999;35:32-5. [Crossref] [PubMed]
  77. Lencioni R, Menchi I, Paolicchi A, et al. Prediction of pathological tumor volume in clinically localized prostate cancer: value of endorectal coil magnetic resonance imaging. MAGMA 1997;5:117-21. [Crossref] [PubMed]
  78. Donnelly SE, Donnelly BJ, Saliken JC, et al. Prostate cancer: gadolinium-enhanced Mr imaging at 3 weeks compared with needle biopsy at 6 months after cryoablation. Radiology 2004;232:830-3. [Crossref] [PubMed]
  79. Rouvière O, Girouin N, Glas L, et al. Prostate cancer transrectal HIFU ablation: detection of local recurrences using T2-weighted and dynamic contrast-enhanced MRI. Eur Radiol 2010;20:48-55. [Crossref] [PubMed]
  80. Bostwick DG, Graham SD, Napalkov P, et al. Staging of early prostate cancer: a proposed tumor volume-based prognostic index. Urology 1993;41:403-11. [Crossref] [PubMed]
  81. Rifkin MD, Alexander A. Prostate:techniques,results,and potential applications of color Doppler US scanning. Radiology 1993;186:509-13. [Crossref] [PubMed]
  82. Ukimura O, Babaian RJ. Role of PSA and its indices in determining the need for repeat prostate biopsies. Urology 1997;50:66-72. [Crossref] [PubMed]
  83. Rosenkrantz AB, Deng FM, Kim S, et al. Prostate cancer: multiparametric MRI for index lesion localization--a multiple-reader study. AJR Am J Roentgenol 2012;199:830-7. [Crossref] [PubMed]
  84. Rosenkrantz AB, Hindman N, Lim RP, et al. Diffusion-weighted imaging of the prostate: Comparison of b1000 and b2000 image sets for index lesion detection. J Magn Reson Imaging 2013;38:694-700. [Crossref] [PubMed]
  85. Reisæter LA, Fütterer JJ, Halvorsen OJ, et al. 1.5-T multiparametric MRI using PI-RADS: a region by region analysis to localize the index-tumor of prostate cancer in patients undergoing prostatectomy. Acta Radiol 2015;56:500-11. [Crossref] [PubMed]
  86. Delongchamps NB, Lefèvre A, Bouazza N, et al. Detection of significant prostate cancer with magnetic resonance targeted biopsies--should transrectal ultrasound-magnetic resonance imaging fusion guided biopsies alone be a standard of care? J Urol 2015;193:1198-204. [Crossref] [PubMed]
  87. Le JD, Tan N, Shkolyar E, et al. Multifocality and prostate cancer detection by multiparametric magnetic resonance imaging: correlation with whole-mount histopathology. Eur Urol 2015;67:569-76. [Crossref] [PubMed]
  88. Radtke JP, Kuru TH, Boxler S, et al. Comparative analysis of transperineal template saturation prostate biopsy versus magnetic resonance imaging targeted biopsy with magnetic resonance imaging-ultrasound fusion guidance. J Urol 2015;193:87-94. [Crossref] [PubMed]
Cite this article as: Wysock JS, Lepor H. Multi-parametric MRI imaging of the prostate—implications for focal therapy. Transl Androl Urol 2017;6(3):453-463. doi: 10.21037/tau.2017.04.29

Refbacks

  • There are currently no refbacks.