Several information technology tools are required to ensure optimal and comfortable image interpretation and reporting:
In our experience, double-reading is especially interesting in the startup-phase of prostate imaging training, as readers with low experience tend to describe typically false-positive images, or still need methodological assistance. Further studies will be required to answer this question in the future.
On the basis of previous observations, and similarly to what other disciplines did , it is possible to propose three standardized levels of competence in prostate multiparametric-MRI reading:
The European Society of Radiology has published a description of three levels of training, consistent with a forementioned levels of competence. Levels I and II correspond to years 1–3 and 4–5 of residency training periods, respectively. Level III corresponds to a subspecialization beyond the fifth year of training . Level I training in uroradiology includes ‘understanding of imaging features and differential diagnoses of pathologies of the prostate, seminal vesicles, and testes/scrotum’. Level II training includes ‘description of zonal anatomy of the prostate’ and ‘description of imaging features of prostatic zones with ultrasound and MRI’, as well as ‘inflammatory and tumoral disorders of the prostate’.
Papers of particular interest, published within the annual period of review, have been highlighted as:
1. Barentsz JO, Richenberg J, Clements R, et al. ESUR prostate
2012. Eur Radiol 2012; 22:746–757.
3. Akin O, Riedl CC, Ishill NM, et al. Interactive dedicated training curriculum improves accuracy in the interpretation
of MR imaging of prostate
cancer. Eur Radiol 2010; 20:995–1002.
4▪▪. Vache T, Bratan F, Mege-Lechevallier F, et al. Characterization of prostate
lesions as benign or malignant at multiparametric MR imaging: comparison of three scoring systems in patients treated with radical prostatectomy. Radiology 2014; 272:446–455.
This article shows robust methodology. It shows that classical scoring systems (Likert-like) perform better than version 1.0 of the PI-RADS, suggesting that its criteria do not perfectly reflect prostate cancer MRI semiology, and opening way for improvements in the new version of PI-RADS.
5. Puech P, Villers A, Ouzzane A, Lemaitre L. Prostate
cancer: diagnosis, parametric imaging and standardized report. Diagn Interv Imaging 2014; 95:743–752.
6. 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; 59:477–494.
7. Dickinson L, Ahmed HU, Allen C, et al. Scoring systems used for the interpretation
of multiparametric MRI
cancer detection, localization, and characterization: could standardization lead to improved utilization of imaging within the diagnostic pathway? J Magn Reson Imaging 2012; 37:48–58.
8. Moore CM, Kasivisvanathan V, Eggener S, et al. Standards of reporting
-targeted biopsy studies (START) of the prostate
: recommendations from an International Working Group. Eur Urol 2013; 64:544–552.
9. Puech P, Ouzzane A, Gaillard V, et al. Multiparametric MRI
-targeted TRUS prostate
biopsies using visual registration. Biomed Res Int 2014; 2014:819360.
10. Mueller-Lisse U, Mueller-Lisse U, Scheidler J, et al. Reproducibility of image interpretation
of the prostate
: application of the sextant framework by two different radiologists. Eur Radiol 2005; 15:1826–1833.
11. Dickinson L, Ahmed HU, Allen C, et al. Clinical applications of multiparametric MRI
within the prostate
cancer diagnostic pathway. Urol Oncol 2013; 31:281–284.
12▪. Muller BG, Shih JH, Sankineni S, et al. Prostate
cancer: interobserver agreement and accuracy with the revised prostate
and data system at multiparametric MR imaging. Radiology 2015; 142818.
This original research is first to assess accuracy of the new PI-RADS version 2.0 score for detection of clinically significant prostate cancer. However, it concludes to moderate reproducibility.
13▪. Hamoen EH, de Rooij M, Witjes JA, et al. Use of the Prostate
and Data System (PI-RADS) for prostate
cancer detection with multiparametric magnetic resonance imaging: a diagnostic meta-analysis. Eur Urol 2015; 67:1112–1121.
This review article pooled data of 14 studies in the literature about PI-RADS scoring, and confirmed reliable sensitivity, specificity, and NPV of prostate multiparametric-MRI for identifying clinically significant prostate cancer.
14. Rosenkrantz AB, Lim RP, Haghighi M, et al. Comparison of interreader reproducibility of the prostate
and data system and likert scales for evaluation of multiparametric prostate MRI
. AJR Am J Roentgenol 2013; 201:W612–W618.
15. Renard-Penna R, Mozer P, Cornud F, et al. Prostate
and data system and likert scoring system: multiparametric MR imaging validation study to screen patients for initial biopsy. Radiology 2015; 275:458–468.
16. Grey AD, Chana MS, Popert R, et al. Diagnostic accuracy of magnetic resonance imaging (MRI
and data system (PI-RADS) scoring in a transperineal prostate
biopsy setting. BJU Int 2015; 115:728–735.
17. Rosenkrantz AB, Kim S, Lim RP, et al. Prostate
cancer localization using multiparametric MR imaging: comparison of Prostate
and Data System (PI-RADS) and Likert scales. Radiology 2013; 269:482–492.
18. Betrouni N, Makni N, Lakroum S, et al. Computer-aided analysis of prostate
multiparametric MR images: an unsupervised fusion-based approach. Int J Comput Assist Radiol Surg 2015.
19. Lemaitre G, Marti R, Freixenet J, et al. Computer-aided detection and diagnosis for prostate
cancer based on mono and multiparametric MRI
: a review. Comput Biol Med 2015; 60:8–31.
20▪. Wang S, Burtt K, Turkbey B, et al. Computer aided-diagnosis of prostate
cancer on multiparametric MRI
: a technical review of current research. Biomed Res Int 2014; 2014:789561.
This article is a nice and detailed review of current literature on CAD analysis of multiparametric prostate MRI data.
21. Zhao K, Wang C, Hu J, et al. Prostate
cancer identification: quantitative analysis of T2-weighted MR images based on a back propagation artificial neural network model. Sci China Life Sci 2015; 58:666–673.
22. Regge D, Halligan S. CAD: how it works, how to use it, performance. Eur J Radiol 2013; 82:1171–1176.
23. Niaf E, Rouviere O, Mege-Lechevallier F, et al. Computer-aided diagnosis of prostate
cancer in the peripheral zone using multiparametric MRI
. Phys Med Biol 2012; 57:3833–3851.
24. Puech P, Betrouni N, Makni N, et al. Computer-assisted diagnosis of prostate
cancer using DCE-MRI
data: design, implementation and preliminary results. Int J Comput Assist Radiol Surg 2009; 4:1–10.
25. Rosenkrantz AB, Geppert C, Grimm R, et al. Dynamic contrast-enhanced MRI
of the prostate
with high spatiotemporal resolution using compressed sensing, parallel imaging, and continuous golden-angle radial sampling: preliminary experience. J Magn Reson Imaging 2015; 41:1365–1373.
26. Rakow-Penner RA, White NS, Parsons JK, et al. Novel technique for characterizing prostate
cancer utilizing MRI
restriction spectrum imaging: proof of principle and initial clinical experience with extraprostatic extension. Prostate
Cancer Prostatic Dis 2015; 18:81–85.
27. Dikaios N, Alkalbani J, Sidhu HS, et al. Logistic regression model for diagnosis of transition zone prostate
cancer on multiparametric MRI
. Eur Radiol 2015; 25:523–532.
28. Wibmer A, Vargas HA, Sosa R, et al. Value of a standardized lexicon for reporting
levels of diagnostic certainty in prostate MRI
. AJR Am J Roentgenol 2014; 203:W651–W657.
29. Westphalen AC, Rosenkrantz AB. Prostate
and data system (PI-RADS): reflections on early experience with a standardized interpretation
scheme for multiparametric prostate MRI
. AJR Am J Roentgenol 2014; 202:121–123.
30. Rothke M, Blondin D, Schlemmer HP, Franiel T. PI-RADS classification: structured reporting
of the prostate
. Rofo 2013; 185:253–261.
31. Kirkham AP, Haslam P, Keanie JY, et al. Prostate MRI
: who, when, and how? Report from a UK consensus meeting. Clin Radiol 2013; 68:1016–1023.
32. Quentin M, Blondin D, Klasen J, et al. Evaluation of a structured report of functional prostate
magnetic resonance imaging in patients with suspicion for prostate
cancer or under active surveillance. Urol Int 2012; 89:25–29.
33▪. Silveira PC, Dunne R, Sainani NI, et al. Impact of an information technology-enabled initiative on the quality of prostate
reports. Acad Radiol 2015; 22:827–833.
Implementation of a structured report template and CAD tool significantly improves the quality of prostate multiparametric-MRI reports.
34. Plumb AA, Grieve FM, Khan SH. Survey of hospital clinicians’ preferences regarding the format of radiology reports. Clin Radiol 2009; 64:386-394395-386.
35. Kahn CE Jr, Heilbrun ME, Applegate KE. From guidelines
to practice: how reporting
templates promote the use of radiology practice guidelines
. J Am College Radiol 2013; 10:268–273.
36. El-Shater Bosaily A, Parker C, Brown LC, et al. PROMIS - Prostate
MR imaging study: a paired validating cohort study evaluating the role of multiparametric MRI
in men with clinical suspicion of prostate
cancer. Contemp Clin Trials 2015; 42:26–40.
This is the URL to a free online web-based computer assisted reporting tool, designed to easily draw multiparametric-MRI findings on a standardized prostate map.
38. Haffner J, Lemaitre L, Puech P, et al. Role of magnetic resonance imaging before initial biopsy: comparison of magnetic resonance imaging-targeted and systematic biopsy for significant prostate
cancer detection. BJU Int 2011; 108:E171–E178.
39. Barentsz J, Villers A, Schouten M. ESUR prostate
. Author reply. Eur Radiol 2013; 23:2322–2323.
40▪. Litjens GJ, Barentsz JO, Karssemeijer N, Huisman HJ. Clinical evaluation of a computer-aided diagnosis system for determining cancer aggressiveness in prostate MRI
. Eur Radiol 2015; doi 10.1007/s00330-015-3743-y. [Epub ahead of print].
This article shows that PI-RADS assessment benefits of the addition of objective criteria, based on computer assisted image analysis.
41. Mata C, Walker PM, Oliver A, et al. ProstateAnalyzer: web-based medical application for the management of prostate
cancer using multiparametric MR imaging. Inform Health Soc Care 2015; 1–21.
42. Futterer JJ, Engelbrecht MR, Huisman HJ, et al. Staging prostate
cancer with dynamic contrast-enhanced endorectal MR imaging prior to radical prostatectomy: experienced versus less experienced readers. Radiology 2005; 237:541–549.
43. Mullerad M, Hricak H, Wang L, et al. Prostate
cancer: detection of extracapsular extension by genitourinary and general body radiologists at MR imaging. Radiology 2004; 232:140–146.
44. Latchamsetty KC, Borden LS Jr, Porter CR, et al. Experience improves staging accuracy of endorectal magnetic resonance imaging in prostate
cancer: what is the learning curve? Can J Urol 2007; 14:3429–3434.
45. Harris RD, Schned AR, Heaney JA. Staging of prostate
cancer with endorectal MR imaging: lessons from a learning curve. Radiographics 1995; 15:813–829.
46. Muller BG, Futterer 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; 113:218–227.
47. Trimboli RM, Verardi N, Cartia F, et al. Breast cancer detection using double reading of unenhanced MRI
including T1-weighted, T2-weighted STIR, and diffusion-weighted imaging: a proof of concept study. AJR Am J Roentgenol 2014; 203:674–681.
48. Klompenhouwer EG, Duijm LE, Voogd AC, et al. Variations in screening outcome among pairs of screening radiologists at nonblinded double reading of screening mammograms: a population-based study. Eur Radiol 2014; 24:1097–1104.
49. Klompenhouwer EG, Voogd AC, den Heeten GJ, et al. Blinded double reading yields a higher programme sensitivity than nonblinded double reading at digital screening mammography: a prospected population based study in the south of The Netherlands. Eur J Cancer 2015; 51:391–399.
50. Klompenhouwer EG, Weber RJ, Voogd AC, et al. Arbitration of discrepant BI-RADS 0 recalls by a third reader at screening mammography lowers recall rate but not the cancer detection rate and sensitivity at blinded and nonblinded double reading. Breast 2015; doi: 10.1016/j.breast.2015.06.004. [Epub ahead of print].
51. Popescu BA, Andrade MJ, Badano LP, et al. European Association of Echocardiography recommendations for training, competence, and quality improvement in echocardiography. Eur J Echocardiogr 2009; 10:893–905.
52. Ertl-Wagner B. European curriculum for further education
in radiology. Der Radiologe 2014; 54:11061107-1110.
53▪. Garcia-Reyes K, Passoni NM, Palmeri ML, et al. Detection of prostate
cancer with multiparametric MRI
(mpMRI): effect of dedicated reader education
on accuracy and confidence of index and anterior cancer diagnosis. Abdominal Imaging 2015; 40:134–142.
This article shows that simple training (two dedicated lectures) for prostate multiparametric-MRI reading significantly increases readers accuracy (especially for anterior tumors detection), and reduces interobserver variability, with a yield of +13.5%.
54. Howard SA, Krajewski KM, Weissman BN, et al. Cancer imaging training in the 21st century: an overview of where we are, and where we need to be. J Am Coll Radiol 2015; 12:714–720.