Faculty Bibliography

AIM: To assess a novel method of three-dimensional (3D) co-registration of prostate cancer digital histology and in-vivo multiparametric magnetic resonance imaging (mpMRI) image sets for clinical usefulness. MATERIAL AND METHODS: A software platform was developed to achieve 3D co-registration. This software was prospectively applied to three patients who underwent radical prostatectomy. Data comprised in-vivo mpMRI [T2-weighted, dynamic contrast-enhanced weighted images (DCE); apparent diffusion coefficient (ADC)], ex-vivo T2-weighted imaging, 3D-rebuilt pathological specimen, and digital histology. Internal landmarks from zonal anatomy served as reference points for assessing co-registration accuracy and precision. RESULTS: Applying a method of deformable transformation based on 22 internal landmarks, a 1.6 mm accuracy was reached to align T2-weighted images and the 3D-rebuilt pathological specimen, an improvement over rigid transformation of 32% (p = 0.003). The 22 zonal anatomy landmarks were more accurately mapped using deformable transformation than rigid transformation (p = 0.0008). An automatic method based on mutual information, enabled automation of the process and to include perfusion and diffusion MRI images. Evaluation of co-registration accuracy using the volume overlap index (Dice index) met clinically relevant requirements, ranging from 0.81-0.96 for sequences tested. Ex-vivo images of the specimen did not significantly improve co-registration accuracy. CONCLUSION: This preliminary analysis suggests that deformable transformation based on zonal anatomy landmarks is accurate in the co-registration of mpMRI and histology. Including diffusion and perfusion sequences in the same 3D space as histology is essential further clinical information. The ability to localize cancer in 3D space may improve targeting for image-guided biopsy, focal therapy, and disease quantification in surveillance protocols.

Purpose: To compare the recently proposed Prostate Imaging Reporting and Data System (PI-RADS) scale that incorporates fixed criteria and a standard Likert scale based on overall impression in prostate cancer localization using multiparametric magnetic resonance (MR) imaging. Materials and Methods: This retrospective study was HIPAA compliant and institutional review board approved. Seventy patients who underwent 3-T pelvic MR imaging, including T2-weighted imaging, diffusion-weighted imaging, and dynamic contrast material-enhanced imaging, with a pelvic phased-array coil before radical prostatectomy were included. Three radiologists, each with 6 years of experience, independently scored 18 regions (12 peripheral zone [PZ], six transition zone [TZ]) using PI-RADS (range, scores 3-15) and Likert (range, scores 1-5) scales. Logistic regression for correlated data was used to compare scales for detection of tumors larger than 3 mm in maximal diameter at prostatectomy. Results: Maximal accuracy was achieved with score thresholds of 8 and higher and of 3 and higher for PI-RADS and Likert scales, respectively. At these thresholds, in the PZ, similar accuracy was achieved with the PI-RADS scale and the Likert scale for radiologist 1 (89.0% vs 88.2%, P = .223) and radiologist 3 (88.5% vs 88.2%, P = .739) and greater accuracy was achieved with the PI-RADS scale than the Likert scale for radiologist 2 (89.6% vs 87.1%, P = .008). In the TZ, accuracy was lower with the PI-RADS scale than with the Likert scale for radiologist 1 (70.0% vs 87.1%, P < .001), radiologist 2 (87.6% vs 92.6%, P = .002), and radiologist 3 (82.9% vs 91.2%, P < .001). For tumors with Gleason score of at least 7, sensitivity was higher with the PI-RADS scale than with the Likert scale for radiologist 1 (88.6% vs 82.6%, P = .032), and sensitivity was similar for radiologist 2 (78.0% vs 76.5, P = .467) and radiologist 3 (77.3% vs 81.1%, P = .125). Conclusion: Radiologists performed well with both PI-RADS and Likert scales for tumor localization, although, in the TZ, performance was better with the Likert scale than the PI-RADS scale. (c) RSNA, 2013 Supplemental material: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.13122233/-/DC1.

OBJECTIVES: To investigate the impact of prostate computed diffusion-weighted imaging (DWI) on image quality and tumour detection. METHODS: Forty-nine patients underwent 3-T magnetic resonance imaging using a pelvic phased-array coil before prostatectomy, including DWI with b values of 50 and 1,000 s/mm(2). Computed DW images with b value 1,500 s/mm(2) were generated from the lower b-value images. Directly acquired b-1,500 DW images were obtained in 39 patients. Two radiologists independently assessed DWI for image quality measures and location of the dominant lesion. A third radiologist measured tumour-to-peripheral-zone (PZ) contrast. Pathological findings from prostatectomy served as the reference standard. RESULTS: Direct and computed b-1,500 DWI showed better suppression of benign prostate tissue than direct b-1,000 DWI for both readers (P /= 0.180). Tumour-to-PZ contrast was greater on computed b-1,500 than on either direct DWI set (P < 0.001). CONCLUSION: Computed DWI of the prostate using b value >/=1,000 s/mm(2) improves image quality and tumour detection compared with acquired standard b-value images. KEY POINTS: * Diffusion weighted MRI is increasingly used for diagnosing and assessing prostate carcinoma. * Prostate computed DWI can extrapolate high b-value images from lower b values. * Computed DWI provides greater suppression of benign tissue than lower b-value images. * Computed DWI provides less distortion and artefacts than images using same b value. * Computed DWI provides better diagnostic performance than lower b-value images.

OBJECTIVE. The purpose of this study was to compare findings at nongaussian diffusional kurtosis imaging and conventional diffusion-weighted MRI as markers of adverse pathologic outcomes among prostate cancer patients who are active surveillance candidates and choose to undergo prostatectomy. MATERIALS AND METHODS. Fifty-eight active surveillance candidates (prostate-specific antigen concentration, < 10 ng/mL; clinical tumor category less than T2a; Gleason score, 3 + 3;