Sensitivity of multiparametric MRI and targeted biopsy for detection of adverse pathologies (Cribriform gleason pattern 4 and intraductal carcinoma): Correlation of detected and missed prostate cancer foci with whole mount histopathology.

PURPOSE: Accurate preoperative detection of prostate cancer (PCa) exhibiting "cribriform" morphology (intraductal carcinoma [IDC-P] or cribriform Gleason pattern 4 [CrP4]) is important as it is independently associated with a variety of adverse clinical outcomes. The sensitivity of multiparametric magnetic resonance imaging (mpMRI) in the detection of PCa exhibiting "cribriform" morphology remains controversial. MATERIALS AND METHODS: A total of 117 eligible men with prospectively reported mpMRI who underwent in-bore MRI targeted biopsy followed by whole-mount radical prostatectomy (RP) were analyzed for lesion-level imaging-pathology correlation. RESULTS: Of the 206 PCa foci at RP (117 index and 89 non-index), 74% (152/206) were detected by mpMRI. Of the 54 tumors missed by mpMRI, most were non-index (98%, 53/54), grade group (GG) 1 (68%, 37/54) or GG 2 (26%, 14/54), with a median size of 1.0 cm (range, 0.7-1.5 cm), and non-cribriform morphology (96%, 52/54). Cribriform morphology was detected in 26% (53/206) of all tumors, and although targeted biopsies identified 96% (51/53) of these cancers, the cribriform component was depicted in only 45% (24/53). Of these, mpMRI detected all (100%, 44/44) index and 78% (7/9) of the non-index tumors. At univariable analysis, tumor size greater than 5 mm, % pattern 4 > 5%, cribriform morphology, zone (transition versus peripheral zone), and region (apex versus mid/base) were significantly associated with tumor visibility at mpMRI. At multivariable analysis, only tumor size, presence of any pattern 4, and peripheral zone remained significant predictors for visibility by mpMRI. CONCLUSION: At a lesion level, mpMRI offers high sensitivity for the detection of cribriform morphologies, however, the cribriform component is frequently missed by targeted biopsies. The MRI visibility is significantly associated with larger tumor size, presence of Gleason pattern 4, and peripheral zone location.

Whole-brain 3D MR fingerprinting brain imaging: clinical validation and feasibility to patients with meningioma.

PURPOSE: MR fingerprinting (MRF) is a MR technique that allows assessment of tissue relaxation times. The purpose of this study is to evaluate the clinical application of this technique in patients with meningioma. MATERIALS AND METHODS: A whole-brain 3D isotropic 1mm3 acquisition under a 3.0T field strength was used to obtain MRF T1 and T2-based relaxometry values in 4:38 s. The accuracy of values was quantified by scanning a quantitative MR relaxometry phantom. In vivo evaluation was performed by applying the sequence to 20 subjects with 25 meningiomas. Regions of interest included the meningioma, caudate head, centrum semiovale, contralateral white matter and thalamus. For both phantom and subjects, mean values of both T1 and T2 estimates were obtained. Statistical significance of differences in mean values between the meningioma and other brain structures was tested using a Friedman's ANOVA test. RESULTS: MR fingerprinting phantom data demonstrated a linear relationship between measured and reference relaxometry estimates for both T1 (r2 = 0.99) and T2 (r2 = 0.97). MRF T1 relaxation times were longer in meningioma (mean ± SD 1429 ± 202 ms) compared to thalamus (mean ± SD 1054 ± 58 ms; p = 0.004), centrum semiovale (mean ± SD 825 ± 42 ms; p < 0.001) and contralateral white matter (mean ± SD 799 ± 40 ms; p < 0.001). MRF T2 relaxation times were longer for meningioma (mean ± SD 69 ± 27 ms) as compared to thalamus (mean ± SD 27 ± 3 ms; p < 0.001), caudate head (mean ± SD 39 ± 5 ms; p < 0.001) and contralateral white matter (mean ± SD 35 ± 4 ms; p < 0.001) CONCLUSIONS: Phantom measurements indicate that the proposed 3D-MRF sequence relaxometry estimations are valid and reproducible. For in vivo, entire brain coverage was obtained in clinically feasible time and allows quantitative assessment of meningioma in clinical practice.

Whole brain 3D MR fingerprinting in multiple sclerosis: a pilot study.

BACKGROUND: MR fingerprinting (MRF) is a novel imaging method proposed for the diagnosis of Multiple Sclerosis (MS). This study aims to determine if MR Fingerprinting (MRF) relaxometry can differentiate frontal normal appearing white matter (F-NAWM) and splenium in patients diagnosed with MS as compared to controls and to characterize the relaxometry of demyelinating plaques relative to the time of diagnosis. METHODS: Three-dimensional (3D) MRF data were acquired on a 3.0T MRI system resulting in isotropic voxels (1 × 1 × 1 mm3) and a total acquisition time of 4 min 38 s. Data were collected on 18 subjects paired with 18 controls. Regions of interest were drawn over MRF-derived T1 relaxometry maps encompassing selected MS lesions, F-NAWM and splenium. T1 and T2 relaxometry features from those segmented areas were used to classify MS lesions from F-NAWM and splenium with T-distributed stochastic neighbor embedding algorithms. Partial least squares discriminant analysis was performed to discriminate NAWM and Splenium in MS compared with controls. RESULTS: Mean out-of-fold machine learning prediction accuracy for discriminant results between MS patients and controls for F-NAWM was 65 % (p = 0.21) and approached 90 % (p < 0.01) for the splenium. There was significant positive correlation between time since diagnosis and MS lesions mean T2 (p = 0.015), minimum T1 (p = 0.03) and negative correlation with splenium uniformity (p = 0.04). Perfect discrimination (AUC = 1) was achieved between selected features from MS lesions and F-NAWM. CONCLUSIONS: 3D-MRF has the ability to differentiate between MS and controls based on relaxometry properties from the F-NAWM and splenium. Whole brain coverage allows the assessment of quantitative properties within lesions that provide chronological assessment of the time from MS diagnosis.

Accuracy and Interobserver Agreement for Prostate Imaging Reporting and Data System, Version 2, for the Characterization of Lesions Identified on Multiparametric MRI of the Prostate.

OBJECTIVE: The objective of this study was to measure the accuracy and interobserver agreement of the Prostate Imaging Reporting and Data System, version 2 (PI-RADSv2), for the characterization of prostate lesions on multiparametric MRI. MATERIALS AND METHODS: This retrospective study included 170 men examined at a single institution between August 2014 and February 2015 on a 3-T MRI scanner. Study patients were found to have lesions concerning for prostate cancer that were targeted for MRI/transrectal ultrasound fusion biopsy. Two experienced readers independently assigned a PI-RADSv2 assessment category to the dominant lesion in each patient. The AUC was calculated to determine reader accuracy for the detection of clinically significant prostate cancer (Gleason score ≥ 3 + 4). The Cohen kappa statistic was used to quantify interobserver agreement. RESULTS: The prevalence of clinically significant prostate cancer was 0.36 (61/170 patients). The AUCs for readers 1 and 2 were 0.871 and 0.882, respectively. The AUCs were greater for peripheral zone lesions than for transition zone lesions. When a PI-RADSv2 assessment category ≥ 3 was considered positive, the agreement between readers was good overall (κ = 0.63) and was fair for transition zone lesions (κ = 0.53). When a PI-RADSv2 assessment category ≥ 4 was considered positive, the agreement was excellent overall (κ = 0.91) and was excellent for both peripheral zone lesions (κ = 0.91) and transition zone lesions (κ = 0.87). CONCLUSION: Two experienced readers were able to accurately identify patients with clinically significant prostate cancer using PI-RADSv2 with good interobserver agreement overall.