Diagnosis of Prostate Cancer with Noninvasive Estimation of Prostate Tissue Composition by Using Hybrid Multidimensional MR Imaging: A Feasibility Study.

Purpose To evaluate whether compartmental analysis by using hybrid multidimensional magnetic resonance (MR) imaging can be used to diagnose prostate cancer and determine its aggressiveness. Materials and Methods Twenty-two patients with prostate cancer underwent preoperative 3.0-T MR imaging. Axial images were obtained with hybrid multidimensional MR imaging by using all combinations of echo times (47, 75, 100 msec) and b values of 0, 750, 1500 sec/mm2, resulting in a 3 × 3 array of data associated with each voxel. Volumes of the tissue components stroma, epithelium, and lumen were calculated by fitting the hybrid data to a three-compartment signal model, with distinct, paired apparent diffusion coefficient (ADC) and T2 values associated with each compartment. Volume fractions and conventional ADC and T2 were measured for regions of interest in sites of prostatectomy-verified malignancy (n = 28) and normal tissue (n = 71). Receiver operating characteristic (ROC) analysis was used to evaluate the performance of various parameters in differentiating prostate cancer from benign tissue. Results Compared with normal tissue, prostate cancer showed significantly increased fractional volumes of epithelium (23.2% ± 7.1 vs 48.8% ± 9.2, respectively) and reduced fractional volumes of lumen (26.4% ± 14.1 vs 14.0% ± 5.2) and stroma (50.5% ± 15.7 vs 37.2% ± 9.1) by using hybrid multidimensional MR imaging. The fractional volumes of tissue components show a significantly higher Spearman correlation coefficient with Gleason score (epithelium: ρ = 0.652, P = .0001; stroma: ρ = -0.439, P = .020; lumen: ρ = -0.390, P = .040) compared with traditional T2 values (ρ = -0.292, P = .132) and ADCs (ρ = -0.315, P = .102). The area under the ROC curve for differentiation of cancer from normal prostate was highest for fractional volume of epithelium (0.991), followed by fractional volumes of lumen (0.800) and stroma (0.789). Conclusion Fractional volumes of prostatic lumen, stroma, and epithelium change significantly when cancer is present. These parameters can be measured noninvasively by using hybrid multidimensional MR imaging and have the potential to improve the diagnosis of prostate cancer and determine its aggressiveness. © RSNA, 2018 Online supplemental material is available for this article.

[1]  Aytekin Oto,et al.  Hybrid multidimensional T2 and diffusion‐weighted MRI for prostate cancer detection , 2014, Journal of magnetic resonance imaging : JMRI.

[2]  Carole Lartizien,et al.  Prostate focal peripheral zone lesions: characterization at multiparametric MR imaging--influence of a computer-aided diagnosis system. , 2014, Radiology.

[3]  Evaluation of T2 values and apparent diffusion coefficient of the masseter muscle by clenching. , 2011, Dento maxillo facial radiology.

[4]  T. Bathen,et al.  Tissue Microstructure Is Linked to MRI Parameters and Metabolite Levels in Prostate Cancer , 2016, Front. Oncol..

[5]  A. Oto,et al.  Multi-parametric MR imaging of the anterior fibromuscular stroma and its differentiation from prostate cancer , 2017, Abdominal Radiology.

[6]  Silvia D. Chang,et al.  MR measurement of luminal water in prostate gland: Quantitative correlation between MRI and histology , 2017, Journal of magnetic resonance imaging : JMRI.

[7]  T. Scheenen,et al.  Contribution of Histopathologic Tissue Composition to Quantitative MR Spectroscopy and Diffusion-weighted Imaging of the Prostate. , 2016, Radiology.

[8]  A. Jemal,et al.  Cancer statistics, 2012 , 2012, CA: a cancer journal for clinicians.

[9]  G. Cowin,et al.  16 T Diffusion microimaging of fixed prostate tissue: Preliminary findings , 2011, Magnetic resonance in medicine.

[10]  A. Evans,et al.  Prostate tissue composition and MR measurements: investigating the relationships between ADC, T2, K(trans), v(e), and corresponding histologic features. , 2010, Radiology.

[11]  Mark McEntee,et al.  Changes in Epithelium, Stroma, and Lumen Space Correlate More Strongly with Gleason Pattern and Are Stronger Predictors of Prostate ADC Changes than Cellularity Metrics. , 2015, Radiology.

[12]  Andrew B Rosenkrantz,et al.  Radiologist, be aware: ten pitfalls that confound the interpretation of multiparametric prostate MRI. , 2014, AJR. American journal of roentgenology.

[13]  J. Geitung,et al.  Prostate magnetic resonance imaging: Multiexponential T2 decay in prostate tissue , 2008, Journal of magnetic resonance imaging : JMRI.

[14]  G. Cowin,et al.  Microscopic diffusivity compartmentation in formalin‐fixed prostate tissue , 2012, Magnetic resonance in medicine.

[15]  Silvia D. Chang,et al.  Luminal Water Imaging: A New MR Imaging T2 Mapping Technique for Prostate Cancer Diagnosis. , 2017, Radiology.

[16]  Linda M. Johnson,et al.  The Role of MRI in Prostate Cancer Active Surveillance , 2014, BioMed research international.

[17]  Deanna L Langer,et al.  Intermixed normal tissue within prostate cancer: effect on MR imaging measurements of apparent diffusion coefficient and T2--sparse versus dense cancers. , 2008, Radiology.

[18]  Aytekin Oto,et al.  Benign Conditions That Mimic Prostate Carcinoma: MR Imaging Features with Histopathologic Correlation. , 2016, Radiographics : a review publication of the Radiological Society of North America, Inc.

[19]  Eleftheria Panagiotaki,et al.  Limitations and Prospects for Diffusion-Weighted MRI of the Prostate , 2016, Diagnostics.

[20]  Evis Sala,et al.  Transition zone prostate cancers: features, detection, localization, and staging at endorectal MR imaging. , 2006, Radiology.

[21]  R. Bourne Magnetic resonance microscopy of prostate tissue: How basic science can inform clinical imaging development , 2013, Journal of medical radiation sciences.