Literature DB >> 26110669

Changes in Epithelium, Stroma, and Lumen Space Correlate More Strongly with Gleason Pattern and Are Stronger Predictors of Prostate ADC Changes than Cellularity Metrics.

Aritrick Chatterjee1, Geoffrey Watson1, Esther Myint1, Paul Sved1, Mark McEntee1, Roger Bourne1.   

Abstract

PURPOSE: To investigate the hypothesis that the clinically observed decrease in apparent diffusion coefficient (ADC) at diffusion-weighted magnetic resonance imaging with increasing prostate cancer Gleason grade can be attributed to an increasing volume of low-diffusivity epithelial cells and corresponding decreasing volumes of higher-diffusivity stroma and lumen space rather than to increased cell density.
MATERIALS AND METHODS: Tissue samples were acquired after institutional ethics review committee approval and informed consent from patients were obtained. Nuclear count, nuclear area, and gland component volumes (epithelium, stroma, lumen space) were measured in tissue from 14 patients. Gland component volumes and cellularity metrics were correlated with Gleason pattern (Spearman rank correlation coefficient) and measured ADC (Pearson correlation coefficient) in six prostates ex vivo. Differences between metrics for cancerous tissue and those for normal tissue were assessed by using a two-tailed two-sample t test. Linear mixed models with a post hoc Fisher least significant difference test were used to assess differences between gland component volumes and cellularity metrics for multiple groups. To adjust for a clustering effect due to repeated measures, the organ mean value of the measured metric for each tissue type was used in the analysis.
RESULTS: There were significant differences between Gleason patterns for gland component volumes (P < .05) but not nuclear count (P = .100) or area (P = .141). There was a stronger correlation of Gleason pattern with gland component volumes (n = 553) of epithelium (Spearman ρ = 0.898, P < .001), stroma (ρ = -0.651, P < .001), and lumen space (ρ = -0.912, P = .007) than with the cellularity metrics (n = 288) nuclear area (ρ = 0.422, P = .133) or nuclear count (ρ = 0.082, P = .780). There was a stronger correlation between measured ADC and lumen volume (r = 0.688, P < .001) and epithelium volume (r = -0.647, P < .001) than between ADC and nuclear count (r = -0.598, P < .001) or nuclear area (r = -0.569, P < .001) (n = 57).
CONCLUSION: Differences in the gland compartment volumes of prostate tissue having distinct diffusivities, rather than changes in the conventionally cited "cellularity" metrics, are likely to be the major contributor to clinically observed variations of ADC in prostate tissue.

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Year:  2015        PMID: 26110669     DOI: 10.1148/radiol.2015142414

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  41 in total

1.  MR measurement of luminal water in prostate gland: Quantitative correlation between MRI and histology.

Authors:  Shirin Sabouri; Ladan Fazli; Silvia D Chang; Richard Savdie; Edward C Jones; S Larry Goldenberg; Peter C Black; Piotr Kozlowski
Journal:  J Magn Reson Imaging       Date:  2017-01-27       Impact factor: 4.813

2.  Diffusion-weighted endorectal MR imaging at 3T for prostate cancer: correlation with tumor cell density and percentage Gleason pattern on whole mount pathology.

Authors:  Daniel I Glazer; Elmira Hassanzadeh; Andriy Fedorov; Olutayo I Olubiyi; Shayna S Goldberger; Tobias Penzkofer; Trevor A Flood; Paul Masry; Robert V Mulkern; Michelle S Hirsch; Clare M Tempany; Fiona M Fennessy
Journal:  Abdom Radiol (NY)       Date:  2017-03

3.  Prostate Cancer: A Correlative Study of Multiparametric MR Imaging and Digital Histopathology.

Authors:  Jin Tae Kwak; Sandeep Sankineni; Sheng Xu; Baris Turkbey; Peter L Choyke; Peter A Pinto; Vanessa Moreno; Maria Merino; Bradford J Wood
Journal:  Radiology       Date:  2017-06-05       Impact factor: 11.105

Review 4.  Artificial intelligence at the intersection of pathology and radiology in prostate cancer.

Authors:  Stephnie A Harmon; Sena Tuncer; Thomas Sanford; Peter L Choyke; Barış Türkbey
Journal:  Diagn Interv Radiol       Date:  2019-05       Impact factor: 2.630

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

Authors:  Aritrick Chatterjee; Roger M Bourne; Shiyang Wang; Ajit Devaraj; Alexander J Gallan; Tatjana Antic; Gregory S Karczmar; Aytekin Oto
Journal:  Radiology       Date:  2018-02-02       Impact factor: 11.105

Review 6.  Restriction spectrum imaging: An evolving imaging biomarker in prostate MRI.

Authors:  Ryan L Brunsing; Natalie M Schenker-Ahmed; Nathan S White; J Kellogg Parsons; Christopher Kane; Joshua Kuperman; Hauke Bartsch; Andrew Karim Kader; Rebecca Rakow-Penner; Tyler M Seibert; Daniel Margolis; Steven S Raman; Carrie R McDonald; Nikdokht Farid; Santosh Kesari; Donna Hansel; Ahmed Shabaik; Anders M Dale; David S Karow
Journal:  J Magn Reson Imaging       Date:  2016-08-16       Impact factor: 4.813

Review 7.  New prostate MRI techniques and sequences.

Authors:  Aritrick Chatterjee; Carla Harmath; Aytekin Oto
Journal:  Abdom Radiol (NY)       Date:  2020-12

Review 8.  Functional and Targeted Lymph Node Imaging in Prostate Cancer: Current Status and Future Challenges.

Authors:  Harriet C Thoeny; Sebastiano Barbieri; Johannes M Froehlich; Baris Turkbey; Peter L Choyke
Journal:  Radiology       Date:  2017-12       Impact factor: 11.105

9.  Bi-parametric magnetic resonance imaging based radiomics for the identification of benign and malignant prostate lesions: cross-vendor validation.

Authors:  Xuefu Ji; Jiayi Zhang; Yuguo Tang; Wei Xia; Wei Shi; Dong He; Jie Bao; Xuedong Wei; Yuhua Huang; Yangchuan Liu; Jyh-Cheng Chen; Xin Gao
Journal:  Phys Eng Sci Med       Date:  2021-06-01

10.  Targeted Biopsy Validation of Peripheral Zone Prostate Cancer Characterization With Magnetic Resonance Fingerprinting and Diffusion Mapping.

Authors:  Ananya Panda; Gregory OʼConnor; Wei Ching Lo; Yun Jiang; Seunghee Margevicius; Mark Schluchter; Lee E Ponsky; Vikas Gulani
Journal:  Invest Radiol       Date:  2019-08       Impact factor: 6.016

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