Literature DB >> 24673731

Prostate tumour volumes: evaluation of the agreement between magnetic resonance imaging and histology using novel co-registration software.

Julien Le Nobin1,2, Clément Orczyk1,3, Fang-Ming Deng4, Jonathan Melamed4, Henry Rusinek5, Samir S Taneja1, Andrew B Rosenkrantz5.   

Abstract

OBJECTIVE: To evaluate the agreement between prostate tumour volume determined using multiparametric magnetic resonance imaging (MRI) and that determined by histological assessment, using detailed software-assisted co-registration.
MATERIALS AND METHODS: A total of 37 patients who underwent 3T multiparametric MRI (T2-weighted imaging [T2WI], diffusion-weighted imaging [DWI]/apparent diffusion coefficient [ADC], dynamic contrast-enhanced [DCE] imaging) were included. A radiologist traced the borders of suspicious lesions on T2WI and ADC and assigned a suspicion score of between 2 and 5, while a uropathologist traced the borders of tumours on histopathological photographs. Software was used to co-register MRI and three-dimensional digital reconstructions of radical prostatectomy specimens and to compute imaging and histopathological volumes. Agreement in volumes between MRI and histology was assessed using Bland-Altman plots and stratified by tumour characteristics.
RESULTS: Among 50 tumours, the mean differences (95% limits of agreement) in MRI relative to histology were -32% (-128 to +65%) on T2WI and -47% (-143 to +49%) on ADC. For all tumour subsets, volume underestimation was more marked on ADC maps (mean difference ranging from -57 to -16%) than on T2WI (mean difference ranging from -45 to +2%). The 95% limits of agreement were wide for all comparisons, with the lower 95% limit ranging between -77 and -143% across assessments. Volume underestimation was more marked for tumours with a Gleason score ≥7 or a MRI suspicion score 4 or 5.
CONCLUSION: Volume estimates of prostate cancer using MRI tended to substantially underestimate histopathological volumes, with a wide variability in extent of underestimation across cases. These findings have implications for efforts to use MRI to guide risk assessment.
© 2014 The Authors. BJU International © 2014 BJU International.

Entities:  

Keywords:  computer-assisted; diffusion-weighted MRI; histology; image processing; prostate cancer; tumour volume

Mesh:

Year:  2014        PMID: 24673731      PMCID: PMC4714042          DOI: 10.1111/bju.12750

Source DB:  PubMed          Journal:  BJU Int        ISSN: 1464-4096            Impact factor:   5.588


  20 in total

1.  Preliminary experience with a novel method of three-dimensional co-registration of prostate cancer digital histology and in vivo multiparametric MRI.

Authors:  C Orczyk; H Rusinek; A B Rosenkrantz; A Mikheev; F-M Deng; J Melamed; S S Taneja
Journal:  Clin Radiol       Date:  2013-08-28       Impact factor: 2.350

2.  Determinations of prostate volume at 3-Tesla using an external phased array coil: comparison to pathologic specimens.

Authors:  Jacob Sosna; Neil M Rofsky; Sandra M Gaston; William C DeWolf; Robert E Lenkinski
Journal:  Acad Radiol       Date:  2003-08       Impact factor: 3.173

3.  Assessment of aggressiveness of prostate cancer: correlation of apparent diffusion coefficient with histologic grade after radical prostatectomy.

Authors:  Sadhna Verma; Arumugam Rajesh; Humberto Morales; Lisa Lemen; Gordon Bills; Mark Delworth; Krish Gaitonde; Jun Ying; Ranasinghe Samartunga; Michael Lamba
Journal:  AJR Am J Roentgenol       Date:  2011-02       Impact factor: 3.959

4.  Diffusion-weighted MRI of peripheral zone prostate cancer: comparison of tumor apparent diffusion coefficient with Gleason score and percentage of tumor on core biopsy.

Authors:  Courtney A Woodfield; Glenn A Tung; David J Grand; John A Pezzullo; Jason T Machan; Joseph F Renzulli
Journal:  AJR Am J Roentgenol       Date:  2010-04       Impact factor: 3.959

5.  Prostate cancer foci detected on multiparametric magnetic resonance imaging are histologically distinct from those not detected.

Authors:  Andrew B Rosenkrantz; Savvas Mendrinos; James S Babb; Samir S Taneja
Journal:  J Urol       Date:  2012-04-11       Impact factor: 7.450

6.  Influence of imaging and histological factors on prostate cancer detection and localisation on multiparametric MRI: a prospective study.

Authors:  Flavie Bratan; Emilie Niaf; Christelle Melodelima; Anne Laure Chesnais; Rémi Souchon; Florence Mège-Lechevallier; Marc Colombel; Olivier Rouvière
Journal:  Eur Radiol       Date:  2013-03-15       Impact factor: 5.315

7.  Correlation of magnetic resonance imaging tumor volume with histopathology.

Authors:  Baris Turkbey; Haresh Mani; Omer Aras; Ardeshir R Rastinehad; Vijay Shah; Marcelino Bernardo; Thomas Pohida; Dagane Daar; Compton Benjamin; Yolanda L McKinney; W Marston Linehan; Bradford J Wood; Maria J Merino; Peter L Choyke; Peter A Pinto
Journal:  J Urol       Date:  2012-08-15       Impact factor: 7.450

8.  MR imaging-guided focal laser ablation for prostate cancer: phase I trial.

Authors:  Aytekin Oto; Ila Sethi; Gregory Karczmar; Roger McNichols; Marko K Ivancevic; Walter M Stadler; Sydeaka Watson; Scott Eggener
Journal:  Radiology       Date:  2013-02-25       Impact factor: 11.105

9.  Prostate tumor volume measurement with combined T2-weighted imaging and diffusion-weighted MR: correlation with pathologic tumor volume.

Authors:  Yousef Mazaheri; Hedvig Hricak; Samson W Fine; Oguz Akin; Amita Shukla-Dave; Nicole M Ishill; Chaya S Moskowitz; Joanna E Grater; Victor E Reuter; Kristen L Zakian; Karim A Touijer; Jason A Koutcher
Journal:  Radiology       Date:  2009-08       Impact factor: 11.105

10.  Intermixed normal tissue within prostate cancer: effect on MR imaging measurements of apparent diffusion coefficient and T2--sparse versus dense cancers.

Authors:  Deanna L Langer; Theodorus H van der Kwast; Andrew J Evans; Laibao Sun; Martin J Yaffe; John Trachtenberg; Masoom A Haider
Journal:  Radiology       Date:  2008-12       Impact factor: 11.105

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  25 in total

Review 1.  Techniques and Outcomes of MRI-TRUS Fusion Prostate Biopsy.

Authors:  Masatomo Kaneko; Dordaneh Sugano; Amir H Lebastchi; Vinay Duddalwar; Jamal Nabhani; Christopher Haiman; Inderbir S Gill; Giovanni E Cacciamani; Andre Luis Abreu
Journal:  Curr Urol Rep       Date:  2021-03-22       Impact factor: 3.092

2.  Magnetic Resonance Imaging Underestimation of Prostate Cancer Geometry: Use of Patient Specific Molds to Correlate Images with Whole Mount Pathology.

Authors:  Alan Priester; Shyam Natarajan; Pooria Khoshnoodi; Daniel J Margolis; Steven S Raman; Robert E Reiter; Jiaoti Huang; Warren Grundfest; Leonard S Marks
Journal:  J Urol       Date:  2016-07-30       Impact factor: 7.450

3.  3D Registration of mpMRI for Assessment of Prostate Cancer Focal Therapy.

Authors:  Clément Orczyk; Andrew B Rosenkrantz; Artem Mikheev; Arnauld Villers; Myriam Bernaudin; Samir S Taneja; Samuel Valable; Henry Rusinek
Journal:  Acad Radiol       Date:  2017-11-06       Impact factor: 3.173

4.  Image Guided Focal Therapy for Magnetic Resonance Imaging Visible Prostate Cancer: Defining a 3-Dimensional Treatment Margin Based on Magnetic Resonance Imaging Histology Co-Registration Analysis.

Authors:  Julien Le Nobin; Andrew B Rosenkrantz; Arnauld Villers; Clément Orczyk; Fang-Ming Deng; Jonathan Melamed; Artem Mikheev; Henry Rusinek; Samir S Taneja
Journal:  J Urol       Date:  2015-02-21       Impact factor: 7.450

5.  Effect of observation size and apparent diffusion coefficient (ADC) value in PI-RADS v2.1 assessment category 4 and 5 observations compared to adverse pathological outcomes.

Authors:  Jorge Abreu-Gomez; Daniel Walker; Tareq Alotaibi; Matthew D F McInnes; Trevor A Flood; Nicola Schieda
Journal:  Eur Radiol       Date:  2020-03-24       Impact factor: 5.315

6.  PRECISION MANAGEMENT OF LOCALIZED PROSTATE CANCER.

Authors:  David J VanderWeele; Baris Turkbey; Adam G Sowalsky
Journal:  Expert Rev Precis Med Drug Dev       Date:  2016-12-12

7.  Multivariate modelling of prostate cancer combining magnetic resonance derived T2, diffusion, dynamic contrast-enhanced and spectroscopic parameters.

Authors:  S F Riches; G S Payne; V A Morgan; D Dearnaley; S Morgan; M Partridge; N Livni; C Ogden; N M deSouza
Journal:  Eur Radiol       Date:  2015-03-07       Impact factor: 5.315

8.  The role of pathology correlation approach in prostate cancer index lesion detection and quantitative analysis with multiparametric MRI.

Authors:  Andriy Fedorov; Tobias Penzkofer; Michelle S Hirsch; Trevor A Flood; Mark G Vangel; Paul Masry; Clare M Tempany; Robert V Mulkern; Fiona M Fennessy
Journal:  Acad Radiol       Date:  2015-02-13       Impact factor: 3.173

9.  Prostate cancer measurements on serial MRI during active surveillance: it's time to be PRECISE.

Authors:  Francesco Giganti; Vasilis Stavrinides; Armando Stabile; Elizabeth Osinibi; Clement Orczyk; Jan Philipp Radtke; Alex Freeman; Aiman Haider; Shonit Punwani; Clare Allen; Mark Emberton; Alex Kirkham; Caroline M Moore
Journal:  Br J Radiol       Date:  2020-09-21       Impact factor: 3.039

10.  Analysis of different tumor volume thresholds of insignificant prostate cancer and their implications for active surveillance patient selection and monitoring.

Authors:  Dong Hoon Lee; Kyo Chul Koo; Seung Hwan Lee; Koon Ho Rha; Young Deuk Choi; Sung Joon Hong; Byung Ha Chung
Journal:  Prostate Int       Date:  2014-06-30
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