Literature DB >> 22190657

Automated computer-derived prostate volumes from MR imaging data: comparison with radiologist-derived MR imaging and pathologic specimen volumes.

Julie C Bulman1, Robert Toth, Amish D Patel, B Nicolas Bloch, Colm J McMahon, Long Ngo, Anant Madabhushi, Neil M Rofsky.   

Abstract

PURPOSE: To compare prostate gland volume (PV) estimation of automated computer-generated multifeature active shape models (MFAs) performed with 3-T magnetic resonance (MR) imaging with that of other methods of PV assessment, with pathologic specimens as the reference standard.
MATERIALS AND METHODS: All subjects provided written informed consent for this HIPAA-compliant and institutional review board-approved study. Freshly weighed prostatectomy specimens from 91 patients (mean age, 59 years; range, 42-84 years) served as the reference standard. PVs were manually calculated by two independent readers from MR images by using the standard ellipsoid formula. Planimetry PV was calculated from gland areas generated by two independent investigators by using manually drawn regions of interest. Computer-automated assessment of PV with an MFA was determined by the aggregate computer-calculated prostate area over the range of axial T2-weighted prostate MR images. Linear regression, linear mixed-effects models, concordance correlation coefficients, and Bland-Altman limits of agreement were used to compare volume estimation methods.
RESULTS: MFA-derived PVs had the best correlation with pathologic specimen PVs (slope, 0.888). Planimetry derived volumes produced slopes of 0.864 and 0.804 for two independent readers when compared with specimen PVs. Ellipsoid formula-derived PVs had slopes closest to one when compared with planimetry PVs. Manual MR imaging and MFA PV estimates had high concordance correlation coefficients with pathologic specimens.
CONCLUSION: MFAs with axial T2-weighted MR imaging provided an automated and efficient tool with which to assess PV. Both MFAs and MR imaging planimetry require adjustments for optimized PV accuracy when compared with prostatectomy specimens. © RSNA, 2012.

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Year:  2012        PMID: 22190657      PMCID: PMC3262981          DOI: 10.1148/radiol.11110266

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


  35 in total

1.  Accuracy and repeatability of prostate volume measurements by transrectal ultrasound.

Authors:  L M Eri; H Thomassen; B Brennhovd; L L Håheim
Journal:  Prostate Cancer Prostatic Dis       Date:  2002       Impact factor: 5.554

2.  Accuracy of in-vivo assessment of prostatic volume by MRI and transrectal ultrasonography.

Authors:  A Rahmouni; A Yang; C M Tempany; T Frenkel; J Epstein; P Walsh; P K Leichner; C Ricci; E Zerhouni
Journal:  J Comput Assist Tomogr       Date:  1992 Nov-Dec       Impact factor: 1.826

3.  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

4.  The accuracy of transrectal ultrasound prostate volume estimation: clinical correlations.

Authors:  G J Matthews; J Motta; J A Fracehia
Journal:  J Clin Ultrasound       Date:  1996 Nov-Dec       Impact factor: 0.910

5.  Reassessment of nonplanimetric transrectal ultrasound prostate volume estimates.

Authors:  M Bazinet; P I Karakiewicz; A G Aprikian; C Trudel; F Péloquin; J Dessureault; M Goyal; L R Bégin; M M Elhilali
Journal:  Urology       Date:  1996-06       Impact factor: 2.649

6.  Intraobserver and interobserver variability of MR imaging- and CT-derived prostate volumes after transperineal interstitial permanent prostate brachytherapy.

Authors:  D F Dubois; B R Prestidge; L A Hotchkiss; J J Prete; W S Bice
Journal:  Radiology       Date:  1998-06       Impact factor: 11.105

7.  Biplane planimetry as a new method for prostatic volume calculation in transrectal ultrasonography.

Authors:  A Kimura; Y Kurooka; T Kitamura; K Kawabe
Journal:  Int J Urol       Date:  1997-03       Impact factor: 3.369

8.  Assessment of prostatic size with computed tomography. Methodologic aspects.

Authors:  H Ohlsén; P Ekman; H Ringertz
Journal:  Acta Radiol Diagn (Stockh)       Date:  1982

9.  Random-effects models for longitudinal data.

Authors:  N M Laird; J H Ware
Journal:  Biometrics       Date:  1982-12       Impact factor: 2.571

10.  Combining prostate specific antigen with cancer and gland volume to predict more reliably pathological stage: the influence of prostate specific antigen cancer density.

Authors:  K L Blackwell; D G Bostwick; R P Myers; H Zincke; J E Oesterling
Journal:  J Urol       Date:  1994-06       Impact factor: 7.450

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  7 in total

1.  Simultaneous Segmentation of Prostatic Zones Using Active Appearance Models With Multiple Coupled Levelsets.

Authors:  Robert Toth; Justin Ribault; John Gentile; Dan Sperling; Anant Madabhushi
Journal:  Comput Vis Image Underst       Date:  2013-09-01       Impact factor: 3.876

2.  Central gland and peripheral zone prostate tumors have significantly different quantitative imaging signatures on 3 Tesla endorectal, in vivo T2-weighted MR imagery.

Authors:  Satish E Viswanath; Nicholas B Bloch; Jonathan C Chappelow; Robert Toth; Neil M Rofsky; Elizabeth M Genega; Robert E Lenkinski; Anant Madabhushi
Journal:  J Magn Reson Imaging       Date:  2012-02-15       Impact factor: 4.813

3.  Machine learning-based prediction of invisible intraprostatic prostate cancer lesions on 68 Ga-PSMA-11 PET/CT in patients with primary prostate cancer.

Authors:  Zhilong Yi; Siqi Hu; Xiaofeng Lin; Qiong Zou; MinHong Zou; Zhanlei Zhang; Lei Xu; Ningyi Jiang; Yong Zhang
Journal:  Eur J Nucl Med Mol Imaging       Date:  2021-11-30       Impact factor: 10.057

4.  Can prostatic arterial embolisation (PAE) reduce the volume of the peripheral zone? MRI evaluation of zonal anatomy and infarction after PAE.

Authors:  Yen-Ting Lin; Grégory Amouyal; Jean-Michel Correas; Héléna Pereira; Olivier Pellerin; Costantino Del Giudice; Carole Déan; Nicolas Thiounn; Marc Sapoval
Journal:  Eur Radiol       Date:  2016-01-06       Impact factor: 5.315

5.  Prostate volumes derived from MRI and volume-adjusted serum prostate-specific antigen: correlation with Gleason score of prostate cancer.

Authors:  Ibrahim Karademir; Dinggang Shen; Yahui Peng; Shu Liao; Yulei Jiang; Ambereen Yousuf; Gregory Karczmar; Steffen Sammet; Shiyang Wang; Milica Medved; Tatjana Antic; Scott Eggener; Aytekin Oto
Journal:  AJR Am J Roentgenol       Date:  2013-11       Impact factor: 3.959

6.  Predicting clinically significant prostate cancer based on pre-operative patient profile and serum biomarkers.

Authors:  Izak Faiena; Sinae Kim; Nicholas Farber; Young Suk Kwon; Brian Shinder; Neal Patel; Amirali H Salmasi; Thomas Jang; Eric A Singer; Wun-Jae Kim; Isaac Y Kim
Journal:  Oncotarget       Date:  2017-09-28

Review 7.  How Accurately Can Prostate Gland Imaging Measure the Prostate Gland Volume? Results of a Systematic Review.

Authors:  David R H Christie; Christopher F Sharpley
Journal:  Prostate Cancer       Date:  2019-03-03
  7 in total

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