Literature DB >> 22578226

Automated vs. manual pattern recognition of 3D (1)H MRSI data of patients with prostate cancer.

Christian M Zechmann1, Bjoern H Menze, B Michael Kelm, Patrik Zamecnik, Uwe Ikinger, Frederik L Giesel, Christian Thieke, Stefan Delorme, Fred A Hamprecht, Peter Bachert.   

Abstract

RATIONALE AND
OBJECTIVES: The aim of this study was to assess (1) automated analysis methods versus manual evaluation by human experts of three-dimensional proton magnetic resonance spectroscopic imaging (MRSI) data from patients with prostate cancer and (2) the contribution of spatial information to decision making.
MATERIALS AND METHODS: Three-dimensional proton MRSI was applied at 1.5 T. MRSI data from 10 patients with histologically proven prostate adenocarcinoma, scheduled either for prostatectomy or intensity-modulated radiation therapy, were evaluated. First, two readers manually labeled spectra using spatial information to identify the localization of spectra and neighborhood information, establishing the reference set of this study. Then, spectra were labeled again manually in a blinded and randomized manner and evaluated automatically using software that applied spectral line fitting as well as pattern recognition routines. Statistical analysis of the results of the different approaches was performed.
RESULTS: Altogether, 1018 spectra were evaluable by all methods. Numbers of evaluable spectra differed significantly depending on patient and evaluation method. Compared to automated analysis, the readers made rather binary decisions, using information from neighboring spectra in ambiguous cases, when evaluating MRSI data as a whole. Differences between anatomically blinded and unblinded evaluation were larger than differences between evaluations using blinded data and automated techniques.
CONCLUSIONS: An automated approach, which evaluates each spectrum individually, can be as good as an anatomy-blinded human reader. Spatial information is routinely used by human experts to support their final decisions. Automated procedures that consider anatomic information for spectral evaluation will enhance the diagnostic impact of MRSI of the human prostate.
Copyright © 2012 AUR. Published by Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 22578226     DOI: 10.1016/j.acra.2012.02.014

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  3 in total

1.  Prostate MRSI predicts outcome in radical prostatectomy patients.

Authors:  Kristen L Zakian; William Hatfield; Omer Aras; Kun Cao; Derya Yakar; Debra A Goldman; Chaya S Moskowitz; Amita Shukla-Dave; Yousef Mazaheri Tehrani; Samson Fine; James Eastham; Hedvig Hricak
Journal:  Magn Reson Imaging       Date:  2016-01-26       Impact factor: 2.546

Review 2.  Metabolic Imaging in Prostate Cancer: Where We Are.

Authors:  Claudia Testa; Cristian Pultrone; David Neil Manners; Riccardo Schiavina; Raffaele Lodi
Journal:  Front Oncol       Date:  2016-11-09       Impact factor: 6.244

Review 3.  Developments in proton MR spectroscopic imaging of prostate cancer.

Authors:  Angeliki Stamatelatou; Tom W J Scheenen; Arend Heerschap
Journal:  MAGMA       Date:  2022-04-20       Impact factor: 2.533

  3 in total

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