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Accuracy and reproducibility of a novel semi-automatic segmentation technique for MR volumetry of the pituitary gland

  • Diagnostic Neuroradiology
  • Published:
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Abstract

Introduction

Although several reports about volumetric determination of the pituitary gland exist, volumetries have been solely performed by indirect measurements or manual tracing on the gland’s boundaries. The purpose of this study was to evaluate the accuracy and reproducibility of a novel semi-automatic MR-based segmentation technique.

Methods

In an initial technical investigation, T1-weighted 3D native magnetised prepared rapid gradient echo sequences (1.5 T) with 1 mm isotropic voxel size achieved high reliability and were utilised in different in vitro and in vivo studies. The computer-assisted segmentation technique was based on an interactive watershed transform after resampling and gradient computation. Volumetry was performed by three observers with different software and neuroradiologic experiences, evaluating phantoms of known volume (0.3, 0.9 and 1.62 ml) and healthy subjects (26 to 38 years; overall 135 volumetries).

Results

High accuracy of the volumetry was shown by phantom analysis; measurement errors were <4% with a mean error of 2.2%. In vitro, reproducibility was also promising with intra-observer variability of 0.7% for observer 1 and 0.3% for observers 2 and 3; mean inter-observer variability was in vitro 1.2%. In vivo, scan–rescan, intra-observer and inter-observer variability showed mean values of 3.2%, 1.8% and 3.3%, respectively. Unifactorial analysis of variance demonstrated no significant differences between pituitary volumes for various MR scans or software calculations in the healthy study groups (p > 0.05).

Conclusion

The analysed semi-automatic MR volumetry of the pituitary gland is a valid, reliable and fast technique. Possible clinical applications are hyperplasia or atrophy of the gland in pathological circumstances either by a single assessment or by monitoring in follow-up studies.

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Abbreviations

CT:

Computer tomography

MRI:

Magnetic resonance imaging

CAD:

Computer-assisted diagnosis

SE:

Spin echo

MPRAGE:

Magnetised prepared rapid gradient echo

MPR:

Multiplanar reconstructed

IWT:

Interactive watershed transform

SD:

Standard deviation

ME:

Measurement error

CV:

Coefficient of variation

SEM:

Standard error of the mean

ANOVA:

Analysis of variance

GE:

Gradient echo

SNR:

Signal-to-noise ratio

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Conflict of interest statement

We declare that we have no conflict of interest.

Author information

Authors and Affiliations

  1. Department of Radiology, Charité University Medicine Berlin, Campus Virchow Clinic, Augustenburger Platz 1, 13353, Berlin, Germany

    Diane M. Renz

  2. Fraunhofer MEVIS, Institute for Medical Image Computing, Universitaetsallee 29, 28359, Bremen, Germany

    Horst K. Hahn & Jan Rexilius

  3. Institute of Diagnostic and Interventional Radiology, Department of Neuroradiology, Friedrich-Schiller-University, Jena University Hospital, Erlanger Allee 101, 07740, Jena, Germany

    Peter Schmidt

  4. MR- and PET/CT Centre Bremen, Sankt-Jürgen-Str. 1, 28177, Bremen, Germany

    Markus Lentschig

  5. Department of Internal Medicine III, Friedrich-Schiller-University, Jena University Hospital, Erlanger Allee 101, 07740, Jena, Germany

    Alexander Pfeil

  6. Department of Radiology, St. Georg Clinic Leipzig, Hospital Hubertusburg, 04779, Wermsdorf, Germany

    Dieter Sauner

  7. Department of Radiology and Neuroradiology, Asklepios Clinic Brandenburg, Anton-Saefkow-Allee 2, 14772, Brandenburg an der Havel, Germany

    Clemens Fitzek

  8. Institute of Diagnostic and Interventional Radiology, Department of Pediatric Radiology, Friedrich-Schiller-University, Jena University Hospital, Kochstr. 2, 07740, Jena, Germany

    Hans-Joachim Mentzel

  9. Institute of Diagnostic and Interventional Radiology, Friedrich-Schiller-University, Jena University Hospital, Erlanger Allee 101, 07740, Jena, Germany

    Werner A. Kaiser

  10. Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Friedrich-Schiller-University, Jena University Hospital, Philosophenweg 3, 07743, Jena, Germany

    Jürgen R. Reichenbach

  11. Institute of Diagnostic and Interventional Radiology, SRH Clinic Gera, Str. des Friedens 122, 07548, Gera, Germany

    Joachim Böttcher

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  1. Diane M. Renz
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  2. Horst K. Hahn
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  10. Werner A. Kaiser
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Correspondence to Diane M. Renz.

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Renz, D.M., Hahn, H.K., Schmidt, P. et al. Accuracy and reproducibility of a novel semi-automatic segmentation technique for MR volumetry of the pituitary gland. Neuroradiology 53, 233–244 (2011). https://doi.org/10.1007/s00234-010-0727-0

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