Literature DB >> 33236827

Methodological approach to create an atlas using a commercial auto-contouring software.

Marta Casati1, Stefano Piffer2,3, Silvia Calusi2, Livia Marrazzo1, Gabriele Simontacchi4, Vanessa Di Cataldo5, Daniela Greto4, Isacco Desideri2, Marco Vernaleone4, Giulio Francolini4, Lorenzo Livi2, Stefania Pallotta2.   

Abstract

PURPOSE: The aim of this work was to establish a methodological approach for creation and optimization of an atlas for auto-contouring, using the commercial software MIM MAESTRO (MIM Software Inc. Cleveland OH).
METHODS: A computed tomography (CT) male pelvis atlas was created and optimized to evaluate how different tools and options impact on the accuracy of automatic segmentation. Pelvic lymph nodes (PLN), rectum, bladder, and femurs of 55 subjects were reviewed for consistency by a senior consultant radiation oncologist with 15 yr of experience. Several atlas and workflow options were tuned to optimize the accuracy of auto-contours. The deformable image registration (DIR), the finalization method, the k number of atlas best matching subjects, and several post-processing options were studied. To test our atlas performances, automatic and reference manual contours of 20 test subjects were statistically compared based on dice similarity coefficient (DSC) and mean distance to agreement (MDA) indices. The effect of field of view (FOV) reduction on auto-contouring time was also investigated.
RESULTS: With the optimized atlas and workflow, DSC and MDA median values of bladder, rectum, PLN, and femurs were 0.91 and 1.6 mm, 0.85 and 1.6 mm, 0.85 and 1.8 mm, and 0.96 and 0.5 mm, respectively. Auto-contouring time was more than halved by strictly cropping the FOV of the subject to be contoured to the pelvic region.
CONCLUSION: A statistically significant improvement of auto-contours accuracy was obtained using our atlas and optimized workflow instead of the MIM Software pelvic atlas.
© 2020 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Entities:  

Keywords:  CT; atlas; automatic contouring; methodological approach; pelvis; radiotherapy; segmentation

Mesh:

Year:  2020        PMID: 33236827      PMCID: PMC7769405          DOI: 10.1002/acm2.13093

Source DB:  PubMed          Journal:  J Appl Clin Med Phys        ISSN: 1526-9914            Impact factor:   2.102


  30 in total

1.  Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation.

Authors:  Simon K Warfield; Kelly H Zou; William M Wells
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2.  Accuracy Validation of an Automated Method for Prostate Segmentation in Magnetic Resonance Imaging.

Authors:  Maysam Shahedi; Derek W Cool; Glenn S Bauman; Matthew Bastian-Jordan; Aaron Fenster; Aaron D Ward
Journal:  J Digit Imaging       Date:  2017-12       Impact factor: 4.056

3.  Computer-assisted, atlas-based segmentation for target volume delineation in whole pelvic IMRT for prostate cancer.

Authors:  Sunanda Pejavar; Sue S Yom; Andrew Hwang; Joycelyn Speight; Alexander Gottschalk; I-Chow Hsu; Mack Roach; Ping Xia
Journal:  Technol Cancer Res Treat       Date:  2012-12-26

4.  Groupwise segmentation with multi-atlas joint label fusion.

Authors:  Hongzhi Wang; Paul A Yushkevich
Journal:  Med Image Comput Comput Assist Interv       Date:  2013

Review 5.  Vision 20/20: perspectives on automated image segmentation for radiotherapy.

Authors:  Gregory Sharp; Karl D Fritscher; Vladimir Pekar; Marta Peroni; Nadya Shusharina; Harini Veeraraghavan; Jinzhong Yang
Journal:  Med Phys       Date:  2014-05       Impact factor: 4.071

6.  Clinical evaluation of atlas and deep learning based automatic contouring for lung cancer.

Authors:  Tim Lustberg; Johan van Soest; Mark Gooding; Devis Peressutti; Paul Aljabar; Judith van der Stoep; Wouter van Elmpt; Andre Dekker
Journal:  Radiother Oncol       Date:  2017-12-05       Impact factor: 6.280

7.  Intra- and inter-observer variability in contouring prostate and seminal vesicles: implications for conformal treatment planning.

Authors:  C Fiorino; M Reni; A Bolognesi; G M Cattaneo; R Calandrino
Journal:  Radiother Oncol       Date:  1998-06       Impact factor: 6.280

8.  Comparison of Automated Atlas-Based Segmentation Software for Postoperative Prostate Cancer Radiotherapy.

Authors:  Grégory Delpon; Alexandre Escande; Timothée Ruef; Julien Darréon; Jimmy Fontaine; Caroline Noblet; Stéphane Supiot; Thomas Lacornerie; David Pasquier
Journal:  Front Oncol       Date:  2016-08-03       Impact factor: 6.244

9.  Automatic segmentation of male pelvic anatomy on computed tomography images: a comparison with multiple observers in the context of a multicentre clinical trial.

Authors:  John P Geraghty; Garry Grogan; Martin A Ebert
Journal:  Radiat Oncol       Date:  2013-04-30       Impact factor: 3.481

10.  Clinical evaluation of multi-atlas based segmentation of lymph node regions in head and neck and prostate cancer patients.

Authors:  Carl Sjöberg; Martin Lundmark; Christoffer Granberg; Silvia Johansson; Anders Ahnesjö; Anders Montelius
Journal:  Radiat Oncol       Date:  2013-10-03       Impact factor: 3.481

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  3 in total

1.  The clinical evaluation of atlas-based auto-segmentation for automatic contouring during cervical cancer radiotherapy.

Authors:  Yi Li; Wenjing Wu; Yuchen Sun; Dequan Yu; Yuemei Zhang; Long Wang; Yao Wang; Xiaozhi Zhang; Yongkai Lu
Journal:  Front Oncol       Date:  2022-08-02       Impact factor: 5.738

2.  Comparison of Eclipse Smart Segmentation and MIM Atlas Segment for liver delineation for yttrium-90 selective internal radiation therapy.

Authors:  Jun Li; Rani Anne
Journal:  J Appl Clin Med Phys       Date:  2022-06-15       Impact factor: 2.243

3.  Clinical validation of an automatic atlas-based segmentation tool for male pelvis CT images.

Authors:  Marta Casati; Stefano Piffer; Silvia Calusi; Livia Marrazzo; Gabriele Simontacchi; Vanessa Di Cataldo; Daniela Greto; Isacco Desideri; Marco Vernaleone; Giulio Francolini; Lorenzo Livi; Stefania Pallotta
Journal:  J Appl Clin Med Phys       Date:  2022-01-22       Impact factor: 2.102

  3 in total

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