Literature DB >> 28097499

Automating Perforator Flap MRA and CTA Reporting.

Christopher J Lange1,2, Nanda Deepa Thimmappa1, Srikanth R Boddu1, Silvina P Dutruel1, Mengchao Pei1, Zerwa Farooq1, Ashkan Heshmatzadeh Behzadi1, Yi Wang1, Ramin Zabih1,2,3, Martin R Prince4,5.   

Abstract

Surgical breast reconstruction after mastectomy requires precise perforator coordinates/dimensions, perforator course, and fat volume in a radiology report. Automatic perforator reporting software was implemented as an OsiriX Digital Imaging and Communications in Medicine (DICOM) viewer plugin. For perforator analysis, the user identifies a reference point (e.g., umbilicus) and marks each perforating artery/vein bundle with multiple region of interest (ROI) points along its course beginning at the muscle-fat interface. Computations using these points and analysis of image data produce content for the report. Post-processing times were compared against conventional/manual methods using de-identified images of 26 patients with surgically confirmed accuracy of perforator locations and caliber. The time from loading source images to completion of report was measured. Significance of differences in mean processing times for this automated approach versus the conventional/manual approach was assessed using a paired t test. The mean conventional reporting time for our radiologists was 76 ± 27 min (median 65 min) compared with 25 ± 6 min (median 25 min) using our OsiriX plugin (p < 0.01). The conventional approach had three reports with transcription errors compared to none with the OsiriX plugin. Otherwise, the reports were similar. In conclusion, automated reporting of perforator magnetic resonance angiography (MRA) studies is faster compared with the standard, manual approach, and transcription errors which are eliminated.

Entities:  

Keywords:  Autologous flap; Automated reporting; Breast reconstruction; Computed tomographic angiography; Magnetic resonance angiography; Perforator

Mesh:

Year:  2017        PMID: 28097499      PMCID: PMC5422233          DOI: 10.1007/s10278-017-9943-z

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  12 in total

1.  Three-dimensional prediction of free-flap volume in autologous breast reconstruction by CT angiography imaging.

Authors:  Maximilian Eder; Stefan Raith; Jalil Jalali; Daniel Müller; Yves Harder; Martin Dobritz; Nikolaos A Papadopulos; Hans-Günther Machens; Laszlo Kovacs
Journal:  Int J Comput Assist Radiol Surg       Date:  2013-10-05       Impact factor: 2.924

2.  Assessment of DICOM Viewers Capable of Loading Patient-specific 3D Models Obtained by Different Segmentation Platforms in the Operating Room.

Authors:  Giuseppe Lo Presti; Marina Carbone; Damiano Ciriaci; Daniele Aramini; Mauro Ferrari; Vincenzo Ferrari
Journal:  J Digit Imaging       Date:  2015-10       Impact factor: 4.056

3.  Comparative study of software techniques for 3D mapping of perforators in deep inferior epigastric artery perforator flap planning.

Authors:  Michael P Chae; David J Hunter-Smith; Warren Matthew Rozen
Journal:  Gland Surg       Date:  2016-04

4.  Gadofosveset trisodium-enhanced abdominal perforator MRA.

Authors:  Zhitong Zou; Hwayoung Kate Lee; Joshua L Levine; David T Greenspun; Robert J Allen; Julie Vasile; Christine Rohde; Martin R Prince
Journal:  J Magn Reson Imaging       Date:  2011-10-26       Impact factor: 4.813

5.  Multidetector-row computed tomography in the planning of abdominal perforator flaps.

Authors:  J Masia; J A Clavero; J R Larrañaga; X Alomar; G Pons; P Serret
Journal:  J Plast Reconstr Aesthet Surg       Date:  2006-02-28       Impact factor: 2.740

6.  Preliminary results using a newly developed projection method to visualize vascular anatomy prior to DIEP flap breast reconstruction.

Authors:  S Hummelink; M Hameeteman; Y Hoogeveen; C H Slump; D J O Ulrich; L J Schultze Kool
Journal:  J Plast Reconstr Aesthet Surg       Date:  2014-11-27       Impact factor: 2.740

7.  Modifying techniques in deep inferior epigastric artery perforator flap harvest with the use of preoperative imaging.

Authors:  Warren M Rozen; Mark W Ashton
Journal:  ANZ J Surg       Date:  2009-09       Impact factor: 1.872

8.  Autologous breast reconstruction: preoperative magnetic resonance angiography for perforator flap vessel mapping.

Authors:  Mukta D Agrawal; Nanda Deepa Thimmappa; Julie V Vasile; Joshua L Levine; Robert J Allen; David T Greenspun; Christina Y Ahn; Constance M Chen; Sandeep S Hedgire; Martin R Prince
Journal:  J Reconstr Microsurg       Date:  2014-05-29       Impact factor: 2.873

9.  Rapid development of image analysis research tools: Bridging the gap between researcher and clinician with pyOsiriX.

Authors:  Matthew D Blackledge; David J Collins; Dow-Mu Koh; Martin O Leach
Journal:  Comput Biol Med       Date:  2015-12-18       Impact factor: 4.589

10.  An open source software for analysis of dynamic contrast enhanced magnetic resonance images: UMMPerfusion revisited.

Authors:  Frank G Zöllner; Markus Daab; Steven P Sourbron; Lothar R Schad; Stefan O Schoenberg; Gerald Weisser
Journal:  BMC Med Imaging       Date:  2016-01-14       Impact factor: 1.930

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  3 in total

1.  Automatic detection of perforator vessels using infrared thermography in reconstructive surgery.

Authors:  Michael Unger; Miriam Markfort; Dirk Halama; Claire Chalopin
Journal:  Int J Comput Assist Radiol Surg       Date:  2018-12-05       Impact factor: 2.924

2.  A Review of Objective Measurement of Flap Volume in Reconstructive Surgery.

Authors:  Alain Joe Azzi; Roy Hilzenrat; Alex Viezel-Mathieu; Thomas Hemmerling; Mirko Gilardino
Journal:  Plast Reconstr Surg Glob Open       Date:  2018-05-15

3.  Automatic detection of perforators for microsurgical reconstruction.

Authors:  Carlos Mavioso; Ricardo J Araújo; Hélder P Oliveira; João C Anacleto; Maria Antónia Vasconcelos; David Pinto; Pedro F Gouveia; Celeste Alves; Fátima Cardoso; Jaime S Cardoso; Maria João Cardoso
Journal:  Breast       Date:  2020-01-12       Impact factor: 4.380

  3 in total

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