Value of multidetector computed tomography image segmentation for preoperative planning in general surgery

Vincenzo Ferrari, Marina Carbone, Carla Cappelli, Luigi Boni, Franca Melfi, Mauro Ferrari, Franco Mosca, Andrea Pietrabissa

Research output: Contribution to journalArticle

28 Citations (Scopus)

Abstract

Background: Using practical examples, this report aims to highlight the clinical value of patient-specific three-dimensional (3D) models, obtained segmenting multidetector computed tomography (MDCT) images, for preoperative planning in general surgery. Methods: In this study, segmentation and 3D model generation were performed using a semiautomatic tool developed in the authors' laboratory. Their segmentation procedure is based on the neighborhood connected region-growing algorithm that, appropriately parameterized for the anatomy of interest and combined with the optimal segmentation sequence, generates good-quality 3D images coupled with facility of use. Using a touch screen monitor, manual refining can be added to segment structures unsuitable for automatic reconstruction. Three-dimensional models of 10 candidates for major general surgery procedures were presented to the operating surgeons for evaluation. A questionnaire then was administered after surgery to assess the perceived added value of the new technology. Results: The questionnaire results were very positive. The authors recorded the diffuse opinion that planning the procedure using a segmented data set allows the surgeon to plan critical interventions with better awareness of the specific patient anatomy and consequently facilitates choosing the best surgical approach. Conclusions: The benefit shown in this report supports a wider use of segmentation software in clinical practice, even taking into account the extra time and effort required to learn and use these systems.

Original languageEnglish
Pages (from-to)616-626
Number of pages11
JournalSurgical Endoscopy and Other Interventional Techniques
Volume26
Issue number3
DOIs
Publication statusPublished - Mar 2012

Fingerprint

Multidetector Computed Tomography
Anatomy
Software
Technology
Surveys and Questionnaires
Surgeons

Keywords

  • General surgery
  • Image segmentation
  • MDCT
  • Patient-specific 3D models
  • Surgical planning
  • Technology

ASJC Scopus subject areas

  • Surgery

Cite this

Value of multidetector computed tomography image segmentation for preoperative planning in general surgery. / Ferrari, Vincenzo; Carbone, Marina; Cappelli, Carla; Boni, Luigi; Melfi, Franca; Ferrari, Mauro; Mosca, Franco; Pietrabissa, Andrea.

In: Surgical Endoscopy and Other Interventional Techniques, Vol. 26, No. 3, 03.2012, p. 616-626.

Research output: Contribution to journalArticle

Ferrari, Vincenzo ; Carbone, Marina ; Cappelli, Carla ; Boni, Luigi ; Melfi, Franca ; Ferrari, Mauro ; Mosca, Franco ; Pietrabissa, Andrea. / Value of multidetector computed tomography image segmentation for preoperative planning in general surgery. In: Surgical Endoscopy and Other Interventional Techniques. 2012 ; Vol. 26, No. 3. pp. 616-626.
@article{8a23c103bce440818829c29f25be014b,
title = "Value of multidetector computed tomography image segmentation for preoperative planning in general surgery",
abstract = "Background: Using practical examples, this report aims to highlight the clinical value of patient-specific three-dimensional (3D) models, obtained segmenting multidetector computed tomography (MDCT) images, for preoperative planning in general surgery. Methods: In this study, segmentation and 3D model generation were performed using a semiautomatic tool developed in the authors' laboratory. Their segmentation procedure is based on the neighborhood connected region-growing algorithm that, appropriately parameterized for the anatomy of interest and combined with the optimal segmentation sequence, generates good-quality 3D images coupled with facility of use. Using a touch screen monitor, manual refining can be added to segment structures unsuitable for automatic reconstruction. Three-dimensional models of 10 candidates for major general surgery procedures were presented to the operating surgeons for evaluation. A questionnaire then was administered after surgery to assess the perceived added value of the new technology. Results: The questionnaire results were very positive. The authors recorded the diffuse opinion that planning the procedure using a segmented data set allows the surgeon to plan critical interventions with better awareness of the specific patient anatomy and consequently facilitates choosing the best surgical approach. Conclusions: The benefit shown in this report supports a wider use of segmentation software in clinical practice, even taking into account the extra time and effort required to learn and use these systems.",
keywords = "General surgery, Image segmentation, MDCT, Patient-specific 3D models, Surgical planning, Technology",
author = "Vincenzo Ferrari and Marina Carbone and Carla Cappelli and Luigi Boni and Franca Melfi and Mauro Ferrari and Franco Mosca and Andrea Pietrabissa",
year = "2012",
month = "3",
doi = "10.1007/s00464-011-1920-x",
language = "English",
volume = "26",
pages = "616--626",
journal = "Surgical Endoscopy",
issn = "0930-2794",
publisher = "Springer New York",
number = "3",

}

TY - JOUR

T1 - Value of multidetector computed tomography image segmentation for preoperative planning in general surgery

AU - Ferrari, Vincenzo

AU - Carbone, Marina

AU - Cappelli, Carla

AU - Boni, Luigi

AU - Melfi, Franca

AU - Ferrari, Mauro

AU - Mosca, Franco

AU - Pietrabissa, Andrea

PY - 2012/3

Y1 - 2012/3

N2 - Background: Using practical examples, this report aims to highlight the clinical value of patient-specific three-dimensional (3D) models, obtained segmenting multidetector computed tomography (MDCT) images, for preoperative planning in general surgery. Methods: In this study, segmentation and 3D model generation were performed using a semiautomatic tool developed in the authors' laboratory. Their segmentation procedure is based on the neighborhood connected region-growing algorithm that, appropriately parameterized for the anatomy of interest and combined with the optimal segmentation sequence, generates good-quality 3D images coupled with facility of use. Using a touch screen monitor, manual refining can be added to segment structures unsuitable for automatic reconstruction. Three-dimensional models of 10 candidates for major general surgery procedures were presented to the operating surgeons for evaluation. A questionnaire then was administered after surgery to assess the perceived added value of the new technology. Results: The questionnaire results were very positive. The authors recorded the diffuse opinion that planning the procedure using a segmented data set allows the surgeon to plan critical interventions with better awareness of the specific patient anatomy and consequently facilitates choosing the best surgical approach. Conclusions: The benefit shown in this report supports a wider use of segmentation software in clinical practice, even taking into account the extra time and effort required to learn and use these systems.

AB - Background: Using practical examples, this report aims to highlight the clinical value of patient-specific three-dimensional (3D) models, obtained segmenting multidetector computed tomography (MDCT) images, for preoperative planning in general surgery. Methods: In this study, segmentation and 3D model generation were performed using a semiautomatic tool developed in the authors' laboratory. Their segmentation procedure is based on the neighborhood connected region-growing algorithm that, appropriately parameterized for the anatomy of interest and combined with the optimal segmentation sequence, generates good-quality 3D images coupled with facility of use. Using a touch screen monitor, manual refining can be added to segment structures unsuitable for automatic reconstruction. Three-dimensional models of 10 candidates for major general surgery procedures were presented to the operating surgeons for evaluation. A questionnaire then was administered after surgery to assess the perceived added value of the new technology. Results: The questionnaire results were very positive. The authors recorded the diffuse opinion that planning the procedure using a segmented data set allows the surgeon to plan critical interventions with better awareness of the specific patient anatomy and consequently facilitates choosing the best surgical approach. Conclusions: The benefit shown in this report supports a wider use of segmentation software in clinical practice, even taking into account the extra time and effort required to learn and use these systems.

KW - General surgery

KW - Image segmentation

KW - MDCT

KW - Patient-specific 3D models

KW - Surgical planning

KW - Technology

UR - http://www.scopus.com/inward/record.url?scp=84857057998&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84857057998&partnerID=8YFLogxK

U2 - 10.1007/s00464-011-1920-x

DO - 10.1007/s00464-011-1920-x

M3 - Article

VL - 26

SP - 616

EP - 626

JO - Surgical Endoscopy

JF - Surgical Endoscopy

SN - 0930-2794

IS - 3

ER -