Limits...
Accuracy of estimation of graft size for living-related liver transplantation: first results of a semi-automated interactive software for CT-volumetry.

Mokry T, Bellemann N, Müller D, Lorenzo Bermejo J, Klauß M, Stampfl U, Radeleff B, Schemmer P, Kauczor HU, Sommer CM - PLoS ONE (2014)

Bottom Line: CT-volumetry was performed using a semi-automated interactive software (P), and compared with a manual commercial software (TR).Inter-observer agreement showed a bias of 1.8 ml for TR with vessels, 5.4 ml for P with vessels, and 4.6 ml for P without vessels.For the degree of manual correction, speed for completion and overall intuitiveness, scale values were 2.6±0.8, 2.4±0.5 and 2.

View Article: PubMed Central - PubMed

Affiliation: Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany.

ABSTRACT

Objectives: To evaluate accuracy of estimated graft size for living-related liver transplantation using a semi-automated interactive software for CT-volumetry.

Materials and methods: Sixteen donors for living-related liver transplantation (11 male; mean age: 38.2±9.6 years) underwent contrast-enhanced CT prior to graft removal. CT-volumetry was performed using a semi-automated interactive software (P), and compared with a manual commercial software (TR). For P, liver volumes were provided either with or without vessels. For TR, liver volumes were provided always with vessels. Intraoperative weight served as reference standard. Major study goals included analyses of volumes using absolute numbers, linear regression analyses and inter-observer agreements. Minor study goals included the description of the software workflow: degree of manual correction, speed for completion, and overall intuitiveness using five-point Likert scales: 1--markedly lower/faster/higher for P compared with TR, 2--slightly lower/faster/higher for P compared with TR, 3--identical for P and TR, 4--slightly lower/faster/higher for TR compared with P, and 5--markedly lower/faster/higher for TR compared with P.

Results: Liver segments II/III, II-IV and V-VIII served in 6, 3, and 7 donors as transplanted liver segments. Volumes were 642.9±368.8 ml for TR with vessels, 623.8±349.1 ml for P with vessels, and 605.2±345.8 ml for P without vessels (P<0.01). Regression equations between intraoperative weights and volumes were y = 0.94x+30.1 (R2 = 0.92; P<0.001) for TR with vessels, y = 1.00x+12.0 (R2 = 0.92; P<0.001) for P with vessels, and y = 1.01x+28.0 (R2 = 0.92; P<0.001) for P without vessels. Inter-observer agreement showed a bias of 1.8 ml for TR with vessels, 5.4 ml for P with vessels, and 4.6 ml for P without vessels. For the degree of manual correction, speed for completion and overall intuitiveness, scale values were 2.6±0.8, 2.4±0.5 and 2.

Conclusions: CT-volumetry performed with P can predict accurately graft size for living-related liver transplantation while improving workflow compared with TR.

Show MeSH

Related in: MedlinePlus

Semi-automated Interactive Software for CT-volumetry (P) – Manual Positioning of 9 Anatomical Landmarks to Define the Segments of Couinaud (Schematic Illustration; Courtesy of Philips Healthcare Germany, Hamburg, Germany).A first bifurcation of the right portal vein (black circle). B inferior caval vein (black circle). C right hepatic vein (black circle). D middle hepatic vein (black circle). E left hepatic vein (black circle). F superficial ligamentum venosum (black circle). G deep ligamentum venosum (black circle). H end of left portal vein (black circle). I left liver tip (black circle) Note: after automated outline of the entire liver with correction of false-positive and false-negative extractions, and then after manual positioning of the 9 anatomical landmarks, volumes of transplanted liver segments are obtained.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4201494&req=5

pone-0110201-g001: Semi-automated Interactive Software for CT-volumetry (P) – Manual Positioning of 9 Anatomical Landmarks to Define the Segments of Couinaud (Schematic Illustration; Courtesy of Philips Healthcare Germany, Hamburg, Germany).A first bifurcation of the right portal vein (black circle). B inferior caval vein (black circle). C right hepatic vein (black circle). D middle hepatic vein (black circle). E left hepatic vein (black circle). F superficial ligamentum venosum (black circle). G deep ligamentum venosum (black circle). H end of left portal vein (black circle). I left liver tip (black circle) Note: after automated outline of the entire liver with correction of false-positive and false-negative extractions, and then after manual positioning of the 9 anatomical landmarks, volumes of transplanted liver segments are obtained.

Mentions: Transverse images of the portal-venous phase (slice thickness of 3 mm and increment of 1 mm) were used for CT-volumetry. Two different software tools were used and compared: a semi-automated interactive commercial software called “IntelliSpace Portal Liver Analysis application” (Philips Medical Systems, Best, The Netherland) (P) and a manual commercial software (TR; Aquarius iNtuition; TeraRecon, Foster City, USA). For P, the images were uploaded, and then the outline of the entire liver was determined between liver tissue and surrounding fatty tissue. The algorithm responsible for the segmentation of the liver in contrast-emhanced CT images belongs to the family of variational approaches. It is based on a deformable mesh guided by Hounsfield units as well as surrounding anatomical structures. The algorithm is composed of four different steps. (1) Surrounding anatomical structures are coarsely segmented to provide spatial context. (2) A region inside the liver is localized. (3) Liver tissue likelihood is estimated and refined as the mesh evolves. (4) The mesh is evolved based on likelihood and proximity to surrounding structures. False-positive and false-negative extractions could be corrected using manual correction tools. After manual positioning of 9 anatomical landmarks proposed by the software using the “work-me-through” tool in the “landmark selection mode”, the segments of Couinaud were then calculated automatically, and volumes of transplanted liver segments were obtained subsequently (Fig. 1). Since the opportunity to segment automatically liver veins and portal veins between liver tissue and vasculature, P provided liver volumes with and without vessels. For TR, the images were uploaded in the ‘CTA Abdomen’ workflow. Using the free region-of-interest (ROI) tool, the outline of the entire liver and transplanted liver segments were set manually on every image slice, and respective liver volumes were provided always with vessels. A forth study group with TR without vessels was not performed since the proceeding would have been extremely time consuming.


Accuracy of estimation of graft size for living-related liver transplantation: first results of a semi-automated interactive software for CT-volumetry.

Mokry T, Bellemann N, Müller D, Lorenzo Bermejo J, Klauß M, Stampfl U, Radeleff B, Schemmer P, Kauczor HU, Sommer CM - PLoS ONE (2014)

Semi-automated Interactive Software for CT-volumetry (P) – Manual Positioning of 9 Anatomical Landmarks to Define the Segments of Couinaud (Schematic Illustration; Courtesy of Philips Healthcare Germany, Hamburg, Germany).A first bifurcation of the right portal vein (black circle). B inferior caval vein (black circle). C right hepatic vein (black circle). D middle hepatic vein (black circle). E left hepatic vein (black circle). F superficial ligamentum venosum (black circle). G deep ligamentum venosum (black circle). H end of left portal vein (black circle). I left liver tip (black circle) Note: after automated outline of the entire liver with correction of false-positive and false-negative extractions, and then after manual positioning of the 9 anatomical landmarks, volumes of transplanted liver segments are obtained.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4201494&req=5

pone-0110201-g001: Semi-automated Interactive Software for CT-volumetry (P) – Manual Positioning of 9 Anatomical Landmarks to Define the Segments of Couinaud (Schematic Illustration; Courtesy of Philips Healthcare Germany, Hamburg, Germany).A first bifurcation of the right portal vein (black circle). B inferior caval vein (black circle). C right hepatic vein (black circle). D middle hepatic vein (black circle). E left hepatic vein (black circle). F superficial ligamentum venosum (black circle). G deep ligamentum venosum (black circle). H end of left portal vein (black circle). I left liver tip (black circle) Note: after automated outline of the entire liver with correction of false-positive and false-negative extractions, and then after manual positioning of the 9 anatomical landmarks, volumes of transplanted liver segments are obtained.
Mentions: Transverse images of the portal-venous phase (slice thickness of 3 mm and increment of 1 mm) were used for CT-volumetry. Two different software tools were used and compared: a semi-automated interactive commercial software called “IntelliSpace Portal Liver Analysis application” (Philips Medical Systems, Best, The Netherland) (P) and a manual commercial software (TR; Aquarius iNtuition; TeraRecon, Foster City, USA). For P, the images were uploaded, and then the outline of the entire liver was determined between liver tissue and surrounding fatty tissue. The algorithm responsible for the segmentation of the liver in contrast-emhanced CT images belongs to the family of variational approaches. It is based on a deformable mesh guided by Hounsfield units as well as surrounding anatomical structures. The algorithm is composed of four different steps. (1) Surrounding anatomical structures are coarsely segmented to provide spatial context. (2) A region inside the liver is localized. (3) Liver tissue likelihood is estimated and refined as the mesh evolves. (4) The mesh is evolved based on likelihood and proximity to surrounding structures. False-positive and false-negative extractions could be corrected using manual correction tools. After manual positioning of 9 anatomical landmarks proposed by the software using the “work-me-through” tool in the “landmark selection mode”, the segments of Couinaud were then calculated automatically, and volumes of transplanted liver segments were obtained subsequently (Fig. 1). Since the opportunity to segment automatically liver veins and portal veins between liver tissue and vasculature, P provided liver volumes with and without vessels. For TR, the images were uploaded in the ‘CTA Abdomen’ workflow. Using the free region-of-interest (ROI) tool, the outline of the entire liver and transplanted liver segments were set manually on every image slice, and respective liver volumes were provided always with vessels. A forth study group with TR without vessels was not performed since the proceeding would have been extremely time consuming.

Bottom Line: CT-volumetry was performed using a semi-automated interactive software (P), and compared with a manual commercial software (TR).Inter-observer agreement showed a bias of 1.8 ml for TR with vessels, 5.4 ml for P with vessels, and 4.6 ml for P without vessels.For the degree of manual correction, speed for completion and overall intuitiveness, scale values were 2.6±0.8, 2.4±0.5 and 2.

View Article: PubMed Central - PubMed

Affiliation: Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany.

ABSTRACT

Objectives: To evaluate accuracy of estimated graft size for living-related liver transplantation using a semi-automated interactive software for CT-volumetry.

Materials and methods: Sixteen donors for living-related liver transplantation (11 male; mean age: 38.2±9.6 years) underwent contrast-enhanced CT prior to graft removal. CT-volumetry was performed using a semi-automated interactive software (P), and compared with a manual commercial software (TR). For P, liver volumes were provided either with or without vessels. For TR, liver volumes were provided always with vessels. Intraoperative weight served as reference standard. Major study goals included analyses of volumes using absolute numbers, linear regression analyses and inter-observer agreements. Minor study goals included the description of the software workflow: degree of manual correction, speed for completion, and overall intuitiveness using five-point Likert scales: 1--markedly lower/faster/higher for P compared with TR, 2--slightly lower/faster/higher for P compared with TR, 3--identical for P and TR, 4--slightly lower/faster/higher for TR compared with P, and 5--markedly lower/faster/higher for TR compared with P.

Results: Liver segments II/III, II-IV and V-VIII served in 6, 3, and 7 donors as transplanted liver segments. Volumes were 642.9±368.8 ml for TR with vessels, 623.8±349.1 ml for P with vessels, and 605.2±345.8 ml for P without vessels (P<0.01). Regression equations between intraoperative weights and volumes were y = 0.94x+30.1 (R2 = 0.92; P<0.001) for TR with vessels, y = 1.00x+12.0 (R2 = 0.92; P<0.001) for P with vessels, and y = 1.01x+28.0 (R2 = 0.92; P<0.001) for P without vessels. Inter-observer agreement showed a bias of 1.8 ml for TR with vessels, 5.4 ml for P with vessels, and 4.6 ml for P without vessels. For the degree of manual correction, speed for completion and overall intuitiveness, scale values were 2.6±0.8, 2.4±0.5 and 2.

Conclusions: CT-volumetry performed with P can predict accurately graft size for living-related liver transplantation while improving workflow compared with TR.

Show MeSH
Related in: MedlinePlus