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Evaluation Of Semiautomated Measurements Of Mesothelioma Tumor Thickness On CT Scans.

S. Armato, G. Oxnard, M. Kocherginsky, N. Vogelzang, H. Kindler, H. MacMahon
Published 2005 · Computer Science, Medicine

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RATIONALE AND OBJECTIVES To evaluate the clinical acceptability of semiautomated methods for the measurement of mesothelioma tumor thickness in computed tomography (CT) scans. MATERIALS AND METHODS A computer interface was developed to allow the acquisition of semiautomated mesothelioma tumor thickness measurements, which require the manual selection of a point along the outer margin of the tumor in a CT section. After application of an automated lung segmentation method, the computer automatically identifies a corresponding point along the inner margin of the tumor (as represented by the lung boundary), constructs a line segment between the manually selected outer tumor margin point and the computer-determined inner tumor margin point, and computes tumor thickness as the length of this line segment. Three radiologists and oncologists independently reviewed line segments representing the semiautomated measurements generated by three different algorithms at 134 measurement sites in the CT scans of 22 mesothelioma patients. The observers either accepted a measurement line segment or modified it through the interface. Differences between the initial semiautomated measurements and the measurements as modified by the observers were analyzed. RESULTS The frequency with which observers accepted the semiautomated measurements without modification was as high as 86%. Of all measurements across all observers and methods (1,206 measurements), 89% were changed by 2 mm or less. CONCLUSION We have developed semiautomated methods to measure mesothelioma tumor thickness. The potential of these methods has been demonstrated through an observer study. We expect these methods to become important tools for the efficient quantification of tumor extent.
This paper references
Measuring response in solid tumors: unidimensional versus bidimensional measurement.
K. James (1999)
Demographic patterns for mesothelioma in the United States.
R. Connelly (1987)
Malignant pleural mesothelioma: CT manifestations in 50 cases.
A. Kawashima (1990)
Reporting results of cancer treatment
A. Miller (1981)
Evaluation of tumor measurements in oncology: use of film-based and electronic techniques.
L. Schwartz (2000)
Malignant pleural mesothelioma: the spectrum of manifestations on CT in 70 cases.
C. Ng (1999)
Automated detection of lung nodules in CT scans: preliminary results.
S. Armato (2001)
New Guidelines to Evaluate the Response to Treatment in Solid Tumors.
P. Therasse (2000)
Cancer : Principles and Practice of Oncology
V. Devita (1982)
CT in differential diagnosis of diffuse pleural disease.
A. Leung (1990)
The role of imaging in malignant pleural mesothelioma.
E. Marom (2002)
Measurement of mesothelioma on thoracic CT scans: a comparison of manual and computer-assisted techniques.
S. Armato (2004)
Computed tomography features in malignant pleural mesothelioma and other commonly seen pleural diseases.
M. Metintas (2002)
Staging of malignant pleural mesothelioma: comparison of CT and MR imaging.
R. Heelan (1999)
Phase III study of pemetrexed in combination with cisplatin versus cisplatin alone in patients with malignant pleural mesothelioma.
N. Vogelzang (2003)
Automated lung segmentation for thoracic CT impact on computer-aided diagnosis.
S. Armato (2004)

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Tumor invasion depth is a useful pathologic assessment for predicting outcomes in cervical squamous cell carcinoma after neoadjuvant radiotherapy
Yang Lv (2015)
Advances in mesothelioma imaging and implications for surgical management
K. Blyth (2018)
Assessment of tumor response in malignant pleural mesothelioma.
G. Ceresoli (2007)
Treatment of malignant pleural mesothelioma: current status and future directions
P. Zucali (2011)
Imaging of mesothelioma.
R. Gill (2011)
Revised Modified Response Evaluation Criteria in Solid Tumors for Assessment of Response in Malignant Pleural Mesothelioma (Version 1.1)
S. Armato (2018)
18F-FDG PET/CT in therapy response and in predicting responders or non-responders in malignant pleural mesothelioma patients, by using semi-quantitative mRECIST and EORTC criteria.
A. Niccoli Asabella (2018)
Computer-Assisted Diagnosis for Early Stage Pleural Mesothelioma: Automated Extraction of Pleura to Detect Pleural Thickenings from Thoracic CT Images
K. Chaisaowong (2007)
Lung Volume Measurements as a Surrogate Marker for Patient Response in Malignant Pleural Mesothelioma
Z. Labby (2013)
Future developments in the management of malignant pleural mesothelioma
Paolo Andrea Zucali (2009)
Computer-assisted diagnosis for early stage pleural mesothelioma: towards automated detection and quantitative assessment of pleural thickening from thoracic CT images.
K. Chaisaowong (2007)
3D-Erkennung, Analyse und Visualisierung pleuraler Verdickungen in CT-Daten
P. Jäger (2006)
Interactive Modeling and Evaluation of Tumor Growth
J. Scharcanski (2009)
[The future of computer-aided diagnostics in chest computed tomography].
Andrei E Nikolaev (2019)
Current trends in radiologic management of malignant pleural mesothelioma.
R. Gill (2009)
1 – Imaging Tumors of the Lung and Pleura
E. Marom (2010)
Computer-assisted volumetric tumour assessment for the evaluation of patient response in malignant pleural mesothelioma
J. A. Schnabel (2011)
Progress in the Management of Malignant Pleural Mesothelioma in 2017
Amanda J McCambridge (2018)
Modeling of mesothelioma growth demonstrates weaknesses of current response criteria.
G. Oxnard (2006)
Variability in mesothelioma tumor response classification.
S. Armato (2006)
The IASLC Mesothelioma Staging Project: Proposals for Revisions of the N Descriptors in the Forthcoming Eighth Edition of the TNM Classification for Pleural Mesothelioma
D. Rice (2016)
The IASLC Mesothelioma Staging Project: Proposals for Revisions of the T Descriptors in the Forthcoming Eighth Edition of the TNM Classification for Pleural Mesothelioma
A. Nowak (2016)
Measuring Malignant Pleural Mesothelioma
A. Nowak (2019)
Current state and future directions of pleural mesothelioma imaging.
S. Armato (2008)
Malignant pleural mesothelioma segmentation for photodynamic therapy planning
W. Brahim (2018)
Anniversary paper: History and status of CAD and quantitative image analysis: the role of Medical Physics and AAPM.
M. Giger (2008)
Computer-aided volumetric assessment of malignant pleural mesothelioma on CT using a random walk-based method
Mitchell Chen (2016)
State of the Art : Advances in Malignant Pleural Mesothelioma in 2017
Amanda J McCambridge (2018)
Three-dimensional evaluation of chemotherapy response in malignant pleural mesothelioma.
G. Ak (2010)
Software System for the Computer-Assisted Diagnosis or Early Stage Pleural Mesothelioma
K. Chaisaowong (2008)
A Multicenter Study of Volumetric Computed Tomography for Staging Malignant Pleural Mesothelioma.
V. Rusch (2016)
The influence of initial outlines on manual segmentation.
W. Sensakovic (2010)
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