Literature DB >> 30219290

Evaluation of Simulated Lesions as Surrogates to Clinical Lesions for Thoracic CT Volumetry: The Results of an International Challenge.

Marthony Robins1, Jayashree Kalpathy-Cramer2, Nancy A Obuchowski3, Andrew Buckler4, Maria Athelogou5, Rudresh Jarecha6, Nicholas Petrick7, Aria Pezeshk7, Berkman Sahiner7, Ehsan Samei8.   

Abstract

RATIONALE AND
OBJECTIVES: To evaluate a new approach to establish compliance of segmentation tools with the computed tomography volumetry profile of the Quantitative Imaging Biomarker Alliance (QIBA); and determine the statistical exchangeability between real and simulated lesions through an international challenge.
MATERIALS AND METHODS: The study used an anthropomorphic phantom with 16 embedded physical lesions and 30 patient cases from the Reference Image Database to Evaluate Therapy Response with pathologically confirmed malignancies. Hybrid datasets were generated by virtually inserting simulated lesions corresponding to physical lesions into the phantom datasets using one projection-domain-based method (Method 1), two image-domain insertion methods (Methods 2 and 3), and simulated lesions corresponding to real lesions into the Reference Image Database to Evaluate Therapy Response dataset (using Method 2). The volumes of the real and simulated lesions were compared based on bias (measured mean volume differences between physical and virtually inserted lesions in phantoms as quantified by segmentation algorithms), repeatability, reproducibility, equivalence (phantom phase), and overall QIBA compliance (phantom and clinical phase).
RESULTS: For phantom phase, three of eight groups were fully QIBA compliant, and one was marginally compliant. For compliant groups, the estimated biases were -1.8 ± 1.4%, -2.5 ± 1.1%, -3 ± 1%, -1.8 ± 1.5% (±95% confidence interval). No virtual insertion method showed statistical equivalence to physical insertion in bias equivalence testing using Schuirmann's two one-sided test (±5% equivalence margin). Differences in repeatability and reproducibility across physical and simulated lesions were largely comparable (0.1%-16% and 7%-18% differences, respectively). For clinical phase, 7 of 16 groups were QIBA compliant.
CONCLUSION: Hybrid datasets yielded conclusions similar to real computed tomography datasets where phantom QIBA compliant was also compliant for hybrid datasets. Some groups deemed compliant for simulated methods, not for physical lesion measurements. The magnitude of this difference was small (<5.4%). While technical performance is not equivalent, they correlate, such that, volumetrically simulated lesions could potentially serve as practical proxies.
Copyright © 2018 The Association of University Radiologists. All rights reserved.

Entities:  

Keywords:  CT; Hybrid dataset; Lung cancer; Quantitative imaging; Segmentation; Volumetry

Mesh:

Year:  2018        PMID: 30219290      PMCID: PMC6414290          DOI: 10.1016/j.acra.2018.07.022

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  22 in total

1.  Deformation analysis to detect and quantify active lesions in three-dimensional medical image sequences.

Authors:  J P Thirion; G Calmon
Journal:  IEEE Trans Med Imaging       Date:  1999-05       Impact factor: 10.048

Review 2.  Change in lung tumor volume as a biomarker of treatment response: a critical review of the evidence.

Authors:  P D Mozley; L H Schwartz; C Bendtsen; B Zhao; N Petrick; A J Buckler
Journal:  Ann Oncol       Date:  2010-03-23       Impact factor: 32.976

3.  Comparison of 1D, 2D, and 3D nodule sizing methods by radiologists for spherical and complex nodules on thoracic CT phantom images.

Authors:  Nicholas Petrick; Hyun J Grace Kim; David Clunie; Kristin Borradaile; Robert Ford; Rongping Zeng; Marios A Gavrielides; Michael F McNitt-Gray; Z Q John Lu; Charles Fenimore; Binsheng Zhao; Andrew J Buckler
Journal:  Acad Radiol       Date:  2014-01       Impact factor: 3.173

4.  Guidelines for Management of Incidental Pulmonary Nodules Detected on CT Images: From the Fleischner Society 2017.

Authors:  Heber MacMahon; David P Naidich; Jin Mo Goo; Kyung Soo Lee; Ann N C Leung; John R Mayo; Atul C Mehta; Yoshiharu Ohno; Charles A Powell; Mathias Prokop; Geoffrey D Rubin; Cornelia M Schaefer-Prokop; William D Travis; Paul E Van Schil; Alexander A Bankier
Journal:  Radiology       Date:  2017-02-23       Impact factor: 11.105

5.  Comparison of treatment response classifications between unidimensional, bidimensional, and volumetric measurements of metastatic lung lesions on chest computed tomography.

Authors:  Lien N Tran; Matthew S Brown; Jonathan G Goldin; Xiaohong Yan; Richard C Pais; Michael F McNitt-Gray; David Gjertson; Sarah R Rogers; Denise R Aberle
Journal:  Acad Radiol       Date:  2004-12       Impact factor: 3.173

6.  Inter-Method Performance Study of Tumor Volumetry Assessment on Computed Tomography Test-Retest Data.

Authors:  Andrew J Buckler; Jovanna Danagoulian; Kjell Johnson; Adele Peskin; Marios A Gavrielides; Nicholas Petrick; Nancy A Obuchowski; Hubert Beaumont; Lubomir Hadjiiski; Rudresh Jarecha; Jan-Martin Kuhnigk; Ninad Mantri; Michael McNitt-Gray; Jan H Moltz; Gergely Nyiri; Sam Peterson; Pierre Tervé; Christian Tietjen; Etienne von Lavante; Xiaonan Ma; Samantha St Pierre; Maria Athelogou
Journal:  Acad Radiol       Date:  2015-09-14       Impact factor: 3.173

7.  The IASLC Lung Cancer Staging Project: proposals for the revision of the TNM stage groupings in the forthcoming (seventh) edition of the TNM Classification of malignant tumours.

Authors:  Peter Goldstraw; John Crowley; Kari Chansky; Dorothy J Giroux; Patti A Groome; Ramon Rami-Porta; Pieter E Postmus; Valerie Rusch; Leslie Sobin
Journal:  J Thorac Oncol       Date:  2007-08       Impact factor: 15.609

8.  New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1).

Authors:  E A Eisenhauer; P Therasse; J Bogaerts; L H Schwartz; D Sargent; R Ford; J Dancey; S Arbuck; S Gwyther; M Mooney; L Rubinstein; L Shankar; L Dodd; R Kaplan; D Lacombe; J Verweij
Journal:  Eur J Cancer       Date:  2009-01       Impact factor: 9.162

9.  Metastatic patterns of cancers: results from a large autopsy study.

Authors:  Guy Disibio; Samuel W French
Journal:  Arch Pathol Lab Med       Date:  2008-06       Impact factor: 5.534

10.  Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010.

Authors:  Rafael Lozano; Mohsen Naghavi; Kyle Foreman; Stephen Lim; Kenji Shibuya; Victor Aboyans; Jerry Abraham; Timothy Adair; Rakesh Aggarwal; Stephanie Y Ahn; Miriam Alvarado; H Ross Anderson; Laurie M Anderson; Kathryn G Andrews; Charles Atkinson; Larry M Baddour; Suzanne Barker-Collo; David H Bartels; Michelle L Bell; Emelia J Benjamin; Derrick Bennett; Kavi Bhalla; Boris Bikbov; Aref Bin Abdulhak; Gretchen Birbeck; Fiona Blyth; Ian Bolliger; Soufiane Boufous; Chiara Bucello; Michael Burch; Peter Burney; Jonathan Carapetis; Honglei Chen; David Chou; Sumeet S Chugh; Luc E Coffeng; Steven D Colan; Samantha Colquhoun; K Ellicott Colson; John Condon; Myles D Connor; Leslie T Cooper; Matthew Corriere; Monica Cortinovis; Karen Courville de Vaccaro; William Couser; Benjamin C Cowie; Michael H Criqui; Marita Cross; Kaustubh C Dabhadkar; Nabila Dahodwala; Diego De Leo; Louisa Degenhardt; Allyne Delossantos; Julie Denenberg; Don C Des Jarlais; Samath D Dharmaratne; E Ray Dorsey; Tim Driscoll; Herbert Duber; Beth Ebel; Patricia J Erwin; Patricia Espindola; Majid Ezzati; Valery Feigin; Abraham D Flaxman; Mohammad H Forouzanfar; Francis Gerry R Fowkes; Richard Franklin; Marlene Fransen; Michael K Freeman; Sherine E Gabriel; Emmanuela Gakidou; Flavio Gaspari; Richard F Gillum; Diego Gonzalez-Medina; Yara A Halasa; Diana Haring; James E Harrison; Rasmus Havmoeller; Roderick J Hay; Bruno Hoen; Peter J Hotez; Damian Hoy; Kathryn H Jacobsen; Spencer L James; Rashmi Jasrasaria; Sudha Jayaraman; Nicole Johns; Ganesan Karthikeyan; Nicholas Kassebaum; Andre Keren; Jon-Paul Khoo; Lisa Marie Knowlton; Olive Kobusingye; Adofo Koranteng; Rita Krishnamurthi; Michael Lipnick; Steven E Lipshultz; Summer Lockett Ohno; Jacqueline Mabweijano; Michael F MacIntyre; Leslie Mallinger; Lyn March; Guy B Marks; Robin Marks; Akira Matsumori; Richard Matzopoulos; Bongani M Mayosi; John H McAnulty; Mary M McDermott; John McGrath; George A Mensah; Tony R Merriman; Catherine Michaud; Matthew Miller; Ted R Miller; Charles Mock; Ana Olga Mocumbi; Ali A Mokdad; Andrew Moran; Kim Mulholland; M Nathan Nair; Luigi Naldi; K M Venkat Narayan; Kiumarss Nasseri; Paul Norman; Martin O'Donnell; Saad B Omer; Katrina Ortblad; Richard Osborne; Doruk Ozgediz; Bishnu Pahari; Jeyaraj Durai Pandian; Andrea Panozo Rivero; Rogelio Perez Padilla; Fernando Perez-Ruiz; Norberto Perico; David Phillips; Kelsey Pierce; C Arden Pope; Esteban Porrini; Farshad Pourmalek; Murugesan Raju; Dharani Ranganathan; Jürgen T Rehm; David B Rein; Guiseppe Remuzzi; Frederick P Rivara; Thomas Roberts; Felipe Rodriguez De León; Lisa C Rosenfeld; Lesley Rushton; Ralph L Sacco; Joshua A Salomon; Uchechukwu Sampson; Ella Sanman; David C Schwebel; Maria Segui-Gomez; Donald S Shepard; David Singh; Jessica Singleton; Karen Sliwa; Emma Smith; Andrew Steer; Jennifer A Taylor; Bernadette Thomas; Imad M Tleyjeh; Jeffrey A Towbin; Thomas Truelsen; Eduardo A Undurraga; N Venketasubramanian; Lakshmi Vijayakumar; Theo Vos; Gregory R Wagner; Mengru Wang; Wenzhi Wang; Kerrianne Watt; Martin A Weinstock; Robert Weintraub; James D Wilkinson; Anthony D Woolf; Sarah Wulf; Pon-Hsiu Yeh; Paul Yip; Azadeh Zabetian; Zhi-Jie Zheng; Alan D Lopez; Christopher J L Murray; Mohammad A AlMazroa; Ziad A Memish
Journal:  Lancet       Date:  2012-12-15       Impact factor: 79.321

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