Literature DB >> 17763856

Pulmonary nodule detection on MDCT images: evaluation of diagnostic performance using thin axial images, maximum intensity projections, and computer-assisted detection.

A Jankowski1, T Martinelli, J F Timsit, C Brambilla, F Thony, M Coulomb, G Ferretti.   

Abstract

This study aimed at evaluating the diagnostic benefits of maximum intensity projections (MIP) and a commercially available computed-assisted detection system (CAD) for the detection of pulmonary nodules on MDCT as compared with standard 1-mm images on lung cancer screening material. Thirty subjects were randomly selected from our database. Three radiologists independently reviewed three types of images: axial 1-mm images, axial MIP slabs, and CAD system detections. Two independent experienced chest radiologists decided which were true-positive nodules. Two hundred eighty-five nodules > or =1 mm were identified as true-positive by consensus of two independent chest radiologists. The detection rates of the three independent observers with 1-mm axial images were 22 +/- 4.8%, 30 +/- 5.3%, and 47 +/- 2.8%; with MIP: 33 +/- 5.4%, 39 +/- 5.7%, and 45 +/- 5.8%; and with CAD: 35 +/- 5.6%, 36 +/- 5.6%, and 36 +/- 5.6%. There was a reading technique effect on the observers' sensitivity for nodule detection: sensitivities with MIP were higher than with 1-mm images or CAD for all nodules (F-values = 0.046). For nodules > or =3 mm, readers' sensitivities were higher with 1-mm images or MIP than with CAD (p < 0.0001). CAD was the most and MIP the less time-consuming technique (p < 0.0001). MIP and CAD reduced the number of overlooked small nodules. As MIP is more sensitive and less time consuming than the CAD we used, we recommend viewing MIP and 1-mm images for the detection of pulmonary nodules.

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Year:  2007        PMID: 17763856     DOI: 10.1007/s00330-007-0727-6

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  38 in total

1.  Computerized detection of pulmonary nodules on CT scans.

Authors:  S G Armato; M L Giger; C J Moran; J T Blackburn; K Doi; H MacMahon
Journal:  Radiographics       Date:  1999 Sep-Oct       Impact factor: 5.333

2.  Automated detection of lung nodules in CT scans: preliminary results.

Authors:  S G Armato; M L Giger; H MacMahon
Journal:  Med Phys       Date:  2001-08       Impact factor: 4.071

3.  Lung micronodules: automated method for detection at thin-section CT--initial experience.

Authors:  Matthew S Brown; Jonathan G Goldin; Robert D Suh; Michael F McNitt-Gray; James W Sayre; Denise R Aberle
Journal:  Radiology       Date:  2003-01       Impact factor: 11.105

4.  Computer-assisted detection of pulmonary nodules: performance evaluation of an expert knowledge-based detection system in consensus reading with experienced and inexperienced chest radiologists.

Authors:  Katharina Marten; Tobias Seyfarth; Florian Auer; Edzard Wiener; Andreas Grillhösl; Silvia Obenauer; Ernst J Rummeny; Christoph Engelke
Journal:  Eur Radiol       Date:  2004-07-03       Impact factor: 5.315

5.  Guidelines for management of small pulmonary nodules detected on CT scans: a statement from the Fleischner Society.

Authors:  Heber MacMahon; John H M Austin; Gordon Gamsu; Christian J Herold; James R Jett; David P Naidich; Edward F Patz; Stephen J Swensen
Journal:  Radiology       Date:  2005-11       Impact factor: 11.105

6.  Characteristics of small lung cancers invisible on conventional chest radiography and detected by population based screening using spiral CT.

Authors:  S Sone; F Li; Z G Yang; S Takashima; Y Maruyama; M Hasegawa; J C Wang; S Kawakami; T Honda
Journal:  Br J Radiol       Date:  2000-02       Impact factor: 3.039

7.  Screening for early lung cancer with low-dose spiral CT: prevalence in 817 asymptomatic smokers.

Authors:  Stefan Diederich; Dag Wormanns; Michael Semik; Michael Thomas; Horst Lenzen; Nikolaus Roos; Walter Heindel
Journal:  Radiology       Date:  2002-03       Impact factor: 11.105

8.  [Multidetector-row CT of the lungs: Multiplanar reconstructions and maximum intensity projections for the detection of pulmonary nodules].

Authors:  R Eibel; T R Türk; C Kulinna; K Herrmann; M F Reiser
Journal:  Rofo       Date:  2001-09

9.  Peripheral lung cancer: screening and detection with low-dose spiral CT versus radiography.

Authors:  M Kaneko; K Eguchi; H Ohmatsu; R Kakinuma; T Naruke; K Suemasu; N Moriyama
Journal:  Radiology       Date:  1996-12       Impact factor: 11.105

10.  Spiral CT of the chest: comparison of cine and film-based viewing.

Authors:  S E Seltzer; P F Judy; D F Adams; F L Jacobson; P Stark; R Kikinis; R G Swensson; S Hooton; B Head; U Feldman
Journal:  Radiology       Date:  1995-10       Impact factor: 11.105

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  18 in total

Review 1.  Screening for lung cancer with low-dose computed tomography: a review of current status.

Authors:  Henry M Marshall; Rayleen V Bowman; Ian A Yang; Kwun M Fong; Christine D Berg
Journal:  J Thorac Dis       Date:  2013-10       Impact factor: 2.895

2.  Multi slice computed tomography in the study of pulmonary metastases.

Authors:  G Angelelli; V Grimaldi; F Spinelli; A Scardapane; A Sardaro
Journal:  Radiol Med       Date:  2008-09-08       Impact factor: 3.469

Review 3.  Missed lung cancer: when, where, and why?

Authors:  Annemilia Del Ciello; Paola Franchi; Andrea Contegiacomo; Giuseppe Cicchetti; Lorenzo Bonomo; Anna Rita Larici
Journal:  Diagn Interv Radiol       Date:  2017 Mar-Apr       Impact factor: 2.630

Review 4.  Lung cancer screening: nodule identification and characterization.

Authors:  Ioannis Vlahos; Konstantinos Stefanidis; Sarah Sheard; Arjun Nair; Charles Sayer; Joanne Moser
Journal:  Transl Lung Cancer Res       Date:  2018-06

5.  Significance of pulmonary nodules in patients with colorectal cancer.

Authors:  Fabio Pomerri; Salvatore Pucciarelli; Isacco Maretto; Ernesta Perrone; Giovanna Pintacuda; Sara Lonardi; Donato Nitti; Pier Carlo Muzzio
Journal:  Eur Radiol       Date:  2012-04-01       Impact factor: 5.315

6.  Computer-aided detection (CAD) of lung nodules in CT scans: radiologist performance and reading time with incremental CAD assistance.

Authors:  Justus E Roos; David Paik; David Olsen; Emily G Liu; Lawrence C Chow; Ann N Leung; Robert Mindelzun; Kingshuk R Choudhury; David P Naidich; Sandy Napel; Geoffrey D Rubin
Journal:  Eur Radiol       Date:  2009-09-16       Impact factor: 5.315

7.  Detection of pulmonary nodules at paediatric CT: maximum intensity projections and axial source images are complementary.

Authors:  Fleur Kilburn-Toppin; Owen J Arthurs; Angela D Tasker; Patricia A K Set
Journal:  Pediatr Radiol       Date:  2013-01-24

Review 8.  A practical and adaptive approach to lung cancer screening: a review of international evidence and position on CT lung cancer screening in the Singaporean population by the College of Radiologists Singapore.

Authors:  Charlene Jin Yee Liew; Lester Chee Hao Leong; Lynette Li San Teo; Ching Ching Ong; Foong Koon Cheah; Wei Ping Tham; Haja Mohamed Mohideen Salahudeen; Chau Hung Lee; Gregory Jon Leng Kaw; Augustine Kim Huat Tee; Ian Yu Yan Tsou; Kiang Hiong Tay; Raymond Quah; Bien Peng Tan; Hong Chou; Daniel Tan; Angeline Choo Choo Poh; Andrew Gee Seng Tan
Journal:  Singapore Med J       Date:  2019-11       Impact factor: 1.858

Review 9.  Lung Cancer Screening, Version 3.2018, NCCN Clinical Practice Guidelines in Oncology.

Authors:  Douglas E Wood; Ella A Kazerooni; Scott L Baum; George A Eapen; David S Ettinger; Lifang Hou; David M Jackman; Donald Klippenstein; Rohit Kumar; Rudy P Lackner; Lorriana E Leard; Inga T Lennes; Ann N C Leung; Samir S Makani; Pierre P Massion; Peter Mazzone; Robert E Merritt; Bryan F Meyers; David E Midthun; Sudhakar Pipavath; Christie Pratt; Chakravarthy Reddy; Mary E Reid; Arnold J Rotter; Peter B Sachs; Matthew B Schabath; Mark L Schiebler; Betty C Tong; William D Travis; Benjamin Wei; Stephen C Yang; Kristina M Gregory; Miranda Hughes
Journal:  J Natl Compr Canc Netw       Date:  2018-04       Impact factor: 11.908

10.  Evaluation of the clinical utility of maximum intensity projections of 3D contrast-enhanced, T1-weighted imaging for the detection of brain metastases.

Authors:  Nicolin Hainc; Christian Federau; Anthony Tyndall; Andreas Mittermeier; Andrea Bink; Christoph Stippich; Tilman Schubert
Journal:  Cancer Rep (Hoboken)       Date:  2020-08-07
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