Is liver perfusion CT reproducible? A study on intra-and interobserver agreement of normal hepatic haemodynamic parameters obtained with two different software packages
Carregando...
Citações na Scopus
9
Tipo de produção
article
Data de publicação
2017
Título da Revista
ISSN da Revista
Título do Volume
Editora
BRITISH INST RADIOLOGY
Autores
BRETAS, Elisa Almeida Sathler
TORRES, Lucas Rios
BEKHOR, Daniel
SAITO FILHO, Celso Fernando
RACY, Douglas Jorge
FAGGIONI, Lorenzo
D'IPPOLITO, Giuseppe
Citação
BRITISH JOURNAL OF RADIOLOGY, v.90, n.1078, article ID 20170214, 8p, 2017
Resumo
Objective: To evaluate the agreement between the measurements of perfusion CT parameters in normal livers by using two different software packages. Methods: This retrospective study was based on 78 liver perfusion CT examinations acquired for detecting suspected liver metastasis. Patients with any morphological or functional hepatic abnormalities were excluded. The final analysis included 37 patients (59.7 +/- 14.9 y). Two readers (1 and 2) independently measured perfusion parameters using different software packages from two major manufacturers (A and B). Arterial perfusion (AP) and portal perfusion (PP) were determined using the dual-input vascular one-compartmental model. Inter-reader agreement for each package and intrareader agreement between both packages were assessed with intraclass correlation coefficients (ICC) and Bland-Altman statistics. Results: Inter-reader agreement was substantial for AP using software A (ICC = 0.82) and B (ICC = 0.85-0.86), fair for PP using software A (ICC = 0.44) and fair to moderate for PP using software B (ICC = 0.56-0.77). Intrareader agreement between software A and B ranged from slight to moderate (ICC = 0.32-0.62) for readers 1 and 2 considering the AP parameters, and from fair to moderate (ICC = 0.40-0.69) for readers 1 and 2 considering the PP parameters. Conclusion: At best there was only moderate agreement between both software packages, resulting in some uncertainty and suboptimal reproducibility. Advances in knowledge: Software-dependent factors may contribute to variance in perfusion measurements, demanding further technical improvements. AP measurements seem to be the most reproducible parameter to be adopted when evaluating liver perfusion CT.
Palavras-chave
Referências
- Bader TR, 1998, RADIOLOGY, V209, P129, DOI 10.1148/radiology.209.1.9769823
- Bankier AA, 2010, RADIOLOGY, V257, P14, DOI 10.1148/radiol.10100252
- Bevilacqua A, 2014, ACAD RADIOL, V21, P1416, DOI 10.1016/j.acra.2014.06.005
- Blomley M, 1997, FUNCTIONAL COMPUTED, P47
- Deak PD, 2010, RADIOLOGY, V257, P158, DOI 10.1148/radiol.10100047
- Di Leo G, 2015, PEDIATR RADIOL, V45, P32, DOI 10.1007/s00247-014-3081-2
- Dighe S, 2013, RADIOLOGY, V268, P400, DOI 10.1148/radiol.13112460
- Fischer MA, 2017, EUR RADIOL, V27, P1074, DOI 10.1007/s00330-016-4432-1
- Garcia-Figueiras R, 2013, AM J ROENTGENOL, V200, P8, DOI 10.2214/AJR.11.8476
- Goh V, 2007, RADIOLOGY, V242, P777, DOI 10.1148/radiol.2423060279
- Gordic S, 2016, RADIOLOGY, V280, P78, DOI 10.1148/radiol.2015151560
- Guggenberger R, 2012, SKELETAL RADIOL, V41, P971, DOI 10.1007/s00256-011-1310-4
- Hatwell C, 2014, HEPATOB PANCREAT DIS, V13, P301, DOI 10.1016/S1499-3872(14)60043-6
- Ippolito D, 2012, EUR RADIOL, V22, P803, DOI 10.1007/s00330-011-2307-z
- Jensen NKG, 2013, ACAD RADIOL, V20, P414, DOI 10.1016/j.acra.2012.09.027
- Kanda T, 2012, EUR J RADIOL, V81, P2470, DOI 10.1016/j.ejrad.2011.10.009
- Kanda T, 2012, EUR J RADIOL, V81, P2075, DOI 10.1016/j.ejrad.2011.07.003
- Kaufmann S, 2015, EUR J RADIOL, V84, P1029, DOI 10.1016/j.ejrad.2015.02.020
- Kim SH, 2014, RADIOLOGY, V272, P321, DOI 10.1148/radiol.14130091
- Leggett DAC, 1997, RADIOLOGY, V205, P716, DOI 10.1148/radiology.205.3.9393526
- Liapi E, 2015, J AM COLL RADIOL, V12, P111, DOI 10.1016/j.jacr.2014.10.007
- Materne R, 2000, CLIN SCI, V99, P517, DOI 10.1042/CS20000080
- McCollough CH, 2009, AM J ROENTGENOL, V193, P28, DOI 10.2214/AJR.09.2754
- Myles PS, 2007, BRIT J ANAESTH, V99, P309, DOI 10.1093/bja/aem214
- Ng CS, 2012, J COMPUT ASSIST TOMO, V36, P388, DOI 10.1097/RCT.0b013e318256b1e2
- Ng CS, 2011, AM J ROENTGENOL, V197, P113, DOI 10.2214/AJR.10.5404
- O'Connor JPB, 2011, BRIT J RADIOL, V84, pS112, DOI 10.1259/bjr/55166688
- Obuchowski NA, 2015, STAT METHODS MED RES, V24, P68, DOI 10.1177/0962280214537390
- Petralia G, 2012, RADIOLOGY, V265, P448, DOI 10.1148/radiol.12111232
- Shiraishi J, 2009, RADIOLOGY, V253, P822, DOI 10.1148/radiol.2533081632
- SHROUT PE, 1979, PSYCHOL BULL, V86, P420, DOI 10.1037/0033-2909.86.2.420
- Skornitzke S, 2015, BRIT J RADIOL, V88, DOI 10.1259/bjr.20140683
- Sousa João Paulo Lira Barros Almeida de, 2012, Radiol Bras, V45, P39, DOI 10.1590/S0100-39842012000100010
- Su TH, 2017, J COMPUT ASSIST TOMO, V41, P315, DOI 10.1097/RCT.0000000000000511
- Sullivan DC, 2015, RADIOLOGY, V277, P813, DOI 10.1148/radiol.2015142202
- Topcuoglu OM, 2016, DIAGN INTERV RADIOL, V22, P495, DOI 10.5152/dir.2016.16612
- Van Beers BE, 2001, AM J ROENTGENOL, V176, P667, DOI 10.2214/ajr.176.3.1760667
- Wang X, 2013, EUR J RADIOL, V82, P220, DOI 10.1016/j.ejrad.2012.09.015
- Yang HF, 2010, EUR RADIOL, V20, P1424, DOI 10.1007/s00330-009-1693-y
- Zussman BM, 2011, AM J ROENTGENOL, V197, P468, DOI 10.2214/AJR.10.6058