PURPOSE: To estimate the conversion factors to transpose macular thickness measurements on time-domain (TD) to various spectral-domain (SD) optical coherence tomography (OCT) machines in patients with macular telangiectasia type 2a (MacTel). PROCEDURES: Macular scans on TD- and SD-OCT were performed on patients at the same visit. The retinal thickness values in various ETDRS subfields and macular volume were compared between different OCT machines. RESULTS: The macular thickness and volume were significantly greater (p < 0.0001, r = 0.678-0.822) on SD-OCT. The mean differences in macular thickness between TD Stratus and SD-OCT by Spectralis, Cirrus and Topcon were 62, 41 and 20 μm, respectively. The conversion factor of macular thickness from TD-OCT to Spectralis, Cirrus and Topcon were +65, +39 and +25 μm, respectively. CONCLUSION AND MESSAGE: The estimates of conversion of macular thickness from TD- to SD-OCT using simple mean differences between machines and those by linear regression were similar suggesting that the former may be used for the longitudinal follow-up of MacTel patients.
PURPOSE: To estimate the conversion factors to transpose macular thickness measurements on time-domain (TD) to various spectral-domain (SD) optical coherence tomography (OCT) machines in patients with macular telangiectasia type 2a (MacTel). PROCEDURES: Macular scans on TD- and SD-OCT were performed on patients at the same visit. The retinal thickness values in various ETDRS subfields and macular volume were compared between different OCT machines. RESULTS: The macular thickness and volume were significantly greater (p < 0.0001, r = 0.678-0.822) on SD-OCT. The mean differences in macular thickness between TD Stratus and SD-OCT by Spectralis, Cirrus and Topcon were 62, 41 and 20 μm, respectively. The conversion factor of macular thickness from TD-OCT to Spectralis, Cirrus and Topcon were +65, +39 and +25 μm, respectively. CONCLUSION AND MESSAGE: The estimates of conversion of macular thickness from TD- to SD-OCT using simple mean differences between machines and those by linear regression were similar suggesting that the former may be used for the longitudinal follow-up of MacTel patients.
Authors: Qinqin Zhang; Ruikang K Wang; Chieh-Li Chen; Andrew D Legarreta; Mary K Durbin; Lin An; Utkarsh Sharma; Paul F Stetson; John E Legarreta; Luiz Roisman; Giovanni Gregori; Philip J Rosenfeld Journal: Retina Date: 2015-11 Impact factor: 4.256
Authors: Roberto Bonelli; Brendan R E Ansell; Luca Lotta; Thomas Scerri; Traci E Clemons; Irene Leung; Tunde Peto; Alan C Bird; Ferenc B Sallo; Claudia Langenberg; Melanie Bahlo Journal: Genome Med Date: 2021-03-09 Impact factor: 11.117
Authors: Sobha Sivaprasad; Stephane A Regnier; Franck Fajnkuchen; Jonathan Wright; Alan R Berger; Paul Mitchell; Michael Larsen Journal: Adv Ther Date: 2016-03-07 Impact factor: 3.845