Imaging Biomarkers of 1-Year Activity in Type 1 Macular Neovascularization.


Journal

Translational vision science & technology
ISSN: 2164-2591
Titre abrégé: Transl Vis Sci Technol
Pays: United States
ID NLM: 101595919

Informations de publication

Date de publication:
03 05 2021
Historique:
entrez: 10 6 2021
pubmed: 11 6 2021
medline: 29 6 2021
Statut: ppublish

Résumé

The purpose of this study was to evaluate the predictive value of optical coherence tomography (OCT) and OCT angiography (OCTA) parameters at baseline on lesion's activity at the 1-year follow-up in type 1 macular neovascularizations (MNVs) treated with 1-year fixed regimen of intravitreal aflibercept injections (q8 IAIs). All patients were imaged by structural OCT to evaluate central macular thickness (CMT), subretinal fluid (SRF), subretinal hyper-reflective material (SHRM), intraretinal fluid (IRF) and intraretinal hyper-reflective dots (HRDs), and by Swept-Source OCTA to measure baseline MNV area, perfusion density (PD), vessel length density (VLD), and vessel diameter index. At the end of q8 IAI, patients were classified in two groups: active-MNV (A-MNV) and inactive-MNV (I-MNV), considering the OCT signs of activity. Three binary logistic regression models were developed: (1) OCT-based, (2) OCTA-based, and (3) OCT/OCTA-based model. Thirty-one treatment-naïve type 1 MNVs were enrolled (13 A-MNV and 18 I-MNV). No differences were observed in baseline OCT and OCTA characteristics between A-MNV and I-MNV. Among the models developed, model 3 that combined OCT/OCTA parameters showed a performance of 87.5% and excellent sensitivity for A-MNV lesions (100%). By analyzing the model, the A-MNV group appears more likely to show at baseline SRF, greater CMT, wider MNV area, and lower PD and VLD compared to I-MNV. Our study demonstrated that the combination of baseline OCT and OCTA parameters allowed to achieve a good models' performance in the prediction of MNV activity permitting to correctly classifying the active lesions at the end of follow-up period, with excellent sensitivity. OCT/OCTA could integrate statistical models potentially useful for artificial intelligence.

Identifiants

pubmed: 34111264
pii: 2772591
doi: 10.1167/tvst.10.6.18
pmc: PMC8131998
doi:

Substances chimiques

Biomarkers 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

18

Références

Retina. 2013 Jan;33(1):23-34
pubmed: 23073338
J Healthc Eng. 2018 Apr 12;2018:8595278
pubmed: 29850003
Retina. 2017 Aug;37(8):1492-1498
pubmed: 27997513
Ophthalmology. 2012 Dec;119(12):2537-48
pubmed: 23084240
Acta Ophthalmol. 2018 Mar;96(2):120-133
pubmed: 29130626
Br J Ophthalmol. 2007 Sep;91(9):1173-6
pubmed: 17383997
Retina. 2018 Feb;38(2):220-230
pubmed: 28582276
Ophthalmology. 2016 Jan;123(1):60-9
pubmed: 26481821
Biomed Res Int. 2020 Apr 24;2020:4501395
pubmed: 32382551
J Ophthalmol. 2019 Jul 9;2019:4806061
pubmed: 31360542
Ophthalmology. 2016 Jul;123(7):1521-9
pubmed: 27157149
Prog Retin Eye Res. 2016 Jan;50:1-24
pubmed: 26307399
Transl Vis Sci Technol. 2019 Mar 27;8(2):8
pubmed: 30941265
Ophthalmology. 2015 Dec;122(12):2523-31.e1
pubmed: 26383996
J Chiropr Med. 2016 Jun;15(2):155-63
pubmed: 27330520
Int J Retina Vitreous. 2020 Aug 20;6:39
pubmed: 32844038
Semin Ophthalmol. 2019;34(3):168-176
pubmed: 31132283
Curr Opin Ophthalmol. 2019 Jan;30(1):13-18
pubmed: 30489359
Br J Ophthalmol. 2014 Dec;98(12):1629-35
pubmed: 25079064
Ophthalmol Ther. 2020 Dec;9(4):697-707
pubmed: 32740741
Ophthalmology. 2020 May;127(5):616-636
pubmed: 31864668
Sci Rep. 2019 Dec 17;9(1):19240
pubmed: 31848438
Retina. 2017 Nov;37(11):2062-2068
pubmed: 28590316
Acta Ophthalmol. 2020 Nov;98(7):e820-e829
pubmed: 32190990
Am J Ophthalmol. 2018 Feb;186:25-31
pubmed: 29169882
Transl Vis Sci Technol. 2020 Aug 31;9(9):48
pubmed: 32934898
Retina. 2019 Mar;39(3):548-557
pubmed: 29210939
Prog Retin Eye Res. 2018 Nov;67:30-55
pubmed: 30059755
Nat Methods. 2012 Jul;9(7):671-5
pubmed: 22930834
Acta Ophthalmol. 2017 Jun;95(4):414-420
pubmed: 28133946
PLoS One. 2018 Oct 9;13(10):e0205513
pubmed: 30300393
Br J Ophthalmol. 2019 Sep;103(9):1320-1326
pubmed: 30361273
Br J Ophthalmol. 2019 Sep;103(9):1342-1346
pubmed: 30467129
Am J Ophthalmol. 2020 May;213:161-176
pubmed: 32059979

Auteurs

Eliana Costanzo (E)

IRCCS - Fondazione Bietti, Rome, Italy.

Mariacristina Parravano (M)

IRCCS - Fondazione Bietti, Rome, Italy.

Daniela Giannini (D)

IRCCS - Fondazione Bietti, Rome, Italy.

Enrico Borrelli (E)

Department of Ophthalmology, IRCCS Ospedale San Raffaele, University Vita-Salute, Milan, Italy.

Riccardo Sacconi (R)

Department of Ophthalmology, IRCCS Ospedale San Raffaele, University Vita-Salute, Milan, Italy.

Giuseppe Querques (G)

Department of Ophthalmology, IRCCS Ospedale San Raffaele, University Vita-Salute, Milan, Italy.

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Classifications MeSH