Publications by authors named "Kanchalika Sathianvichitr"
Article Synopsis
- The study focuses on improving the diagnosis of arteritic anterior ischemic optic neuropathy (AAION) from giant cell arteritis, which can prevent vision loss, particularly when symptoms are subtle or unreliable tests are involved.
- Researchers developed a deep learning system (DLS) to differentiate between AAION and nonarteritic anterior ischemic optic neuropathy (NAION) by analyzing color fundus images from a large international dataset involving 961 eyes from 802 patients.
- The DLS demonstrated promising performance metrics, such as area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy, validating its potential as a diagnostic tool during the acute phase.
Background: Optic disc drusen (ODD) represent an important differential diagnosis of papilledema caused by intracranial hypertension, but their distinction may be difficult in clinical practice. The aim of this study was to train, validate, and test a dedicated deep learning system (DLS) for binary classification of ODD vs papilledema (including various subgroups within each category), on conventional mydriatic digital ocular fundus photographs collected in a large international multiethnic population.
Methods: This retrospective study included 4,508 color fundus images in 2,180 patients from 30 neuro-ophthalmology centers (19 countries) participating in the Brain and Optic Nerve Study with Artificial Intelligence (BONSAI) Group.
Introduction: Detection of neurological conditions is of high importance in the current context of increasingly ageing populations. Imaging of the retina and the optic nerve head represents a unique opportunity to detect brain diseases, but requires specific human expertise. We review the current outcomes of artificial intelligence (AI) methods applied to retinal imaging for the detection of neurological and neuro-ophthalmic conditions.
View Article and Find Full Text PDFThe quality of ocular fundus photographs can affect the accuracy of the morphologic assessment of the optic nerve head (ONH), either by humans or by deep learning systems (DLS). In order to automatically identify ONH photographs of optimal quality, we have developed, trained, and tested a DLS, using an international, multicentre, multi-ethnic dataset of 5015 ocular fundus photographs from 31 centres in 20 countries participating to the Brain and Optic Nerve Study with Artificial Intelligence (BONSAI). The reference standard in image quality was established by three experts who independently classified photographs as of "good", "borderline", or "poor" quality.
View Article and Find Full Text PDFPurpose: Leber's hereditary optic neuropathy (LHON), the most common mitochondrial optic neuropathy, causes visual loss, especially in young adults. Due to the absence of epidemiological data in Southeast Asia, we aimed to determine Thai LHON patients' characteristics (demographic data, mutation types, and prognoses) as the first study in this region.
Methods: This retrospective chart review enrolled all Thai LHON patients confirmed by three mitochondrial DNA mutations (G11778A, T14484C, and G3460A) between January 1997 and December 2016.
Clinical diagnoses of slow, progressive, painless visual losses with various degrees of visual field (VF) losses and disc atrophy are often confused between suprasellar compressive optic neuropathy (CON) and open-angle glaucomatous optic neuropathy (GON). We plotted the thickness of the peripapillary retinal nerve fiber layer (RNFL) and macular ganglion cell-inner plexiform layer (GCIPL) against the mean deviation (MD) of the VF of 34 eyes of CON at diagnosis, 30 eyes of CON after therapy, 29 eyes of GON, and 60 eyes of healthy controls in a cross-sectional investigation. At diagnosis, a disproportionally early pattern of structural thinning compared with the corresponding VF losses was unique to CON.
View Article and Find Full Text PDFAim: To investigate the relationship between the levels of prostaglandin E2 (PGE2) in tears and dry eye disease severity based on both clinical symptoms and signs.
Methods: Tear samples were collected from 36 non-Sjögren syndrome dry eye patients (10 males and 26 females, mean age 50.11±11.
Objective: To study the factors associated with dengue prevention and control in Moo 6 (the 6th village) and Moo 7 of Tambon Kaeng-phak-kut, Thaluang District, Lopburi Province.
Material And Method: The authors reviewed the raw data collected by public health officers and village health volunteers (VHVs) as their routine tasks. The authors analyzed the data, 30 dwellings per each village, to compare the demographics, knowledge, attitude, and practice of subjects from Moo 6, a dengue-outbreak community, with that from Moo 7, a control group, as well as larval indices between these 2 studied groups.