Dataset Information

Segmenting OCT for detecting drug efficacy in CRAO.

ABSTRACT:

Purpose

Thinning of the inner layers of the retina occurs in patients with central retinal artery occlusion (CRAO). The mechanism for such thinning may be partially due to proteolysis by a calcium-activated protease called calpain. Calpain inhibitor SNJ-1945 ameliorated the proteolysis in a past series of model experiments. The purposes of the present retrospective study were to: 1) use segmentation analysis of optical coherence tomography (OCT) images to mathematically model the loss of specific retinal layers in CRAO patients, and 2) predict the number of patients and days of observation needed for clinical trials of inhibitors against CRAO.

Methods

A retrospective case control study was conducted by computer-aided search for CRAO (ICD10 H43.1) with at least one OCT procedure (CPT: 92134) in the OHSU Epic patient data base.

Results

After initial swelling, thinning of the inner retinal layers, especially the ganglion cell (GCL) layer followed exponential decay curves. Using sample size statistics and GCL thickness as a marker in a 30-day clinical trial, 19 eyes/group could theoretically detect a 20% beneficial effect of an inhibitor against CRAO. Other markers, such as the whole retinal thickness and combined inner layers could also be used as less-specific markers.

Conclusions

Using thickness changes in the GCL layer to monitor the efficacy of potential inhibitors against CRAO is practical in human trials requiring a reasonable number of patients and relatively short trial period.

Translational relevance

Measurement of GCL thickness would be a useful indicator of CRAO progression in a clinical trial of putative inhibitors.

SUBMITTER: Shearer TR

PROVIDER: S-EPMC7732080 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Segmenting OCT for detecting drug efficacy in CRAO.

Shearer Thomas R TR Hwang Thomas S TS Steinkamp Peter N PN Azuma Mitsuyoshi M

PloS one 20201211 12

<h4>Purpose</h4>Thinning of the inner layers of the retina occurs in patients with central retinal artery occlusion (CRAO). The mechanism for such thinning may be partially due to proteolysis by a calcium-activated protease called calpain. Calpain inhibitor SNJ-1945 ameliorated the proteolysis in a past series of model experiments. The purposes of the present retrospective study were to: 1) use segmentation analysis of optical coherence tomography (OCT) images to mathematically model the loss of ...[more]

PMID: 33306701

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Project description:PURPOSE:To evaluate whether loss of 5 ?m or more in global retinal nerve fiber layer (RNFL) thickness on spectral-domain (SD) between 2 consecutive visits is specific for glaucoma progression. DESIGN:Prospective cohort. PARTICIPANTS:Ninety-two eyes of 49 control participants and 300 eyes of 210 glaucoma patients. METHODS:Patients completed at least 5 standard automated perimetry and SD OCT examinations at 6-month intervals over at least 2 years. Eyes were categorized as progressing from glaucoma if the average RNFL declined by 5 ?m or more between 2 consecutive visits. The false-positive proportion was estimated by 2 methods: (1) 5-?m or more loss in control participants and (2) 5-?m or more gain in glaucoma. The false-positive proportion was subtracted from the cumulative proportion of eyes categorized with glaucoma progression to estimate the true progression prevalence. MAIN OUTCOME MEASURES:False-positive and true progression prevalence of patients with glaucoma detected as progressing on SD OCT. RESULTS:After 5 years of semiannual testing, the cumulative proportion of false-positive results based on 5-?m or more RNFL losses between visits was 24.8% in the control participants. Although 40.6% of glaucoma eyes were diagnosed with progression at 5 years, only 15.8% would have been considered to show true progression based on the expected false-positive ratio from the control participants (i.e., 40.6%-24.8%). The cumulative proportion of an intervisit gain of 5 ?m or more at 5 years was 27.4% in glaucoma eyes, suggesting that only 13.2% of eyes with glaucoma truly had progressed (i.e., 40.6%-27.4%). CONCLUSIONS:Loss of 5 ?m or more in average RNFL thickness between consecutive SD OCT tests is not specific for glaucoma progression. Application of this intervisit rule of 5 can result in a high cumulative proportion of false-positive results over time, which could lead to unnecessary interventions in patients whose disease is stable. More specific diagnostic criteria are needed to help clinicians determine whether patients with glaucoma are progressing so that therapy escalation is both timely and appropriate.

Project description:ObjectivesTo evaluate short-term test-retest repeatability of a deep learning architecture (U-Net) in slice- and lesion-level detection and segmentation of clinically significant prostate cancer (csPCa: Gleason grade group > 1) using diffusion-weighted imaging fitted with monoexponential function, ADCm.MethodsOne hundred twelve patients with prostate cancer (PCa) underwent 2 prostate MRI examinations on the same day. PCa areas were annotated using whole mount prostatectomy sections. Two U-Net-based convolutional neural networks were trained on three different ADCm b value settings for (a) slice- and (b) lesion-level detection and (c) segmentation of csPCa. Short-term test-retest repeatability was estimated using intra-class correlation coefficient (ICC(3,1)), proportionate agreement, and dice similarity coefficient (DSC). A 3-fold cross-validation was performed on training set (N = 78 patients) and evaluated for performance and repeatability on testing data (N = 34 patients).ResultsFor the three ADCm b value settings, repeatability of mean ADCm of csPCa lesions was ICC(3,1) = 0.86-0.98. Two CNNs with U-Net-based architecture demonstrated ICC(3,1) in the range of 0.80-0.83, agreement of 66-72%, and DSC of 0.68-0.72 for slice- and lesion-level detection and segmentation of csPCa. Bland-Altman plots suggest that there is no systematic bias in agreement between inter-scan ground truth segmentation repeatability and segmentation repeatability of the networks.ConclusionsFor the three ADCm b value settings, two CNNs with U-Net-based architecture were repeatable for the problem of detection of csPCa at the slice-level. The network repeatability in segmenting csPCa lesions is affected by inter-scan variability and ground truth segmentation repeatability and may thus improve with better inter-scan reproducibility.Key points• For the three ADCm b value settings, two CNNs with U-Net-based architecture were repeatable for the problem of detection of csPCa at the slice-level. • The network repeatability in segmenting csPCa lesions is affected by inter-scan variability and ground truth segmentation repeatability and may thus improve with better inter-scan reproducibility.

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Dataset Information

Segmenting OCT for detecting drug efficacy in CRAO.

Purpose

Methods

Results

Conclusions

Translational relevance

Publications

Segmenting OCT for detecting drug efficacy in CRAO.

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