Changes in saccadic intrusions over time as an objective biomarker to follow ALS disease progression.

Objective: Saccadic Intrusions (SIs) are abnormal eye movements during gaze fixation. Studies have indicated the clinical relevance of SIs, especially of square wave jerks (SWJ) in ALS. We used a software-based platform to extract SIs as a part of an interventional drug trial. The objective was to examine SIs' change over time as a potential biomarker of ALS disease progression. Methods: 28 ALS patients (61.95 ± 8.6 years) were assessed with the revised ALS Functional Rating Scale (ALSFRS-R) and with an oculometric test. Changes of SIs over time and correlations with ALSFRS-R and its bulbar subscale were calculated. A power calculation was conducted to understand the practical implications of results. Results: A significant increase of SWJ over trial duration was observed, with an increase in frequency (mean rise of 0.14 ± 0.28, p < 0.01), amplitude (0.001 ± 0.0016 degrees, p < 0.005), overall duration of SWJ (0.13 ± 0.25, in %, p < 0.01), and in their relative part out of all intrusions (0.18 ± 0.32, in %, p < 0.005). Negative correlations were found with the bulbar subscale (R=-0.43, -0.41, -0.39 and -0.47, respectively, p < 0.001). The required sample size for observing a 40% reduction in bulbar aspects when using the oculometric test (α = 0.05 and ß = 0.8), was found to be 150 patients per arm, compared with 200 patients using the bulbar subscale. Conclusions: Evaluation of saccadic intrusions during fixation was able to detect disease progression over time, correlated with ALSFRS-R bulbar subscale. Eye movements can potentially serve as an objective biomarker in ALS clinical trials and reduce the required sample size to show clinical effect of therapies.

Advancements in eye movement measurement technologies for assessing neurodegenerative diseases.

Eye movements have long been recognized as a valuable indicator of neurological conditions, given the intricate involvement of multiple neurological pathways in vision-related processes, including motor and cognitive functions, manifesting in rapid response times. Eye movement abnormalities can indicate neurological condition severity and, in some cases, distinguish between disease phenotypes. With recent strides in imaging sensors and computational power, particularly in machine learning and artificial intelligence, there has been a notable surge in the development of technologies facilitating the extraction and analysis of eye movements to assess neurodegenerative diseases. This mini-review provides an overview of these advancements, emphasizing their potential in offering patient-friendly oculometric measures to aid in assessing patient conditions and progress. By summarizing recent technological innovations and their application in assessing neurodegenerative diseases over the past decades, this review also delves into current trends and future directions in this expanding field.

Oculometric measures as a tool for assessment of clinical symptoms and severity of Parkinson's disease.

Abnormalities of oculometric measures (OM) are widely described in people with Parkinson's disease (PD). However, knowledge of correlations between abnormal OM, disease severity and clinical assessment in PD patients is still lacking. To evaluate these correlations, PD patients (215 patients, mean age 69 ± 9.1 years, 79 females) with severe (H&Y > 3) and mild to moderate (H&Y ≤ 2) disease, and 215 age-matched healthy subjects were enrolled. All patients were evaluated using MDS-UPDRS and an oculometric test using computer vision and deep learning algorithms. Comparisons of OM between groups and correlations between OM and MDS-UPDRS scores were calculated. Saccadic latency (ms) was prolonged in patients with severe compared with mild to moderate disease (pro-saccades: 267 ± 69 vs. 238 ± 53, p = 0.0011; anti-saccades: 386 ± 119 vs. 352 ± 106, p = 0.0393) and in patients with mild to moderate disease versus healthy subjects (pro-saccades: 238 ± 53 vs. 220 ± 45, p = 0.0003; anti-saccades: 352 ± 106 vs. 289 ± 71, p < 0.0001). Error rate (%) was higher among patients with severe (64.06 ± 23.08) versus mild to moderate disease (49.84 ± 24.81, p = 0.0001), and versus healthy subjects (49.84 ± 24.81 vs. 28.31 ± 21.72, p = 0.00001). Response accuracy (%) was lower for patients with severe (75.66 ± 13.11) versus mild to moderate disease (79.66 ± 13.56, p = 0.0462), and versus healthy subjects (79.66 ± 13.56 vs. 90.27 ± 8.79, p < 0.0001). Pro- and anti-saccadic latency, error rate and accuracy were correlated with MDS-UPDRS scores (r = 0.32, 0.28, 0.36 and -0.30, respectively, p < 0.0001) and similar correlations were found with its axial subscore (R = 0.38, 0.29, 0.44, and -0.30, respectively, p < 0.0001). Several OM were different in patients under levodopa treatment. OM worsened as PD severity increases, and were correlated with MDS-UPDRS scores. Using OM can be implemented for PD patients' assessment as a tool to follow disease progression.

Correlation between oculometric measures and clinical assessment in ALS patients participating in a phase IIb clinical drug trial.

Objective: Oculometric measures (OM) can be extracted from eye movements during presentation of visual stimuli. Studies have indicated the benefit of OM in assessment of neurological disorders, including Amyotrophic Lateral Sclerosis (ALS). We used a new software-based platform for the extraction of OM during patients' assessment. Our objective was to examine the correlation between OM and clinical assessment as a part of a clinical drug trial. Methods: 32 ALS patients (mean age 60.75 ± 10.36 years, 13 females), were assessed using a validated score (ALSFRS-R), and a novel software-based oculometric platform (NeuraLight, Israel) as a part of a clinical drug trial. Correlations of ALSFRS-R with OM were calculated and compared with matched healthy subjects' data (N = 129). Results: A moderate correlation was found between ALSFRS-R and corrective saccadic latency (R = 0.52, p = 0.002). Fixation time during smooth pursuit and peak velocity during pro-saccades were both worse in ALS patients versus healthy subjects (mean (SD)=0.34(0.06) vs. 0.3(0.07), p = 0.01, and 0.41(0.05) vs. 0.38(0.07), p = 0.04, respectively). Patients with bulbar symptoms (N = 14) had a decreased pro-saccade gain compared with patients without bulbar symptoms (mean (SD)=0.1 (0.04) vs. 0.93 (0.07), p = 0.01), and a larger error rate of anti-saccade movement (mean (SD)=0.42 (0.21) vs. 0.28 (0.16), p = 0.04). Conclusions: Oculometric measures correlated with the clinical assessment and were different from data of healthy subjects. Further studies are warranted to establish the role of oculometrics in the evaluation of patients with ALS and other neurodegenerative disorders, and its possible use in clinical trials.