Spatial and spatio-temporal statistical analyses of retinal images: a review of methods and applications.

Background: Clinical research and management of retinal diseases greatly depend on the interpretation of retinal images and often longitudinally collected images. Retinal images provide context for spatial data, namely the location of specific pathologies within the retina. Longitudinally collected images can show how clinical events at one point can affect the retina over time. In this review, we aimed to assess statistical approaches to spatial and spatio-temporal data in retinal images. We also review the spatio-temporal modelling approaches used in other medical image types. Methods: We conducted a comprehensive literature review of both spatial or spatio-temporal approaches and non-spatial approaches to the statistical analysis of retinal images. The key methodological and clinical characteristics of published papers were extracted. We also investigated whether clinical variables and spatial correlation were accounted for in the analysis. Results: Thirty-four papers that included retinal imaging data were identified for full-text information extraction. Only 11 (32.4%) papers used spatial or spatio-temporal statistical methods to analyse images, others (23 papers, 67.6%) used non-spatial methods. Twenty-eight (82.4%) papers reported images collected cross-sectionally, while 6 (17.6%) papers reported analyses on images collected longitudinally. In imaging areas outside of ophthalmology, 19 papers were identified with spatio-temporal analysis, and multiple statistical methods were recorded. Conclusions: In future statistical analyses of retinal images, it will be beneficial to clearly define and report the spatial distributions studied, report the spatial correlations, combine imaging data with clinical variables into analysis if available, and clearly state the software or packages used

Automated Classification of Changes of Direction in Soccer Using Inertial Measurement Units

Changes of direction (COD) are an important aspect of soccer match play. Understanding the physiological and biomechanical demands on players in games allows sports scientists to effectively train and rehabilitate soccer players. COD are conventionally recorded using manually annotated time-motion video analysis which is highly time consuming, so more time-efficient approaches are required. The aim was to develop an automated classification model based on multi-sensor player tracking device data to detect COD > 45°. Video analysis data and individual multi-sensor player tracking data (GPS, accelerometer, gyroscopic) for 23 academy-level soccer players were used. A novel ‘GPS-COD Angle’ variable was developed and used in model training; along with 24 GPS-derived, gyroscope and accelerometer variables. Video annotation was the ground truth indicator of occurrence of COD > 45°. The random forest classifier using the full set of features demonstrated the highest accuracy (AUROC = 0.957, 95% CI = 0.956–0.958, Sensitivity = 0.941, Specificity = 0.772. To balance sensitivity and specificity, model parameters were optimised resulting in a value of 0.889 for both metrics. Similarly high levels of accuracy were observed for random forest models trained using a reduced set of features, accelerometer-derived variables only, and gyroscope-derived variables only. These results point to the potential effectiveness of the novel methodology implemented in automatically identifying COD in soccer players

A systematic review and meta-analysis of the prevalence of small fiber pathology in fibromyalgia: Implications for a new paradigm in fibromyalgia etiopathogenesis

Objectives: Fibromyalgia is a condition which exhibits chronic widespread pain with neuropathic pain features and has a major impact on health-related quality of life. The pathophysiology remains unclear, however, there is increasing evidence for involvement of the peripheral nervous system with a high prevalence of small fiber pathology (SFP). The aim of this systematic literature review is to establish the prevalence of SFP in fibromyalgia. Methods: An electronic literature search was performed using MEDLINE, EMBASE, PubMed, Web of Science, CINAHL and the Cochrane Library databases. Published full-text, English language articles that provide SFP prevalence data in studies of fibromyalgia of patients over 18years old were included. All articles were screened by two independent reviewers using a priori criteria. Methodological quality and risk of bias were evaluated using the critical appraisal tool by Munn et al. Overall and subgroup pooled prevalence were calculated by random-effects meta-analysis with 95% CI. Results: Database searches found 935 studies; 45 articles were screened of which 8 full text articles satisfied the inclusion criteria, providing data from 222 participants. The meta-analysis demonstrated the pooled prevalence of SFP in fibromyalgia is 49% (95% CI: 38–60%) with a moderate degree of heterogeneity, (I2= 68%). The prevalence estimate attained by a skin biopsy was 45% (95% CI: 32–59%, I2= 70%) and for corneal confocal microscopy it was 59% (95% CI: 40–78%, I2= 51%). Conclusion: There is a high prevalence of SFP in fibromyalgia. This study provides compelling evidence of a distinct phenotype involving SFP in fibromyalgia. Identifying SFP will aid in determining its relationship to pain and potentially facilitate the development of future interventions and pharmacotherapy

Adaptation to post-stroke homonymous hemianopia - a prospective longitudinal cohort study to identify predictive factors of the adaptation process

Purpose: To determine any factors that predict how an individual will adapt to post-stroke hemianopic visual field loss, with close monitoring of the adaptation process from an early stage. Materials and methods: The Hemianopia Adaptation Study (HAST) is a prospective observational longitudinal cohort clinical study. Adult stroke survivors (n = 144) with new onset homonymous hemianopia were monitored using standardised mobility assessment course (MAC) as the primary outcome measure of adaptation. Results: Several baseline variables were found to be good predictors of adaptation. Three variables were associated with adaptation status at 12-weeks post-stroke: inferior % visual field, % total MAC omissions, and MAC completion time (seconds). Baseline measurements of these variables can predict the adaptation at 12 weeks with moderate to high accuracy (area under ROC curve, 0.82, 95% CI 0.74–0.90). A cut-off score of ≤25% target omissions is suggested to predict which individuals are likely to adapt by 12-weeks post-stroke following gold standard care. Conclusions: Adaptation to hemianopia is a personal journey with several factors being important for prediction of its presence, including MAC outcomes and extent of inferior visual field loss. A clinical recommendation is made for inclusion of the MAC as part of a functional assessment for hemianopia. Implications for rehabilitation The mobility assessment course (MAC) should be considered as an assessment of mobility/scanning in the rehabilitation of patients with homonymous hemianopia. A cut-off score of ≤25% omissions on MAC could be employed to determine those likely to adapt to hemianopia long-term. Targeted support and therapy for patients with significant visual loss in the inferior visual field area should be considered

Effunet-spagen: An efficient and spatial generative approach to glaucoma detection

Current research in automated disease detection focuses on making algorithms “slimmer” reducing the need for large training datasets and accelerating recalibration for new data while achieving high accuracy. The development of slimmer models has become a hot research topic in medical imaging. In this work, we develop a two-phase model for glaucoma detection, identifying and exploiting a redundancy in fundus image data relating particularly to the geometry. We propose a novel algorithm for the cup and disc segmentation “EffUnet” with an efficient convolution block and combine this with an extended spatial generative approach for geometry modelling and classification, termed “SpaGen” We demonstrate the high accuracy achievable by EffUnet in detecting the optic disc and cup boundaries and show how our algorithm can be quickly trained with new data by recalibrating the EffUnet layer only. Our resulting glaucoma detection algorithm, “EffUnet-SpaGen”, is optimized to significantly reduce the computational burden while at the same time surpassing the current state-of-art in glaucoma detection algorithms with AUROC 0.997 and 0.969 in the benchmark online datasets ORIGA and DRISHTI, respectively. Our algorithm also allows deformed areas of the optic rim to be displayed and investigated, providing explainability, which is crucial to successful adoption and implementation in clinical settings

Prospective, single UK centre, comparative study of the predictive values of contrast-enhanced ultrasound compared to time-resolved CT angiography in the detection and characterisation of endoleaks in high-risk patients undergoing endovascular aneurysm repair surveillance: a protocol.

INTRODUCTION: Diagnosis of endoleaks is imperative to prevent failure of endovascular aneurysm repairs (EVARs). The gold standard for diagnosis of endoleaks is catheter-directed subtraction angiography, which is not a practicable choice for surveillance. CT angiography (CTA) is the historical surveillance modality of choice. Concerns over cost, potential nephrotoxicity of contrast agents and repeated radiation exposure led to colour duplex ultrasound scan (CDUS) becoming an established alternative. CDUS has a lower sensitivity and specificity for endoleaks detection compared to CTA. Contrast-enhanced ultrasound scan (CEUS) represents an improvement of ultrasound imaging but comparisons against CTA report widely varying results, likely due to technical factors of CEUS and limitations of single-phase CTA.The development of time-resolved CTA (tCTA) offers timing information that much more closely mirrors the dynamic information available from CEUS. Theoretically, these two imaging modalities have the best potential for diagnostic accuracy. The aim of this study will be to compare CEUS to tCTA and investigate the utility of other measurements available from tCTA. METHODS AND ANALYSIS: This is a prospective, single UK centre, comparative study of paired binary diagnostic imaging modalities. Patients identified in routine post-EVAR surveillance as at risk of having a graft-related endoleak will undergo a CEUS and tCTA on the same day. This will allow the first comparison of CEUS to a semidynamic form of CTA. CEUS sensitivity and specificity to endoleak detection will be calculated. ETHICS AND DISSEMINATION: The study has achieved ethical approval. We hope the results will define the diagnostic accuracy of CEUS in comparison to a semidynamic form of CTA, representing a methodological improvement from previous studies. Results will be submitted for presentation at national and international vascular surgeryandradiology meetings. The full results are planned to be published in a medical journal. TRIAL REGISTRATION NUMBER: NCT02688751

Automatic detection of glaucoma via fundus imaging and artificial intelligence: A review.

Glaucoma is a leading cause of irreversible vision impairment globally, and cases are continuously rising worldwide. Early detection is crucial, allowing timely intervention that can prevent further visual field loss. To detect glaucoma, examination of the optic nerve head via fundus imaging can be performed, at the center of which is the assessment of the optic cup and disc boundaries. Fundus imaging is non-invasive and low-cost; however, the image examination relies on subjective, time-consuming, and costly expert assessments. A timely question to ask is: "Can artificial intelligence mimic glaucoma assessments made by experts?". Specifically, can artificial intelligence automatically find the boundaries of the optic cup and disc (providing a so-called segmented fundus image) and then use the segmented image to identify glaucoma with high accuracy? We conducted a comprehensive review on artificial intelligence-enabled glaucoma detection frameworks that produce and use segmented fundus images and summarized the advantages and disadvantages of such frameworks. We identified 36 relevant papers from 2011-2021 and 2 main approaches: 1) logical rule-based frameworks, based on a set of rules; and 2) machine learning/statistical modelling based frameworks. We critically evaluated the state-of-art of the 2 approaches, identified gaps in the literature and pointed at areas for future research

Radial shape discrimination testing for new-onset neovascular age-related macular degeneration in at-risk eyes

We investigated the performance of the handheld radial shape discrimination (hRSD) test in detecting the development of neovascular AMD (nAMD) in a prospective, longitudinal, observational study. Patients diagnosed with unilateral nAMD, with no nAMD in the othereye (the study eye, SE), completed the hRSD test on consecutive, routine clinic visits up toa maximum of 12, or until they were diagnosed with nAMD in the SE based on slit-lamp biomicroscopy and spectral-domain OCT assessment, with fluorescein angiography confirmation. Masked grading was carried out to confirm the diagnosis of nAMD, and to ensure nocases of nAMD were missed. Receiver operating characteristics (ROC) analysis was used to explore the diagnostic performance of the hRSD test relative to clinical diagnosis. Data were available from 179 patients of whom 19 (10.6%; “converters”) developed nAMD in the SE. The mean hRSD threshold at conversion was -0.47 (95% CI -0.38 to -0.55) logMAR compared to -0.53 (-0.50 to -0.57) logMAR in 160 non-converters. hRSD threshold in the converters began to decline 190 days before diagnosis of nAMD. The ROC curve demonstrated that at an hRSD cut-off of -0.60 logMAR, sensitivity was 0.79 (0.54–0.94) with a specificity of 0.54 (0.46–0.62); positive and negative predictive values were 0.16 and 0.96 respectively. We conclude that the hRSD test has moderate sensitivity for detecting the earliest stages of nAMD in the at-risk fellow eyes of patients with unilateral nAMD, compared to clinical diagnosis. Given its relative inexpensiveness, ease of use and the inherent connectivity of the platforms it can be presented on, it may have a role in early detection of nAMD in the population at large