Automated Detection of Malarial Retinopathy in Patients Diagnosed With Cerebral Malaria (ASPIRE)

Analyzing the Performance of Automated Software in the Identification of Malarial Retinopathy in Digital Retinal Images of Cerebral Malaria Patients

The focus of the study is performance validation of ASPIRE software device in processing mydriatic retinal images of a patient with clinically diagnosed Cerebral Malaria (CM), to detect malarial retinopathy (MR). The outcome expected is the sensitivity and specificity of ASPIRE in detecting MR in patients with clinical diagnosis of CM, who may be addressed by a physician or ophthalmic specialist with follow-up and/or treatment. The reference standard for detection of MR is based on an adjudicated diagnoses by a panel of three ophthalmic graders (ophthalmologists) trained in the detection of MR in retinal images.

Study Overview

• Status: Completed
• Conditions: Cerebral Malaria; Malarial Retinopathy
• Intervention / Treatment: Diagnostic test: Automated software for malarial retinopathy detection

Detailed Description

A prospective, pivotal, multi-center clinical study was conducted at 12 healthcare facilities (hospitals and clinics) across two countries in Africa, Malawi and Nigeria; with the goal to validate the performance of ASPIRE in detecting malarial retinopathy (MR) in the retinal images of diagnosed cerebral malaria (CM) patients. The clinical evaluation was conducted in compliance with 21 CFR parts 50, 56, and 812, under the institutional review board (IRB) and/or independent ethics committee (IEC) approval provided by an internal IRB or IEC of the respective institution or clinical facility, and in accordance with good clinical practice (GCP). The internal IRB or IEC's that reviewed the study application are in compliance with the definition in 21 CFR 812.3(t) and GCP. Informed consent was obtained from all enrolled subjects.

The study recruited and imaged N = 834 pediatric patients below 21 years of age with clinical diagnosis of cerebral malaria (intended target population). Of these, 141 patient-cases were rejected either by human graders (reference standard) or by the image quality analysis (IQA) algorithm due to inadequate image quality in the patient-case, or had a missing ASPIRE output for MR detection. Remaining N=693 patient-cases with adequate image quality were used for the validation of MR detection algorithm.

The clinical study relied on the out-of-United States (OUS) clinical data due to the minuscule prevalence of malaria in the US (on an average, 2000 malaria cases are detected per year in the US, or 0.0006% of the US population is diagnosed with malaria). Malaria is not endemic and does not regularly occur or spread in the US. The greatest prevalence and risk of CM and malaria is in the sub-Saharan region of Africa. Over 90% of malaria cases in Africa are due to the Plasmodium falciparum parasite, which causes CM and MR; for which the clinical sites and facilities in Sub-Saharan African countries were engaged to enroll CM patients and collect clinical validation data. The ASPIRE software application used in this clinical study conducted outside the United States is identical to the ASPIRE software application developed in the US.

The study recruited N = 834 pediatric patients clinically diagnosed with cerebral malaria. The study population represented the intended population for the use of this device. All recruited patients were imaged with VistaView retinal camera operated by the users who were minimally skilled healthcare providers such as nurses or medical technicians. Before any patient-participant was recruited and imaged using VistaView camera, ASPIRE users underwent a one-time standardized training program on how to acquire images, how to reattempt imaging and improve image quality if ASPIRE gave an inadequate image quality result, and how to submit images for analysis to ASPIRE. All users underwent the same standardized training program using VistaView camera, irrespective of their educational qualifications, clinical experience, clinical environment, and the type of clinical setting. No additional training was provided to users for the duration of the study.

Study population: The target/intended population for ASPIRE is pediatric population under 21 years of age, clinically diagnosed with cerebral malaria. The enrollment was conducted sequentially at all clinical sites. The study investigators, local principal investigators, and study coordinators were trained to comply with GCP and study protocol and were committed to conduct the study accordingly, although no written commitments were obtained.

Demographics: The study aims to collect data that spans the gender, race, and ethnicity distribution from subjects that meet the inclusion criteria.

Enrollment and informed consent: Subjects were enrolled at the time of diagnosis of CM. If the patients met the inclusion criteria, the patient's parents or guardian were approached with information regarding the study. If parents/guardians agreed to participate, clinic personnel followed and gained informed consent. No subject sampling was done to enroll subjects in the clinical study. Thus, enrollment was done in consecutive order as subjects clinically diagnosed with CM were identified and consent was obtained. No incentives were provided to subjects for study participation, except transportation as needed.

Description of protocol/study design: This clinical study is designed to collect data to establish the safety and effectiveness of ASPIRE when compared to the clinical reference standard. A total of 834 subjects clinically diagnosed with CM were recruited to participate in this study. These subjects were enrolled through 12 clinical sites. The study procedure was as follows:

1. Pupillary light response is checked and then pupils are dilated with 0.5% tropicamide or 10% phenylephrine.
2. A trained user (imager) captures retinal images using VistaView camera (at least 8 photos per eye: recommended as 4 optic disc centered, 4 macula centered, and 2 peripheral retinal photos).
3. The retinal images captured by VistaView camera are transmitted to a smartphone storage folder automatically.
4. The ASPIRE application accesses the stored retinal images and analyzes them for image quality using ASPIRE analysis software. The software either accepts or rejects each image based on adequate or inadequate image quality, respectively. A graphical display on smartphone is shown to the user that displays the captured image and whether it was accepted (passed image quality analysis) or rejected (failed image quality analysis).
5. The user takes additional retinal images if ASPIRE identifies that a sufficient number of adequate quality images is not available for processing, and then submits them again for ASPIRE's processing.
6. Once a sufficient number of adequate quality retinal images is available, images are analyzed for detection of malarial retinopathy (MR) by ASPIRE analysis software.
7. The analysis of retinal images for image quality and MR detection is fully automatic and does not require manual inputs or intervention from the user.

Reference Standard: Using an internationally recognized grading system developed by the Malarial Retinopathy grading consensus group at the University of Liverpool (UoL), United Kingdom; the retinal images were independently reviewed and graded to determine the presence of malarial retinopathy lesions such as retinal whitening and hemorrhages, and the quality of retinal images. For each participating subject, the retinal images were graded independently by three experienced and validated graders. First, two ophthalmologists graded the images, and in case of significant differences in the two independent gradings, the third ophthalmologist independently adjudicated the grades. The ophthalmologists demonstrate over 15 years of experience in working with cerebral malaria patients and/or in grading and screening for malarial retinopathy lesions, and all of them received a training course in the grading of malarial retinopathy as per the MR grading protocol developed by the Malarial Retinopathy grading consensus group at the University of Liverpool (UoL), United Kingdom. Throughout the study, the graders and study staff were masked to the patient history, ASPIRE algorithm training, and/or ASPIRE algorithm outputs/results. The grading of retinal images by validated ophthalmic graders was used as the clinical reference standard for detecting the presence of malarial retinopathy, based on the definition of reference standard by the US FDA as the "best available" method for establishing the presence or absence of the target condition, that is acceptable within the medical, laboratory, and regulatory community. The reference standard for each subject was categorized as:

• Positive, if retinal whitening and/or hemorrhages were detected (MR detected)
• Negative, if retinal whitening and hemorrhages were not detected (MR not detected)
• Ungradable, if image quality was inadequate/questionable to grade MR (Inadequate photo quality)

Study Hypothesis: The study investigators aim to demonstrate MR detection performance of ASPIRE on a validation dataset collected with sequential enrollment of clinically diagnosed CM patients, with or without malarial retinopathy. About 61% of CM-diagnosed patients show manifestation of CM in retina, in form of retinal lesions, called malarial retinopathy (MR). The remaining 39% of CM-diagnosed patients may not exhibit MR. So, the prevalence of MR in CM-diagnosed patients is 61%. The study hypothesis is that the sensitivity and specificity of detecting MR using ASPIRE's MR detection software is non-inferior to the clinical reference standard, which is defined as the reading of retinal images for MR detection by ophthalmic specialists such as ophthalmologists.

Statistical power and sample size calculation: To establish that ASPIRE's software-based test is non-inferior to the standard test (ophthalmologist's reading of images) that exhibits sensitivity of 89% and specificity of 87%; the investigators require a minimum number of disease-positive (MR-positive) "cases" of 366, and minimum number of disease-negative (MR-negative) "controls" of 234. In total, the investigators require a minimum sample size of 600 CM-diagnosed patients to validate the proposed ASPIRE test. ASPIRE's minimum required performance goals/thresholds are defined at 82% for sensitivity and 80% for specificity, reflecting the requirement to prove that ASPIRE's software-based test is non-inferior to the standard test (with a non-inferiority margin of 7%), and based on anticipated enrollment numbers and prespecified regulatory requirements.

The investigators propose to validate ASPIRE's software-based test performance on the MR-positive and MR-negative patients sample and verify if the resulting sensitivity/specificity is within the margin of difference. Upon verification, it can be concluded that the software-based test (ASPIRE) is non-inferior to the standard test within a non-inferiority margin of 7%.

ASPIRE processing: All images for each patient-case are processed by ASPIRE software. As per ASPIRE's image quality analysis (IQA) protocol, each image is processed by the IQA algorithm to determine a probability score for the image to have adequate quality. If the image is found to be inadequate quality, it is rejected from further processing for malarial retinopathy detection. The algorithm for MR detection requires at least four images with clinically acceptable/adequate quality to complete the processing of a patient-case. If the IQA algorithm does not find at least four images of adequate quality in a patient-case, then the case is rejected from the processing for malarial retinopathy (MR) detection, until additional images are captured and submitted for processing.

The MR detection algorithm uses the adequate quality case to determine the probability of detecting MR by combining individual MR probability scores of all adequate quality images obtained from the patient. The result for each clinically diagnosed CM patient is either "Malarial retinopathy detected", "Malarial retinopathy not detected", or "Inadequate photo quality" when adequate-quality images are not present. The ASPIRE results for each patient are compared to the clinical reference standard.

Study Data: The study recruited and imaged N = 834 patients with clinical diagnosis of cerebral malaria, and it was mutually exclusive from the patient data previously used for training the ASPIRE algorithm. Out of 834 patient-cases, 141 cases were rejected either due to inadequate image quality in patient-cases as determined by the human graders (33), or IQA algorithm (63), or the case had a missing ASPIRE output for MR detection (45). The adequate quality retinal image data of N=693 patients was used to validate the MR detection algorithm. This validation data included 394 MR-positive patients and 299 MR-negative patients, per the clinical reference standard. The prevalence of MR in inadequate quality data (determined by IQA algorithm) was 61%, against the clinical reference standard determined by human graders.

• Study Type: Interventional
• Enrollment (Actual): 834

Contacts and Locations

Study Locations

• Malawi
  • Mlambe, Malawi
    • Mlambe mission hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

• 1. Pediatric patients under 21 years admitted to any one of the study sites who satisfy the standard clinical case definition of cerebral malaria according to the World health organization (WHO) criteria:

  1. Blantyre coma score of ≤2
  2. Known positive result of a malaria test for peripheral Plasmodium falciparum parasitemia (blood smear or malaria rapid diagnostic test) 2. Consent provided by parents/caregivers of the eligible pediatric patients

Exclusion Criteria:

• Pediatric patients admitted who satisfy the standard clinical case definition of cerebral malaria, but there is no clinician/nurse available to do an examination within 6 hours of admission, or no consent provided by parents/caregivers.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Diagnostic
• Allocation: N/A
• Interventional Model: Single Group Assignment
• Masking: None (Open Label)

Number of Arms

1

Arms and Interventions

Participant Group / Arm

Intervention / Treatment

Experimental: Automated detection of malarial retinopathy in patients diagnosed with cerebral malaria; All recruited patients are subjected to retinal imaging using Vistaview retinal camera. The retinal images for each patient are processed by ASPIRE software. As per ASPIRE's image quality analysis (IQA) protocol, each image is processed by the IQA algorithm to determine a probability score for the image to have adequate quality. The algorithm for malarial retinopathy (MR) detection requires at least four images with clinically acceptable/adequate quality to complete the processing. The MR detection algorithm uses the adequate quality case to determine the probability of detecting MR by combining individual MR probability scores of all adequate quality images obtained from the patient. The result for each clinically diagnosed CM patient is either "Malarial retinopathy detected", "Malarial retinopathy not detected", or "Inadequate photo quality" when adequate-quality images are not present. The ASPIRE results for each patient are compared to the clinical reference standard.

Diagnostic test: Automated software for malarial retinopathy detection; ASPIRE mobile application (App) software is intended to perform computer-aided detection of malarial retinopathy (MR) in digital retinal images of clinically diagnosed cerebral malaria (CM) patients under 21 years of age, to be used by a healthcare provider (user) with basic training, in primary care settings such as healthcare clinics and hospitals. The mobile Application hosts a software module developed using Deep-Learning algorithms to analyze digital retinal images of diagnosed CM patients for features suggestive of malarial retinopathy. ASPIRE requires at least four adequate quality retinal images (as determined by the image quality analysis software) captured from a patient to process it for MR detection. ASPIRE outputs a screening result of "Malarial retinopathy detected" or "Malarial retinopathy not detected" to the user. ASPIRE software is designed and validated to perform at clinically acceptable sensitivity and specificity in the detection of MR.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Sensitivity and Specificity of ASPIRE to Detect Malarial Retinopathy in Eyes of the Subjects Clinically Diagnosed With CM	The primary endpoint is the non-inferiority test for sensitivity and specificity (with two-sided 95% confidence intervals or CIs) of ASPIRE to detect malarial retinopathy in eyes of the subjects clinically diagnosed with CM, when compared to the reference standard. ASPIRE and the ophthalmic grader panel (reference standard) give their outputs based on the analysis of a set of retinal fundus photographs captured with mydriasis from the study subjects, that are compared to calculate ASPIRE's performance.	Through the study completion, an average of 2 years

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Positive Predictive Value (PPV) and Negative Predictive Value (NPV) of ASPIRE to Detect Malarial Retinopathy in Eyes of the Subjects Clinically Diagnosed With CM	Secondary endpoints include positive predictive value (PPV) and negative predictive value (NPV) of ASPIRE to detect malarial retinopathy in eyes of the subjects clinically diagnosed with CM, when compared against the reference standard.	Through the study completion, an average of 2 years

Collaborators and Investigators

• Sponsor: VisionQuest Biomedical LLC
• Collaborators: National Institute of Allergy and Infectious Diseases (NIAID); Kamuzu University of Health Sciences; Federal Ministry of Health, Nigeria

Publications and helpful links

General Publications

• Harding SP, Broadbent DM, Neoh C, White MC, Vora J. Sensitivity and specificity of photography and direct ophthalmoscopy in screening for sight threatening eye disease: the Liverpool Diabetic Eye Study. BMJ. 1995 Oct 28;311(7013):1131-5. doi: 10.1136/bmj.311.7013.1131.
• Severe falciparum malaria. World Health Organization, Communicable Diseases Cluster. Trans R Soc Trop Med Hyg. 2000 Apr;94 Suppl 1:S1-90. No abstract available.
• Reyburn H, Mbatia R, Drakeley C, Carneiro I, Mwakasungula E, Mwerinde O, Saganda K, Shao J, Kitua A, Olomi R, Greenwood BM, Whitty CJ. Overdiagnosis of malaria in patients with severe febrile illness in Tanzania: a prospective study. BMJ. 2004 Nov 20;329(7476):1212. doi: 10.1136/bmj.38251.658229.55. Epub 2004 Nov 12.
• Noubiap JJ, Nkeck JR, Kwondom BS, Nyaga UF. Epidemiology of infective endocarditis in Africa: a systematic review and meta-analysis. Lancet Glob Health. 2022 Jan;10(1):e77-e86. doi: 10.1016/S2214-109X(21)00400-9.
• Maude, R.J., Sayeed, A.A., Beare, N.A. et al. Retinopathy and microcirculation in adult severe malaria. Malar J 9 (Suppl 2), I7 (2010)
• Beare NA, Southern C, Chalira C, Taylor TE, Molyneux ME, Harding SP. Prognostic significance and course of retinopathy in children with severe malaria. Arch Ophthalmol. 2004 Aug;122(8):1141-7. doi: 10.1001/archopht.122.8.1141.
• Guidance for Industry and FDA Staff: Statistical Guidance on Reporting Results from Studies Evaluating Diagnostic Tests, Document issued on: March 13, 2007
• Harding SP, Lewallen S, Beare NA, Smith A, Taylor TE, Molyneux ME. Classifying and grading retinal signs in severe malaria. Trop Doct. 2006 Apr;36 Suppl 1:1-13. doi: 10.1258/004947506776315781. No abstract available.
• Daily JP, Minuti A, Khan N. Diagnosis, Treatment, and Prevention of Malaria in the US: A Review. JAMA. 2022 Aug 2;328(5):460-471. doi: 10.1001/jama.2022.12366.
• Colon-Gonzalez FJ, Sewe MO, Tompkins AM, Sjodin H, Casallas A, Rocklov J, Caminade C, Lowe R. Projecting the risk of mosquito-borne diseases in a warmer and more populated world: a multi-model, multi-scenario intercomparison modelling study. Lancet Planet Health. 2021 Jul;5(7):e404-e414. doi: 10.1016/S2542-5196(21)00132-7.
• Sani UM, Ahmed H, Jiya NM. Pattern of acquired heart diseases among children seen in Sokoto, North-Western Nigeria. Niger J Clin Pract. 2015 Nov-Dec;18(6):718-25. doi: 10.4103/1119-3077.163284.
• Gupta S, Sakhuja A, McGrath E, Asmar B. Trends, microbiology, and outcomes of infective endocarditis in children during 2000-2010 in the United States. Congenit Heart Dis. 2017 Mar;12(2):196-201. doi: 10.1111/chd.12425. Epub 2016 Nov 25.
• Piddock K, Beare N, MacCormick I. Malarial retinopathy affecting visual function in a Malawian adult with cerebral malaria. IDCases. 2014 Oct 13;1(4):82-3. doi: 10.1016/j.idcr.2014.10.003. eCollection 2014. No abstract available.
• Sithole, H. (2011). A review of malarial retinopathy in severe malaria. African Vision and Eye Health, 70(3), 129-135
• Beare NA, Taylor TE, Harding SP, Lewallen S, Molyneux ME. Malarial retinopathy: a newly established diagnostic sign in severe malaria. Am J Trop Med Hyg. 2006 Nov;75(5):790-7.
• White VA, Lewallen S, Beare NA, Molyneux ME, Taylor TE. Retinal pathology of pediatric cerebral malaria in Malawi. PLoS One. 2009;4(1):e4317. doi: 10.1371/journal.pone.0004317. Epub 2009 Jan 29.
• Birbeck GL, Beare N, Lewallen S, Glover SJ, Molyneux ME, Kaplan PW, Taylor TE. Identification of malaria retinopathy improves the specificity of the clinical diagnosis of cerebral malaria: findings from a prospective cohort study. Am J Trop Med Hyg. 2010 Feb;82(2):231-4. doi: 10.4269/ajtmh.2010.09-0532.
• Essuman VA, Ntim-Amponsah CT, Astrup BS, Adjei GO, Kurtzhals JA, Ndanu TA, Goka B. Retinopathy in severe malaria in Ghanaian children--overlap between fundus changes in cerebral and non-cerebral malaria. Malar J. 2010 Aug 12;9:232. doi: 10.1186/1475-2875-9-232.
• Lewallen S, Taylor TE, Molyneux ME, Wills BA, Courtright P. Ocular fundus findings in Malawian children with cerebral malaria. Ophthalmology. 1993 Jun;100(6):857-61. doi: 10.1016/s0161-6420(93)31563-0.
• Idro R, Marsh K, John CC, Newton CR. Cerebral malaria: mechanisms of brain injury and strategies for improved neurocognitive outcome. Pediatr Res. 2010 Oct;68(4):267-74. doi: 10.1203/PDR.0b013e3181eee738.
• Fernando SD, Rodrigo C, Rajapakse S. The 'hidden' burden of malaria: cognitive impairment following infection. Malar J. 2010 Dec 20;9:366. doi: 10.1186/1475-2875-9-366.
• English M, Punt J, Mwangi I, McHugh K, Marsh K. Clinical overlap between malaria and severe pneumonia in Africa children in hospital. Trans R Soc Trop Med Hyg. 1996 Nov-Dec;90(6):658-62. doi: 10.1016/s0035-9203(96)90423-x.
• Kallander K, Nsungwa-Sabiiti J, Peterson S. Symptom overlap for malaria and pneumonia--policy implications for home management strategies. Acta Trop. 2004 Apr;90(2):211-4. doi: 10.1016/j.actatropica.2003.11.013.
• Taylor TE, Fu WJ, Carr RA, Whitten RO, Mueller JS, Fosiko NG, Lewallen S, Liomba NG, Molyneux ME. Differentiating the pathologies of cerebral malaria by postmortem parasite counts. Nat Med. 2004 Feb;10(2):143-5. doi: 10.1038/nm986. Epub 2004 Jan 25.

Study record dates

Study Major Dates

• Study Start (Actual): March 15, 2022
• Primary Completion (Actual): April 30, 2024
• Study Completion (Actual): April 30, 2024

Study Registration Dates

• First Submitted: March 26, 2025
• First Submitted That Met QC Criteria: April 3, 2025
• First Posted (Actual): April 8, 2025

Study Record Updates

• Last Update Posted (Actual): July 3, 2025
• Last Update Submitted That Met QC Criteria: July 1, 2025
• Last Verified: July 1, 2025

More Information

Terms related to this study

• Keywords: Automated screening; Malarial retinopathy; Cerebral malaria
• Additional Relevant MeSH Terms: Vector Borne Diseases; Mosquito-Borne Diseases; Central Nervous System Diseases; Nervous System Diseases; Infections; Eye Diseases; Protozoan Infections; Parasitic Diseases; Central Nervous System Infections; Central Nervous System Parasitic Infections; Central Nervous System Protozoal Infections; Retinal Diseases; Malaria; Malaria, Cerebral
• Other Study ID Numbers: SB1AI162452 (U.S. NIH Grant/Contract)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: The IPD may remain as a part of trade secret and/or proprietary information for the sponsoring organization, and hence cannot be shared at individual participant's level.