A Clinical Study to Evaluate Autofluorescence Imaging of Diabetic Foot Ulcers Using a Novel Artificial Intelligence Enabled Noninvasive Device

Abstract

Diabetic foot ulcers, with worldwide prevalence ranging from 12%-25%, are an important cause of nontraumatic lower limb amputation. Evidence-based assessment of early infection can help the clinician provide the right first line treatment thus helping improve the wound closure rate. Illuminate®, a novel point of care device working on multispectral autofluorescence imaging, helps in the rapid identification and classification of bacteria. This study was aimed to evaluate the diagnostic accuracy of the device in detecting bacterial gram type against standard culture methods. A total of 178 patients from a tertiary care center for diabetes was recruited and 203 tissue samples were obtained from the wound base by the plastic surgeon. The device was handled by the trained investigator to take wound images. The tissue samples were taken from the color-coded infected region as indicated by the device's Artificial Intelligence algorithm and sent for microbial assessment. The results were compared against the Gram type inferred by the device and the device was found to have an accuracy of 89.54%, a positive predictive value of 86.27% for detecting Gram-positive bacteria, 80.77% for Gram-negative bacteria, and 91.67% for no infection. The negative predictive value corresponded to 87.25% for Gram-positive, 92% for Gram-negative, and 96.12% for no infection. The Results exhibited the accuracy of this novel autofluorescence device in identifying and classifying the gram type of bacteria and its potential in significantly aiding clinicians towards early infection assessment and treatment.

Multimodal imaging device to comprehensively assess infection, oxygenation, and wound analytics—A pilot study

“…The device was set to ‘Autofluorescence’ mode to detect the presence of bioburden. The protocol followed for imaging was similar to the imaging procedure for the earlier version of the device (Illuminate®) as described previously 18 . To summarise, the wounds were cleaned with aseptic saline solution according to the standard wound care procedure prior to the imaging., The imaging was carried out under a black drape, to avoid the interference from surrounding light.…”

Artificial Intelligence Methodologies Applied to Technologies for Screening, Diagnosis and Care of the Diabetic Foot: A Narrative Review

“…The study by Viswanathan et al aimed to evaluate the accuracy of an imaging device working on multispectral autofluorescence (Illuminate ® , Adiuvo Diagnostics, Private Limited, Chennai, India) in detecting bacterial Gram type compared with standard culture methods [ 56 ]. Indeed, evidence-based assessment of early infections can be of help in providing the right first-line treatment, thus improving the wound healing rate.…”

Penggunaan perangkat pencitraan fluoresensi bakteri pada luka: A literature review

“…Kejadian ulkus kaki diabetik diawali dengan kejadian neuropati perifer yang akhirnya berujung pada luka kronis. Salah satu penyebab luka sulit sembuh pada pasien ulkus kaki diabetik adalah karena luka yang sudah terinfeksi secara kronis (Viswanathan, Govindan, Selvaraj, Rupert, & Kumar, 2021). Kejadian infeksi perlu di diagnosis berdasarkan gejala lokal dan sistemik yang terjadi pada pasien.…”

“…Pada 203 luka, FL-Imaging Device dapat mendeteksi bakteri pada 71,92% (146/203) luka, dan hal tersebut dibandingkan dengan hasil kultur yang telah dilakukan yaitu terdapat bakteri pada 86,2% (175/203) luka. Sehingga diketahui bahwa FL-Imaging Device memiliki akurasi sebesar 89,54% (Viswanathan, Govindan, Selvaraj, Rupert, & Kumar, 2021).…”

“…Penggunaan FL-Imaging Device telah berhasil dilakukan dalam mendiagnosis infeksi dan pertumbuhan bakteri pada luka, hal tersebut juga dijelaskan dalam setiap literatur diatas. Metode fluoresensi ini dipercaya sebagai salah satu metode yang paling mudah, tanpa memerlukan kontak langsung, dan sensitif untuk mendeteksi bakteri pada luka (Viswanathan, Govindan, Selvaraj, Rupert, & Kumar, 2021).…”