title: Auto-classification of acne lesions using multimodal imaging.
abstract: Differentiating inflammatory and non-inflammatory acne lesions and obtaining lesion counts is pivotal part of acne evaluation. Manual lesion counting has reliably demonstrated the clinical efficacy of anti-acne products for decades. However, maintaining assessment consistency within and across acne trials is an important consideration since lesion counting can be subjective to the individual evaluators, and the technique has not been rigorously standardized. VISIA-CR is a multi-spectral and multi-modal facial imaging system. It captures fluorescence images of Horn and Porphyrin, absorption images of Hemoglobin and Melanin, and skin texture and topography characterizing broad-spectrum polarized and non-polarized images. These images are analyzed for auto-classification of inflammatory and non-inflammatory acne lesion, measurement of erythema, and post-acne pigmentation changes. In this work the accuracy of this acne lesion auto-classification technique is demonstrated by comparing the auto-detected lesions counts with those counted by expert physicians. The accuracy is further substantiated by comparing and confirming the facial location and type of every auto-identified acne lesion with those identified by the physicians. Our results indicate a strong correlation between manual and auto-classified lesion counts (correlation coefficient >0.9) for both inflammatory and non inflammatory lesions This technology has the potential to eliminate the tedium of manual lesion counting, and provide an accurate, reproducible, and clinically relevant evaluation of acne lesions. As an aid to physicians it will allow development of a standardized technique for evaluating acne in clinical research, as well as accurately choosing treatment options for their patients according to the severity of a specific lesion type in clinical practice
authors.affiliation: Canfield Scientific Inc, Fairfield, NJ, USA.
authors.forename: Sachin V
authors.initials: SV
authors.lastname: Patwardhan
authors.forename: Joseph R
authors.initials: JR
authors.lastname: Kaczvinsky
authors.forename: James F
authors.initials: JF
authors.lastname: Joa
authors.forename: Douglas
authors.initials: D
authors.lastname: Canfield
mesh_terms: D000152:Acne Vulgaris / Q000145:classification / Q000175:diagnosis* / Q000473:pathology; D005453:Fluorescence; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D007249:Inflammation / Q000145:classification / Q000175:diagnosis / Q000473:pathology; D010781:Photography / Q000295:instrumentation / Q000379:methods*; D015203:Reproducibility of Results; D012720:Severity of Illness Index