title: Thermal depth profiling of vascular lesions: automated regularization of reconstruction algorithms.
abstract: Pulsed photo-thermal radiometry (PPTR) is a non-invasive, non-contact diagnostic technique used to locate cutaneous chromophores such as melanin (epidermis) and hemoglobin (vascular structures). Clinical utility of PPTR is limited because it typically requires trained user intervention to regularize the inversion solution. Herein, the feasibility of automated regularization was studied. A second objective of this study was to depart from modeling port wine stain PWS, a vascular skin lesion frequently studied with PPTR, as strictly layered structures since this may influence conclusions regarding PPTR reconstruction quality. Average blood vessel depths, diameters and densities derived from histology of 30 PWS patients were used to generate 15 randomized lesion geometries for which we simulated PPTR signals. Reconstruction accuracy for subjective regularization was compared with that for automated regularization methods. The objective regularization approach performed better. However, the average difference was much smaller than the variation between the 15 simulated profiles. Reconstruction quality depended more on the actual profile to be reconstructed than on the reconstruction algorithm or regularization method. Similar, or better, accuracy reconstructions can be achieved with an automated regularization procedure which enhances prospects for user friendly implementation of PPTR to optimize laser therapy on an individual patient basis.
authors.affiliation: Beckman Laser Institute and Medical Clinic, University of California, Irvine, CA 92612, USA. wverkruy@uci.edu
authors.forename: Wim
authors.initials: W
authors.lastname: Verkruysse
authors.forename: Bernard
authors.initials: B
authors.lastname: Choi
authors.forename: Jenny R
authors.initials: JR
authors.lastname: Zhang
authors.forename: Jeehyun
authors.initials: J
authors.lastname: Kim
authors.forename: J Stuart
authors.initials: JS
authors.lastname: Nelson
mesh_terms: D000465:Algorithms; D001331:Automation; D001808:Blood Vessels / Q000473:pathology*; D019339:Port-Wine Stain / Q000175:diagnosis*; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*; D013696:Temperature