Biomedical Imaging and Instrumentation
Kavon Karrobi, PhD
Lecturer
Boston University
Boston, Massachusetts, United States
Aarohi Mehendale
Ph.D. Candidate
Boston University, United States
Anahita Pilvar
Postdoctoral Associate
Boston University, United States
Andreea Bujor
Assistant Professor
Boston University Chobanian & Avedisian School of Medicine, United States
Darren Roblyer
Associate Professor
Boston University, United States
Systemic sclerosis (SSc) or scleroderma is a chronic autoimmune disorder characterized by fibrosis (deposition of excess collagen) in the skin and internal organs, as well as vascular dysfunction[1]. While SSc is a rare disease with a prevalence of 3.8 to 50 individuals per 100,000 in the world and an incidence of 0.77 to 5.6 individuals per 100,000 each year, SSc disproportionately afflicts females compared to males with approximately 80% of diagnosed SSc patients being females[2,3]. The current gold standard of scleroderma skin assessment is the modified Rodnan Skin Score (mRSS, integer scale 0-3), which is an estimate of skin thickness based on clinical palpation where mRSS=0 refers to normal skin with no appreciable skin thickening and mRSS=3 refers to the most severe skin thickening[4]. Accurate quantification of skin fibrosis in scleroderma is of vital importance as it can provide important clues about the severity of disease, survival, and response to therapy[5,6]. mRSS, however, is a semi-quantitative, subjective metric with well documented drawbacks such as poor inter-observer reliability[7,8]. Thus, there is a need for a reproducible, objective, and quantitative metric of assessing scleroderma disease progression. Spatial Frequency Domain Imaging (SFDI) is a non-contact, widefield diffuse optical imaging technique that can quantify tissue reflectance and measure wavelength dependent tissue optical properties such as absorption (μa) and reduced scattering (μs′)[9]. The measured optical properties provide functional and structural information about the tissue[10]. We evaluated SFDI as an alternate and potentially improved method over mRSS for the tracking of scleroderma disease progression.
Details of SFDI are provided elsewhere[9,10]. Briefly, sinusoidal patterns at multiple NIR wavelengths and spatial frequencies are projected on a sample and the remitted light is captured by a camera (Figure-1). At each spatial frequency, three phases (0°, 120°, 240°) are projected and the captured images are demodulated and corrected for height and angle variations[11]. The resulting demodulated images are calibrated using a phantom with known optical properties to remove the instrument response and produce maps of calibrated diffuse reflectance (Rd). Using two spatial frequencies, each pixel in the calibrated Rd maps is converted to unique μa and μs′ values using a Monte Carlo based lookup table (LUT) inversion algorithm[10,12].
The study was conducted with an approved IRB protocol. SFDI measurements were performed on 10 SSc patients and 8 healthy controls (Table-1) at six different anatomic sites (right and left forearms, hands, and fingers), followed by corresponding mRSS assessments by a rheumatologist. For each anatomical site, mean values computed from SFDI maps were used to compare SFDI-derived parameters with clinical measurements. Biopsies were obtained from each subject’s forearm to assess collagen (Trichome staining) and dermal fibroblast activation (ASMA)[13].
Wilcoxon rank-sum tests were used to investigate differences in SFDI-derived parameters between healthy controls and SSc patients, and Wilcoxon signed-rank tests were used for SFDI differences between anatomical regions with mRSS=0 and regions with mRSS >0 in SSc patients. The Spearman’s rank correlation coefficient was used to assess correlations between SFDI parameters and mRSS and histopathology metrics. p-values< 0.05 were statistically significant.
While there was no significant difference in μa between SSc patients and healthy controls, there was a significant difference in μs′ between patients and controls, irrespective of race and ethnicity (Figure-2). Specifically, μs′ at the longer 851nm wavelength better distinguished SSc from healthy skin compared to the shorter 691nm wavelength. There was also a significant difference in μs′ (851nm) between healthy controls and patients with mRSS=0 (no palpable skin thickening), demonstrating SFDI can detect early changes that mRSS cannot. Additionally, among patients, there was a significant difference in μs′ comparing locations with mRSS=0 and locations with any level of skin fibrosis (mRSS >0).
There was no significant correlation between local μs′ and local mRSS (Figure-3). However, there was a significant negative correlation between local Rd (851nm) at 0.2mm-1 spatial frequency and the local mRSS. Local metrics were calculated by summing each metric at all six measurement sites per subject. These results suggest that while μs′ can differentiate healthy from SSc, as well as patients with preclinical skin involvement from those with skin fibrosis, Rd better correlates with the mRSS for subjects with clinical skin involvement.
Activation of dermal fibroblasts into ASMA-expressing myofibroblasts producing excess collagen is a hallmark of SSc disease progression[14], and we observed strong negative correlations between Rd and histopathology metrics of SSc (ASMA and Trichome)[13] across all subjects (Figure-4). The fact that Rd at 0.2mm-1 had the best correlations with local mRSS and histopathology suggests this spatial frequency is well matched to tissue depths related to fibrosis and/or SSc tissue remodeling, which aligns with median penetration depth estimates< 1.3mm using an established computational method[15].
Inter-/Intra-observer variability assessments with SFDI were performed on 10 separate healthy subjects using intraclass correlation coefficients (ICCs) to estimate the reliability of SFDI measurements[16,17]. While mRSS has ICCs< 0.8[7,8], the assessments showed excellent reliability (ICCs >0.8)[18] with SFDI.
A more compact hand-held SFDI device could overcome body positioning difficulties during measurements, thus improving efficiency to increase sample size and evaluate more anatomic sites. Nevertheless, the results indicate SFDI could be an improved, reliable method for objective and quantitative assessments of scleroderma disease progression.