Yale University School of Medicine Pompton Plains, NJ, United States
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Baran Gunes1, Lucy Duran Camacho1, Shawn Cowper2, Gauri Panse2, Elizabeth Bundschuh3, Alyssa Williams4, Nicolas Page5, Mary Karns6, Kathleen Aren6, Niki Pradhan7, Elana Bernstein8, Sarah Fantus9, Elizabeth Volkmann10, Heather Bukiri10, Chase Correia11, Francis Wilson1, Seamus Mawe12, J. Matthew Mahoney13, Monique Hinchcliff14 and Rui Wang15, 1Yale University School of Medicine, New Haven, CT, 2Yale School of Medicine - Dermatopathology, New Haven, CT, 3Yale University School of Medicine, New York, NY, 4Yale University School of Medicine, Winchester, MA, 5Yale University School of Medicine, Salem, CT, 6Northwestern University Division of Rheumatology, Chicago, IL, 7Columbia University Irving Medical Center, New York, NY, 8Division of Rheumatology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, 9Kansas City Physician Partners- Center for Rheumatic Disease, Kansas City, MO, 10University of California Los Angeles, Los Angeles, CA, 11Riverside Medical Group, Hampton, VA, 12The Jackson Laboratory, Bar Harbor, ME, 13Jackson Laboratory, Bar Harbor, ME, 14Yale School of Medicine, Westport, CT, 15Sanofi, Cambridge, MA
Background/Purpose: We previously published a proof-of-principle study demonstrating the potential utility of computer vision (Deep Neural Network/DNN) methods applied to stained skin biopsy sections from patients with systemic sclerosis (SSc) as a novel skin outcome. The present study compared the 'DNN-Fibrosis Score' with histopathologic and modified Rodnan Skin Score (mRSS) changes for participants enrolled in a clinical trial.
Methods: Ten adults with early (≤ 6 y) diffuse cutaneous SSc (15 ≤ mRSS ≤ 35) in an open-label belumosudil (ROCK2 inhibitor, 200 mg PO BID) trial had mRSS and two, 4mm, dorsal arm skin biopsies performed at weeks 0, 24, and 52. Biopsies were stained with CD34, CD3, CD8, alpha smooth muscle actin (ASMA), H&E, and trichrome. Two blinded dermatopathologists assessed biopsies for 16 histopathological parameters important in SSc (Van Praet JT et al., 2011). CD3+, CD8+ were counted, and visual analogue scales (VAS) were used to score CD34, ASMA, and relative SSc severity on H&E and trichrome (Fig. 1). A previously developed DNN algorithm (AlexNet) was applied to trichrome-stained images to generate a 'DNN-Fibrosis Score' as previously reported. 'DNN-Fibrosis Scores' were compared to mRSS using a linear regression model and Spearman correlation. Histopathologic parameters were compared to mRSS or DNN Fibrosis-Scores using logistic regression models. A p≤0.05 was considered significant.
Results: Five patients had paired biopsies (Fig. 2). The median (interquartile range/IQR) mRSS change between 0 - 52W was -2.5 (-11 to 7.5) while the median (IQR) DNN-Fibrosis Score change (W0 - last follow-up) was -6 (-10.5 to 6.5) (Fig. 3). Of the histopathological scores, subcutaneous (SC) fat loss (p = 0.012), eccrine entrapment (p = 0.008), % CD8+ among CD3+ cells (p = 0.006) changed most during treatment. The correlation between mRSS and DNN-Fibrosis Score for the 5 paired biopsies was 0.18 [at higher mRSS, i.e. 25-51, the correlation was weaker] (Fig. 3b). Per 1-unit mRSS increase, the histopathological parameter odds ratios (OR); p-values were: telangiectasia =2.01; 0.001, perivascular CD3+ =1.03; 0.015, and % of CD8+ among CD3+ =1.08; 0.031 (Fig. 3c). Likewise, per 1-unit DNN Fibrosis-Score increase, OR; p-values for histopathological parameters were: hyalinized collagen =1.1; 0.00033, SC fat loss =1.47; 0.00033, intima wall =1.21; 0.005, and eccrine entrapment =1.14; 0.046 (Fig. 3c).
Conclusion: In this novel exploratory analysis, the DNN-Fibrosis Score exhibited sensitivity to histopathologic changes. The weak correlation between mRSS and DNN-Fibrosis Score contrasted with our previous findings. We note that predicted DNN-Fibrosis Scores tended to be lower for participants with higher mRSS ( >25). We attribute this divergence to batch effects from staining protocols between our published and our current analysis which may be overcome with analyses of larger cohorts. However, despite the weak correlation with mRSS, the DNN-Fibrosis Score significantly correlated with a set of histopathological variables that were distinct from those correlated with mRSS, including hyalinized collagen, SC fat loss, intima wall thickness, and eccrine entrapment.
Figure 1. Histopathology assessment. a. Visual Analog Scale keys. b. Composite visual analog scales (from normal to maximum).
Figure 2. Stained sections from the 3 subjects with the largest mRSS changes between W0, 24 and 52 (40x).
Figure 3. Belumosudil open-label trial results. a. Subject’s mRSS W0 to last follow-up. b. Scatter plot of DNN Fibrosis Score and mRSS (p = 0.125). c. Ordinal logistic regression (95% CI) comparing DNN Fibrosis Score to 16 scored histologic parameters.
B. Gunes: None; L. Duran Camacho: None; S. Cowper: None; G. Panse: None; E. Bundschuh: None; A. Williams: None; N. Page: None; M. Karns: None; K. Aren: None; N. Pradhan: None; E. Bernstein: Boehringer Ingelheim, 2, 5, Kadmon, 5, Pfizer, 5; S. Fantus: None; E. Volkmann: Boehringer-Ingelheim, 2, 5, 6, CSL Behring, 2, GlaxoSmithKline, 2, Horizon, 5, Prometheus, 5, Roche, 2; H. Bukiri: None; C. Correia: None; F. Wilson: Amgen, 5, AstraZeneca, 5, Vifor Pharma, 5; S. Mawe: None; J. Mahoney: None; M. Hinchcliff: Boehringer-Ingelheim, 5, Kadmon, 5; R. Wang: None.