Gunes Ilayda, Bernstein Elana, Cowper Shawn E, Panse Gauri, Pradhan Niki, Camacho Lucy Duran, Page Nicolas, Bundschuh Elizabeth, Williams Alyssa, Carns Mary, Aren Kathleen, Fantus Sarah, Volkmann Elizabeth R, Bukiri Heather, Correia Chase, Wang Rui, Kolachalama Vijaya, Wilson F Perry, Mawe Seamus, Mahoney J Matthew, Hinchcliff Monique
Yale School of Medicine, Department of Internal Medicine, Section of Rheumatology, Allergy, & Immunology.
Columbia University.
Res Sq. 2024 Oct 15:rs.3.rs-4889334. doi: 10.21203/rs.3.rs-4889334/v1.
The modified Rodnan skin score (mRSS), used to measure dermal thickness in patients with systemic sclerosis (SSc), is agnostic to inflammation and vasculopathy. Previously, we demonstrated the potential of neural network-based digital pathology applied to stained skin biopsies from SSc patients as a quantitative outcome. We leveraged deep learning and histologic analyses of clinical trial biopsies to decipher SSc skin features 'seen' by artificial intelligence (AI).
Adults with diffuse cutaneous SSc (disease duration ≤ 6 years) enrolled in an open-label trial evaluating belumosudil underwent serial mRSS assessment and dorsal arm biopsies at week 0, 24 and 52/end of trial. Two blinded dermatopathologists independently scored stained sections [Masson's trichrome, hematoxylin and eosin (H&E), CD3, CD34, CD8, α smooth muscle actin (αSMA)] for 16 published SSc dermal pathological parameters. We applied our previously published deep learning model to generate QIF signatures/biopsy and generated Fibrosis Scores. Associations between Fibrosis Score and mRSS (Spearman correlation); and between Fibrosis Score mRSS versus histologic parameters [odds ratios (OR)] were determined.
Only ten patients were enrolled because the sponsor terminated the trial early. Median, interquartile range (IQR) for mRSS change (0-52 weeks) for the five participants with paired biopsies was - 2.5 (-11-7.5), and for the ten participants was - 2 (-9-7.5). The correlation between Fibrosis Score and mRSS was R = 0.3; p = 0.674. Per 1-unit mRSS change (0-52W), histologic parameters with the greatest associated changes were (OR, p-value): telangiectasia (2.01, 0.001), perivascular CD3+ (1.03, 0.015), and % of CD8 + among CD3+ (1.08, 0.031). Likewise, per 1-unit Fibrosis Score change, parameters with greatest changes were (OR, p-value): hyalinized collagen (1.1, < 0.001), subcutaneous (SC) fat loss (1.47, < 0.001), thickened intima (1.21, 0.005), and eccrine entrapment (1.14, 0.046).
Belumosudil was associated with a non-clinically meaningful improvement in mRSS. Fibrosis Score changes correlated with histologic feature changes (., hyalinized collagen, SC fat loss) that were distinct from those associated with mRSS changes (., telangiectasia, perivascular CD3+, and % of CD8 + among CD3+). These data suggest that AI applied to SSc biopsies may be useful for quantifying pathologic features of SSc beyond skin thickness.
改良罗德南皮肤评分（mRSS）用于测量系统性硬化症（SSc）患者的皮肤厚度，对炎症和血管病变不敏感。此前，我们证明了基于神经网络的数字病理学应用于SSc患者染色皮肤活检作为定量结果的潜力。我们利用深度学习和临床试验活检的组织学分析来解读人工智能（AI）“看到”的SSc皮肤特征。
参加一项评估巴瑞替尼的开放标签试验的弥漫性皮肤型SSc（病程≤6年）成人患者在第0、24和52周/试验结束时接受了系列mRSS评估和上臂背部活检。两名盲法皮肤科病理学家对16项已发表的SSc皮肤病理参数的染色切片[马松三色染色、苏木精和伊红（H&E）、CD3、CD34、CD8、α平滑肌肌动蛋白（αSMA）]进行独立评分。我们应用我们之前发表的深度学习模型生成QIF特征/活检并生成纤维化评分。确定纤维化评分与mRSS之间的关联（斯皮尔曼相关性）；以及纤维化评分mRSS与组织学参数之间的关联[比值比（OR）]。
由于申办方提前终止试验，仅招募了10名患者。有配对活检的5名参与者的mRSS变化（0 - 52周）的中位数、四分位数间距（IQR）为 - 2.5（-11 - 7.5），10名参与者的为 - 2（-9 - 7.5）。纤维化评分与mRSS之间的相关性为R = ０.3；p = 0.674。每1单位mRSS变化（0 - 52周），关联变化最大的组织学参数为（OR，p值）：毛细血管扩张（2.01，0.001）、血管周围CD3 +（1.03，0.015）以及CD3 +中CD8 +的百分比（1.08，0.031）。同样，每1单位纤维化评分变化，变化最大的参数为（OR，p值）：玻璃样变的胶原（1.1，<0.001）、皮下（SC）脂肪减少（1.47，<0.001）、内膜增厚（1.２1，0.005）和汗腺包埋（1.14，0.046）。
巴瑞替尼与mRSS的非临床意义上的改善相关。纤维化评分变化与组织学特征变化（如玻璃样变的胶原、SC脂肪减少）相关，这些变化与mRSS变化（如毛细血管扩张、血管周围CD3 +以及CD3 +中CD8 +的百分比）相关的变化不同。这些数据表明，应用于SSc活检的AI可能有助于量化SSc除皮肤厚度之外的病理特征。
