4.7 Article

Distinguishing lupus lymphadenitis from Kikuchi disease based on clinicopathological features and C4d immunohistochemistry

Journal

RHEUMATOLOGY
Volume 60, Issue 3, Pages 1543-1552

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/rheumatology/keaa524

Keywords

artificial intelligence; biopsy; C4d; histopathology; immunohistochemistry; Kikuchi-Fujimoto disease; lymphadenopathy; machine learning; necrotizing lymphadenitis; systemic lupus erythematosus

Categories

Funding

  1. Department of Medical Research, National Taiwan University Hospital [107-6, UN106-016, UN107-011]

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Through clinical, histological, and immunohistochemical studies, distinguishing lupus lymphadenitis (LL) from Kikuchi disease (KD) is possible. LL patients tend to be older with broader lesion areas and distinctive histological features. C4d immunohistochemical staining is valuable in this differentiation.
Objectives. Distinguishing Kikuchi disease (KD) from lupus lymphadenitis (LL) histologically is nearly impossible. We applied C4d immunohistochemical (IHC) stain to develop diagnostic tools. Methods. We retrospectively investigated clinicopathological features and C4d IHC staining in an LL-enriched development cohort (19 LL and 81 KD specimens), proposed risk stratification criteria and trained machine learning models, and validated them in an external cohort (2 LL and 55 KD specimens). Results. Clinically, we observed that LL was associated with an older average age (33 vs 25 years; P=0.005), higher proportion of biopsy sites other than the neck [4/19 (21%) vs 1/81 (1%); P=0.004], and higher proportion of generalized lymphadenopathy compared with KD [9/16 (56%) vs 7/31 (23%); P=0.028]. Histologically, LL involved a larger tissue area than KD did (P=0.006). LL specimens exhibited more frequent interfollicular pattern [5/19 (26%) vs 3/81 (4%); P=0.001] and plasma cell infiltrates (P=0.002), and less frequent histiocytic infiltrates in the necrotic area (P=0.030). Xanthomatous infiltrates were noted in 6/19 (32%) LL specimens. Immunohistochemically, C4d endothelial staining in the necrotic area [11/17 (65%) vs 2/62 (3%); P<10(-7)], and capillaries/venules [5/19 (26%) vs 7/81 (9%); P=0.048] and trabecular/hilar vessels [11/18 (61%) vs 8/81 (10%); P<10(-4)] in the viable area was more common in LL. During validation, both the risk stratification criteria and machine learning models were superior to conventional histological criteria. Conclusions. Integrating clinicopathological and C4d findings could distinguish LL from KD.

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