ABSTRACT
PURPOSE: To investigate the possibility of distinguishing between IgG4-related ophthalmic disease (IgG4-ROD) and orbital MALT lymphoma using artificial intelligence (AI) and hematoxylin-eosin (HE) images. METHODS: After identifying a total of 127 patients from whom we were able to procure tissue blocks with IgG4-ROD and orbital MALT lymphoma, we performed histological and molecular genetic analyses, such as gene rearrangement. Subsequently, pathological HE images were collected from these patients followed by the cutting out of 10 different image patches from the HE image of each patient. A total of 970 image patches from the 97 patients were used to construct nine different models of deep learning, and the 300 image patches from the remaining 30 patients were used to evaluate the diagnostic performance of the models. Area under the curve (AUC) and accuracy (ACC) were used for the performance evaluation of the deep learning models. In addition, four ophthalmologists performed the binary classification between IgG4-ROD and orbital MALT lymphoma. RESULTS: EVA, which is a vision-centric foundation model to explore the limits of visual representation, was the best deep learning model among the nine models. The results of EVA were ACC = 73.3% and AUC = 0.807. The ACC of the four ophthalmologists ranged from 40 to 60%. CONCLUSIONS: It was possible to construct an AI software based on deep learning that was able to distinguish between IgG4-ROD and orbital MALT. This AI model may be useful as an initial screening tool to direct further ancillary investigations.
ABSTRACT
Purpose: To examine the molecular biological differences between conjunctival mucosa-associated lymphoid tissue (MALT) lymphoma and orbital MALT lymphoma in ocular adnexa lymphoma. Methods: Observational case series. A total of 129 consecutive, randomized cases of ocular adnexa MALT lymphoma diagnosed histopathologically between 2008 and 2020.Total RNA was extracted from formalin-fixed paraffin-embedded tissue from ocular adnexa MALT lymphoma, and RNA-sequencing was performed. Orbital MALT lymphoma gene expression was compared with that of conjunctival MALT lymphoma. Gene set (GS) analysis detecting for gene set cluster was performed in RNA-sequence. Related proteins were further examined by immunohistochemical staining. In addition, artificial segmentation image used to count stromal area in HE images. Results: GS analysis showed differences in expression in 29 GS types in primary orbital MALT lymphoma (N=5,5, FDR q-value <0.25). The GS with the greatest difference in expression was the GS of epithelial-mesenchymal transition (EMT). Based on this GS change, immunohistochemical staining was added using E-cadherin as an epithelial marker and vimentin as a mesenchymal marker for EMT. There was significant staining of vimentin in orbital lymphoma (P<0.01, N=129) and of E-cadherin in conjunctival lesions (P=0.023, N=129). Vimentin staining correlated with Ann Arbor staging (1 versus >1) independent of age and sex on multivariate analysis (P=0.004). Stroma area in tumor were significant difference(P<0.01). Conclusion: GS changes including EMT and stromal area in tumor were used to demonstrate the molecular biological differences between conjunctival MALT lymphoma and orbital MALT lymphoma in ocular adnexa lymphomas.
ABSTRACT
PURPOSE: To investigate relationship between vitreous interleukin-6 levels and vitreous particles findings on widefield optical coherence tomography in posterior uveitis. METHODS: This retrospective study examined vitreous inflammatory cells (hyperreflective particles) of posterior uveitis on widefield optical coherence tomography (WOCT). We examined the number of hyperreflective particles (possibility of vitreous inflammatory cells) observed on WOCT and the correlations with interleukin-6 (IL-6) levels. The relationship between vitreous IL-6 levels and image findings from WOCT from 37 eyes (34 patients) with posterior uveitis were analyzed. Mean patient age was 63.4±15.7 years. (Mean± standard deviation) IL-6 concentration in vitreous humor was 79.9±7380.9 pg/mL Uveitis was infectious in 9 cases and non-infectious in 28 cases with multiplex polymerase chain reaction system. We measured the number and size of vitreous cells in the posterior vitreous, defined as the space between the upper vitreous and the internal limiting membrane on WOCT at the macular, upper, and lower regions. Image analysis software was also used for cell counting. RESULTS: A strong correlation was seen between human and software counts. Pearson's correlation coefficient (PCC) was performed to compare categorial variables (on macular +0.866; upper cavity +0.713; lower cavity +0.568; total vitreous cavity +0.834; P<0.001 each). IL-6 levels correlated with both vitreous cell counts and cell counts observed on macular WOCT (human-counted group +0.339, P = 0.04; software-counted group +0.349, P = 0.03). Infectious uveitis showed higher IL-6 levels (P = 0.016) and high cell counts compared with non-infectious uveitis (P = 0.04). CONCLUSIONS: Vitreous number of hyperreflective particles (cells) findings on WOCTcorrelated well with human and software cell counts. Vitreous cells findings on WOCT also correlated with IL-6 concentrations on macular.