June 2022
Volume 63, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2022
Diagnostic Yield of Vitreous Biopsy for Primary Vitreoretinal Lymphoma
Author Affiliations & Notes
  • sruti tekumalla
    Thomas Jefferson University Sidney Kimmel Medical College, Philadelphia, Pennsylvania, United States
  • David Xu
    Wills Eye Hospital, Philadelphia, Pennsylvania, United States
  • Katherine Awh
    Thomas Jefferson University Sidney Kimmel Medical College, Philadelphia, Pennsylvania, United States
  • Nancy Philp
    Thomas Jefferson University, Philadelphia, Pennsylvania, United States
  • Tatyana Milman
    Wills Eye Hospital, Philadelphia, Pennsylvania, United States
  • Sunir Garg
    Wills Eye Hospital, Philadelphia, Pennsylvania, United States
  • Footnotes
    Commercial Relationships   sruti tekumalla None; David Xu Gyroscope Therapeutics, Alimera Sciences, Code C (Consultant/Contractor); Katherine Awh None; Nancy Philp None; Tatyana Milman None; Sunir Garg Bausch & Lomb, Johnson & Johnson, Allergan, Kanaph, Regeneron, Aerpio, Apellis, Boehringer lngelheim, Code C (Consultant/Contractor)
  • Footnotes
    Support  Arch McNamara Research Grant
Investigative Ophthalmology & Visual Science June 2022, Vol.63, 3584 – A0013. doi:
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      sruti tekumalla, David Xu, Katherine Awh, Nancy Philp, Tatyana Milman, Sunir Garg; Diagnostic Yield of Vitreous Biopsy for Primary Vitreoretinal Lymphoma. Invest. Ophthalmol. Vis. Sci. 2022;63(7):3584 – A0013.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Primary vitreoretinal lymphoma (PVRL) is the most common intraocular lymphoproliferative disorder. The disease is often difficult to diagnose, having an insidious onset that can masquerade as chronic uveitis. Histologic identification remains important for diagnosis, and vitreous biopsy is frequently obtained. Degradation of fragile lymphoma cells after pars plana vitrectomy (PPV) occurs in many cases, and may be impacted by the transition to smaller gauge and very high cut rate vitrectomy. We evaluated the diagnostic yield of PPV, specifically using modern high-cut rate dual-cycle cutters, on in vitro cell viability and diagnostic yield.

Methods : Human Burkitt lymphoma cell line Namalwa was processed by 25-G dual blade guillotine-type vitrectomy at five different cut rates (500, 1000, 4000, 7500, or 15000 cuts per minute [cpm]) at 2x10^5 cells/mL suspended in BSS. The cell viability and diagnostic yield in each subtype group was determined using hemocytometry with trypan blue staining, viable cell count using Cell Counting Kit-8 (CCK-8), and ocular pathologist-guided manual count. Yield was analyzed by regression analysis and ANOVA test.

Results : Linear regression and ANOVA were performed using viable cell concentration as measured by CCK-8 and cut rate (Figure 1). Linear regression analysis of CCK-8 samples demonstrated no significant variation of cellular yield by cut rate (R2= 0.188, P=0.47). ANOVA found no statistically significant differences (P=0.61). The same were performed for histological cell count as a function of cut rate (Figure 2). Linear regression was not statistically significant (R2= 0.531, P = 0.16) as well as ANOVA (P = 0.096).

Conclusions : Using a dual blade, high cut rate vitrector system, there was no statistical significance correlating number of viable cells with increasing cut speed. These results suggest that in contrast to prior findings using 20G or 23G vitrectomy for diagnostic vitrectomy, modern vitrectomy systems may be employed at their maximum cut rate without compromising the viability of lymphoma cells and potential PVRL diagnoses.

This abstract was presented at the 2022 ARVO Annual Meeting, held in Denver, CO, May 1-4, 2022, and virtually.

 

Dilution curve using CCK-8 absorbances was used to estimate experimental cell concentrations from each cut rate. Linear regression (R2 0.188, P=0.47) and ANOVA (P=0.61) were not statistically significant.

Dilution curve using CCK-8 absorbances was used to estimate experimental cell concentrations from each cut rate. Linear regression (R2 0.188, P=0.47) and ANOVA (P=0.61) were not statistically significant.

 

Manual cell count was plotted as a function of cut rate. Linear regression (R2= 0.531, P=0.16) and ANOVA (P=0.096) were not statistically significant.

Manual cell count was plotted as a function of cut rate. Linear regression (R2= 0.531, P=0.16) and ANOVA (P=0.096) were not statistically significant.

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