Urine diagnostic testing for bladder cancer using imaging flow cytometry
Author(s):
Mr Zohaib Khawaja
,
Mr Zohaib Khawaja
Affiliations:
Mr Kenneth Lai
,
Mr Kenneth Lai
Affiliations:
Mr PJ Chana
,
Mr PJ Chana
Affiliations:
Mr. Ramesh Thurairaja
,
Mr. Ramesh Thurairaja
Affiliations:
Mr. Muhammad Shamim Khan
,
Mr. Muhammad Shamim Khan
Affiliations:
Prof Prokar Dasgupta
,
Prof Prokar Dasgupta
Affiliations:
Dr Ashish Chandra
,
Dr Ashish Chandra
Affiliations:
Mr. Hidekazu Yamamoto
Mr. Hidekazu Yamamoto
Affiliations:
BAUS ePoster online library. Khawaja Z. 06/26/17; 177337; P1-9
Mr. Zohaib Khawaja
Mr. Zohaib Khawaja
Login now to access Regular content available to all registered users.

You may also access this content "anytime, anywhere" with the Free MULTILEARNING App for iOS and Android
Abstract
Discussion Forum (0)
Rate & Comment (0)
Introduction:
An accurate urine-based test for bladder cancer is the holy grail of bladder cancer diagnostics. Urine cytology provides the highest specificity although suffers from inter-observer variability and low sensitivity. We hypothesized that an objective assessment of urothelial cell morphology by high-resolution imaging flow cytometry will result in accurate diagnosis of bladder cancer.

Materials and Methods:
Following ethical approval, urine samples were collected from new haematuria patients undergoing cystoscopy. Samples were stained using a nuclear dye and analysed using the ImageStream® cytometer. More than 100,000 cell images were recorded per fixed-volume urine sample. Images of focused, singlet, nuclear stain positive cells were selected for analysis. Cytological parameters to differentiate between malignant and benign cases were assessed using the Paris System for Reporting Urinary Cytology (VandenBussche. Cytopathology 2016; 27(3): 153-6). Cases with <10 urothelial cells or those that encountered technical issues such as cell-clumping were excluded from imaging analysis.

Results:
79/96 of invited patients provided a urine sample for our study. Nucleated cell numbers per sample was significantly higher in cancer cases (9751±3999 vs 2264±314, p=0.002). Cancer cases also had significantly higher percentages of urothelial cells with a nuclear-cytoplasmic (N:C) ratio≥0.3 (p=0.015) and ≥0.5 (p=0.019), and a higher mean N:C ratio (p=0.033). ROC analysis revealed N:C ratio ≥0.3 to be optimal for discriminating cases with 80% sensitivity and 93% specificity.

Conclusions:
Imaging flow cytometry has the potential to identify bladder cancer cases with high sensitivity and specificity.
Introduction:
An accurate urine-based test for bladder cancer is the holy grail of bladder cancer diagnostics. Urine cytology provides the highest specificity although suffers from inter-observer variability and low sensitivity. We hypothesized that an objective assessment of urothelial cell morphology by high-resolution imaging flow cytometry will result in accurate diagnosis of bladder cancer.

Materials and Methods:
Following ethical approval, urine samples were collected from new haematuria patients undergoing cystoscopy. Samples were stained using a nuclear dye and analysed using the ImageStream® cytometer. More than 100,000 cell images were recorded per fixed-volume urine sample. Images of focused, singlet, nuclear stain positive cells were selected for analysis. Cytological parameters to differentiate between malignant and benign cases were assessed using the Paris System for Reporting Urinary Cytology (VandenBussche. Cytopathology 2016; 27(3): 153-6). Cases with <10 urothelial cells or those that encountered technical issues such as cell-clumping were excluded from imaging analysis.

Results:
79/96 of invited patients provided a urine sample for our study. Nucleated cell numbers per sample was significantly higher in cancer cases (9751±3999 vs 2264±314, p=0.002). Cancer cases also had significantly higher percentages of urothelial cells with a nuclear-cytoplasmic (N:C) ratio≥0.3 (p=0.015) and ≥0.5 (p=0.019), and a higher mean N:C ratio (p=0.033). ROC analysis revealed N:C ratio ≥0.3 to be optimal for discriminating cases with 80% sensitivity and 93% specificity.

Conclusions:
Imaging flow cytometry has the potential to identify bladder cancer cases with high sensitivity and specificity.
Code of conduct/disclaimer available in General Terms & Conditions

By clicking “Accept Terms & all Cookies” or by continuing to browse, you agree to the storing of third-party cookies on your device to enhance your user experience and agree to the user terms and conditions of this learning management system (LMS).

Cookie Settings
Accept Terms & all Cookies