
==== Front
J Cytol
J Cytol
JCytol
J Cytol
Journal of Cytology
0970-9371
0974-5165
Wolters Kluwer - Medknow India

JCytol-41-137
10.4103/joc.joc_177_23
Original Article
Utility of Image Morphometry in the Atypical Urothelial Cells and High-Grade Urothelial Carcinoma Categories of the Paris System for Reporting Urinary Cytology
Sharan K.C. 1
Rohilla Manish 1
Dey Pranab 1
Srinivasan Radhika 1
Kakkar Nandita 2
Mavuduru Ravimohan S. 3
1 Department of Cytology and Gynecological Pathology, Postgraduate Institute of Medical Education and Research, Chandigarh, India
2 Department of Histopathology, Postgraduate Institute of Medical Education and Research, Chandigarh, India
3 Department of Urology, Postgraduate Institute of Medical Education and Research, Chandigarh, India
Address for correspondence: Dr. Manish Rohilla, Department of Cytology and Gynec Pathology, Post Graduate Institute of Medical Education and Research, Chandigarh – 160 012, India. E-mail: rohillamanishpgi@gmail.com
Jul-Sep 2024
18 7 2024
41 3 137142
19 10 2023
10 4 2024
07 5 2024
Copyright: © 2024 Journal of Cytology | Indian Academy of Cytologists
2024
https://creativecommons.org/licenses/by-nc-sa/4.0/ This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
Introduction:

Urinary cytology (UrCy) is highly sensitive to diagnosing high-grade urothelial carcinoma (HGUC) but cannot predict muscularis propria invasion. Further, the atypical urothelial cell category (AUC) may have variable outcomes. Image morphometry (IM) may be a valuable adjunct technique in this setting. Hence, we evaluated IM in the AUC and HGUC categories to improve the diagnostic performance.

Materials and Methods:

The following six nuclear parameters were evaluated by IM on 3150 cells: nucleo-cytoplasmic (N:C) ratio, nuclear area, diameter, perimeter, standard deviation of the nuclear area (SDNA; pleomorphism) and integrated density (ID; nuclear chromasia), using the ImageJ software, in three cohorts based on the histopathology outcome: 20 cases of AUC – benign non-neoplastic outcome (AUC-B); 22 cases of HGUC Muscle invasive (HGUC-MI) and 21 cases of HGUC non-muscle invasive (HGUC-MF).

Results:

A retrospective analysis of urine cytology. The patient’s ages ranged from 36 to 85 years, with a mean age of 60.6. The male-to-female ratio was 5.4:1. A total of 20 cases of AUC-B and 43 cases of HGUC were selected for IM analysis. HGUC cases had higher nuclear parameters than AUC-B, and HGUC-MI had higher SDNA, ID, diameter, and area than HGUC-MF. SDNA and ID predict muscularis propria invasion in HGUC.

Conclusions:

Image morphometry successfully differentiates HGUC cases from benign non-neoplastic ones and might help to identify muscularis propria invasion in HGUC using a combination of nuclear parameters.

Atypical urothelial cells
image morphometry
risk of malignancy
risk stratification
urine cytology
urothelial carcinoma
==== Body
pmcINTRODUCTION

Cancers of the urinary bladder are currently the 10th most common malignancy worldwide, the 4th most common malignancy among males, and the 13th most commonest cause of all cancer-related deaths globally.[1] Cystoscopy is the gold standard for detecting bladder lesions in the initial management and follow-up. Urine cytology (UrCy) is a widely used method for screening primary or recurrent bladder malignancy despite its limitation in diagnosing low-grade urothelial carcinoma (LGUC). Recently, a standardized reporting system, “The Paris system for reporting urinary cytology (TPS),” was introduced, which includes specific diagnostic categories,[2] proper sampling, and processing recommendations that provide valuable material for ancillary tests like image morphometry (IM). Overall frequencies of the AUC and HGUC categories reported in our previous study were 8.5% and 14.1%.[3]

The two major challenging areas in UrCy are the atypical urothelial cells (AUC) and the prediction of myo-invasive carcinoma in high-grade urothelial carcinoma (HGUC), which is the most critical factor in deciding the further treatment of these patients. TPS has specifically emphasized reducing the reporting rate of AUC and recommends using ancillary techniques to categorize AUC as favoring reactive atypia or neoplasia.[2]

Image morphometry (IM) is utilized as an ancillary tool along with routine urinary cytology to differentiate benign cells from malignant cells in diagnosing urothelial carcinoma.[4] The IM methods allow a more objective assessment of nuclear and cellular characteristics, increasing the accuracy and decreasing the frequency of reporting of AUC cases.[5] Many previous studies described the usefulness of various cellular parameters like nuclear-to-cytoplasmic (N:C) ratio, nuclear area, cytoplasmic area, cell size, nuclear diameter, nuclear perimeter, nuclear roundness, and optical density to diagnose the urothelial neoplasm.[56789] Till now, very few studies have attempted to quantify all major and minor criteria of TPS, and no study is available to predict muscularis propria invasion in HGUC; hence, the present study was carried out to evaluate IM in predicting HGUC in comparison with AUC and muscularis propria invasion in HGUC.

MATERIALS AND METHODS

The study is approved by the PGIMER Institute Ethics Committee Year – 2020 with office number NK/6802/MD/469. This was a retrospective study of cases of urothelial neoplasm diagnosed and treated in a single institute from June 2016 to July 2020. Papanicolaou stained urine cytology imprint smears were prepared by processing voided urine samples using the Millipore filtration technique. All the cases were reported according to TPS.

The two cohorts of UrCy samples were selected with follow-up definitive histopathology diagnosis, which included 25 cases of AUC-B and 50 cases of HGUC. In the HGUC group, there were two groups selected: 25 cases of HGUC without muscularis propria invasion (HGUC-MF) and 25 cases of HGUC with muscularis propria invasion (HGUC-MI) depending on the follow-up biopsy diagnosis were selected for the IM. The number of cases was selected based on the incidence of AUC and HGUC, which was 4.1% and 9.5%, respectively, for four years. The cases with well-stained smears with well-preserved cells and well-visualized cellular morphology were chosen for study. On grounds of low cellularity and lack of well-visualized target cells, five cases of AUC-B, three cases of HGUC-MI, and four cases of HGUC-MF were excluded from the study. After exclusion, there were three cohorts: 20 cases of AUC-B, 22 cases of HGUC-MI, and 21 cases of HGUC-MF. IM was performed to differentiate HGUC from AUC-B, and its role in identifying myo-invasion in HGUC (HGUC-MF and MI) was explored.

Image morphometry was done with the help of Image J software (NIH) on Papanicolaou stained slides by taking multiple (15-20) representative images using an Olympus EP50 digital camera attached to a BX53 microscope in high power magnification (40X objectives).

For each case, a minimum of 50 malignant cells were assessed for six nuclear parameters, namely nuclear-cytoplasmic (N:C) ratio, nuclear area, nuclear diameter, nuclear perimeter, Standard deviation of the nuclear area (SDNA; a measure of pleomorphism) and Integrated density (ID; a measure of nuclear chromasia) using ImageJ software.[10] Image morphometric study on urothelial cells was a part of the study by Muralidaran et al.[11] It utilized Image J software (NIH) by adjusting the gray threshold value and converting it into an 8-bit gray image of each nucleus. All five nuclear parameters except the N:C ratio were evaluated similarly as described in previous studies and details given in subsequent texts.[111213141516]

The area of interest showed loosely cohesive clusters and singly scattered, non-overlapping, viable, well-preserved, and well-stained atypical/malignant cells (should have n = 50 representative cells), as shown in Figure 1a. If 50 representative cells were absent in the same area, more microphotographs were taken from the other area or slide, as shown in Figures 1b and 1c. The nuclear image of each cell was detected with the help of Image J software (NIH) in a sequential stepwise manner. The initial step was setting the measurement scale of Image J software. It is done because Image J software measures various parameters in pixels, and this pixel should be correlated to real-world units. Like in this study, µm is the unit in the image captured by a digital camera attached to a microscope in high power magnification (40X objectives), as shown in Figure 2a (the distance between two cells is 115.27 µm). This image of two points with a known distance was opened in Image J software, and a line was drawn between the two points. After this, under the heading of analyze, the set scale tab was opened; in the set scale window, the length of the line, in pixels, was displayed, the known distance was typed (115.27 µm), and the units of measure in the appropriate boxes were mentioned and checked “global” to apply this scale to other image frames and finally click OK shown in Figure 2b. For five nuclear parameters except for the N:C ratio, the following steps were followed: Step 1 – The image is imported in the ImageJ software and converted into an 8-bit gray image under the image tab shown in Figure 3a; Step 2 – Contrast and brightness of the image is adjusted by threshold subtab under image tab to facilitate software to distinguish nucleus from the cytoplasm [Figure 3b]; Step 3 – nuclei of cells to be analyzed were selected by wand tool [Figure 4a]; Step 4 – the threshold is applied over remaining all cells [Figure 4b]; Step 5 – various parameters were measures by analyze particles under analyze tab [Figure 5a]; Step 6 – image and results of measurement were saved [Figure 5b].

Figure 1 High-grade urothelial carcinoma case. (a) the area of interest with clusters and singly scattered non-overlapping atypical/malignant cells seen in single focus (n = 50 representative cells) (Papanicolaou stain, x400). (b and c), singly scattered non-overlapping atypical/malignant cells together n = 50 representative cells in two foci (Papanicolaou stain, x400)

Figure 2 (a and b) Demonstrate initial calibration in ImageJ software. (a) showed the distance between two cells on a microphotograph taken by a digital camera attached to a microscope (Papanicolaou stain, x400). (b) showed the same image in the ImageJ software with a set scale parameter (Papanicolaou stain, x400)

Figure 3 (a) The image is imported into the ImageJ software and converted into an 8-bit gray image under the image tab; (b) under the threshold subtab of the image tab, the contrast and brightness of the image were adjusted to facilitate software to distinguish the nucleus from the cytoplasm

Figure 4 (a) Nuclei of the cells to be analyzed were selected by a wand tool. (b) Threshold is applied over the selected cells

Figure 5 (a) Various parameters were measured by analyzing particles under analyze tab. (b) the image and the results of measurement were saved in an Excel format

We repeated the steps in the duplicate image to compute the N:C ratio [Figure 6a]. The entire cell was selected this time, and only the area was measured, as shown in Figure 6b. The cytoplasmic area was determined by subtracting the nuclear area [Figure 6c] from the entire cell area [Entire cell area – nuclear area = cytoplasmic area], and subsequently N:C ratio was attained by dividing nuclear by cytoplasmic area by Using the Microsoft Excel sheet formula. A separate Excel sheet was made for each case with all 50-cell data comprising the N:C ratio, nuclear area, nuclear diameter, nuclear perimeter, SDNA, ID, and the entire cell area. The average time to compute interpretable data from the initial point of capturing microphotographs under the microscope to perform IM in Image J software to enter the data in the Excel sheet is 15 to 20 minutes per case. Similar steps were repeated for each case of all three cohorts of study, namely AUC-benign, HGUC-MI, and HGUC-MF, and all the data was saved in a Microsoft Excel sheet. The whole process of IM is summarized in a flowchart, as shown in Figure 7. We have also given the JavaScript of Image J software for better reproducibility of the data as shown in Supplementary Table 1. For this, the whole JavaScript given in the right column of Supplementary Table 1 should be copied and pasted to plugins (plugin-new-JavaScript) of Image J software. After this, the bold text of step 1 (x:/path_to_your_image.jpg) in Supplementary Table 1 should be replaced by the location of the image in the folder of the computer. After that, on running the JavaScript only nuclear parameters can be computed directly. The JavaScript for the N:C ratio could not be created because it requires the selection of the whole cytoplasm manually with the help of the wand tool.

Figure 6 High-grade urothelial carcinoma case. (a) the area of interest with clusters and singly scattered non-overlapping malignant cells (n = 50 representative cells; Papanicolaou stain, x400). (b) – Measurement of the entire cell area. (c) – Measurement of nuclear area

Figure 7 Flowchart depicting the whole process of image morphometry followed in this study

Supplementary Table 1 – JavaScript for ImageJ software to compute nuclear parameters only

Steps	JavaScript for computing nuclear parameter	
Step 1 – Load an image from local disk (x drive)	var imagePath=“x:/path_to_your_image.jpg”
//Adjust the file extension if necessary	
	var imp=IJ.openImage (imagePath);	
Step 2 - Convert the image to 8-bit grayscale	IJ.run(imp, “8-bit”, “”)	
Step 3 – Apply thresholding	IJ.setAutoThreshold(imp, “Default dark”)	
Step 4 – Convert the image to binary	IJ.run(imp, “Convert to Mask”, “”)	
Step 5 – Display the processed image	imp.show();	
Step 6 – Set scale	var unit=“mm”//Change to your desired unit	
	var pixelWidth=1.0;//Change to the width of a pixel in your desired unit	
	var pixelHeight=1.0;//Change to the height of a pixel in your desired unit	
	var knownDistance=10.0;//Change to the known distance in your desired unit	
	var knownPixelDistance=100.0;//Change to the known distance in pixels	
	IJ.run (imp, “Set Scale...”, “distance=” + knownDistance + “ known=” + knownPixelDistance + “ pixel=” + pixelWidth + “ unit=” + unit + “ global”)	
Step 7 – Select the wand tool	IJ.setTool(“wand”)	
Step 8 – Open the final image with the wand tool selected	imp.show();	

Statistics

For descriptive statistics, mean + SD was used in the study. The Shapiro–Wilk test was used to check the data’s normality using SPSS (v28.0.10). Mann–Whitney and t-tests were performed for non-uniformly and uniformly distributed variables, respectively. To compare the four variables, we used the ANOVA post-HOC LSD test using SPSS (v28.0.10). All statistical tests were two-tailed, with a significance level of P ≤ 0.05.

RESULTS

On retrospective analysis of urine cytology, the patients’ ages ranged from 36 to 85 years, with a mean age of 60.6 and the male-to-female ratio was 5.4:1. In non-neoplastic cytology cases, the age range was 36 to 82 years, with a mean age of 56.4 years and the male-to-female ratio was 5.6:1, and in neoplastic lesions age range was 43–75 years with a mean age of 60.3 years and the male-to-female ratio was 14:1. The study’s objective was to apply IM in the AUC-B and HGUC categories and examine their utility in differentiating HGUC from AUC-B non-neoplastic cases and prediction of muscularis propria invasion in these HGUC cases. After excluding the cases with low cellularity and unpreserved morphology, we selected 20 AUC cases with a benign histopathology follow-up (AUC-B). In 20 AUC-B cases, 18 cases were reported as negative for malignancy with only normal urothelial cells in the biopsy; 1 case was reported as granulomatous inflammation, the stain for AFB was negative, and 1 case was reported as amyloidosis. Further, 43 HPE-proven HGUC cases were selected, 21 of which did not show muscularis propria invasion (HGUC-MF), and 22 showed frank invasion of the muscularis propria on HPE (HGUC-MI).

IM was performed in a total of 3150 cells as described. The statistics were applied to the output data showing the mean and SD for 1000 cells evaluated for the AUC-B group and 2150 cells for HGUC groups for the parameters of N:C ratio, nuclear area, nuclear diameter, nuclear perimeter, SDNA, and ID as shown in Table 1. HGUC groups [HGUC-MF (group 2) and HUC-MI (group 3)] had a higher mean N:C ratio, nuclear area, nuclear diameter, nuclear perimeter, SDNA, and ID than AUC-B (group 1). HGUC-MI showed maximum mean values of all six nuclear parameters among all three groups.

Table 1 Image Morphometry data of all parameters evaluated (n=63 cases; 1000 cells in AUC-benign-group 1, 1050 cells in HGUC-MF-group 2, and 1100 cells each in HGUC-MI-groups 3) [Annexure 2]

Group	Statistical parameter	Nuclear area	N:C ratio	Nuclear perimeter	SDNA	Integrated density	Nuclear diameter	
1 (AUC-Benign)	Mean	37.50	0.52	30.78	7.83	9477.89	5.72	
	SD	41.69	0.80	20.22	12.79	10469.01	6.02	
2 (HGUC-MF)	Mean	61.60	1.25	38.70	9.01	15080.80	7.37	
	SD	66.56	26.02	22.10	14.11	16934.52	3.53	
3 (HGUC-MI)	Mean	64.49	2.34	40.06	11.83	16454.76	7.55	
	SD	53.26	46.20	24.24	14.77	13499.70	3.15	
N:C Ratio-Nucleocytoplasmic ratio; SDNA-Standard deviation of the nuclear area – a measure of Pleomorphism; AUC-Atypical urothelial cells; HGUC-High grade urothelial carcinoma; MF-Muscle free; MI-Muscle invasive; (bold fonts highlighted maximum values)

Intergroup comparison (INGCOMP) of all nuclear parameters was carried out by ANOVA, and results are shown in Table 2 (bold fonts highlight significant P values). There is a statistical significance (P < 0.05) in the mean values of all the nuclear parameters between the HGUC groups [HGUC-MF (group 2) and HUC-MI (group 3)] and AUC-B. While in the HGUC group [group 2 (HGUC-MF) versus group 3 (HGUC-MI)], statistically significant differences (P < 0.05) were noted in SDNA and ID.

Table 2 Intergroup comparison of nuclear parameters

Group	ANOVA test, P^^	
	Nuclear area	N C Ratio*	Nuclear perimeter	SDNA^	Integrated density	Nuclear diameter	
Group 1 vs 2	<0.001	<0.001	<0.001	<0.001	<0.001	< 0.001	
Group 1 vs 3	<0.001	<0.001	<0.001	<0.001	<0.001	<0.001	
Group 2 vs 3	0.282	0.828	0.181	<0.001	0.043	0.243	
*N:C Ratio-Nucleocytoplasmic ratio. ^Standard deviation of the nuclear area measure of pleomorphism and integrated density is a measure of nuclear chromasia. ^^P value of ≤0.05 is considered to be significant (highlighted in bold fonts). Group 1 – AUC-benign; Group 2 – HGUC-MF; Group 3 – HGUC-MI

Thus, all the nuclear parameters differentiated AUC-B non-neoplastic lesions from HGUC. At the same time, SDNA (nuclear pleomorphism) and ID (nuclear chromasia) were associated with the muscularis propria invasion in the HGUC cases.

DISCUSSION

Expenditure on health care and management for bladder malignancy is considered one of the highest among all cancers.[17] Early diagnosis reduces the cost of care for the patients, eventually resulting in decreased mortality and morbidity rates. Urine cytology examination is a routine procedure that is the first step in diagnosing malignancy. To improve the diagnostic efficiency of urine cytology, various ancillary techniques are recommended by TPS.[2]

The main aim of this study is to assess the efficiency of IM as an ancillary technique for improving the diagnostic performance of cytology in identifying HGUC and predicting muscularis propria invasion in HGUC cases.

In our study using IM, we have attempted to quantify the various nuclear parameters, including N:C ratio. It was found that the mean values of the N:C ratio, nuclear area, perimeter, diameter, SDNA (nuclear pleomorphism), and ID (nuclear chromasia) were all higher in the HGUC cohort compared to the AUC-B non-neoplastic cohort and were also statistically significant. A study done by P K Lipponen et al.[12] in 1990 found that the nuclear area, nuclear volume, and corrected mitotic index were efficient in categorizing older 3-tier grading systems. R N Borland et al.[13] found that the values of the nuclear area, minimum feret-diameter ratio, and kurtosis of feret-diameter ratio were higher in cases with metastasis compared to non-metastatic HGUC. E Ozer et al.[14] found that mean nuclear area and minor diameter were associated with the advanced stage. David Ramos et al.[15] proposed that nuclear area appeared as an independent prognostic factor in LGUC. Kate Poropatich et al.[16] found that the nuclear area was higher in urothelial carcinoma than in reactive urothelial cells. All these studies correlate with our findings. In a recent study, Sakumo et al.[18] highlighted the usefulness of the N:C ratio, nuclear area and nuclear roundness in predicting HGUC cases in urine cytology by comparing these parameters between HGUC cases and reactive urothelial cells. However, a ROC curve was not attempted in our study as we compared the nuclear parameters between HGUC cells and AUC, rather a pure benign urothelial cell as done by the author. In addition, Sakumo et al.[18] did not include important nuclear parameters like pleomorphism and nuclear chromasia to assess chromatin, which are satisfactorily evaluated in the current study.[18] In overall findings from our study as well as from previous studies, it is clear that all six nuclear parameters on IM perfectly corroborate with the cytomorphological criteria to differentiate HGUC from AUC-B, as described by the TPS.[2]

The muscularis propria invasion in urothelial carcinoma cannot be assessed on urine cytology. However, along with cytomorphology, many ancillary techniques like detailed genetic examination were explored to predict muscularis propria invasion on urine samples.[19202122] In our study, two nuclear parameters, SDNA (nuclear pleomorphism) and ID (nuclear chromasia), were able to differentiate HGUC-MI from HGUC-MF. Similarly, Muralidaran et al.[11] analyzed nuclear area, nuclear diameter, nuclear perimeter, Standard deviation of nuclear area, and Integrated gray value. They found a significant difference in all parameters between malignant and benign cases. However, the author has used artificial intelligence. Nuclear pleomorphism (SDNA) and chromatin (ID) are important IM parameters differentiating benign versus malignant tumors.[52324] However, large prospective studies are required to validate these findings.

Follow-up data was available in all 43 cases of HGUC. Out of these 43 cases, disease recurrence was seen in 11 (25.5%) cases, including 6 HGUC-MI cases and 5 HGUC-MF cases. No statistical significance was observed when the nuclear parameters were analyzed between the HGUC cases with recurrence and HGUC cases without recurrence.

The average time taken to create the data (from taking microphotographs and assessment in image J software) in one case is around 15 to 20 minutes in the current study, which is far less than any other ancillary procedure performed on urine cytology. The advantage of the IM is that it gives objectivity in the measurement of nuclear parameters by using quantitative data, which may further help to develop cytomorphological parameters and an automated cytodiagnosis system.[71618]

Thus, in this study, using IM as an ancillary technique and comparing nuclear parameters and the N:C ratio among AUC-B non-neoplastic and HGUC cases, we found that all six nuclear parameters can differentiate AUC-B from HGUC cases. The nuclear parameters associated with muscularis propria invasion of HGUC are SDNA (nuclear pleomorphism) and ID (nuclear chromasia).

CONCLUSIONS

Thus, this study concludes that nuclear parameters such as nuclear area, nuclear diameter, nuclear perimeter, N:C ratio, Standard deviation of nuclear area, and Integrated gray value can differentiate AUC-B from HGUC cases. Further, SDNA (nuclear pleomorphism) and ID (nuclear chromasia) are associated with muscularis propria invasion in the HGUC cases. However, more prospective studies with large sample sizes and the application of artificial intelligence are required to validate these findings and to formulate a diagnostic set criterion for each differentiating parameter.

Key messages

Image morphometry (IM) may be a valuable adjunct technique that differentiates HGUC cases from benign non-neoplastic ones and might help to identify muscularis propria invasion in HGUC using a combination of nuclear parameters.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.
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