Comparison of Ki67 Index Measurements in Breast Cancer with Manual and Digital Methods

Yıl 2023, Sayı: 20, 397 - 408, 09.09.2023

Zuhal Silav

https://doi.org/10.38079/igusabder.1299072

Öz

Aim: Ki67 protein, which shows promise as an immunohistochemical biomarker in breast cancer, is used in cell proliferation assessments since it is present in all active phases of the mitotic cycle. Ki67 index has predictive and prognostic value in patients with breast cancer. Ki67 counting with manual assessment (MD) is sensitive to interobserver variability and is time consuming. In recent years, studies indicating that digital image analysis (DGA) is fast and objective for Ki67 measurements have been increasing, but the routine application of this method requires further studies. In this study, we compared MD, DGA and GK Ki67 measurements in 85 invasive breast cancer cases.
Method: Tumor molecular types, mitotic numbers, Ki67 values measured by GK, MD and DGA and their correlations, were determined. DGA analyses were analyzed with ViraPath (Virasoft Yazılım, Istanbul, Turkey) software, and statistical correlations between parameters were analyzed with NCSS (Number Cruncher Statistical System, 2020).
Results: The correlations and differences of Ki67 index values determined by all three different methods in terms of age, histological grade, mitotic numbers, and molecular type were found to be compatible with the international literature. The intraclass correlation coefficient between Ki67 indices counted with DGA and MD was measured as 0.974, and the difference between Bland Altman analysis and MD and DGA counts was found to be close to zero.
Conclusion: DGA counts give reliable results to replace MD. With multicenter studies that optimize method standards, time savings and high sensitivity can be brought to the practice of pathology.

Anahtar Kelimeler

Breast Cancer, Ki67, manual counting, digital image analysis

Meme Kanserinde Ki67 İndeks Ölçümlerinin Manuel ve Dijital Yöntemler Açısından Kıyaslanması

Öz

Amaç: Meme kanserinde immunhistokimyasal biyobelirteç olarak umut vaat eden Ki67 proteini, mitoz döngüsünün tüm aktif fazlarında bulunduğundan hücre proliferasyon değerlendirmelerinde kullanılır. Ki67 indeksi meme kanserli hastalarda prediktif ve prognostik değerdedir. Manuel değerlendirme (MD) ile Ki67 sayımı gözlemciler arası değişkenliğe hassas ve zaman alıcıdır. Son yıllarda, dijital görüntü analizinin (DGA) Ki67 ölçümleri için hızlı ve objektif olduğunu belirten çalışmalar artmaktadır ancak bu yöntemin rutin uygulamaya girmesi ileri çalışmaları gerektirmektedir. Bu araştırmada 85 invaziv meme kanseri vakasında MD, DGA ve GK (göz kararı) Ki67 ölçümlerini kıyaslanmıştır.
Yöntem: Tümör moleküler tipleri, mitoz sayıları, GK, MD ve DGA ile ölçülmüş Ki67 değerleri ve korelasyonları saptandı. DGA analizleri ViraPath (Virasoft Yazılım, İstanbul, Türkiye) yazılımıyla, parametreler arasında istatistik korelasyonlar NCSS (Number Cruncher Statistical System, 2020) ile incelendi.
Bulgular: Her üç farklı metotla belirlenmiş Ki67 indeks değerlerinin yaş, histolojik derece, mitoz sayıları ve moleküler tip açısından korelasyon ve farklılıkları literatür ile uyumlu bulundu. DGA ve MD ile sayılmış Ki67 indeksleri arasında sınıf içi korelasyon katsayısı 0,974 olarak ölçüldü ve Bland Altman analizleri ile MD ve DGA sayımları arasındaki fark sıfıra yakın saptandı.
Sonuç: DGA sayımları MD’nin yerini alacak güvenilirlikte sonuçlar vermektedir. Çok merkezli ve metot standartlarını optimize edecek çalışmalarla patoloji pratiğine zamansal katkı ve yüksek hassasiyet kazandırılabilir.

Anahtar Kelimeler

Meme kanseri, Ki67, manuel sayım, dijital görüntü analizi

Teşekkür

Teşekkür: Yazar, dijital Ki67 taramalarında sağladıkları teknik destek ve Virapath yazılımını ücretsiz hibe etmesi nedeni ile Virasoft firmasına teşekkür eder.

Kaynakça

• Geread RS, Sivanandarajah A, Brouwer ER, et al. piNET-An automated proliferation index calculator framework for KI67 breast cancer images. Cancers (Basel). 2020;13(1):11.
• Arun I, Venkatesh S, Ahmed R, Agrawal SK, Leung SCY. Reliability of Ki67 visual scoring app compared to eyeball estimate and digital image analysis and its prognostic significance in hormone receptor-positive breast cancer. APMIS. 2021;129(8):489-502.
• Ayad E, Soliman A, Anis SE, Salem AB, Hu P, Dong Y. Ki 67 assessment in breast cancer in an Egyptian population: A comparative study between manual assessment on optical microscopy and digital quantitative assessment. Diagn Pathol. 2018;13(1):63.
• Marwah N, Batra A, Marwah S, Gupta V, Shakya S, Sen R. Correlation of proliferative index with various clinicopathologic prognostic parameters in primary breast carcinoma: A study from North India. J Cancer Res Ther. 2018;14(3):537-542.
• Zhong F, Bi R, Yu B, Yang F, Yang W, Shui R. A comparison of visual assessment and automated digital image analysis of Ki67 labeling index in breast cancer. PLoS One. 2016;11(2):e0150505.
• Goldhirsch A, Wood WC, Coates AS, et al. Strategies for subtypes--dealing with the diversity of breast cancer: Highlights of the St. Gallen International Expert Consensus on the primary therapy of early breast cancer 2011. Ann Oncol. 2011;22(8):1736-47.
• Ács B, Madaras L, Kovács KA, et al. Reproducibility and prognostic potential of Ki-67 proliferation index when comparing digital-image analysis with standard semi-quantitative evaluation in breast cancer. Pathol Oncol Res. 2018;24(1):115-127.
• Parks RM, Alfarsi LH, Green AR, Cheung KL. Biology of primary breast cancer in older women beyond routine biomarkers. Breast Cancer. 2021;28(5):991-1001.
• Zhu JW, Charkhchi P, Adekunte S, Akbari MR. What is known about breast cancer in young women? Cancers (Basel). 2023;15(6):1917.
• Ignatiadis M, Sotiriou C. Understanding the molecular basis of histologic grade. Pathobiology. 2008;75(2):104-11.
• Sun X, Kaufman PD. Ki-67: More than a proliferation marker. Chromosoma. 2018;127(2):175-186.
• Ibrahim A, Lashen A, Toss M, Mihai R, Rakha E. Assessment of mitotic activity in breast cancer: revisited in the digital pathology era. J Clin Pathol. 2022;75(6):365-372.
• Cheang MC, Chia SK, Voduc D, et al. Ki67 index, HER2 status, and prognosis of patients with luminal B breast cancer. J Natl Cancer Inst. 2009;101(10):736-50.
• Hashmi AA, Hashmi KA, Irfan M, et al. Ki67 index in intrinsic breast cancer subtypes and its association with prognostic parameters. BMC Res Notes. 2019;12(1):605.
• Kwon AY, Park HY, Hyeon J, et al. Practical approaches to automated digital image analysis of Ki-67 labeling index in 997 breast carcinomas and causes of discordance with visual assessment. PLoS One. 2019;14(2):e0212309.
• Wang M, McLaren S, Jeyathevan R, et al. Laboratory validation studies in Ki-67 digital image analysis of breast carcinoma: A pathway to routine quality assurance. Pathology. 2019;51(3):246-252.
• Morioka T, Niikura N, Kumaki N, et al. Comparison of Ki-67 labeling index measurements using digital image analysis and scoring by pathologists. Breast Cancer. 2018;25(6):768-777.
• Koopman T, Buikema HJ, Hollema H, de Bock GH, van der Vegt B. Digital image analysis of Ki67 proliferation index in breast cancer using virtual dual staining on whole tissue sections: Clinical validation and inter-platform agreement. Breast Cancer Res Treat. 2018;169(1):33-42.
• Reid MD, Bagci P, Ohike N, et al. Calculation of the Ki67 index in pancreatic neuroendocrine tumors: A comparative analysis of four counting methodologies. Mod Pathol. 2015;28(5):686-94.
• Gándara-Cortes M, Vázquez-Boquete Á, Fernández-Rodríguez B, et al. Breast cancer subtype discrimination using standardized 4-IHC and digital image analysis. Virchows Arch. 2018;472(2):195-203.
• Tao M, Chen S, Zhang X, Zhou Q. Ki-67 labeling index is a predictive marker for a pathological complete response to neoadjuvant chemotherapy in breast cancer: A meta-analysis. Medicine (Baltimore). 2017;96(51):e9384.
• Nielsen TO, Leung SCY, Rimm DL, et al. Assessment of Ki67 in Breast cancer: Updated recommendations from the international Ki67 in Breast Cancer Working Group. J Natl Cancer Inst. 2021;113(7):808-819.
• Muller K, Jorns JM, Tozbikian G. What's new in breast pathology 2022: WHO 5th edition and biomarker updates. J Pathol Transl Med. 2022;56(3):170-171.