Multispectral imaging (MSI) based on imaging and spectroscopy, as relatively novel to the field of histopathology, has been used in biomedical multidisciplinary researches. We analyzed and compared the utility of multispectral (MS) versus conventional red–green–blue (RGB) images for immunohistochemistry (IHC) staining to explore the advantages of MSI in clinical-pathological diagnosis. The MS images acquired of IHC-stained membranous marker human epidermal growth factor receptor 2 (HER2), cytoplasmic marker cytokeratin5/6 (CK5/6), and nuclear marker estrogen receptor (ER) have higher resolution, stronger contrast, and more accurate segmentation than the RGB images. The total signal optical density (OD) values for each biomarker were higher in MS images than in RGB images (all P < 0.05). Moreover, receiver operator characteristic (ROC) analysis revealed that a greater area under the curve (AUC), higher sensitivity, and specificity in evaluation of HER2 gene were achieved by MS images (AUC = 0.91, 89.1 %, 83.2 %) than RGB images (AUC = 0.87, 84.5, and 81.8 %). There was no significant difference between quantitative results of RGB images and clinico-pathological characteristics (P > 0.05). However, by quantifying MS images, the total signal OD values of HER2 positive expression were correlated with lymph node status and histological grades (P = 0.02 and 0.04). Additionally, the consistency test results indicated the inter-observer agreement was more robust in MS images for HER2 (inter-class correlation coefficient (ICC) = 0.95, r s = 0.94), CK5/6 (ICC = 0.90, r s = 0.88), and ER (ICC = 0.94, r s = 0.94) (all P < 0.001) than that in RGB images for HER2 (ICC = 0.91, r s = 0.89), CK5/6 (ICC = 0.85, r s = 0.84), and ER (ICC = 0.90, r s = 0.89) (all P < 0.001). Our results suggest that the application of MS images in quantitative IHC analysis could obtain higher accuracy, reliability, and more information of protein expression in relation to clinico-pathological characteristics versus conventional RGB images. It may become an optimal IHC digital imaging system used in quantitative pathology.
Cregger M, Berger AJ, Rimm DL. Immunohistochemistry and quantitative analysis of protein expression. Arch Pathol Lab Med. 2006;130:1026–30. PubMed
Tani S, Fukunaga Y, Shimizu S, Fukunishi M, Ishii K, Tamiya K. Color standardization method and system for whole slide imaging based on spectral sensing. Anal Cell Pathol (Amst). 2012;35:107–15. CrossRef
Van der Loos CM. Chromogens in multiple immunohistochemical staining used for visual assessment and spectral imaging: the colorful future. J Histotechnol. 2010;33:31–40. CrossRef
Edge SB, Byrd DR, Compton CC, Fritz AG, Greene FL, Trotti A. AJCC Cancer Staging Manual. 7th ed. New York: Springer; 2010.
Lakhani SR, Ellis IO, Schnitt SJ, Tan PH, van de Vijver MJ. WHO classification of tumours of the breast. World Health Organization classification of tumours. 4th ed. Lyon: IARC Press; 2012.
Nuance™ 3.0 Quick Start Guide. P/N 130805 Rev. 00. Caliper Life Sciences, Inc., 68 Elm St., Hopkinton, MA, 01748, USA 508-435-9500. www.CaliperLS.com.
McNutt NS, Levenson RM, Peters SB. Spectral imaging microscopy reveals nuclear eosinophilia in hyperchromatic nuclei of mycosis fungoides and other disorders. Am J Dermatopathol. 2005;27:532. CrossRef
Levenson R, Beechem J, McNamara G. Spectral imaging in preclinical research and clinical pathology. Stud Health Technol Inform. 2013;185:43–75. PubMed
Maeda T, Nakanishi Y, Hirotani Y, et al. Immunohistochemical co-expression status of cytokeratin 5/6, androgen receptor, and p53 as prognostic factors of adjuvant chemotherapy for triple negative breast cancer. Med Mol Morphol. 2015. doi: 10.1007/s00795-015-0109-0.
Badve S, Nakshatri H. Oestrogen-receptor-positive breast cancer: towards bridging histopathological and molecular classifications. J Chin Pathol. 2009;62:6–12. CrossRef
- Application of multispectral imaging in quantitative immunohistochemistry study of breast cancer: a comparative study
- Springer Netherlands