Software BreastAnalyser for the semi-automatic analysis of breast cancer immunohistochemical images

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作者
Marina Rodríguez-Candela Mateos
Maria Azmat
Paz Santiago-Freijanes
Eva María Galán-Moya
Manuel Fernández-Delgado
Rosa Barbella Aponte
Joaquín Mosquera
Benigno Acea
Eva Cernadas
María D. Mayán
机构
[1] Complexo Hospitalario Universitario A Coruña (CHUAC),Institute of Biomedical Research of A Coruña (INIBIC)
[2] SERGAS,CiTIUS
[3] Universidade de Santiago de Compostela, Centro Singular de Investigación en Tecnoloxías Intelixentes da USC
[4] Complexo Hospitalario Universitario A Coruña (CHUAC),Department of Pathology
[5] SERGAS,Physiology and Cell Dynamics, Centro Regional de Investigaciones Biomédicas (CRIB) and Faculty of Nursing
[6] Universidad de Castilla-La Mancha,Grupo Mixto de Oncología Traslacional UCLM
[7] Universidad de Castilla-La Mancha,GAI Albacete
[8] Servicio de Salud de Castilla-La Mancha,Anatomic Pathology Unit
[9] Hospital General Universitario de Albacete,Breast Unit
[10] Complexo Hospitalario Universitario A Coruña (CHUAC),CELLCOM Research Group. Biomedical Research Center (CINBIO) and Institute of Biomedical Research of Ourense
[11] SERGAS,Pontevedra
[12] University of Vigo. Edificio Olimpia Valencia,Vigo (IBI)
[13] Campus Universitario Lagoas Marcosende,undefined
[14] 36310,undefined
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Scientific Reports | / 14卷
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摘要
Breast cancer is the most diagnosed cancer worldwide and represents the fifth cause of cancer mortality globally. It is a highly heterogeneous disease, that comprises various molecular subtypes, often diagnosed by immunohistochemistry. This technique is widely employed in basic, translational and pathological anatomy research, where it can support the oncological diagnosis, therapeutic decisions and biomarker discovery. Nevertheless, its evaluation is often qualitative, raising the need for accurate quantitation methodologies. We present the software BreastAnalyser, a valuable and reliable tool to automatically measure the area of 3,3’-diaminobenzidine tetrahydrocholoride (DAB)-brown-stained proteins detected by immunohistochemistry. BreastAnalyser also automatically counts cell nuclei and classifies them according to their DAB-brown-staining level. This is performed using sophisticated segmentation algorithms that consider intrinsic image variability and save image normalization time. BreastAnalyser has a clean, friendly and intuitive interface that allows to supervise the quantitations performed by the user, to annotate images and to unify the experts’ criteria. BreastAnalyser was validated in representative human breast cancer immunohistochemistry images detecting various antigens. According to the automatic processing, the DAB-brown area was almost perfectly recognized, being the average difference between true and computer DAB-brown percentage lower than 0.7 points for all sets. The detection of nuclei allowed proper cell density relativization of the brown signal for comparison purposes between the different patients. BreastAnalyser obtained a score of 85.5 using the system usability scale questionnaire, which means that the tool is perceived as excellent by the experts. In the biomedical context, the connexin43 (Cx43) protein was found to be significantly downregulated in human core needle invasive breast cancer samples when compared to normal breast, with a trend to decrease as the subtype malignancy increased. Higher Cx43 protein levels were significantly associated to lower cancer recurrence risk in Oncotype DX-tested luminal B HER2- breast cancer tissues. BreastAnalyser and the annotated images are publically available https://citius.usc.es/transferencia/software/breastanalyser for research purposes.
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