António Polónia
Ipatimup Diagnostics
Team Member
Surgical Pathologist (MD) at Ipatimup Diagnostics (2014-Present)
Degree in Medicine (MD) (1998-2004): Faculdade de Ciência Médicas da Universidade Nova de Lisboa (FCM-UNL)
Master´s degree in Molecular Oncology (2010-2012): Faculdade de Medicina da Universidade do Porto (FMUP)
PhD degree in Molecular Oncology (2012-2018): Faculdade de Medicina da Universidade do Porto (FMUP)
Invited Associate Professor in Escola de Medicina e Ciências Biomédicas da Universidade Fernando Pessoa (EMCB-UFP) (2023-Present)
Co-chair of the Digital and Computational Pathology Working Group (DCP-WG) of the European Society of Pathology (ESP) (2021-Present)
Selected Publications
Shi R., Pinto J.C., Rienda I., Caie P., Eloy C., Polónia A.
Image analysis for bright-field HER2 in situ hybridization: validation for clinical use. Virchows Archiv:, 2024. [Journal: Article] [IF: 3.4 (*)]
DOI: 10.1007/s00428-024-03889-3 SCOPUS: 85200605232
Polónia A., Caramelo A.
HER2 in situ hybridization test in breast cancer: quantifying margins of error and genetic heterogeneity. Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc34(8):1478-1486, 2021. [Journal: Article] [CI: 9] [IF: 8,2]
DOI: 10.1038/s41379-021-00813-x SCOPUS: 85105817899
Polónia A., Canelas C., Caramelo A.
The spectrum of HER2 expression in breast cancer: linking immunohistochemistry quantification with in situ hybridization assay. Virchows Archiv480(6):1171-1179, 2022. [Journal: Article] [CI: 6] [IF: 3,5]
DOI: 10.1007/s00428-022-03290-y SCOPUS: 85124353881
Conde-Sousa E., Vale J., Feng M., Xu K., Wang Y., Della Mea V., La Barbera D., Montahaei E., Baghshah M., Turzynski A., Gildenblat J., Klaiman E., Hong Y., Aresta G., Araújo T., Aguiar P., Eloy C., Polónia A.
HEROHE Challenge: Predicting HER2 Status in Breast Cancer from Hematoxylin–Eosin Whole-Slide Imaging. Journal of Imaging8(8):, 2022. [Journal: Article] [CI: 21] [IF: 3,2]
DOI: 10.3390/jimaging8080213 SCOPUS: 85136794538
Polónia A., Campelos S., Ribeiro A., Aymore I., Pinto D., Biskup-Fruzynska M., Veiga R.S., Canas-Marques R., Aresta G., Araújo T., Campilho A., Kwok S., Aguiar P., Eloy C.
Artificial Intelligence Improves the Accuracy in Histologic Classification of Breast Lesions. American Journal of Clinical Pathology155(4):527-536, 2021. [Journal: Article] [CI: 19] [IF: 5,4]
DOI: 10.1093/ajcp/aqaa151 SCOPUS: 85102964948
Aresta G., Araújo T., Kwok S., Chennamsetty S.S., Safwan M., Alex V., Marami B., Prastawa M., Chan M., Donovan M., Fernandez G., Zeineh J., Kohl M., Walz C., Ludwig F., Braunewell S., Baust M., Vu Q.D., To M.N.N., Kim E., Kwak J.T., Galal S., Sanchez-Freire V., Brancati N., Frucci M., Riccio D., Wang Y., Sun L., Ma K., Fang J., Kone I., Boulmane L., Campilho A., Eloy C., Polónia A., Aguiar P.
BACH: Grand challenge on breast cancer histology images. Medical Image Analysis56:122-139, 2019. [Journal: Article] [CI: 438] [IF: 11,1]
DOI: 10.1016/j.media.2019.05.010 SCOPUS: 85067343074
Araujo T., Aresta G., Castro E., Rouco J., Aguiar P., Eloy C., Polonia A., Campilho A.
Classification of breast cancer histology images using convolutional neural networks. PLoS ONE12(6):, 2017. [Journal: Article] [CI: 756] [IF: 2,8]
DOI: 10.1371/journal.pone.0177544 SCOPUS: 85020032538
Shamai G., Schley R., Cretu A., Neoran T., Sabo E., Binenbaum Y., Cohen S., Goldman T., Polónia A., Drumea K., Stoliar K., Kimmel R.
Clinical utility of receptor status prediction in breast cancer and misdiagnosis identification using deep learning on hematoxylin and eosin-stained slides. Communications Medicine4(1):, 2024. [Journal: Article] [IF: 5.4 (*)]
DOI: 10.1038/s43856-024-00695-5 SCOPUS: 85212773131
Mercan C., Balkenhol M., Salgado R., Sherman M., Vielh P., Vreuls W., Polónia A., Horlings H.M., Weichert W., Carter J.M., Bult P., Christgen M., Denkert C., van de Vijver K., Bokhorst J.M., van der Laak J., Ciompi F.
Deep learning for fully-automated nuclear pleomorphism scoring in breast cancer. npj Breast Cancer8(1):, 2022. [Journal: Article] [CI: 9] [IF: 5,9]
DOI: 10.1038/s41523-022-00488-w SCOPUS: 85141368231
Shamai G., Livne A., Polónia A., Sabo E., Cretu A., Bar-Sela G., Kimmel R.
Deep learning-based image analysis predicts PD-L1 status from H&E-stained histopathology images in breast cancer. Nature Communications13(1):, 2022. [Journal: Article] [CI: 54] [IF: 16,6]
DOI: 10.1038/s41467-022-34275-9 SCOPUS: 85141603463
Polónia A., Pinto R., Cameselle-Teijeiro J.F., Schmitt F.C., Paredes J.
Prognostic value of stromal tumour infiltrating lymphocytes and programmed cell death-ligand 1 expression in breast cancer. Journal of Clinical Pathology70(10):860-867, 2017. [Journal: Article] [CI: 51] [IF: 2,9]
DOI: 10.1136/jclinpath-2016-203990 SCOPUS: 85027245035
Eloy C., Marques A., Pinto J., Pinheiro J., Campelos S., Curado M., Vale J., Polónia A.
Artificial intelligence–assisted cancer diagnosis improves the efficiency of pathologists in prostatic biopsies. Virchows Archiv482(3):595-604, 2023. [Journal: Article] [CI: 30] [IF: 3.4]
DOI: 10.1007/s00428-023-03518-5 SCOPUS: 85148422122
Faryna K., Tessier L., Retamero J., Bonthu S., Samanta P., Singhal N., Kammerer-Jacquet S.F., Radulescu C., Agosti V., Collin A., Farre´ X., Fontugne J., Grobholz R., Hoogland A.M., Moreira Leite K.R., Oktay M., Polonia A., Roy P., Salles P.G., van der Kwast T.H., van Ipenburg J., van der Laak J., Litjens G.
Evaluation of Artificial Intelligence-Based Gleason Grading Algorithms “in the Wild”. Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc37(11):, 2024. [Journal: Article] [CI: 3] [IF: 7.1 (*)]
DOI: 10.1016/j.modpat.2024.100563 SCOPUS: 85201462818
Rienda I., Vale J., Pinto J., Polónia A., Eloy C.
Using artificial intelligence to prioritize pathology samples: report of a test drive. Virchows Archiv:, 2024. [Journal: Article] [IF: 3.4 (*)]
DOI: 10.1007/s00428-024-03988-1 SCOPUS: 85211506703
Curado M., Caramelo A.S., Eloy C., Polónia A.
What to expect from the 2018 ASCO/CAP HER2 guideline in the reflex in situ hybridization test of immunohistochemically equivocal 2+ cases?. Virchows Archiv475(3):303-311, 2019. [Journal: Article] [CI: 8] [IF: 2,9]
DOI: 10.1007/s00428-019-02567-z SCOPUS: 85064443645
Polónia A., Oliveira G., Schmitt F.
Characterization of HER2 gene amplification heterogeneity in invasive and in situ breast cancer using bright-field in situ hybridization. Virchows Archiv471(5):589-598, 2017. [Journal: Article] [CI: 9] [IF: 2,9]
DOI: 10.1007/s00428-017-2189-9 SCOPUS: 85023176730
Polónia A., Eloy C., Pinto J., Braga A.C., Oliveira G., Schmitt F.
Counting invasive breast cancer cells in the HER2 silver in-situ hybridization test: how many cells are enough?. Histopathology71(2):247-257, 2017. [Journal: Article] [CI: 6] [IF: 3,3]
DOI: 10.1111/his.13208 SCOPUS: 85018695677
Eloy C., Vale J., Curado M., Polónia A., Campelos S., Caramelo A., Sousa R., Sobrinho-Simões M.
Digital pathology workflow implementation at ipatimup. Diagnostics11(11):, 2021. [Journal: Article] [CI: 45] [IF: 4]
DOI: 10.3390/diagnostics11112111 SCOPUS: 85119612542
Fraggetta F., L’imperio V., Ameisen D., Carvalho R., Leh S., Kiehl T.R., Serbanescu M., Racoceanu D., Mea V.D., Polonia A., Zerbe N., Eloy C.
Best practice recommendations for the implementation of a digital pathology workflow in the anatomic pathology laboratory by the european society of digital and integrative pathology (ESDIP). Diagnostics11(11):, 2021. [Journal: Article] [CI: 64] [IF: 4]
DOI: 10.3390/diagnostics11112167 SCOPUS: 85119998486
Image analysis for bright-field HER2 in situ hybridization: validation for clinical use. Virchows Archiv:, 2024. [Journal: Article] [IF: 3.4 (*)]
DOI: 10.1007/s00428-024-03889-3 SCOPUS: 85200605232
Polónia A., Caramelo A.
HER2 in situ hybridization test in breast cancer: quantifying margins of error and genetic heterogeneity. Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc34(8):1478-1486, 2021. [Journal: Article] [CI: 9] [IF: 8,2]
DOI: 10.1038/s41379-021-00813-x SCOPUS: 85105817899
Polónia A., Canelas C., Caramelo A.
The spectrum of HER2 expression in breast cancer: linking immunohistochemistry quantification with in situ hybridization assay. Virchows Archiv480(6):1171-1179, 2022. [Journal: Article] [CI: 6] [IF: 3,5]
DOI: 10.1007/s00428-022-03290-y SCOPUS: 85124353881
Conde-Sousa E., Vale J., Feng M., Xu K., Wang Y., Della Mea V., La Barbera D., Montahaei E., Baghshah M., Turzynski A., Gildenblat J., Klaiman E., Hong Y., Aresta G., Araújo T., Aguiar P., Eloy C., Polónia A.
HEROHE Challenge: Predicting HER2 Status in Breast Cancer from Hematoxylin–Eosin Whole-Slide Imaging. Journal of Imaging8(8):, 2022. [Journal: Article] [CI: 21] [IF: 3,2]
DOI: 10.3390/jimaging8080213 SCOPUS: 85136794538
Polónia A., Campelos S., Ribeiro A., Aymore I., Pinto D., Biskup-Fruzynska M., Veiga R.S., Canas-Marques R., Aresta G., Araújo T., Campilho A., Kwok S., Aguiar P., Eloy C.
Artificial Intelligence Improves the Accuracy in Histologic Classification of Breast Lesions. American Journal of Clinical Pathology155(4):527-536, 2021. [Journal: Article] [CI: 19] [IF: 5,4]
DOI: 10.1093/ajcp/aqaa151 SCOPUS: 85102964948
Aresta G., Araújo T., Kwok S., Chennamsetty S.S., Safwan M., Alex V., Marami B., Prastawa M., Chan M., Donovan M., Fernandez G., Zeineh J., Kohl M., Walz C., Ludwig F., Braunewell S., Baust M., Vu Q.D., To M.N.N., Kim E., Kwak J.T., Galal S., Sanchez-Freire V., Brancati N., Frucci M., Riccio D., Wang Y., Sun L., Ma K., Fang J., Kone I., Boulmane L., Campilho A., Eloy C., Polónia A., Aguiar P.
BACH: Grand challenge on breast cancer histology images. Medical Image Analysis56:122-139, 2019. [Journal: Article] [CI: 438] [IF: 11,1]
DOI: 10.1016/j.media.2019.05.010 SCOPUS: 85067343074
Araujo T., Aresta G., Castro E., Rouco J., Aguiar P., Eloy C., Polonia A., Campilho A.
Classification of breast cancer histology images using convolutional neural networks. PLoS ONE12(6):, 2017. [Journal: Article] [CI: 756] [IF: 2,8]
DOI: 10.1371/journal.pone.0177544 SCOPUS: 85020032538
Shamai G., Schley R., Cretu A., Neoran T., Sabo E., Binenbaum Y., Cohen S., Goldman T., Polónia A., Drumea K., Stoliar K., Kimmel R.
Clinical utility of receptor status prediction in breast cancer and misdiagnosis identification using deep learning on hematoxylin and eosin-stained slides. Communications Medicine4(1):, 2024. [Journal: Article] [IF: 5.4 (*)]
DOI: 10.1038/s43856-024-00695-5 SCOPUS: 85212773131
Mercan C., Balkenhol M., Salgado R., Sherman M., Vielh P., Vreuls W., Polónia A., Horlings H.M., Weichert W., Carter J.M., Bult P., Christgen M., Denkert C., van de Vijver K., Bokhorst J.M., van der Laak J., Ciompi F.
Deep learning for fully-automated nuclear pleomorphism scoring in breast cancer. npj Breast Cancer8(1):, 2022. [Journal: Article] [CI: 9] [IF: 5,9]
DOI: 10.1038/s41523-022-00488-w SCOPUS: 85141368231
Shamai G., Livne A., Polónia A., Sabo E., Cretu A., Bar-Sela G., Kimmel R.
Deep learning-based image analysis predicts PD-L1 status from H&E-stained histopathology images in breast cancer. Nature Communications13(1):, 2022. [Journal: Article] [CI: 54] [IF: 16,6]
DOI: 10.1038/s41467-022-34275-9 SCOPUS: 85141603463
Polónia A., Pinto R., Cameselle-Teijeiro J.F., Schmitt F.C., Paredes J.
Prognostic value of stromal tumour infiltrating lymphocytes and programmed cell death-ligand 1 expression in breast cancer. Journal of Clinical Pathology70(10):860-867, 2017. [Journal: Article] [CI: 51] [IF: 2,9]
DOI: 10.1136/jclinpath-2016-203990 SCOPUS: 85027245035
Eloy C., Marques A., Pinto J., Pinheiro J., Campelos S., Curado M., Vale J., Polónia A.
Artificial intelligence–assisted cancer diagnosis improves the efficiency of pathologists in prostatic biopsies. Virchows Archiv482(3):595-604, 2023. [Journal: Article] [CI: 30] [IF: 3.4]
DOI: 10.1007/s00428-023-03518-5 SCOPUS: 85148422122
Faryna K., Tessier L., Retamero J., Bonthu S., Samanta P., Singhal N., Kammerer-Jacquet S.F., Radulescu C., Agosti V., Collin A., Farre´ X., Fontugne J., Grobholz R., Hoogland A.M., Moreira Leite K.R., Oktay M., Polonia A., Roy P., Salles P.G., van der Kwast T.H., van Ipenburg J., van der Laak J., Litjens G.
Evaluation of Artificial Intelligence-Based Gleason Grading Algorithms “in the Wild”. Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc37(11):, 2024. [Journal: Article] [CI: 3] [IF: 7.1 (*)]
DOI: 10.1016/j.modpat.2024.100563 SCOPUS: 85201462818
Rienda I., Vale J., Pinto J., Polónia A., Eloy C.
Using artificial intelligence to prioritize pathology samples: report of a test drive. Virchows Archiv:, 2024. [Journal: Article] [IF: 3.4 (*)]
DOI: 10.1007/s00428-024-03988-1 SCOPUS: 85211506703
Curado M., Caramelo A.S., Eloy C., Polónia A.
What to expect from the 2018 ASCO/CAP HER2 guideline in the reflex in situ hybridization test of immunohistochemically equivocal 2+ cases?. Virchows Archiv475(3):303-311, 2019. [Journal: Article] [CI: 8] [IF: 2,9]
DOI: 10.1007/s00428-019-02567-z SCOPUS: 85064443645
Polónia A., Oliveira G., Schmitt F.
Characterization of HER2 gene amplification heterogeneity in invasive and in situ breast cancer using bright-field in situ hybridization. Virchows Archiv471(5):589-598, 2017. [Journal: Article] [CI: 9] [IF: 2,9]
DOI: 10.1007/s00428-017-2189-9 SCOPUS: 85023176730
Polónia A., Eloy C., Pinto J., Braga A.C., Oliveira G., Schmitt F.
Counting invasive breast cancer cells in the HER2 silver in-situ hybridization test: how many cells are enough?. Histopathology71(2):247-257, 2017. [Journal: Article] [CI: 6] [IF: 3,3]
DOI: 10.1111/his.13208 SCOPUS: 85018695677
Eloy C., Vale J., Curado M., Polónia A., Campelos S., Caramelo A., Sousa R., Sobrinho-Simões M.
Digital pathology workflow implementation at ipatimup. Diagnostics11(11):, 2021. [Journal: Article] [CI: 45] [IF: 4]
DOI: 10.3390/diagnostics11112111 SCOPUS: 85119612542
Fraggetta F., L’imperio V., Ameisen D., Carvalho R., Leh S., Kiehl T.R., Serbanescu M., Racoceanu D., Mea V.D., Polonia A., Zerbe N., Eloy C.
Best practice recommendations for the implementation of a digital pathology workflow in the anatomic pathology laboratory by the european society of digital and integrative pathology (ESDIP). Diagnostics11(11):, 2021. [Journal: Article] [CI: 64] [IF: 4]
DOI: 10.3390/diagnostics11112167 SCOPUS: 85119998486