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  1. Article ; Online: Assessment of tumor-infiltrating lymphocytes in head and neck cancer: Clinical scenarios.

    Almangush, Alhadi / Mäkitie, Antti A / Leivo, Ilmo

    Oral oncology

    2024  Volume 153, Page(s) 106829

    MeSH term(s) Humans ; Head and Neck Neoplasms/immunology ; Head and Neck Neoplasms/pathology ; Lymphocytes, Tumor-Infiltrating/immunology
    Language English
    Publishing date 2024-05-04
    Publishing country England
    Document type Letter
    ZDB-ID 1120465-5
    ISSN 1879-0593 ; 0964-1955 ; 1368-8375
    ISSN (online) 1879-0593
    ISSN 0964-1955 ; 1368-8375
    DOI 10.1016/j.oraloncology.2024.106829
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    Zs.A 4869: Show issues Location:
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  2. Article ; Online: Intestinal-Type Adenocarcinoma: Classification, Immunophenotype, Molecular Features and Differential Diagnosis.

    Leivo, Ilmo

    Head and neck pathology

    2017  Volume 11, Issue 3, Page(s) 295–300

    Abstract: Intestinal-type adenocarcinoma is the second most frequent sinonasal adenocarcinoma. High incidence of these tumors is seen among workers with occupational wood dust exposure, particularly of hardwood dusts. Intestinal-type adenocarcinoma has striking ... ...

    Abstract Intestinal-type adenocarcinoma is the second most frequent sinonasal adenocarcinoma. High incidence of these tumors is seen among workers with occupational wood dust exposure, particularly of hardwood dusts. Intestinal-type adenocarcinoma has striking histomorphologic and immunophenotypic similarities with colorectal adenocarcinomas, but on the level of molecular pathologic mechanisms these tumors have their own specific features different from gastrointestinal tumors. This article provides an update on current histopathologic classification of intestinal-type adenocarcinomas, their immunophenotypic properties, recent advances in molecular pathologic features and differential diagnostic considerations.
    MeSH term(s) Adenocarcinoma ; Diagnosis, Differential ; Humans ; Immunophenotyping ; Paranasal Sinus Neoplasms
    Language English
    Publishing date 2017-09
    Publishing country United States
    Document type Journal Article ; Review
    ZDB-ID 2407834-7
    ISSN 1936-0568 ; 1936-055X
    ISSN (online) 1936-0568
    ISSN 1936-055X
    DOI 10.1007/s12105-017-0800-7
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  3. Article ; Online: Tumour budding in head and neck cancer: what have we learnt and the next steps towards clinical implementation.

    Almangush, Alhadi / Mäkitie, Antti A / Leivo, Ilmo

    British journal of cancer

    2023  Volume 130, Issue 1, Page(s) 1–2

    MeSH term(s) Humans ; Head and Neck Neoplasms/therapy ; Prognosis
    Language English
    Publishing date 2023-12-14
    Publishing country England
    Document type Letter ; Comment
    ZDB-ID 80075-2
    ISSN 1532-1827 ; 0007-0920
    ISSN (online) 1532-1827
    ISSN 0007-0920
    DOI 10.1038/s41416-023-02531-4
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  4. Article ; Online: Can TILs supplement the TNM staging system (as TNM-Immune)?

    Almangush, Alhadi / Mäkitie, Antti A / Leivo, Ilmo

    British journal of cancer

    2023  Volume 129, Issue 5, Page(s) 739–740

    MeSH term(s) Humans ; Neoplasm Staging ; Prognosis ; Lung Neoplasms/pathology ; Lymphocytes, Tumor-Infiltrating ; Dietary Supplements ; Retrospective Studies
    Language English
    Publishing date 2023-07-28
    Publishing country England
    Document type Letter ; Comment
    ZDB-ID 80075-2
    ISSN 1532-1827 ; 0007-0920
    ISSN (online) 1532-1827
    ISSN 0007-0920
    DOI 10.1038/s41416-023-02368-x
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  5. Article ; Online: Sinonasal Adenocarcinoma: Update on Classification, Immunophenotype and Molecular Features.

    Leivo, Ilmo

    Head and neck pathology

    2016  Volume 10, Issue 1, Page(s) 68–74

    Abstract: Adenocarcinomas of the sinonasal tract may originate from respiratory surface epithelium or the underlying seromucinous glands. These malignancies are divided into salivary-type adenocarcinomas and non-salivary-type adenocarcinomas. The latter are ... ...

    Abstract Adenocarcinomas of the sinonasal tract may originate from respiratory surface epithelium or the underlying seromucinous glands. These malignancies are divided into salivary-type adenocarcinomas and non-salivary-type adenocarcinomas. The latter are further divided into intestinal-type and nonintestinal-type adenocarcinomas. This review provides an update on tumor classification, differential diagnostic considerations and molecular features, as well as new adenocarcinoma entities in the sinonasal area.
    MeSH term(s) Adenocarcinoma/classification ; Adenocarcinoma/genetics ; Adenocarcinoma/pathology ; Biomarkers, Tumor ; Humans ; Immunophenotyping ; Paranasal Sinus Neoplasms/classification ; Paranasal Sinus Neoplasms/genetics ; Paranasal Sinus Neoplasms/pathology
    Chemical Substances Biomarkers, Tumor
    Language English
    Publishing date 2016-02-01
    Publishing country United States
    Document type Journal Article ; Review
    ZDB-ID 2407834-7
    ISSN 1936-0568 ; 1936-055X
    ISSN (online) 1936-0568
    ISSN 1936-055X
    DOI 10.1007/s12105-016-0694-9
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  6. Article ; Online: Interpretable machine learning model for prediction of overall survival in laryngeal cancer.

    Alabi, Rasheed Omobolaji / Almangush, Alhadi / Elmusrati, Mohammed / Leivo, Ilmo / Mäkitie, Antti A

    Acta oto-laryngologica

    2024  , Page(s) 1–7

    Abstract: Background: ...

    Abstract Background:
    Language English
    Publishing date 2024-01-27
    Publishing country England
    Document type Journal Article
    ISSN 1651-2251
    ISSN (online) 1651-2251
    DOI 10.1080/00016489.2023.2301648
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  7. Article ; Online: Artificial Intelligence-Driven Radiomics in Head and Neck Cancer: Current Status and Future Prospects.

    Alabi, Rasheed Omobolaji / Elmusrati, Mohammed / Leivo, Ilmo / Almangush, Alhadi / Mäkitie, Antti A

    International journal of medical informatics

    2024  Volume 188, Page(s) 105464

    Abstract: Background: Radiomics is a rapidly growing field used to leverage medical radiological images by extracting quantitative features. These are supposed to characterize a patient's phenotype, and when combined with artificial intelligence techniques, to ... ...

    Abstract Background: Radiomics is a rapidly growing field used to leverage medical radiological images by extracting quantitative features. These are supposed to characterize a patient's phenotype, and when combined with artificial intelligence techniques, to improve the accuracy of diagnostic models and clinical outcome prediction.
    Objectives: This review aims at examining the application areas of artificial intelligence-based radiomics (AI-based radiomics) for the management of head and neck cancer (HNC). It further explores the workflow of AI-based radiomics for personalized and precision oncology in HNC. Finally, it examines the current challenges of AI-based radiomics in daily clinical oncology and offers possible solutions to these challenges.
    Methods: Comprehensive electronic databases (PubMed, Medline via Ovid, Scopus, Web of Science, CINAHL, and Cochrane Library) were searched following the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. The quality of included studies and their risk of biases were evaluated using the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD)and Prediction Model Risk of Bias Assessment Tool (PROBAST).
    Results: Out of the 659 search hits retrieved, 45 fulfilled the inclusion criteria. Our review revealed that the application of AI-based radiomics model as an ancillary tool for improved decision-making in HNC management includes radiomics-based cancer diagnosis and radiomics-based cancer prognosis. The radiomics-based cancer diagnosis includes tumor staging, tumor grading, and classification of malignant and benign tumors. Similarly, radiomics-based cancer prognosis includes prediction for treatment response, recurrence, metastasis, and survival. In addition, the challenges in the implementation of these models for clinical evaluations include data imbalance, feature engineering (extraction and selection), model generalizability, multi-modal fusion, and model interpretability.
    Conclusion: Considering the highly subjective and interobserver variability that is peculiar to the interpretation of medical images by expert clinicians, AI-based radiomics seeks to offer potentially useful quantitative information, which is not visible to the human eye or unintentionally often remain ignored during clinical imaging practice. By enabling the extraction of this type of information, AI-based radiomics has the potential to revolutionize HNC oncology, providing a platform for more personalized, higher quality, and cost-effective care for HNC patients.
    Language English
    Publishing date 2024-04-23
    Publishing country Ireland
    Document type Journal Article ; Review
    ZDB-ID 1466296-6
    ISSN 1872-8243 ; 1386-5056
    ISSN (online) 1872-8243
    ISSN 1386-5056
    DOI 10.1016/j.ijmedinf.2024.105464
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  8. Article ; Online: Molecular pathology in diagnosis and prognostication of head and neck tumors.

    Skálová, Alena / Bradová, Martina / Michal, Michael / Mosaieby, Elaheh / Klubíčková, Natálie / Vaněček, Tomáš / Leivo, Ilmo

    Virchows Archiv : an international journal of pathology

    2024  Volume 484, Issue 2, Page(s) 215–231

    Abstract: Classification of head and neck tumors has evolved in recent decades including a widespread application of molecular testing in tumors of the salivary glands, sinonasal tract, oropharynx, nasopharynx, and soft tissue. Availability of new molecular ... ...

    Abstract Classification of head and neck tumors has evolved in recent decades including a widespread application of molecular testing in tumors of the salivary glands, sinonasal tract, oropharynx, nasopharynx, and soft tissue. Availability of new molecular techniques allowed for the definition of multiple novel tumor types unique to head and neck sites. Moreover, the expanding spectrum of immunohistochemical markers facilitates a rapid identification of diagnostic molecular abnormalities. As such, it is currently possible for head and neck pathologists to benefit from a molecularly defined classifications, while making diagnoses that are still based largely on histopathology and immunohistochemistry. This review highlights some principal molecular alterations in head and neck neoplasms presently available to assist pathologists in the practice of diagnosis, prognostication and prediction of response to treatment.
    MeSH term(s) Humans ; Pathology, Molecular ; Head and Neck Neoplasms/diagnosis ; Head and Neck Neoplasms/genetics ; Salivary Glands ; Immunohistochemistry ; Pathologists
    Language English
    Publishing date 2024-01-13
    Publishing country Germany
    Document type Journal Article ; Review
    ZDB-ID 1184867-4
    ISSN 1432-2307 ; 0945-6317
    ISSN (online) 1432-2307
    ISSN 0945-6317
    DOI 10.1007/s00428-023-03731-2
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  9. Article ; Online: Rearrangement of

    Othman, Bacem K / Steiner, Petr / Leivo, Ilmo / Skálová, Alena

    Fetal and pediatric pathology

    2023  Volume 42, Issue 5, Page(s) 796–807

    Abstract: Introduction: ...

    Abstract Introduction:
    MeSH term(s) Young Adult ; Humans ; Child ; DNA-Binding Proteins/genetics ; Trans-Activators/genetics ; Carcinoma, Mucoepidermoid/genetics ; Carcinoma, Mucoepidermoid/pathology ; Nuclear Proteins/genetics ; Precursor Cell Lymphoblastic Leukemia-Lymphoma ; Gene Rearrangement
    Chemical Substances DNA-Binding Proteins ; Trans-Activators ; Nuclear Proteins
    Language English
    Publishing date 2023-07-30
    Publishing country England
    Document type Journal Article
    ZDB-ID 2165508-X
    ISSN 1551-3823 ; 1551-3815 ; 1522-7952
    ISSN (online) 1551-3823
    ISSN 1551-3815 ; 1522-7952
    DOI 10.1080/15513815.2023.2241903
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  10. Article ; Online: Update from the 5th Edition of the World Health Organization Classification of Head and Neck Tumors: Salivary Glands.

    Skálová, Alena / Hyrcza, Martin D / Leivo, Ilmo

    Head and neck pathology

    2022  Volume 16, Issue 1, Page(s) 40–53

    Abstract: The salivary gland section in the 5th edition of the World Health Organization Classification of Head and Neck Tumours features a description and inclusion of several new entities, including sclerosing polycystic adenoma, keratocystoma, intercalated duct ...

    Abstract The salivary gland section in the 5th edition of the World Health Organization Classification of Head and Neck Tumours features a description and inclusion of several new entities, including sclerosing polycystic adenoma, keratocystoma, intercalated duct adenoma, and striated duct adenoma among the benign neoplasms; and microsecretory adenocarcinoma and sclerosing microcystic adenocarcinoma as the new malignant entities. The new entry also includes mucinous adenocarcinoma subdivided into papillary, colloid, signet ring, and mixed subtypes with recurrent AKT1 E17K mutations across patterns suggesting that mucin-producing salivary adenocarcinomas represent a histologically diverse single entity that may be related to salivary intraductal papillary mucinous neoplasm (IPMN). Importantly, the number of entities in the salivary chapter has been reduced by omitting tumors or lesions if they do not occur exclusively or predominantly in salivary glands, including hemangioma, lipoma, nodular fasciitis and hematolymphoid tumors. They are now discussed in detail elsewhere in the book. Cribriform adenocarcinoma of salivary gland origin (CASG) now represents a distinctive subtype of polymorphous adenocarcinoma (PAC). PAC is defined as a clinically, histologically and molecularly heterogeneous disease group. Whether CASG is a different diagnostic category or a variant of PAC is still controversial. Poorly differentiated carcinomas and oncocytic carcinomas are discussed in the category "Salivary carcinoma not otherwise specified (NOS) and emerging entities". New defining genomic alterations have been characterized in many salivary gland tumors. In particular, they include gene fusions, which have shown to be tightly tumor-type specific, and thus valuable for use in diagnostically challenging cases. The recurrent molecular alterations were included in the definition of mucoepidermoid carcinoma, adenoid cystic carcinoma, secretory carcinoma, polymorphous adenocarcinoma, hyalinizing clear cell carcinoma, mucinous adenocarcinoma, and microsecretory adenocarcinoma.
    MeSH term(s) Adenocarcinoma/pathology ; Adenocarcinoma, Mucinous ; Adenoma/genetics ; Adenoma/pathology ; Biomarkers, Tumor/genetics ; Humans ; Salivary Gland Neoplasms/genetics ; Salivary Gland Neoplasms/pathology ; Salivary Glands/pathology ; World Health Organization
    Chemical Substances Biomarkers, Tumor
    Language English
    Publishing date 2022-03-21
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2407834-7
    ISSN 1936-0568 ; 1936-055X
    ISSN (online) 1936-0568
    ISSN 1936-055X
    DOI 10.1007/s12105-022-01420-1
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