LIVIVO - The Search Portal for Life Sciences

zur deutschen Oberfläche wechseln
Advanced search

Search results

Result 1 - 10 of total 28

Search options

  1. Article ; Online: Cervical cytology and HPV distribution in Cape Verde: A snapshot of a country taken during its first HPV nation-wide vaccination campaign.

    Vieira, Rita / Montezuma, Diana / Barbosa, Carla / Macedo Pinto, Isabel

    Tumour virus research

    2024  , Page(s) 200280

    Abstract: Cervical cancer ranks as the third most common female cancer in Cape Verde and is the leading cause of cancer-related deaths among women in the country. While Human Papillomavirus (HPV) vaccination, which started in 2021, is anticipated to significantly ... ...

    Abstract Cervical cancer ranks as the third most common female cancer in Cape Verde and is the leading cause of cancer-related deaths among women in the country. While Human Papillomavirus (HPV) vaccination, which started in 2021, is anticipated to significantly reduce disease incidence, cervical screening remains crucial for non-vaccinated women. We retrospectively reviewed gynecologic cytology exams and HPV tests performed in Cape Verde between 2017 and April 2023 and processed at IMP Diagnostics. For this study, we considered 13035 women with cytology examinations performed and, 2013 of these, also with an HPV molecular test. Cytology diagnostics comprised 83 % NILM cases; 12 % ASC-US; 2.7 % LSIL; 1.2 % ASC-H; 0.5 % HSIL and 0.1 % SCC. In 505 (25.1 %) high-risk HPV infection was detected. Prevalence of HPV infection varied with age, peaking at young ages - ≤24 years old (55.5 %) and 25-35-year-old women (31.5 %) - and the lowest after 66 years old (9.7 %). Herein we present a comprehensive study regarding Cape Verde's cervical cytology and HPV distribution, aiming to provide a snapshot of the country's cervical cytology results and HPV distribution in recent years. Moreover, these data may contribute to establish a baseline to assess, in the future, the vaccination impact in the country.
    Language English
    Publishing date 2024-05-01
    Publishing country Netherlands
    Document type Journal Article
    ISSN 2666-6790
    ISSN (online) 2666-6790
    DOI 10.1016/j.tvr.2024.200280
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  2. Article ; Online: Invisible for a few but essential for many: the role of Histotechnologists in the establishment of digital pathology.

    Magalhães, Gisela / Calisto, Rita / Freire, Catarina / Silva, Regina / Montezuma, Diana / Canberk, Sule / Schmitt, Fernando

    Journal of histotechnology

    2023  Volume 47, Issue 1, Page(s) 39–52

    Abstract: Digital pathology (DP) is indisputably the future for histopathology laboratories. The process of digital implementation requires deep workflow reorganisation which involves an interdisciplinary team. This transformation may have the greatest impact on ... ...

    Abstract Digital pathology (DP) is indisputably the future for histopathology laboratories. The process of digital implementation requires deep workflow reorganisation which involves an interdisciplinary team. This transformation may have the greatest impact on the Histotechnologist (HTL) profession. Our review of the literature has clearly revealed that the role of HTLs in the establishment of DP is being unnoticed and guidance is limited. This article aims to bring HTLs from behind-the-scenes into the spotlight. Our objective is to provide them guidance and practical recommendations to successfully contribute to the implementation of a new digital workflow. Furthermore, it also intends to contribute for improvement of study programs, ensuring the role of HTL in DP is addressed as part of graduate and post-graduate education. In our review, we report on the differences encountered between workflow schemes and the limitations observed in this process. The authors propose a digital workflow to achieve its limitless potential, focusing on the HTL's role. This article explores the novel responsibilities of HTLs during specimen gross dissection, embedding, microtomy, staining, digital scanning, and whole slide image quality control. Furthermore, we highlight the benefits and challenges that DP implementation might bring the HTLs career. HTLs have an important role in the digital workflow: the responsibility of achieving the perfect glass slide.
    MeSH term(s) Laboratories ; Workflow
    Language English
    Publishing date 2023-10-23
    Publishing country England
    Document type Journal Article ; Review
    ZDB-ID 604634-4
    ISSN 2046-0236 ; 0147-8885
    ISSN (online) 2046-0236
    ISSN 0147-8885
    DOI 10.1080/01478885.2023.2268297
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

    In stock of ZB MED Cologne/Königswinter

    Zs.A 1701: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

  3. Article: Is it "hybrid" or "intermediate"?-more than just a semantic issue in oncocytic renal cell tumors.

    Montezuma, Diana / Jerónimo, Carmen / Henrique, Rui

    Annals of translational medicine

    2020  Volume 7, Issue Suppl 8, Page(s) S356

    Language English
    Publishing date 2020-01-03
    Publishing country China
    Document type Editorial ; Comment
    ZDB-ID 2893931-1
    ISSN 2305-5847 ; 2305-5839
    ISSN (online) 2305-5847
    ISSN 2305-5839
    DOI 10.21037/atm.2019.09.54
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

  4. Article ; Online: Epigenetic extracellular vesicle-based biomarkers for urological malignancies: is the hope worth the hype?

    Montezuma, Diana / Teixeira-Marques, Ana / Jerónimo, Carmen / Henrique, Rui

    Epigenomics

    2021  Volume 13, Issue 19, Page(s) 1514–1521

    MeSH term(s) Biomarkers, Tumor ; Disease Management ; Disease Susceptibility ; Epigenesis, Genetic ; Extracellular Vesicles/metabolism ; Gene Expression Regulation, Neoplastic ; Humans ; Prognosis ; Urologic Neoplasms/diagnosis ; Urologic Neoplasms/genetics
    Chemical Substances Biomarkers, Tumor
    Language English
    Publishing date 2021-10-07
    Publishing country England
    Document type Letter ; Research Support, Non-U.S. Gov't
    ZDB-ID 2537199-X
    ISSN 1750-192X ; 1750-1911
    ISSN (online) 1750-192X
    ISSN 1750-1911
    DOI 10.2217/epi-2021-0333
    Database MEDical Literature Analysis and Retrieval System OnLINE

    Full text online

    More links

    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

  5. Article ; Online: Annotating for Artificial Intelligence Applications in Digital Pathology: A Practical Guide for Pathologists and Researchers.

    Montezuma, Diana / Oliveira, Sara P / Neto, Pedro C / Oliveira, Domingos / Monteiro, Ana / Cardoso, Jaime S / Macedo-Pinto, Isabel

    Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc

    2023  Volume 36, Issue 4, Page(s) 100086

    Abstract: Training machine learning models for artificial intelligence (AI) applications in pathology often requires extensive annotation by human experts, but there is little guidance on the subject. In this work, we aimed to describe our experience and provide a ...

    Abstract Training machine learning models for artificial intelligence (AI) applications in pathology often requires extensive annotation by human experts, but there is little guidance on the subject. In this work, we aimed to describe our experience and provide a simple, useful, and practical guide addressing annotation strategies for AI development in computational pathology. Annotation methodology will vary significantly depending on the specific study's objectives, but common difficulties will be present across different settings. We summarize key aspects and issue guiding principles regarding team interaction, ground-truth quality assessment, different annotation types, and available software and hardware options and address common difficulties while annotating. This guide was specifically designed for pathology annotation, intending to help pathologists, other researchers, and AI developers with this process.
    MeSH term(s) Humans ; Artificial Intelligence ; Pathologists ; Software ; Machine Learning
    Language English
    Publishing date 2023-01-11
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 645073-8
    ISSN 1530-0285 ; 0893-3952
    ISSN (online) 1530-0285
    ISSN 0893-3952
    DOI 10.1016/j.modpat.2022.100086
    Database MEDical Literature Analysis and Retrieval System OnLINE

    Full text online

    More links

    Kategorien

    In stock of ZB MED Cologne/Königswinter

    Zs.A 2450: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

  6. Article: Author Correction: An interpretable machine learning system for colorectal cancer diagnosis from pathology slides.

    Neto, Pedro C / Montezuma, Diana / Oliveira, Sara P / Oliveira, Domingos / Fraga, João / Monteiro, Ana / Monteiro, João / Ribeiro, Liliana / Gonçalves, Sofia / Reinhard, Stefan / Zlobec, Inti / Pinto, Isabel M / Cardoso, Jaime S

    NPJ precision oncology

    2024  Volume 8, Issue 1, Page(s) 83

    Language English
    Publishing date 2024-04-03
    Publishing country England
    Document type Published Erratum
    ISSN 2397-768X
    ISSN 2397-768X
    DOI 10.1038/s41698-024-00581-2
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  7. Article ; Online: Breast Fine Needle Aspiration Biopsy Cytology Using the Newly Proposed IAC Yokohama System for Reporting Breast Cytopathology: The Experience of a Single Institution.

    Montezuma, Diana / Malheiros, Daniela / Schmitt, Fernando C

    Acta cytologica

    2019  , Page(s) 1–6

    Abstract: Objective: Recently the International Academy of Cytology (IAC) proposed a new reporting system for breast fine needle aspiration biopsy (FNAB) cytology. We aimed to categorize our samples according to this classification and to assess the risk of ... ...

    Abstract Objective: Recently the International Academy of Cytology (IAC) proposed a new reporting system for breast fine needle aspiration biopsy (FNAB) cytology. We aimed to categorize our samples according to this classification and to assess the risk of malignancy (ROM) for each category as well as the diagnostic yield of breast FNAB.
    Study design: Breast FNAB specimens obtained between January 2007 and December 2017 were reclassified according to the newly proposed IAC Yokohama reporting system. The ROM for each category was determined. Diagnostic yield was evaluated based on a three-category approach, benign versus malignant.
    Results: The samples were distributed as follows: insufficient material 5.77%, benign 73.38%, atypical 13.74%, suspicious for malignancy 1.57%, and malignant 5.54%. Of the 3,625 cases collected, 776 (21.4%) had corresponding histology. The respective ROM for each category was 4.8% for category 1 (insufficient material), 1.4% for category 2 (benign), 13% for category 3 (atypical), 97.1% for category 4 (suspicious for malignancy), and 100% for category 5 (malignant). When only malignant cases were considered positive tests, the sensitivity, specificity, and diagnostic accuracy were 97.56, 100, and 99.11%, respectively.
    Conclusions: Our study is the first to categorize breast FNAB cytology samples according to the proposed IAC reporting system and to evaluate patient outcomes based on this categorization.
    Language English
    Publishing date 2019-02-15
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 80003-x
    ISSN 1938-2650 ; 0001-5547
    ISSN (online) 1938-2650
    ISSN 0001-5547
    DOI 10.1159/000492638
    Database MEDical Literature Analysis and Retrieval System OnLINE

    Full text online

    More links

    Kategorien

    In stock of ZB MED Cologne/Königswinter

    Zs.A 358: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

  8. Article: An interpretable machine learning system for colorectal cancer diagnosis from pathology slides.

    Neto, Pedro C / Montezuma, Diana / Oliveira, Sara P / Oliveira, Domingos / Fraga, João / Monteiro, Ana / Monteiro, João / Ribeiro, Liliana / Gonçalves, Sofia / Reinhard, Stefan / Zlobec, Inti / Pinto, Isabel M / Cardoso, Jaime S

    NPJ precision oncology

    2024  Volume 8, Issue 1, Page(s) 56

    Abstract: Considering the profound transformation affecting pathology practice, we aimed to develop a scalable artificial intelligence (AI) system to diagnose colorectal cancer from whole-slide images (WSI). For this, we propose a deep learning (DL) system that ... ...

    Abstract Considering the profound transformation affecting pathology practice, we aimed to develop a scalable artificial intelligence (AI) system to diagnose colorectal cancer from whole-slide images (WSI). For this, we propose a deep learning (DL) system that learns from weak labels, a sampling strategy that reduces the number of training samples by a factor of six without compromising performance, an approach to leverage a small subset of fully annotated samples, and a prototype with explainable predictions, active learning features and parallelisation. Noting some problems in the literature, this study is conducted with one of the largest WSI colorectal samples dataset with approximately 10,500 WSIs. Of these samples, 900 are testing samples. Furthermore, the robustness of the proposed method is assessed with two additional external datasets (TCGA and PAIP) and a dataset of samples collected directly from the proposed prototype. Our proposed method predicts, for the patch-based tiles, a class based on the severity of the dysplasia and uses that information to classify the whole slide. It is trained with an interpretable mixed-supervision scheme to leverage the domain knowledge introduced by pathologists through spatial annotations. The mixed-supervision scheme allowed for an intelligent sampling strategy effectively evaluated in several different scenarios without compromising the performance. On the internal dataset, the method shows an accuracy of 93.44% and a sensitivity between positive (low-grade and high-grade dysplasia) and non-neoplastic samples of 0.996. On the external test samples varied with TCGA being the most challenging dataset with an overall accuracy of 84.91% and a sensitivity of 0.996.
    Language English
    Publishing date 2024-03-05
    Publishing country England
    Document type Journal Article
    ISSN 2397-768X
    ISSN 2397-768X
    DOI 10.1038/s41698-024-00539-4
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  9. Article: Digital Pathology Implementation in Private Practice: Specific Challenges and Opportunities.

    Montezuma, Diana / Monteiro, Ana / Fraga, João / Ribeiro, Liliana / Gonçalves, Sofia / Tavares, André / Monteiro, João / Macedo-Pinto, Isabel

    Diagnostics (Basel, Switzerland)

    2022  Volume 12, Issue 2

    Abstract: Digital pathology (DP) is being deployed in many pathology laboratories, but most reported experiences refer to public health facilities. In this paper, we report our experience in DP transition at a high-volume private laboratory, addressing the main ... ...

    Abstract Digital pathology (DP) is being deployed in many pathology laboratories, but most reported experiences refer to public health facilities. In this paper, we report our experience in DP transition at a high-volume private laboratory, addressing the main challenges in DP implementation in a private practice setting and how to overcome these issues. We started our implementation in 2020 and we are currently scanning 100% of our histology cases. Pre-existing sample tracking infrastructure facilitated this process. We are currently using two high-capacity scanners (Aperio GT450DX) to digitize all histology slides at 40×. Aperio eSlide Manager WebViewer viewing software is bidirectionally linked with the laboratory information system. Scanning error rate, during the test phase, was 2.1% (errors detected by the scanners) and 3.5% (manual quality control). Pre-scanning phase optimizations and vendor feedback and collaboration were crucial to improve WSI quality and are ongoing processes. Regarding pathologists' validation, we followed the Royal College of Pathologists recommendations for DP implementation (adapted to our practice). Although private sector implementation of DP is not without its challenges, it will ultimately benefit from DP safety and quality-associated features. Furthermore, DP deployment lays the foundation for artificial intelligence tools integration, which will ultimately contribute to improving patient care.
    Language English
    Publishing date 2022-02-18
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2662336-5
    ISSN 2075-4418
    ISSN 2075-4418
    DOI 10.3390/diagnostics12020529
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

  10. Article: iMIL4PATH: A Semi-Supervised Interpretable Approach for Colorectal Whole-Slide Images.

    Neto, Pedro C / Oliveira, Sara P / Montezuma, Diana / Fraga, João / Monteiro, Ana / Ribeiro, Liliana / Gonçalves, Sofia / Pinto, Isabel M / Cardoso, Jaime S

    Cancers

    2022  Volume 14, Issue 10

    Abstract: Colorectal cancer (CRC) diagnosis is based on samples obtained from biopsies, assessed in pathology laboratories. Due to population growth and ageing, as well as better screening programs, the CRC incidence rate has been increasing, leading to a higher ... ...

    Abstract Colorectal cancer (CRC) diagnosis is based on samples obtained from biopsies, assessed in pathology laboratories. Due to population growth and ageing, as well as better screening programs, the CRC incidence rate has been increasing, leading to a higher workload for pathologists. In this sense, the application of AI for automatic CRC diagnosis, particularly on whole-slide images (WSI), is of utmost relevance, in order to assist professionals in case triage and case review. In this work, we propose an interpretable semi-supervised approach to detect lesions in colorectal biopsies with high sensitivity, based on multiple-instance learning and feature aggregation methods. The model was developed on an extended version of the recent, publicly available CRC dataset (the CRC+ dataset with 4433 WSI), using 3424 slides for training and 1009 slides for evaluation. The proposed method attained 90.19% classification ACC, 98.8% sensitivity, 85.7% specificity, and a quadratic weighted kappa of 0.888 at slide-based evaluation. Its generalisation capabilities are also studied on two publicly available external datasets.
    Language English
    Publishing date 2022-05-18
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2527080-1
    ISSN 2072-6694
    ISSN 2072-6694
    DOI 10.3390/cancers14102489
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

To top