We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
LGC Clinical Diagnostics

Philips Healthcare

Operates in Diagnostic Imaging Systems, Patient Care and Clinical Informatics, Customer Services, and Home Healthcare... read more Featured Products: More products

Download Mobile App




Mitoses Counted with Digital Pathology in Breast Phyllodes Tumors

By LabMedica International staff writers
Posted on 26 Nov 2020
Print article
Image: IntelliSite Ultra-Fast Digital pathology slide scanner is designed to accommodate current histopathology needs for routine use in high volume labs and integrated pathology networks (Photo courtesy of Philips Digital Pathology Solutions).
Image: IntelliSite Ultra-Fast Digital pathology slide scanner is designed to accommodate current histopathology needs for routine use in high volume labs and integrated pathology networks (Photo courtesy of Philips Digital Pathology Solutions).
Phyllodes tumors (PTs) are a fibroepithelial tumor composed of an epithelial and a cellular stromal component. They may be considered benign, borderline, or malignant depending on histologic features including stromal cellularity, infiltration at the tumor's edge, and mitotic activity.

Digital pathology (DP) is becoming more widely available and has been harnessed to enhance diagnosis and access to subspecialty opinion, promote education, and may also be deployed for remote reporting. DP has enabled the development of artificial intelligence (AI) in pathology, through image analysis and machine learning, including working toward open source access.

Pathologists at the Singapore General Hospital (Singapore) and their colleagues chose representative slides from 93 cases of PTs diagnosed between 2014 and 2015. The mean age ± SD of the cohort was 42.5 ± 12.7 years. Of these, 60 were benign, 31 borderline, and two malignant, which were graded based on the World Health Organization guidelines. Specifically, stromal hypercellularity and stromal atypia were categorized into mild, moderate, and marked, according to the consensus review.

The slides were scanned with the IntelliSite Ultra-Fast Scanner (Philips Digital Pathology Solutions, Eindhoven, the Netherlands) and viewed with the Philips’ Image Management System viewer. Mitotic counting was conducted on the whole slide image, before choosing 10 high powered fields (HPFs) and demarcating the tumor area in DP. Values of mitoses/mm2 were used to compare results between 10 HPFs and the whole slide. Correlations with clinicopathological parameters were conducted.

The scientists reported that in terms of atypia, 65 (70.0%) PT cases displayed mild atypia, followed by 27 (29.0%) moderate atypia and one (1%) marked atypia. For stromal cellularity, 50 (53.8%) tumors displayed moderate hypercellularity, followed by 31 (33.3%) mild hypercellularity and 12 (12.9%) marked hypercellularity. The mean size of the tumors was 4.6 ± 3.3 cm3 (mean ± SD cm3). Both whole slide counting of mitoses and 10 HPFs had similar statistically significant correlation coefficients with grade, stromal atypia, and stromal hypercellularity. Neither whole slide mitotic counts nor mitoses per 10 HPFs showed statistically significant correlations with patient age and tumor size.

The authors concluded that an accurate set of 10 HPFs that yielded a maximal mitotic count can be chosen after evaluating the whole slide. DP makes counting mitoses over a larger area subjectively easier, with the possibility of AI being used as facilitator and enabler. This could influence how to approach training, testing, and validation of future AI algorithms for mitotic counting. The study was published in the November. 2020 issue of the journal Archives of Pathology and Laboratory Medicine.

Related Links:
Singapore General Hospital
Philips Digital Pathology Solutions


Gold Member
Serological Pipet Controller
PIPETBOY GENIUS
Verification Panels for Assay Development & QC
Seroconversion Panels
New
Malondialdehyde HPLC Test
Malondialdehyde in Serum/Plasma – HPLC
New
Cytomegalovirus Test
NovaLisa Cytomegalovirus (CMV) IgG Test

Print article

Channels

Clinical Chemistry

view channel
Image: The GlycoLocate platform uses multi-omics and advanced computational biology algorithms to diagnose early-stage cancers (Photo courtesy of AOA Dx)

AI-Powered Blood Test Accurately Detects Ovarian Cancer

Ovarian cancer ranks as the fifth leading cause of cancer-related deaths in women, largely due to late-stage diagnoses. Although over 90% of women exhibit symptoms in Stage I, only 20% are diagnosed in... Read more

Molecular Diagnostics

view channel
Image: The advanced molecular test is designed to improve diagnosis of a genetic form of COPD (Photo courtesy of National Jewish Health)

Groundbreaking Molecular Diagnostic Test Accurately Diagnoses Major Genetic Cause of COPD

Chronic obstructive pulmonary disease (COPD) and Alpha-1 Antitrypsin Deficiency (AATD) are both conditions that can cause breathing difficulties, but they differ in their origins and inheritance.... Read more

Immunology

view channel
Image: The cancer stem cell test can accurately choose more effective treatments (Photo courtesy of University of Cincinnati)

Stem Cell Test Predicts Treatment Outcome for Patients with Platinum-Resistant Ovarian Cancer

Epithelial ovarian cancer frequently responds to chemotherapy initially, but eventually, the tumor develops resistance to the therapy, leading to regrowth. This resistance is partially due to the activation... Read more

Technology

view channel
Image: The new algorithms can help predict which patients have undiagnosed cancer (Photo courtesy of Adobe Stock)

Advanced Predictive Algorithms Identify Patients Having Undiagnosed Cancer

Two newly developed advanced predictive algorithms leverage a person’s health conditions and basic blood test results to accurately predict the likelihood of having an undiagnosed cancer, including ch... Read more

Industry

view channel
Image: The collaboration aims to leverage Oxford Nanopore\'s sequencing platform and Cepheid\'s GeneXpert system to advance the field of sequencing for infectious diseases (Photo courtesy of Cepheid)

Cepheid and Oxford Nanopore Technologies Partner on Advancing Automated Sequencing-Based Solutions

Cepheid (Sunnyvale, CA, USA), a leading molecular diagnostics company, and Oxford Nanopore Technologies (Oxford, UK), the company behind a new generation of sequencing-based molecular analysis technologies,... Read more
Copyright © 2000-2025 Globetech Media. All rights reserved.