Evidence map›Paper›PMID 42250057›Full record

ArticleBreast cancer (Tokyo, Japan)2026

A simple morphometric algorithm based on nuclear atypia features of invasive breast carcinoma: relationship with nuclear grade, Ki-67 level, and hormone receptor status.

Tomohiro Tsuru, Takanori Watanabe, Keita Kouzu, Youji Yamagishi, Takahiro Einama, Tamio Yamasaki, Hironori Tsujimoto, Yoji Kishi, Hideki Ueno, Hitoshi Tsuda

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Breast cancer (Tokyo, Japan), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Tomohiro TsuruDepartment of Surgery, National Defense Medical College Hospital, 3-2 Namiki, Tokorozawa, 359-8513, Saitama, Japan.ORCID http://orcid.org/0009-0006-6913-0868
Takanori WatanabeDepartment of Basic Pathology, National Defense Medical College, 3-2 Namiki, Tokorozawa, 359-8513, Saitama, Japan.
Keita KouzuDepartment of Surgery, National Defense Medical College Hospital, 3-2 Namiki, Tokorozawa, 359-8513, Saitama, Japan.ORCID http://orcid.org/0000-0002-6433-3184
Youji YamagishiDepartment of Surgery, National Defense Medical College Hospital, 3-2 Namiki, Tokorozawa, 359-8513, Saitama, Japan.
Takahiro EinamaDepartment of Surgery, National Defense Medical College Hospital, 3-2 Namiki, Tokorozawa, 359-8513, Saitama, Japan.ORCID http://orcid.org/0000-0002-4434-0803
Tamio YamasakiDepartment of Surgery, National Defense Medical College Hospital, 3-2 Namiki, Tokorozawa, 359-8513, Saitama, Japan.
Hironori TsujimotoDepartment of Surgery, National Defense Medical College Hospital, 3-2 Namiki, Tokorozawa, 359-8513, Saitama, Japan.ORCID http://orcid.org/0000-0002-2808-4723
Yoji KishiDepartment of Surgery, National Defense Medical College Hospital, 3-2 Namiki, Tokorozawa, 359-8513, Saitama, Japan.ORCID http://orcid.org/0000-0001-8885-1210
Hideki UenoDepartment of Surgery, National Defense Medical College Hospital, 3-2 Namiki, Tokorozawa, 359-8513, Saitama, Japan.ORCID http://orcid.org/0000-0002-8600-1199
Hitoshi TsudaDepartment of Basic Pathology, National Defense Medical College, 3-2 Namiki, Tokorozawa, 359-8513, Saitama, Japan. hstsuda@gmail.com.ORCID http://orcid.org/0000-0003-3457-4224

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background With the widespread availability of whole-slide imaging, many studies have utilized digital images of hematoxylin and eosin (H&E)-stained breast cancer tissues and applied convolutional neural networks (CNNs) for pathological diagnosis. However, CNN-based diagnosis is largely a black box and may be limited in quantitative morphological research. In this study, we developed a simple algorithm for morphometric analysis of three nuclear atypia features on H&E-stained whole-slide images to predict nuclear grade, hormone receptor status, and Ki-67 levels in breast cancer.Materials and Methods Using 43,183 H&E-stained nuclear images larger than 20 µm

Indexed as

AlgorithmsBreast NeoplasmsCarcinoma, Ductal, BreastCell NucleusKi-67 AntigenBiomarkers, TumorConvolutional Neural NetworksFemaleHumansImage Processing, Computer-AssistedNeoplasm GradingReceptors, EstrogenReceptors, ProgesteroneBiomarkers, TumorKi-67 AntigenReceptors, EstrogenReceptors, ProgesteroneBreast cancerDigital pathologyHormone receptorInvasive breast carcinomaMorphometryNuclear atypiaNuclear gradeNucleoliWhole-slide imaging

Identifiers

PMID42250057
PMCPMC13283171

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.