Evidence map›Paper›PMID 37706239›Full record

ArticleHistopathology2023

Ki67 proliferation index in medullary thyroid carcinoma: a comparative study of multiple counting methods and validation of image analysis and deep learning platforms.

Saad Nadeem, Matthew G Hanna, Kartik Viswanathan, Joseph Marino, Mahsa Ahadi, Bayan Alzumaili, Mohamed-Amine Bani, Federico Chiarucci, Angela Chou, Antonio De Leo and 12 more

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Histopathology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 19% of its field
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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.

  1. Pooled it
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  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors at 5 institutions in 4 countries.

Saad NadeemDepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.ORCID https://orcid.org/0000-0001-5030-9792
Matthew G HannaDepartment of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Kartik ViswanathanDepartment of Pathology, Emory University Hospital Midtown, Atlanta, GA, USA.ORCID https://orcid.org/0000-0003-0031-0001
Joseph MarinoDepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Mahsa AhadiRoyal North Shore Hospital and Northern Clinical School, Sydney Medical School, University of Sydney, Sydney, Australia.ORCID https://orcid.org/0000-0002-4687-8666
Bayan AlzumailiDepartment of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Mohamed-Amine BaniMedical Pathology and Biology Department, Gustave Roussy Campus Cancer, Villejuif, France.
Federico ChiarucciDepartment of Medical and Surgical Sciences (DIMEC), University of Bologna Medical Center, Bologna, Italy.
Angela ChouRoyal North Shore Hospital and Northern Clinical School, Sydney Medical School, University of Sydney, Sydney, Australia.
Antonio De LeoDepartment of Medical and Surgical Sciences (DIMEC), University of Bologna Medical Center, Bologna, Italy.
Talia L FuchsRoyal North Shore Hospital and Northern Clinical School, Sydney Medical School, University of Sydney, Sydney, Australia.ORCID https://orcid.org/0000-0002-9166-6822
Daniel J LubinDepartment of Pathology, Emory University Hospital Midtown, Atlanta, GA, USA.
Catherine LuxfordRoyal North Shore Hospital and Northern Clinical School, Sydney Medical School, University of Sydney, Sydney, Australia.
Kelly MaglioccaDepartment of Pathology, Emory University Hospital Midtown, Atlanta, GA, USA.
Germán MartinezDepartment of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Qiuying ShiDepartment of Pathology, Emory University Hospital Midtown, Atlanta, GA, USA.ORCID https://orcid.org/0000-0002-0224-3167
Stan SidhuRoyal North Shore Hospital and Northern Clinical School, Sydney Medical School, University of Sydney, Sydney, Australia.
Abir Al GhuzlanMedical Pathology and Biology Department, Gustave Roussy Campus Cancer, Villejuif, France.
Anthony J GillRoyal North Shore Hospital and Northern Clinical School, Sydney Medical School, University of Sydney, Sydney, Australia.
Giovanni TalliniDepartment of Medical and Surgical Sciences (DIMEC), University of Bologna Medical Center, Bologna, Italy.
Ronald GhosseinDepartment of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Bin XuDepartment of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.ORCID https://orcid.org/0000-0003-4638-9835
Memorial Sloan Kettering Cancer Center · USThe University of Sydney · AUEmory University Hospital Midtown · USAzienda USL di Bologna · ITInstitut Gustave Roussy · FR

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI SELWYN M VICKERS · 1985 to 2026
$347.4M
Implementing a Maternal health and PRegnancy Outcomes Vision for Everyone (IMPROVE)UL1TR002378 · NCATS · EMORY UNIVERSITY · PI Andres J Garcia, Elizabeth O. Ofili · 2017 to 2026
$92.1M
Winship Cancer Institute Cancer Center Support GrantP30CA138292 · NCI · EMORY UNIVERSITY · PI Ragini Reiney Kudchadkar · 2009 to 2026
$47.5M
NCATS NIH HHS UL1 TR002378NCI NIH HHS P30 CA008748NCI NIH HHS P30 CA138292
6 · The paper itself

Abstract

aimsThe International Medullary Thyroid Carcinoma Grading System, introduced in 2022, mandates evaluation of the Ki67 proliferation index to assign a histological grade for medullary thyroid carcinoma. However, manual counting remains a tedious and time-consuming task. METHODS AND

resultsWe aimed to evaluate the performance of three other counting techniques for the Ki67 index, eyeballing by a trained experienced investigator, a machine learning-based deep learning algorithm (DeepLIIF) and an image analysis software with internal thresholding compared to the gold standard manual counting in a large cohort of 260 primarily resected medullary thyroid carcinoma. The Ki67 proliferation index generated by all three methods correlate near-perfectly with the manual Ki67 index, with kappa values ranging from 0.884 to 0.979 and interclass correlation coefficients ranging from 0.969 to 0.983. Discrepant Ki67 results were only observed in cases with borderline manual Ki67 readings, ranging from 3 to 7%. Medullary thyroid carcinomas with a high Ki67 index (≥ 5%) determined using any of the four methods were associated with significantly decreased disease-specific survival and distant metastasis-free survival.

conclusionsWe herein validate a machine learning-based deep-learning platform and an image analysis software with internal thresholding to generate accurate automatic Ki67 proliferation indices in medullary thyroid carcinoma. Manual Ki67 count remains useful when facing a tumour with a borderline Ki67 proliferation index of 3-7%. In daily practice, validation of alternative evaluation methods for the Ki67 index in MTC is required prior to implementation.

Indexed as

Deep LearningThyroid NeoplasmsCarcinoma, NeuroendocrineCell ProliferationHumansKi-67 AntigenKi-67 Antigendeep learninggradeKi67 proliferation indexmachine learningmedullary thyroid carcinoma

Identifiers

PMID37706239
PMCPMC10840805
OpenAlexW4386726176

What OpenQuestion holds

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Registered trials

None linked

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.