Semantic Scholar Open Access 2023 43 sitasi

Pitfalls in machine learning‐based assessment of tumor‐infiltrating lymphocytes in breast cancer: A report of the International Immuno‐Oncology Biomarker Working Group on Breast Cancer

J. Thagaard G. Broeckx D. Page C. Jahangir Sara Verbandt +137 lainnya

Lihat Sumber DOI

Abstrak

The clinical significance of the tumor‐immune interaction in breast cancer is now established, and tumor‐infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple‐negative (estrogen receptor, progesterone receptor, and HER2‐negative) breast cancer and HER2‐positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state‐of‐the‐art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false‐positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in‐depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple‐negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Topik & Kata Kunci

Medicine

Penulis (142)

J. Thagaard

G. Broeckx

D. Page

C. Jahangir

Sara Verbandt

Z. Kos

Rajarsi R. Gupta

R. Khiroya

K. AbdulJabbar

G. Acosta Haab

B. Ács

Guray Akturk

Jonas S. Almeida

I. Alvarado-Cabrero

M. Amgad

Farid Azmoudeh-Ardalan

S. Badve

Nurkhairul Bariyah Baharun

E. Balslev

E. Bellolio

V. Bheemaraju

K. Blenman

Luciana Botinelly Mendonça Fujimoto

Najat Bouchmaa

O. Burgués

Alexandros Chardas

Maggie Chon U Cheang

F. Ciompi

L. Cooper

A. Coosemans

Germán Corredor

A. Dahl

Flavio Luis Dantas Portela

F. Deman

S. Demaria

Johan Doré Hansen

S. Dudgeon

T. Ebstrup

Mahmoud Elghazawy

Claudio Fernandez-Martín

S. Fox

W. Gallagher

J. Giltnane

S. Gnjatic

P. Gonzalez-Ericsson

A. Grigoriadis

N. Halama

M. Hanna

A. Harbhajanka

S. Hart

J. Hartman

Søren Hauberg

Stephen M. Hewitt

A. Hida

H. Horlings

Z. Husain

E. Hytopoulos

Sheeba Irshad

E. Janssen

M. Kahila

T. Kataoka

K. Kawaguchi

Durga Kharidehal

A. Khramtsov

Umay Kiraz

Pawan Kirtani

Liudmila L Kodach

Konstanty Korski

A. Kovács

A. Laenkholm

Corinna Lang-Schwarz

D. Larsimont

J. Lennerz

Marvin Lerousseau

Xiaoxian Li

A. Ly

A. Madabhushi

S. Maley

Vidya Manur Narasimhamurthy

D. Marks

E. McDonald

R. Mehrotra

S. Michiels

F. Minhas

Shachi Mittal

D. Moore

Shamim Mushtaq

Hussain Nighat

T. Papathomas

F. Penault-Llorca

Rashindrie Perera

C. Pinard

Juan Carlos Pinto-Cárdenas

G. Pruneri

L. Pusztai

Arman Rahman

N. Rajpoot

B. Rapoport

T. Rau

J. Reis-Filho

J. M. Ribeiro

D. Rimm

A. Roslind

A. Vincent‐Salomon

M. Salto‐Tellez

J. Saltz

S. Sayed

E. Scott

K. Siziopikou

C. Sotiriou

A. Stenzinger

M. Sughayer

Daniel G Sur

S. Fineberg

F. Symmans

Sunao Tanaka

T. Taxter

S. Tejpar

Jonas Teuwen

E. Thompson

T. Tramm

W. Tran

J. A. van der Laak

P. V. van Diest

G. Verghese

G. Viale

M. Vieth

N. Wahab

Thomas Walter

Y. Waumans

H. Wen

Wentao Yang

Yinyin Yuan

R. Zin

S. Adams

John M. S. Bartlett

S. Loibl

C. Denkert

P. Savas

S. Loi

R. Salgado

Elisabeth Specht Stovgaard

Format Sitasi

APA MLA BibTeX

Thagaard, J., Broeckx, G., Page, D., Jahangir, C., Verbandt, S., Kos, Z. et al. (2023). Pitfalls in machine learning‐based assessment of tumor‐infiltrating lymphocytes in breast cancer: A report of the International Immuno‐Oncology Biomarker Working Group on Breast Cancer. https://doi.org/10.1002/path.6155

@article{thagaard2023, author = {J. Thagaard and G. Broeckx and D. Page and C. Jahangir and Sara Verbandt and Z. Kos and Rajarsi R. Gupta and R. Khiroya and K. AbdulJabbar and G. Acosta Haab and B. Ács and Guray Akturk and Jonas S. Almeida and I. Alvarado-Cabrero and M. Amgad and Farid Azmoudeh-Ardalan and S. Badve and Nurkhairul Bariyah Baharun and E. Balslev and E. Bellolio and V. Bheemaraju and K. Blenman and Luciana Botinelly Mendonça Fujimoto and Najat Bouchmaa and O. Burgués and Alexandros Chardas and Maggie Chon U Cheang and F. Ciompi and L. Cooper and A. Coosemans and Germán Corredor and A. Dahl and Flavio Luis Dantas Portela and F. Deman and S. Demaria and Johan Doré Hansen and S. Dudgeon and T. Ebstrup and Mahmoud Elghazawy and Claudio Fernandez-Martín and S. Fox and W. Gallagher and J. Giltnane and S. Gnjatic and P. Gonzalez-Ericsson and A. Grigoriadis and N. Halama and M. Hanna and A. Harbhajanka and S. Hart and J. Hartman and Søren Hauberg and Stephen M. Hewitt and A. Hida and H. Horlings and Z. Husain and E. Hytopoulos and Sheeba Irshad and E. Janssen and M. Kahila and T. Kataoka and K. Kawaguchi and Durga Kharidehal and A. Khramtsov and Umay Kiraz and Pawan Kirtani and Liudmila L Kodach and Konstanty Korski and A. Kovács and A. Laenkholm and Corinna Lang-Schwarz and D. Larsimont and J. Lennerz and Marvin Lerousseau and Xiaoxian Li and A. Ly and A. Madabhushi and S. Maley and Vidya Manur Narasimhamurthy and D. Marks and E. McDonald and R. Mehrotra and S. Michiels and F. Minhas and Shachi Mittal and D. Moore and Shamim Mushtaq and Hussain Nighat and T. Papathomas and F. Penault-Llorca and Rashindrie Perera and C. Pinard and Juan Carlos Pinto-Cárdenas and G. Pruneri and L. Pusztai and Arman Rahman and N. Rajpoot and B. Rapoport and T. Rau and J. Reis-Filho and J. M. Ribeiro and D. Rimm and A. Roslind and A. Vincent‐Salomon and M. Salto‐Tellez and J. Saltz and S. Sayed and E. Scott and K. Siziopikou and C. Sotiriou and A. Stenzinger and M. Sughayer and Daniel G Sur and S. Fineberg and F. Symmans and Sunao Tanaka and T. Taxter and S. Tejpar and Jonas Teuwen and E. Thompson and T. Tramm and W. Tran and J. A. van der Laak and P. V. van Diest and G. Verghese and G. Viale and M. Vieth and N. Wahab and Thomas Walter and Y. Waumans and H. Wen and Wentao Yang and Yinyin Yuan and R. Zin and S. Adams and John M. S. Bartlett and S. Loibl and C. Denkert and P. Savas and S. Loi and R. Salgado and Elisabeth Specht Stovgaard}, title = {Pitfalls in machine learning‐based assessment of tumor‐infiltrating lymphocytes in breast cancer: A report of the International Immuno‐Oncology Biomarker Working Group on Breast Cancer}, year = {2023}, journal = {Semantic Scholar}, doi = {10.1002/path.6155}, url = {https://www.semanticscholar.org/paper/13a37cf9771c8fbabc261e13c8a246346244f4ca}, }

Akses Cepat

Lihat di Sumber doi.org/10.1002/path.6155

Informasi Jurnal

Tahun Terbit: 2023
Bahasa: en
Total Sitasi: 43×
Sumber Database: Semantic Scholar
DOI: 10.1002/path.6155
Akses: Open Access ✓