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Computed Tomography-Based Radiomics with Machine Learning Outperforms Radiologist Assessment in Estimating Colorectal Liver Metastases Pathologic Response After Chemotherapy

Crossref DOI link: https://doi.org/10.1245/s10434-024-15373-y

Published Online: 2024-10-05

Published Print: 2024-12

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Karagkounis, Georgios

Horvat, Natally

Danilova, Sofia

Chhabra, Salini

Narayan, Raja R.

Barekzai, Ahmad B.

Kleshchelski, Adam

Joanne, Chou

Gonen, Mithat

Balachandran, Vinod

Soares, Kevin C.

Wei, Alice C.

Kingham, T. Peter

Jarnagin, William R.

Shia, Jinru

Chakraborty, Jayasree

D’Angelica, Michael I.
Funding

Funding for this research was provided by:

Division of Cancer Epidemiology and Genetics (P30 CA008748)

Memorial Sloan-Kettering Cancer Center (2022 Molecularly Targeted Intra-Operative Imaging)
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Text and Data Mining valid from 2024-10-05

Version of Record valid from 2024-10-05
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Article History

Received: 15 November 2023

Accepted: 14 April 2024

First Online: 5 October 2024

Disclosure

: Dr. Natally Horvat: Bayer (lecture) and Guerbet (consultant fee). Dr. Alice Wei: Ipsen: clinical trial funding; Histosonics: consulting; Medtronic: honorarium for teaching. Dr. Jinru Shia: Paige.AI, Inc. Professional Services and Activities.

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