Quantitative Pathologic Analysis of Digitized Images of Colorectal Carcinoma Improves Prediction of Recurrence-Free Survival

Copyright © 2022 AGA Institute. Published by Elsevier Inc. All rights reserved..

BACKGROUND & AIMS: To examine whether quantitative pathologic analysis of digitized hematoxylin and eosin slides of colorectal carcinoma (CRC) correlates with clinicopathologic features, molecular alterations, and prognosis.

METHODS: A quantitative segmentation algorithm (QuantCRC) was applied to 6468 digitized hematoxylin and eosin slides of CRCs. Fifteen parameters were recorded from each image and tested for associations with clinicopathologic features and molecular alterations. A prognostic model was developed to predict recurrence-free survival using data from the internal cohort (n = 1928) and validated on an internal test (n = 483) and external cohort (n = 938).

RESULTS: There were significant differences in QuantCRC according to stage, histologic subtype, grade, venous/lymphatic/perineural invasion, tumor budding, CD8 immunohistochemistry, mismatch repair status, KRAS mutation, BRAF mutation, and CpG methylation. A prognostic model incorporating stage, mismatch repair, and QuantCRC resulted in a Harrell's concordance (c)-index of 0.714 (95% confidence interval [CI], 0.702-0.724) in the internal test and 0.744 (95% CI, 0.741-0.754) in the external cohort. Removing QuantCRC from the model reduced the c-index to 0.679 (95% CI, 0.673-0.694) in the external cohort. Prognostic risk groups were identified, which provided a hazard ratio of 2.24 (95% CI, 1.33-3.87, P = .004) for low vs high-risk stage III CRCs and 2.36 (95% CI, 1.07-5.20, P = .03) for low vs high-risk stage II CRCs, in the external cohort after adjusting for established risk factors. The predicted median 36-month recurrence rate for high-risk stage III CRCs was 32.7% vs 13.4% for low-risk stage III and 15.8% for high-risk stage II vs 5.4% for low-risk stage II CRCs.

CONCLUSIONS: QuantCRC provides a powerful adjunct to routine pathologic reporting of CRC. A prognostic model using QuantCRC improves prediction of recurrence-free survival.

Medienart:

E-Artikel

Erscheinungsjahr:

2022

Erschienen:

2022

Enthalten in:

Zur Gesamtaufnahme - volume:163

Enthalten in:

Gastroenterology - 163(2022), 6 vom: 28. Dez., Seite 1531-1546.e8

Sprache:

Englisch

Beteiligte Personen:

Pai, Reetesh K [VerfasserIn]
Banerjee, Imon [VerfasserIn]
Shivji, Sameer [VerfasserIn]
Jain, Suchit [VerfasserIn]
Hartman, Douglas [VerfasserIn]
Buchanan, Daniel D [VerfasserIn]
Jenkins, Mark A [VerfasserIn]
Schaeffer, David F [VerfasserIn]
Rosty, Christophe [VerfasserIn]
Como, Julia [VerfasserIn]
Phipps, Amanda I [VerfasserIn]
Newcomb, Polly A [VerfasserIn]
Burnett-Hartman, Andrea N [VerfasserIn]
Le Marchand, Loic [VerfasserIn]
Samadder, Niloy J [VerfasserIn]
Patel, Bhavik [VerfasserIn]
Swallow, Carol [VerfasserIn]
Lindor, Noralane M [VerfasserIn]
Gallinger, Steven J [VerfasserIn]
Grant, Robert C [VerfasserIn]
Westerling-Bui, Thomas [VerfasserIn]
Conner, James [VerfasserIn]
Cyr, David P [VerfasserIn]
Kirsch, Richard [VerfasserIn]
Pai, Rish K [VerfasserIn]

Links:

Volltext

Themen:

Colorectal Cancer
Eosine Yellowish-(YS)
Hematoxylin
Image Analysis
Journal Article
Prognosis
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Stroma
TDQ283MPCW
Tumor Infiltrating Lymphocytes
YKM8PY2Z55

Anmerkungen:

Date Completed 01.04.2023

Date Revised 02.12.2023

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1053/j.gastro.2022.08.025

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM345040570