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  11. Prediction Of Transformation In The Histopathological Growth Pattern Of Colorectal Liver Metastases After Chemotherapy Using Ct-based Radiomics

Prediction of transformation in the histopathological growth pattern of colorectal liver metastases after chemotherapy using CT-based radiomics

Shengcai Wei1, Xinyi Gou1, Yinli Zhang2

  • 1Department of Radiology, Peking University People's Hospital, 11 Xizhimen South St, Beijing, 100044, China.

Clinical & Experimental Metastasis
|February 28, 2024

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View abstract on PubMed

Summary
This summary is machine-generated.

Chemotherapy changes histopathological growth patterns (HGP) in colorectal liver metastases (CRLMs). A CT-based radiomics model effectively predicts HGP transformation after chemotherapy, aiding treatment decisions for CRLM patients.

Area of Science:

  • Radiology
  • Oncology
  • Pathology

Background:

  • Chemotherapy significantly alters the histopathological growth pattern (HGP) phenotype in colorectal liver metastases (CRLMs).
  • Understanding these changes is crucial for prognostic assessment and treatment planning in CRLM patients.

Purpose of the Study:

  • To develop and validate a CT-based radiomics model for predicting HGP transformation in CRLMs following chemotherapy.
  • To assess the bidirectional nature of HGP changes induced by chemotherapy.

Main Methods:

  • A cohort of 181 patients with 298 CRLMs was retrospectively analyzed.
  • Radiomics features were extracted from pre-operative contrast-enhanced CT scans (portal venous phase).
  • A radiomics signature was developed to predict pre-chemotherapy HGPs and compared with post-chemotherapy pathological findings.
Keywords:
ChemotherapyColorectal liver metastasesHistopathologic growth pattensRadiomics

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Main Results:

  • The radiomics signature demonstrated strong performance in distinguishing pure desmoplastic HGP (pdHGP) from non-pdHGP (AUCs 0.906-0.805).
  • Significant HGP transformation was observed post-chemotherapy, with a notable shift towards pdHGP.
  • Bidirectional transformation occurred, with 15.2% shifting from pdHGP to non-pdHGP and 30.4% from non-pdHGP to pdHGP.

Conclusions:

  • CT-based radiomics is an effective tool for predicting HGP transformation in chemotherapy-treated CRLMs.
  • This predictive capability can inform personalized treatment strategies for CRLM patients.