MRE for Assessment of Histopathological Growth Patterns in Colorectal Liver Metastases

Official title

Noninvasive Evaluation in Diagnosis and Treatment of Histopathological Growth Patterns in Colorectal Liver Metastases Using MR Elastography-based Shear Strain Mapping

Overview

The goal of this study is to investigate the value of MR elastography-based SII as a means of detecting HGP noninvasively in patients with pathology-proven CRLM. MRE will provide a direct measure of tumor-liver adhesion to investigate the relationship between imaging findings and pathophysiological changes in the Liver.

Detailed description

Colorectal cancer ranks third in terms of incidence and second in terms of mortality among all cancers on the global cancer burden, based on the GLOBOCAN 2020 estimates. Among people diagnosed with colorectal cancer, 20% have metastatis, and 40% present with recurrence after previously treated localized disease. Liver is the most common site of metastasis besides lymph nodes, with a 5-year survival rate of less than 20%. Histopathological growth patterns (HGPs) appear at the interface between the tumour border and surrounding liver parenchyma which can be identified by light microscopy on tissue sections. Three primary HGPs have been identified: desmoplastic HGP (dHGP), replacement HGP and the pushing HGP. In the dHGP, the cancer cells are separated from the liver by a capsule of desmoplastic stroma in which new blood vessels are formed by sprouting angiogenesis. Recently, it has been reported that dHGP is linked to a better outcome in terms of survival and more clinical benefit achieved with preoperative anti-angiogenic therapy in patients with colorectal cancer liver metastasis (CRLM). Thus, planning of preoperative treatment might greatly benefit from HGP prediction. Preoperative prediction of HGP is challenging, however, as HGP is a histopathologic finding that can be diagnosed only with a postoperative surgical specimen. Previous studies have made many efforts to identify HGP through radiologic features (e.g., tumor margin, perilesional rim enhancement, or fused radiomics signature) by CT or MRI. However, high variability was observed in the assessment of these imaging characteristics, and they did not provide a direct measure of tumor-liver adhesion, leading to controversy in clinical practice. Recently, an MRE-based technique, termed "slip interface imaging" (SII), has been used to quantify the degree of tumor-peritumoral tissue adhesion in brain tumors and microvascular invasion in hepatocellular carcinoma noninvasively, may have the potential to characterize the mechanical characteristics of the tumor-liver interface and predict HGP of CRLM.

Interventions

• Diagnostic test Magnetic Resonance Elastography and routine MRI
  Assessed boundary conditions through MRE-base SII before surgery and recorded HGP of tumor after surgery.

Primary outcome measures

• Radiological assessment of CRLM [Time frame: Baseline to 6 weeks]

Eligibility criteria

Inclusion criteria

• Diagnosed CRLM
• Pathologic results obtained in surgical patients
• No contraindications for magnetic resonance imaging examination

Exclusion criteria

• Image quality does not meet the measurement requirements.
• the diameter of CRLM <1cm
• Combined with other important organ dysfunction
• Combined with malignant tumor
• Patients who do not sign an informed consent
• Patients with metallic implants or foreign bodies in their bodies (pacemakers, artificial metallic heart valves, metal joints, metal implants, and those who cannot remove dentures, insulin pumps, or contraceptive rings)

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: Yes

Study design

Observational model

Cohort

Study locations

China · 1 center

• Shengjing Hospital of China Medical University — Shenyang

Publications

• Latacz E, Hoppener D, Bohlok A, Leduc S, Tabaries S, Fernandez Moro C, Lugassy C, Nystrom H, Bozoky B, Floris G, Geyer N, Brodt P, Llado L, Van Mileghem L, De Schepper M, Majeed AW, Lazaris A, Dirix P, Zhang Q, Petrillo SK, Vankerckhove S, Joye I, Meyer Y, Gregorieff A, Roig NR, Vidal-Vanaclocha F, Denis L, Oliveira RC, Metrakos P, Grunhagen DJ, Nagtegaal ID, Mollevi DG, Jarnagin WR, D'Angelica MI PMID 35650276
• Frentzas S, Simoneau E, Bridgeman VL, Vermeulen PB, Foo S, Kostaras E, Nathan M, Wotherspoon A, Gao ZH, Shi Y, Van den Eynden G, Daley F, Peckitt C, Tan X, Salman A, Lazaris A, Gazinska P, Berg TJ, Eltahir Z, Ritsma L, Van Rheenen J, Khashper A, Brown G, Nystrom H, Sund M, Van Laere S, Loyer E, Dirix L, Cunningham D, Metrakos P, Reynolds AR. Vessel co-option mediates resistance to anti-angiogenic PMID 27748747
• Li M, Yin Z, Hu B, Guo N, Zhang L, Zhang L, Zhu J, Chen W, Yin M, Chen J, Ehman RL, Wang J. MR Elastography-Based Shear Strain Mapping for Assessment of Microvascular Invasion in Hepatocellular Carcinoma. Eur Radiol. 2022 Jul;32(7):5024-5032. doi: 10.1007/s00330-022-08578-w. Epub 2022 Feb 11. PMID 35147777
• Yin Z, Lu X, Cohen Cohen S, Sui Y, Manduca A, Van Gompel JJ, Ehman RL, Huston J 3rd. A new method for quantification and 3D visualization of brain tumor adhesion using slip interface imaging in patients with meningiomas. Eur Radiol. 2021 Aug;31(8):5554-5564. doi: 10.1007/s00330-021-07918-6. Epub 2021 Apr 14. PMID 33852045

Identifiers

NCT: NCT06208397 · ShengjingH-CRLM2023

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗