Literature DB >> 32145597

Tumor segmentation analysis at different post-contrast time points: A possible source of variability of quantitative DCE-MRI parameters in locally advanced breast cancer.

Valeria Romeo1, Carlo Cavaliere2, Massimo Imbriaco3, Francesco Verde3, Mario Petretta4, Monica Franzese2, Arnaldo Stanzione3, Renato Cuocolo3, Marco Aiello2, Luca Basso2, Michele Amitrano3, Rossella Lauria5, Antonello Accurso6, Arturo Brunetti3, Marco Salvatore2.   

Abstract

PURPOSE: to assess if tumor segmentation analysis performed at different post-contrast time points (TPs) on dynamic images could influence the extraction of dynamic contrast enhanced (DCE)-MRI parameters in locally advanced breast cancer (LABC), and potentially represent a source of variability.
METHOD: forty patients with forty-two LABC lesions were prospectively enrolled and underwent breast DCE-MRI examination at 3 T. On post-processed dynamic images, enhancing tumor lesions were manually segmented at four different TPs: at the first post-contrast dynamic image in which the lesion was appreciable (TP 1) and at 1, 5 and 10 min after contrast-agent administration (TPs 2, 3 and 4, respectively) and corresponding DCE-MRI parameters were extracted. Friedman's test followed by Bonferroni-adjusted Wilcoxon signed rank test for post-hoc analysis was used to compare DCE-MRI parameters. Intra- and inter-observer reliability of DCE-MRI parameters measurements was assessed using the Intraclass Correlation Coefficient (ICC) analysis.
RESULTS: Ktrans, Kep and iAUC were significantly higher when extracted from ROIs placed at TP1 and progressively decreased from TP 2-4. The intra-observer reliability ranged from good to excellent (ICC's: 0.894 to 0.990). The inter-observer reliability varied from moderate to excellent (0.770 to 0.942). The inter-observer reliability was significantly higher for Ktrans and Kep extracted at TPs1 and 2 as compared to TPs 3 and 4.
CONCLUSIONS: A significant variability of DCE-MRI quantitative parameters occurs when tumor segmentation is performed at different TPs. We suggest to performing tumor delineation at an established TP, preferably the earliest, in order to extract reliable and comparable DCE-MRI data.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Dynamic contrast enhanced MRI; Ktrans; Locally advanced breast cancer; Magnetic resonance imaging; Perfusion weighted MRI

Mesh:

Substances:

Year:  2020        PMID: 32145597     DOI: 10.1016/j.ejrad.2020.108907

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  5 in total

1.  Different CT slice thickness and contrast-enhancement phase in radiomics models on the differential performance of lung adenocarcinoma.

Authors:  Yang Wang; Fang Liu; Yan Mo; Chencui Huang; Yingxin Chen; Fuliang Chen; Xiangwei Zhang; Yunxin Yin; Qiang Liu; Lin Zhang
Journal:  Thorac Cancer       Date:  2022-05-11       Impact factor: 3.223

2.  A Clinical Semantic and Radiomics Nomogram for Predicting Brain Invasion in WHO Grade II Meningioma Based on Tumor and Tumor-to-Brain Interface Features.

Authors:  Ning Li; Yan Mo; Chencui Huang; Kai Han; Mengna He; Xiaolan Wang; Jiaqi Wen; Siyu Yang; Haoting Wu; Fei Dong; Fenglei Sun; Yiming Li; Yizhou Yu; Minming Zhang; Xiaojun Guan; Xiaojun Xu
Journal:  Front Oncol       Date:  2021-10-22       Impact factor: 6.244

3.  Delta-Radiomics Based on Dynamic Contrast-Enhanced MRI Predicts Pathologic Complete Response in Breast Cancer Patients Treated with Neoadjuvant Chemotherapy.

Authors:  Liangcun Guo; Siyao Du; Si Gao; Ruimeng Zhao; Guoliang Huang; Feng Jin; Yuee Teng; Lina Zhang
Journal:  Cancers (Basel)       Date:  2022-07-20       Impact factor: 6.575

4.  A Simultaneous Multiparametric 18F-FDG PET/MRI Radiomics Model for the Diagnosis of Triple Negative Breast Cancer.

Authors:  Valeria Romeo; Panagiotis Kapetas; Paola Clauser; Pascal A T Baltzer; Sazan Rasul; Peter Gibbs; Marcus Hacker; Ramona Woitek; Katja Pinker; Thomas H Helbich
Journal:  Cancers (Basel)       Date:  2022-08-16       Impact factor: 6.575

Review 5.  Assessment and Prediction of Response to Neoadjuvant Chemotherapy in Breast Cancer: A Comparison of Imaging Modalities and Future Perspectives.

Authors:  Valeria Romeo; Giuseppe Accardo; Teresa Perillo; Luca Basso; Nunzia Garbino; Emanuele Nicolai; Simone Maurea; Marco Salvatore
Journal:  Cancers (Basel)       Date:  2021-07-14       Impact factor: 6.639

  5 in total

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